Binding Affinity

Binding affinity, the strength of interaction between molecules like proteins and ligands, is crucial for drug discovery and materials science. Current research heavily focuses on predicting binding affinity using machine learning, employing diverse architectures such as graph neural networks (GNNs), transformers, and gradient boosting decision trees, often incorporating structural and physicochemical information. These advancements aim to improve the accuracy and efficiency of drug design and materials synthesis by enabling faster and more reliable identification of high-affinity compounds. The development of large datasets and innovative model designs continues to drive progress in this critical area.

Papers

November 6, 2024

BAPULM: Binding Affinity Prediction using Language Models
Radheesh Sharma Meda, Amir Barati Farimani
Language Model Sequence to Sequence Molecular Representation Drug Target Interaction Binding Affinity

September 30, 2024

Binding Affinity Prediction: From Conventional to Machine Learning-Based Approaches
Xuefeng Liu, Songhao Jiang, Xiaotian Duan, Archit Vasan, Chong Liu, Chih-chan Tien, Heng Ma, Thomas Brettin, Fangfang Xia, Ian T. Foster, Rick L. Stevens
New Machine Constructive Approach Small Molecule Drug Like Drug Design Novel Ligand Binding Affinity

August 23, 2024

Zeoformer: Coarse-Grained Periodic Graph Transformer for OSDA-Zeolite Affinity Prediction
Xiangxiang Shen, Zheng Wan, Lingfeng Wen, Licheng Sun, Ou Yang Ming Jie, Xuan Tang, Xian Zeng, Mingsong Chen, Xiao He, Xian Wei
Graph Transformer Crystal Structure Binding Affinity

August 21, 2024

CoPRA: Bridging Cross-domain Pretrained Sequence Models with Complex Structures for Protein-RNA Binding Affinity Prediction
Rong Han, Xiaohong Liu, Tong Pan, Jing Xu, Xiaoyu Wang, Wuyang Lan, Zhenyu Li, Zixuan Wang, Jiangning Song, Guangyu Wang, Ting Chen
Cross Domain Domain Specific Language Model Multi Modal Language Model Affinity Prediction Complex Structure miRNA Description Binding Affinity

July 10, 2024

SPIN: SE(3)-Invariant Physics Informed Network for Binding Affinity Prediction
Seungyeon Choi, Sangmin Seo, Sanghyun Park
Protein Ligand Affinity Prediction Binding Affinity Spin Direction Protein Ligand Binding

June 24, 2024

General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design
Yue Jian, Curtis Wu, Danny Reidenbach, Aditi S. Krishnapriyan
Diffusion Model Structure Based Drug Design Protein Ligand Diffusion Guidance Novel Ligand Binding Affinity

June 11, 2024

DualBind: A Dual-Loss Framework for Protein-Ligand Binding Affinity Prediction
Meng Liu, Saee Gopal Paliwal
New Framework Binding Affinity Denoising Score Matching Protein Ligand Binding Affinity Prediction

April 10, 2024

VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification
Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer
Equivariant Graph Neural Network Protein Data Binding Affinity AlphaFold2 Protein Structure Prediction

October 10, 2023

DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening
Bowen Gao, Bo Qiang, Haichuan Tan, Minsi Ren, Yinjun Jia, Minsi Lu, Jingjing Liu, Weiying Ma, Yanyan Lan
Drug Discovery Virtual Screening Binding Affinity

July 3, 2023

PIGNet2: A Versatile Deep Learning-based Protein-Ligand Interaction Prediction Model for Binding Affinity Scoring and Virtual Screening
Seokhyun Moon, Sang-Yeon Hwang, Jaechang Lim, Woo Youn Kim
Drug Discovery Protein Ligand Virtual Screening Versatile Approach Binding Affinity

February 23, 2023

EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction
Yang Zhang, Zhewei Wei, Ye Yuan, Chongxuan Li, Wenbing Huang
Equivariant Graph Neural Network Binding Affinity Equivariant Message Protein Surface

February 20, 2023

Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation
Daeseok Lee, Jeunghyun Byun, Bonggun Shin
Transfer Learning Small Molecule Feature Augmentation Protein Structure Protein Target Novel Ligand Binding Affinity Se Bi Equivariant Transformer

January 15, 2023

Geometric Graph Learning with Extended Atom-Types Features for Protein-Ligand Binding Affinity Prediction
Md Masud Rana, Duc Duy Nguyen
Protein Ligand Drug Design Affinity Prediction Atomic Knowledge Binding Affinity Protein Ligand Binding Affinity Prediction

August 19, 2022

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
Yaosen Min, Ye Wei, Peizhuo Wang, Xiaoting Wang, Han Li, Nian Wu, Stefan Bauer, Shuxin Zheng, Yu Shi, Yingheng Wang, Ji Wu, Dan Zhao, Jianyang Zeng
Structure Based Drug Design Virtual Screening Protein Ligand Affinity Prediction Drug Discovery Process Structural Dynamic Graph Based Deep Learning Binding Affinity

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

Binding Affinity

Papers

BAPULM: Binding Affinity Prediction using Language Models

Binding Affinity Prediction: From Conventional to Machine Learning-Based Approaches

Zeoformer: Coarse-Grained Periodic Graph Transformer for OSDA-Zeolite Affinity Prediction

CoPRA: Bridging Cross-domain Pretrained Sequence Models with Complex Structures for Protein-RNA Binding Affinity Prediction

SPIN: SE(3)-Invariant Physics Informed Network for Binding Affinity Prediction

General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design

DualBind: A Dual-Loss Framework for Protein-Ligand Binding Affinity Prediction

VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification

DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening

PIGNet2: A Versatile Deep Learning-based Protein-Ligand Interaction Prediction Model for Binding Affinity Scoring and Virtual Screening

EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction

Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation

Geometric Graph Learning with Extended Atom-Types Features for Protein-Ligand Binding Affinity Prediction

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning

High Performance of Gradient Boosting in Binding Affinity Prediction