Merveille Eguida
A5020612989- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- Genetics, Bioinformatics, and Biomedical Research
- vaccines and immunoinformatics approaches
- RNA and protein synthesis mechanisms
- Microbial Natural Products and Biosynthesis
- Image Processing and 3D Reconstruction
- Click Chemistry and Applications
- Research Data Management Practices
- Chemical Synthesis and Analysis
- Monoclonal and Polyclonal Antibodies Research
- Bacterial Genetics and Biotechnology
- thermodynamics and calorimetric analyses
- Genomics and Chromatin Dynamics
- Protein purification and stability
Université de Strasbourg
2020-2024
Centre National de la Recherche Scientifique
2020-2024
Laboratoire d'Innovation Thérapeutique
2020-2024
Merck (Germany)
2020
Accurate ranking of compounds with regards to their binding affinity a protein using computational methods is great interest pharmaceutical research. Physics-based free energy calculations are regarded as the most rigorous way estimate affinity. In recent years, many retrospective studies carried out both in academia and industry have demonstrated its potential. Here, we present results large-scale prospective application FEP+ method active drug discovery projects an setting at Merck KGaA,...
Here we present an evaluation of the binding affinity prediction accuracy free energy calculation method FEP+ on internal active drug discovery projects and a large new public benchmark set.<br>
The CACHE challenges are a series of prospective benchmarking exercises to evaluate progress in the field computational hit-finding. Here we report results inaugural challenge which 23 teams each selected up 100 commercially available compounds that they predicted would bind WDR domain Parkinson's disease target LRRK2, with no known ligand and only an apo structure PDB. lack binding data presumably low druggability is hit finding methods. Of 1955 molecules by participants Round 1 challenge,...
ou non, émanant des établissements d'enseignement et de recherche français étrangers, laboratoires publics privés.
Ultralarge chemical spaces describing several billion compounds are revolutionizing hit identification in early drug discovery. Because of their size, such cannot be fully enumerated and require ad-hoc computational tools to navigate them pick potentially interesting hits. We here propose a structure-based approach ultralarge space screening which commercial reagents first docked the target interest then directly connected according organic chemistry topological rules, enumerate drug-like...
Identifying local similarities in binding sites from distant proteins is a major hurdle to rational drug design. We herewith present novel method, borrowed computer vision, adapted mine fragment subpockets and compare them whole ligand-binding sites. Pockets are represented by pharmacophore-annotated point clouds mimicking ideal ligands or fragments. Point cloud registration used find the transformation enabling an optimal overlap of points sharing similar topological pharmacophoric...
We here describe a computational approach (POEM: Pocket Oriented Elaboration of Molecules) to drive the generation target-focused libraries while taking advantage all publicly available structural information on protein–ligand complexes. A collection 31 384 PDB-derived images with key shapes and pharmacophoric properties, describing fragment-bound microenvironments, is first aligned query target cavity by computer vision method. The fragments most similar PDB subpockets are then directly...
ABSTRACT The CACHE challenges are a series of prospective benchmarking exercises meant to evaluate progress in the field computational hit-finding. Here we report results inaugural #1 challenge which 23 teams each selected up 100 commercially available compounds that they predicted would bind WDR domain Parkinson’s disease target LRRK2, with no known ligand and only an apo structure PDB. lack binding data presumably low druggability is hit finding methods. Seventy-three 1955 procured...
Here we present an evaluation of the binding affinity prediction accuracy free energy calculation method FEP+ on internal active drug discovery projects and a large new public benchmark set.
Here we present an evaluation of the binding affinity prediction accuracy free energy calculation method FEP+ on internal active drug discovery projects and a large new public benchmark set.
Abstract Rationalizing the identification of hidden similarities across repertoire druggable protein cavities remains a major hurdle to true proteome-wide structure-based discovery novel drug candidates. We recently described new computational approach (ProCare), inspired by numerical image processing, identify local in fragment-based subpockets. During validation method, we unexpectedly identified possible similarity binding pockets two unrelated targets, human tumor necrosis factor alpha...
Abstract Ultra-large chemical spaces describing several billion compounds are revolutionizing hit identification in early drug discovery. Because of their size, such cannot be fully enumerated and requires ad-hoc computational tools to navigate them pick potentially interesting hits. We here propose a structure-based approach ultra-large space screening which commercial reagents first docked the target interest then directly connected according organic chemistry topological rules, enumerate...
ABSTRACT Rationalizing the identification of hidden similarities across repertoire druggable protein cavities remains a major hurdle to true proteome-wide structure-based discovery novel drug candidates. We recently described new computational approach (ProCare), inspired by numerical image processing, identify local in fragment-based subpockets. During validation method, we unexpectedly identified possible similarity binding pockets two unrelated targets, human tumor necrosis factor alpha...
Abstract Rationalizing the identification of hidden similarities across repertoire druggable protein cavities remains a major hurdle to true proteome‐wide structure‐based discovery novel drug candidates. We recently described new computational approach (ProCare), inspired by numerical image processing, identify local in fragment‐based subpockets. During validation method, we unexpectedly identified possible similarity binding pockets two unrelated targets, human tumor necrosis factor alpha...