Affinity Prediction

Affinity prediction, the task of computationally estimating the strength of binding between molecules (e.g., proteins and ligands, proteins and RNA), is crucial for drug discovery and various biological studies. Current research heavily utilizes graph neural networks (GNNs), often incorporating 3D structural information and leveraging pre-training strategies on large datasets, including multimodal data sources like protein sequences and physicochemical properties. These advanced models aim to overcome limitations of simpler methods, particularly in data-scarce scenarios and when dealing with diverse assay types and noisy data, ultimately improving the accuracy and efficiency of drug development and biological research. Active learning techniques are also being explored to optimize the use of experimental data and reduce the cost of annotation.

Papers

November 6, 2024

Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification
Benedict Aaron Tjandra, Federico Barbero, Michael Bronstein
Link Prediction Temporal Graph Behavior Expressivity Style Affinity Prediction Temporal Graph Network Temporal Graph Benchmark Target Source

October 19, 2024

DEL-Ranking: Ranking-Correction Denoising Framework for Elucidating Molecular Affinities in DNA-Encoded Libraries
Hanqun Cao, Chunbin Gu, Mutian He, Ning Ma, Chang-yu Hsieh, Pheng-Ann Heng
Protein Ligand Affinity Prediction Novel Ligand Compound Library Low Complexity Explanation

September 19, 2024

Improving generalisability of 3D binding affinity models in low data regimes
Julia Buhmann, Ward Haddadin, Lukáš Pravda, Alan Bilsland, Hagen Triendl
Stronger Generalizability Local Model Low Data Regime Affinity Prediction Affinity Graph TXL PBC Dataset

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 miRNA Description Complex Structure Binding Affinity

July 15, 2024

On Machine Learning Approaches for Protein-Ligand Binding Affinity Prediction
Nikolai Schapin, Carles Navarro, Albert Bou, Gianni De Fabritiis
Protein Ligand Affinity Prediction Novel Ligand Molecular Embeddings Protein Ligand Binding Affinity Prediction

July 10, 2024

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

June 11, 2024

Active learning for affinity prediction of antibodies
Alexandra Gessner, Sebastian W. Ober, Owen Vickery, Dino Oglić, Talip Uçar
Active Learning Selective Engagement Affinity Prediction Monoclonal Antibody Antibody Antigen

May 3, 2024

Protein binding affinity prediction under multiple substitutions applying eGNNs on Residue and Atomic graphs combined with Language model information: eGRAL
Arturo Fiorellini-Bernardis, Sebastien Boyer, Christoph Brunken, Bakary Diallo, Karim Beguir, Nicolas Lopez-Carranza, Oliver Bent
High Throughput Protein Data Affinity Prediction Back Substitution Affinity Loss Residue Number

February 20, 2024

Equivariant Pretrained Transformer for Unified Geometric Learning on Multi-Domain 3D Molecules
Rui Jiao, Xiangzhe Kong, Ziyang Yu, Wenbing Huang, Yang Liu
Domain Specific Geometric Learning 3D Molecule Affinity Prediction Chemical Domain

December 5, 2023

MATE-Pred: Multimodal Attention-based TCR-Epitope interaction Predictor
Etienne Goffinet, Raghvendra Mall, Ankita Singh, Rahul Kaushik, Filippo Castiglione
Affinity Prediction Cell Receptor

October 16, 2023

Active Learning Framework for Cost-Effective TCR-Epitope Binding Affinity Prediction
Pengfei Zhang, Seojin Bang, Heewook Lee
Active Learning Framework Affinity Prediction

October 5, 2023

Improved prediction of ligand-protein binding affinities by meta-modeling
Ho-Joon Lee, Prashant S. Emani, Mark B. Gerstein
Molecular Docking Affinity Prediction Novel Ligand Molecular Descriptor Better Prediction Entropic Affinity

September 6, 2023

A hybrid quantum-classical fusion neural network to improve protein-ligand binding affinity predictions for drug discovery
L. Domingo, M. Chehimi, S. Banerjee, S. He Yuxun, S. Konakanchi, L. Ogunfowora, S. Roy, S. Selvaras, M. Djukic, C. Johnson
Neural Network Quantum Machine Learning Drug Discovery Quantum Classical Affinity Prediction Quantum Classical Neural Network Candidate Molecule

August 17, 2023

Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions
Lucian Chan, Marcel Verdonk, Carl Poelking
Drug Discovery Neural Process Virtual Screening Unobserved Heterogeneity Affinity Prediction Computer Aided Drug Discovery Bioactivity Prediction Bioactivity Data

July 18, 2023

GraphCL-DTA: a graph contrastive learning with molecular semantics for drug-target binding affinity prediction
Xinxing Yang, Genke Yang, Jian Chu
Contrastive Learning Graph Drawing Affinity Prediction Drug Representation

June 22, 2023

Otter-Knowledge: benchmarks of multimodal knowledge graph representation learning from different sources for drug discovery
Hoang Thanh Lam, Marco Luca Sbodio, Marcos Martínez Galindo, Mykhaylo Zayats, Raúl Fernández-Díaz, Víctor Valls, Gabriele Picco, Cesar Berrospi Ramis, Vanessa López
New Benchmark Drug Discovery Multiple Source Affinity Prediction Multimodal Knowledge Multimodal Knowledge Graph Molecular Embeddings Drug Smile String

June 8, 2023

Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction
Jiaxian Yan, Zhaofeng Ye, Ziyi Yang, Chengqiang Lu, Shengyu Zhang, Qi Liu, Jiezhong Qiu
Affinity Prediction Protein Ligand Binding Affinity Prediction

March 20, 2023

ResDTA: Predicting Drug-Target Binding Affinity Using Residual Skip Connections
Partho Ghosh, Md. Aynal Haque
Protein Ligand Residual Connection Affinity Prediction Drug Target Drug Target Pair

March 6, 2023

3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction
Jiaqi Guan, Wesley Wei Qian, Xingang Peng, Yufeng Su, Jian Peng, Jianzhu Ma
Molecule Generation Model Free Drug Design Affinity Prediction Protein Target Equivariant Diffusion

January 25, 2023

Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation
Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler
Unsupervised Setting Drug Discovery Protein Ligand Affinity Prediction Novel Ligand Protein Ligand Binding Affinity Prediction Dataset Affinity

Affinity Prediction

Papers

Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification

DEL-Ranking: Ranking-Correction Denoising Framework for Elucidating Molecular Affinities in DNA-Encoded Libraries

Improving generalisability of 3D binding affinity models in low data regimes

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

On Machine Learning Approaches for Protein-Ligand Binding Affinity Prediction

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

Active learning for affinity prediction of antibodies

Protein binding affinity prediction under multiple substitutions applying eGNNs on Residue and Atomic graphs combined with Language model information: eGRAL

Equivariant Pretrained Transformer for Unified Geometric Learning on Multi-Domain 3D Molecules

MATE-Pred: Multimodal Attention-based TCR-Epitope interaction Predictor

Active Learning Framework for Cost-Effective TCR-Epitope Binding Affinity Prediction

Improved prediction of ligand-protein binding affinities by meta-modeling

A hybrid quantum-classical fusion neural network to improve protein-ligand binding affinity predictions for drug discovery

Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions

GraphCL-DTA: a graph contrastive learning with molecular semantics for drug-target binding affinity prediction

Otter-Knowledge: benchmarks of multimodal knowledge graph representation learning from different sources for drug discovery

Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction

ResDTA: Predicting Drug-Target Binding Affinity Using Residual Skip Connections

3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction

Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation