Low-Quality Structural and Interaction Data Improves Binding Affinity Prediction via Random Forest

Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets

(2015) Hongjian Li et al.   Molecular Informatics

Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case study

(2014) Hongjian Li et al.   BMC BIOINFORMATICS

Does a More Precise Chemical Description of Protein–Ligand Complexes Lead to More Accurate Prediction of Binding Affinity?

(2014) Pedro J. Ballester et al.   Journal of Chemical Information and Modeling

Comparative Assessment of Scoring Functions on an Updated Benchmark: 2. Evaluation Methods and General Results

(2014) Yan Li et al.   Journal of Chemical Information and Modeling

Comparative Assessment of Scoring Functions on an Updated Benchmark: 1. Compilation of the Test Set

(2014) Yan Li et al.   Journal of Chemical Information and Modeling

istar: A Web Platform for Large-Scale Protein-Ligand Docking

(2014) Hongjian Li et al.   PLoS One

Binding Affinity Prediction for Protein–Ligand Complexes Based on β Contacts and B Factor

(2013) Qian Liu et al.   Journal of Chemical Information and Modeling

ID-Score: A New Empirical Scoring Function Based on a Comprehensive Set of Descriptors Related to Protein–Ligand Interactions

(2013) Guo-Bo Li et al.   Journal of Chemical Information and Modeling

Essential considerations for using protein–ligand structures in drug discovery

(2012) Gregory L. Warren et al.   DRUG DISCOVERY TODAY

Characterization of Small Molecule Binding. I. Accurate Identification of Strong Inhibitors in Virtual Screening

(2012) Bo Ding et al.   Journal of Chemical Information and Modeling

Bioinformatics and variability in drug response: a protein structural perspective

(2012) J. L. Lahti et al.   Journal of the Royal Society Interface

Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification

(2012) P. J. Ballester et al.   Journal of the Royal Society Interface

Target-Specific Support Vector Machine Scoring in Structure-Based Virtual Screening: Computational Validation, In Vitro Testing in Kinases, and Effects on Lung Cancer Cell Proliferation

(2011) Liwei Li et al.   Journal of Chemical Information and Modeling

Support Vector Regression Scoring of Receptor–Ligand Complexes for Rank-Ordering and Virtual Screening of Chemical Libraries

(2011) Liwei Li et al.   Journal of Chemical Information and Modeling

Comments on “Leave-Cluster-Out Cross-Validation Is Appropriate for Scoring Functions Derived from Diverse Protein Data Sets”: Significance for the Validation of Scoring Functions

(2011) Pedro J. Ballester et al.   Journal of Chemical Information and Modeling

NNScore 2.0: A Neural-Network Receptor–Ligand Scoring Function

(2011) Jacob D. Durrant et al.   Journal of Chemical Information and Modeling

A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking

(2010) Pedro J. Ballester et al.   BIOINFORMATICS

CREDO: A Protein-Ligand Interaction Database for Drug Discovery

(2009) Adrian Schreyer et al.   Chemical Biology & Drug Design

Comparative Assessment of Scoring Functions on a Diverse Test Set

(2009) Tiejun Cheng et al.   Journal of Chemical Information and Modeling

AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

(2009) Oleg Trott et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY