Target specific peptide design using latent space approximate trajectory collector
preprint
OA: closed
CC-BY-4.0
Abstract
Abstract Despite the prevalence and many successes of deep learning applications in de novo molecular design, the problem of peptide generation targeting specific proteins remains unsolved. A main barrier for this is the scarcity of the high-quality training data. To tackle the issue, we propose a novel machine learning based peptide design architecture, called Latent Space Approximate Trajectory Collector (LSATC). It consists of a series of samplers on an optimization trajectory on a highly non-convex energy landscape that approximates the distributions of peptides with desired properties in a latent space. The process involves little human intervention and can be implemented in an end-to-end manner. We demonstrate the model by the design of peptide extensions targeting β-catenin, a key nuclear effector protein involved in canonical Wnt signalling. When compared with a random sampler, LSATC can sample peptides with 36% lower mean binding scores in a 16 times smaller interquartile range (IQR) and 284% less mean hydrophobicity with a 1.4 times smaller IQR. LSATC also largely outperforms other common generative models.Finally, we utilize a clustering algorithm to select 4 peptides from the100 LSATC designed peptides for experimental validation. The resultconfirms that all the four peptides extended by LSATC show improved β-catenin binding by at least 20.0%, and two of the peptides show a 3 fold increase in binding affinity as compared to the base peptide.
Full text
5,819 characters
· extracted from
preprint-html
· click to expand
:root { --font-inter: 'Inter', 'Roboto', sans-serif, Symbol; --font-monospace: monospace; --font-roboto: 'Roboto', sans-serif, Symbol; --font-sans-serif: sans-serif; } html, body, div, span, h1, h2, h3, h4, h5, h6, p, ol, ul, li, table, caption, tbody, tfoot, thead, tr, th, td {margin: 0;padding: 0;border: 0;font-size: 100%;font: inherit;vertical-align: baseline;} html {font-size: 14px;line-height: 1.5;} body {font-size: 14px;line-height: 1.5;font-family: var(--font-Roboto);} ol, ul {list-style: none;} blockquote, q {quotes: none;} blockquote:before, blockquote:after, q:before, q:after {content: '';content: none;} img {max-width: 100%;} table {border-collapse: collapse;border-spacing: 0;} b {font-weight: bold;} a {color: #2c71d6;text-decoration: none;} p {margin: 10px 0 10px 0;} .no-select {-o-user-select: none;-moz-user-select: none;-khtml-user-select: none;-webkit-user-select: none;user-select: none;} * {box-sizing: border-box;} @keyframes blink {0% {opacity: .1;}20% {opacity: 1;}100% {opacity: .1;}} .main-preloader{position:fixed;display: flex;top:0;bottom:0;left:0;right:0;align-items: center;justify-content: center;z-index:200000000;text-align:center;background:#F2F3F6;} .main-preloader.dark{background:#363636;} .main-preloader.hidden {display: none;} .main-preloader .mp-logo{height:100px;width:100px;} Target specific peptide design using latent space approximate trajectory collector V.1 {"@context":"https://schema.org","@id":"https://www.protocols.io/#org","@type":"Organization","logo":{"@type":"ImageObject","height":"1550","url":"https://www.protocols.io/img/protocols-og.jpg","width":"1920"},"name":"protocols.io","url":"https://www.protocols.io/"} {"@context":"https://schema.org","@id":"https://www.protocols.io/#website","@type":"WebSite","name":"protocols.io","publisher":{"@id":"https://www.protocols.io/#org"},"url":"https://www.protocols.io/"} {"@context":"https://schema.org","@id":"https://www.protocols.io/view/target-specific-peptide-design-using-latent-space-5qpvo9mo7v4o/v1#webpage","@type":"WebPage","about":{"@id":"https://www.protocols.io/#org"},"description":"Target specific peptide design using latent space approximate trajectory collector\n. Despite the preva. Read full protocol, steps, and materials on protocols.io","isPartOf":{"@id":"https://www.protocols.io/#website"},"name":"Target specific peptide design using latent space approximate trajectory collector\n V.1","url":"https://www.protocols.io/view/target-specific-peptide-design-using-latent-space-5qpvo9mo7v4o/v1"} {"@context":"https://schema.org","@id":"https://www.protocols.io/view/target-specific-peptide-design-using-latent-space-d4ac8saw#article","@type":"Article","author":{"@type":"Person","affiliation":"Dev","name":"Protocols Importer"},"dateModified":"2024-05-31T08:10:30Z","datePublished":"2024-05-31T08:10:30Z","description":"Target specific peptide design using latent space approximate trajectory collector\n. Despite the preva. Read full protocol, steps, and materials on protocols.io","headline":"Target specific peptide design using latent space approximate trajectory collector\n V.1","image":{"@type":"ImageObject","url":"https://files.protocols.io/webapp/images/q2ckeg/meta/protocolsio.png"},"mainEntityOfPage":{"@id":"https://www.protocols.io/view/target-specific-peptide-design-using-latent-space-d4ac8saw#webpage"},"publisher":{"@id":"https://www.protocols.io/#org"}} var WebappBundlePath = "https:\/\/files.protocols.io\/webapp\/bundles\/production-afd2742\/"; var AMPLITUDE_API_KEY="c250ed1d862cb9c01587e1f779a32c9";var FFMPEG_HOST="https://ffmpeg.protocols.io";var FILES_CDN_URL="https://files.protocols.io";var FILES_S3_BUCKET="protocols-io-files";var FILES_S3_PREFIX="external";var GA_MEASUREMENT_ID="G-33ZGV5CT0B";var GOOGLE_CLIENT_ID="182746271041-rdtjk0b1h9706r0fgpq1o2h55lgbo8un.apps.googleusercontent.com";var HAS_SSR= false ;var HOST_ROLE= 1 ;var HOST_ROLES={"HOST_DEV":2,"HOST_LOCAL":3,"HOST_PROD":1};var IMAGE_BASE_PATH="https://files.protocols.io/webapp/images/q2ckeg/";var NATS_SERVER="wss://ws.protocols.io";var ORCID_CLIENT_ID="APP-7405TP4958GFSZXV";var ORCID_URL="https://orcid.org/oauth/authorize";var RECAPTCHA_SITE_ID="6LeMF6YUAAAAAOYzOqfc9Ml3PdTgIzO1oDdIwCYc";var SITE_URL="https://www.protocols.io";var SPRINGERNATURE_CLIENT_ID="protocolsio";var SPRINGERNATURE_REDIRECT="https://www.protocols.io/api/v1/auth/springernature/authcallback";var SPRINGERNATURE_URL="https://idp.springernature.com";var STRIPE_PUB_KEY="pk_live_51PfMxdRshFFmaQRVGeDsSX7NFFLMkMuqr17SxP6JcJuieglmQYHPgM7cz0XdO91IEVP9k4E4MC7PZB2ATyuuaOy800ivYpRURi";var UIPE="wc05D1v3cmNUzSbgJrtE4b2Tmq8MTTxeLA31r0RcNxA=";var VPC_ALLOW_REGENTS_LINKING= false ;var VPC_DISABLED_INVITE_COLLEAGUES= false ;var VPC_DISABLED_PUBLISHING= false ;var VPC_DISABLED_SIGN_UP= false ;var VPC_DISABLED_WORKSPACE_CREATION= false ;var VPC_EXTERNAL_STORAGES= null ;var VPC_FORWARDED_VIEW_URL_PREFIX="";var VPC_MAIN_CLOUD_URL="https://www.protocols.io";var VPC_REQUIRE_SIGN_IN= false ;var VPC_USE_MAIN_GLOBAL_SEARCH= false ;var WEBAPP_VERSION="production-afd2742";var __stripeGlobal= null ;var cookie_session_guid="7F3CDAEC5BAF11F18D2F0A58A9FEAC02";var gosessid="7F3CD92D5BAF11F18D2F0A58A9FEAC02";var is_premium= false ;var loadedAmplitude= false ;var loadedGA= false ;var logged_in= false ;var session_guid="";var show_loader= true ;var user_theme="default"; var is_grecaptcha_loaded = false; if (!Element.prototype.matches) Element.prototype.matches = Element.prototype.msMatchesSelector; if (!Element.prototype.closest) Element.prototype.closest = function (selector) {var el = this; while (el) {if (el.matches(selector)) return el; el = el.parentElement;}}; .noscript-container { margin: 0 auto; width: 400px; text-align: center; margin-top: 150px; } protocols.io requires JavaScript to be enabled in the browser.
Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.
My notes (saved in your browser only)
Ask this paper
Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.
Source provenance
- europepmc
- last seen: 2026-05-20T01:45:00.602351+00:00
- unpaywall
- last seen: 2026-05-28T02:00:01.590549+00:00
License: CC-BY-4.0