Live-cell quantitative monitoring reveals distinct, high-affinity Gβγ regulations of GIRK2 and GIRK1/2 channels

Live-cell quantitative monitoring reveals distinct, high-affinity Gβγ regulations of GIRK2 and GIRK1/2 channels | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Live-cell quantitative monitoring reveals distinct, high-affinity Gβγ regulations of GIRK2 and GIRK1/2 channels Reem Handklo-Jamal , Tal Keren Raifman , View ORCID Profile Boris Shalomov , Patrick Hofer , Uri Kahanovitch , Theres Friesacher , Galit Tabak , Vladimir Tsemakhovich , Haritha P. Reddy , Orna Chomsky-Hecht , Debi Ranjan Tripathy , Kerstin Zuhlke , View ORCID Profile Carmen W. Dessauer , Enno Klussmann , View ORCID Profile Yoni Haitin , Joel A. Hirsch , View ORCID Profile Anna Stary-Weinzinger , Daniel Yakubovich , View ORCID Profile Nathan Dascal doi: https://doi.org/10.1101/2025.10.15.682510 Reem Handklo-Jamal 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tal Keren Raifman 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Boris Shalomov 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Boris Shalomov Patrick Hofer 3 Department of Pharmaceutical Sciences, Division of Pharmacology and Toxicology, University of Vienna , Josef-Holaubek-Platz 2, 1090 Vienna, Austria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Uri Kahanovitch 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Theres Friesacher 3 Department of Pharmaceutical Sciences, Division of Pharmacology and Toxicology, University of Vienna , Josef-Holaubek-Platz 2, 1090 Vienna, Austria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Galit Tabak 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vladimir Tsemakhovich 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Haritha P. Reddy 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Orna Chomsky-Hecht 4 Department of Biochemistry & Molecular Biology, School of Neurobiology, Biochemistry and Biophysics, George S. Weiss Faculty of Life Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Debi Ranjan Tripathy 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel 4 Department of Biochemistry & Molecular Biology, School of Neurobiology, Biochemistry and Biophysics, George S. Weiss Faculty of Life Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kerstin Zuhlke 5 Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC) , Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Carmen W. Dessauer 6 Department of Integrative Biology and Pharmacology, University of Texas Health Science Center , Houston, Texas, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Carmen W. Dessauer Enno Klussmann 5 Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC) , Berlin, Germany 7 DZHK (German Centre for Cardiovascular Research) , partner site Berlin, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yoni Haitin 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel 2 Sagol School of Neuroscience, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yoni Haitin Joel A. Hirsch 2 Sagol School of Neuroscience, Tel Aviv University , Tel Aviv, Israel 4 Department of Biochemistry & Molecular Biology, School of Neurobiology, Biochemistry and Biophysics, George S. Weiss Faculty of Life Sciences, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anna Stary-Weinzinger 3 Department of Pharmaceutical Sciences, Division of Pharmacology and Toxicology, University of Vienna , Josef-Holaubek-Platz 2, 1090 Vienna, Austria Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anna Stary-Weinzinger For correspondence: dascaln{at}tauex.tau.ac.il danielya{at}ariel.ac.il anna.stary{at}univie.ac.at Daniel Yakubovich 8 The Adelson School of Medicine, Ariel University , Ariel 4077625, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: dascaln{at}tauex.tau.ac.il danielya{at}ariel.ac.il anna.stary{at}univie.ac.at Nathan Dascal 1 Department of Physiology and Pharmacology, Faculty of Health and Medical Sciences, Tel Aviv University , Tel Aviv, Israel 2 Sagol School of Neuroscience, Tel Aviv University , Tel Aviv, Israel Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nathan Dascal For correspondence: dascaln{at}tauex.tau.ac.il danielya{at}ariel.ac.il anna.stary{at}univie.ac.at Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract G i/o protein-coupled receptors (GPCRs) inhibit cardiac and neuronal excitability via G protein-activated K + channels (GIRK), assembled by combinations of GIRK1 - GIRK4 subunits. GIRKs are activated by direct binding of the Gβγ dimer of inhibitory G i/o proteins. However, key aspects of this textbook signaling pathway remain debated. Recent studies suggested no G i/o -GIRK pre-coupling and low (>250 µM) Gβγ-GIRK interaction affinity, contradicting earlier sub-µM estimates and implying low signaling efficiency. We show that Gγ prenylation, which mediates Gβγ membrane attachment required for GIRK activation, also contributes to the Gβγ-GIRK interaction, explaining the poor affinity obtained with non-prenylated Gβγ. Using quantitative protein titration and electrophysiology in live Xenopus oocytes, Gβγ affinity for homotetrameric GIRK2 ranged from 4-30 µM. Heterotetrameric GIRK1/2 showed a higher Gβγ apparent affinity due to unique Gβγ-docking site (anchor) in GIRK1, which enriches Gβγ at the channel. Biochemical approaches and molecular dynamic simulations revealed that the Gβγ anchor is formed by interacting N-terminal and distal C-terminal domains of the GIRK1 subunits, distinct from the Gβγ-binding “activation” site(s) underlying channel opening. Thus, the affinity of Gβγ-GIRK interaction is within the expected physiological range, while dynamic pre-coupling of Gβγ to GIRK1-containing channels through high-affinity interactions further enhances the GPCR-G i/o -GIRK signaling efficiency. Introduction G protein-activated inwardly rectifying K + channels (GIRK; Kir3) mediate inhibitory effects of G i/o protein-coupled receptors (GPCRs), controlling neuronal and cardiac excitability; GIRK malfunction is linked to neurological, cardiac and endocrine disorders 1 – 4 . GIRKs form homotetramers (GIRK2, GIRK4) or heterotetramers (GIRK1/2, 1/4, 1/3, 2/3), differing in tissue distribution and gating properties. Homotetrameric GIRK2 is best characterized in molecular terms, including a crystal structure in complex with Gβγ 5 . GIRKs are activated by direct, cooperative binding of up to 4 molecules of Gβγ 6 – 10 ( Fig. 1a ). This membrane-delimited process requires posttranslational Gγ prenylation, essential for Gβγ accumulation at the plasma membrane (PM) 11 and GIRK activation 12 , 13 . Download figure Open in new tab Fig. 1. Lipid modification of Gγ is essential for GIRK activation and important for GIRK-Gβγ interaction. a , scheme of Gβγ activation of the GIRK2 channel. An agonist-bound GPCR (m2R) interacts with the Gα i/o βγ heterotrimer (Gα i1 β 1 γ 2 , PDB: 1gp2), catalyzing the GDP-GTP exchange at Gα i/o and its separation from Gβγ. Up to four Gβγ molecules bind sequentially to GIRK2. Channel opens when all four Gβγ-binding sites are occupied. The scheme shown represents the WTM model for the case of constant PIP 2 and Na + concentrations. b , whole-cell currents in oocytes expressing GIRK2 and m2R without Gβγ (left), with Gβγ (middle), or with Gβγ C68S (right). Switching from a low-K to a high-K external solution (here 96 mM [K + ] out ) reveals I basal . ACh (10 µM) elicits I evoked , and then GIRK is blocked by 2.5 mM Ba 2+ , revealing the non-GIRK background current. RNA doses (ng/oocyte) were: m2R, 1; GIRK2, 2; Gβ, 5; Gγ or Gγ C68S , 2. c, d , only Gβγ, but not Gβγ C68S , increased I basal ( c ) and abolished I evoked ( d ). Statistics: Kruskal-Wallis test with Dunn’s multiple comparison vs. control (GIRK2+m2R). One experiment, representative of two. e , linear presentation of G1NC, G2NC and the truncated constructs. The transmembrane (TM) domains were replaced by a linker. f, purified prenylated His-Gβγ WT , captured on Ni-NTA beads, pulls down various [ 35 S]Met-labeled ivt proteins better than the non-prenylated Gβγ C68S . Top , Coomassie staining of eluted proteins. Ni-NTA beads bound equal amounts of His-Gβγ and His-Gβγ C68S . Middle , autoradiogram of a separate gel of 1/60 th of the initial reaction mix (input). Bottom , autoradiogram of Gβγ-bound ivt proteins eluted from the beads (same gel as in upper image). Full gels are shown in Supplementary Fig. 2. g , summary of binding to Gβγ of ivt proteins (% of input of the same protein). Statistics for binding to His-Gβγ vs. His-Gβγ C68S : unpaired t-test or Mann-Whitney test (for G1NC). GPCR-Gα i/o βγ-GIRK is an archetypal G protein-mediated cascade. The coupling between GPCR and Gα i/o βγ varies by receptor, G protein, cell type, and location, ranging from collision-coupling (e.g., muscarinic m2 receptor (m2R) 14 – 17 ) to precoupling within dynamic multiprotein complexes (e.g., GABAB receptor with G i/o and GIRK 18 – 20 ), or a combination of both modes within protein-enriched membrane "hot spots" 21 , organized by specific scaffolds 22 or driven by low-affinity protein interactions 23 . Controversies linger regarding the affinity, specificity, and efficiency of Gαβγ-GIRK coupling. Early in vitro measurements of GIRK interaction with prenylated Gβγ yielded dissociation constants (K d ) between 50-800 nM 8 , 24 , comparable to other Gβγ interactors (typically 3 nM to 3 µM; Supplementary Table 1). Contrastingly, an NMR study reported a Kd of 250 µM for the interaction of non-prenylated Gβγ with GIRK1’s truncated cytosolic domain 25 . Wang, Touhara, MacKinnon and colleagues analyzed Gβγ activation of purified recombinant GIRK2 in-depth, while controlling the Gβγ surface density by titrating a non-prenylated His-tagged Gγ into GIRK2 and NTA lipid-containing bilayers. Their studies revealed high cooperativity of Gβγ binding and its allosteric enhancement by Na + and PIP 2 10 , 15 , 26 , 27 . The resulting model, termed here WTM model, postulated sequential Gβγ binding to GIRK2, with channel opening when all four Gβγ sites are occupied 10 , 15 ( Fig. 1a ). Unexpectedly, binding of the first Gβγ showed an exceptionally low affinity, with K d ∼1.9 mM at [Na + ]=0 and ∼300 µM at saturating [Na + ] 10 . (Due to cooperativity, the affinity increases for subsequent Gβγ bindings; Supplementary Table 2). Low affinity entails inefficient signaling. With a K d >250 µM, GIRK activation (10-80%, depending on intracellular Na + concentration, [Na + ] in ) would require free surface Gβγ exceeding 1200 µm -2 (molecules/µm 2 ) 10 , hundredfold higher than the 2-10 µm -2 GIRK channel density in PM of neurons or atrial myocytes 16 , 28 . While there is no evidence for such massive accumulation of Gαβγ around GIRKs, it could theoretically occur in membrane “hot spots”. Alternatively, higher affinity or dynamic (reversible) GIRK-G protein preassociation could enable fast and efficient signaling 29 . Several studies suggested preassociation of GIRKs with Gβγ or Gαβγ heterotrimers 18 , 30 – 35 , while others support pure collision coupling 10 , 16 , 26 . Subunit-specific differences in GIRK-Gβγ interaction and gating may play a role. GIRK1, but not GIRK2, recruits Gβγ to the PM; the unique cytosolic distal C terminal segment of GIRK1 (G1-dCT) is essential for Gβγ recruitment 36 . We proposed that G1-dCT is part of a Gβγ-docking site (Gβγ anchor) that facilitates high-affinity, dynamic pre-association of GIRK1/2 with Gβγ 4 , 17 , 36 – 38 . However, the exact composition and interaction mode of the Gβγ-anchor remain unclear. Here we show that, besides its role in Gβγ attachment to the PM, Gγ’s prenylation directly contributes to GIRK-Gβγ interaction. We demonstrate distinct, low-micromolar interaction affinities of Gβγ with GIRK2 and GIRK1/2 in a living cell, the Xenopus oocyte, and determine the composition of the GIRK1’s Gβγ anchor and its role in higher apparent affinity of GIRK1/2 compared to GIRK2. Results Lipid modification of Gγ is essential for GIRK activation and important for GIRK-Gβγ interaction All high-affinity estimates of Gβγ binding to GIRKs were obtained using prenylated Gβγ. We hypothesized that Gγ’s prenylation enhances Gβγ-GIRK interaction, as observed in Gβγ interactions with