Deep learning for flexible and site-specific protein docking and design
M McPartlon, J Xu - BioRxiv, 2023 - biorxiv.org
Protein complexes are vital to many biological processes and their understanding can lead
to the development of new drugs and therapies. Although the structure of individual protein …
to the development of new drugs and therapies. Although the structure of individual protein …
Flexible protein–protein docking with a multitrack iterative transformer
Conventional protein–protein docking algorithms usually rely on heavy candidate sampling
and reranking, but these steps are time‐consuming and hinder applications that require high …
and reranking, but these steps are time‐consuming and hinder applications that require high …
Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking
Antibody-antigen complex modelling is an important step in computational workflows for
therapeutic antibody design. While experimentally determined structures of both antibody …
therapeutic antibody design. While experimentally determined structures of both antibody …
Advances to tackle backbone flexibility in protein docking
A Harmalkar, JJ Gray - Current opinion in structural biology, 2021 - Elsevier
Computational docking methods can provide structural models of protein–protein
complexes, but protein backbone flexibility upon association often thwarts accurate …
complexes, but protein backbone flexibility upon association often thwarts accurate …
LightDock: a new multi-scale approach to protein–protein docking
B Jiménez-García, J Roel-Touris… - …, 2018 - academic.oup.com
Motivation Computational prediction of protein–protein complex structure by docking can
provide structural and mechanistic insights for protein interactions of biomedical interest …
provide structural and mechanistic insights for protein interactions of biomedical interest …
Do deep learning models really outperform traditional approaches in molecular docking?
Molecular docking, given a ligand molecule and a ligand binding site (called``pocket'') on a
protein, predicting the binding mode of the protein-ligand complex, is a widely used …
protein, predicting the binding mode of the protein-ligand complex, is a widely used …
Deep learning model for flexible and efficient protein-ligand docking
M Masters, AH Mahmoud, Y Wei… - … Machine Learning for Drug …, 2022 - openreview.net
Protein-ligand docking is an essential tool in structure-based drug design with applications
ranging from virtual high-throughput screening to pose prediction for lead optimization. Most …
ranging from virtual high-throughput screening to pose prediction for lead optimization. Most …
Pre-Training on Large-Scale Generated Docking Conformations with HelixDock to Unlock the Potential of Protein-ligand Structure Prediction Models
L Liu, D He, X Ye, S Zhang, X Zhang, J Zhou… - arXiv preprint arXiv …, 2023 - arxiv.org
Molecular docking, a pivotal computational tool for drug discovery, predicts the binding
interactions between small molecules (ligands) and target proteins (receptors) …
interactions between small molecules (ligands) and target proteins (receptors) …
Integrated structure prediction of protein–protein docking with experimental restraints using ColabDock
S Feng, Z Chen, C Zhang, Y Xie… - Nature Machine …, 2024 - nature.com
Protein complex structure prediction plays important roles in various applications, such as
drug discovery and antibody design. However, due to limited prediction accuracy, there are …
drug discovery and antibody design. However, due to limited prediction accuracy, there are …
[PDF][PDF] Fusiondock: Physics-informed diffusion model for molecular docking
M Masters, A Mahmoud, M Lill - ICML2023 CompBio …, 2023 - icml-compbio.github.io
Protein-ligand docking is an important task in drug discovery and structure-based drug
design. Generative deep learning models have recently emerged as a new approach to …
design. Generative deep learning models have recently emerged as a new approach to …