Evaluation of AlphaFold antibody–antigen modeling with implications for improving predictive accuracy
High resolution antibody–antigen structures provide critical insights into immune recognition
and can inform therapeutic design. The challenges of experimental structural determination …
and can inform therapeutic design. The challenges of experimental structural determination …
Revolutionizing protein–protein interaction prediction with deep learning
Protein–protein interactions (PPIs) are pivotal for driving diverse biological processes, and
any disturbance in these interactions can lead to disease. Thus, the study of PPIs has been …
any disturbance in these interactions can lead to disease. Thus, the study of PPIs has been …
Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking
Motivation Antibody-antigen complex modelling is an important step in computational
workflows for therapeutic antibody design. While experimentally determined structures of …
workflows for therapeutic antibody design. While experimentally determined structures of …
Integrative modeling meets deep learning: Recent advances in modeling protein assemblies
B Shor, D Schneidman-Duhovny - Current Opinion in Structural Biology, 2024 - Elsevier
Recent progress in protein structure prediction based on deep learning revolutionized the
field of Structural Biology. Beyond single proteins, it also enabled high-throughput prediction …
field of Structural Biology. Beyond single proteins, it also enabled high-throughput prediction …
The structure assessment web server: for proteins, complexes and more
The 'structure assessment'web server is a one-stop shop for interactive evaluation and
benchmarking of structural models of macromolecular complexes including proteins and …
benchmarking of structural models of macromolecular complexes including proteins and …
Leveraging coevolutionary insights and AI-based structural modeling to unravel receptor–peptide ligand-binding mechanisms
Secreted signaling peptides are central regulators of growth, development, and stress
responses, but specific steps in the evolution of these peptides and their receptors are not …
responses, but specific steps in the evolution of these peptides and their receptors are not …
TT3D: Leveraging precomputed protein 3D sequence models to predict protein–protein interactions
Motivation High-quality computational structural models are now precomputed and available
for nearly every protein in UniProt. However, the best way to leverage these models to …
for nearly every protein in UniProt. However, the best way to leverage these models to …
[HTML][HTML] CAPRI-Q: The CAPRI resource evaluating the quality of predicted structures of protein complexes
KW Collins, MM Copeland, G Brysbaert… - Journal of Molecular …, 2024 - Elsevier
Protein interactions are essential for cellular processes. In recent years there has been
significant progress in computational prediction of 3D structures of individual protein chains …
significant progress in computational prediction of 3D structures of individual protein chains …
Architecture of full-length type I modular polyketide synthases revealed by X-ray crystallography, cryo-electron microscopy, and AlphaFold2
SR Bagde, CY Kim - Natural Product Reports, 2024 - pubs.rsc.org
Covering: up to the end of 2023Type I modular polyketide synthases construct polyketide
natural products in an assembly line-like fashion, where the growing polyketide chain …
natural products in an assembly line-like fashion, where the growing polyketide chain …
Critical assessment of methods of protein structure prediction (CASP)—Round XV
Computing protein structure from amino acid sequence information has been a long‐
standing grand challenge. Critical assessment of structure prediction (CASP) conducts …
standing grand challenge. Critical assessment of structure prediction (CASP) conducts …