EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction

7 February 2022

Papers citing "EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction"

7 / 107 papers shown

Title
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions Fang Wu Siyuan Li Lirong Wu Dragomir R. Radev Stan Z. Li 27 2 0 15 May 2022
In-Pocket 3D Graphs Enhance Ligand-Target Compatibility in Generative Small-Molecule Creation Seung-gu Kang J. Weber Joseph A. Morrone Leili Zhang T. Huynh Wendy D. Cornell DiffM 11 3 0 05 Apr 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 31 86 0 28 Mar 2022
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands Ayan Chatterjee Robin G. Walters Zohair Shafi O. Ahmed Michael Sebek D. Gysi Rose Yu Tina Eliassi-Rad A. Barabási G. Menichetti AI4CE 16 4 0 25 Dec 2021
Structure-aware generation of drug-like molecules Pavol Drotár Arian R. Jamasb Ben Day Cătălina Cangea Pietro Lió 26 17 0 07 Nov 2021
DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction Alex Morehead Chen Chen A. Sedova Jianlin Cheng 6 24 0 06 Jun 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 203 1,238 0 08 Jan 2021