In drug discovery, where a model of the protein structure is known, molecular docking is a well-established approach for predictive modeling. Docking algorithms utilize a search strategy for exploring ligand poses within an active site and a scoring function for evaluating the poses. This ...
此外,可以使用新类型的特征(分子间特征、仅配体和仅蛋白质特征)来提高评分函数的性能,将这些评分函数作为开放软件生成对于这个领域的更多研究人员来说也非常重要。 Li, J., Fu, A. & Zhang, L. An Overview of Scoring Functions Used for Protein–Ligand Interactions in Molecular Docking.Interdiscip Sci Comput...
If my own scoring function use a numpy array to represent the grids of molecules and proteins (the python function to turn them into grid has been completed) , and I need to use my own CNN scoring function model to instruct vina.dock(), I think there is no need to transfer the numpy...
Proteins: Structure, Function, and BioinformaticsChen, R., & Weng, Z. (2003). A novel shape complementarity scoring function for protein-protein docking. Proteins, 51(3), 397-408.Chen, R. and Weng, Z. (2003). A novel shape complementarity scoring function for protein-protein docking. ...
Virtual screening of large chemical libraries plays a key role in lead identification and optimization in rational approaches to pharmaceutical drug discovery. Both ligand-based (e.g. 3D-QSAR) and structure-based (e.g. automated docking) methods are exten-sively used in such screening experiments...
Conversely, DNA–drug and RNA–drug dockings are generally less investigated. In particular, we did not find a QSBR scoring function for DNA–Furocoumarin docking. The furocoumarins are a class of natural or synthetic compounds with very interesting pharmacological properties [47], commonly used in...
Determination of parameter values for a chosen (linear or nonlinear) function to best fit a set of observations. POTENTIAL OF MEAN FORCE (PMF). In the context of docking and scoring, PMFs are derived from statistical analysis of experimentally observed distributions and frequencies of specific atom...
scoring functionstructure‐based drug designMolecule docking has been regarded as a routine tool for drug discovery, but its accuracy highly depends on the reliability of scoring functions (SFs). With the rapid development of machine learning (ML) techniques, ML‐based SFs have gradually emerged as...
Ligand-docking-based methods are starting to play a critical role in lead discovery and optimization, thus resulting in new 'drug-candidates'. They offer t... Claudio,N.,Cavasotto,... - 《Current Topics》 被引量: 186发表: 2007年 Modifications of the scoring function in FlexX for virtual ...
This leads to an improved robustness of the resulting scoring function parameters. Extensive validation experiments clearly demonstrate that (1) virtual screening performance for kinases improves significantly; (2) variations in database content affect this kind of machine-learning strategy to a lesser ...