GPCRs, Gα, adenylyl cyclase and phospholipase Cβ 39 – 45 (Supplementary Table 1). In cells, the prenyl (geranylgeranyl in Gγ 2 ) moiety, Gγ prenyl , is attached to Cys68 within the C-terminal CAAX motif, while the remaining residues are cleaved 11 . To assess the role of prenylation we used the non-prenylated mutant Gγ C68S that associates with Gβ 42 ; however, Gβγ C68S fails to activate GIRK channels in excised PM patches 12 , 13 . We expressed GIRK2 channels with m2R (adjusted to maximize I evoked 17 ) and Gβ 1 γ 2 (Gβγ) or Gβγ C68S in Xenopus oocytes and measured whole-cell basal (I basal ), agonist (acetylcholine; ACh)-evoked (I evoked ), and Gβγ-induced (I βγ ) GIRK currents in high-K + solutions. As reported 37 , GIRK2 had a small I basal , which was enhanced 4-8-fold by ACh (by activating the endogenous Gα i/o βγ) and 30-60 fold by coexpressing nearly-saturating doses of Gβγ. In contrast, the non-prenylated Gβγ C68S neither activated GIRK nor affected I evoked ( Fig. 1b-d , Supplementary Fig. 1a). To assess PM localization, we immunostained Gβ in oocytes’ excised giant membrane patches (GMP) 35 , 46 using wild-type (WT) Gβ or an N-terminally myristoylated Gβ (myr-Gβ). Only WT Gγ (Gγ WT ), but not Gγ C68S , supported GIRK2 activation and, correspondingly, PM enrichment of WT-Gβ and myr-Gβ (Supplementary Fig. 1b-d). These results confirm that prenylation of Gγ is essential for PM attachment of Gβγ and GIRK2 activation; but is it also involved in Gβγ interaction with GIRKs? We examined the interaction of purified, His-tagged Gβγ and Gβγ C68S with in vitro translated ( ivt ) Gβγ-binding proteins: Gα i3 ; phosducin; cytosolic domains of GIRK1 and GIRK2 (G1NC and G2NC, respectively); and their truncated versions, G1NC ΔdCT and G2NC trunc ( Fig. 1e ). G1NC is a fusion protein of N- and C-terminal domains of GIRK1 (G1-NT and G1-CT). G1NC ΔdCT lacks the G1-dCT and binds Gβγ much weaker than G1NC 36 (Supplementary Fig. 2). G2NC trunc lacks the distal segments of the N- and C-terminal domains (G2-NT and G2-CT, respectively), as in structural and bilayer studies 5 , 26 , 47 , 48 . All ivt proteins bound Gβγ. Remarkably, lack of prenylation dramatically reduced Gβγ interaction with Gα i3 and phosducin, corroborating previous reports 39 – 41 , and with all GIRK constructs ( Fig. 1f,g ), suggesting that Gγ prenylation directly contributes to Gβγ-GIRK interaction. Estimating Gβγ density in PM using calibrated fluorescence and quantitative Western blotting We aspired to quantitatively analyze the membrane-delimited GIRK-Gβγ interaction in intact cells, using prenylated Gγ. A major challenge was to accurately calibrate protein surface density. To this end, we extended our previously developed calibration methods in Xenopus oocytes 17 , 38 , which use two independent approaches. The calibrated fluorescence (CF) approach measures the surface density of yellow, cyan or Split-Venus fluorescent proteins (YFP, CFP or SpV; collectively xFP), using xFP-labeled channels as molecular calipers. We used Gβγ-activated xFP-GIRK1/2 38 , and additionally the constitutively active homotetrameric IRK1-xFP (usually IRK1-YFP; Fig. 2a,b ). Calibration involved expressing these channels at varying RNA doses, measuring whole-cell currents, and calculating the surface density of functional channels based on open probability (P o ), single-channel current (i single ) and cell’s surface area 49 ( Eqn. 1 in Methods, Supplementary Fig. 3, Supplementary Table 3). YFP surface density was calculated assuming two or four YFP molecules per YFP-GIRK1/2 or IRK1-YFP channel, respectively. To avoid artifacts arising from any non-functional channels, we used channels’ RNA doses in the 0.01-1 ng range, ensuring a linear relationship between fluorescence and whole-cell current and, accordingly, the calculated YFP surface density ( Fig. 2a ). Deviations were observed only at high levels of YFP-GIRK1/2 (5 ng RNA; Supplementary Fig. 6a). Additionally, we compared the calibration with both YFP-GIRK1/2 and IRK1-YFP in the same experiment ( Fig. 2a,b ). The relationship between fluorescence and calculated YFP surface density was almost identical with both calipers. Download figure Open in new tab Fig. 2. Estimating Gβγ density in PM using calibrated fluorescence (CF) and quantitative Western blotting (qWB). In oocyte experiments RNAs of YFP-Gγ and Gβ were injected at a constant ratio. a, calibrating surface YFP-Gγ density with YFP-GIRK1/2 coexpressed with Gβγ (5:2 ng RNA/oocyte) or IRK1-YFP. Amounts of channel RNA are shown near symbols. Surface density of channel-associated YFP was estimated from whole-cell currents. YFP fluorescence (in arbitrary units, AU) was measured from confocal images of intact oocytes (right panel). b, calibration with either IRK1-YFP or YFP-GIRK1/2 gives similar estimates of surface density of Gβ· YFP Gγ (same experiment in a ). Data points represent individual oocytes. Inset shows representative oocytes (red symbols). c, measuring PM-attached Gβ (20 plasma membranes per lane) using WB with a Gβ antibody that well recognizes both endogenous and expressed Gβ 38 , from naïve (uninjected) oocytes, or injected with GIRK2 RNA (2 ng) without or with Gβγ (5:2 ng RNA/oocyte). Lanes 4-7: calibration with recombinant Gβγ (0.25-2.5 ng/lane). d, estimating the amounts of Gβγ in PMs for lanes 1-3 from the calibration plot drawn using linear regression of data from lanes 4-7. e, qWB-estimated surface density of Gβ, coexpressed with either Gγ or YFP-Gγ, is similar. Net amounts of Gβ were calculated in each experiment by subtracting the Gβ level of GIRK2-only expressing oocytes. Statistics: unpaired t-test. f , comparing the estimated levels surface density of YFP-Gγ (by the CF approach) and Gβ (by the qWB approach. Data with Gγ and YFP-Gγ were pooled). Statistics: unpaired t-test. g , representative confocal images of GMPs from oocytes expressing Gβ, YFP-Gγ, and GIRK1/2 or GIRK2. Amounts of Gβ RNA are shown. h,i , Gβ levels in GMPs and YFP-Gγ levels in intact oocytes are linearly correlated. Protein levels induced by different RNA doses were normalized to 5 ng Gβ in each experiment. Numbers of experiments and cells are shown in Supplementary Table 5. Concomitantly, we expressed Gβ· YFP Gγ (Gβ and N-terminally labeled YFP-Gγ) in separate groups of oocytes, measured YFP fluorescence at the oocyte’s perimeter, and converted it to YFP-Gγ surface density with each caliper. The estimates of YFP-Gγ with both calipers showed strong linear correlation with a slope of 0.9 ( Fig. 2b ), validating the calibration protocol. The CF procedure with Gβ· YFP Gγ monitors YFP-Gγ rather than Gβ. We directly assessed the surface density of Gβ using the independent approach 38 , quantitative Western blotting (qWB) of manually separated oocyte plasma membranes. We measured PM-associated Gβ with a Gβ antibody, using purified recombinant Gβγ for calibration ( Fig. 2c,d ). The PM density of the endogenous oocyte Gβ was 30±13 µm -2 , consistent with previous estimates (Supplementary Table 4) and comparable to ∼40 µm -2 in HEK cells 50 . Expressed Gβ surface levels were similar with either coexpressed Gγ or YFP-Gγ ( Fig. 2e , Supplementary Table 4). Overall, expressed surface Gβ (with 5 ng Gβ RNA) measured by qWB was 35±9 µm -2 (n=6), about 2.5-fold lower than surface YFP-Gγ estimated by CF (91±19 µm -2 , n=7, Fig. 2f ). The difference is probably not related to methodology, because previously both CF and qWB gave similar estimates of 22-28 µm -2 for a YFP-labeled Gβ 38 . Thus, evaluating YFP-Gγ may overestimate the coexpressed Gβ’s surface density, possibly because YFP-Gγ associates with endogenous Gβ, or exists as a separate protein 51 , 52 . Therefore, we tested a variety of C- or N-terminally xFP-fused Gβ constructs (Supplementary Fig. 4). However, they yielded partial or no GIRK2 activation, and usually poorly activated GIRK1/2. SpV-Gβγ activated both GIRK1/2 and GIRK2 but induced smaller currents than WT-Gβγ. Only Gβ· YFP Gγ activated GIRK channels like the WT-Gβγ 36 . We next varied expression levels of Gβ· YFP Gγ and examined changes in surface densities of YFP-Gγ in intact oocytes and Gβ in GMPs ( Fig. 2g ). Reassuringly, there was a linear correlation between surface levels of Gβ and YFP-Gγ with either GIRK2 or GIRK1/2 channels coexpressed ( Fig. 2h,i ). Thus, RNA dose-dependent changes in surface YFP-Gγ reflect corresponding changes in surface Gβ. Consequently, we routinely used Gβ· YFP Gγ in the following experiments. Affinity of Gβγ-GIRK2 interaction is in the low µM range We investigated the dose-dependent activation of GIRK2 by Gβ· YFP Gγ using the CF approach. We expressed GIRK2 at a low density, with a range of Gβ· YFP Gγ RNA doses. Following calibration ( Fig. 3a ), we quantified surface Gβ· YFP Gγ density in oocytes expressing GIRK2 and Gβ· YFP Gγ and then measured single-channel P o in cell-attached patches of the same oocytes ( Fig. 3b-d ). The activation of GIRK2 was steeply Gβ· YFP Gγ dose-dependent, with an initial slope of almost 3 on log-log coordinates ( Fig. 3e ). This indicates the requirement for at least 3 Gβγ molecules to open the channel, corroborating the WTM model 10 ( Figs. 1a , 3e ). Therefore, we analyzed the dose-response data using the WTM model version adjusted for real-cell conditions 15 ( Fig. 3e , Supplementary Fig. 8a #2, Methods Eqn. 5 ) and, for comparison, the familiar but mechanistically less informative Hill equation ( Eqn. 4 ). We added to the equations a constant component (c) corresponding to I basal . To convert the two-dimensional surface density to concentration we used a standard procedure 10 , 15 , 38 , 53 assuming a submembrane 10 nm thick interaction volume. Download figure Open in new tab Fig. 3. Coexpressed Gβ· YFP Gγ activates single GIRK2 channels with low-µM apparent affinity. P o and Gβ· YFP Gγ expression were measured in the same oocytes, injected with RNA of GIRK2 (25 or 50 pg/oocyte), Gβ (0.2-20 ng/oocyte) and YFP-Gγ (40% of Gβ RNA). a , calibration of surface density of YFP using YFP-GIRK1/GIRK2 (1 ng RNA each) coexpressed with WT-Gβγ (5:2 ng RNA, respectively). b-d , representative confocal images of intact oocytes, and cell-attached patch records from these oocytes. e , changes in P o vs. estimated Gβ· YFP Gγ PM density. Each circle represents P o measurement in a separate patch. Low P o observed in two patches from one oocyte (grey circles) with high surface Gβ· YFP γ (290 µm -2 ) was attributed to Gβγ-induced desensitization, as reported previously for high [Gβγ] for GIRK1/4 and GIRK1/2 9 , 46 . These patches were excluded from fit. Lines show fits to Hill equation and to the WTM model, the latter with either fixed (µ=0.3) or free cooperativity factor µ. Inset (right) shows the log(P o )-log[Gβ· YFP Gγ] plot for the lowest Gβ· YFP Gγ expression levels. The slope of the linear regression (black line) was 2.93. Hill coefficient (n H ) in the Hill plot fit was 2.37. The average Gβ· YFP Gγ density at 5 ng Gβ RNA was 39.7±6 μm - 2 (n=12 oocytes). f , K d and P o,max values from fits shown in e. For a full set of WTM fit parameters, see Supplementary Table 6. g , simulated Gβγ dose-response curves with µ=0.3 and c=0.03, P o,max =0.19, K d =17.3 µM from the WTM fit of our data shown in f , compared to values reported by Wang et al. 10 : K d =1.9 mM for [Na + ] in =0 and K d =300 µM for high [Na + ] in (>20 mM). For visualization purposes, P o values from patches with similar Gβ· YFP Gγ levels were pulled and presented as mean±SEM. Fitting the data with the WTM model ( Fig. 3e ) yielded cooperativity factor for each successive Gβγ binding (µ) of 0.44 and dissociation constant (K d ) of 44 Gβγ µm -2 (7.4 µM). Fixing µ=0.3 as in Touhara et al. 15 , yielded a K d of 17.3 µM, and Hill equation fit yielded a K d of ∼4 µM ( Fig. 3f ). This is much lower than the 300 µM measured in bilayers even at saturating [Na + ] of >20 mM 10 , as highlighted with simulated dose-response curves in Fig. 3g . Similar K d values were obtained for whole-cell currents of GIRK2 or HA-tagged GIRK2 HA (which is activated by Gβγ like GIRK2 36 , 37 , Supplementary Fig. 1a). Fitting with WTM model (with fixed µ, to reduce the number of free parameters) yielded K d of ∼11 µM with µ=0.44 and ∼31 µM with µ=0.3 ( Fig. 4f ; Supplementary Table 6). In one experiment we compared WT-GIRK2 and truncated GIRK2 (as used in lipid bilayers); they showed similar Gβγ sensitivity (Supplementary Fig. 5). Download figure Open in new tab Fig. 4. GIRK2 and dCT-truncated GIRK1 show lower apparent affinity to Gβγ than GIRK1/2. a-d, GIRK2 HA was used in these experiments. Gβ:YFP-Gγ RNA ratio was 2:1. RNA doses of GIRKs and WTM fit parameters are shown in insets in b-d. Surface density of YFP was calibrated using IRK1-YFP. Currents were measured in 24 mM [K + ] out . a-c, dose-dependent activation of GIRK2 HA homotetramers and GIRK1/2 HA heterotetramers by Gβ· YFP Gγ (experiment #4). a , examples of confocal images in oocytes expressing Gβ· YFP Gγ with GIRK1/2 HA or GIRK2 HA . b, dose-dependent activation of GIRK1/2 HA and GIRK2 HA by Gβ· YFP Gγ. Each point represents an individual oocyte. Currents were normalized to the maximal I βγ (I max , Supplementary Table 6) and fitted to the WTM model (with µ = 0.3). The differences between the fitted K d were significant (F(1, 81)= 18.95, p<0.0001). See additional analysis in Supplementary Fig. 7a. c , results of the same experiment were analyzed for groups of oocytes according to the amount of Gβ RNA (shown near each point). Data are presented as mean ± SEM of I βγ and YFP-Gγ; numbers of oocytes are shown in Supplementary Table 5. d , dose-dependent activation of GIRK1/2 HA and GIRK1 ΔdCT /2 HA by Gβ· YFP Gγ. (Experiment #7; additional details in Supplementary Fig. 7b). Analysis and presentation of data are as in b. The differences between fitted K d were significant: F(1, 103)=14.18, P=0.0003). e, f , summary of parameters of the WTM fit with fixed µ=0.3 for all experiments ( e ; statistics: Kruskal-Wallis test) and with µ=0.3 or µ=0.44, presented as mean±SEM ( f ). See Supplementary Table 6 for full details. g , simulation of GIRK1/2 HA activation by Gβγ with a range of K d values (solid lines) with the cooperative models (Supplementary Fig. 8a). The simulated curves are superimposed on data from experiments #4 (closed circles) and #7 (open circles). More details in Supplementary Fig. 8c. GIRK1/2 vs. GIRK2: higher apparent affinity to Gβγ and the role of Gβγ docking to GIRK1 Heterologously expressed GIRK1/2 has a high, Gβγ-dependent I basal , contrasting the smaller, Gβγ-independent I basal of homotetrameric GIRK2 35 , 37 , 46 , 54 , 55 . Gβγ recruitment 36 and high I basal of GIRK1/2 and GIRK1/4 require an intact G1-dCT 37 , 55 , 56 , suggesting that Gβγ docking by GIRK1 increases the local concentration of Gβγ around GIRK 4 , 17 , 36 , 38 . We hypothesized that this may also render higher apparent Gβγ affinity for GIRK1/2 compared to GIRK2. We previously observed GIRK1/2 activation by expressing Gβγ at relatively low densities (5-50 µm -2 ) 38 . Here, we compared activation of GIRK2 and GIRK1/2 by Gβ· YFP Gγ in the same experiment ( Fig. 4a-c ). Surface levels of YFP-Gγ and, subsequently, GIRK currents were measured in individual intact oocytes. Fitting these data with the WTM model revealed a significant difference between K d of GIRK2 and GIRK1/2 (45 and 9 µM, respectively, with µ=0.3, p=<0.0001; Fig. 4b , Supplementary Fig. 7a). Similar K d values were obtained for data grouped according to the RNA dosage ( Fig. 4c ). On average, the K d of GIRK1/2 was about 6-fold lower than GIRK2 (∼5.5 µM vs. ∼31 µM, p=0.027, Fig. 4e,f , Supplementary Table 6). We also observed an ∼8-fold difference in K d of GIRK2-CFP and GIRK1/2-CFP (Supplementary Fig. 6). GIRK1/2 also exhibited the expected higher I basal than GIRK2. The basal fraction (c) was ∼0.26 in GIRK1/2 and 0.02-0.03 in GIRK2 ( Fig. 4e,f ). To investigate the role of Gβγ-anchor, we compared the Gβγ dose-dependence of GIRK1/2 to GIRK1 ΔdCT /2. GIRK1 ΔdCT /2 lacks the Gβγ-anchor, does not recruit Gβγ and has a reduced I basal 36 . Remarkably, the K d of GIRK1 ΔdCT /2 was 9-fold higher compared to GIRK1/2 ( Fig. 4d ; p=0.0003) and 3.8-fold higher in another experiment (Supplementary Fig. 7c; p=0.0009). Thus, GIRK1’s Gβγ-anchor contributes to the high apparent Gβγ affinity of GIRK1/2. We added the c parameter to the original WTM model to account for I basal . Instead of fitting c, I basal can be mechanistically explained and calculated using algorithms utilizing I basal , I evoked and I βγ to estimate basal Gβγ and Gα in GIRK1/2 microenvironment 17 , 38 . We compared the modified WTM (concerted cooperative), the graded contribution (channel opens with one Gβγ and sequential Gβγ binding progressively increases P o 9 , 57 ), and two non-cooperative models ( Fig. 4g , Supplementary Methods, Supplementary Fig. 8). With each model, we calculated basal Gα, Gβγ and I basal for a range of K d values, and subsequently simulated dose-response curves for expressed Gβγ with µ=0.3. Both cooperative models matched the experimental data with K d between 1-10 µM ( Fig. 4g ). Expectedly, the non-cooperative models predicted lower K d . The cooperative models also provided stable estimates of basal Gα and Gβγ across a wide K d range, 0.1-30 µM (Supplementary Fig. 8). The interactions of Gβγ with the PM and the channel are reversible. Therefore, we expected that removing the cytosolic Gβγ reserve by excising a membrane patch into a Gβγ-free solution would reduce the PM- and GIRK-associated Gβγ, deactivating GIRK channels. We anticipated slower deactivation in channels with a high-affinity Gβγ-anchor. To test this hypothesis, we recorded Gβγ-activated channels in cell-attached patches and then excised them into an ATP and Na + -containing bath solution ( Fig. 5a-d ). GIRK1/2 activity decayed (deactivated) slowly, with 30-50% persisting after 5 minutes ( Fig. 5a,d ). The decay followed a single exponent with a time constant (τ) of >2 min and a non-deactivating fraction (C) of 0.34. In contrast, GIRK2 and GIRK1 ΔdCT /2 exhibited faster and more complete decay ( Fig. 5b-d ,f). Excising patches into an ATP-free solution, which could deplete PIP 2 in the PM 58 , had a minimal impact on GIRK2 and GIRK1 ΔdCT /2 decay, and slightly affected GIRK1/2 ( Fig. 5e,f ). This suggests that GIRK deactivation is mainly governed by the depletion of Gβγ associated with or surrounding the channel, rather than PIP 2 depletion. Download figure Open in new tab Fig. 5. Different patterns of deactivation of GIRK2 and GIRK1/2 after patch excision and the role of G1-dCT. Channels were expressed at low densities, with a high dose of Gβγ or SpV-Gβγ (5 ng Gβ and 1 ng Gγ). a , representative recording of GIRK1/2. Top , the complete original recording that lasted 13.5 min. After ∼4 min in cell-attached mode, the patch was excised into bath solution containing 2 mM ATP and 6 mM NaCl, causing a gradual decay of activity. Bottom , zoom on 20 s segments of the record during the indicated times before and after excision. b , c , similar stretches from recordings of representative GIRK1 ΔdCT /2 and GIRK2 recordings. d , time course of deactivation after excision summarized as NP o within consecutive 60 s segments of record, normalized to NP o during the last minute before excision. (NP o is a measure of total activity in the patch, i.e. number of channels times P o ). Each point is mean±SEM, with number of patches shown near each symbol. Lines show single-exponential fits; fitting with two exponents did not produce better results (exemplified for GIRK1/2 with ATP, black line). e , similar results were obtained when the patches were excised into an ATP-free solution. f , comparison of exponential fit parameters for the three channel types, with and without ATP. τ is the time constant of the exponential decay and C is the extrapolated non-deactivating fraction. G1-NT and G1-dCT form a Gβγ-binding site and contribute to channel’s interaction with Gγ’s prenylation tail, Gγ prenyl Although deleting G1-dCT thwarts Gβγ binding, G1-dCT alone does not strongly bind Gβγ 59 , indicating that the Gβγ-anchor includes additional Gβγ-binding segments 36 . To identify these regions, we scanned arrays of overlapping peptides covering the cytosolic domains of GIRK1 and GIRK2 (G1NC, G2NC) for His-Gβγ binding ( Fig. 1e , 6a-c, Supplementary Fig. 9). Scanning revealed three Gβγ-binding segments mainly overlapping the C1 and C3 segments from previous biochemical studies 30 , 59 . Two segments fully (in GIRK2) or partially (in GIRK1) overlapped the Gβγ-binding amino acid (a.a.) clusters from the crystallized GIRK2/Gβγ complex 5 ( Fig. 6d ). Additionally, Gβγ bound segments in G1-NT (a.a. ∼20-50), parts of G1-dCT (a.a. ∼390-440 and ∼485-501), and G2-NT and G2-dCT. Download figure Open in new tab Fig. 6. Peptide array scanning for Gβγ binding sites in the cytosolic domains of GIRKs. a, linear scheme of G1NC incorporating segment names (NT, CT, etc.) and a.a. numbers illustrating the design of the peptide array (b) and the constructs used in pull down experiments of Fig. 7 . b , c, arrays of 25-mer overlapping peptides with a 5 a.a. shift of G1NC (b) and G2NC (c), spotted onto a membrane. Upper images show overlays with purified His-Gβγ, probed with the Gβ antibody (4 experiments for G1NC, 3 for G2NC). Gβγ-binding segments are enclosed within solid-border rectangles. Bottom images show control arrays overlayed with Gβ antibody only (two experiments for each channel). In GIRK2 some non-specific labeling (without Gβγ) was observed in segments designated as Gβγ-binding. The non-specific labeling was weaker and appeared in fewer spots, therefore we have not discarded these spots from the area assigned as Gβγ-binding. d, alignment of rGIRK1 (rat GIRK1) and hGIRK2 (human GIRK2) a.a. sequences used in peptide array scans. The Gβγ-binding segments suggested by peptide arrays are highlighted in yellow (GIRK1) and gray (GIRK2). A weakly labeled potential Gβγ-binding segment in the distal CT of hGIRK2 is labeled with a lighter gray background. Gβγ-binding segments suggested by molecular dynamics (MD) simulations (from Fig. 8 ) are framed by dark red (GIRK1) and blue (GIRK2) rectangles. Amino acids in GIRK2 that make contacts with Gβγ according to the crystal structure of the GIRK2-Gβγ complex, 4KFM 5 , were determined using the Prodigy software ( https://rascar.science.uu.nl/prodigy/ ) and are highlighted in bold red letters. If any of the GIRK1’s Gβγ-binding segments combines with G1-dCT to form the Gβγ-anchor, deleting it from G1NC should reduce Gβγ binding. We used prenylated His-Gβγ to pull-down the full-length ivt G1NC or G1NC with specific segment deletions, and a fusion protein of G1-NT and G1-dCT, G1NdCT ( Fig. 7 ). Gβγ binding was unaffected by the deletion of internal segments C1-C3 and tended to decrease after the deletion of G1-NT (G1CT construct). G1-dCT and G1-NT showed weak and negligible Gβγ binding, respectively. However, both G1NdCT and the fusion of the second half of G1-NT (a.a. 40-84) with G1-dCT bound Gβγ very strongly, suggesting that the GIRK1’s Gβγ-anchor comprises G1-dCT and part(s) of G1-NT. Download figure Open in new tab Fig. 7. Fused G1-NT and G1-dCT of GIRK1 form a high-affinity Gβγ-binding site. a, b, SDS-PAGE autoradiograms of pull-down of [ 35 Met]-labeled ivt G1NC, G1NC-derived constructs and additional controls by His-Gβγ WT from two representative experiments. G1-NT and G1-dCT were fused to Sumo for stability. c , summary of pull-down experiments. Binding of each construct was calculated as percentage of input of that construct in the same experiment. Statistics: One Way ANOVA followed by Dunnet’s multiple comparison method vs. control group, G1NdCT. Statistics for G1NC comparisons are shown in Supplementary Table 7. We conducted coarse-grain molecular dynamics (MD) simulations to further investigate the involvement of G1-NT, G1-dCT and Gγ prenyl in GIRK-Gβγ interactions. These elements are missing from the available high-resolution structures. Creating a system where Gβγ is added ab initio and equilibrates with the channel and PM is challenging. Therefore, the initial system included four Gβγ molecules bound to a G1NC or G2NC tetramer without the PM and bulk Gβγ in the cytosol. We modeled full-length and truncated G1NC and G2NC tetramers complexed with Gβγ using AlphaFold3 and manually