EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction

7 February 2022

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

50 / 107 papers shown

Title
PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking Yize Jiang Xinze Li Y. Zhang Jin Han Youjun Xu ... Yejin Choi Wu-Jun Li Tianfan Fu Fang Wu Junhong Liu 42 0 0 03 May 2025
Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation Chenbin Zhang Zhiqiang Hu Chuchu Jiang Wen Chen Jie Xu S. Zhang 19 0 0 13 Apr 2025
EquiCPI: SE(3)-Equivariant Geometric Deep Learning for Structure-Aware Prediction of Compound-Protein Interactions Ngoc-Quang Nguyen 28 0 0 07 Apr 2025
Uni-3DAR: Unified 3D Generation and Understanding via Autoregression on Compressed Spatial Tokens Shuqi Lu Haowei Lin Lin Yao Zhifeng Gao Xiaohong Ji W. Elwasif Linfeng Zhang Guolin Ke 48 0 0 20 Mar 2025
PharMolixFM: All-Atom Foundation Models for Molecular Modeling and Generation Yizhen Luo Jiashuo Wang Siqi Fan Zaiqing Nie 35 0 0 12 Mar 2025
SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation Fanglei Xue Meihan Zhang Shuqi Li Xinyu Gao James A. Wohlschlegel Wenbing Huang Yi Yang Weixian Deng 71 0 0 26 Feb 2025
Fast and Accurate Blind Flexible Docking Zizhuo Zhang Lijun Wu Kaiyuan Gao Jiangchao Yao Tao Qin Bo Han 36 0 0 20 Feb 2025
Group Ligands Docking to Protein Pockets Jiaqi Guan Jiahan Li Xiangxin Zhou Xingang Peng Sheng Wang Yunan Luo Jian-wei Peng Jianzhu Ma 33 0 0 28 Jan 2025
FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction Alex Morehead Jianlin Cheng OOD 112 2 0 14 Dec 2024
GNNAS-Dock: Budget Aware Algorithm Selection with Graph Neural Networks for Molecular Docking Yiliang Yuan Mustafa Misir 66 0 0 19 Nov 2024
Dockformer: A transformer-based molecular docking paradigm for large-scale virtual screening Zhangfan Yang Junkai Ji Shan He Jianqiang Li Ruibin Bai Zexuan Zhu Yew-Soon Ong Y. Ong 33 0 0 11 Nov 2024
QuickBind: A Light-Weight And Interpretable Molecular Docking Model Wojtek Treyde Seohyun Chris Kim N. Bouatta Mohammed AlQuraishi 22 0 0 21 Oct 2024
RapidDock: Unlocking Proteome-scale Molecular Docking Rafał Powalski Bazyli Klockiewicz Maciej Jaśkowski Bartosz Topolski Paweł Dąbrowski-Tumański Maciej Wiśniewski Łukasz Kuciński Piotr Miłoś Dariusz Plewczynski 24 0 0 16 Oct 2024
DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking Jiaxian Yan Zaixi Zhang Jintao Zhu Kai Zhang Jianfeng Pei Qi Liu 26 2 0 15 Oct 2024
Assessing interaction recovery of predicted protein-ligand poses David Errington Constantin Schneider Cédric Bouysset Frédéric A. Dreyer AI4CE 23 3 0 30 Sep 2024
Reactzyme: A Benchmark for Enzyme-Reaction Prediction Chenqing Hua Bozitao Zhong Sitao Luan Liang Hong Guy Wolf Doina Precup Shuangjia Zheng 32 5 0 24 Aug 2024
What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much? Rafał Karczewski Samuel Kaski Markus Heinonen Vikas K. Garg 33 0 0 12 Aug 2024
SPIN: SE(3)-Invariant Physics Informed Network for Binding Affinity Prediction Seungyeon Choi Sangmin Seo Sanghyun Park 32 0 0 10 Jul 2024
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents Yilun Xu Gabriele Corso Tommi Jaakkola Arash Vahdat Karsten Kreis 29 12 0 03 Jul 2024
Towards Understanding Sensitive and Decisive Patterns in Explainable AI: A Case Study of Model Interpretation in Geometric Deep Learning Jiajun Zhu Siqi Miao Rex Ying Pan Li 38 1 0 30 Jun 2024
How Interpretable Are Interpretable Graph Neural Networks? Yongqiang Chen Yatao Bian Bo Han James Cheng 44 4 0 12 Jun 2024
DualBind: A Dual-Loss Framework for Protein-Ligand Binding Affinity Prediction Meng Liu Saee Paliwal 21 0 0 11 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 39 7 0 11 Jun 2024
