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Gerard van Westen

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Full Professor AI & Medicinal Chemistry

Leiden University

Netherlands

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About

Gerard van Westen is a Full Professor of AI & Medicinal Chemistry at Universiteit Leiden in the Netherlands. His research focuses on the interaction of HLA-E/peptide complexes with immune receptors, the synthesis of novel drug design tools, and the application of computational methods to understand ligand binding and receptor function. He has contributed to recent publications exploring the optimization of drug candidates and the role of membrane proteins in cancer treatment.

Recent Grants

Grant: Open

OncodePACT

Open Date: 2023-01-01

Close Date: 2032-01-01

Grant: Close

DrugTRAIN

Open Date: 2021-01-01

Close Date: 2024-01-01

Grant: Close

AI for Computational Life Sciences

Open Date: 2021-01-01

Close Date: 2026-01-01

Grant: Close

Building an Artificial Intelligence Infrastructure for Mechanistic Pathology Understanding (MechPath)

Open Date: 2021-01-01

Close Date: 2023-01-01

Grant: Close

The Virtual Human Platform for Safety Assessment

Open Date: 2021-01-01

Close Date: 2026-01-01

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Collaborators (17)

David Mobley

Professor

University of California, Irvine

UNITED STATES

Gerard van Westen

Research Interests

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About

Recent Grants

Articles (34)

Doing More with Less: Accurate and Scalable Ligand Free Energy Calculations by Focusing on the Binding Site

PyTEA-O: a Python implementation of Two-Entropies Analysis for protein sequence variation analysis

In silico prediction of endocrine activity

IMERGE-FEP: Improving Relative Free Energy Calculation Convergence with Chemical Intermediates

In Search of Beautiful Molecules: A Perspective on Generative Modeling for Drug Design

Toward Assay-Aware Bioactivity Model(er)s: Getting a Grip on Biological Context

HLA-E/peptide complexes differentially interact with NKG2A/CD94 and T cell receptors

Generate what you can make: achieving in-house synthesizability with readily available resources in de novo drug design

Improved Translational Relevance of In Vitro Fibrosis Models by Integrating IOX2-Mediated Hypoxia-Mimicking Pathways

A Patient‐Derived 3D Cyst Model of Polycystic Kidney Disease That Mimics Disease Development and Responds to Repurposing Candidates

Combining Bayesian and Evidential Uncertainty Quantification for Improved Bioactivity Modeling

Combining AlphaFold with Focused Virtual Library Design in the Development of Novel CCR2 and CCR5 Antagonists

Machine Learning-Identified Potent Antimicrobial Peptides Against Multidrug-Resistant Bacteria and Skin Infections

Identification of determinants of high-fidelity DNA synthesis in mycobacterium smegmatis DnaE1 through in silico and in vivo approaches

Barcode-free hit discovery from massive libraries enabled by automated small molecule structure annotation

PyVADesign: a python-based cloning tool for one-step generation of large mutant libraries

Integrating Pharmacokinetics and Quantitative Systems Pharmacology Approaches in Generative Drug Design

N-Acyl-N-Alkyl Sulfonamide Probes for Ligand-Directed Covalent Labeling of GPCRs: The Adenosine A2B Receptor as Case Study

Exploring novel dilazep derivatives as hENT1 inhibitors and potentially covalent molecular tools

Computational Characterization of Membrane Proteins as Anticancer Targets: Current Challenges and Opportunities

The effect of cancer-associated mutations on ligand binding and receptor function

AlphaFold Meets De Novo Drug Design: Leveraging Structural Protein Information in Multitarget Molecular Generative Models

Stereochemical optimization of N,2-substituted cycloalkylamines as norepinephrine reuptake inhibitors

CalcAMP: A New Machine Learning Model for the Accurate Prediction of Antimicrobial Activity of Peptides

Development of an Affinity-Based Probe to Profile Endogenous Human Adenosine A3 Receptor Expression

DrugEx: Deep Learning Models and Tools for Exploration of Drug-Like Chemical Space

Large-Scale Modeling of Sparse Protein Kinase Activity Data

Artificial intelligence in multi-objective drug design

Proteochemometric Modeling Identifies Chemically Diverse Norepinephrine Transporter Inhibitors

Collaborative SAR Modeling and Prospective In Vitro Validation of Oxidative Stress Activation in Human HepG2 Cells

Hypoxia Triggers TAZ Phosphorylation in Basal A Triple Negative Breast Cancer Cells

Identifying Novel Inhibitors for Hepatic Organic Anion Transporting Polypeptides by Machine Learning-Based Virtual Screening

Impact of cancer-associated mutations in CC chemokine receptor 2 on receptor function and antagonism

Pan-cancer functional analysis of somatic mutations in G protein-coupled receptors

Collaborators (17)

David Mobley

Willem Jespers

Lars Verschuren

Peter Steinberger

Johan Åqvist

Alexander Julian

Jan Wouter Drijfhout

Sylvia Emmanuelle Le Dévédec

Dorien Peters

Ad IJzerman

Olivier JM BÉQUIGNON

erik danen

Mike Preuss

Martijn Riool

Alzbeta Tuerkova

Barbara Zdrazil

Antti Poso

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