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

November 1, 2023

Delta Score: Improving the Binding Assessment of Structure-Based Drug Design Methods
Minsi Ren, Bowen Gao, Bo Qiang, Yanyan Lan
Global Evaluation Drug Discovery Structure Based Drug Design Protein Ligand

October 21, 2023

Pre-Training on Large-Scale Generated Docking Conformations with HelixDock to Unlock the Potential of Protein-ligand Structure Prediction Models
Lihang Liu, Shanzhuo Zhang, Donglong He, Xianbin Ye, Jingbo Zhou, Xiaonan Zhang, Yaoyao Jiang, Weiming Diao, Hang Yin, Hua Chai, Fan Wang, Jingzhou He, Liang Zheng, Yonghui Li, Xiaomin Fang
Full Potential Molecular Docking Protein Ligand Unlocking Insight Pre Trained Protein Model

October 11, 2023

ProFSA: Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment
Bowen Gao, Yinjun Jia, Yuanle Mo, Yuyan Ni, Weiying Ma, Zhiming Ma, Yanyan Lan
Molecular Representation Self Supervised Pretraining Protein Ligand Property Prediction Protein Sequence Encoder Sequence Alignment

October 10, 2023

FABind: Fast and Accurate Protein-Ligand Binding
Qizhi Pei, Kaiyuan Gao, Lijun Wu, Jinhua Zhu, Yingce Xia, Shufang Xie, Tao Qin, Kun He, Tie-Yan Liu, Rui Yan
Protein Ligand Novel Ligand Docking Process Protein Ligand Binding

October 6, 2023

PGraphDTA: Improving Drug Target Interaction Prediction using Protein Language Models and Contact Maps
Rakesh Bal, Yijia Xiao, Wei Wang
Drug Discovery Protein Language Model Protein Ligand Drug Target Interaction Drug Target Drug Target Interaction Prediction

October 5, 2023

TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design
Tony Shen, Seonghwan Seo, Grayson Lee, Mohit Pandey, Jason R Smith, Artem Cherkasov, Woo Youn Kim, Martin Ester
Structure Based Drug Design Virtual Screening Protein Ligand Molecular Generative

September 22, 2023

HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery
Alvaro Prat, Hisham Abdel Aty, Gintautas Kamuntavičius, Tanya Paquet, Povilas Norvaišas, Piero Gasparotto, Roy Tal
Deep Learning Approach Drug Discovery Structure Based Drug Design High Throughput Protein Ligand

July 13, 2023

Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond
Kenichiro Takaba, Iván Pulido, Pavan Kumar Behara, Chapin E. Cavender, Anika J. Friedman, Michael M. Henry, Hugo MacDermott Opeskin, Christopher R. Iacovella, Arnav M. Nagle, Alexander Matthew Payne, Michael R. Shirts, David L. Mobley, John D. Chodera, Yuanqing Wang
Simulation Study Protein Ligand Force Field Quantum Chemistry Biomolecular Simulation Molecular Mechanic

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

March 27, 2023

Learning Harmonic Molecular Representations on Riemannian Manifold
Yiqun Wang, Yuning Shen, Shi Chen, Lihao Wang, Fei Ye, Hao Zhou
Molecular Representation Protein Ligand Property Prediction 3D Molecule Riemannian Geometry Approach

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

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

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

January 3, 2023

Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform
Jonathan P. Mailoa, Zhaofeng Ye, Jiezhong Qiu, Chang-Yu Hsieh, Shengyu Zhang
Molecular Conformation Protein Ligand Computer Aided Drug Discovery Protein Pocket

December 20, 2022

Dynamic Molecular Graph-based Implementation for Biophysical Properties Prediction
Carter Knutson, Gihan Panapitiya, Rohith Varikoti, Neeraj Kumar
Molecular Graph Molecular Representation Molecular Dynamic Protein Ligand Affinity Prediction Interaction Prediction

November 12, 2022

Innovative Drug-like Molecule Generation from Flow-based Generative Model
Haotian Zhang, Linxiaoyi Wan
Molecular Docking Protein Ligand Drug Like Novel Molecule Flow Based Generative

October 27, 2022

Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network
Yiqiang Yi, Xu Wan, Kangfei Zhao, Le Ou-Yang, Peilin Zhao
Protein Ligand Equivariant Graph Neural Network Affinity Prediction 3D Ligand Protein Ligand Binding

October 12, 2022

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking
Yangtian Zhang, Huiyu Cai, Chence Shi, Bozitao Zhong, Jian Tang
Equivariant Network Molecular Docking Protein Ligand Novel Ligand Protein Structure Prediction

September 30, 2022

State-specific protein-ligand complex structure prediction with a multi-scale deep generative model
Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller, Anima Anandkumar
Molecular Docking Protein Ligand Protein Structure 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 Protein Ligand Virtual Screening Affinity Prediction Drug Discovery Process Structural Dynamic Graph Based Deep Learning Binding Affinity

Protein Ligand

Papers

Delta Score: Improving the Binding Assessment of Structure-Based Drug Design Methods

Pre-Training on Large-Scale Generated Docking Conformations with HelixDock to Unlock the Potential of Protein-ligand Structure Prediction Models

ProFSA: Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment

FABind: Fast and Accurate Protein-Ligand Binding

PGraphDTA: Improving Drug Target Interaction Prediction using Protein Language Models and Contact Maps

TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design

HydraScreen: A Generalizable Structure-Based Deep Learning Approach to Drug Discovery

Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond

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

Learning Harmonic Molecular Representations on Riemannian Manifold

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

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

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

Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform

Dynamic Molecular Graph-based Implementation for Biophysical Properties Prediction

Innovative Drug-like Molecule Generation from Flow-based Generative Model

Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking

State-specific protein-ligand complex structure prediction with a multi-scale deep generative model

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