Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis

Identification of the SIRT1 gene's most harmful... | F1000Research "use strict";function _typeof(t){return(_typeof="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}!function(){var t=function(){var t,e,o=[],n=window,r=n;for(;r;){try{if(r.frames.__tcfapiLocator){t=r;break}}catch(t){}if(r===n.top)break;r=r.parent}t||(!function t(){var e=n.document,o=!!n.frames.__tcfapiLocator;if(!o)if(e.body){var r=e.createElement("iframe");r.style.cssText="display:none",r.name="__tcfapiLocator",e.body.appendChild(r)}else setTimeout(t,5);return!o}(),n.__tcfapi=function(){for(var t=arguments.length,n=new Array(t),r=0;r 3&&2===parseInt(n[1],10)&&"boolean"==typeof n[3]&&(e=n[3],"function"==typeof n[2]&&n[2]("set",!0)):"ping"===n[0]?"function"==typeof n[2]&&n[2]({gdprApplies:e,cmpLoaded:!1,cmpStatus:"stub"}):o.push(n)},n.addEventListener("message",(function(t){var e="string"==typeof t.data,o={};if(e)try{o=JSON.parse(t.data)}catch(t){}else o=t.data;var n="object"===_typeof(o)&&null!==o?o.__tcfapiCall:null;n&&window.__tcfapi(n.command,n.version,(function(o,r){var a={__tcfapiReturn:{returnValue:o,success:r,callId:n.callId}};t&&t.source&&t.source.postMessage&&t.source.postMessage(e?JSON.stringify(a):a,"*")}),n.parameter)}),!1))};"undefined"!=typeof module?module.exports=t:t()}(); dataLayer = dataLayer || []; // Standard GTM initialization - Google Consent Mode handles consent automatically (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl+ '>m_auth=hzk0Vc3qFsQYhCrIoHz68A>m_preview=env-1>m_cookies_win=x';f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-MWFK8L5J'); ;window.NREUM||(NREUM={});NREUM.init={distributed_tracing:{enabled:true},privacy:{cookies_enabled:true},ajax:{deny_list:["bam.nr-data.net"]}}; ;NREUM.loader_config={accountID:"438030",trustKey:"438030",agentID:"772317073",licenseKey:"97f8f67f26",applicationID:"772317073"} ;NREUM.info={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net",licenseKey:"97f8f67f26",applicationID:"772317073",sa:1} ;/*! For license information please see nr-loader-spa-1.236.0.min.js.LICENSE.txt */ (()=>{"use strict";var e,t,r={5763:(e,t,r)=>{r.d(t,{P_:()=>l,Mt:()=>g,C5:()=>s,DL:()=>v,OP:()=>T,lF:()=>D,Yu:()=>y,Dg:()=>h,CX:()=>c,GE:()=>b,sU:()=>_});var n=r(8632),i=r(9567);const o={beacon:n.ce.beacon,errorBeacon:n.ce.errorBeacon,licenseKey:void 0,applicationID:void 0,sa:void 0,queueTime:void 0,applicationTime:void 0,ttGuid:void 0,user:void 0,account:void 0,product:void 0,extra:void 0,jsAttributes:{},userAttributes:void 0,atts:void 0,transactionName:void 0,tNamePlain:void 0},a={};function s(e){if(!e)throw new Error("All info objects require an agent identifier!");if(!a[e])throw new Error("Info for ".concat(e," was never set"));return a[e]}function c(e,t){if(!e)throw new Error("All info objects require an agent identifier!");a[e]=(0,i.D)(t,o),(0,n.Qy)(e,a[e],"info")}var u=r(7056);const d=()=>{const e={blockSelector:"[data-nr-block]",maskInputOptions:{password:!0}};return{allow_bfcache:!0,privacy:{cookies_enabled:!0},ajax:{deny_list:void 0,enabled:!0,harvestTimeSeconds:10},distributed_tracing:{enabled:void 0,exclude_newrelic_header:void 0,cors_use_newrelic_header:void 0,cors_use_tracecontext_headers:void 0,allowed_origins:void 0},session:{domain:void 0,expiresMs:u.oD,inactiveMs:u.Hb},ssl:void 0,obfuscate:void 0,jserrors:{enabled:!0,harvestTimeSeconds:10},metrics:{enabled:!0},page_action:{enabled:!0,harvestTimeSeconds:30},page_view_event:{enabled:!0},page_view_timing:{enabled:!0,harvestTimeSeconds:30,long_task:!1},session_trace:{enabled:!0,harvestTimeSeconds:10},harvest:{tooManyRequestsDelay:60},session_replay:{enabled:!1,harvestTimeSeconds:60,sampleRate:.1,errorSampleRate:.1,maskTextSelector:"*",maskAllInputs:!0,get blockClass(){return"nr-block"},get ignoreClass(){return"nr-ignore"},get maskTextClass(){return"nr-mask"},get blockSelector(){return e.blockSelector},set blockSelector(t){e.blockSelector+=",".concat(t)},get maskInputOptions(){return e.maskInputOptions},set maskInputOptions(t){e.maskInputOptions={...t,password:!0}}},spa:{enabled:!0,harvestTimeSeconds:10}}},f={};function l(e){if(!e)throw new Error("All configuration objects require an agent identifier!");if(!f[e])throw new Error("Configuration for ".concat(e," was never set"));return f[e]}function h(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");f[e]=(0,i.D)(t,d()),(0,n.Qy)(e,f[e],"config")}function g(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");var r=l(e);if(r){for(var n=t.split("."),i=0;i {r.d(t,{D:()=>i});var n=r(50);function i(e,t){try{if(!e||"object"!=typeof e)return(0,n.Z)("Setting a Configurable requires an object as input");if(!t||"object"!=typeof t)return(0,n.Z)("Setting a Configurable requires a model to set its initial properties");const r=Object.create(Object.getPrototypeOf(t),Object.getOwnPropertyDescriptors(t)),o=0===Object.keys(r).length?e:r;for(let a in o)if(void 0!==e[a])try{"object"==typeof e[a]&&"object"==typeof t[a]?r[a]=i(e[a],t[a]):r[a]=e[a]}catch(e){(0,n.Z)("An error occurred while setting a property of a Configurable",e)}return r}catch(e){(0,n.Z)("An error occured while setting a Configurable",e)}}},6818:(e,t,r)=>{r.d(t,{Re:()=>i,gF:()=>o,q4:()=>n});const n="1.236.0",i="PROD",o="CDN"},385:(e,t,r)=>{r.d(t,{FN:()=>a,IF:()=>u,Nk:()=>f,Tt:()=>s,_A:()=>o,il:()=>n,pL:()=>c,v6:()=>i,w1:()=>d});const n="undefined"!=typeof window&&!!window.document,i="undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self.navigator instanceof WorkerNavigator||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis.navigator instanceof WorkerNavigator),o=n?window:"undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis),a=""+o?.location,s=/iPad|iPhone|iPod/.test(navigator.userAgent),c=s&&"undefined"==typeof SharedWorker,u=(()=>{const e=navigator.userAgent.match(/Firefox[/\s](\d+\.\d+)/);return Array.isArray(e)&&e.length>=2?+e[1]:0})(),d=Boolean(n&&window.document.documentMode),f=!!navigator.sendBeacon},1117:(e,t,r)=>{r.d(t,{w:()=>o});var n=r(50);const i={agentIdentifier:"",ee:void 0};class o{constructor(e){try{if("object"!=typeof e)return(0,n.Z)("shared context requires an object as input");this.sharedContext={},Object.assign(this.sharedContext,i),Object.entries(e).forEach((e=>{let[t,r]=e;Object.keys(i).includes(t)&&(this.sharedContext[t]=r)}))}catch(e){(0,n.Z)("An error occured while setting SharedContext",e)}}}},8e3:(e,t,r)=>{r.d(t,{L:()=>d,R:()=>c});var n=r(2177),i=r(1284),o=r(4322),a=r(3325);const s={};function c(e,t){const r={staged:!1,priority:a.p[t]||0};u(e),s[e].get(t)||s[e].set(t,r)}function u(e){e&&(s[e]||(s[e]=new Map))}function d(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"feature";if(u(e),!e||!s[e].get(t))return a(t);s[e].get(t).staged=!0;const r=[...s[e]];function a(t){const r=e?n.ee.get(e):n.ee,a=o.X.handlers;if(r.backlog&&a){var s=r.backlog[t],c=a[t];if(c){for(var u=0;s&&u {let[t,r]=e;return r.staged}))&&(r.sort(((e,t)=>e[1].priority-t[1].priority)),r.forEach((e=>{let[t]=e;a(t)})))}function f(e,t){var r=e[1];(0,i.D)(t[r],(function(t,r){var n=e[0];if(r[0]===n){var i=r[1],o=e[3],a=e[2];i.apply(o,a)}}))}},2177:(e,t,r)=>{r.d(t,{c:()=>f,ee:()=>u});var n=r(8632),i=r(2210),o=r(1284),a=r(5763),s="nr@context";let c=(0,n.fP)();var u;function d(){}function f(e){return(0,i.X)(e,s,l)}function l(){return new d}function h(){u.aborted=!0,u.backlog={}}c.ee?u=c.ee:(u=function e(t,r){var n={},c={},f={},g=!1;try{g=16===r.length&&(0,a.OP)(r).isolatedBacklog}catch(e){}var p={on:b,addEventListener:b,removeEventListener:y,emit:v,get:x,listeners:w,context:m,buffer:A,abort:h,aborted:!1,isBuffering:E,debugId:r,backlog:g?{}:t&&"object"==typeof t.backlog?t.backlog:{}};return p;function m(e){return e&&e instanceof d?e:e?(0,i.X)(e,s,l):l()}function v(e,r,n,i,o){if(!1!==o&&(o=!0),!u.aborted||i){t&&o&&t.emit(e,r,n);for(var a=m(n),s=w(e),d=s.length,f=0;fn,p:()=>i});var n=r(2177).ee.get("handle");function i(e,t,r,i,o){o?(o.buffer([e],i),o.emit(e,t,r)):(n.buffer([e],i),n.emit(e,t,r))}},4322:(e,t,r)=>{r.d(t,{X:()=>o});var n=r(5546);o.on=a;var i=o.handlers={};function o(e,t,r,o){a(o||n.E,i,e,t,r)}function a(e,t,r,i,o){o||(o="feature"),e||(e=n.E);var a=t[o]=t[o]||{};(a[r]=a[r]||[]).push([e,i])}},3239:(e,t,r)=>{r.d(t,{bP:()=>s,iz:()=>c,m$:()=>a});var n=r(385);let i=!1,o=!1;try{const e={get passive(){return i=!0,!1},get signal(){return o=!0,!1}};n._A.addEventListener("test",null,e),n._A.removeEventListener("test",null,e)}catch(e){}function a(e,t){return i||o?{capture:!!e,passive:i,signal:t}:!!e}function s(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;window.addEventListener(e,t,a(r,n))}function c(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;document.addEventListener(e,t,a(r,n))}},4402:(e,t,r)=>{r.d(t,{Ht:()=>u,M:()=>c,Rl:()=>a,ky:()=>s});var n=r(385);const i="xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx";function o(e,t){return e?15&e[t]:16*Math.random()|0}function a(){const e=n._A?.crypto||n._A?.msCrypto;let t,r=0;return e&&e.getRandomValues&&(t=e.getRandomValues(new Uint8Array(31))),i.split("").map((e=>"x"===e?o(t,++r).toString(16):"y"===e?(3&o()|8).toString(16):e)).join("")}function s(e){const t=n._A?.crypto||n._A?.msCrypto;let r,i=0;t&&t.getRandomValues&&(r=t.getRandomValues(new Uint8Array(31)));const a=[];for(var s=0;s {r.d(t,{Bq:()=>n,Hb:()=>o,oD:()=>i});const n="NRBA",i=144e5,o=18e5},7894:(e,t,r)=>{function n(){return Math.round(performance.now())}r.d(t,{z:()=>n})},7243:(e,t,r)=>{r.d(t,{e:()=>o});var n=r(385),i={};function o(e){if(e in i)return i[e];if(0===(e||"").indexOf("data:"))return{protocol:"data"};let t;var r=n._A?.location,o={};if(n.il)t=document.createElement("a"),t.href=e;else try{t=new URL(e,r.href)}catch(e){return o}o.port=t.port;var a=t.href.split("://");!o.port&&a[1]&&(o.port=a[1].split("/")[0].split("@").pop().split(":")[1]),o.port&&"0"!==o.port||(o.port="https"===a[0]?"443":"80"),o.hostname=t.hostname||r.hostname,o.pathname=t.pathname,o.protocol=a[0],"/"!==o.pathname.charAt(0)&&(o.pathname="/"+o.pathname);var s=!t.protocol||":"===t.protocol||t.protocol===r.protocol,c=t.hostname===r.hostname&&t.port===r.port;return o.sameOrigin=s&&(!t.hostname||c),"/"===o.pathname&&(i[e]=o),o}},50:(e,t,r)=>{function n(e,t){"function"==typeof console.warn&&(console.warn("New Relic: ".concat(e)),t&&console.warn(t))}r.d(t,{Z:()=>n})},2587:(e,t,r)=>{r.d(t,{N:()=>c,T:()=>u});var n=r(2177),i=r(5546),o=r(8e3),a=r(3325);const s={stn:[a.D.sessionTrace],err:[a.D.jserrors,a.D.metrics],ins:[a.D.pageAction],spa:[a.D.spa],sr:[a.D.sessionReplay,a.D.sessionTrace]};function c(e,t){const r=n.ee.get(t);e&&"object"==typeof e&&(Object.entries(e).forEach((e=>{let[t,n]=e;void 0===u[t]&&(s[t]?s[t].forEach((e=>{n?(0,i.p)("feat-"+t,[],void 0,e,r):(0,i.p)("block-"+t,[],void 0,e,r),(0,i.p)("rumresp-"+t,[Boolean(n)],void 0,e,r)})):n&&(0,i.p)("feat-"+t,[],void 0,void 0,r),u[t]=Boolean(n))})),Object.keys(s).forEach((e=>{void 0===u[e]&&(s[e]?.forEach((t=>(0,i.p)("rumresp-"+e,[!1],void 0,t,r))),u[e]=!1)})),(0,o.L)(t,a.D.pageViewEvent))}const u={}},2210:(e,t,r)=>{r.d(t,{X:()=>i});var n=Object.prototype.hasOwnProperty;function i(e,t,r){if(n.call(e,t))return e[t];var i=r();if(Object.defineProperty&&Object.keys)try{return Object.defineProperty(e,t,{value:i,writable:!0,enumerable:!1}),i}catch(e){}return e[t]=i,i}},1284:(e,t,r)=>{r.d(t,{D:()=>n});const n=(e,t)=>Object.entries(e||{}).map((e=>{let[r,n]=e;return t(r,n)}))},4351:(e,t,r)=>{r.d(t,{P:()=>o});var n=r(2177);const i=()=>{const e=new WeakSet;return(t,r)=>{if("object"==typeof r&&null!==r){if(e.has(r))return;e.add(r)}return r}};function o(e){try{return JSON.stringify(e,i())}catch(e){try{n.ee.emit("internal-error",[e])}catch(e){}}}},3960:(e,t,r)=>{r.d(t,{K:()=>a,b:()=>o});var n=r(3239);function i(){return"undefined"==typeof document||"complete"===document.readyState}function o(e,t){if(i())return e();(0,n.bP)("load",e,t)}function a(e){if(i())return e();(0,n.iz)("DOMContentLoaded",e)}},8632:(e,t,r)=>{r.d(t,{EZ:()=>u,Qy:()=>c,ce:()=>o,fP:()=>a,gG:()=>d,mF:()=>s});var n=r(7894),i=r(385);const o={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net"};function a(){return i._A.NREUM||(i._A.NREUM={}),void 0===i._A.newrelic&&(i._A.newrelic=i._A.NREUM),i._A.NREUM}function s(){let e=a();return e.o||(e.o={ST:i._A.setTimeout,SI:i._A.setImmediate,CT:i._A.clearTimeout,XHR:i._A.XMLHttpRequest,REQ:i._A.Request,EV:i._A.Event,PR:i._A.Promise,MO:i._A.MutationObserver,FETCH:i._A.fetch}),e}function c(e,t,r){let i=a();const o=i.initializedAgents||{},s=o[e]||{};return Object.keys(s).length||(s.initializedAt={ms:(0,n.z)(),date:new Date}),i.initializedAgents={...o,[e]:{...s,[r]:t}},i}function u(e,t){a()[e]=t}function d(){return function(){let e=a();const t=e.info||{};e.info={beacon:o.beacon,errorBeacon:o.errorBeacon,...t}}(),function(){let e=a();const t=e.init||{};e.init={...t}}(),s(),function(){let e=a();const t=e.loader_config||{};e.loader_config={...t}}(),a()}},7956:(e,t,r)=>{r.d(t,{N:()=>i});var n=r(3239);function i(e){let t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2?arguments[2]:void 0,i=arguments.length>3?arguments[3]:void 0;return void(0,n.iz)("visibilitychange",(function(){if(t)return void("hidden"==document.visibilityState&&e());e(document.visibilityState)}),r,i)}},1214:(e,t,r)=>{r.d(t,{em:()=>v,u5:()=>N,QU:()=>S,_L:()=>I,Gm:()=>L,Lg:()=>M,gy:()=>U,BV:()=>Q,Kf:()=>ee});var n=r(2177);const i="nr@original";var o=Object.prototype.hasOwnProperty,a=!1;function s(e,t){return e||(e=n.ee),r.inPlace=function(e,t,n,i,o){n||(n="");var a,s,c,u="-"===n.charAt(0);for(c=0;c 2?n-2:0),o=2;o {r(A[T],e,w),r(E[T],e,w)})),r(l._A,"fetch",y),t.on(y+"end",(function(e,r){var n=this;if(r){var i=r.headers.get("content-length");null!==i&&(n.rxSize=i),t.emit(y+"done",[null,r],n)}else t.emit(y+"done",[e],n)})),t}const O={},j=["pushState","replaceState"];function S(e){const t=function(e){return(e||n.ee).get("history")}(e);return!l.il||O[t.debugId]++||(O[t.debugId]=1,s(t).inPlace(window.history,j,"-")),t}var P=r(3239);const C={},R=["appendChild","insertBefore","replaceChild"];function I(e){const t=function(e){return(e||n.ee).get("jsonp")}(e);if(!l.il||C[t.debugId])return t;C[t.debugId]=!0;var r=s(t),i=/[?&](?:callback|cb)=([^&#]+)/,o=/(.*)\.([^.]+)/,a=/^(\w+)(\.|$)(.*)$/;function c(e,t){var r=e.match(a),n=r[1],i=r[3];return i?c(i,t[n]):t[n]}return r.inPlace(Node.prototype,R,"dom-"),t.on("dom-start",(function(e){!function(e){if(!e||"string"!=typeof e.nodeName||"script"!==e.nodeName.toLowerCase())return;if("function"!=typeof e.addEventListener)return;var n=(a=e.src,s=a.match(i),s?s[1]:null);var a,s;if(!n)return;var u=function(e){var t=e.match(o);if(t&&t.length>=3)return{key:t[2],parent:c(t[1],window)};return{key:e,parent:window}}(n);if("function"!=typeof u.parent[u.key])return;var d={};function f(){t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}function l(){t.emit("jsonp-error",[],d),t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}r.inPlace(u.parent,[u.key],"cb-",d),e.addEventListener("load",f,(0,P.m$)(!1)),e.addEventListener("error",l,(0,P.m$)(!1)),t.emit("new-jsonp",[e.src],d)}(e[0])})),t}var k=r(5763);const H={};function L(e){const t=function(e){return(e||n.ee).get("mutation")}(e);if(!l.il||H[t.debugId])return t;H[t.debugId]=!0;var r=s(t),i=k.Yu.MO;return i&&(window.MutationObserver=function(e){return this instanceof i?new i(r(e,"fn-")):i.apply(this,arguments)},MutationObserver.prototype=i.prototype),t}const z={};function M(e){const t=function(e){return(e||n.ee).get("promise")}(e);if(z[t.debugId])return t;z[t.debugId]=!0;var r=n.c,o=s(t),a=k.Yu.PR;return a&&function(){function e(r){var n=t.context(),i=o(r,"executor-",n,null,!1);const s=Reflect.construct(a,[i],e);return t.context(s).getCtx=function(){return n},s}l._A.Promise=e,Object.defineProperty(e,"name",{value:"Promise"}),e.toString=function(){return a.toString()},Object.setPrototypeOf(e,a),["all","race"].forEach((function(r){const n=a[r];e[r]=function(e){let i=!1;[...e||[]].forEach((e=>{this.resolve(e).then(a("all"===r),a(!1))}));const o=n.apply(this,arguments);return o;function a(e){return function(){t.emit("propagate",[null,!i],o,!1,!1),i=i||!e}}}})),["resolve","reject"].forEach((function(r){const n=a[r];e[r]=function(e){const r=n.apply(this,arguments);return e!==r&&t.emit("propagate",[e,!0],r,!1,!1),r}})),e.prototype=a.prototype;const n=a.prototype.then;a.prototype.then=function(){var e=this,i=r(e);i.promise=e;for(var a=arguments.length,s=new Array(a),c=0;c e())),t};function m(e,t){i.inPlace(t,["onreadystatechange"],"fn-",E)}function b(){var e=this,t=r.context(e);e.readyState>3&&!t.resolved&&(t.resolved=!0,r.emit("xhr-resolved",[],e)),i.inPlace(e,f,"fn-",E)}if(function(e,t){for(var r in e)t[r]=e[r]}(o,p),p.prototype=o.prototype,i.inPlace(p.prototype,J,"-xhr-",E),r.on("send-xhr-start",(function(e,t){m(e,t),function(e){h.push(e),a&&(y?y.then(A):u?u(A):(w=-w,x.data=w))}(t)})),r.on("open-xhr-start",m),a){var y=c&&c.resolve();if(!u&&!c){var w=1,x=document.createTextNode(w);new a(A).observe(x,{characterData:!0})}}else t.on("fn-end",(function(e){e[0]&&e[0].type===d||A()}));function A(){for(var e=0;e {r.d(t,{t:()=>n});const n=r(3325).D.ajax},6660:(e,t,r)=>{r.d(t,{A:()=>i,t:()=>n});const n=r(3325).D.jserrors,i="nr@seenError"},3081:(e,t,r)=>{r.d(t,{gF:()=>o,mY:()=>i,t9:()=>n,vz:()=>s,xS:()=>a});const n=r(3325).D.metrics,i="sm",o="cm",a="storeSupportabilityMetrics",s="storeEventMetrics"},4649:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageAction},7633:(e,t,r)=>{r.d(t,{Dz:()=>i,OJ:()=>a,qw:()=>o,t9:()=>n});const n=r(3325).D.pageViewEvent,i="firstbyte",o="domcontent",a="windowload"},9251:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageViewTiming},3614:(e,t,r)=>{r.d(t,{BST_RESOURCE:()=>i,END:()=>s,FEATURE_NAME:()=>n,FN_END:()=>u,FN_START:()=>c,PUSH_STATE:()=>d,RESOURCE:()=>o,START:()=>a});const n=r(3325).D.sessionTrace,i="bstResource",o="resource",a="-start",s="-end",c="fn"+a,u="fn"+s,d="pushState"},7836:(e,t,r)=>{r.d(t,{BODY:()=>A,CB_END:()=>E,CB_START:()=>u,END:()=>x,FEATURE_NAME:()=>i,FETCH:()=>_,FETCH_BODY:()=>v,FETCH_DONE:()=>m,FETCH_START:()=>p,FN_END:()=>c,FN_START:()=>s,INTERACTION:()=>l,INTERACTION_API:()=>d,INTERACTION_EVENTS:()=>o,JSONP_END:()=>b,JSONP_NODE:()=>g,JS_TIME:()=>T,MAX_TIMER_BUDGET:()=>a,REMAINING:()=>f,SPA_NODE:()=>h,START:()=>w,originalSetTimeout:()=>y});var n=r(5763);const i=r(3325).D.spa,o=["click","submit","keypress","keydown","keyup","change"],a=999,s="fn-start",c="fn-end",u="cb-start",d="api-ixn-",f="remaining",l="interaction",h="spaNode",g="jsonpNode",p="fetch-start",m="fetch-done",v="fetch-body-",b="jsonp-end",y=n.Yu.ST,w="-start",x="-end",A="-body",E="cb"+x,T="jsTime",_="fetch"},5938:(e,t,r)=>{r.d(t,{W:()=>o});var n=r(5763),i=r(2177);class o{constructor(e,t,r){this.agentIdentifier=e,this.aggregator=t,this.ee=i.ee.get(e,(0,n.OP)(this.agentIdentifier).isolatedBacklog),this.featureName=r,this.blocked=!1}}},9144:(e,t,r)=>{r.d(t,{j:()=>m});var n=r(3325),i=r(5763),o=r(5546),a=r(2177),s=r(7894),c=r(8e3),u=r(3960),d=r(385),f=r(50),l=r(3081),h=r(8632);function g(){const e=(0,h.gG)();["setErrorHandler","finished","addToTrace","inlineHit","addRelease","addPageAction","setCurrentRouteName","setPageViewName","setCustomAttribute","interaction","noticeError","setUserId"].forEach((t=>{e[t]=function(){for(var r=arguments.length,n=new Array(r),i=0;i 1?r-1:0),i=1;i {e.exposed&&e.api[t]&&o.push(e.api[t](...n))})),o.length>1?o:o[0]}(t,...n)}}))}var p=r(2587);function m(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},m=arguments.length>2?arguments[2]:void 0,v=arguments.length>3?arguments[3]:void 0,{init:b,info:y,loader_config:w,runtime:x={loaderType:m},exposed:A=!0}=t;const E=(0,h.gG)();y||(b=E.init,y=E.info,w=E.loader_config),(0,i.Dg)(e,b||{}),(0,i.GE)(e,w||{}),(0,i.sU)(e,x),y.jsAttributes??