Validation of an Allosteric Binding Site of Src Kinase Identified by Unbiased Ligand Binding Simulations. Issue 17 (15th September 2022)

• Record Type: Journal Article
• Authors: Mingione, Victoria R.; Foda, Zachariah H.; Paung, YiTing; Philipose, Hannah; Rangwala, Aziz M.; Shan, Yibing; Seeliger, Markus A.
• Is Part Of: Journal of molecular biology. Volume 434:Issue 17(2022)
• Publication Date: 2022-09-15
• Subjects: docking -- drug binding process -- cancer -- NMR -- inhibitor; FDA Food and Drug Administration -- PTK protein tyrosine kinase -- TROSY transverse relaxation-optimized spectroscopy -- HSQC heteronuclear single quantum correlation -- CSP chemical shift perturbation -- IP intensity perturbation -- STD-NMR saturation transfer difference – nuclear magnetic resonance -- KD kinase domain -- Src 3D Src kinase containing the Src homology 3, 2 and 1 domains -- MD molecular dynamics -- SD standard deviation -- SEM standard error of the mean -- DSF differential scanning fluorimetry -- ADME Adsorption distribution metabolism excretion; Molecular biology -- Periodicals; Biology -- Periodicals; Biochemistry -- Periodicals; Bacteriology -- Periodicals; Molecular Biology -- Periodicals; Biochemistry -- Periodicals; Biologie moléculaire -- Périodiques; Biologie -- Périodiques; Biochimie -- Périodiques; Moleculaire biologie; Biochemistry; Biology; Molecular biology; Periodicals; 572.805
• DOI: 10.1016/j.jmb.2022.167628
• Languages: English
• ISSNs: 0022-2836

Abstract

Graphical abstract: Highlights: Druggable allosteric sites are desirable, yet they are difficult to identify. Our unbiased ligand binding simulations predict allosteric sites in Src kinase. We confirm a novel allosteric regulatory site in the G-loop of Src kinase. We present a new Src-selective small-molecule inhibitor that targets the G-loop site. This may be a generalizable method to predict novel allosteric drug binding sites. Abstract: Allostery plays a primary role in regulating protein activity, making it an important mechanism in human disease and drug discovery. Identifying allosteric regulatory sites to explore their biological significance and therapeutic potential is invaluable to drug discovery; however, identification remains a challenge. Allosteric sites are often "cryptic" without clear geometric or chemical features. Since allosteric regulatory sites are often less conserved in protein kinases than the orthosteric ATP binding site, allosteric ligands are commonly more specific than ATP competitive inhibitors. We present a generalizable computational protocol to predict allosteric ligand binding sites based on unbiased ligand binding simulation trajectories. We demonstrate the feasibility of this protocol by revisiting our previously published ligand binding simulations using the first identified viral proto-oncogene, Src kinase, as a model system. The binding paths for kinase inhibitor PP1 uncovered three metastable intermediate states before binding the high-affinity ATP-binding pocket, revealing two previously known allosteric sites and one novel site. Herein, we validate the novel site using a combination of virtual screening and experimental assays to identify a V-type allosteric small-molecule inhibitor that targets this novel site with specificity for Src over closely related kinases. This study provides a proof-of-concept for employing unbiased ligand binding simulations to identify cryptic allosteric binding sites and is widely applicable to other protein–ligand systems.