added the prenylation tails ( Fig. 8 , Supplementary Fig. 10a). MD simulations accurately captured the two Gβγ-interacting surfaces from the GIRK2-Gβγ crystal structure 5 and predicted additional Gβγ-binding segments. Most of these segments showed excellent (in G2NC) or considerable (in G1NC) agreement with peptide arrays ( Fig. 6d , 8b , Supplementary Fig. 10b), lending credibility to the combined analysis. Further analysis revealed that Gγ prenyl spent 100% of the simulation time interacting with G1NC, mainly with the beginning of G1-NT, as compared to only 6.4% with G2NC ( Fig. 8c,d ). This interaction likely accounts for most of the Gβγ binding to the first NT segment predicted by the MD (compare Fig. 8b and 8c ), explaining the poor Gβγ labeling of a.a. 1-25 in peptide array overlays, where solid support-spotted peptides may be less accessible to Gγ lipid moiety. Additionally, Gγ prenyl also interacted with hydrophobic a.a. in the C-terminus of Gβ (Supplementary Fig. 10c). If PM were present, it would attract Gγ prenyl and reduce its contact time with channel parts; but binding site mapping would remain unaffected. Download figure Open in new tab Fig. 8. MD simulations corroborate the role of G1-NT and G1-dCT in interactions with Gβγ and the prenylation tail, Gγ prenyl . a , the initial AlphaFold 3 models of complexes of G1NC and G2NC with prenylated Gβγ. b, heatmaps illustrating the G1NC and G2NC residues contributing to Gβγ binding. Analysis was carried out on five 1-µs production runs for G1NC and ten for G2NC. Black dots above the bars are placed at 10 a.a. intervals. Darker coloring corresponds to greater overall contacts between the channel and Gβγ across all production runs. The magenta rectangles superimposed onto the heatmaps correspond to the Gβγ-binding segments identified by the peptide arrays ( Fig. 6 ). The cyan rectangle outlines the main Gγ prenyl -binding segment, the beginning of G1-NT. c , heatmaps of interactions of G1NC and G2NC and their truncated versions with Gγ prenyl . % binding is the percentage of time when at least one prenylation tail is bound to the channel. Note that the Gγ prenyl interaction with the most prominent site, a.a. 1-20 of G1-NT (cyan rectangle), is lost after G1-dCT removal. d , the histogram shows % of time spent by G1NC a.a. residues in contact with the Gγ prenyl . e, f , the interaction between G1-NT and G1-dCT in G1NC. A frame with a contact was defined as one in which at least one G1-dCT chain is bound to the G1-NT, with a cutoff of 6 Å. G1-NT andG1-dCT were in contact in 97.3% of the frames in the five runs. The structures of G1NC (e) are shown at the beginning and at the end (1 µs) of a representative run. Areas of contact are highlighted. The heatmap (f) indicates that the main interaction segment in G1-NT is a.a. 25-32. Remarkably, deleting dCT abolished Gγ preny -G1-NT binding ( Fig. 8c ), reinforcing the idea that G1-NT and G1-dCT form a Gβγ-binding unit. Truncating G2NC reduced the Gγ prenyl binding by ∼40%. MD simulations also revealed details of the GIRK1’s NT-dCT structural unit, with segments of a.a. 27-31 (NT) and ∼450-460 (dCT) interacting 97.3% of the simulation time ( Fig. 8e,f ). Notably, this NT-dCT unit is not predicted in the G1NC-Gβγ model by AlphaFold but assembles dynamically during the simulation. Discussion In this study we address two key issues in the GPCR-Gαβγ-GIRK signaling cascade: the Gβγ-GIRK interaction affinity and the subunit-dependent GIRK-Gβγ preassociation. We hypothesized that Gγ prenylation contributes to Gβγ-GIRK interactions and demonstrated that elimination of prenylation thwarts Gβγ interaction with cytosolic domains of GIRK1 and GIRK2 (G1NC and G2NC; Fig. 1 ). Expectedly, PM targeting was also abolished (Supplementary Fig. 1). However, since our Gβγ binding assays were performed in membrane-free detergent solutions, membrane targeting was not involved. The importance of Gγ prenyl in full channel context in PM is supported by higher GIRK2-Gβγ affinity in intact oocytes ( Figs. 3 , 4) compared to non-prenylated Gβγ in bilayers 10 . We conclude that, besides its well-established role in membrane attachment of Gβγ, Gγ prenylation enhances Gβγ-GIRK interaction, as in other Gβγ binding partners 39 – 45 . The mechanism could involve transient interactions of Gγ prenyl with hydrophobic sites in Gβγ’s partner 60 or Gβ itself, stabilizing the conformation favoring Gβγ function 41 , 43 , 45 , 61 . In support, MD simulations reveal interactions of Gγ prenyl with both, specific sites in GIRK1 and GIRK2, and C-terminal hydrophobic residues of Gβ ( Fig. 8 , Supplementary Fig. 10). The dual role of Gγ prenylation complicates the interpretation of in vitro affinity measurements. Measuring GIRK’s K d in excised PM patches with prenylated Gβγ in bath solution grossly overestimates affinity (K d =2-11 nM, Supplementary Table 8) due to Gβγ’s preferential partitioning to the PM. We addressed the challenge of quantitating GIRK activation by prenylated Gβγ in intact cells utilizing Xenopus oocytes, which are exceptionally suitable for accurate titration and monitoring of expression and function of GPCRs, transporters and ion channels 38 , 62 . We constructed Gβγ-GIRK dose-response relationships by varying Gβγ expression and measuring surface densities of Gβγ and GIRK responses. Our results support the WTM model 10 , 15 of collision-coupled, cooperative activation of GIRK2 by four Gβγ molecules. However, our affinity estimates are substantially higher. K d estimates rely on accurate calibrations used to measure Gβγ surface levels. We validated our CF calibrations using two molecular calipers, YFP-GIRK1/2 and IRK1-YFP ( Fig. 2 ). These results, along with previous compatibility tests between CF and qWB methods 38 , enhance confidence in both calibration procedures. The CF approach is advantageous for measuring protein expression and function in individual, intact cells but requires using fluorescently labeled proteins. Disappointingly, xFP-Gβ constructs poorly activated GIRKs, especially GIRK2, calling for caution in using xFP-labeled Gβ in functional studies. Consequently, in most dose-response experiments we used Gβ· YFP Gγ, which activated GIRKs like WT Gβγ. When expressing Gβ· YFP Gγ, the surface densities of Gβ and YFP-Gγ were linearly related, but measuring YFP-Gγ might overestimate coexpressed Gβ, and accordingly the K d , by up to 2.5-fold ( Fig. 2 ). To avoid overinterpretation, we did not apply the YFP-Gγ correction (for measuring YFP-Gγ as a proxy for Gβγ) in our tables and figures. Even before formal curve fitting, the Gβγ-GIRK2 dose-responses clearly show that only 10 to 150 µm -2 of free Gβγ is needed for 10% to 80-90% GIRK2 activation in intact oocytes ( Figs. 3 , 4 ), much less than the >1200 µm -2 predicted by bilayer results 10 . Applying the 2.5-fold YFP-Gγ correction shifts the activation range to 4-60 µm -2 . We propose that the higher affinity that we find is mainly due to Gγ prenylation. Truncation of G2NC somewhat reduces Gβγ binding (Supplementary Fig. 2), but the functional impact appears minor (Supplementary Fig. 5). Interestingly, GIRK2’s I evoked (via m2R) is only 10% of Gβγ-evoked (Supplementary Fig. 1a). Thus, activation of endogenous G i/o (Gα i/o βγ) releases 10-15 molecules/µm -2 of free Gβγ, corresponding to 30-50% of total endogenous Gβγ in oocyte’s PM, ∼30 µm -2 ( Fig. 2 ). Importantly, coexpressing Gα i3 and Gβγ with m2R yields I evoked matching I βγ 63 . Clearly, endogenous G i/o is insufficient to activate all GIRKs; but m2R can activate all channels when enough G i/o is present. Comparing K d for a multistep cooperative reaction is complex, even with the same kinetic model. The K d derived from dose-response data is interdependent with the Gβγ cooperativity factor µ: higher µ gives a lower K d . µ is Na + -dependent 10 but can be considered constant at stable cytosolic [Na + ] 15 . (We consider [Na + ] in in oocytes, 10-20 mM, as close to saturating for GIRK2). Our average K d estimates for GIRK2 are 11 µM with µ=0.44 (from Fig. 3 ) and 31 µM with µ=0.3 15 . These are likely overestimates, for two reasons. First, Hill and WTM models assume ligand excess over receptors. This is uncommon in cellular protein-protein interactions, leading to ligand depletion and K d overestimation: more receptors (GIRK) mean less free ligand (Gβγ) per receptor 64 . This is relevant to our whole-cell experiments, where GIRK2 surface density was 17±5 µm -2 (Supplementary Table 6), comparable to the functional Gβγ range. Second, applying the 2.5-fold YFP-Gγ correction would shift K d to 4-12 µM, quite close to the most accurate in vitro measurement available for prenylated Gβγ, 0.8 µM (interaction with CT of GIRK4, by surface plasmon resonance) 24 . Notably, less Gβγ is needed for GIRK1/2; 50 µm -2 yields full activation ( Fig. 4 ), confirming previous results 38 . The 10-15 Gβγ molecules/µm 2 released by GPCR activation would yield I evoked of about 50% of I βγ ( Fig. 4 ), consistent with experiments 38 . Accordingly, GIRK1/2’s apparent K d from WTM fits is 5-6-fold lower than GIRK2’s. We further analyzed the GIRK1/2 dose-response data by including explicit calculations of Gα and Gβγ needed to produce the observed I basal and I evoked 17 , 38 . Across a broad K d range (0.1 to 10 µM), the two cooperative models ( Fig. 4g ) predicted that both I basal and I evoked could be generated by physiologically relevant amounts of 1-2 Gα and 3-4 Gβγ per channel (Supplementary Fig. 8). This corresponds to less than 40 µm -2 of Gβγ assuming physiological densities of GIRKs (2-10 µm -2 ) 16 , 28 . GIRK1’s Gβγ docking site (anchor) emerges as the major factor determining the higher affinity of GIRK1/2. This is suggested by (i) the 4-9-fold affinity drop in GIRK1 ΔdCT /2, which lacks the main part of the anchor, G1-dCT 36 ( Fig. 4 ); (ii) the fast deactivation after patch excision of GIRK1 ΔdCT /2, mirroring GIRK2, indicating faster Gβγ dissociation ( Fig. 5 ). These results, along with the preservation in GIRK1 ΔdCT of Asn-217 that renders GIRK1 Na + -insensitive 65 , imply a minor role for the differences in Na + -dependence of Gβγ affinity in GIRK1 and GIRK2 27 in our experiments. The anchor probably increases the apparent affinity through local enrichment of Gβγ (see below). We proposed that Gβγ-anchors are distinct from the Gβγ-binding “activation” sites, which induce channel opening 4 and are located at the interface between core-CTs of two adjacent GIRK subunits 5 , 66 , 67 . Removal of G1-dCT preserves maximal Gβγ activation and P o but eliminates Gβγ recruitment and high I basal 36 , suggesting functional separation of docking and activation. Structural separation is suggested by strong Gβγ binding to G1NC that persists after removing major components of the activation site (C1-C3) and even the whole core-CT, leaving only the fused NT and dCT (G1NdCT) ( Fig. 7 ). Thus, the anchor dominates the overall Gβγ affinity of GIRK1’s cytosolic domain and does not include elements from core-CT. Both G1-NT and G1-dCT bind Gβγ 59 , 68 ( Fig. 6 ) but much weaker than their fusion protein, G1NdCT ( Fig. 7 ). These results suggest that the Gβγ-anchor is formed jointly by G1-NT and G1-dCT. Interestingly, adding G1-dCT to GIRK2 increased I basal and conferred Gβγ recruitment 36 , suggesting that G2-NT may form Gβγ anchors with G1-dCT. Peptide array scan and MD simulations provide additional insights. Both approaches identify known Gβγ-binding sites in core-CT, and new NT and dCT Gβγ-binding sites in GIRK1 and GIRK2. Our MD analysis used AlphaFold-models including unstructured but essential elements absent from crystal structures: Gγ prenyl and GIRKs’ NT and dCT. Despite the low-confidence of AlphaFold predictions for these elements, MD calculates interactions based on physical parameters and can capture dynamic interactions even if the initial structure is uncertain. Importantly, the simulations reveal a dynamically arising structural unit formed by G1-NT and G1-dCT, and extensive interactions of Gγ prenyl with G1NC, particularly G1-NT, and some with G2NC ( Fig. 8 ). Remarkably, Gγ prenyl –G1-NT interaction is lost, and Gβγ–G1-NT interaction is reduced after