={},d.v6&&(y.jsAttributes.isWorker=!0),(0,i.CX)(e,y),g();const T=function(e,t){t||(0,c.R)(e,"api");const h={};var g=a.ee.get(e),p=g.get("tracer"),m="api-",v=m+"ixn-";function b(t,r,n,o){const a=(0,i.C5)(e);return null===r?delete a.jsAttributes[t]:(0,i.CX)(e,{...a,jsAttributes:{...a.jsAttributes,[t]:r}}),x(m,n,!0,o||null===r?"session":void 0)(t,r)}function y(){}["setErrorHandler","finished","addToTrace","inlineHit","addRelease"].forEach((e=>h[e]=x(m,e,!0,"api"))),h.addPageAction=x(m,"addPageAction",!0,n.D.pageAction),h.setCurrentRouteName=x(m,"routeName",!0,n.D.spa),h.setPageViewName=function(t,r){if("string"==typeof t)return"/"!==t.charAt(0)&&(t="/"+t),(0,i.OP)(e).customTransaction=(r||"http://custom.transaction")+t,x(m,"setPageViewName",!0)()},h.setCustomAttribute=function(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if("string"==typeof e){if(["string","number"].includes(typeof t)||null===t)return b(e,t,"setCustomAttribute",r);(0,f.Z)("Failed to execute setCustomAttribute.\nNon-null value must be a string or number type, but a type of was provided."))}else(0,f.Z)("Failed to execute setCustomAttribute.\nName must be a string type, but a type of was provided."))},h.setUserId=function(e){if("string"==typeof e||null===e)return b("enduser.id",e,"setUserId",!0);(0,f.Z)("Failed to execute setUserId.\nNon-null value must be a string type, but a type of was provided."))},h.interaction=function(){return(new y).get()};var w=y.prototype={createTracer:function(e,t){var r={},i=this,a="function"==typeof t;return(0,o.p)(v+"tracer",[(0,s.z)(),e,r],i,n.D.spa,g),function(){if(p.emit((a?"":"no-")+"fn-start",[(0,s.z)(),i,a],r),a)try{return t.apply(this,arguments)}catch(e){throw p.emit("fn-err",[arguments,this,"string"==typeof e?new Error(e):e],r),e}finally{p.emit("fn-end",[(0,s.z)()],r)}}}};function x(e,t,r,i){return function(){return(0,o.p)(l.xS,["API/"+t+"/called"],void 0,n.D.metrics,g),i&&(0,o.p)(e+t,[(0,s.z)(),...arguments],r?null:this,i,g),r?void 0:this}}function A(){r.e(439).then(r.bind(r,7438)).then((t=>{let{setAPI:r}=t;r(e),(0,c.L)(e,"api")})).catch((()=>(0,f.Z)("Downloading runtime APIs failed...")))}return["actionText","setName","setAttribute","save","ignore","onEnd","getContext","end","get"].forEach((e=>{w[e]=x(v,e,void 0,n.D.spa)})),h.noticeError=function(e,t){"string"==typeof e&&(e=new Error(e)),(0,o.p)(l.xS,["API/noticeError/called"],void 0,n.D.metrics,g),(0,o.p)("err",[e,(0,s.z)(),!1,t],void 0,n.D.jserrors,g)},d.il?(0,u.b)((()=>A()),!0):A(),h}(e,v);return(0,h.Qy)(e,T,"api"),(0,h.Qy)(e,A,"exposed"),(0,h.EZ)("activatedFeatures",p.T),T}},3325:(e,t,r)=>{r.d(t,{D:()=>n,p:()=>i});const n={ajax:"ajax",jserrors:"jserrors",metrics:"metrics",pageAction:"page_action",pageViewEvent:"page_view_event",pageViewTiming:"page_view_timing",sessionReplay:"session_replay",sessionTrace:"session_trace",spa:"spa"},i={[n.pageViewEvent]:1,[n.pageViewTiming]:2,[n.metrics]:3,[n.jserrors]:4,[n.ajax]:5,[n.sessionTrace]:6,[n.pageAction]:7,[n.spa]:8,[n.sessionReplay]:9}}},n={};function i(e){var t=n[e];if(void 0!==t)return t.exports;var o=n[e]={exports:{}};return r[e](o,o.exports,i),o.exports}i.m=r,i.d=(e,t)=>{for(var r in t)i.o(t,r)&&!i.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:t[r]})},i.f={},i.e=e=>Promise.all(Object.keys(i.f).reduce(((t,r)=>(i.f[r](e,t),t)),[])),i.u=e=>(({78:"page_action-aggregate",147:"metrics-aggregate",242:"session-manager",317:"jserrors-aggregate",348:"page_view_timing-aggregate",412:"lazy-feature-loader",439:"async-api",538:"recorder",590:"session_replay-aggregate",675:"compressor",733:"session_trace-aggregate",786:"page_view_event-aggregate",873:"spa-aggregate",898:"ajax-aggregate"}[e]||e)+"."+{78:"ac76d497",147:"3dc53903",148:"1a20d5fe",242:"2a64278a",317:"49e41428",348:"bd6de33a",412:"2f55ce66",439:"30bd804e",538:"1b18459f",590:"cf0efb30",675:"ae9f91a8",733:"83105561",786:"06482edd",860:"03a8b7a5",873:"e6b09d52",898:"998ef92b"}[e]+"-1.236.0.min.js"),i.o=(e,t)=>Object.prototype.hasOwnProperty.call(e,t),e={},t="NRBA:",i.l=(r,n,o,a)=>{if(e[r])e[r].push(n);else{var s,c;if(void 0!==o)for(var u=document.getElementsByTagName("script"),d=0;d {s.onerror=s.onload=null,clearTimeout(h);var i=e[r];if(delete e[r],s.parentNode&&s.parentNode.removeChild(s),i&&i.forEach((e=>e(n))),t)return t(n)},h=setTimeout(l.bind(null,void 0,{type:"timeout",target:s}),12e4);s.onerror=l.bind(null,s.onerror),s.onload=l.bind(null,s.onload),c&&document.head.appendChild(s)}},i.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},i.j=364,i.p="https://js-agent.newrelic.com/",(()=>{var e={364:0,953:0};i.f.j=(t,r)=>{var n=i.o(e,t)?e[t]:void 0;if(0!==n)if(n)r.push(n[2]);else{var o=new Promise(((r,i)=>n=e[t]=[r,i]));r.push(n[2]=o);var a=i.p+i.u(t),s=new Error;i.l(a,(r=>{if(i.o(e,t)&&(0!==(n=e[t])&&(e[t]=void 0),n)){var o=r&&("load"===r.type?"missing":r.type),a=r&&r.target&&r.target.src;s.message="Loading chunk "+t+" failed.\n("+o+": "+a+")",s.name="ChunkLoadError",s.type=o,s.request=a,n[1](s)}}),"chunk-"+t,t)}};var t=(t,r)=>{var n,o,[a,s,c]=r,u=0;if(a.some((t=>0!==e[t]))){for(n in s)i.o(s,n)&&(i.m[n]=s[n]);if(c)c(i)}for(t&&t(r);u {i.r(o);var e=i(3325),t=i(5763);const r=Object.values(e.D);function n(e){const n={};return r.forEach((r=>{n[r]=function(e,r){return!1!==(0,t.Mt)(r,"".concat(e,".enabled"))}(r,e)})),n}var a=i(9144);var s=i(5546),c=i(385),u=i(8e3),d=i(5938),f=i(3960),l=i(50);class h extends d.W{constructor(e,t,r){let n=!(arguments.length>3&&void 0!==arguments[3])||arguments[3];super(e,t,r),this.auto=n,this.abortHandler,this.featAggregate,this.onAggregateImported,n&&(0,u.R)(e,r)}importAggregator(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};if(this.featAggregate||!this.auto)return;const r=c.il&&!0===(0,t.Mt)(this.agentIdentifier,"privacy.cookies_enabled");let n;this.onAggregateImported=new Promise((e=>{n=e}));const o=async()=>{let t;try{if(r){const{setupAgentSession:e}=await Promise.all([i.e(860),i.e(242)]).then(i.bind(i,3228));t=e(this.agentIdentifier)}}catch(e){(0,l.Z)("A problem occurred when starting up session manager. This page will not start or extend any session.",e)}try{if(!this.shouldImportAgg(this.featureName,t))return void(0,u.L)(this.agentIdentifier,this.featureName);const{lazyFeatureLoader:r}=await i.e(412).then(i.bind(i,8582)),{Aggregate:o}=await r(this.featureName,"aggregate");this.featAggregate=new o(this.agentIdentifier,this.aggregator,e),n(!0)}catch(e){(0,l.Z)("Downloading and initializing ".concat(this.featureName," failed..."),e),this.abortHandler?.(),n(!1)}};c.il?(0,f.b)((()=>o()),!0):o()}shouldImportAgg(r,n){return r!==e.D.sessionReplay||!1!==(0,t.Mt)(this.agentIdentifier,"session_trace.enabled")&&(!!n?.isNew||!!n?.state.sessionReplay)}}var g=i(7633),p=i(7894);class m extends h{static featureName=g.t9;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];if(super(r,n,g.t9,i),("undefined"==typeof PerformanceNavigationTiming||c.Tt)&&"undefined"!=typeof PerformanceTiming){const n=(0,t.OP)(r);n[g.Dz]=Math.max(Date.now()-n.offset,0),(0,f.K)((()=>n[g.qw]=Math.max((0,p.z)()-n[g.Dz],0))),(0,f.b)((()=>{const t=(0,p.z)();n[g.OJ]=Math.max(t-n[g.Dz],0),(0,s.p)("timing",["load",t],void 0,e.D.pageViewTiming,this.ee)}))}this.importAggregator()}}var v=i(1117),b=i(1284);class y extends v.w{constructor(e){super(e),this.aggregatedData={}}store(e,t,r,n,i){var o=this.getBucket(e,t,r,i);return o.metrics=function(e,t){t||(t={count:0});return t.count+=1,(0,b.D)(e,(function(e,r){t[e]=w(r,t[e])})),t}(n,o.metrics),o}merge(e,t,r,n,i){var o=this.getBucket(e,t,n,i);if(o.metrics){var a=o.metrics;a.count+=r.count,(0,b.D)(r,(function(e,t){if("count"!==e){var n=a[e],i=r[e];i&&!i.c?a[e]=w(i.t,n):a[e]=function(e,t){if(!t)return e;t.c||(t=x(t.t));return t.min=Math.min(e.min,t.min),t.max=Math.max(e.max,t.max),t.t+=e.t,t.sos+=e.sos,t.c+=e.c,t}(i,a[e])}}))}else o.metrics=r}storeMetric(e,t,r,n){var i=this.getBucket(e,t,r);return i.stats=w(n,i.stats),i}getBucket(e,t,r,n){this.aggregatedData[e]||(this.aggregatedData[e]={});var i=this.aggregatedData[e][t];return i||(i=this.aggregatedData[e][t]={params:r||{}},n&&(i.custom=n)),i}get(e,t){return t?this.aggregatedData[e]&&this.aggregatedData[e][t]:this.aggregatedData[e]}take(e){for(var t={},r="",n=!1,i=0;i t.max&&(t.max=e),e 2&&void 0!==arguments[2])||arguments[2];super(e,r,j.t,n),c.il&&((0,t.OP)(e).initHidden=Boolean("hidden"===document.visibilityState),(0,N.N)((()=>(0,s.p)("docHidden",[(0,p.z)()],void 0,j.t,this.ee)),!0),(0,O.bP)("pagehide",(()=>(0,s.p)("winPagehide",[(0,p.z)()],void 0,j.t,this.ee))),this.importAggregator())}}var P=i(3081);class C extends h{static featureName=P.t9;constructor(e,t){let r=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(e,t,P.t9,r),this.importAggregator()}}var R,I=i(2210),k=i(1214),H=i(2177),L={};try{R=localStorage.getItem("__nr_flags").split(","),console&&"function"==typeof console.log&&(L.console=!0,-1!==R.indexOf("dev")&&(L.dev=!0),-1!==R.indexOf("nr_dev")&&(L.nrDev=!0))}catch(e){}function z(e){try{L.console&&z(e)}catch(e){}}L.nrDev&&H.ee.on("internal-error",(function(e){z(e.stack)})),L.dev&&H.ee.on("fn-err",(function(e,t,r){z(r.stack)})),L.dev&&(z("NR AGENT IN DEVELOPMENT MODE"),z("flags: "+(0,b.D)(L,(function(e,t){return e})).join(", ")));var M=i(6660);class B extends h{static featureName=M.t;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(r,n,M.t,i),this.skipNext=0;try{this.removeOnAbort=new AbortController}catch(e){}const o=this;o.ee.on("fn-start",(function(e,t,r){o.abortHandler&&(o.skipNext+=1)})),o.ee.on("fn-err",(function(t,r,n){o.abortHandler&&!n[M.A]&&((0,I.X)(n,M.A,(function(){return!0})),this.thrown=!0,(0,s.p)("err",[n,(0,p.z)()],void 0,e.D.jserrors,o.ee))})),o.ee.on("fn-end",(function(){o.abortHandler&&!this.thrown&&o.skipNext>0&&(o.skipNext-=1)})),o.ee.on("internal-error",(function(t){(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,o.ee)})),this.origOnerror=c._A.onerror,c._A.onerror=this.onerrorHandler.bind(this),c._A.addEventListener("unhandledrejection",(t=>{const r=function(e){let t="Unhandled Promise Rejection: ";if(e instanceof Error)try{return e.message=t+e.message,e}catch(t){return e}if(void 0===e)return new Error(t);try{return new Error(t+(0,D.P)(e))}catch(e){return new Error(t)}}(t.reason);(0,s.p)("err",[r,(0,p.z)(),!1,{unhandledPromiseRejection:1}],void 0,e.D.jserrors,this.ee)}),(0,O.m$)(!1,this.removeOnAbort?.signal)),(0,k.gy)(this.ee),(0,k.BV)(this.ee),(0,k.em)(this.ee),(0,t.OP)(r).xhrWrappable&&(0,k.Kf)(this.ee),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}onerrorHandler(t,r,n,i,o){"function"==typeof this.origOnerror&&this.origOnerror(...arguments);try{this.skipNext?this.skipNext-=1:(0,s.p)("err",[o||new F(t,r,n),(0,p.z)()],void 0,e.D.jserrors,this.ee)}catch(t){try{(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,this.ee)}catch(e){}}return!1}}function F(e,t,r){this.message=e||"Uncaught error with no additional information",this.sourceURL=t,this.line=r}let U=1;const q="nr@id";function G(e){const t=typeof e;return!e||"object"!==t&&"function"!==t?-1:e===c._A?0:(0,I.X)(e,q,(function(){return U++}))}function V(e){if("string"==typeof e&&e.length)return e.length;if("object"==typeof e){if("undefined"!=typeof ArrayBuffer&&e instanceof ArrayBuffer&&e.byteLength)return e.byteLength;if("undefined"!=typeof Blob&&e instanceof Blob&&e.size)return e.size;if(!("undefined"!=typeof FormData&&e instanceof FormData))try{return(0,D.P)(e).length}catch(e){return}}}var X=i(7243);class W{constructor(e){this.agentIdentifier=e,this.generateTracePayload=this.generateTracePayload.bind(this),this.shouldGenerateTrace=this.shouldGenerateTrace.bind(this)}generateTracePayload(e){if(!this.shouldGenerateTrace(e))return null;var r=(0,t.DL)(this.agentIdentifier);if(!r)return null;var n=(r.accountID||"").toString()||null,i=(r.agentID||"").toString()||null,o=(r.trustKey||"").toString()||null;if(!n||!i)return null;var a=(0,_.M)(),s=(0,_.Ht)(),c=Date.now(),u={spanId:a,traceId:s,timestamp:c};return(e.sameOrigin||this.isAllowedOrigin(e)&&this.useTraceContextHeadersForCors())&&(u.traceContextParentHeader=this.generateTraceContextParentHeader(a,s),u.traceContextStateHeader=this.generateTraceContextStateHeader(a,c,n,i,o)),(e.sameOrigin&&!this.excludeNewrelicHeader()||!e.sameOrigin&&this.isAllowedOrigin(e)&&this.useNewrelicHeaderForCors())&&(u.newrelicHeader=this.generateTraceHeader(a,s,c,n,i,o)),u}generateTraceContextParentHeader(e,t){return"00-"+t+"-"+e+"-01"}generateTraceContextStateHeader(e,t,r,n,i){return i+"@nr=0-1-"+r+"-"+n+"-"+e+"----"+t}generateTraceHeader(e,t,r,n,i,o){if(!("function"==typeof c._A?.btoa))return null;var a={v:[0,1],d:{ty:"Browser",ac:n,ap:i,id:e,tr:t,ti:r}};return o&&n!==o&&(a.d.tk=o),btoa((0,D.P)(a))}shouldGenerateTrace(e){return this.isDtEnabled()&&this.isAllowedOrigin(e)}isAllowedOrigin(e){var r=!1,n={};if((0,t.Mt)(this.agentIdentifier,"distributed_tracing")&&(n=(0,t.P_)(this.agentIdentifier).distributed_tracing),e.sameOrigin)r=!0;else if(n.allowed_origins instanceof Array)for(var i=0;i 2&&void 0!==arguments[2])||arguments[2];super(r,n,Z.t,i),(0,t.OP)(r).xhrWrappable&&(this.dt=new W(r),this.handler=(e,t,r,n)=>(0,s.p)(e,t,r,n,this.ee),(0,k.u5)(this.ee),(0,k.Kf)(this.ee),function(r,n,i,o){function a(e){var t=this;t.totalCbs=0,t.called=0,t.cbTime=0,t.end=E,t.ended=!1,t.xhrGuids={},t.lastSize=null,t.loadCaptureCalled=!1,t.params=this.params||{},t.metrics=this.metrics||{},e.addEventListener("load",(function(r){_(t,e)}),(0,O.m$)(!1)),c.IF||e.addEventListener("progress",(function(e){t.lastSize=e.loaded}),(0,O.m$)(!1))}function s(e){this.params={method:e[0]},T(this,e[1]),this.metrics={}}function u(e,n){var i=(0,t.DL)(r);i.xpid&&this.sameOrigin&&n.setRequestHeader("X-NewRelic-ID",i.xpid);var a=o.generateTracePayload(this.parsedOrigin);if(a){var s=!1;a.newrelicHeader&&(n.setRequestHeader("newrelic",a.newrelicHeader),s=!0),a.traceContextParentHeader&&(n.setRequestHeader("traceparent",a.traceContextParentHeader),a.traceContextStateHeader&&n.setRequestHeader("tracestate",a.traceContextStateHeader),s=!0),s&&(this.dt=a)}}function d(e,t){var r=this.metrics,i=e[0],o=this;if(r&&i){var a=V(i);a&&(r.txSize=a)}this.startTime=(0,p.z)(),this.listener=function(e){try{"abort"!==e.type||o.loadCaptureCalled||(o.params.aborted=!0),("load"!==e.type||o.called===o.totalCbs&&(o.onloadCalled||"function"!=typeof t.onload)&&"function"==typeof o.end)&&o.end(t)}catch(e){try{n.emit("internal-error",[e])}catch(e){}}};for(var s=0;s 1?e[1]=i:e.push(i)}else e[0]&&e[0].headers&&s(e[0].headers,n)&&(this.dt=n);function s(e,t){var r=!1;return t.newrelicHeader&&(e.set("newrelic",t.newrelicHeader),r=!0),t.traceContextParentHeader&&(e.set("traceparent",t.traceContextParentHeader),t.traceContextStateHeader&&e.set("tracestate",t.traceContextStateHeader),r=!0),r}}function x(e,t){this.params={},this.metrics={},this.startTime=(0,p.z)(),this.dt=t,e.length>=1&&(this.target=e[0]),e.length>=2&&(this.opts=e[1]);var r,n=this.opts||{},i=this.target;"string"==typeof i?r=i:"object"==typeof i&&i instanceof Y?r=i.url:c._A?.URL&&"object"==typeof i&&i instanceof URL&&(r=i.href),T(this,r);var o=(""+(i&&i instanceof Y&&i.method||n.method||"GET")).toUpperCase();this.params.method=o,this.txSize=V(n.body)||0}function A(t,r){var n;this.endTime=(0,p.z)(),this.params||(this.params={}),this.params.status=r?r.status:0,"string"==typeof this.rxSize&&this.rxSize.length>0&&(n=+this.rxSize);var o={txSize:this.txSize,rxSize:n,duration:(0,p.z)()-this.startTime};i("xhr",[this.params,o,this.startTime,this.endTime,"fetch"],this,e.D.ajax)}function E(t){var r=this.params,n=this.metrics;if(!this.ended){this.ended=!0;for(var o=0;o 2&&void 0!==arguments[2])||arguments[2];super(e,t,we.t,r),this.importAggregator()}}new class{constructor(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:(0,_.ky)(16);c._A?(this.agentIdentifier=t,this.sharedAggregator=new y({agentIdentifier:this.agentIdentifier}),this.features={},this.desiredFeatures=new Set(e.features||[]),this.desiredFeatures.add(m),Object.assign(this,(0,a.j)(this.agentIdentifier,e,e.loaderType||"agent")),this.start()):(0,l.Z)("Failed to initial the agent. Could not determine the runtime environment.")}get config(){return{info:(0,t.C5)(this.agentIdentifier),init:(0,t.P_)(this.agentIdentifier),loader_config:(0,t.DL)(this.agentIdentifier),runtime:(0,t.OP)(this.agentIdentifier)}}start(){const t="features";try{const r=n(this.agentIdentifier),i=[...this.desiredFeatures];i.sort(((t,r)=>e.p[t.featureName]-e.p[r.featureName])),i.forEach((t=>{if(r[t.featureName]||t.featureName===e.D.pageViewEvent){const n=function(t){switch(t){case e.D.ajax:return[e.D.jserrors];case e.D.sessionTrace:return[e.D.ajax,e.D.pageViewEvent];case e.D.sessionReplay:return[e.D.sessionTrace];case e.D.pageViewTiming:return[e.D.pageViewEvent];default:return[]}}(t.featureName);n.every((e=>r[e]))||(0,l.Z)("".concat(t.featureName," is enabled but one or more dependent features has been disabled (").concat((0,D.P)(n),"). This may cause unintended consequences or missing data...")),this.features[t.featureName]=new t(this.agentIdentifier,this.sharedAggregator)}})),(0,T.Qy)(this.agentIdentifier,this.features,t)}catch(e){(0,l.Z)("Failed to initialize all enabled instrument classes (agent aborted) -",e);for(const e in this.features)this.features[e].abortHandler?.();const r=(0,T.fP)();return delete r.initializedAgents[this.agentIdentifier]?.api,delete r.initializedAgents[this.agentIdentifier]?.[t],delete this.sharedAggregator,r.ee?.abort(),delete r.ee?.get(this.agentIdentifier),!1}}}({features:[J,m,S,class extends h{static featureName=oe;constructor(t,r){if(super(t,r,oe,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;const n=this.ee;let i;(0,k.QU)(n),this.eventsEE=(0,k.em)(n),this.eventsEE.on(se,(function(e,t){this.bstStart=(0,p.z)()})),this.eventsEE.on(ae,(function(t,r){(0,s.p)("bst",[t[0],r,this.bstStart,(0,p.z)()],void 0,e.D.sessionTrace,n)})),n.on(ce+ne,(function(e){this.time=(0,p.z)(),this.startPath=location.pathname+location.hash})),n.on(ce+ie,(function(t){(0,s.p)("bstHist",[location.pathname+location.hash,this.startPath,this.time],void 0,e.D.sessionTrace,n)}));try{i=new PerformanceObserver((t=>{const r=t.getEntries();(0,s.p)(te,[r],void 0,e.D.sessionTrace,n)})),i.observe({type:re,buffered:!0})}catch(e){}this.importAggregator({resourceObserver:i})}},C,xe,B,class extends h{static featureName=de;constructor(e,r){if(super(e,r,de,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;if(!(0,t.OP)(e).xhrWrappable)return;try{this.removeOnAbort=new AbortController}catch(e){}let n,i=0;const o=this.ee.get("tracer"),a=(0,k._L)(this.ee),s=(0,k.Lg)(this.ee),u=(0,k.BV)(this.ee),d=(0,k.Kf)(this.ee),f=this.ee.get("events"),l=(0,k.u5)(this.ee),h=(0,k.QU)(this.ee),g=(0,k.Gm)(this.ee);function m(e,t){h.emit("newURL",[""+window.location,t])}function v(){i++,n=window.location.hash,this[ve]=(0,p.z)()}function b(){i--,window.location.hash!