Francesco Luigi Gervasio

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Full Professor

University of Geneva

Switzerland

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Francesco Luigi Gervasio is a Full Professor at the University of Geneva, Switzerland. His research focuses on computational biophysics, particularly in protein folding energy landscapes, ligand binding dynamics, and advanced sampling techniques in molecular dynamics. Recent publications highlight his work on drug discovery, collective variables for enhanced sampling, and machine learning applications in biophysical studies.

Recent Grants

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Understanding and Modelling Cryptic Binding Pockets for Biology and Drug Discovery

Open Date: 2022-03-01

Close Date: 2026-02-01

Grant: Close

Efficient calculation of binding free-energies and druggability in challenging drug targets

Open Date: 2019-09-22

Close Date: 2023-09-28

Grant: Close

Computer Aided Design of Synthetic Viruses

Open Date: 2017-09-24

Close Date: 2021-07-30

Grant: Close

Characterising structure, interactions and dynamics of large molecular machines and intrinsically disordered proteins using novel carbon-detected NMR

Open Date: 2017-07-31

Close Date: 2018-07-30

Grant: Close

Efficient modelling and validation of cryptic protein binding sites for drug discovery

Open Date: 2017-06-30

Close Date: 2020-06-29

Francesco Luigi Gervasio

Research Interests

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About

Recent Grants

Articles (26)

Computational advances in discovering cryptic pockets for drug discovery

The Arch from the Stones: Understanding Protein Folding Energy Landscapes via Bioinspired Collective Variables

Enhanced Sampling and Tailored Collective Variables Yield Reproducible Free Energy Landscapes of Beta-1 Adrenergic Receptor Activation

Learning committor-consistent collective variables

Drug-resistant EGFR mutations promote lung cancer by stabilizing interfaces in ligand-free kinase-active EGFR oligomers

Extended Metadynamics Protocol for Binding/Unbinding Free Energies of Peptide Ligands to Class A G-Protein-Coupled Receptors

DeepLNE++ leveraging knowledge distillation for accelerated multi-state path-like collective variables

Absolute Binding Free Energies with OneOPES

When two kinases go for a dance

Deep learning path-like collective variable for enhanced sampling molecular dynamics

SWISH-X, an Expanded Approach to Detect Cryptic Pockets in Proteins and at Protein–Protein Interfaces

Determinants of Neutral Antagonism and Inverse Agonism in the β2-Adrenergic Receptor

Addressing Suboptimal Poses in Nonequilibrium Alchemical Calculations

Host–Guest Binding Free Energies à la Carte: An Automated OneOPES Protocol

Investigating Ligand-Mediated Conformational Dynamics of Pre-miR21: A Machine-Learning-Aided Enhanced Sampling Study

Subcellular location defines GPCR signal transduction

Architecture of the MKK6-p38α complex defines the basis of MAPK specificity and activation

OneOPES, a Combined Enhanced Sampling Method to Rule Them All

General Metadynamics Protocol To Simulate Activation/Deactivation of Class A GPCRs: Proof of Principle for the Serotonin Receptor

Activation/Deactivation Free-Energy Profiles for the β2-Adrenergic Receptor: Ligand Modes of Action

Revealing druggable cryptic pockets in the Nsp1 of SARS-CoV-2 and other β-coronaviruses by simulations and crystallography

Mechanistic Insights into the Ligand-Induced Unfolding of an RNA G-Quadruplex

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses

Allosteric communication in class a β-lactamases occurs via cooperative coupling of loop dynamics

Structural basis of the effect of activating mutations on the EGF receptor

A different perspective for nonphotochemical quenching in plant antenna complexes

Collaborators (12)

Pratul Agarwal

Susanta Haldar

Timothy Clark

Gilbert Otto Fruhwirth

Catherine Tooke

Zoë A. E. Waller

Miriam Stoeber

Chiara Cabrele

Shozeb Haider

Zoe Cournia

Thorben Fröhlking

Oscar Vadas

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