deleting G1-dCT, although G1-dCT itself barely interacts with Gγ prenyl . These results corroborate the idea that the Gβγ-anchor is a standalone structural and functional unit formed by G1-NT and G1-dCT, with G1-dCT essential for its integrity. Notably, Gγ assists Gβ in GIRK activation 52 , 61 . Gγ prenyl -anchor interaction may also be involved, since removing G1-dCT or Gγ’s C-terminal region, which includes the prenylation site, eliminates Gγ’s enhancing effect 52 , 61 . Fig. 9 summarizes our view of Gβγ-GIRK2 vs. Gβγ-GIRK1/2 interactions, gating, and the anchor’s role. The dynamic equilibrium between channel-bound, membrane-associated and cytosolic Gβγ determines the local Gβγ concentration within the channel’s microdomain. Free Gβγ can reversibly partition from the cytosolic reserve to the PM, activating GIRKs. Comparing K d for GIRK1/2 activation by Gβγ in whole oocytes ( Fig. 4f ) and excised oocyte’s patches 46 yields a Gβγ PM/cytosol partition coefficient between 140 and 425 (Supplementary Fig. 11), close to earlier estimates of ∼300 69 . Download figure Open in new tab Fig. 9. Differences between GIRK2 and GIRK1/2 in their interaction and gating by Gβγ. a , GIRK2 homotetramer does not preassociate with Gβγ and has low I basal . Channel opening requires the binding of four Gβγ. The affinity of first Gβγ binding is ∼4-30 µM and increases with the binding of each additional Gβγ. b , GIRK1/2 reversibly preassociates with Gβγ or Gαβγ due to two Gβγ-docking sites (anchors) formed by G1-dCT and NT (❸,❻) and opened following Gβγ binding to its activation sites (e.g. ❹). In the “graded contribution” scenario shown, binding of even one Gβγ to an activation site induces opening, and P o as well as K + flux are increased with each additional bound Gβγ. GIRK1/2 operates within a complex dynamic system that includes the channel and membrane-associated (❶), cytosolic (❷) and channel-bound Gαβγ and Gβγ, and free Gα GDP or Gα GTP (❺). Gγ prenyl plays an important part in the emerging equilibrium by interacting with the PM or, alternatively, Gα, the anchor, and Gβ C-terminus (most of these interactions are not shown). The anchors attract Gβγ, leading to an enrichment of Gβγ and, potentially, Gαβγ in channel’s microenvironment even in the absence of GPCR activation (basal states i, ii). Free Gβγ is in excess over Gαβγ because the presence of the anchor renders the channel with an overall higher affinity to Gβγ than Gα. Because of excess of free Gβγ, 1-3 out of the 4 activation sites of the GIRK1/2 tetramer are already occupied by Gβγ in basal state, I basal is high, and full activation (state iii) is achieved by binding of additional 1-3 Gβγ molecules. Our findings confirm that GIRK2 is gated through collision-coupling with Gβγ, cooperative Gβγ binding, and concerted activation after Gβγ occupies four activation sites ( Fig. 9a ), consistent with the WTM model 10 , 15 , 16 . However, in intact Xenopus oocytes (at estimated [Na + ] of 10-20 mM), the Gβγ-GIRK2 affinity is significantly higher than the bilayer estimates, primarily due to Gγ prenylation, which enhances Gβγ functionality and interaction with GIRKs. The high affinity guarantees efficient G i/o -GIRK2 signaling without the need for obligatory hotspots to account for physiological response (although we cannot exclude hotspots or crowding in oocyte PM, which could upshift our K d estimates). GIRK1/2, on the other hand, operates within a more complex dynamic system featuring two kinds of binding sites, docking (Gβγ-anchors) and activating. The anchor is formed jointly by G1-NT and G1-dCT and is functionally and topologically separate from the activation sites. The similarity of K d values and deactivation rates in GIRK1 ΔdCT /2 and GIRK2 indicates that the activation sites in GIRK2 and GIRK1/2 have similar Gβγ affinities. If the anchor does not participate in channel opening, how does it increase the apparent affinity? We propose that this is the consequence of the local enrichment of Gβγ around GIRK1/2 due to Gβγ recruitment 4 , through kinetic scaffolding-like mechanisms 70 – 73 , functionally equivalent to dynamic preassociation. The increased local Gβγ concentration, in excess over Gα, leads to partial occupation of the activation sites and high I basal 36 , 38 . Moreover, the added Gβγ will bind to the subsequent (unoccupied) sites with higher affinity due to cooperativity, explaining the leftward shift in GIRK1/2’s Gβγ dose-response curve. Added efficiency could arise if Gβγ’s binding surfaces for docking and activation sites are non-overlapping, allowing the docked Gβγ to repeatedly contact the nearby activation site before Gβγ dissociation from the anchor. Mapping the anchor-Gβγ interface is a challenge for the future. What is the role of Gα? Gα i/o interacts with GIRKs and has been hypothesized to dock the Gα i/o βγ heterotrimer to GIRKs 32 , 46 , 74 . However, the affinity of Gα to GIRK1 is lower than Gβγ 75 , 76 . Importantly, binding of Gα i to G1NC is enhanced by added Gβγ, suggesting that the heterotrimer is docked via Gβγ 4 , 37 , 75 . Both Gβγ-dependent Gα i3 -GIRK1 interactions and the speed and amplitude of I evoked are maximized when both G1-NT and G1-dCT are present 31 , 55 , 56 , 75 , indicating that the NT-dCT anchor is involved in docking the heterotrimer ( Fig. 9b ). The stoichiometry of anchor-associated Gαβγ and Gβγ in heterologous models and neurons likely varies with GIRK1/x density, constitutive GPCR activity, and other factors 4 . Summary We quantitated the interaction between Gβγ and GIRK channels in live Xenopus oocytes by combining accurate titrated protein expression, PM level monitoring and concurrent functional assays with biochemical and computational approaches. We discovered a novel role for Gγ prenylation in Gβγ-GIRK interaction, resolved the controversy over interaction affinity, and determined the composition of GIRK1’s unique Gβγ-docking site. Our findings reveal efficient, subunit-specific GIRK regulation by Gβγ and will facilitate further quantitative and structure-function analysis of this important signaling cascade. Methods Ethical approval and Xenopus oocytes handling Experiments have been approved by Tel Aviv University Institutional Animal Care and Use Committee (permit #01-20-083). Maintenance and surgery of female frogs were done as described 46 . Female frogs, aged 1.5-5 years, were kept at 20 ± 2°C at 10/14-hour light-dark cycle. During surgeries, frogs are anesthetized with a 0.25% Tricaine methanesulfonate (MS-222, Sigma-Aldrich #886-86-2) solution, and parts of ovary are removed through a small abdominal incision. Oocytes were defolliculated with collagenase in Ca 2+ free ND96 solution (in mM: 96 NaCl, 2 KCl, 1 MgCl 2 , 5 HEPES, pH 7.5). 2 hours later oocytes were washed with NDE solution (in mM: 96 NaCl, 2 KCl, 1 MgCl 2 , 1 CaCl 2 , 5 HEPES, 2.5 mM sodium pyruvate, 50 mg/ml gentamycin, pH 7.5) and left in NDE for 2-24 hours before injection. Oocytes were injected with 50 nl RNA using microinjection pipette (Drummond Scientific, Broomall, PA, USA) and incubated at 20°C for 72 hours for two-electrode voltage clamp, or 48-72 hours for single-channel patch clamp experiments. DNA constructs, RNA, antibodies DNA constructs are summarized in Supplementary Table 9. Antibodies are described in relevant sections of the Methods and summarized in Supplementary Table 10. Gβγ stands for Gβ 1 γ 2 throughout the paper. All DNA constructs used to produce RNA were inserted in vectors containing 5’ and 3’ untranslated sequences of Xenopus β-globin (pGEM-HE, pGEM-HJ or pBS-MXT) 75 . New constructs were prepared using standard PCR-based procedures and fully sequenced. We used the mouse isoform GIRK2A, which is 11 a.a. shorter than the longer isoform (mouse and human) not studied here, which includes a PDZ-binding consensus sequence at the dCT 77 . The truncated GIRK2 construct (GIRK2 trunk ) was prepared by deleting a.a. 1-51 and 381-414 from the GIRK2A construct by PCR. G2NC trunc was prepared by deleting, from G2NC, of the same regions. Myristoylated Gβ 1 (myr-Gβ) was created by adding the myristoylation signal (the first 15 aa of Src added to the N terminus of Gβ 1 ) 35 . GIRK2-CFP was created by fusing CFP A207K to the CT of GIRK2 via a Ser-Arg linker. IRK1-YFP and IRK1-CFP were created by fusing YFP A207K and CFP A207K , respectively, to the CT of IRK1 via a Lys-Leu linker, as described 78 . N-terminally Split Venus labeled Gβ 1 (SpV-Gβ) and N-terminally Split Venus labeled Gγ 2 (SpV-Gγ) 63 were subcloned into pGEM-HJ. G1NdCT (the fused cytosolic G1-NT and G1-dCT), G1N(1-40)dCT (the first 40 a.a. of G1-NT fused to G1-dCT), G1N(40-84)dCT (the last 44 a.a. of G1-NT fused to G1-dCT), Sumo-G1NT and Sumo-G1dCT (Sumo fused to G1-NT or G1-dCT). In all cases the fusion was via the 8-a.a. linker, QSTASQST. The Sumo construct used here was a truncated version of human Sumo 2 protein (a.a. 3-95; PDB: 5ELU_B). RNAs were transcribed in vitro as described 46 . The amounts of injected RNAs varied according to the experimental design. For whole-cell electrophysiology experiments we used, in ng/oocyte: 0.01-1 of GIRK1 or YFP-GIRK1, 0.2-10 GIRK2, 0.2-10 Gβ, 0.04-2.5 Gγ, 0.08-5 YFP-Gγ. Equal amounts of GIRK1 and GIRK2 RNAs were injected to express GIRK1/2 channels. In all experiments where several Gβγ expression levels were tested, the ratio of Gβ:Gγ RNA was kept constant: for Gβ:Gγ, the RNA ratio was 5:1 or 2.5:1, and for Gβ:YFP-Gγ the ratio was 2:1 or 2.5:1. For single channel patch clamp, the injected RNAs (in ng/oocyte) were: 0.005-0.01 IRK1-CFP; for GIRK2 alone, 0.02-0.05; for GIRK1/2 HA , GIRK1 0.01-0.02 of GIRK1 with 0.01-0.02 GIRK2 HA . In the experiments of Fig. 5 , we injected, in ng/oocyte: GIRK2 alone, 0.2-0.5; GIRK1/2, 0.02-0.05 of GIRK1 and 0.01-0.025 of GIRK2; for GIRK1ΔdCT/2, 0.02-0.05 of GIRK1ΔdCT and 0.01-0.025 of GIRK2. In all patch clamp experiments with Gβγ-activated GIRKs, we injected 5 ng Gβ 1 and 1-2 ng Gγ 2 RNA, and 25-50 ng/oocyte of the GIRK5 antisense oligonucleotide 38 to prevent the formation of GIRK1/5 channels. Gβγ expression and purification The pFastBac Dual vector (Invitrogen) was utilized to coexpress the bovine Gγ 2 (WT and C68S) and Gβ 1 genes in Sf9 insect cells. The bovine Gγ2 gene was subcloned downstream of a His-tag and a Tobacco Etch Virus (TEV) protease recognition site in the first multiple cloning site, under the control of the polyhedrin promoter. The Gβ1 gene was inserted into the second MCS, under the control of the p10 promoter. His 6 -Gβγ and His 6 -Gβγ C68S were purified essentially as described 79 . The pFastBac construct was transformed into DH10Bac competent E. coli to generate a recombinant bacmid. The recombinant bacmid was isolated and used for transfection to SF9 cells in presence of CellFectin II reagent (Thermo Fisher Scientific) to generate recombinant baculovirus. Further, this baculovirus stock was amplified and optimized for maximum protein expression via infection to Trichoplusia ni (T.ni) cells. The infected T.ni cells were grown for 60-72 hrs. Infected T.ni cells were harvested by centrifugation at 1000 rpm and stored at -80°C until further use. Purification of Gβγ: Cells were suspended and homogenized using glass homogenizer in 20 mM Hepes pH 8.0, 100 mM NaCl, 3 mM MgCl2, 100 mM EDTA, 10 mM 2-mercapto ethanol, cocktail protease inhibitors, 1% Triton X-100. Then the cells were lysed in sonicator using a program 5/25 sec on/off pulse for 30 min and subjected to centrifugation at 42000 rpm for 45 min. The soluble fraction was filtered using 0.4 µM filter and His-tag Gβγ was purified by sequential Ni 2+ chelate, size-exclusion [Superdex-75 HiPrep (GE Healthcare)] column chromatography. Final buffer conditions were: 20 mM Hepes pH 8.0, 100 mM NaCl, 1 mM MgCl 2 , 10 mM 2-mercaptoethanol. The fraction purity was analyzed using SDS-PAGE. The protein was also characterized by Western blot using anti-Gβ (GTX114442) and anti-His tag (Roche 11 965 085 001) antibody (Supplementary Table 10). Electrophysiology Whole-cell GIRK currents were measured using standard two-electrode voltage clamp at 20-22°C using GeneClamp 500B amplifier (Molecular Devices, Sunnyvale, CA, USA) and digitized using Axon Digidata 1440a