==n&&m(0,!0);var e=(0,p.z)();this[pe]=~~this[pe]+e-this[ve],this[ye]=e}function y(e,t){e.on(t,(function(){this[t]=(0,p.z)()}))}this.ee.on(ve,v),s.on(be,v),a.on(be,v),this.ee.on(ye,b),s.on(ge,b),a.on(ge,b),this.ee.buffer([ve,ye,"xhr-resolved"],this.featureName),f.buffer([ve],this.featureName),u.buffer(["setTimeout"+le,"clearTimeout"+fe,ve],this.featureName),d.buffer([ve,"new-xhr","send-xhr"+fe],this.featureName),l.buffer([me+fe,me+"-done",me+he+fe,me+he+le],this.featureName),h.buffer(["newURL"],this.featureName),g.buffer([ve],this.featureName),s.buffer(["propagate",be,ge,"executor-err","resolve"+fe],this.featureName),o.buffer([ve,"no-"+ve],this.featureName),a.buffer(["new-jsonp","cb-start","jsonp-error","jsonp-end"],this.featureName),y(l,me+fe),y(l,me+"-done"),y(a,"new-jsonp"),y(a,"jsonp-end"),y(a,"cb-start"),h.on("pushState-end",m),h.on("replaceState-end",m),window.addEventListener("hashchange",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("load",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("popstate",(function(){m(0,i>1)}),(0,O.m$)(!0,this.removeOnAbort?.signal)),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}}],loaderType:"spa"})})(),window.NRBA=o})(); window.jQuery || document.write(' ') CKEDITOR_BASEPATH='https://f1000research.com/js/vendor/ckeditor/' window.reactTheme = 'research'; window.MathJax = { CommonHTML: { linebreaks: { automatic: true } }, 'HTML-CSS': { linebreaks: { automatic: true } }, SVG: { linebreaks: { automatic: true } }, AuthorInit: function() { MathJax.Hub.Register.MessageHook('End Process', function () { let timeout = false; // holder for timeout id const delay = 250; // delay after event is "complete" to run callback const reflowMath = function() { const dispFormulas = document.querySelectorAll('.disp-formula.panel'); if (!dispFormulas) { return; } for (const dispFormula of dispFormulas) { const child = dispFormula.querySelector('.MathJax_Preview').nextSibling.firstChild; const isMultiline = MathJax.Hub.getAllJax(dispFormula)[0].root.isMultiline; if (dispFormula.offsetWidth < child.offsetWidth || isMultiline) { MathJax.Hub.Queue(['Rerender', MathJax.Hub, dispFormula]); } } }; window.addEventListener('resize', function() { clearTimeout(timeout); // clear the timeout timeout = setTimeout(reflowMath, delay); // start timing for event "completion" }); }); }, }; if (window.location.hash == '#_=_'){ window.location = window.location.href.split('#')[0] } !function(f,b,e,v,n,t,s){if(f.fbq)return;n=f.fbq=function() {n.callMethod? n.callMethod.apply(n,arguments):n.queue.push(arguments)} ;if(!f._fbq)f._fbq=n; n.push=n;n.loaded=!0;n.version='2.0';n.queue=[];t=b.createElement(e);t.async=!0; t.src=v;s=b.getElementsByTagName(e)[0];s.parentNode.insertBefore(t,s)}(window, document,'script','https://connect.facebook.net/en_US/fbevents.js'); fbq('init', '1641728616063202'); fbq('track', "PixelInitialized", {}); (function(h,o,t,j,a,r){ h.hj=h.hj||function(){(h.hj.q=h.hj.q||[]).push(arguments)}; h._hjSettings={hjid:2318163,hjsv:6}; a=o.getElementsByTagName('head')[0]; r=o.createElement('script');r.async=1; r.src=t+h._hjSettings.hjid+j+h._hjSettings.hjsv; a.appendChild(r); })(window,document,'https://static.hotjar.com/c/hotjar-','.js?sv='); search file_upload Submit your research search menu close search Browse Gateways & Collections How to Publish Submit your Research My Submissions Article Guidelines Article Guidelines (New Versions) Open Data, Software and Code Guidelines Open Data and Accessible Source Materials Guidelines (HSS) Open Data, Software and Code Guidelines (PSE) Prepublication Checks Production Process Posters and Slides Guidelines Document Guidelines Article Processing Charges Peer Review Finding Article Reviewers About How it Works For Reviewers Our Advisors Policies Glossary FAQs For Developers Newsroom Contact My Research Submissions Content and Tracking Alerts My Details Sign In file_upload Submit your research { "@context": "https://schema.org", "@type": "ScholarlyArticle", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://f1000research.com/articles/12-66" }, "headline": "Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and...", "datePublished": "2023-01-16T17:23:52", "dateModified": "2024-01-19T14:44:57", "author": [ { "@type": "Person", "name": "Desy Thayyil Menambath" }, { "@type": "Person", "name": "Usha Adiga" }, { "@type": "Person", "name": "Tirthal Rai" }, { "@type": "Person", "name": "Sachidananda Adiga" }, { "@type": "Person", "name": "Vijith Shetty" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": " Introduction The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 67 dangerous, and I-Mutant found 58 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/12-66", "name": "Identification of the SIRT1 gene's most harmful non-synonymous SNPs..." } } ] } Home Browse Identification of the SIRT1 gene's most harmful non-synonymous SNPs... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Thayyil Menambath D, Adiga U, Rai T et al. Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.12688/f1000research.128706.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Revised Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] Desy Thayyil Menambath 1 , Usha Adiga https://orcid.org/0000-0001-7832-3991 1 , Tirthal Rai https://orcid.org/0000-0002-6952-3788 1 , Sachidananda Adiga 2 , Vijith Shetty 3 Desy Thayyil Menambath 1 , Usha Adiga https://orcid.org/0000-0001-7832-3991 1 , [...] Tirthal Rai https://orcid.org/0000-0002-6952-3788 1 , Sachidananda Adiga 2 , Vijith Shetty 3 PUBLISHED 19 Jan 2024 Author details Author details 1 Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, Karnataka, 575018, India 2 Pharmacology, KS Hegde Medical Academy, NITTE(DU), Mangalore, Karnataka, 575018, India 3 Oncology, KS Hegde Medical Academy, NITTE(DU), Mangalore, Karnataka, 575018, India Desy Thayyil Menambath Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Usha Adiga Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation Tirthal Rai Roles: Formal Analysis, Resources, Validation, Writing – Review & Editing Sachidananda Adiga Roles: Formal Analysis, Resources, Validation, Visualization, Writing – Review & Editing Vijith Shetty Roles: Formal Analysis, Supervision, Validation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Genomics and Genetics gateway. This article is included in the Cell & Molecular Biology gateway. Abstract Introduction The sirtuin (Silent mating type information regulation 2 homolog)1(SIRT1) protein plays a vital role in many disorders such as diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases. The objective of this in silico analysis of SIRT1's functional single nucleotide polymorphisms (SNPs) was to gain valuable insight into the harmful effects of non-synonymous SNPs (nsSNPs) on the protein. The objective of the study was to use bioinformatics methods to investigate the genetic variations and modifications that may have an impact on the SIRT1 gene's expression and function. Methods nsSNPs of SIRT1 protein were collected from the dbSNP site, from its three (3) different protein accession IDs. These were then fed to various bioinformatic tools such as SIFT, Provean, and I- Mutant to find the most deleterious ones. Functional and structural effects were examined using the HOPE server and I-Tasser. Gene interactions were predicted by STRING software. The SIFT, Provean, and I-Mutant tools detected the most deleterious three nsSNPs (rs769519031, rs778184510, and rs199983221). Results Out of 252 nsSNPs, SIFT analysis showed that 94 were deleterious, Provean listed 67 dangerous, and I-Mutant found 58 nsSNPs resulting in lowered stability of proteins. HOPE modelling of rs199983221 and rs769519031 suggested reduced hydrophobicity due to Ile 4Thr and Ile223Ser resulting in decreased hydrophobic interactions. In contrast, on modelling rs778184510, the mutant protein had a higher hydrophobicity than the wild type. Conclusions Our study reports that three nsSNPs (D357A, I223S, I4T) are the most damaging mutations of the SIRT1 gene. Mutations may result in altered protein structure and functions. Such altered protein may be the basis for various disorders. Our findings may be a crucial guide in establishing the pathogenesis of various disorders. READ ALL READ LESS Keywords SIRT1, nsSNP, bioinformatics, protein modelling Corresponding Author(s) Usha Adiga ( [email protected] ) Close Corresponding author: Usha Adiga Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2024 Thayyil Menambath D et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Thayyil Menambath D, Adiga U, Rai T et al. Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.12688/f1000research.128706.2 ) First published: 16 Jan 2023, 12 :66 ( https://doi.org/10.12688/f1000research.128706.1 ) Latest published: 19 Jan 2024, 12 :66 ( https://doi.org/10.12688/f1000research.128706.2 ) Revised Amendments from Version 1 The revised article shows significant improvements. First, the introduction now includes the latest reference articles. Second, the explanation of criteria for selecting harmful nsSNPs improves the transparency of the methodology. Figure 1 has been carefully modified after re-analysis, making it a clearer visual representation. Lastly, a detailed explanation for Figure 5 enhances reader comprehension. The revised article shows significant improvements. First, the introduction now includes the latest reference articles. Second, the explanation of criteria for selecting harmful nsSNPs improves the transparency of the methodology. Figure 1 has been carefully modified after re-analysis, making it a clearer visual representation. Lastly, a detailed explanation for Figure 5 enhances reader comprehension. See the authors' detailed response to the review by Bhushan L. Thakur See the authors' detailed response to the review by Laxminarayana Kurady Bairy READ REVIEWER RESPONSES Introduction In silico analysis of SIRT1 Gene Sirtuins are nicotinamide adenine dinucleotide (NAD+)-dependent deacetylases that regulate transcriptional activity intracellularly. They are present in a wide range of tissues, such as the adipose, kidney, brain, liver, and muscle tissues. 1 , 2 SIRT1 (Silent mating-type information regulation 2 homolog 1) is known to regulate a variety of cellular processes, including lipid and glucose metabolism, stress tolerance, autophagy, circadian rhythms, and mitochondrial biogenesis, according to several studies. 3 – 5 SIRT1 gene expression modulates its downstream pathways in diabetes, cancer, obesity, inflammation, and neurodegenerative and cardiovascular diseases by focusing on numerous cellular proteins, including nuclear factor-κB (NF-κB), endothelial nitric oxide synthase (eNOS), forkhead transcriptional factors (FoxOs), AMP-activated protein kinase (AMPK), protein tyrosine phosphatase (PTP). However, considerable evidence suggests that in a variety of malignant cell types, SIRT1 is upregulated and that SIRT1 antagonists prevented the development of cancer cells. 6 – 8 Single nucleotide polymorphisms (SNPs) are variations in the DNA sequence that result from the alterations in a single nucleotide (A, T, C, or G). Around 90% of human genetic variation is made up of SNPs. The three-billion-base human genome has SNPs at every 100–300 bases, with varying densities between regions. 9 The genome's coding and noncoding sections can both present SNPs. SNPs can have a wide spectrum of effects on how cells behave, from having no effect to causing disease or altering the reaction to a drug. Since they are responsible for about half of the genetic differences associated with human hereditary diseases, non-synonymous SNPs (nsSNPs) that result in an amino acid residue substitution in the protein product are also of high relevance. 10 There may be effects on transcription factor binding, splicing, or gene expression from coding synonymous SNPs (sSNPs) and SNPs that aren't in the gene promoter or coding regions. 11 , 12 Human reactions to viruses, medications, vaccinations, and other agents are significantly influenced by SNPs. SNPs are therefore useful in biomedical research, the creation of pharmaceutical products, the improvement of medical diagnostics, and the application of personalised medicine. 13 SNPs are responsible for specific phenotypes and therefore it is very important to identify them. This is a difficult task as it necessitates repeatedly evaluating thousands of SNPs in candidate genes. Selecting a group of SNPs for a study to determine the role of an SNP in a disease is a challenging endeavour; in these situations, a bioinformatics tool may be very helpful to distinguish between neutral and functional SNPs. They might also show the structural underpinnings of the mutations. These bioinformatics applications are used to assess the SNPs’ functional significance. To find the SIRT1 protein's most dangerous nsSNPs, we applied bioinformatics techniques. We hypothesised that SIRT1 protein would be harmful because of nsSNPs on the gene. This is the first study of its kind for the SIRT1 gene to include both protein structure prediction and mutation analysis. Methods Multiple steps were used to complete the study. The figure below shows the equipment used to complete the task ( Figure 1 ). Figure 1. Sorting of nsSNPs of SIRT1. Extraction of nsSNPs The NCBI SNP database was accessed. Information on the entire SIRT1 gene, including its nsSNPs, was obtained. As the query sequence, filtered nsSNPs from the dbSNP database were examined. The NCBI Protein accession IDs NP_ 036370.2, NP_001135970.1, and NP_002294.2 for the SIRT1 gene were used. Identification of damaging nsSNPs SIFT, Provean, and I-Mutant software were used to identify the impact of spotted nsSNPs on the SIRT1 gene. SIFT (Sorting Intolerant from Tolerant) server The SIFT server is a web-based bioinformatics tool that forecasts the detrimental effects of nucleotide substitution and frame shift (insertion/deletion) on protein function based on the degree of amino acid residue maintenance in sequence alignments obtained from highly associated sequences, with the primary assumption that mutations in evolutionarily conserved regions primarily affect its function. 14 The distinct input data order for the SIFT server includes protein sequence, chromosome location, and dbSNP reference number. SNPs and Indels were separated from the overall number in order to use this tool, and they were provided with the chromosome positions for frame shift indels and the residue number (rs) ID numbers for missense, nonsense, and stop gain SNPs. Each residue was given a value from 0 to 1 by the SIFT server, with scores below 0.05 indicating detrimental amino acid changes and scores above 0.05 indicating tolerance. 15 The website hosts SIFT version 5.2.2. Provean A protein's biological activity may be impacted by an amino acid substitution or indel, according to predictions made by the programme Protein Variation Effect Analyzer (PROVEAN). When filtering sequence variants, PROVEAN is useful for locating nonsynonymous or indel variations that are anticipated to be functionally significant. 16 The tool takes as input a protein sequence and several amino acid combinations, runs a BLAST search to find related sequences (supporting sequences), and outputs PROVEAN scores. The interpretation was done using the score thresholds. The default threshold is -2.5, meaning that variants with a score of -2.5 or less are deemed harmful, whereas variants with a score of -2.5 or more are considered neutral. http://provean.jcvi.org/index.php can be visited to access Provean. I-Mutant 2.0 I-Mutant 2.0 was used in the investigation to analyse the stability of the targeted SIRT1 protein. This website server estimates any mutation-related changes to protein stability. 17 By adjusting the pH to 7 and the temperature to 25°C, this technique was used to analyse the SIRT1 protein sequences. It gives the opportunity to forecast how the protein's stability will be altered in response to single-site changes in the protein's structure or sequence. The design of the I-Mutant outcome is as follows: Free energy change value; Delta Delta G (DDG)= 0 is neutral, DDG > 0 is an increase in stability, and DDG <0 is a reduction in stability (I-Mutant website ) Examining the functional and structural effect of nsSNPs To understand the effect of nsSNPs on the SIRT1 protein structure, the study used Polyphen , HOPE and I-Tasser software. The three most deleterious and damaging nsSNPs of the SIRT1 gene from each of its isoforms were chosen and processed to examine their structural and functional effects on SIRT1 protein. Polyphen Using simple physical and comparative considerations, polymorphism phenotyping v2(PolyPhen) is a method that estimates the potential effects of an amino acid substitution on the structure and functionality of a human protein. 18 HOPE modelling The HOPE server analyses mutations automatically and can show the structural repercussions of a mutation. In addition to predictions from DAS services, sequence annotations from the UniProt database and calculations on the 3D coordinates of the protein using WHAT IF Web services are just a few of the data sources that HOPE uses to compile its information. 19 Iterative Threading ASSEmbly Refinement ( I-Tasser) I-Tasser is a software package for protein structure and function modelling. The Template modelling score was used to compare the wild and mutant models. The estimated values of root mean square deviation (RMSD) and melting temperature (TM) allowed for the precise determination of similarity score. According to statistics, a TM-score of 0.17 or less indicates that two randomly chosen structures from the Protein DataBank library are comparable, while a score of 0.5 or more indicates that two structures have a similar topology. Studies have demonstrated a clear correlation between a high level of RMSD value and a high amount of change between wild-type and mutant. 20 , 21 The harmful mutations were then introduced into I-Tasser by adhering to their values. 22 – 24 Chimera 1.11 was used to study the molecular characteristics and interactive visualisation of the final protein structure. 25 Gene-gene interactions of the SIRT1 gene Managing protein interactions is essential for maintaining the system's homeostasis. STRING's task is to display the total score of interaction genes. In this stage, SIRT1 served as the input target gene, and analysis was completed. Results and discussion Extraction of nsSNPs The number of SNPs of the SIRT1 gene obtained from the NCBI database were 15,865. Three isoforms for SIRT1 were found ( isoform a , isoform b and isoform c). Isoform a (NP_036370.2) comprised 597 nsSNPs, isoform b (NP_001135970.1) comprised a total of 330 nsSNPs and isoform c (NP_001300978.1) 331 nsSNPs. The diagrammatical depiction is shown in Figure 1 . The nsSNPs listed in all the isoforms are listed and the duplicates were deleted; the total number of nsSNPs included in all the isoforms was 252 ( Table 1 ). Table 1. SIFT, I-Mutant, and Provean analyses for the nsSNPs of the SIRT1 Gene. Coordinates Known protein ID Substitution dbSNP ID Prediction SIFT score DDG (Kcal/mol/stability) Provean score prediction 10,69647216,1,C/T Q96EB6 H158Y rs767540399 TOLERATED 1 0.06/increased -1.115 Neutral 10,69648720,1,A/G Q96EB6 I210V rs369379188 TOLERATED 0.82 -0.61/decreased 0.333 Neutral 10,69644769,1,C/A Q96EB6 A97E rs550317521 TOLERATED 0.76 -0.21/decreased -0.457 Neutral 10,69647188,1,C/A Q96EB6 F148L rs773494159 TOLERATED 0.75 -1.27/decreased 0.215 Neutral 10,69644762,1,A/T Q96EB6 T95S rs767360333 TOLERATED 0.75 -0.03/decreased -0.254 Neutral 10,69647286,1,G/A Q96EB6 R181Q rs547102478 TOLERATED 0.72 -1.13/decreased 0.115 Neutral 10,69648649,1,C/G Q96EB6 T186S rs201841214 TOLERATED 0.64 -0.59/decreased 0.061 Neutral 10,69644828,1,G/A Q96EB6 A117T rs756786838 TOLERATED 0.59 -0.77/decreased 0.599 Neutal 10,69644675,1,G/C Q96EB6 G66R rs531048058 TOLERATED 0.59 -0.20/decreased 0.25 Neutral 10,69644864,1,G/A Q96EB6 G129S rs746381892 TOLERATED 0.53 -0.58/decreased -0.191 Neutral 10,69648723,1,C/A Q96EB6 P211T rs201007799 TOLERATED 0.51 -0.92/decreased -0.014 Neutral 10,69647222,1,T/A Q96EB6 C160S rs763883280 TOLERATED 0.49 -0.82/decreased 0.042 Neutral 10,69644778,1,A/G Q96EB6 E100G rs199624804 TOLERATED 0.49 -0.73/decreased -1.003 Neutral 10,69648724,1,C/T Q96EB6 P211L rs201668639 TOLERATED 0.48 -0.43/decreased 1.077 Neutral 10,69647273,1,A/G Q96EB6 T177A rs565217830 TOLERATED 0.47 -1.23/decreased -0.59 Neutral 10,69644820,1,C/A Q96EB6 P114Q rs182199697 TOLERATED 0.45 -1.37/decreased -0.658 Neutral 10,69648744,1,A/G Q96EB6 M218V rs745979871 TOLERATED 0.4 -0.63/decreased -1.14 Neutral 10,69644688,1,C/T Q96EB6 A70V rs751564985 TOLERATED 0.37 -0.05/decreased 0.69 Neutral 10,69647183,1,C/G Q96EB6 L147V rs748384143 TOLERATED 0.34 -1.7/decreased -0.174 Neutral 10,69648722,1,A/G Q96EB6 I210M rs201862792 TOLERATED 0.32 -1.39/decreased -0.025 Neutral 10,69647233,1,T/A Q96EB6 D163E rs761508157 TOLERATED 0.31 -0.06/decreased -1.813 Neutral 10,69644519,1,T/C Q96EB6 S14P rs201230502 TOLERATED 0.27 0.06/increased -0.631 Neutral 10,69647181,1,T/C Q96EB6 L146P rs772106776 TOLERATED 0.26 -1.89/decreased -0.95 Neutral 10,69644589,1,C/T Q96EB6 P37L rs548590752 TOLERATED 0.26 -0.27/decreased 0.112 Neutral 10,69648765,1,A/G Q96EB6 I225V rs559057403 TOLERATED 0.22 -1.10/decreased -0.362 Neutral 10,69648669,1,A/G Q96EB6 M193V rs762526864 TOLERATED 0.22 -0.49/decreased -0.716 Neutral 10,69647253,1,A/G Q96EB6 H170R rs144124002 TOLERATED 0.21 -0.19/decreased -1.457 Neutral 10,69644799,1,T/C Q96EB6 L107P rs587776957 TOLERATED 0.21 -1.31/decreased -1.226 Neutral 10,69647175,1,A/G Q96EB6 D144G rs142378619 TOLERATED 0.2 -0.61/decreased 1.231 Neutral 10,69647219,1,T/C Q96EB6 S159P rs200660028 TOLERATED 0.2 -0.40/decreased -1.69 Neutral 10,69647276,1,C/G Q96EB6 P178A rs752035789 TOLERATED 0.17 E -2.017 Neutral 10,69648861,1,A/G Q96EB6 I257V rs765326045 TOLERATED 0.14 -0.79/decreased -0.642 Neutral 10,69648670,1,T/C Q96EB6 M193T rs200994303 TOLERATED 0.12 -0.81/decreased -1.398 Neutral 10,69648666,1,C/G Q96EB6 L192V rs772852024 TOLERATED 0.11 -1.28/decreased -0.843 Neutral 10,69647289,1,T/G Q96EB6 I182R rs749341245 TOLERATED 0.09 -1.63/decreased -0.979 Neutral 10,69644622,1,C/T Q96EB6 P48L rs568432780 TOLERATED 0.08 -0.20/decreased -0.384 Neutral 10,69648819,1,A/G Q96EB6 I243V rs200711525 TOLERATED 0.06 -1.08/decreased -0.89 Neutral 10,69644886,1,C/G Q96EB6 A136G rs775978922 DAMAGING 0.05 -1.07/decreased -0.329 Neutral 10,69648718,1,C/G Q96EB6 T209R rs756483371 DAMAGING 0.05 -0.16/decreased -2.574 Deleterious 10,69648745,1,T/C Q96EB6 M218T rs201583175 DAMAGING 0.04 -0.70/decreased -1.991 Neutral 10,69647279,1,A/G Q96EB6 R179G rs200805107 DAMAGING 0.04 -1.66/decreased -1.894 Neutral 10,69647220,1,C/A Q96EB6 S159Y rs760482544 DAMAGING 0.04 -0.23/decreased -2.272 Neutral 10,69647264,1,A/C Q96EB6 S174R rs758805613 DAMAGING 0.04 -0.27/decreased -2.166 Neutral 10,69651254,1,C/G Q96EB6 A295G rs368002483 DAMAGING 0.01 -1.33/decreased -3.508 Deleterious 10,69647193,1,A/T Q96EB6 D150V rs776925394 DAMAGING 0.01 -0.13/decreased -2.979 Deleterious 10,69651200,1,A/G Q96EB6 D277G rs776933716 DAMAGING 0.01 -1.50/decreased -4.86 Deleterious 10,69651236,1,A/G Q96EB6 D289G rs375090685 DAMAGING 0.01 -0.90/decreased -5.977 Deleterious 10,69644516,1,G/T Q96EB6 G13C rs200005116 DAMAGING *Warning! Low confidence. 