Brian Jiménez‐García

HADDOCK3 is a new modular platform for integrative biomolecular complex modelling, offering enhanced flexibility and integration with third-party tools to complement machine learning predictions.

The paper summarizes HADDOCK's performance in CAPRI rounds 47-55, highlighting the effectiveness of integrating HADDOCK with AI-driven methods like AlphaFold2 for protein complex structure prediction.

The paper presents a computational method to predict PROTAC-compatible protein-protein interfaces using docking and scoring techniques, achieving high accuracy in benchmark tests.

This paper introduces a membrane-driven docking protocol for modeling membrane-associated protein complexes using AI-based methods and evaluates its performance.

proABC-2 predicts antibody-antigen contacts using a convolutional neural network and integrates with HADDOCK for docking.

The paper introduces a two-step method to improve protein docking simulations by incorporating interface information, showing significant performance gains over blind docking.

MuGVRE provides a cloud-based infrastructure for 3D/4D genomics analysis, supporting both high-computational and high-throughput applications.

SKEMPI 2.0 updates a database of binding energy changes upon mutation with expanded data on kinetics, thermodynamics, and binding abolition.