23 citations · 23 across the 1 of their papers we have counts for
6 papers
Leak Proof PDBBind: A Reorganized Dataset of Protein-Ligand Complexes for More Generalizable Binding Affinity Prediction
Jie Li, Xingyi Guan, Oufan Zhang +4
The majority of machine learning scoring functions used in drug discovery for predicting protein-ligand binding poses and affinities have been trained on the PDBBind dataset. Howev…
Deep Learning of Proteins with Local and Global Regions of Disorder
Oufan Zhang, Zi Hao Liu, Julie D Forman-Kay +1
Although machine learning has transformed protein structure prediction of folded protein ground states with remarkable accuracy, intrinsically disordered proteins and regions (IDPs…
A Workflow to Create a High-Quality Protein-Ligand Binding Dataset for Training, Validation, and Prediction Tasks
Yingze Wang, Kunyang Sun, Jie Li +4
Development of scoring functions (SFs) used to predict protein-ligand binding energies requires high-quality 3D structures and binding assay data for training and testing their par…
Biological Insights from Integrative Modeling of Intrinsically Disordered Protein Systems
Zi Hao Liu, Maria Tsanai, Oufan Zhang +2
Intrinsically disordered proteins and regions are increasingly appreciated for their abundance in the proteome and the many functional roles they play in the cell. In this short re…
Computational Methods to Investigate Intrinsically Disordered Proteins and their Complexes
Zi Hao Liu, Maria Tsanai, Oufan Zhang +2
In 1999 Wright and Dyson highlighted the fact that large sections of the proteome of all organisms are comprised of protein sequences that lack globular folded structures under phy…
A Curated Rotamer Library for Common Post-Translational Modifications of Proteins
Oufan Zhang, Shubhankar A. Naik, Zi Hao Liu +2
Sidechain rotamer libraries of the common amino acids of a protein are useful for folded protein structure determination and for generating ensembles of intrinsically disordered pr…