0.01 -0.64/decreased -0.496 Neutral 10,69648820,1,T/C Q96EB6 I243T rs776084517 DAMAGING 0.01 -1.91/decreased -2.831 Deleterious 10,69648712,1,C/T Q96EB6 P207L rs375988661 DAMAGING 0.01 -0.48/decreased -6.177 Deleterious 10,69648786,1,C/A Q96EB6 P232T rs750787952 DAMAGING 0.01 -0.98/decreased -4.805 Deleterious 10,69648748,1,C/G Q96EB6 T219R rs199716245 DAMAGING 0.01 -0.24/decreased -4.312 Deleterious 10,69651253,1,G/A Q96EB6 A295T rs751811485 DAMAGING 0 -0.81/decreased -3.491 Deleterious 10,69648827,1,T/A Q96EB6 D245E rs201479376 DAMAGING 0 -0.28/decreased -3.358 Deleterious 10,69648825,1,G/C Q96EB6 D245H rs761327480 DAMAGING 0 -0.41/decreased -5.393 Deleterious 10,69644488,1,C/A Q96EB6 D3E rs35671182 DAMAGING *Warning! Low confidence. 0 0.59/increase -0.464 Neutral 10,69648760,1,T/G Q96EB6 I223S rs769519031 DAMAGING 0 -2.25/decreased -4.47 Deleterious 10,69648811,1,T/C Q96EB6 I240T rs199618656 DAMAGING 0 -1.77/decreased -3.43 Deleterious 10,69648867,1,C/G Q96EB6 L259V rs750671807 DAMAGING 0 -1.35/decreased -2.769 Deleterious 10,69651218,1,T/G Q96EB6 L283R rs773632625 DAMAGING 0 -2/decreased -5.537 Deleterious 10,69651215,1,G/A Q96EB6 R282H rs762393274 DAMAGING 0 -1.60/decreased -4.481 Deleterious 10,69651193,1,T/A Q96EB6 S275T rs779685735 DAMAGING 0 -0.67/decreased -2.769 Deleterious 10,69651285,1,T/G NP_001135970 D10E rs780983084 DAMAGING 0.01 -0.52/decreased -3.322 Deleterious 10,69651266,1,T/C NP_001135970 I4T rs199983221 DAMAGING 0 -2.2/decreased -4.39 Deleterious 10,69651258,1,G/T NP_001135970 M1I rs753708973 DAMAGING 0 -0.17/decreased -3.705 Deleterious 10,69651292,1,C/G NP_001135970 P13A rs200902165 DAMAGING 0 -1.26/decreased -7.539 Deleterious 10,69672378,1,G/A B0QZ35 C199Y rs150099719 TOLERATED 1 -0.64/decreased -1.163 Neutral 10,69676275,1,T/A B0QZ35 D420E rs775109357 TOLERATED 1 -0.31/decreased -0.41 Neutral 10,69676297,1,A/G B0QZ35 I428V rs35224060 TOLERATED 1 0.33/increased 0.108 Neutral 10,69669103,1,C/G B0QZ35 Q118E rs746762337 TOLERATED 1 -1.24/decreased 0.07 Neutral 10,69666602,1,C/T B0QZ35 S30L s200610338 TOLERATED 1 E 3.993 Neutral 10,69667859,1,G/A B0QZ35 V80I rs750895479 TOLERATED 1 0.37/increased 0.385 Neutral 10,69672512,1,C/T B0QZ35 P244S rs201723648 TOLERATED 0.94 E 0.648 Neutral 10,69672620,1,C/A B0QZ35 Q280K rs769257926 TOLERATED 0.92 -0.94/decreased -0.787 Neutral 10,69672599,1,G/A B0QZ35 E273K rs779678154 TOLERATED 0.85 -1.3/decreased -1.264 Neutral 10,69669016,1,G/A B0QZ35 V89I rs201152568 TOLERATED 0.85 -0.27/decreased 0.201 Neutral 10,69672597,1,T/C B0QZ35 M272T rs757828571 TOLERATED 0.81 -0.33//decreased -0.187 Neutral 10,69676028,1,A/G B0QZ35 Q338R rs766102594 TOLERATED 0.81 -1.7/decreased -1.453 Neutral 10,69672692,1,A/G B0QZ35 T304A rs779413432 TOLERATED 0.8 -0.83/decreased -0.746 Neutral 10,69672720,1,T/C B0QZ35 V313A rs781614748 TOLERATED 0.76 -1.24/decreased -0.056 Neutral 10,69672590,1,G/A B0QZ35 G270S rs144625497 TOLERATED 0.73 -0.58/decreased 0.377 Neutral 10,69676289,1,A/G B0QZ35 N425S rs761406151 TOLERATED 0.72 -0.12/decreased -0.158 Neutral 10,69672755,1,G/C B0QZ35 V325L rs567829185 TOLERATED 0.71 -0.86/decreased -0.246 Neutral 10,69672683,1,G/A B0QZ35 G301S rs200296961 TOLERATED 0.67 -0.77/decreased 0.011 Neutral 10,69672680,1,G/C B0QZ35 V300L rs750092788 TOLERATED 0.62 -0.18/decreased -0.652 Neutral 10,69672383,1,C/A B0QZ35 P201T rs116499760 TOLERATED 0.59 -0.28/decreased -0.581 Neutral 10,69672605,1,A/C B0QZ35 K275Q rs747447296 TOLERATED 0.58 -0.69/decreased -1.15 Neutral 10,69672684,1,G/A B0QZ35 G301D rs533321736 TOLERATED 0.57 -0.55/decreased 0.908 Neutral 10,69672243,1,A/G B0QZ35 H154R rs146837595 TOLERATED 0.57 -0.17/decreased -1.947 Neutral 10,69672479,1,G/A B0QZ35 E233K rs116040871 TOLERATED 0.54 -1.18/decreased -0.433 Neutral 10,69672675,1,A/G B0QZ35 K298R rs765178020 TOLERATED 0.52 -0.11/decreased -0.612 Neutral 10,69672597,1,T/A B0QZ35 M272K rs757828571 TOLERATED 0.52 -0.31/decreased -1.385 Neutral 10,69672539,1,T/G B0QZ35 L253V rs377735046 TOLERATED 0.51 -0.27/decreased 0.246 Neutral 10,69672495,1,C/G B0QZ35 P238R rs768902657 TOLERATED 0.51 0 -2.575 Deleterious 10,69672426,1,A/G B0QZ35 Q215R rs201058854 TOLERATED 0.49 -1.37/decreased -1.134 Neutral 10,69672630,1,G/C B0QZ35 R283T rs773365044 TOLERATED 0.49 -0.44/decreased 0.351 Neutral 10,69676289,1,A/C B0QZ35 N425T rs761406151 TOLERATED 0.48 -0.03/decreased -0.034 Neutral 10,69672438,1,C/T B0QZ35 A219V rs61754500 TOLERATED 0.44 -0.82/decreased -0.93 Neutral 10,69672644,1,A/G B0QZ35 I288V rs370128548 TOLERATED 0.42 -0.19/decreased 0.248 Neutral 10,69669104,1,A/G B0QZ35 Q118R rs371326132 TOLERATED 0.42 -1.07/decreased -1.537 Neutral 10,69672357,1,G/A B0QZ35 G192D rs369274325 TOLERATED 0.41 -0.2/decreased -2.13 Neutral 10,69672380,1,A/G B0QZ35 N200D rs201090108 TOLERATED 0.41 -0.01/decreased -1.016 Neutral 10,69672657,1,T/C B0QZ35 M292T rs139635382 TOLERATED 0.39 0.26/increased -0.466 Neutral 10,69676240,1,G/A B0QZ35 A409T rs114182972 TOLERATED 0.38 -0.23/decreased -0.877 Neutral 10,69672593,1,T/G B0QZ35 C271G rs745527350 TOLERATED 0.38 -2.81/decreased -1.457 Neutral 10,69672335,1,G/C B0QZ35 E185Q rs771126114 TOLERATED 0.38 -0.9/decreased -0.676 Neutral 10,69676099,1,G/A B0QZ35 V362I rs201730062 TOLERATED 0.38 -0.66/decreased -0.29 Neutral 10,69676168,1,C/T B0QZ35 P385S rs757740493 TOLERATED 0.37 -0.82/decreased -0.649 Neutral 10,69672564,1,A/G B0QZ35 D261G s756116247 TOLERATED 0.36 E -0.904 Neutral 10,69672567,1,A/G B0QZ35 D262G rs763773932 TOLERATED 0.36 E -1.552 Neutral 10,69669136,1,G/A B0QZ35 E129K rs763496433 TOLERATED 0.35 -0.86/decreased -1.352 Neutral 10,69672456,1,C/T B0QZ35 P225L rs770755510 TOLERATED 0.35 0.36/increased -1.813 Neutral 10,69667871,1,A/G B0QZ35 I84V rs17855431 TOLERATED 0.34 -0.28/decreased -0.432 Neutral 10,69672377,1,T/C B0QZ35 C199R rs202116390 TOLERATED 0.33 -0.43/decreased -3.055 Deleterious 10,69672632,1,A/G B0QZ35 N284D rs763220339 TOLERATED 0.33 -1.22/decreased -0.461 Neutral 10,69667878,1,A/G B0QZ35 N86S rs17855432 TOLERATED 0.33 -0.7/decreased -0.927 Neutral 10,69667859,1,G/C B0QZ35 V80L rs750895479 TOLERATED 0.33 0.19/increased -0.68 Neutral 10,69672552,1,C/G B0QZ35 A257G rs762955289 TOLERATED 0.32 -3/decreased -0.793 Neutral 10,69676118,1,G/C B0QZ35 C368S rs114575266 TOLERATED 0.32 -0.76/decreased -2.036 Neutral 10,69676243,1,G/C B0QZ35 G410R rs771866041 TOLERATED 0.32 -0.14/decreased -0.936 Neutral 10,69672621,1,A/C B0QZ35 Q280P rs201096600 TOLERATED 0.32 -0.63/decreased -1.255 Neutral 10,69672456,1,C/A B0QZ35 P225Q rs770755510 TOLERATED 0.31 E -1.222 Neutral 10,69676231,1,C/A B0QZ35 P406T rs770824011 TOLERATED 0.31 -0.66/decreased -1.383 Neutral 10,69672684,1,G/T B0QZ35 G301V rs533321736 TOLERATED 0.3 -0.13/decreased -0.94 Neutral 10,69676190,1,T/C B0QZ35 I392T rs140030776 TOLERATED 0.3 -0.26/decreased -0.248 Neutral 10,69672490,1,T/G B0QZ35 S236R rs192990424 TOLERATED 0.3 -0.99/decreased -1.914 Neutral 10,69672629,1,A/G B0QZ35 R283G rs202044007 TOLERATED 0.29 -1.1/decreased -1.032 Neutral 10,69669023,1,G/A B0QZ35 R91Q rs766737138 TOLERATED 0.29 -0.85/decreased -1.062 Neutral 10,69676297,1,A/C B0QZ35 I428L rs35224060 TOLERATED 0.28 0.72/increased -0.316 Neutral 10,69672622,1,A/C B0QZ35 Q280H rs777147954 TOLERATED 0.28 -1.18/decreased -1.047 Neutral 10,69669058,1,A/G B0QZ35 I103V rs757140711 TOLERATED 0.27 -0.32/decreased -0.427 Neutral 10,69667830,1,T/G B0QZ35 I70S rs763566753 TOLERATED 0.27 E 0.432 Neutral 10,69672662,1,A/G B0QZ35 N294D rs753828684 TOLERATED 0.27 -0.4/decreased -0.577 Neutral 10,69676282,1,G/T B0QZ35 A423S rs776051187 TOLERATED 0.26 -0.93/decreased -0.122 Neutral 10,69672488,1,A/G B0QZ35 S236G rs199497583 TOLERATED 0.26 -2.12/decreased -1.407 Neutral 10,69672369,1,A/G B0QZ35 K196R rs549636735 TOLERATED 0.25 -0.15/decreased -0.838 Neutral 10,69672430,1,A/T B0QZ35 K216N rs200415719 TOLERATED 0.25 -0.97/decreased -0.117 Neutral 10,69676231,1,C/T B0QZ35 P406S rs770824011 TOLERATED 0.25 -0.84/decreased -1.273 Neutral 10,69672504,1,C/G B0QZ35 T241S rs777098039 TOLERATED 0.25 -0.74/decreased -0.77 Neutral 10,69676286,1,T/C B0QZ35 I424T rs202021325 TOLERATED 0.23 E -0.394 Neutral 10,69676298,1,T/C B0QZ35 I428T rs758781892 TOLERATED 0.23 0.03/increased -0.426 Neutral 10,69676169,1,C/A B0QZ35 P385H rs765609303 TOLERATED 0.23 -0.92/decreased -1.139 Neutral 10,69666569,1,A/G B0QZ35 Q19R rs532201569 TOLERATED 0.22 -0.1/decreased -1.062 Neutral 10,69676276,1,C/G B0QZ35 Q421E rs201854199 TOLERATED 0.22 -0.33/decreased -0.47 Neutral 10,69676238,1,G/C B0QZ35 R408T rs774376548 TOLERATED 0.22 -0.42/decreased -0.622 Neutral 10,69676156,1,A/G B0QZ35 S381G rs114572830 TOLERATED 0.22 -1.11/decreased -1.35 Neutral 10,69672755,1,G/A B0QZ35 V325M rs567829185 TOLERATED 0.21 -1.01/decreased -0.598 Neutral 10,69669028,1,C/T B0QZ35 P93S rs752020872 TOLERATED 0.2 -1.86/decreased -5.682 Deleterious 10,69666581,1,G/C B0QZ35 C23S rs200987359 TOLERATED 0.19 -1.24/decreased -6.059 Deleterious 10,69672453,1,T/G B0QZ35 L224W rs748917510 TOLERATED 0.19 0.09/increased -1.771 Neutral 10,69676205,1,A/G B0QZ35 N397S rs116459300 TOLERATED 0.19 -0.44//decreased -1.479 Neutral 10,69672369,1,A/C B0QZ35 K196T rs549636735 TOLERATED 0.18 -0.26/decreased -2.109 Neutral 10,69676340,1,A/G B0QZ35 N442S rs756220511 TOLERATED 0.18 -1.64/decreased -0.75 Neutral 10,69676075,1,G/T B0QZ35 V354L rs199502996 TOLERATED 0.18 -0.53/decreased -1.596 Neutral 10,69667850,1,T/G B0QZ35 C77G rs779440453 TOLERATED 0.17 -2.97/decreased -3.709 Deleterious 10,69669041,1,C/G B0QZ35 A97G rs755416990 TOLERATED 0.16 -2.16/decreased -0.743 Neutral 10,69669041,1,C/T B0QZ35 A97V rs755416990 TOLERATED 0.16 E -0.179 Neutral 10,69676087,1,T/C B0QZ35 S358P rs754313614 TOLERATED 0.15 0.18/increased -0.896 Neutral 10,69669139,1,G/A B0QZ35 V130I rs745364339 TOLERATED 0.15 -0.14/decreased -0.482 Neutral 10,69676075,1,G/A B0QZ35 V354I rs199502996 TOLERATED 0.15 -0.27/decreased -0.369 Neutral 10,69676303,1,G/A B0QZ35 V430M rs766908589 TOLERATED 0.15 0.45/increased -0.04 Neutral 10,69676169,1,C/G B0QZ35 P385R rs765609303 TOLERATED 0.14 -0.37/decreased -1.564 Neutral 10,69666562,1,C/G B0QZ35 Q17E rs772390347 TOLERATED 0.14 -1.38/decreased -1.579 Neutral 10,69672655,1,G/C B0QZ35 Q291H rs759555466 TOLERATED 0.14 -1.17/decreased -1.134 Neutral 10,69669105,1,G/C B0QZ35 Q118H rs776212608 TOLERATED 0.13 -1.92/decreased -1.877 Neutral 10,69672447,1,C/T B0QZ35 S222L rs199649997 TOLERATED 0.13 -0.25/decreased -1.509 Neutral 10,69667865,1,G/A B0QZ35 G82R rs758727461 TOLERATED 0.12 -0.26/decreased -0.355 Neutral 10,69669131,1,A/G B0QZ35 K127R rs772640272 TOLERATED 0.12 -1.33/decreased -2.53 Deleterious 10,69666607,1,A/G B0QZ35 K32E rs751410492 TOLERATED 0.12 0.31/increased -1.657 Neutral 10,69669097,1,C/T B0QZ35 P116S rs775426483 TOLERATED 0.12 -1.84/decreased -6.457 Deleterious 10,69672627,1,C/G B0QZ35 S282C rs748473217 TOLERATED 0.11 -0.44/decreased -1.282 Neutral 10,69672524,1,G/A B0QZ35 V248M rs758444346 TOLERATED 0.11 -0.69/decreased -0.538 Neutral 10,69669050,1,C/A B0QZ35 P100Q rs748394475 TOLERATED 0.1 -0.85/decreased -1.547 Neutral 10,69672276,1,C/G B0QZ35 P165R rs777705431 TOLERATED 0.1 -0.76/decreased -5.303 Deleterious 10,69669139,1,G/C B0QZ35 V130L rs745364339 TOLERATED 0.1 -0.48/decreased -1.206 Neutral 10,69666595,1,G/A B0QZ35 A28T rs201340003 TOLERATED 0.09 -1.02/decreased -1.057 Neutral 10,69676223,1,C/G B0QZ35 P403R rs749218988 TOLERATED 0.08 -0.77/decreased -0.966 Neutral 10,69672519,1,C/G B0QZ35 S246C rs373331174 TOLERATED 0.08 -1.16/decreased -0.839 Neutral 10,69676033,1,C/G B0QZ35 L340V rs751212678 TOLERATED 0.07 -0.67/decreased -0.868 Neutral 10,69676204,1,A/C B0QZ35 N397H rs747251569 TOLERATED 0.07 -0.59/decreased -1.742 Neutral 10,69669029,1,C/T B0QZ35 P93L rs757269120 TOLERATED 0.07 -1.34/decreased -7.329 Deleterious 10,69672780,1,G/A B0QZ35 R333Q rs771135356 TOLERATED 0.07 -1.35/decreased -2.059 Neutral 10,69669115,1,G/A B0QZ35 A122T rs200690371 TOLERATED 0.06 -0.03/decreased -1.862 Neutral 10,69667848,1,A/C B0QZ35 D76A rs756786753 TOLERATED 0.06 -0.91/decreased -3.303 Deleterious 10,69676215,1,A/C B0QZ35 E400D rs201327262 TOLERATED 0.06 -1.36/decreased -0.816 Neutral 10,69676215,1,A/T B0QZ35 E400D rs201327262 TOLERATED 0.06 -1.36/decreased -0.816 Neutral 10,69672530,1,G/T B0QZ35 V250F rs773456695 TOLERATED 0.06 -0.26/decreased -0.799 Neutral 10,69667869,1,A/C B0QZ35 D83A rs17855430:C DAMAGING 0.05 -1.35/decreased -5.798 Deleterious 10,69672285,1,A/G B0QZ35 H168R rs779026786 DAMAGING 0.05 -1.31/decreased -7.23 Deleterious 10,69672324,1,T/A B0QZ35 V181D rs1063111 DAMAGING 0.05 -1.59/decreased -6.395 Deleterious 10,69666665,1,C/T B0QZ35 A51V rs141528984 DAMAGING 0.04 0.69/increased -3.419 Deleterious 10,69676219,1,G/A B0QZ35 E402K rs778261267 DAMAGING *Warning! Low confidence. 0.04 -0.42/decreased -1.024 Neutral 10,69672282,1,C/T B0QZ35 P167L rs201948258 DAMAGING 0.04 -0.72/decreased -5.575 Deleterious 10,69666675,1,A/C B0QZ35 Q54H s116374368 DAMAGING 0.04 -1.4/decreased -2.377 Neutral 10,69666675,1,A/T B0QZ35 Q54H rs116374368 DAMAGING 0.04 -1.4/decreased -2.377 Neutral 10,69672374,1,T/C B0QZ35 C198R rs772656917 DAMAGING 0.03 -1.56/decreased -8.169 Deleterious 10,69676279,1,G/A B0QZ35 E422K rs201112743 DAMAGING *Warning! Low confidence. 0.03 -0.95/decreased -0.509 Neutral 10,69672290,1,C/T B0QZ35 H170Y rs751498023 DAMAGING 0.03 0.1/decreased -2.752 Deleterious 10,69667835,1,A/G B0QZ35 K72E rs753398498 DAMAGING 0.03 -0.42/decreased -2.77 Deleterious 10,69676156,1,A/C B0QZ35 S381R rs114572830 DAMAGING *Warning! Low confidence. 0.03 -0.49/decreased -1.398 Neutral 10,69669116,1,C/G B0QZ35 A122G rs201635394 DAMAGING 0.02 -1.07/decreased -2.995 Deleterious 10,69667871,1,A/C B0QZ35 I84L rs17855431 DAMAGING 0.02 -0.09/decreased -1.848 Neutral 10,69669050,1,C/T B0QZ35 P100L rs748394475 DAMAGING 0.02 -0.33/decreased -3.331 Deleterious 10,69676105,1,T/G B0QZ35 S364A rs772469360 DAMAGING 0.02 -1.07/decreased -1.339 Neutral 10,69676123,1,A/G B0QZ35 S370G rs377449611 DAMAGING 0.02 -1.98/decreased -2.004 Neutral 10,69676129,1,A/G B0QZ35 S372G rs759347614 DAMAGING 0.02 E -2.414 Neutral 10,69672405,1,C/T B0QZ35 T208I rs750553699 DAMAGING 0.02 1.34/increased -3.254 Deleterious 10,69669115,1,G/C B0QZ35 A122P rs200690371 DAMAGING 0.01 -0.12/decreased -3.21 Deleterious 10,69666664,1,G/T B0QZ35 A51S rs777323664 DAMAGING 0.01 -0.35/decreased -2.737 Deleterious 10,69667850,1,T/C B0QZ35 C77R rs779440453 DAMAGING 0.01 -1.55/decreased -4.545 Deleterious 10,69676085,1,A/C B0QZ35 D357A rs778184510 DAMAGING 0.01 -2.58/decreased -4.873 Deleterious 10,69676217,1,A/C B0QZ35 D401A rs151026272 DAMAGING *Warning! Low confidence. 0.01 -0.19/decreased -1.941 Neutral 10,69667869,1,A/G B0QZ35 D83G rs17855430 DAMAGING 0.01 -2.13/decreased -5.487 Deleterious 10,69669090,1,A/C B0QZ35 E113D rs771950281 DAMAGING 0.01 -0.78/decreased -2.83 Deleterious 10,69669073,1,A/G B0QZ35 I108V rs149206117 DAMAGING 0.01 -0.86/decreased -0.932 Neutral 10,69666592,1,A/G B0QZ35 I27V rs552023236 DAMAGING 0.01 -0.06/decreased -0.823 Neutral 10,69672761,1,A/G B0QZ35 K327E rs199770148 DAMAGING 0.01 -0.33/decreased -2.073 Neutral 10,69669148,1,C/T B0QZ35 L133F rs755327185 DAMAGING 0.01 0.05/increased -3.628 Deleterious 10,69672308,1,C/T B0QZ35 L176F rs754951946 DAMAGING 0.01 0.36/increased -3.79 Deleterious 10,69676160,1,T/C B0QZ35 L382S rs754362414 DAMAGING *Warning! Low confidence. 0.01 E -2.203 Neutral 10,69676172,1,T/G B0QZ35 M386R rs750707792 DAMAGING *Warning! Low confidence. 0.01 -0.04/decreased -1.467 Neutral 10,69676205,1,A/T B0QZ35 N397I rs116459300 DAMAGING *Warning! Low confidence. 