Literature DB >> 25647463

Classification of current scoring functions.

Jie Liu1, Renxiao Wang1,2.   

Abstract

Scoring functions are a class of computational methods widely applied in structure-based drug design for evaluating protein-ligand interactions. Dozens of scoring functions have been published since the early 1990s. In literature, scoring functions are typically classified as force-field-based, empirical, and knowledge-based. This classification scheme has been quoted for more than a decade and is still repeatedly quoted by some recent publications. Unfortunately, it does not reflect the recent progress in this field. Besides, the naming convention used for describing different types of scoring functions has been somewhat jumbled in literature, which could be confusing for newcomers to this field. Here, we express our viewpoint on an up-to-date classification scheme and appropriate naming convention for current scoring functions. We propose that they can be classified into physics-based methods, empirical scoring functions, knowledge-based potentials, and descriptor-based scoring functions. We also outline the major difference and connections between different categories of scoring functions.

Mesh:

Substances:

Year:  2015        PMID: 25647463     DOI: 10.1021/ci500731a

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  43 in total

1.  Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks.

Authors:  Zhiqiang Yan; Jin Wang
Journal:  J Comput Aided Mol Des       Date:  2016-02-15       Impact factor: 3.686

Review 2.  Rotamer Dynamics: Analysis of Rotamers in Molecular Dynamics Simulations of Proteins.

Authors:  Yazan Haddad; Vojtech Adam; Zbynek Heger
Journal:  Biophys J       Date:  2019-04-22       Impact factor: 4.033

3.  Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

Authors:  Ying-Duo Gao; Yuan Hu; Alejandro Crespo; Deping Wang; Kira A Armacost; James I Fells; Xavier Fradera; Hongwu Wang; Huijun Wang; Brad Sherborne; Andreas Verras; Zhengwei Peng
Journal:  J Comput Aided Mol Des       Date:  2017-10-06       Impact factor: 3.686

4.  Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization.

Authors:  Maria Kadukova; Sergei Grudinin
Journal:  J Comput Aided Mol Des       Date:  2017-09-18       Impact factor: 3.686

5.  Assessing protein-ligand interaction scoring functions with the CASF-2013 benchmark.

Authors:  Yan Li; Minyi Su; Zhihai Liu; Jie Li; Jie Liu; Li Han; Renxiao Wang
Journal:  Nat Protoc       Date:  2018-03-08       Impact factor: 13.491

6.  Nonparametric chemical descriptors for the calculation of ligand-biopolymer affinities with machine-learning scoring functions.

Authors:  Edelmiro Moman; Maria A Grishina; Vladimir A Potemkin
Journal:  J Comput Aided Mol Des       Date:  2019-11-14       Impact factor: 3.686

7.  The role of human in the loop: lessons from D3R challenge 4.

Authors:  Oleg V Stroganov; Fedor N Novikov; Michael G Medvedev; Artem O Dmitrienko; Igor Gerasimov; Igor V Svitanko; Ghermes G Chilov
Journal:  J Comput Aided Mol Des       Date:  2020-01-21       Impact factor: 3.686

8.  Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions.

Authors:  Jianing Lu; Xuben Hou; Cheng Wang; Yingkai Zhang
Journal:  J Chem Inf Model       Date:  2019-10-31       Impact factor: 4.956

9.  Flexible CDOCKER: Development and application of a pseudo-explicit structure-based docking method within CHARMM.

Authors:  Jessica K Gagnon; Sean M Law; Charles L Brooks
Journal:  J Comput Chem       Date:  2015-12-21       Impact factor: 3.376

10.  The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.

Authors:  Jie Xia; Jui-Hua Hsieh; Huabin Hu; Song Wu; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2017-06-01       Impact factor: 4.956

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.