New empirical scoring functions have been developed to estimate the binding affinity of a given protein-ligand complex with known three-dimensional structure.
Summary. New empirical scoring functions have been developed to estimate the binding affinity of a given protein-ligand complex with known three-dimensional�...
New empirical scoring functions have been developed to estimate the binding affinity of a given protein-ligand complex with known three-dimensional�...
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The results show that this consensus scoring function, X-CSCORE, improves the docking accuracy considerably when compared to the conventional force field�...
New empirical scoring functions have been developed to estimate the binding affinity of a given protein-ligand complex with known three-dimensional structure.
Sep 24, 2018 � This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects.
Feb 4, 2021 � We developed a set of new empirical scoring functions, named DockTScore, by explicitly accounting for physics-based terms combined with machine learning.
The development of scoring functions has advanced further with the integration of machine learning models for bioactivity assessment. Recently, neural networks�...
Wang R, Lai L, Wang S. Further development and validation of empirical scoring functions for structure-based binding affinity prediction.
Here we review structure-based scoring functions for binding affinity prediction based on deep learning, focussing on different types of architectures,�...