0.01 0.29/increased -2.884 Deleterious 10,69669097,1,C/A B0QZ35 P116T rs775426483 DAMAGING 0.01 -1.89/decreased -6.707 Deleterious 10,69672239,1,C/G B0QZ35 P153A rs201348222 DAMAGING 0.01 -1.64/decreased -7.352 Deleterious 10,69672239,1,C/A B0QZ35 P153T rs201348222 DAMAGING 0.01 -1.39/decreased -7.319 Deleterious 10,69672270,1,G/A B0QZ35 R163K rs764179598 DAMAGING 0.01 -0.45/decreased -2.743 Deleterious 10,69676088,1,C/T B0QZ35 S358F rs757624637 DAMAGING 0.01 0.21/increased -3.193 Deleterious 10,69676105,1,T/C B0QZ35 S364P rs772469360 DAMAGING 0.01 -0.48/decreased -1.779 Neutral 10,69676115,1,C/T B0QZ35 S367F rs768864413 DAMAGING 0.01 -0.32/decreased -2.558 Deleterious 10,69676115,1,C/A B0QZ35 S367Y rs768864413 DAMAGING 0.01 -0.47/decreased -2.064 Neutral 10,69676129,1,A/T B0QZ35 S372C rs759347614 DAMAGING 0.01 -0.82/decreased -2.959 Deleterious 10,69666661,1,G/C B0QZ35 V50L rs200058231 DAMAGING 0.01 -0.01/decreased -2.384 Neutral 10,69672320,1,G/A B0QZ35 D180N rs145326137 DAMAGING 0 -0.7/decreased -4.738 Deleterious 10,69666668,1,G/A B0QZ35 G52E rs757804740 DAMAGING 0 -1.9/decreased -6.479 Deleterious 10,69669152,1,T/C B0QZ35 I134T rs768051584 DAMAGING 0 -0.23/decreased -4.51 Deleterious 10,69672238,1,A/G B0QZ35 I152M rs200021101 DAMAGING 0 -1.03/decreased -2.226 Neutral 10,69672258,1,T/A B0QZ35 I159K rs140677498 DAMAGING 0 -0.37/decreased -6.333 Deleterious 10,69672327,1,T/C B0QZ35 I182T rs1063112 DAMAGING 0 -0.4/decreased -4.671 Deleterious 10,69669173,1,A/G B0QZ35 K141R rs756329197 DAMAGING 0 -1.54/decreased -2.846 Deleterious 10,69669145,1,C/T B0QZ35 L132F rs199593180 DAMAGING 0 0.67/increased -3.795 Deleterious 10,69669146,1,T/A B0QZ35 L132H rs766945174 DAMAGING 0 -0.73/decreased -6.641 Deleterious 10,69669145,1,C/G B0QZ35 L132V rs199593180 DAMAGING 0 0.23/increased -2.846 Deleterious 10,69672262,1,A/T B0QZ35 L160F rs761122062 DAMAGING 0 -1.43/decreased -3.79 Deleterious 10,69666629,1,A/C B0QZ35 N39T rs767148239 DAMAGING 0 -0.32/decreased -5.535 Deleterious 10,69669196,1,C/T B0QZ35 P149S rs267602551 DAMAGING 0 -0.6/decreased -7.579 Deleterious 10,69672417,1,C/T B0QZ35 P212L rs201863201 DAMAGING 0 E -3.214 Deleterious 10,69672779,1,C/T B0QZ35 R333W rs201647881 DAMAGING 0 -0.75/decreased -4.292 Deleterious 10,69666625,1,C/T B0QZ35 R38C rs201583982 DAMAGING 0 -0.52/decreased -7.38 Deleterious 10,69666626,1,G/A B0QZ35 R38H rs147909071 DAMAGING 0 -0.72/decreased -4.613 Deleterious 10,69669164,1,C/T B0QZ35 S138F rs752958196 DAMAGING 0 -1.61/decreased -5.693 Deleterious 10,69676106,1,C/T B0QZ35 S364F rs780449017 DAMAGING 0 -0.1/decreased -2.214 Neutral 10,69666661,1,G/T B0QZ35 V50F rs200058231 DAMAGING 0 0.23/increased -4.016 Deleterious Identification of damaging nsSNPs The following bioinformatics tools have provided the supplied data to further detect the influence of 252 nsSNPs on the structure and function of the SIRT1 gene. Because the resulting values were lower than the Tolerance Index (0.05), the SIFT software revealed 94 nsSNPs to be intolerant ( Table 1 ). Protein stability changed depending on which amino acid was substituted and 216 nsSNPs demonstrated a decline in stability based on DDG value received from I-Mutant server ( Table 1 ). PROVEAN identified 77 nsSNPs as having a negative impact since the final score of the variations was lower than the specified value of threshold (-2.5). In the SIRT1 gene, three isoforms were identified, resulting in a total of 252 identified Single Nucleotide Polymorphisms (SNPs). Among them, SIFT software identified 94 non-synonymous SNPs (nsSNPs) as intolerant (using a cutoff value of <0.05). Subsequently, these 94 intolerant nsSNPs underwent Provean analysis, revealing 67 nsSNPs as harmful (with a cutoff value of <-2.5). The selected 67 nsSNPs then underwent I-Mutant analysis, which indicated 58 nsSNPs with decreased stability (using a cutoff value of 0). From this subset, we selected three nsSNPs from each isoform, rs778184510, rs769519031, rs199983221respectively, based on decreasing protein stability. Structural and functional effect of nsSNPs I-Mutant predicted the three (3) nsSNPs which played a role in decreasing SIRT1 stability (from each isoform - rs778184510, rs769519031, rs199983221), and they were selected for finding the impact of substitution of amino acid on structure and function of human protein (using Polyphen) and for the comparison of protein model (using I-Tasser). To generate the SIRT1 protein structure, SIRT1 protein sequences, single amino acid from the wild type, and mutations were uploaded to I-Tasser, which is one of the most accurate and sophisticated technique for predicting protein structure ( Figure 2 ). Then, using this technique, five models for each SIRT1 mutation and protein were produced. Figure 2. Predicted protein structure models by I Tasser of SIRT1 Gene for each SNPs rs778184510, rs769519031, rs199983221 respectively. When the native structure is known, TM score and RMSD can be used to compare the structural similarity of two structures. 26 The proposed TM score is supposed to solve the RMSD issue, which is prone to local errors. A local error (such as a mismatched tail) will raise the RMSD score even if the overall topology is good, since the RMSD measures the average distance between all residue pairs between two structures. The TM-score is insensitive to the local modelling error, nevertheless, because the short distance is weighted more severely than the long distance. A model with a proper topology is indicated by a TM-score and IT greater than 0.5, while a random similarity is indicated by a TM-score & IT less than 0.17 ( Table 2 ). These cut-offs are independent of the length of the protein. Table 2. Results of Polyphen and I-Tasser analyses of three nsSNPs. Protein ID Residual change Polyphen I-Tasser Score Sensitivity specificity TM Score RMSD values C Score rs778184510 D357A 0.983/Damaging 0.74 0.96 0.29±0.09 17.0±2.8Ǻ -3.92 rs769519031 I223S 0.997/Damaging 0.27 0.98 0.42±0.14 14.6±3.7Ǻ -2.55 rs199983221 I4T 1.00/Damaging 0.00 1.00 0.48±0.15 11.7±4.5Ǻ 1.93 By calculating a confidence score, or C-score, I-Tasser evaluates the accuracy of anticipated models. The convergence parameters from simulations of the structure assembly and the significance of threading template alignments are used to make this determination. A model with a high level of confidence also has a higher C-score. The C-score typically ranges from (-5,2). HOPE modelling for rs199983221 Isoleucine turned into threonine in position 4. The mutant residue was more compact than the wild-type residue. The mutant residue was also less hydrophobic than the wild-type residue. The mutation caused the hydrophobic contacts in the protein's core to disappear. An overview of the protein is also displayed in the ribbon presentation ( Figure 3a ). Additionally, there are five detailed pictures of the mutation site ( Figure 3b ). Figure 3a. Overview of the protein in ribbon presentation (I4T). Figure 3b. Close-up of the mutation. The protein is coloured grey, the side chains of both the wild-type and the mutant residue are shown and coloured green and red respectively. (I4T). HOPE modelling of rs769519031 In this case, isoleucine turns into serine at position 223. The mutant residue was more compact than the wild-type residue. The mutant residue was less hydrophobic than the wild-type residue. This could lead to a lack of interactions with the other genes The mutation may cause the proteins' surface-bound hydrophobic interactions with other molecules to disappear. 19 An overview of the protein is also displayed in the ribbon presentation ( Figure 4a ). There are also five enlargements of the mutation location ( Figure 4b ). Figure 4a. Overview of the protein in ribbon presentation (I223S). Figure 4b. Close-up of the mutation. The protein is coloured grey, the side chains of both the wild-type and the mutant residue are shown and coloured green and red respectively (I223S). HOPE modelling of rs778184510 The mutant residue was smaller than the wild-type residue in this instance because alanine has replaced aspartic acid at position 357. In contrast to the wild-type residue charge, which was negative, the mutant residue charge was neutral. The mutant residue was more hydrophobic than the wild-type residue. The wild-type residue is expected to be located in its preferred secondary structure turn, according to the Reprof programme. The local conformation would only be slightly unstable since the mutant residue prefers a different secondary structure. The mutation places a more hydrophobic residue here. Hydrogen bonds may break as a result of this, and it may also prevent correct folding. Gene interactions STRING revealed the physical interactions between SIRT1 and other genes in the gene's interactions. In its pathways, it interacted with NFKB1, NFKB1A, DDX5, AURKA, BARD1, RPA1, UBEBA, ARNTL,CLOCK,CRY1, PPARGC1A, FOXO1, FOXO3, RELA, MYOD1, SUV39H1, MDM2, EP300, PPARG and TP53 ( Figure 5 ). The query proteins and the initial line of SIRT1's interaction are represented by coloured nodes on the picture. White nodes are the second interactional shell. Protein-protein interactions are represented by edges. The edges of the known interactions are blue and pink. Others illustrate the predicted interplay between proteins. In evidence mode, an edge may be drawn with up to 7 differently colored lines - these lines represent the existence of the seven types of evidence used in predicting the associations. Red lines indicate the presence of fusion evidence, green lines represent neighbourhood evidence, blue lines suggest cooccurrence evidence, purple lines correspond to experimental evidence, yellow lines denote text mining evidence, light blue lines signify database evidence, and black lines represent co-expression evidence. TP53 is more connected to and interdependent with SIRT1 than any other interaction on the list. Figure 5. Gene interactions of SIRT1. Numerous studies have been done in the past to determine the connection between the SIRT1 gene's polymorphism and a number of conditions, such as cancer, inflammation, obesity, diabetes, and cardiovascular and neurological illnesses. The most harmful nsSNPs in the SIRT1 gene that may be crucial in the development of certain disorders have been explored in this work. The SIRT1 gene has 252 nsSNPs, according to our findings. The present study's SIFT findings revealed that the SIRT1 protein contains 94 harmful nsSNPs, 66 of which are detrimental as indicated by PROVEAN. Provean scores were -4.873, -4.47, -4.39 for rs778184510, rs769519031 and rs199983221 respectively which were higher compared to other SNP’s and were chosen from each isoform of SIRT1 protein. These three nsSNPs, which cause high risk of altering normal functioning of SIRT1 gene, were selected for further evaluation based on the I-Mutant value, from each isoform of the SIRT1 protein. D357A, I223S, and I4T’s respective Polyphen2 scores, which range from 0 to 1, were 0.983, 0.997, and 1.00, respectively; all three were classified as having probable damage by Polyphen2. Protein structure and functional activity depend on protein stability. 27 Thus, I-Mutant, which was used to assess the stability of protein, demonstrated the protein stability for D357A, I223S, and I4T as -2.58, -2.25 and -2.2, respectively, as the lowest values. Thus, these three SNPs affect the function and structure of SIRT1 protein. By determining the RMSD values and TM scores for each mutant model, we expanded our analysis. While RMSD aids in calculating the average distance between the carbon backbones of wild and mutant models, the TM score is utilised to assess the topological similarity between wild- and mutant-type models. 20 , 21 The mutant model D357A demonstrated a greater RMSD value, which had a greater deviation from the wild type compared to the other two mutant models. To further establish the detrimental impacts of these nsSNPs, the SIRT1 protein structure was determined using I-Tasser, and the protein's FASTA sequence served as the sole input. Using I-Tasser, the prototypes are acquired, and the protein simulation is carried out. Following the introduction of the mutant models to the HOPE server, the server generated the effects of mutations on the contacts and the structural placement. Mutations can affect a protein's stability, structure, and ultimately, function. Mutations are components of the "raw material" of evolution. The majority of, if not all, protein mutations are eliminated by negative, purifying selection, which lowers the probability of subsequent adaptations. Because of this, under the influence of positive selection, only a small portion of all potential mutations will be resolved to take on a new function. Randomness or "neutral drift" might theoretically cause neutral mutations to randomly correct in small populations. At the level of the organism, the consequences of mutations on fitness are complicated and seldom ever correlate to the characteristics of a single gene or protein. Several levels of redundancy, resilience, and backup decrease the impact of numerous mutations. Understanding and predicting the impact of mutations at the organismal level present important problems for evolutionary biology. 28 , 29 The stability of the proteins is influenced by the quantity of functional protein present. According to previous research, stability and folding effects are responsible for 80% of the negative consequences of pathogenic mutations. 30 Protein dysfunctionalization is mostly caused by mutations that reduce the amount of soluble, functional proteins over a specified threshold (or DDG value). 30 Experimental studies on a variety of proteins indicated that between 33 and 40% of the time, a detrimental mutation is likely to occur. 29 As mutation rates increase, protein fitness therefore substantially decreases. When five mutations are introduced into a protein, its fitness is decreased by 20%. Protein evolution rates, and maybe even the rates at which entire organisms evolve, seem to be primarily (though surely not solely) influenced by stability, 31 , 32 particularly but not entirely in connection with the acquisition of new functionalities. Stability appears to be the primary (though surely not the only) driver of how rapidly proteins change, despite the fact that a protein's starting stability might mitigate some of the destabilising effects of mutations. For a small number of proteins, experimental datasets are frequently made accessible, and they generally focus on changes in mutation thermodynamic stability (DDG values). Recent developments in computing have made it possible for researchers to predict the DDG values of certain protein mutations. Some prediction methods strongly rely on sequence, whereas others mostly rely on three-dimensional structures. 33 , 34 New protein functions cannot be developed because of the destabilising impact of mutations. Neutral or non-adaptive mutational drifts have been found to be less disruptive and to occur frequently at buried residues as compared to new function or adaptive mutations. 35 The mutant study shows the decreased thermodynamic stability of the proteins, regardless of whether SIFT and Provean examinations of SNPs in the leptin and leptin receptor genes suggest that they are detrimental or tolerated. This might have an impact on how leptin and leptin receptor proteins function. This conclusion supports previous studies linking leptin, leptin gene polymorphisms, and the incidence of depression in obese individuals. Despite several studies relating SNPs in different genes to a number of disorders, computational analysis of the functional effects of SNPs in SIRT1 is still lacking. To determine whether an amino acid change will have an impact on protein function, the SIFT technique examines sequence homology across related genes and domains across evolution. The physical-chemical properties of the residues of amino acids are also considered. According to estimates, SIFT has error rates of 31% and 20% for false negatives and positives, respectively. When amino acid changes are used as the test set, SIFT is roughly 80% effective in benchmarking trials and is thought to significantly reduce the residual activity of the variant protein. However, utilizing SIFT and Provean, it is now feasible to analyse gene polymorphisms and forecast how a mutation will alter a protein's functionality. Since most disease mutations have an effect on protein stability, I-Mutant assessed the stability of the mutant proteins. To find, characterize, validate, and predict the functional consequences of harmful non-synonymous SNPs (nsSNPs) in the interleukin-8 gene, Dakal et al. carried out a comparable. 36 It may also be deduced that all three of the SIRT1 gene's most harmful nsSNPs eventually interfere with and disrupt the normal function of other expressive genes. Based on their interaction patterns and their correlation profiles with numerous diseases and their pathways, SIRT1 is involved in pathways with genes such as NFKB1, NFKB1A, DDX5, AURKA, BARD1, RPA1, UBEBA, ARNTL, CLOCK, CRY1, PPARGC1A, FOXO1, FOXO3, RELA, MYOD1, SUV39H1, MDM2, EP300, PPARG and TP53, which, therefore indicate its importance. 37 Conclusions The SIRT1 protein plays a crucial role in various disorders, and its structural confirmation is essential for its proper functioning. Through our in-silico analysis of functional SNPs, we have gained significant insight into the potential detrimental effects of ns-SNPs on SIRT1 protein structure and functionality. Our findings highlight the three ns-SNPs (D357A, I223S, and I4T) could be the most harmful mutations, and these results may serve as a valuable reference point for future research on diagnostic and therapeutic approaches related to SIRT1-associated disorders. Large-scale experimental mutational validation will be necessary to validate these findings and advance our understanding of the role of SIRT1 in disease. Author contributions Desy TM and Usha Adiga designed the research, performed softwares and wrote the manuscript; Tirthal Rai and Sachidananda Adiga, Vijith Shetty revised the manuscript and involved in data analysis. All authors read and approved the fnal manuscript. Data availability Underlying data Biostudies: Identification Of The SIRT1 Gene's Most Harmful Non-Synonymous SNPs And Their Effects On Functional And Structural Features- An Insilico Analysis; Accession number: S-BSST944. https://identifiers.org/biostudies: S-BSST944 This project contains the following underlying data - Table 1: SIFT, I mutant analysis, Provean for the nsSNPs of SIRT1 Gene - Figure 1: Sorting of nsSNPs of SIRT1 Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). References 1. Ashok K, Mona D-G: Sirtuins as NAD+-dependent deacetylases and their potential in medical therapy. Medical Epigenetics. 2nd ed.2021; pp. 633–664. Publisher Full Text 2. Yang T, Fu M, Pestell R, et al. : SIRT1 and endocrine signaling. Trends Endocrinol. Metab. 2006 Jul 1; 17 (5): 186–191. Publisher Full Text 3. Yeon-Hwa L, Su-Jung K, Young-Joon S: Role of Post-translational Modification of Silent Mating Type Information Regulator 2 Homolog 1 in Cancer and Other Disorders. J. Cancer Prev. 2022; 27 : 157–169. PubMed Abstract | Publisher Full Text | Free Full Text 4. Yanting G, Dechun J, Pengcheng X, et al. : Protective Effect of Silent Mating Type Information Regulation 2 Homolog 1 on TGF- β 1 Pathway via mTOR in Diabetic Nephropathy. J. Biosci. Med. 2023; 11 : 194–207. Publisher Full Text 5. Ding RB, Bao J, Deng CX: Emerging roles of SIRT1 in fatty liver diseases.Int. J. Biol. Sci.2017; 13 (7): 852–867. PubMed Abstract | Publisher Full Text | Free Full Text 6. Patricia S, Pardo, Aladin M, et al. : SIRT1 Regulation in Ageing and Obesity. Mech. Ageing Dev. 2020; 188 : 111249. Publisher Full Text 7. Kosgei VJ, Coelho D, Guéant-Rodriguez R-M, et al. : Sirt1-PPARS Cross-Talk in Complex Metabolic Diseases and Inherited Disorders of the One Carbon Metabolism. Cells. 2020; 9 . Publisher Full Text 8. Chalkiadaki A, Guarente L: The multifaceted functions of sirtuins in cancer. Nat. Rev. Cancer. 2015 Oct; 15 (10): 608–624. Publisher Full Text 9. Todd L: Single Nucleotide Polymorphisms (SNPs). 2022. Publisher Full Text 10. Metin Y, Metin Y, Pemra O: In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review. Omics. 2021; 25 (1): 23–37. Publisher Full Text 11. Arina O, Degtyareva EV, Antontseva T, et al. : Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases. Int. J. Mol. Sci. 2021; 22 . PubMed Abstract | Publisher Full Text | Free Full Text 12. Robert F, Pelletier J: Exploring the impact of single-nucleotide polymorphisms on translation. Front. Genet. 2018 Oct 30; 9 (9): 507. PubMed Abstract | Publisher Full Text | Free Full Text 13. Jain KK, Jain KK: Molecular Diagnostics in Personalized Medicine. Textbook of Personalized Medicine. 2015; pp. 35–89. Publisher Full Text 14. Sim NL, Kumar P, Hu J, et al. : SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res. 2012 Jul 1; 40 (W1): W452–W457. PubMed Abstract | Publisher Full Text | Free Full Text 15. Kumar P, Henikoff S, Ng PC: Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc. 2009 Jul; 4 (7): 1073–1081. PubMed Abstract | Publisher Full Text 16. Choi Y, Chan AP: PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics. 2015 Aug 15; 31 (16): 2745–2747. PubMed Abstract | Publisher Full Text | Free Full Text 17. Capriotti E, Fariselli P, Casadio R: I-Mutant2. 