Author

Gennady M. Verkhivker

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#protein folding Open access Oct 2026

Frustration Quenching and Network Topology of the Energy Landscape as Primary Determinants of Protein–Ligand Binding Pose Prediction by Deep Learning Models

Deep learning co-folding and docking models accurately predict ligand binding poses at orthosteric sites yet systematically underperform at allosteric pockets. Here, we demonstrate that this accuracy gap reflects a fundamental biophysical property of local energy landscape topology specifically, the magnitude of frustr...

L. Turano, Brandon Foley, Ryan Dennis et al. · bioRxiv · 0 citations

Sep 2026

Contrasting dynamic and mechanistic signatures of Class 3 and Class 4 neutralizing antibodies targeting SARS-CoV-2 spike protein: dissecting molecular determinants of neutralization mechanisms using a multi-pronged computational approach.

An integrated computational framework combining structural analysis, conformational dynamics, mutational scanning, binding energetics, and allosteric network modeling to systematically dissect Class 3 and Class 4 antibodies provides a generalizable paradigm for understanding antibody neutralization mechanisms, predicti...

Mohammed Alshahrani, Will Gatlin, Max Ludwick et al. · Physical Chemistry, Chemical... · 0 citations

Open access Aug 2026

Dynamics-aware geometric learning predicts disease-associated molecular perturbations

DynGeo-Pheno is presented, a unified geometric deep learning framework that integrates protein language model representations with anisotropic network model–derived dynamics to jointly capture evolutionary, structural, and biophysical information and establishes a unified framework for interpretable AI predictions and...

Yuhan Ning, Mingyue Cai, Dongfang Luo et al. · bioRxiv · 0 citations

Open access Jul 2026

Localized Rigidification and Allosteric Modulation Mechanisms of SARS-CoV-2 Spike Neutralization by Class 3 and Class 4 Antibodies at Atomic Resolution: An Integrated Computational Study of Binding, Dynamics, and Allostery

An integrated computational framework combining structural analysis, conformational dynamics, mutational scanning, binding energetics, and allosteric network modeling is employed to dissect the mechanistic signatures of class 3 and class 4 antibodies targeting the receptor-binding domain of the SARS-CoV-2 spike protein...

Mohammed Alshahrani, Will Gatlin, Max Ludwick et al. · bioRxiv · 0 citations

Open access Jul 2026

Decoding the allosteric grammar of protein kinases: A dual‐stream framework integrating protein language models and energy landscape frustration analysis

This study reveals how the organization of the protein energy landscape shapes universal "allosteric grammar" and algorithmic detectability of regulatory binding sites and proposes that allosteric sites are encoded in persistent neutrally frustrated regions optimized for context‐dependent regulatory modulation.

Will Gatlin, Max Ludwick, L. Turano et al. · Protein Science · 1 citation