using pCLAMP software (Molecular Devices). Agarose cushion microelectrodes were filled with 3M KCl, with resistances of 0.1–1 MΩ 37 . GIRK currents were measured in either low-[K + ] solution ND96 (same as Ca 2+ -free but with 1 mM CaCl 2 ) or high-K solution with 24 mM [K] out (in mM: 24 KCl, 72 NaCl, 1 CaCl 2 , 1 MgCl 2 and 5 Hepes). In experiments of Fig. 1 , to maximize GIRK2’s I basal , we used a 96 mM high-[K] out solution (in mM: 96 KCl, 2 NaCl, 1 CaCl 2 , 1 MgCl 2 and 5 Hepes). Net GIRK currents (I basal and I βγ ) were determined by subtraction of currents recorded in presence of 1-2.5 mM Ba 2+ that blocked GIRK currents. The pH of all solutions was 7.5–7.6. Cell-attached patch clamp recordings were performed as previously described 38 , at 20–23°C, using borosilicate glass pipettes with resistances of 1.5–3.5 MΩ. The electrode solution contained (in mM): 146 KCl, 2 NaCl, 1 CaCl 2 , 1 MgCl 2 , 10 Hepes and 1 GdCl 3 (pH 7.6). Bath solution contained (in mM): 146 KCl, 2 MgCl 2 , 6 NaCl, 10 Hepes and 1 EGTA (pH 7.6). Block of stretch-activated channels by GdCl 3 was confirmed by recording currents at +80 mV. Single channel currents were recorded at −80 mV in cell-attached patches with the Axopatch 200B amplifier (Molecular Devices) at −80 mV, filtered at 2 or 5 kHz and sampled at 10 or 25 kHz. Giant membrane patches (GMPs) GMPs were prepared and imaged as described 63 . Oocytes were devitellinized using tweezers in hypertonic solution (in mM: 6 NaCl, 150 KCl, 4 MgCl2, 10 Hepes, pH 7.6). The devitellinized oocytes were transferred onto a Thermanox TM coverslip (Nunc, Roskilde, Denmark) and immersed in Ca 2+ -free ND96 solution with their black hemisphere facing the coverslip, for 30– 45 min. The oocytes were then suctioned using a Pasteur pipette, leaving a GMP attached to the coverslip, with the cytosolic part facing the medium. The coverslip was washed thoroughly with fresh ND96 solution, and fixated using 4% formaldehyde for 30 min. Fixated GMPs were immunostained in 5% milk in PBS and non-specific binding was blocked with Donkey IgG 1:200 (Jackson ImmunoResearch, West Grove, PA, USA). Primary rabbit anti-Gβ (1:200; Santa Cruz, SC-378 or GeneTex, GTX114442) was applied for 45 min at 37°C either alone or with blocking peptide supplied with the antibody. Then DyLight549 or DyLight® 650-conjugated anti-rabbit secondary antibodies (KPL) were applied at 1:300 dilution for 30 min at 37°C, washed with PBS and mounted on a slide for visualization. Immunostained slides were kept at 4°C in the dark. Pull-down assay Pull-down binding experiments were performed as described 36 . Briefly, in vitro translated ( ivt ) [ 35 S]methionine-labelled proteins were prepared in rabbit reticulocyte lysate (Promega, Madison, WI, USA). Ivt proteins were mixed with ∼2 µg of either purified His-Gβγ WT or purified His-Gβγ C68S in 300 μl of the incubation buffer (in mM: 150 KCl, 50 Tris, 0.6 MgCl 2 , 1 EDTA, 0.1% Lubrol or 0.5% CHAPS and 10 imidazole; pH 7.4). The mixture was incubated while shaking for 45 min at room temperature, then 30 μl beads were added, and incubated for 30 min at 4°C. His-Gβγ was pulled-down using HisPurTM Ni-NTA Resin affinity beads (ThermoFisher Scientific, Rockford, IL, USA). The beads were washed three times with 500 μl buffer. Elution was done with 30 μl elution buffer (incubation buffer supplemented with 250 mM imidazole). After washing, the samples were analyzed on 12% gels by SDS-PAGE. Also, 1/60 of the mixture before the pull-down was loaded, usually on a separate gel (‘input’). Gels were imaged using Sapphire™ Biomolecular Imager (Azure Biosystems, Dublin, CA, USA). Autoradiograms were analyzed using ImageQuant 5.2 (GE Healthcare) and ImageJ/Fuji ( https://imagej.net/software/fiji/ ). Binding was calculated as percentage or fraction of the input of this construct in the same experiment. Confocal imaging Confocal imaging and analysis were performed as described 78 , with Zeiss 510, Ziess 710 or Leica TCS SP5 confocal microscopes, using a 20× objective. Live oocytes were images at their animal hemisphere in ND96 or NDE solutions. Giant membrane patches were imaged at their edges, so both the membrane and the background were visible. Images were acquired using spectral (λ)-mode or channel mode. For imaging the following wavelength parameters were used: YFP, excitation 514 nm, imaging at 525–540 nm; DyLight 650, excitation 633 nm, imaging at 663-673 nm. For whole oocytes, fluorescence signals at the maximum emission wavelength are averaged from three regions of interest using Zeiss LSM Image Browser (Carl Zeiss Jena GmbH), ImageJ or LAS AF (Lecia Microsystems CMC GmbH) Image software. For giant membrane patches, the entire visible membrane and background were averaged. Averaged background for each signal, and the average net signal from uninjected (native) oocytes of the same experiment, were subtracted to obtain net signal. For the effect of Gβγ on the expression of GIRK2 and GIRK2HA, signals were normalized by dividing the signal of each oocyte with the average of the group that did not contain Gβγ. Western blots of Gβ in oocytes’ plasma membranes Quantitative Western blots of Gβ in manually separated oocytes’ PMs have been performed as described 38 . Briefly, PMs together with the vitelline membranes (extracellular collagen-like matrix) were manually separated from the rest of the oocyte (“cytosol”) with fine forceps, after a 5-15 min incubation in a low osmolarity solution (5 mM NaCl, 5 mM HEPES, and protease inhibitors (Roche Complete Protease Inhibitors Cocktail (Merck), 1 tablet/50 ml, pH=7.5). PMs of ∼20 oocytes were pooled for each sample (lane on polyacrylamide-SDS gel). The cytosol was processed separately: the nuclei were separated by centrifugation for 10 min at 700×g at 4°C and removing the pellet (nuclei). Plasma membranes and cytosols were then solubilized in 35 µl running buffer (2% SDS, 10% glycerol, 5% β-mercaptoethanol, 0.05% Bromophenol Blue, 62.5 mM Tris-HCl pH 6.8) and heated to 65°C for 5 min. Samples were electrophoresed on 12% polyacrylamide-SDS gel and transferred to nitrocellulose membranes for standard Western blotting. Known amounts of purified His-Gβγ were run on the same gel for the construction of the calibration curve. Gβγ was detected with anti-GNB1 antibody (GTX114442) at 1:500 or 1:1000 dilution on Fusion FX7 (Witec AG, Sursee, Switzerland) and quantitated using Fiji software. Signal in each band was assessed as (mean intensity)×(area) using ImageJ/Fiji. To quantify the expressed Gβ, endogenous Gβ signal from oocytes expressing the channel alone was subtracted from the total signal. Peptide spot array Peptide arrays were generated by automatic SPOT synthesis and blotted on a Whatman membrane as described 80 . Briefly, N-terminal and C-terminal parts of GIRK1 and GIRK2 were spot-synthesized as 25-mer peptides overlapping sequences, shifted by 5 a.a. along the sequence, using AutoSpot Robot ASS 222 (Intavis Bioanalytical Instruments, Cologne, Germany). The peptides were designed according to human GIRK2 (NCBI: NM_002240.5) (NT: a.a. 1-93, CT: a.a. 193-423) and rat GIRK1 (NCBI: NP_113798.1) (NT: a.a. 1-84, CT: a.a. 183-501). The interaction with spot-synthesized peptides was investigated by an overlay assay. Following blocking of 1 hour at room temperature with 5% BSA in 20 mM Tris and 150 mM NaCl with 0.1% Tween-20 (TBST), 0.016-0.16 μM purified His-Gβγ were incubated with the immobilized peptide-dots, overnight at 4 °C. His-Gβγ was detected by anti-GNB1 antibody (GTX114442) at 1:500 or 1:1000 dilution, and anti-rabbit HRP-coupled secondary antibody (1:40000) incubated with 5% BSA/TBST, and the membrane was imaged using Fusion FX7, as for Western blotting. Electrophysiological data analysis and surface density calibration Whole-cell and single-channel data were analyzed using Clampex and Clampfit (pCLAMP suite, Molecular Devices, Sunnyvale, CA, USA). In oocytes expressing the m2 receptor, the fold activation by agonist, R a , was measured in each cell and defined as where I total =I basal +I evoked . R a =1 when there is no response to agonist. The fold activation by Gβγ, R βγ , was defined as where I βγ is the net GIRK current in a Gβγ-expressing oocyte, and Ῑ basal is the average GIRK current in oocytes of control group, that express only the channel, from the same experiment 37 . Single channel amplitudes were calculated from Gaussian fits of all-points histograms of 30–90 s segments of the record. The open channel probability ( P o ) was estimated from 1–5 min segments of 4–20 min recordings from patches containing one to three channels using a standard 50% idealization criterion 38 . The PM density of functional channels was determined from the whole-cell current, I, using the classical equation 49 where N ch is the total number of channels in the cell, i single is the single-channel current and P o is the open probability. P o and i single for Gβγ-activated GIRK1/2 are known, and for GIRK2, GIRK1/2 HA and IRK1-xFP we determined them here (Supplementary Fig. 3, Supplementary Table 3). The surface density, in channels/µm 2 (µm -2 ) was calculated by dividing N ch by the membrane surface area of the oocyte 81 , 2·10 7 µm 2 . Protein surface densities were converted to concentrations using the standard procedure based on a submembrane interaction space 10 nm deep. i single was measured in cell-attached patches in 146 mM [K + ] out , whole-cell currents were measured in 24 mM [K + ] out . The amplitude translation factor for these solutions was 4.63. The conversion factor from surface density to sub-PM space concentration was 1 µm -2 = 0.166 µM 38 . In calculating the surface density of channel-attached YFP (two for YFP-GIRK1/2 and four for IRK1-YFP), we assumed similar levels of fluorescence maturation of channel- and Gβ-attached YFP molecules, therefore no correction for such maturation was made. For CF calibrations with YFP-GIRK1/2 or IRK1-YFP, the linear fit included the zero-fluorescence point (with no expressed channels). In the analysis of Gβγ dose-response data in intact oocytes, we assumed that the PM level of the GIRK2 channels was not significantly altered by Gβγ, as shown previously 37 , 63 and confirmed for CFP-GIRK2 (Supplementary Fig. 6). In one experiment we monitored GIRK2HA and observed changes at different doses of Gβγ, and corrected the currents accordingly (Supplementary Table 6). Similarly, coexpression of Gβγ causes no significant changes in PM levels of GIRK1/2 up to 2 ng RNA of Gβ 63 . In most experiments, the maximal GIRK1/2 current was observed already with 1 or 2 ng Gβ RNA. With 5 ng Gβ RNA, a 20-30% decrease in channel expression is occasionally seen 63 . No correction for this potential change has been made. Modeling, simulation and curve fitting for Gβγ dose-response data Standard fitting for Gβγ-GIRK dose-response curves with Hill or modified WTM models was done assuming that, in the absence of GPCR simulation, the endogenous G proteins are in the form of heterotrimers. Data were fitted to Hill equation in the following form: where x is the concentration of coexpressed Gβγ ([Gβγ]), I GIRK is GIRK current, I max is the maximal GIRK current at saturating concentrations of coexpressed Gβγ, h H is the Hill coefficient, c is a constant component corresponding to I basal ; or a modified WTM model 15 with the addition of a constant component c: where x, c and I max have the same meaning as in Eq. 4 , K d is the dissociation constant of the first Gβγ binding to the one of the four sites in GIRK molecule, µ is the cooperativity factor for each successive Gβγ binding 10 for the specific case of a constant Na + concentration 15 . In whole-cell of cell-attached recordings from intact Xenopus oocytes, both intracellular Na + and the membrane PIP 2 can be assumed constant during the experiment. Therefore, in most WTM model fits, we utilized a constant cooperativity factor µ=0.3 15 or µ=0.44 (from Fig. 3 ). In two experiments with GIRK2 we were able to obtain independent estimates of µ from fit, which were 0.44 and 0.62 (Supplementary Table 6, “free µ”). To simulate Gβγ activation of GIRK1/2, we tested four kinetic schemes (models) (Supplementary Fig. 8a, Supplementary Methods). First, we calculated the basal available Gβγ and Gα from the experimentally observed I basal as described previously 17 , 38 . For simulation, we constructed systems of differential equations based on these schemes and solved them numerically in Berkley Madonna (Berkeley Madonna, Inc., Albany, CA) 82 utilizing 4th order Runge-Kutta integration method. The simulations were run till apparent steady state was achieved. Molecular dynamics simulations Primary structures of G1NC and G2NC were generated by fusing the NT and CT of human GIRK1 (UniProt-ID: P48549; a.a.1-84 and 183-501) and human GIRK2 (UniProt-ID: P48051, a.a. 1-93 and 193-414), respectively ( Fig. 8 ). The heatmaps in Fig. 8 show G412 as the last a.a., which corresponds to G414 of mGIRK2 (Supplementary Fig. 9). Additionally, Gβγ (UniProt-ID: P62873, P59768) units were incorporated into the sequences. Similarly, truncated constructs were obtained by omitting a.a. 379-501 and a.a. 1-52 and 381-412 for G1NC and G2NC, respectively. The truncated G1NC and G2NC are the same as G1NC ΔdCT and G2NC trunc used in biochemical experiments (see Fig. 1e ). Heterotetramers bound to four Gβγ were modeled using AlphaFold 3 83 . Coarse-grained constructs were modeled with CHARMM-GUI 84 . Simulations were conducted with Gromacs 2022.3 85 based on the Martini force field Elnedyn22p 86 and polarizable water 87 in 100mM KCl. For the geranylgeranyl moiety, previously published parameters were used 88 . Minimization and equilibration procedures followed the CHARMM-GUI protocol. Simulation runs of 1 μs each were performed with a time step of 20 fs. During the production runs, the temperature was set to 310 K using the v-rescale thermostat 89 , and the pressure was kept at 1 bar with the Parrinello-Rahman barostat 90 . Lennard-Jones potentials and Coulombic interactions are switched off between 9 to 12 Å and 0 to 12 Å, respectively. Contacts were analyzed using MDAnalysis 91 with a distance cut-off of 6 Å. Statistical analysis Statistical analysis was performed using GraphPad Prism (GraphPad, La Jolla, CA, USA). For normally distributed data (by Shapiro-Wilk test), pairwise comparison was done by t-test and multiple comparisons by one-way ANOVA, and data were presented as bar graphs with individual data points and mean ± SEM (except if non-normally distributed data were presented on the same panel, in which case box plots were shown). If the data did not pass the normal distribution test, they were analyzed using Mann-Whitney (pairwise) and Kruskal-Wallis non-parametric ANOVA tests, and data were presented as box plots and individual data points. The boxes represent the 25th and 75th percentiles, the whiskers show the smallest and maximal values, and the horizontal line represents the median. Statistical analysis for differences between dose-response curves for two different GIRK compositions was done on WTM model fits of normalized dose-response data from individual oocytes for two fits (as in Fig. 4b,d ), as well on three fits (details in Supplementary Fig. 7). Graphics Structures of GIRK2, Gα and Gβγ were drawn with PyMOL (Schrodinger LLC). All final figures were produced with Inkscape ( inkscape.org ). Competing interests We declare no competing interests. Authors contributions ND, DY, ASW – conceptualization RH, TKR, BS, UK, TF, CWD, YH, JAH, ASW, DY, ND – experimental design RH, TKR, BS, PH, UK, TF, GT, VT, HRP, ASW, DY, ND – investigation RH, GT, OCH, DRT, KZ, CWD, EK, JAH – resources RH, THK, PH, UK, TF, ASW, ND – data curation EK, YH, JAH, ASW, DY, ND – supervision CWD, EK, YH, JAH, ASW, ND – funding acquisition RH, ASW, DY, ND – writing the initial version of the paper RH, HRP, UK, EK, CWD, YH, JAH, ASW, DY, ND - review and editing All authors read and confirmed the paper. Materials & correspondence All materials created in this paper, such as DNA constructs, are fully available upon reasonable request. Correspondence regarding experimental procedures and results to ND dascaln{at}tauex.tau.ac.il , kinetic modeling and analysis to DY danielya{at}ariel.ac.il , molecular dynamics simulations AWS anna.stary{at}univie.ac.at . Data availability All data are presented in figures and tables in the main paper and in Supplementary Material. MD simulation data has been stored on Zenodo: doi: 10.5281/zenodo.15075373. Acknowledgements This work was supported by grants 1282/18 and 581/22 from Israel Science Foundation (ND), KL1415/14-1 from the Deutsche Forschungsgemeinschaft (EK), R35GM145921 from the National Institute of General Medical Science, National Institutes of Health, W1232 from the Austrian Science Fund (ASW, TF). The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Funder Information Declared Israel Science Foundation, https://ror.org/04sazxf24 , 581/22 , 1282/18 Deutsche Forschungsgemeinschaft, https://ror.org/018mejw64 , KL1415/14-1 National Institutes of Health, https://ror.org/01cwqze88 , R35GM145921 FWF Austrian Science Fund, https://ror.org/013tf3c58 , W1232 References 1. ↵ Luscher C , Slesinger PA . Emerging roles for G protein-gated inwardly rectifying potassium (GIRK) channels in health and disease . Nat Rev Neurosci 11 , 301 – 315 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 2. ↵ Luo H , Marron Fernandez de Velasco E , Wickman K. Neuronal G protein-gated K + channels . Am J Physiol Cell Physiol 323 , C439 – c460 ( 2022 ). OpenUrl CrossRef PubMed 3. Chiamvimonvat N , et al. Potassium currents in the heart: functional roles in repolarization, arrhythmia and therapeutics . J Physiol 595 , 2229 – 2252 ( 2017 ). OpenUrl CrossRef PubMed 4. ↵ Dascal N , Kahanovitch U . The roles of Gβγ and Gα in gating and regulation of GIRK channels . Int Rev Neurobiol 123 , 27 – 85 ( 2015 ). OpenUrl CrossRef PubMed 5. ↵ Whorton MR , MacKinnon R . X-ray structure of the mammalian GIRK2-βγ G-protein complex . Nature 498 , 190 – 197 ( 2013 ). OpenUrl CrossRef PubMed Web of Science 6. ↵ Logothetis DE , Kurachi Y , Galper J , Neer EJ , Clapham DE . The βγ subunits of GTP-binding proteins activate the muscarinic K + channel in heart . Nature 325 , 321 – 326 ( 1987 ). OpenUrl CrossRef PubMed Web of Science 7. Yamada M , Jahangir A , Hosoya Y , Inanobe A , Katada T , Kurachi Y . GK* and brain Gbg activate muscarinic K + channel through the same mechanism . J Biol Chem 268 , 24551 – 24554 ( 1993 ). OpenUrl Abstract / FREE Full Text 8. ↵ Krapivinsky G , Krapivinsky L , Wickman K , Clapham DE . Gbg binds directly to the G protein-gated K + channel, I KACh . J Biol Chem 270 , 29059 – 29062 ( 1995 ). OpenUrl Abstract / FREE Full Text 9. ↵ Ivanova-Nikolova TT , Nikolov EN , Hansen C , Robishaw JD. Muscarinic K + channel in the heart. Modal regulation by G protein βγ subunits . J Gen Physiol 112 , 199 – 210 ( 1998 ). OpenUrl Abstract / FREE Full Text 10. ↵ Wang W , Touhara KK , Weir K , Bean BP , MacKinnon R . Cooperative regulation by G proteins and Na + of neuronal GIRK2 K + channels . Elife 5 , ( 2016 ). 11. ↵ Escriba PV , Wedegaertner PB , Goni FM , Vogler O . Lipid-protein interactions in GPCR-associated signaling . Biochim Biophys Acta 1768 , 836 – 852 ( 2007 ). OpenUrl CrossRef PubMed 12. ↵ Schreibmayer W , et al. Inhibition of an inwardly rectifying K channel by G-protein α-subunits . Nature 380 , 624 – 627 ( 1996 ). OpenUrl CrossRef PubMed 13. ↵ Nakajima Y , Nakajima S , Kozasa T . Activation of G protein-coupled inward rectifier K + channels in brain neurons requires association of G protein bg subunits with cell membrane . FEBS Lett 390 , 217 – 220 . ( 1996 ). OpenUrl CrossRef PubMed Web of Science 14. ↵ Vorobiov D , Bera AK , Keren-Raifman T , Barzilai R , Dascal N . Coupling of the muscarinic m2 receptor to G protein-activated K + channels via Ga z and a receptor-Ga z fusion protein. Fusion between the receptor and Ga z eliminates catalytic (collision) coupling . J Biol Chem 275 , 4166 – 4170 ( 2000 ). OpenUrl Abstract / FREE Full Text 15. ↵ Touhara KK , MacKinnon R . Molecular basis of signaling specificity between GIRK channels and GPCRs . Elife 7 , ( 2018 ). 16. ↵ Zhang Y , MacKinnon R . Higher-order transient structures and the principle of dynamic connectivity in membrane signaling . Proc Natl Acad Sci U S A 122 , e2421280121 ( 2025 ). OpenUrl CrossRef PubMed 17. ↵ Berlin S , et al. A collision coupling model governs the activation of neuronal GIRK1/2 channels by muscarinic-2 receptors . Front Pharmacol 11 , 1216 ( 2020 ). OpenUrl PubMed 18. ↵ Fowler CE , Aryal P , Suen KF , Slesinger PA . Evidence for association of GABA B receptors with Kir3 channels and RGS4 proteins . J Physiol (Lond ) 580 , 51 – 65 ( 2006 ). OpenUrl CrossRef PubMed 19. Kahanovitch U , Berlin S , Dascal N . Collision coupling in the GABA B receptor - G protein - GIRK signaling cascade . FEBS Lett 591 , 2816 – 2825 ( 2017 ). OpenUrl PubMed 20. ↵ Fritzius T , et al. Preassembly of specific Gβγ subunits at GABA B receptors through auxiliary KCTD proteins accelerates channel gating . Biochem Pharmacol 228 , 116176 ( 2024 ). OpenUrl PubMed 21. ↵ Hein P , Bunemann M . Coupling mode of receptors and G proteins . Naunyn Schmiedebergs Arch Pharmacol 379 , 435 – 443 ( 2009 ). OpenUrl CrossRef PubMed 22. ↵ Sungkaworn T , Jobin M-L , Burnecki K , Weron A , Lohse MJ , Calebiro D . Single-molecule imaging reveals receptor–G protein interactions at cell surface hot spots . Nature 550 , 543 – 547 ( 2017 ). OpenUrl CrossRef PubMed 23. ↵ Zhang Y , et al. Higher-order transient membrane protein structures . Proc Natl Acad Sci U S A 122 , e2421275121 ( 2025 ). OpenUrl CrossRef PubMed 24. ↵ Doupnik CA , Dessauer CW , Slepak VZ , Gilman AG , Davidson N , Lester HA . Time resolved kinetics of direct Gb 1 g 2 interactions with the carboxyl terminus of Kir3.4 inward rectifier K + channel subunits . Neuropharmacol 35 , 923 – 931 ( 1996 ). OpenUrl CrossRef PubMed Web of Science 25. ↵ Yokogawa M , Osawa M , Takeuchi K , Mase Y , Shimada I . NMR analyses of the Gβγ binding and conformational rearrangements of the cytoplasmic pore of G protein-activated inwardly rectifying potassium channel 1 (GIRK1) . J Biol Chem 286 , 2215 – 2223 ( 2011 ). OpenUrl Abstract / FREE Full Text 26. ↵ Wang W , Whorton MR , MacKinnon R . Quantitative analysis of mammalian GIRK2 channel regulation by G proteins, the signaling lipid PIP 2 and Na + in a reconstituted system . Elife 3 , e03671 ( 2014 ). OpenUrl CrossRef PubMed 27. ↵ Touhara KK , Wang W , MacKinnon R . The GIRK1 subunit potentiates G protein activation of cardiac GIRK1/4 hetero-tetramers . Elife 5 , ( 2016 ). 