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.
Interformer: an interaction-aware model for protein-ligand docking …
2024年11月25日 · As a crucial task in optimization of drug molecular structures, protein-ligand docking is to predict the position and orientation of a ligand (a small molecule) when it binds to a protein...
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.
DynamicBind: predicting ligand-specific protein-ligand complex ...
2024年2月5日 · In this study, we present DynamicBind, a deep learning method that employs equivariant geometric diffusion networks to construct a smooth energy landscape, promoting efficient transitions between...
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. From: Drug Discovery Today: Technologies, 2012
Insights into Protein–Ligand Interactions: Mechanisms, Models, …
In the present review, first, the physicochemical mechanisms underlying protein–ligand binding, including the binding kinetics, thermodynamic concepts and relationships, and binding driving forces, are introduced and rationalized.
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...
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.
Protein-Ligand Docking in the Machine-Learning Era - PubMed
2022年7月18日 · 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.
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