Computational structural biology aims to accurately predict biomolecular complexes with
AlphaFold 3 spearheading the field. However, challenges loom for structural analysis …

Abstract Predicting three-dimensional (3D) protein structures has been challenging for
decades. The emergence of AlphaFold2 (AF2), a deep learning-based machine learning …

Aflatoxin B1 (AFB1) accumulates in crops, where it poses a threat to human health. To detect
AFB1, anti-AFB1 monoclonal antibodies have been developed and are widely used. While …

The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in
many oncological diseases. This checkpoint protein inhibits T lymphocytes from attacking …

Antibodies play critical roles in modern medicine, serving as diagnostics and therapeutics
for various diseases due to their ability to specifically bind to target antigens. Traditional …

The HADDOCK team participated in CAPRI rounds 47–55 as server, manual predictor, and
scorers. Throughout these CAPRI rounds, we used a plethora of computational strategies to …

Nanobodies, the smallest functional antibody fragment derived from camelid heavy‐chain‐
only antibodies, have emerged as powerful tools for diverse biomedical applications. In this …

Integrative modeling of macromolecular assemblies allows for structural characterization of
large assemblies that are recalcitrant to direct experimental observation. A Bayesian …

Defining the binding epitopes of antibodies is essential for understanding how they bind to
their antigens and perform their molecular functions. However, while determining linear …

The advent of sequence-to-structure deep-learning models have transformed protein
engineering landscape by providing an accurate and cost effective way to determine crystal …