Da Silva, F.

Exhaustive Repertoire of Druggable Cavities at Protein-Protein Interfaces of Known Three-Dimensional Structure

Protein-protein interactions (PPIs) offer the unique opportunity to tailor ligands aimed at specifically stabilizing or disrupting the corresponding interfaces and providing a …

Da Silva, F.

Unsupervised Classification of G-Protein Coupled Receptors and Their Conformational States Using IChem Intramolecular Interaction Patterns

Over the past decade, the ever-growing structural information on G-protein coupled receptors (GPCRs) has revealed the three-dimensional (3D) characteristics of a receptor structure …

Koensgen, F.

All in One: Cavity Detection, Druggability Estimate, Cavity-Based Pharmacophore Perception, and Virtual Screening

Discovering the very first ligands of pharmacologically important targets in a fast and cost-efficient manner is an important issue in drug discovery.

Tran-Nguyen, V.

IChem: A Versatile Toolkit for Detecting, Comparing, and Predicting Protein–Ligand Interactions

Abstract Structure-based ligand design requires an exact description of the topology of molecular entities under scrutiny.

Da Silva, F.

Structure-Based Detection of Orthosteric and Allosteric Pockets at Protein-Protein Interfaces

Protein-protein interfaces represent challenging but very promising targets to discover novel drugs with exquisite specificity profiles.

Da Silva, F.

Ranking docking poses by graph matching of protein–ligand interactions: lessons learned from the D3R Grand Challenge 2

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, …

Da Silva Figueiredo Celestino Gomes, P.

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015

High affinity ligands for a given target tend to share key molecular interactions with important anchoring amino acids and therefore often present quite conserved interaction …

Slynko, I.

IChemPIC: A Random Forest Classifier of Biological and Crystallographic Protein–Protein Interfaces

Protein–protein interactions are becoming a major focus of academic and pharmaceutical research to identify low molecular weight compounds able to modulate oligomeric signaling …

Da Silva, F.