Protein–ligand docking - Wikipedia
Protein–ligand docking is a molecular modelling technique. The goal of protein–ligand docking is to predict the position and orientation of a ligand (a small molecule) when it is bound to a protein receptor or enzyme. [1]
DynamicBind: predicting ligand-specific protein-ligand complex …
2024年2月5日 · DynamicBind executes “dynamic docking”, a process that performs prediction of the protein–ligand complex structure while accommodating substantial protein conformational changes.
Computational protein-ligand docking and virtual drug screening …
Computational docking can be used to predict bound conformations and free energies of binding for small molecule ligands to macromolecular targets. Docking is widely used for the study of biomolecular interactions and mechanisms, and is applied to structure-based drug design.
Computational protein–ligand docking and virtual drug ... - Nature
2016年4月14日 · Computational docking can be used to predict bound conformations and free energies of binding for small-molecule ligands to macromolecular targets. Docking is widely used for the study of...
Protein-Ligand Docking - an overview | ScienceDirect Topics
Protein-ligand docking is the most important structure-based 3D approach, which aims at predicting the binding mode of a ligand for a protein with known 3D structure, assuming the protein binding site to be mostly rigid and the ligand to be flexible.
Protein–Ligand Docking in the Machine-Learning Era - PMC
Molecular docking plays a significant role in early-stage drug discovery, from structure-based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive power is critically dependent on the protein–ligand scoring function.
Advances and Challenges in Protein-Ligand Docking - PMC
An important type of molecular docking is protein-ligand docking because of its therapeutic applications in modern structure-based drug design. Here, we review the recent advances of protein flexibility, ligand sampling, and scoring functions—the three important aspects in …
Deep Learning Model for Efficient Protein–Ligand Docking with …
2023年3月14日 · 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 docking programs for pose prediction are optimized for redocking to an existing cocrystallized protein structure, ignoring protein flexibility.
PGBind: pocket-guided explicit attention learning for protein–ligand …
2024年9月18日 · In this work, we propose a pocket-guided strategy for guiding the ligand to dock to potential docking regions on a protein. To this end, we design a plug-and-play module to enhance the protein features, which can be directly incorporated into existing deep learning-based blind docking methods.
AutoDockFR : Advances in Protein-Ligand Docking with Explicitly …
2015年12月2日 · We present AutoDockFR – AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function.