0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res. 2005 Jul 1; 33 (suppl_2): W306–W310. PubMed Abstract | Publisher Full Text | Free Full Text 18. Adzhubei IA, Schmidt S, Peshkin L, et al. : A method and server for predicting damaging missense mutations. Nat. Methods. 2010 Apr; 7 (4): 248–249. PubMed Abstract | Publisher Full Text | Free Full Text 19. Venselaar H, Te Beek TA, Kuipers RK, et al. : Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces. BMC bioinformatics. 2010 Dec; 11 (1): 1. Publisher Full Text 20. Carugo O, Pongor S: A normalized root-mean-spuare distance for comparing protein three-dimensional structures. Protein Sci. 2001 Jul; 10 (7): 1470–1473. PubMed Abstract 21. Zhang Y, Skolnick J: TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 2005 Jan 1; 33 (7): 2302–2309. PubMed Abstract | Publisher Full Text | Free Full Text 22. Zhang Y: I-TASSER server for protein 3D structure prediction. BMC bioinformatics. 2008 Dec; 9 (1): 1–8. Publisher Full Text 23. Roy A, Kucukural A, Zhang Y: I-TASSER: a unified platform for automated protein structure and function prediction. Nat. Protoc. 2010 Apr; 5 (4): 725–738. PubMed Abstract | Publisher Full Text | Free Full Text 24. Roy A, Kucukural A, Zhang Y: I-TASSER: a unified platform for automated protein structure and function prediction. Nat. Protoc. 2010 Apr; 5 (4): 725–738. PubMed Abstract | Publisher Full Text 25. Pettersen EF, Goddard TD, Huang CC, et al. : UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 2004 Oct; 25 (13): 1605–1612. PubMed Abstract | Publisher Full Text 26. Zhang Y, Skolnick J: Scoring function for automated assessment of protein structure template quality. Proteins: Structure, Function, and Bioinformatics. 2004 Dec 1; 57 (4): 702–710. PubMed Abstract | Publisher Full Text 27. Deller MC, Kong L, Rupp B: Protein stability: a crystallographer's perspective. Acta Crystallographica Section F: Structural Biology Communications. 2016 Feb 1; 72 (2): 72–95. 28. Pál C, Papp B, Lercher MJ: An integrated view of protein evolution. Nat. Rev. Genet. 2006; 7 (5): 337–348. Publisher Full Text 29. Camps M, Herman A, Loh ER, et al. : Genetic constraints on protein evolution. Crit. Rev. Biochem. Mol. Biol. 2007; 42 (5): 313–326. PubMed Abstract | Publisher Full Text | Free Full Text 30. Yue P, Li Z, Moult J: Loss of protein structure stability as a major causative factor in monogenic disease. J. Mol. Biol. 2005; 353 (2): 459–473. PubMed Abstract | Publisher Full Text 31. Bloom JD, Silberg JJ, Wilke CO, et al. : Thermodynamic prediction of protein neutrality. Proc. Natl. Acad. Sci. 2005; 102 (3): 606–611. PubMed Abstract | Publisher Full Text | Free Full Text 32. Zeldovich KB, Chen P, Shakhnovich EI: Protein stability imposes limits on organism complexity and speed of molecular evolution. Proc. Natl. Acad. Sci. 2007; 104 (41): 16152–16157. PubMed Abstract | Publisher Full Text | Free Full Text 33. Huang LT, Gromiha MM, Ho SY: iPTREE-STAB: interpretable decision tree based method for predicting protein stability changes upon mutations. Bioinformatics. 2007; 23 (10): 1292–1293. PubMed Abstract | Publisher Full Text 34. Parthiban V, Gromiha MM, Schomburg D: CUPSAT: prediction of protein stability upon point mutations. Nucleic Acids Res. 2006; 34 (suppl_2): W239–W242. PubMed Abstract | Publisher Full Text | Free Full Text 35. Vendruscolo M, Tartaglia GG: Towards quantitative predictions in cell biology using chemical properties of proteins. Mol. BioSyst. 2008; 4 (12): 1170–1175. Publisher Full Text 36. Tokuriki N, Stricher F, Serrano L, et al. : How protein stability and new functions trade off. PLoS Comput. Biol. 2008; 4 (2): e1000002. PubMed Abstract | Publisher Full Text | Free Full Text 37. Rahman S, Islam R: Mammalian Sirt1: insights on its biological functions. Cell Commun. Signal. 2011 Dec; 9 (1): 1–8. Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 16 Jan 2023 ADD YOUR COMMENT Comment Author details Author details 1 Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, Karnataka, 575018, India 2 Pharmacology, KS Hegde Medical Academy, NITTE(DU), Mangalore, Karnataka, 575018, India 3 Oncology, KS Hegde Medical Academy, NITTE(DU), Mangalore, Karnataka, 575018, India Desy Thayyil Menambath Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Usha Adiga Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation Tirthal Rai Roles: Formal Analysis, Resources, Validation, Writing – Review & Editing Sachidananda Adiga Roles: Formal Analysis, Resources, Validation, Visualization, Writing – Review & Editing Vijith Shetty Roles: Formal Analysis, Supervision, Validation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (2) version 2 Revised Published: 19 Jan 2024, 12:66 https://doi.org/10.12688/f1000research.128706.2 version 1 Published: 16 Jan 2023, 12:66 https://doi.org/10.12688/f1000research.128706.1 Copyright © 2024 Thayyil Menambath D et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Thayyil Menambath D, Adiga U, Rai T et al. Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.12688/f1000research.128706.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 2 VERSION 2 PUBLISHED 19 Jan 2024 Revised Views 0 Cite How to cite this report: Thakur BL. Reviewer Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.161353.r239165 ) The direct URL for this report is: https://f1000research.com/articles/12-66/v2#referee-response-239165 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 27 Jan 2024 Bhushan L. Thakur , DNA replication group, DTB, NCI/NIH, National Cancer Institute, Bethesda, Maryland, USA Approved VIEWS 0 https://doi.org/10.5256/f1000research.161353.r239165 The authors ... Continue reading READ ALL The authors have addressed all my concerns. Competing Interests: No competing interests were disclosed. Reviewer Expertise: SIRT1 biology, DNA replication, Genomics. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Thakur BL. Reviewer Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.161353.r239165 ) The direct URL for this report is: https://f1000research.com/articles/12-66/v2#referee-response-239165 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 16 Jan 2023 Views 0 Cite How to cite this report: Thakur BL. Reviewer Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.141323.r224496 ) The direct URL for this report is: https://f1000research.com/articles/12-66/v1#referee-response-224496 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 19 Dec 2023 Bhushan L. Thakur , DNA replication group, DTB, NCI/NIH, National Cancer Institute, Bethesda, Maryland, USA Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.141323.r224496 The study provides a comprehensive analysis of single nucleotide polymorphisms (SNPs) in the SIRT1 protein, identifying the three most deleterious non-synonymous SNPs from the NCBI database. The objective of this research is to identify potentially harmful nsSNPs for SIRT1, which ... Continue reading READ ALL The study provides a comprehensive analysis of single nucleotide polymorphisms (SNPs) in the SIRT1 protein, identifying the three most deleterious non-synonymous SNPs from the NCBI database. The objective of this research is to identify potentially harmful nsSNPs for SIRT1, which may potentially impact disease biology. The study is executed and written well. Below are suggested changes to improve clarity and structure: The introduction should include citations to the most recent literature. The methods section provides a concise outline of the collection and analysis of non-synonymous SNPs from the dbSNP site using bioinformatic tools. However, to enhance transparency and reproducibility, the authors should include additional details about the specific criteria or thresholds used to select deleterious nsSNPs. In Figure 1, the method flowchart seems to indicate that the authors used SIFT, Provean, and I-Mutant sequentially to identify the final 66 nsSNPs. However, based on the method description and Table 1, it appears that they utilized commonality between high-score predictions from the three tools to identify the top three hits. The authors should clarify this in the method to reduce ambiguity and make necessary changes in Figure 1. Based on Table 1 and the author's selection criteria for SNP selection, it is unclear why the authors did not shortlist the following three SNPs: D83G (rs17855430), P116T (rs775426483), and G52E (rs757804740). The authors should consider including the variants, G52D (rs757804740) and G52E (rs757804740), in the current manuscript or explain their exclusion. The conclusion succinctly summarizes the most damaging mutations, if possible authors are encouraged to explicitly state the potential implications of these findings for understanding the pathogenesis of various disorders, any reports that cite identification of these SNP’s, and connecting them back to the broader significance mentioned in the introduction. Minor comments - Correct the typo on page 5: " Isofrom a (NP_036370.2) comprised 597 nsSNPs, " should be isoform. - Verify the discrepancy on page 16: "PROVEAN identified 77 nsSNPs as having…" (Figure 1 shows 76). - Correct the typo on page 16: "..rs778184510, rs76519031, rs199983221)…" should be rs769519031. - Add a key for line colors connecting proteins in Figure 5. - Verify and provide a reference or criteria for the claim about I-Tasser in the statement: "...mutations were uploaded to I-Tasser, which is the most accurate and sophisticated technique for predicting protein structure (Figure 2)." Consider modifying it to "...one of the most..." if needed. -Please clarify, what is “E” in Table 1 in DDG column. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: SIRT1 biology, DNA replication, Genomics. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Thakur BL. Reviewer Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.141323.r224496 ) The direct URL for this report is: https://f1000research.com/articles/12-66/v1#referee-response-224496 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 19 Jan 2024 Usha Adiga , Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, 575018, India 19 Jan 2024 Author Response Comment 1: The introduction should include citations to the most recent literature. Answer: The latest references will be included respectively. Comment 2: The methods section provides a concise outline ... Continue reading Comment 1: The introduction should include citations to the most recent literature. Answer: The latest references will be included respectively. Comment 2: The methods section provides a concise outline of the collection and analysis of non-synonymous SNPs from the dbSNP site using bioinformatic tools. However, to enhance transparency and reproducibility, the authors should include additional details about the specific criteria or thresholds used to select deleterious nsSNPs. Answer: All three tools provide valuable insights into the functional consequences of genetic variations, their methodologies and focuses differ. SIFT predicts the functional impact of amino acid substitutions based on sequence conservation. It evaluates how well a particular amino acid is conserved across different species. PROVEAN predicts the impact of protein sequence variations using a combination of sequence homology and structural information. It considers the alignment of the query sequence with homologous sequences and the predicted structure changes caused by the variation. I-Mutant focuses on predicting the impact of amino acid substitutions on protein stability. It employs an energy-based approach, evaluating changes in free energy upon mutation to predict whether a mutation destabilizes or stabilizes the protein structure. Comment 3: In Figure 1, the method flowchart seems to indicate that the authors used SIFT, Provean, and I-Mutant sequentially to identify the final 66 nsSNPs. However, based on the method description and Table 1, it appears that they utilized commonality between high-score predictions from the three tools to identify the top three hits. The authors should clarify this in the method to reduce ambiguity and make necessary changes in Figure 1. Answer: In the SIRT1 gene, three isoforms were identified, resulting in a total of 252 identified Single Nucleotide Polymorphisms (SNPs). Among them, SIFT software identified 94 non-synonymous SNPs (nsSNPs) as intolerant (using a cutoff value of <0.05). Subsequently, these 94 intolerant nsSNPs underwent Provean analysis, revealing 67 nsSNPs as harmful (with a cutoff value of <-2.5). The selected 67 nsSNPs then underwent I-Mutant analysis, which indicated 58 nsSNPs with decreased stability (using a cutoff value of 0). From this subset, we selected three nsSNPs from each isoform, respectively, based on decreasing protein stability. The figure will be modified accordingly. Comment 4: Based on Table 1 and the author's selection criteria for SNP selection, it is unclear why the authors did not shortlist the following three SNPs: D83G (rs17855430), P116T (rs775426483), and G52E (rs757804740). The authors should consider including the variants, G52D (rs757804740) and G52E (rs757804740), in the current manuscript or explain their exclusion. Answer: We have chosen one non-synonymous Single Nucleotide Polymorphisms (nsSNPs) from each of the three isoforms, specifically focusing on those identified as more damaging and exhibiting decreased stability. Comment 5: The conclusion succinctly summarizes the most damaging mutations, if possible authors are encouraged to explicitly state the potential implications of these findings for understanding the pathogenesis of various disorders, any reports that cite identification of these SNP’s, and connecting them back to the broader significance mentioned in the introduction. Answer: There is no existing literature on the specified SNPs of SIRT1 gene. Minor comments - Correct the typo on page 5: " Isofrom a (NP_036370.2) comprised 597 nsSNPs, " should be isoform. Answer: Corrected - Verify the discrepancy on page 16: "PROVEAN identified 77 nsSNPs as having…" (Figure 1 shows 76). Answer: corrected the number of SNPs after rechecking to 67 - Correct the typo on page 16: "..rs778184510, rs76519031, rs199983221)…" should be rs769519031. Answer: Corrected - Add a key for line colors connecting proteins in Figure 5. Answer: The explanation will be included in the text. In evidence mode, an edge may be drawn with up to 7 differently colored lines - these lines represent the existence of the seven types of evidence used in predicting the associations. Red lines indicate the presence of fusion evidence, green lines represent neighborhood evidence, blue lines suggest cooccurrence evidence, purple lines correspond to experimental evidence, yellow lines denote text mining evidence, light blue lines signify database evidence, and black lines represent co-expression evidence. - Verify and provide a reference or criteria for the claim about I-Tasser in the statement: "...mutations were uploaded to I-Tasser, which is the most accurate and sophisticated technique for predicting protein structure (Figure 2)." Consider modifying it to "...one of the most..." if needed. Answer: The statement is corrected accordingly. -Please clarify, what is “E” in Table 1 in DDG column. Answer: E represents error from the analysis report. Thank you for the valuable comments. All the corrections and suggestions will be incorporated in the manuscript accordingly. Comment 1: The introduction should include citations to the most recent literature. Answer: The latest references will be included respectively. Comment 2: The methods section provides a concise outline of the collection and analysis of non-synonymous SNPs from the dbSNP site using bioinformatic tools. However, to enhance transparency and reproducibility, the authors should include additional details about the specific criteria or thresholds used to select deleterious nsSNPs. Answer: All three tools provide valuable insights into the functional consequences of genetic variations, their methodologies and focuses differ. SIFT predicts the functional impact of amino acid substitutions based on sequence conservation. It evaluates how well a particular amino acid is conserved across different species. PROVEAN predicts the impact of protein sequence variations using a combination of sequence homology and structural information. It considers the alignment of the query sequence with homologous sequences and the predicted structure changes caused by the variation. I-Mutant focuses on predicting the impact of amino acid substitutions on protein stability. It employs an energy-based approach, evaluating changes in free energy upon mutation to predict whether a mutation destabilizes or stabilizes the protein structure. Comment 3: In Figure 1, the method flowchart seems to indicate that the authors used SIFT, Provean, and I-Mutant sequentially to identify the final 66 nsSNPs. However, based on the method description and Table 1, it appears that they utilized commonality between high-score predictions from the three tools to identify the top three hits. The authors should clarify this in the method to reduce ambiguity and make necessary changes in Figure 1. Answer: In the SIRT1 gene, three isoforms were identified, resulting in a total of 252 identified Single Nucleotide Polymorphisms (SNPs). Among them, SIFT software identified 94 non-synonymous SNPs (nsSNPs) as intolerant (using a cutoff value of <0.05). Subsequently, these 94 intolerant nsSNPs underwent Provean analysis, revealing 67 nsSNPs as harmful (with a cutoff value of <-2.5). The selected 67 nsSNPs then underwent I-Mutant analysis, which indicated 58 nsSNPs with decreased stability (using a cutoff value of 0). From this subset, we selected three nsSNPs from each isoform, respectively, based on decreasing protein stability. The figure will be modified accordingly. Comment 4: Based on Table 1 and the author's selection criteria for SNP selection, it is unclear why the authors did not shortlist the following three SNPs: D83G (rs17855430), P116T (rs775426483), and G52E (rs757804740). The authors should consider including the variants, G52D (rs757804740) and G52E (rs757804740), in the current manuscript or explain their exclusion. Answer: We have chosen one non-synonymous Single Nucleotide Polymorphisms (nsSNPs) from each of the three isoforms, specifically focusing on those identified as more damaging and exhibiting decreased stability. Comment 5: The conclusion succinctly summarizes the most damaging mutations, if possible authors are encouraged to explicitly state the potential implications of these findings for understanding the pathogenesis of various disorders, any reports that cite identification of these SNP’s, and connecting them back to the broader significance mentioned in the introduction. Answer: There is no existing literature on the specified SNPs of SIRT1 gene. Minor comments - Correct the typo on page 5: " Isofrom a (NP_036370.2) comprised 597 nsSNPs, " should be isoform. Answer: Corrected - Verify the discrepancy on page 16: "PROVEAN identified 77 nsSNPs as having…" (Figure 1 shows 76). Answer: corrected the number of SNPs after rechecking to 67 - Correct the typo on page 16: "..rs778184510, rs76519031, rs199983221)…" should be rs769519031. Answer: Corrected - Add a key for line colors connecting proteins in Figure 5. Answer: The explanation will be included in the text. In evidence mode, an edge may be drawn with up to 7 differently colored lines - these lines represent the existence of the seven types of evidence used in predicting the associations. Red lines indicate the presence of fusion evidence, green lines represent neighborhood evidence, blue lines suggest cooccurrence