Protein Ligand

Protein-ligand interactions are crucial for understanding biological processes and drug discovery, with primary research objectives focused on accurately predicting binding affinity and 3D structure of complexes. Current research heavily utilizes machine learning, employing graph neural networks, diffusion models, and transformer architectures to analyze protein and ligand structures, often incorporating geometric and physicochemical information to improve prediction accuracy and efficiency. These advancements significantly impact drug development by enabling faster and more accurate virtual screening, leading to improved drug design and reduced development costs.

Papers

June 23, 2022

CoSP: Co-supervised pretraining of pocket and ligand
Zhangyang Gao, Cheng Tan, Lirong Wu, Stan Z. Li
Molecular Property Prediction Negative Sampling Protein Ligand Virtual Screening Novel Ligand Co Training Pre Training Task New POCKET

May 25, 2022

SS-GNN: A Simple-Structured Graph Neural Network for Affinity Prediction
Shuke Zhang, Yanzhao Jin, Tianmeng Liu, Qi Wang, Zhaohui Zhang, Shuliang Zhao, Bo Shan
Graph Neural Network Gene Level GNN Protein Ligand Affinity Prediction Feature Aggregation Network

May 14, 2022

High Performance of Gradient Boosting in Binding Affinity Prediction
Dmitrii Gavrilev, Nurlybek Amangeldiuly, Sergei Ivanov, Evgeny Burnaev
Drug Discovery Gradient Boosting Protein Ligand High Performance Gradient Boosted Decision Tree Binding Affinity

April 5, 2022

In-Pocket 3D Graphs Enhance Ligand-Target Compatibility in Generative Small-Molecule Creation
Seung-gu Kang, Jeffrey K. Weber, Joseph A. Morrone, Leili Zhang, Tien Huynh, Wendy D. Cornell
Molecule Generation Structure Based Drug Design Protein Ligand 3D Graph Ligand Based Generative Molecular Design

March 25, 2022

Meaningful machine learning models and machine-learned pharmacophores from fragment screening campaigns
Carl Poelking, Gianni Chessari, Christopher W. Murray, Richard J. Hall, Lucy Colwell, Marcel Verdonk
Machine Learning Model Drug Discovery Protein Ligand Molecular Structure Molecular Modeling Large Scale Screening Pharmacophore Modeling

December 25, 2021

AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands
Ayan Chatterjee, Robin Walters, Zohair Shafi, Omair Shafi Ahmed, Michael Sebek, Deisy Gysi, Rose Yu, Tina Eliassi-Rad, Albert-László Barabási, Giulia Menichetti
Drug Discovery Protein Ligand Drug Target Interaction Protein Target Novel Ligand Protein Graph

November 30, 2021

Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks
Carter Knutson, Mridula Bontha, Jenna A. Bilbrey, Neeraj Kumar
Graph Neural Network Protein Ligand Novel Ligand Molecular Interaction Scalable Graph Neural Network

November 7, 2021

Structure-aware generation of drug-like molecules
Pavol Drotár, Arian Rokkum Jamasb, Ben Day, Cătălina Cangea, Pietro Liò
Molecular Graph Structure Based Drug Design Protein Ligand Virtual Screening Drug Like Structured Generation Molecular Shape