由于它们具有简单的能量项,这些SFs擅长于预测结合亲和力、配体构象和具有低计算成本的虚拟筛选[46],但它们不适合描述结合亲和力与晶体结构之间的关系,而且会遇到双计数问题[47]。 4 Knowledge‑Based Scoring Functions 基于知识的打分函数(Knowledge-based SFs)[48, 49]根据逆玻尔兹曼统计原理,从大量的蛋白质-配体复合...
Molecule 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 a promising alternative for protein–...
Molecular docking tests were conducted on four additional data sets, each of which consisted of some congeneric ligand molecules for one target protein. Application of KGS2 also led to somewhat improved re- sults. We demonstrate in this study that the perform- ance of current scoring functions ...
Development of filter functions for protein-ligand docking Current docking methods can generate bound conformations of a ligand close to the experimentally observed structure of a -ligand complex. However, the scor... M Stahl,HJ Böhm - 《Journal of Molecular Graphics & Modelling》 被引量: 129...
protein dockingshape complementaritypairwise shape complementaritybenchmarkFast Fourier TransformShape complementarity is the most basic ingredient of the scoring functions for protein-protein docking. Most grid-based docking algorithms use the total number of grid points at the binding interface to quantify...
Target-specific optimization of scoring functions for protein–ligand docking is an effective method for significantly improving the discrimination of active and inactive molecules in virtual screening applications. Its applicability, however, is limited due to the narrow focus on, e.g., single protein...
Korb O, Stützle T, Exner TE (2009) Empirical scoring functions for advanced protein-ligand docking with PLANTS. J Chem Inf Model 49(1):84–96. https://doi.org/10.1021/ci800298z ISSN 1549-9596 Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll ...
Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically co...
A knowledge-based scoring function for protein-ligand interactions: Probing the reference state Knowledge-based scoring functions have recently emerged as an alternative and very promising way of ranking protein-ligand complexes with known 3D structur... I Muegge - 《Perspectives in Drug Discovery & ...
The class of empirical scoring functions aims to provide them via a regression-based approach. Using experimental structures and affinity data of protein-ligand complexes and descriptors suitable to capture the essential features of the interaction, these functions are trained with classical linear ...