evidence, purple lines correspond to experimental evidence, yellow lines denote text mining evidence, light blue lines signify database evidence, and black lines represent co-expression evidence. - Verify and provide a reference or criteria for the claim about I-Tasser in the statement: "...mutations were uploaded to I-Tasser, which is the most accurate and sophisticated technique for predicting protein structure (Figure 2)." Consider modifying it to "...one of the most..." if needed. Answer: The statement is corrected accordingly. -Please clarify, what is “E” in Table 1 in DDG column. Answer: E represents error from the analysis report. Thank you for the valuable comments. All the corrections and suggestions will be incorporated in the manuscript accordingly. Competing Interests: No competing interests Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 19 Jan 2024 Usha Adiga , Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, 575018, India 19 Jan 2024 Author Response Comment 1: The introduction should include citations to the most recent literature. Answer: The latest references will be included respectively. Comment 2: The methods section provides a concise outline ... Continue reading Comment 1: The introduction should include citations to the most recent literature. Answer: The latest references will be included respectively. Comment 2: The methods section provides a concise outline of the collection and analysis of non-synonymous SNPs from the dbSNP site using bioinformatic tools. However, to enhance transparency and reproducibility, the authors should include additional details about the specific criteria or thresholds used to select deleterious nsSNPs. Answer: All three tools provide valuable insights into the functional consequences of genetic variations, their methodologies and focuses differ. SIFT predicts the functional impact of amino acid substitutions based on sequence conservation. It evaluates how well a particular amino acid is conserved across different species. PROVEAN predicts the impact of protein sequence variations using a combination of sequence homology and structural information. It considers the alignment of the query sequence with homologous sequences and the predicted structure changes caused by the variation. I-Mutant focuses on predicting the impact of amino acid substitutions on protein stability. It employs an energy-based approach, evaluating changes in free energy upon mutation to predict whether a mutation destabilizes or stabilizes the protein structure. Comment 3: In Figure 1, the method flowchart seems to indicate that the authors used SIFT, Provean, and I-Mutant sequentially to identify the final 66 nsSNPs. However, based on the method description and Table 1, it appears that they utilized commonality between high-score predictions from the three tools to identify the top three hits. The authors should clarify this in the method to reduce ambiguity and make necessary changes in Figure 1. Answer: In the SIRT1 gene, three isoforms were identified, resulting in a total of 252 identified Single Nucleotide Polymorphisms (SNPs). Among them, SIFT software identified 94 non-synonymous SNPs (nsSNPs) as intolerant (using a cutoff value of <0.05). Subsequently, these 94 intolerant nsSNPs underwent Provean analysis, revealing 67 nsSNPs as harmful (with a cutoff value of <-2.5). The selected 67 nsSNPs then underwent I-Mutant analysis, which indicated 58 nsSNPs with decreased stability (using a cutoff value of 0). From this subset, we selected three nsSNPs from each isoform, respectively, based on decreasing protein stability. The figure will be modified accordingly. Comment 4: Based on Table 1 and the author's selection criteria for SNP selection, it is unclear why the authors did not shortlist the following three SNPs: D83G (rs17855430), P116T (rs775426483), and G52E (rs757804740). The authors should consider including the variants, G52D (rs757804740) and G52E (rs757804740), in the current manuscript or explain their exclusion. Answer: We have chosen one non-synonymous Single Nucleotide Polymorphisms (nsSNPs) from each of the three isoforms, specifically focusing on those identified as more damaging and exhibiting decreased stability. Comment 5: The conclusion succinctly summarizes the most damaging mutations, if possible authors are encouraged to explicitly state the potential implications of these findings for understanding the pathogenesis of various disorders, any reports that cite identification of these SNP’s, and connecting them back to the broader significance mentioned in the introduction. Answer: There is no existing literature on the specified SNPs of SIRT1 gene. Minor comments - Correct the typo on page 5: " Isofrom a (NP_036370.2) comprised 597 nsSNPs, " should be isoform. Answer: Corrected - Verify the discrepancy on page 16: "PROVEAN identified 77 nsSNPs as having…" (Figure 1 shows 76). Answer: corrected the number of SNPs after rechecking to 67 - Correct the typo on page 16: "..rs778184510, rs76519031, rs199983221)…" should be rs769519031. Answer: Corrected - Add a key for line colors connecting proteins in Figure 5. Answer: The explanation will be included in the text. In evidence mode, an edge may be drawn with up to 7 differently colored lines - these lines represent the existence of the seven types of evidence used in predicting the associations. Red lines indicate the presence of fusion evidence, green lines represent neighborhood evidence, blue lines suggest cooccurrence evidence, purple lines correspond to experimental evidence, yellow lines denote text mining evidence, light blue lines signify database evidence, and black lines represent co-expression evidence. - Verify and provide a reference or criteria for the claim about I-Tasser in the statement: "...mutations were uploaded to I-Tasser, which is the most accurate and sophisticated technique for predicting protein structure (Figure 2)." Consider modifying it to "...one of the most..." if needed. Answer: The statement is corrected accordingly. -Please clarify, what is “E” in Table 1 in DDG column. Answer: E represents error from the analysis report. Thank you for the valuable comments. All the corrections and suggestions will be incorporated in the manuscript accordingly. Comment 1: The introduction should include citations to the most recent literature. Answer: The latest references will be included respectively. Comment 2: The methods section provides a concise outline of the collection and analysis of non-synonymous SNPs from the dbSNP site using bioinformatic tools. However, to enhance transparency and reproducibility, the authors should include additional details about the specific criteria or thresholds used to select deleterious nsSNPs. Answer: All three tools provide valuable insights into the functional consequences of genetic variations, their methodologies and focuses differ. SIFT predicts the functional impact of amino acid substitutions based on sequence conservation. It evaluates how well a particular amino acid is conserved across different species. PROVEAN predicts the impact of protein sequence variations using a combination of sequence homology and structural information. It considers the alignment of the query sequence with homologous sequences and the predicted structure changes caused by the variation. I-Mutant focuses on predicting the impact of amino acid substitutions on protein stability. It employs an energy-based approach, evaluating changes in free energy upon mutation to predict whether a mutation destabilizes or stabilizes the protein structure. Comment 3: In Figure 1, the method flowchart seems to indicate that the authors used SIFT, Provean, and I-Mutant sequentially to identify the final 66 nsSNPs. However, based on the method description and Table 1, it appears that they utilized commonality between high-score predictions from the three tools to identify the top three hits. The authors should clarify this in the method to reduce ambiguity and make necessary changes in Figure 1. Answer: In the SIRT1 gene, three isoforms were identified, resulting in a total of 252 identified Single Nucleotide Polymorphisms (SNPs). Among them, SIFT software identified 94 non-synonymous SNPs (nsSNPs) as intolerant (using a cutoff value of <0.05). Subsequently, these 94 intolerant nsSNPs underwent Provean analysis, revealing 67 nsSNPs as harmful (with a cutoff value of <-2.5). The selected 67 nsSNPs then underwent I-Mutant analysis, which indicated 58 nsSNPs with decreased stability (using a cutoff value of 0). From this subset, we selected three nsSNPs from each isoform, respectively, based on decreasing protein stability. The figure will be modified accordingly. Comment 4: Based on Table 1 and the author's selection criteria for SNP selection, it is unclear why the authors did not shortlist the following three SNPs: D83G (rs17855430), P116T (rs775426483), and G52E (rs757804740). The authors should consider including the variants, G52D (rs757804740) and G52E (rs757804740), in the current manuscript or explain their exclusion. Answer: We have chosen one non-synonymous Single Nucleotide Polymorphisms (nsSNPs) from each of the three isoforms, specifically focusing on those identified as more damaging and exhibiting decreased stability. Comment 5: The conclusion succinctly summarizes the most damaging mutations, if possible authors are encouraged to explicitly state the potential implications of these findings for understanding the pathogenesis of various disorders, any reports that cite identification of these SNP’s, and connecting them back to the broader significance mentioned in the introduction. Answer: There is no existing literature on the specified SNPs of SIRT1 gene. Minor comments - Correct the typo on page 5: " Isofrom a (NP_036370.2) comprised 597 nsSNPs, " should be isoform. Answer: Corrected - Verify the discrepancy on page 16: "PROVEAN identified 77 nsSNPs as having…" (Figure 1 shows 76). Answer: corrected the number of SNPs after rechecking to 67 - Correct the typo on page 16: "..rs778184510, rs76519031, rs199983221)…" should be rs769519031. Answer: Corrected - Add a key for line colors connecting proteins in Figure 5. Answer: The explanation will be included in the text. In evidence mode, an edge may be drawn with up to 7 differently colored lines - these lines represent the existence of the seven types of evidence used in predicting the associations. Red lines indicate the presence of fusion evidence, green lines represent neighborhood evidence, blue lines suggest cooccurrence evidence, purple lines correspond to experimental evidence, yellow lines denote text mining evidence, light blue lines signify database evidence, and black lines represent co-expression evidence. - Verify and provide a reference or criteria for the claim about I-Tasser in the statement: "...mutations were uploaded to I-Tasser, which is the most accurate and sophisticated technique for predicting protein structure (Figure 2)." Consider modifying it to "...one of the most..." if needed. Answer: The statement is corrected accordingly. -Please clarify, what is “E” in Table 1 in DDG column. Answer: E represents error from the analysis report. Thank you for the valuable comments. All the corrections and suggestions will be incorporated in the manuscript accordingly. Competing Interests: No competing interests Close Report a concern COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Bairy LK. Reviewer Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.141323.r162701 ) The direct URL for this report is: https://f1000research.com/articles/12-66/v1#referee-response-162701 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 21 Feb 2023 Laxminarayana Kurady Bairy , Department of Pharmacology, RAK College of Medical Sciences, RAK Medical and Health Sciences University, Ras al Khaimah, United Arab Emirates Approved VIEWS 0 https://doi.org/10.5256/f1000research.141323.r162701 The article is well presented. The aims and objectives are clearly mentioned. The introduction part is well written. However, the cited references are before 2016. In fact, the majority are before 2010. ... Continue reading READ ALL The article is well presented. The aims and objectives are clearly mentioned. The introduction part is well written. However, the cited references are before 2016. In fact, the majority are before 2010. There is no update on the recent developments in the field. Hence, the introduction needs to be rewritten with recent references. The study design is appropriate and the work is technically sound. The methodology used is clear, described in detail and is enough for anyone to repeat the experiment. The statistical method is appropriate. The source data is not available in the manuscript provided. However, it is not customary to give sorce data in the manuscript. Most of the journals do not ask for source data. However, if it is required, editorial can ask for the same. There is some ambiguity in the conclusion drawn. It is a bit vague. This needs to rewritten to make it more lucid. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? No source data required Are the conclusions drawn adequately supported by the results? Partly Competing Interests: No competing interests were disclosed. Reviewer Expertise: My area of research includes pharmacogenomics, wound healing and neurogenerative disorders. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Bairy LK. Reviewer Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.141323.r162701 ) The direct URL for this report is: https://f1000research.com/articles/12-66/v1#referee-response-162701 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 03 Apr 2023 Usha Adiga , Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, 575018, India 03 Apr 2023 Author Response Introduction will be modified with recent references. Conclusion will be modified. Competing Interests: No competing interests were disclosed. Introduction will be modified with recent references. Conclusion will be modified. Introduction will be modified with recent references. Conclusion will be modified. Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 03 Apr 2023 Usha Adiga , Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, 575018, India 03 Apr 2023 Author Response Introduction will be modified with recent references. Conclusion will be modified. Competing Interests: No competing interests were disclosed. Introduction will be modified with recent references. Conclusion will be modified. Introduction will be modified with recent references. Conclusion will be modified. Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 16 Jan 2023 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 Version 2 (revision) 19 Jan 24 read Version 1 16 Jan 23 read read Laxminarayana Kurady Bairy , RAK Medical and Health Sciences University, Ras al Khaimah, United Arab Emirates Bhushan L. Thakur , National Cancer Institute, Bethesda, USA Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Thakur B. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. 27 Jan 2024 | for Version 2 Bhushan L. Thakur , DNA replication group, DTB, NCI/NIH, National Cancer Institute, Bethesda, Maryland, USA 0 Views copyright © 2024 Thakur B. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The authors have addressed all my concerns. Competing Interests No competing interests were disclosed. Reviewer Expertise SIRT1 biology, DNA replication, Genomics. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Thakur BL. Peer Review Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.161353.r239165) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-66/v2#referee-response-239165 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2023 Thakur B. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. 19 Dec 2023 | for Version 1 Bhushan L. Thakur , DNA replication group, DTB, NCI/NIH, National Cancer Institute, Bethesda, Maryland, USA 0 Views copyright © 2023 Thakur B. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The study provides a comprehensive analysis of single nucleotide polymorphisms (SNPs) in the SIRT1 protein, identifying the three most deleterious non-synonymous SNPs from the NCBI database. The objective of this research is to identify potentially harmful nsSNPs for SIRT1, which may potentially impact disease biology. The study is executed and written well. Below are suggested changes to improve clarity and structure: The introduction should include citations to the most recent literature. The methods section provides a concise outline of the collection and analysis of non-synonymous SNPs from the dbSNP site using bioinformatic tools. However, to enhance transparency and reproducibility, the authors should include additional details about the specific criteria or thresholds used to select deleterious nsSNPs. In Figure 1, the method flowchart seems to indicate that the authors used SIFT, Provean, and I-Mutant sequentially to identify the final 66 nsSNPs. However, based on the method description and Table 1, it appears that they utilized commonality between high-score predictions from the three tools to identify the top three hits. The authors should clarify this in the method to reduce ambiguity and make necessary changes in Figure 1. Based on Table 1 and the author's selection criteria for SNP selection, it is unclear why the authors did not shortlist the following three SNPs: D83G (rs17855430), P116T (rs775426483), and G52E (rs757804740). The authors should consider including the variants, G52D (rs757804740) and G52E (rs757804740), in the current manuscript or explain their exclusion. The conclusion succinctly summarizes the most damaging mutations, if possible authors are encouraged to explicitly state the potential implications of these findings for understanding the pathogenesis of various disorders, any reports that cite identification of these SNP’s, and connecting them back to the broader significance mentioned in the introduction. Minor comments - Correct the typo on page 5: " Isofrom a (NP_036370.2) comprised 597 nsSNPs, " should be isoform. - Verify the discrepancy on page 16: "PROVEAN identified 77 nsSNPs as having…" (Figure 1 shows 76). - Correct the typo on page 16: "..rs778184510, rs76519031, rs199983221)…" should be rs769519031. - Add a key for line colors connecting proteins in Figure 5. - Verify and provide a reference or criteria for the claim about I-Tasser in the statement: "...mutations were uploaded to I-Tasser, which is the most accurate and sophisticated technique for predicting protein structure (Figure 2)." Consider modifying it to "...one of the most..." if needed. -Please clarify, what is “E” in Table 1 in DDG column. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise SIRT1 biology, DNA replication, Genomics. