1.1k citations · 1.6k across the 25 of their papers we have counts for
27 papers
Evaluating Electrostatic Embedding MLIP/MM for Relative Binding Free Energy Calculations
Stephen E. Farr, Gianni De Fabritiis
Alchemical relative binding free energy (RBFE) calculations are limited by the fixed-charge approximation of classical force fields. Hybrid machine learning interatomic potential/m…
Acep: Thermodynamics-Informed p Prediction and Protonation-State Generation in PlayMolecule AI
Francesco Pesce, Stephen Farr, Gianni de Fabritiis
The acid dissociation constants (p) and the protonation states that they determine govern solubility, permeability, and protein--ligand binding, making their accurate pr…
On Machine Learning Approaches for Protein-Ligand Binding Affinity Prediction
Nikolai Schapin, Carles Navarro, Albert Bou +1
Binding affinity optimization is crucial in early-stage drug discovery. While numerous machine learning methods exist for predicting ligand potency, their comparative efficacy rema…
PlayMolecule pKAce: Small Molecule Protonation through Equivariant Neural Networks
Nikolai Schapin, Maciej Majewski, Mariona Torrens-Fontanals +1
Small molecule protonation is an important part of the preparation of small molecules for many types of computational chemistry protocols. For this, a correct estimation of the pKa…
mdCATH: A Large-Scale MD Dataset for Data-Driven Computational Biophysics
Antonio Mirarchi, Toni Giorgino, Gianni De Fabritiis
Recent advancements in protein structure determination are revolutionizing our understanding of proteins. Still, a significant gap remains in the availability of comprehensive data…
BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO
Sebastian Dittert, Vincent Moens, Gianni De Fabritiis
We present BricksRL, a platform designed to democratize access to robotics for reinforcement learning research and education. BricksRL facilitates the creation, design, and trainin…