28. ↵ Fernandez-Alacid L , Watanabe M , Molnar E , Wickman K , Lujan R . Developmental regulation of G protein-gated inwardly-rectifying K + (GIRK/Kir3) channel subunits in the brain . Eur J Neurosci 34 , 1724 – 1736 ( 2011 ). OpenUrl CrossRef PubMed 29. ↵ Shea LD , Neubig RR , Linderman JJ . Timing is everything - The role of kinetics in G protein activation . Life Sci 68 , 647 – 658 ( 2000 ). OpenUrl CrossRef PubMed Web of Science 30. ↵ Huang CL , Slesinger PA , Casey PJ , Jan YN , Jan LY . Evidence that direct binding of Gβγ to the GIRK1 G protein-gated inwardly rectifying K + channel is important for channel activation . Neuron 15 , 1133 – 1143 ( 1995 ). OpenUrl CrossRef PubMed Web of Science 31. ↵ Slesinger PA , Reuveny E , Jan YN , Jan LY . Identification of structural elements involved in G protein gating of the GIRK1 potassium channel . Neuron 15 , 1145 – 1156 ( 1995 ). OpenUrl CrossRef PubMed Web of Science 32. ↵ Clancy SM , et al. Pertussis-toxin-sensitive Gα subunits selectively bind to C-terminal domain of neuronal GIRK channels: evidence for a heterotrimeric G-protein-channel complex . Mol Cell Neurosci 28 , 375 – 389 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 33. Rebois RV , et al. Heterotrimeric G proteins form stable complexes with adenylyl cyclase and Kir3.1 channels in living cells . J Cell Sci 119 , 2807 – 2818 ( 2006 ). OpenUrl Abstract / FREE Full Text 34. Riven I , Iwanir S , Reuveny E . GIRK channel activation involves a local rearrangement of a preformed G protein channel complex . Neuron 51 , 561 – 573 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 35. ↵ Rishal I , Porozov Y , Yakubovich D , Varon D , Dascal N . Gβγ-dependent and Gβγ-independent basal activity of G protein-activated K + channels . J Biol Chem 280 , 16685 – 16694 ( 2005 ). OpenUrl Abstract / FREE Full Text 36. ↵ Kahanovitch U , et al. Recruitment of Gβγ controls the basal activity of G-protein coupled inwardly rectifying potassium (GIRK) channels: crucial role of distal C terminus of GIRK1 . J Physiol 592 , 5373 – 5390 ( 2014 ). OpenUrl CrossRef PubMed 37. ↵ Rubinstein M , et al. Divergent regulation of GIRK1 and GIRK2 subunits of the neuronal G protein gated K + channel by Ga i GDP and Gbg . J Physiol 587 , 3473 – 3491 ( 2009 ). OpenUrl CrossRef PubMed 38. ↵ Yakubovich D , et al. A quantitative model of the GIRK1/2 channel reveals that its basal and evoked activities are controlled by unequal stoichiometry of Gα and Gβγ . PLoS Comput Biol 11 , e1004598 ( 2015 ). OpenUrl CrossRef PubMed 39. ↵ Higgins JB , Casey PJ . In vitro processing of recombinant G protein γ subunits. Requirements for assembly of an active βγ complex . J Biol Chem 269 , 9067 – 9073 ( 1994 ). OpenUrl Abstract / FREE Full Text 40. Jian X , Clark WA , Kowalak J , Markey SP , Simonds WF , Northup JK . Gβγ affinity for bovine rhodopsin is determined by the carboxyl-terminal sequences of the γ subunit . J Biol Chem 276 , 48518 – 48525 ( 2001 ). OpenUrl Abstract / FREE Full Text 41. ↵ Lukov GL , et al. Role of the isoprenyl pocket of the G protein β γ subunit complex in the binding of phosducin and phosducin-like protein . Biochemistry 43 , 5651 – 5660 ( 2004 ). OpenUrl CrossRef PubMed Web of Science 42. ↵ Iniguez-Lluhi JA , Simon MI , Robishaw JD , Gilman AG . G protein β γ subunits synthesized in Sf9 cells. Functional characterization and the significance of prenylation of γ . J Biol Chem 267 , 23409 – 23417 ( 1992 ). OpenUrl Abstract / FREE Full Text 43. ↵ Myung CS , Garrison JC . Role of C-terminal domains of the G protein β subunit in the activation of effectors . Proc Natl Acad Sci U S A 97 , 9311 – 9316 ( 2000 ). OpenUrl Abstract / FREE Full Text 44. Fogg VC , Azpiazu I , Linder ME , Smrcka A , Scarlata S , Gautam N . Role of the γ subunit prenyl moiety in G protein βγ complex interaction with phospholipase Cβ . J Biol Chem 276 , 41797 – 41802 ( 2001 ). OpenUrl Abstract / FREE Full Text 45. ↵ Akgoz M , Azpiazu I , Kalyanaraman V , Gautam N . Role of the G protein γ subunit in βγ complex modulation of phospholipase Cβ function . J Biol Chem 277 , 19573 – 19578 ( 2002 ). OpenUrl Abstract / FREE Full Text 46. ↵ Peleg S , Varon D , Ivanina T , Dessauer CW , Dascal N . Ga i controls the gating of the G-protein-activated K + channel, GIRK . Neuron 33 , 87 – 99 ( 2002 ). OpenUrl CrossRef PubMed Web of Science 47. ↵ Niu Y , Tao X , Touhara KK , MacKinnon R . Cryo-EM analysis of PIP 2 regulation in mammalian GIRK channels . Elife 9 , ( 2020 ). 48. ↵ Mathiharan YK , Glaaser IW , Zhao Y , Robertson MJ , Skiniotis G , Slesinger PA . Structural insights into GIRK2 channel modulation by cholesterol and PIP2 . Cell Rep 36 , 109619 ( 2021 ). OpenUrl CrossRef PubMed 49. ↵ Hille B . Ion Channels of Excitable Membranes . Sinauer ( 2002 ). 50. ↵ Falkenburger BH , Jensen JB , Hille B . Kinetics of M1 muscarinic receptor and G protein signaling to phospholipase C in living cells . J Gen Physiol 135 , 81 – 97 ( 2010 ). OpenUrl Abstract / FREE Full Text 51. ↵ Knol JC , Engel R , Blaauw M , Visser AJ , van Haastert PJ . The phosducin-like protein PhLP1 is essential for Gβγ dimer formation in Dictyostelium discoideum . Mol Cell Biol 25 , 8393 – 8400 ( 2005 ). OpenUrl Abstract / FREE Full Text 52. ↵ Tabak G , Keren-Raifman T , Kahanovitch U , Dascal N . Mutual action by Gγ and Gβ for optimal activation of GIRK channels in a channel subunit-specific manner . Sci Rep 9 , 508 ( 2019 ). OpenUrl PubMed 53. ↵ Runnels LW , Scarlata SF . Determination of the affinities between heterotrimeric G protein subunits and their phospholipase C-β effectors . Biochemistry 38 , 1488 – 1496 ( 1999 ). OpenUrl CrossRef PubMed 54. ↵ Leaney JL , Tinker A . The role of members of the pertussis toxin-sensitive family of G proteins in coupling receptors to the activation of the G protein-gated inwardly rectifying potassium channel . Proc Natl Acad Sci U S A 97 , 5651 – 5656 ( 2000 ). OpenUrl Abstract / FREE Full Text 55. ↵ Wydeven N , Young D , Mirkovic K , Wickman K . Structural elements in the Girk1 subunit that potentiate G protein-gated potassium channel activity . Proc Natl Acad Sci U S A 109 , 21492 – 21497 ( 2012 ). OpenUrl Abstract / FREE Full Text 56. ↵ Chan KW , Sui JL , Vivaudou M , Logothetis DE . Specific regions of heteromeric subunits involved in enhancement of G protein-gated K + channel activity . J Biol Chem 272 , 6548 – 6555 ( 1997 ). OpenUrl Abstract / FREE Full Text 57. ↵ Sadja R , Alagem N , Reuveny E . Graded contribution of the Gβγ binding domains to GIRK channel activation . Proc Natl Acad Sci U S A 99 , 10783 – 10788 ( 2002 ). OpenUrl Abstract / FREE Full Text 58. ↵ Sui JL , Petit-Jacques J , Logothetis DE . Activation of the atrial KACh channel by the βγ subunits of G proteins or intracellular Na + ions depends on the presence of phosphatidylinositol phosphates . Proc Natl Acad Sci U S A 95 , 1307 – 1312 ( 1998 ). OpenUrl Abstract / FREE Full Text 59. ↵ Ivanina T , et al. Mapping the Gβγ-binding sites in GIRK1 and GIRK2 subunits of the G protein-activated K + channel . J Biol Chem 278 , 29174 – 29183 ( 2003 ). OpenUrl Abstract / FREE Full Text 60. ↵ McIntire WE . A model for how Gβγ couples Gα to GPCR . J Gen Physiol 154 , ( 2022 ). 61. ↵ Peng L , Mirshahi T , Zhang H , Hirsch JP , Logothetis DE . Critical determinants of the G protein γ subunits in the Gβγ stimulation of G protein-activated inwardly rectifying potassium (GIRK) channel activity . J Biol Chem 278 , 50203 – 50211 ( 2003 ). OpenUrl Abstract / FREE Full Text 62. ↵ Bhatt M , Di Iacovo A , Romanazzi T , Roseti C , Cinquetti R , Bossi E . The "www" of Xenopus laevis oocytes: The why, when, what of Xenopus laevis oocytes in membrane transporters research . Membranes 12 , ( 2022 ). 63. ↵ Reddy HP , et al. Encephalopathy-causing mutations in Gβ1 (GNB1) alter regulation of neuronal GIRK channels . iScience 24 , 103018 ( 2021 ). OpenUrl PubMed 64. ↵ Edelstein SJ , Stefan MI , Le Novère N . Ligand depletion in vivo modulates the dynamic range and cooperativity of signal transduction . PLOS ONE 5 , e8449 ( 2010 ). OpenUrl CrossRef PubMed 65. ↵ Ho IH , Murrell-Lagnado RD . Molecular determinants for sodium-dependent activation of G protein-gated K + channels . J Biol Chem 274 , 8639 – 8648 ( 1999 ). OpenUrl Abstract / FREE Full Text 66. ↵ Mahajan R , Ha J , Zhang M , Kawano T , Kozasa T , Logothetis DE . A computational model predicts that Gβγ acts at a cleft between channel subunits to activate GIRK1 channels . Sci Signal 6 , ra69 ( 2013 ). OpenUrl Abstract / FREE Full Text 67. ↵ Li D , Jin T , Gazgalis D , Cui M , Logothetis DE . On the mechanism of the GIRK2 channel gating by phosphatidylinositol bisphosphate (PIP2), sodium, and the Gβγ dimer . J Biol Chem 294 , 18934 – 18948 ( 2019 ). OpenUrl Abstract / FREE Full Text 68. ↵ Huang CL , Jan YN , Jan LY . Binding of the G protein bg subunit to multiple regions of G protein-gated inward-rectifying K + channels . FEBS Lett 405 , 291 – 298 ( 1997 ). OpenUrl CrossRef PubMed Web of Science 69. ↵ Runnels LW , Scarlata SF . Regulation of the rate and extent of phospholipase Cβ2 effector activation by the βγ subunits of heterotrimeric G proteins . Biochemistry 37 , 15563 – 15574 ( 1998 ). OpenUrl CrossRef PubMed 70. ↵ Mori MX , Erickson MG , Yue DT . Functional stoichiometry and local enrichment of calmodulin interacting with Ca 2+ channels . Science 304 , 432 – 435 ( 2004 ). OpenUrl Abstract / FREE Full Text 71. Zhong H , Wade SM , Woolf PJ , Linderman JJ , Traynor JR , Neubig RR . A spatial focusing model for G protein signals. Regulator of G protein signaling (RGS) protein-mediated kinetic scaffolding . J Biol Chem 278 , 7278 – 7284 ( 2003 ). OpenUrl Abstract / FREE Full Text 72. Ross EM . Coordinating speed and amplitude in G-protein signaling . Curr Biol 18 , R777 – R783 ( 2008 ). OpenUrl CrossRef PubMed Web of Science 73. ↵ Eungdamrong NJ , Iyengar R . Compartment-specific feedback loop and regulated trafficking can result in sustained activation of Ras at the Golgi . Biophys J 92 , 808 – 815 ( 2007 ). OpenUrl CrossRef PubMed 74. ↵ Ivanina T , et al. Gα i1 and Gα i3 differentially interact with, and regulate, the G protein-activated K + channel . J Biol Chem 279 , 17260 – 17268 ( 2004 ). OpenUrl Abstract / FREE Full Text 75. ↵ Berlin S , et al. Two distinct aspects of coupling between Gαi protein and G protein-activated K + channel (GIRK) revealed by fluorescently labeled Gα i3 protein subunits . J Biol Chem 286 , 33223 – 33235 ( 2011 ). OpenUrl Abstract / FREE Full Text 76. ↵ Mase Y , Yokogawa M , Osawa M , Shimada I . Structural basis for modulation of gating property of G protein-gated inwardly rectifying potassium ion channel (GIRK) by i/o-family G protein α subunit (Galphai/o) . J Biol Chem 287 , 19537 – 19549 ( 2012 ). OpenUrl Abstract / FREE Full Text 77. ↵ Marron Fernandez de Velasco E , et al. GIRK2 splice variants and neuronal G protein-gated K + channels: implications for channel function and behavior . Sci Rep 7 , 1639 ( 2017 ). OpenUrl PubMed 78. ↵ Berlin S , et al. Gα i and Gβγ jointly regulate the conformations of a Gβγ effector, the neuronal G protein-activated K + channel (GIRK) . J Biol Chem 285 , 6179 – 6185 ( 2010 ). OpenUrl Abstract / FREE Full Text 79. ↵ Dessauer CW , Gilman AG . Purification and characterization of a soluble form of mammalian adenylyl cyclase . J Biol Chem 271 , 16967 – 16974 ( 1996 ). OpenUrl Abstract / FREE Full Text 80. ↵ Dema A , et al. The A-kinase anchoring protein (AKAP) glycogen synthase kinase 3β interaction protein (GSKIP) regulates β-catenin through its interactions with both protein kinase A (PKA) and GSK3β . J Biol Chem 291 , 19618 – 19630 ( 2016 ). OpenUrl Abstract / FREE Full Text 81. ↵ Dascal N . The use of Xenopus oocytes for the study of ion channels . CRC Crit Rev Biochem 22 , 317 – 387 ( 1987 ). OpenUrl CrossRef PubMed Web of Science 82. ↵ Marcoline FV , Furth J , Nayak S , Grabe M , Macey RI . Berkeley Madonna version 10-A simulation package for solving mathematical models . CPT Pharmacometrics Syst Pharmacol 11 , 290 – 301 ( 2022 ). OpenUrl PubMed 83. ↵ Abramson J , et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3 . Nature 630 , 493 – 500 ( 2024 ). OpenUrl CrossRef PubMed 84. ↵ Qi Y , Ingólfsson HI , Cheng X , Lee J , Marrink SJ , Im W . CHARMM-GUI martini maker for coarse-grained simulations with the martini force field . J Chem Theory Comput 11 , 4486 – 4494 ( 2015 ). OpenUrl CrossRef PubMed 85. ↵ Abraham MJ , et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers . SoftwareX 1-2 , 19 – 25 ( 2015 ). OpenUrl 86. ↵ Periole X , Cavalli M , Marrink SJ , Ceruso MA . Combining an elastic network with a coarse-grained molecular force field: Structure, dynamics, and intermolecular recognition . J Chem Theory Comput 5 , 2531 – 2543 ( 2009 ). OpenUrl CrossRef PubMed 87. ↵ Yesylevskyy SO , Schäfer LV , Sengupta D , Marrink SJ . Polarizable water model for the coarse-grained MARTINI force field . PLoS Comput Biol 6 , e1000810 ( 2010 ). OpenUrl CrossRef PubMed 88. ↵ Atsmon-Raz Y , Tieleman DP . Parameterization of palmitoylated cysteine, farnesylated cysteine, geranylgeranylated cysteine, and myristoylated glycine for the martini force field . J Phys Chem B 121 , 11132 – 11143 ( 2017 ). OpenUrl CrossRef 89. ↵ Bussi G , Donadio D , Parrinello M . Canonical sampling through velocity rescaling . J Chem Phys 126 , 014101 ( 2007 ). OpenUrl CrossRef PubMed 90. ↵ Parrinello M , Rahman A . Polymorphic transitions in single crystals: A new molecular dynamics method . J Appl Phys 52 , 7182 – 7190 ( 1981 ). OpenUrl CrossRef PubMed Web of Science 91. ↵ Michaud-Agrawal N , Denning EJ , Woolf TB , Beckstein O . MDAnalysis: a toolkit for the analysis of molecular dynamics simulations . J Comput Chem 32 , 2319 – 2327 ( 2011 ). OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted October 15, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about bioRxiv. 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