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 19 Jan 2024 Usha Adiga, Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, 575018, India Comment 1: The introduction should include citations to the most recent literature. Answer: The latest references will be included respectively. Comment 2: The methods section provides a concise outline of the collection and analysis of non-synonymous SNPs from the dbSNP site using bioinformatic tools. However, to enhance transparency and reproducibility, the authors should include additional details about the specific criteria or thresholds used to select deleterious nsSNPs. Answer: All three tools provide valuable insights into the functional consequences of genetic variations, their methodologies and focuses differ. SIFT predicts the functional impact of amino acid substitutions based on sequence conservation. It evaluates how well a particular amino acid is conserved across different species. PROVEAN predicts the impact of protein sequence variations using a combination of sequence homology and structural information. It considers the alignment of the query sequence with homologous sequences and the predicted structure changes caused by the variation. I-Mutant focuses on predicting the impact of amino acid substitutions on protein stability. It employs an energy-based approach, evaluating changes in free energy upon mutation to predict whether a mutation destabilizes or stabilizes the protein structure. Comment 3: In Figure 1, the method flowchart seems to indicate that the authors used SIFT, Provean, and I-Mutant sequentially to identify the final 66 nsSNPs. However, based on the method description and Table 1, it appears that they utilized commonality between high-score predictions from the three tools to identify the top three hits. The authors should clarify this in the method to reduce ambiguity and make necessary changes in Figure 1. Answer: In the SIRT1 gene, three isoforms were identified, resulting in a total of 252 identified Single Nucleotide Polymorphisms (SNPs). Among them, SIFT software identified 94 non-synonymous SNPs (nsSNPs) as intolerant (using a cutoff value of <0.05). Subsequently, these 94 intolerant nsSNPs underwent Provean analysis, revealing 67 nsSNPs as harmful (with a cutoff value of <-2.5). The selected 67 nsSNPs then underwent I-Mutant analysis, which indicated 58 nsSNPs with decreased stability (using a cutoff value of 0). From this subset, we selected three nsSNPs from each isoform, respectively, based on decreasing protein stability. The figure will be modified accordingly. Comment 4: Based on Table 1 and the author's selection criteria for SNP selection, it is unclear why the authors did not shortlist the following three SNPs: D83G (rs17855430), P116T (rs775426483), and G52E (rs757804740). The authors should consider including the variants, G52D (rs757804740) and G52E (rs757804740), in the current manuscript or explain their exclusion. Answer: We have chosen one non-synonymous Single Nucleotide Polymorphisms (nsSNPs) from each of the three isoforms, specifically focusing on those identified as more damaging and exhibiting decreased stability. Comment 5: The conclusion succinctly summarizes the most damaging mutations, if possible authors are encouraged to explicitly state the potential implications of these findings for understanding the pathogenesis of various disorders, any reports that cite identification of these SNP’s, and connecting them back to the broader significance mentioned in the introduction. Answer: There is no existing literature on the specified SNPs of SIRT1 gene. Minor comments - Correct the typo on page 5: " Isofrom a (NP_036370.2) comprised 597 nsSNPs, " should be isoform. Answer: Corrected - Verify the discrepancy on page 16: "PROVEAN identified 77 nsSNPs as having…" (Figure 1 shows 76). Answer: corrected the number of SNPs after rechecking to 67 - Correct the typo on page 16: "..rs778184510, rs76519031, rs199983221)…" should be rs769519031. Answer: Corrected - Add a key for line colors connecting proteins in Figure 5. Answer: The explanation will be included in the text. In evidence mode, an edge may be drawn with up to 7 differently colored lines - these lines represent the existence of the seven types of evidence used in predicting the associations. Red lines indicate the presence of fusion evidence, green lines represent neighborhood evidence, blue lines suggest cooccurrence evidence, purple lines correspond to experimental evidence, yellow lines denote text mining evidence, light blue lines signify database evidence, and black lines represent co-expression evidence. - Verify and provide a reference or criteria for the claim about I-Tasser in the statement: "...mutations were uploaded to I-Tasser, which is the most accurate and sophisticated technique for predicting protein structure (Figure 2)." Consider modifying it to "...one of the most..." if needed. Answer: The statement is corrected accordingly. -Please clarify, what is “E” in Table 1 in DDG column. Answer: E represents error from the analysis report. Thank you for the valuable comments. All the corrections and suggestions will be incorporated in the manuscript accordingly. View more View less Competing Interests No competing interests reply Respond Report a concern Thakur BL. Peer Review Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.141323.r224496) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-66/v1#referee-response-224496 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2023 Bairy L. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 21 Feb 2023 | for Version 1 Laxminarayana Kurady Bairy , Department of Pharmacology, RAK College of Medical Sciences, RAK Medical and Health Sciences University, Ras al Khaimah, United Arab Emirates 0 Views copyright © 2023 Bairy L. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The article is well presented. The aims and objectives are clearly mentioned. The introduction part is well written. However, the cited references are before 2016. In fact, the majority are before 2010. There is no update on the recent developments in the field. Hence, the introduction needs to be rewritten with recent references. The study design is appropriate and the work is technically sound. The methodology used is clear, described in detail and is enough for anyone to repeat the experiment. The statistical method is appropriate. The source data is not available in the manuscript provided. However, it is not customary to give sorce data in the manuscript. Most of the journals do not ask for source data. However, if it is required, editorial can ask for the same. There is some ambiguity in the conclusion drawn. It is a bit vague. This needs to rewritten to make it more lucid. Is the work clearly and accurately presented and does it cite the current literature? No Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? No source data required Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. Reviewer Expertise My area of research includes pharmacogenomics, wound healing and neurogenerative disorders. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (1) Author Response 03 Apr 2023 Usha Adiga, Biochemistry, KS Hegde Medical Academy, NITTE (DU), Mangalore, 575018, India Introduction will be modified with recent references. Conclusion will be modified. View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Bairy LK. Peer Review Report For: Identification of the SIRT1 gene's most harmful non-synonymous SNPs and their effects on functional and structural features-an in silico analysis [version 2; peer review: 2 approved] . F1000Research 2024, 12 :66 ( https://doi.org/10.5256/f1000research.141323.r162701) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/12-66/v1#referee-response-162701 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Stay Updated Sign up for content alerts and receive a weekly or monthly email with all newly published articles Register with F1000Research Already registered? Sign in Not now, thanks close PLEASE NOTE If you are an AUTHOR of this article, please check that you signed in with the account associated with this article otherwise we cannot automatically identify your role as an author and your comment will be labelled as a “User Comment”. If you are a REVIEWER of this article, please check that you have signed in with the account associated with this article and then go to your account to submit your report, please do not post your review here. If you do not have access to your original account, please contact us . All commenters must hold a formal affiliation as per our Policies . The information that you give us will be displayed next to your comment. User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions . Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available. I accept the User Comment Terms and Conditions Please confirm that you accept the User Comment Terms and Conditions. Affiliation ✕ refresh Please enter your institution. Note: To add your institution or organisation, start typing the name and then select the correct name from the list. Where applicable, the name will appear in both the original language and in English. Do not paste in the name. If the name does not appear in the drop-down list, we will display the information you have entered. ✕ refresh Country/Region * USA UK Canada China France Germany Afghanistan Aland Islands Albania Algeria American Samoa Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory British Virgin Islands Brunei Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Cook Islands Costa Rica Cote d'Ivoire Croatia Cuba Cyprus Czech Republic Democratic Republic of the Congo Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands Faroe Islands Federated States of Micronesia Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and Mcdonald Islands Holy See (Vatican City State) Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Kosovo (Serbia and Montenegro) Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macao Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Minor Outlying Islands of the United States Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island North Korea North Macedonia Northern Mariana Islands Norway Oman Pakistan Palau Palestinian Territory Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Puerto Rico Qatar Reunion Romania Russian Federation Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Is South Korea South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand The Gambia The Netherlands Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu UK USA Uganda Ukraine United Arab Emirates United States Virgin Islands Uruguay Uzbekistan Vanuatu Venezuela Vietnam Wallis and Futuna West Bank and Gaza Strip Western Sahara Yemen Zambia Zimbabwe Please select your country/region. You must enter a comment. Competing Interests Please disclose any competing interests that might be construed to influence your judgment of the article's or peer review report's validity or importance. Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Please state your competing interests The comment has been saved. An error has occurred. Please try again. Cancel Post var lTitle = "Identification of the SIRT1 gene\'s most...".replace("'", ''); var linkedInUrl = "http://www.linkedin.com/shareArticle?url=https://f1000research.com/articles/12-66/v2" + "&title=" + encodeURIComponent(lTitle) + "&summary=" + encodeURIComponent('Read the article by '); var deliciousUrl = "https://del.icio.us/post?url=https://f1000research.com/articles/12-66/v2&title=" + encodeURIComponent(lTitle); var redditUrl = "http://reddit.com/submit?url=https://f1000research.com/articles/12-66/v2" + "&title=" + encodeURIComponent(lTitle); linkedInUrl += encodeURIComponent('Thayyil Menambath D et al.'); var offsetTop = /chrome/i.test( navigator.userAgent ) ? 4 : -10; var addthis_config = { ui_offset_top: offsetTop, services_compact : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_expanded : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_custom : [ { name: "LinkedIn", url: linkedInUrl, icon:"/img/icon/at_linkedin.svg" }, { name: "Mendeley", url: "http://www.mendeley.com/import/?url=https://f1000research.com/articles/12-66/v2/mendeley", icon:"/img/icon/at_mendeley.svg" }, { name: "Reddit", url: redditUrl, icon:"/img/icon/at_reddit.svg" }, ] }; var addthis_share = { url: "https://f1000research.com/articles/12-66", templates : { twitter : "Identification of the SIRT1 gene\'s most harmful non-synonymous.... Thayyil Menambath D et al., published by " + "@F1000Research" + ", https://f1000research.com/articles/12-66/v2" } }; if (typeof(addthis) != "undefined"){ addthis.addEventListener('addthis.ready', checkCount); addthis.addEventListener('addthis.menu.share', checkCount); } $(".f1r-shares-twitter").attr("href", "https://twitter.com/intent/tweet?text=" + addthis_share.templates.twitter); $(".f1r-shares-facebook").attr("href", "https://www.facebook.com/sharer/sharer.php?u=" + addthis_share.url); $(".f1r-shares-linkedin").attr("href", addthis_config.services_custom[0].url); $(".f1r-shares-reddit").attr("href", addthis_config.services_custom[2].url); $(".f1r-shares-mendelay").attr("href", addthis_config.services_custom[1].url); function checkCount(){ setTimeout(function(){ $(".addthis_button_expanded").each(function(){ var count = $(this).text(); if (count !== "" && count != "0") $(this).removeClass("is-hidden"); else $(this).addClass("is-hidden"); }); }, 1000); } close How to cite this report {{reportCitation}} Cancel Copy Citation Details $(function(){R.ui.buttonDropdowns('.dropdown-for-downloads');}); $(function(){R.ui.toolbarDropdowns('.toolbar-dropdown-for-downloads');}); $.get("/articles/acj/128706/161353") new F1000.Clipboard(); new F1000.ThesaurusTermsDisplay("articles", "article", "161353"); $(document).ready(function() { $( "#frame1" ).on('load', function() { var mydiv = $(this).contents().find("div"); var h = mydiv.height(); console.log(h) }); var tooltipLivingFigure = jQuery(".interactive-living-figure-label .icon-more-info"), titleLivingFigure = tooltipLivingFigure.attr("title"); tooltipLivingFigure.simpletip({ fixed: true, position: ["-115", "30"], baseClass: 'small-tooltip', content:titleLivingFigure + " " }); tooltipLivingFigure.removeAttr("title"); $("body").on("click", ".cite-living-figure", function(e) { e.preventDefault(); var ref = $(this).attr("data-ref"); $(this).closest(".living-figure-list-container").find("#" + ref).fadeIn(200); }); $("body").on("click", ".close-cite-living-figure", function(e) { e.preventDefault(); $(this).closest(".popup-window-wrapper").fadeOut(200); }); $(document).on("mouseup", function(e) { var metricsContainer = $(".article-metrics-popover-wrapper"); if (!metricsContainer.is(e.target) && metricsContainer.has(e.target).length === 0) { $(".article-metrics-close-button").click(); } }); var articleId = $('#articleId').val(); if($("#main-article-count-box").attachArticleMetrics) { $("#main-article-count-box").attachArticleMetrics(articleId, { articleMetricsView: true }); } }); var figshareWidget = $(".new_figshare_widget"); if (figshareWidget.length > 0) { window.figshare.load("f1000", function(Widget) { // Select a tag/tags defined in your page. In this tag we will place the widget. _.map(figshareWidget, function(el){ var widget = new Widget({ articleId: $(el).attr("figshare_articleId") //height:300 // this is the height of the viewer part. [Default: 550] }); widget.initialize(); // initialize the widget widget.mount(el); // mount it in a tag that's on your page // this will save the widget on the global scope for later use from // your JS scripts. This line is optional. //window.widget = widget; }); }); } close Error Close Add Reset F1000.MICROSERVICES.AFFILIATION = ''; $(document).ready(function () { $('.js-affiliations-form').each((index, form) => { new AffiliationForm({ formId: form.id, institutionErrorSelector: '.comment-enter-institution', departmentErrorSelector: '.comment-enter-department', placeSelector: '.js-add-comment-place', stateSelector: '.js-add-comment-state', zipCodeSelector: '.js-add-comment-zipcode', countrySelector: '.js-add-comment-country', countryErrorSelector: '.comment-enter-country', }); }); }); $(document).ready(function () { var reportIds = { "162698": 0, "162699": 0, "162702": 0, "162700": 0, "162701": 29, "162704": 0, "214827": 0, "214831": 0, "214830": 0, "214829": 0, "214828": 0, "214835": 0, "214834": 0, "214833": 0, "214832": 0, "214836": 0, "239165": 13, "239164": 0, "200007": 0, "200011": 0, "200010": 0, "200009": 0, "200008": 0, "200015": 0, "200014": 0, "200013": 0, "200012": 0, "200016": 0, "224469": 0, "224475": 0, "224472": 0, "224479": 0, "224483": 0, "224488": 0, "208879": 0, "195438": 0, "224493": 0, "208883": 0, "224498": 0, "208882": 0, "208881": 0, "208880": 0, "224496": 31, "208887": 0, "208886": 0, "208885": 0, "224500": 0, "208884": 0, "208888": 0, }; $(".referee-response-container,.js-referee-report").each(function(index, el) { var reportId = $(el).attr("data-reportid"), reportCount = reportIds[reportId] || 0; $(el).find(".comments-count-container,.js-referee-report-views").html(reportCount); }); var uuidInput = $("#article_uuid"), oldUUId = uuidInput.val(), newUUId = "e17bcfaa-1263-4611-99b9-2341ba2bf559"; uuidInput.val(newUUId); $("a[href*='article_uuid=']").each(function(index, el) { var newHref = $(el).attr("href").replace(oldUUId, newUUId); $(el).attr("href", newHref); }); }); An innovative open access publishing platform offering rapid publication and open peer review, whilst supporting data deposition and sharing. Browse Gateways Collections How it Works Contact For Developers Cookie Notice Privacy Notice RSS Submit Your Research Follow us © 2012-2026 F1000 Research Ltd. ISSN 2046-1402 | Legal | Partner of Research4Life • CrossRef • ORCID • FAIRSharing R.templateTests.simpleTemplate = R.template(' $text $text $text $text $text '); R.templateTests.runTests(); var F1000platform = new F1000.Platform({ name: "f1000research", displayName: "F1000Research", hostName: "f1000research.com", id: "1", editorialEmail: "[email protected]", infoEmail: "[email protected]", usePmcStats: true }); $(function(){R.ui.dropdowns('.dropdown-for-authors, .dropdown-for-about, .dropdown-for-myresearch');}); // $(function(){R.ui.dropdowns('.dropdown-for-referees');}); $(document).ready(function () { if ($(".cookie-warning").is(":visible")) { $(".sticky").css("margin-bottom", "35px"); $(".devices").addClass("devices-and-cookie-warning"); } $(".cookie-warning .close-button").click(function (e) { $(".devices").removeClass("devices-and-cookie-warning"); $(".sticky").css("margin-bottom", "0"); }); $("#tweeter-feed .tweet-message").each(function (i, message) { var self = $(message); self.html(linkify(self.html())); }); $(".partner").on("mouseenter mouseleave", function() { $(this).find(".gray-scale, .colour").toggleClass("is-hidden"); }); }); Sign In Remember me Forgotten your password? Sign In Cancel Email or password not correct. Please try again Please wait... $(function(){ // Note: All the setup needs to run against a name attribute and *not* the id due the clonish // nature of facebox... $("a[id=googleSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("GOOGLE"); $("form[id=oAuthForm]").submit(); }); $("a[id=facebookSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("FACEBOOK"); $("form[id=oAuthForm]").submit(); }); $("a[id=orcidSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("ORCID"); $("form[id=oAuthForm]").submit(); }); }); If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password. The email address should be the one you originally registered with F1000. Email address not valid, please try again You registered with F1000 via Google, so we cannot reset your password. To sign in, please click here . If you still need help with your Google account password, please click here . You registered with F1000 via Facebook, so we cannot reset your password. To sign in, please click here . If you still need help with your Facebook account password, please click here . Code not correct, please try again Reset password Cancel Email us for further assistance. Server error, please try again. If your email address is registered with us, we will email you instructions to reset your password. If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance. Please wait... Register $(document).ready(function () { signIn.createSignInAsRow($("#sign-in-form-gfb-popup")); $(".target-field").each(function () { var uris = $(this).val().split("/"); if (uris.pop() === "login") { $(this).val(uris.toString().replace(",","/")); } }); });