Rafaël Najmanovich

NRGRank: Coarse-grained structurally-informed ultra-massive virtual screening

NRGRank is a fast, accurate virtual screening tool that outperforms docking methods on some targets and complements them on others, enabling efficient large-scale screening.

Comprehensive Analysis of SARS-CoV-2 Spike Evolution: Epitope Classification and Immune Escape Prediction

This paper analyzes SARS-CoV-2 Spike protein evolution, identifying epitopes and predicting immune escape by correlating structural and sequence data with DMS measurements.

NRGSuite-Qt: A PyMOL plugin for high-throughput virtual screening, molecular docking, normal-mode analysis, the study of molecular interactions and the detection of binding-site similarities

NRGSuite-Qt is a PyMOL plugin that integrates multiple tools for protein modeling and analysis, improving workflow efficiency and performance in normal mode analysis.

TRIM7 ubiquitinates SARS-CoV-2 membrane protein to limit apoptosis and viral replication

This study identifies TRIM7 as an E3-ubiquitin ligase that ubiquitinates SARS-CoV-2 M protein to inhibit apoptosis and viral replication.

Surfaces: A software to quantify and visualize interactions within and between proteins and ligands

Surfaces quantifies and visualizes molecular interactions using surface area calculations, showing comparable results to expensive molecular dynamics methods.

The Elastic Network Contact Model applied to RNA: enhanced accuracy for conformational space prediction

The paper adapts the Elastic Network Contact Model (ENCoM) for RNA dynamics, showing improved accuracy in predicting conformational changes and structural variance compared to existing methods.

A coarse-grained elastic network atom contact model and its use in the simulation of protein dynamics and the prediction of the effect of mutations

This paper introduces ENCoM, a new elastic network contact model for protein dynamics simulation and mutation effect prediction, showing comparable accuracy to existing methods and reduced bias in predicting stabilizing mutations.