Jorge Roel‐Touris

The paper introduces SNAC-DB, a database with expanded structural diversity for antibody and NANOBODY VHH-antigen complexes, and benchmarks seven models showing limited accuracy and ranking issues.

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.

This study designs a structurally diverse library of immunoglobulin domains using de novo methods and deep learning, revealing structural requirements and rotational preferences.

The paper reports the cryo-EM structure of a bacterial adhesin complex and identifies epitopes that affect adhesion and motility in Mycoplasma pneumoniae.

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

The paper evaluates HADDOCK's performance in CAPRI rounds 38-45, showing it produces acceptable or better models for most targets using data-driven strategies.

The paper introduces a coarse-grained modeling approach in HADDOCK to predict large biomolecular assemblies, achieving faster calculations with maintained accuracy.

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