Tx-LLM: A Large Language Model for Therapeutics Juan Manuel Zambrano Chaves Eric Wang Tao Tu E. D. Vaishnav Byron Lee S. S. Mahdavi Christopher Semturs David Fleet Vivek Natarajan Shekoofeh Azizi LM&MA 29 12 0 10 Jun 2024
Sifting through the Noise: A Survey of Diffusion Probabilistic Models and Their Applications to Biomolecules Trevor Norton Debswapna Bhattacharya MedIm DiffM 45 2 0 31 May 2024
Deep Learning for Protein-Ligand Docking: Are We There Yet? Alex Morehead Nabin Giri Jian Liu Jianlin Cheng Jianlin Cheng OOD 32 4 0 23 May 2024
ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering Yiqing Shen Outongyi Lv Houying Zhu Yu Guang Wang 33 4 0 21 Apr 2024
On the Scalability of GNNs for Molecular Graphs Maciej Sypetkowski Frederik Wenkel Farimah Poursafaei Nia Dickson Karush Suri Philip Fradkin Dominique Beaini GNN AI4CE 34 11 0 17 Apr 2024
PROflow: An iterative refinement model for PROTAC-induced structure prediction Bo Qiang Wenxian Shi Yuxuan Song Menghua Wu 40 1 0 10 Apr 2024
Graph Reinforcement Learning for Combinatorial Optimization: A Survey and Unifying Perspective Victor-Alexandru Darvariu Stephen Hailes Mirco Musolesi AI4CE 50 6 0 09 Apr 2024
GeoDirDock: Guiding Docking Along Geodesic Paths Raúl Minán Javier Gallardo Álvaro Ciudad Alexis Molina DiffM 30 0 0 09 Apr 2024
FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation Kaiyuan Gao Qizhi Pei Jinhua Zhu Kun He Lijun Wu Lijun Wu 34 6 0 29 Mar 2024
SGNet: Folding Symmetrical Protein Complex with Deep Learning Zhaoqun Li Jingcheng Yu Qiwei Ye 23 0 0 07 Mar 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications Jiaqi Han Jiacheng Cen Liming Wu Zongzhao Li Xiangzhe Kong ... Zhewei Wei Deli Zhao Yu Rong Wenbing Huang Wenbing Huang AI4CE 34 20 0 01 Mar 2024
Deep Confident Steps to New Pockets: Strategies for Docking Generalization Gabriele Corso Arthur Deng Benjamin Fry Nicholas Polizzi Regina Barzilay Tommi Jaakkola OOD 37 27 0 28 Feb 2024
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics Siqi Miao Zhiyuan Lu Mia Liu Javier Duarte Pan Li 49 4 0 19 Feb 2024
Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains Jiale Zhao Wanru Zhuang Jia Song Yaqi Li Shuqi Lu AI4CE 8 5 0 02 Feb 2024
Quantum-Inspired Machine Learning for Molecular Docking Runqiu Shu Bowen Liu Zhaoping Xiong Xiaopeng Cui Yunting Li Wei Cui Manhong Yung Nan Qiao 24 1 0 22 Jan 2024
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms Bowen Jing Tommi Jaakkola Bonnie Berger 18 2 0 07 Dec 2023
ResMGCN: Residual Message Graph Convolution Network for Fast Biomedical Interactions Discovering Zecheng Yin 10 0 0 13 Nov 2023
Protein-ligand binding representation learning from fine-grained interactions Shikun Feng Minghao Li Yinjun Jia Wei-Ying Ma Yanyan Lan SSL AI4CE 16 8 0 09 Nov 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 ... Fan Wang Jingzhou He Liang Zheng Yonghui Li Xiaomin Fang AI4CE 22 8 0 21 Oct 2023
ETDock: A Novel Equivariant Transformer for Protein-Ligand Docking Yi Yi Xu Wan Yatao Bian Ou-Yang Le Peilin Zhao 13 3 0 12 Oct 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 34 19 0 10 Oct 2023
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design Hannes Stärk Bowen Jing Regina Barzilay Tommi Jaakkola 31 25 0 09 Oct 2023
PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling Seonghwan Seo Woo Youn Kim 18 4 0 01 Oct 2023
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation Tuan Le Julian Cremer Frank Noé Djork-Arné Clevert Kristof T. Schütt DiffM 27 25 0 29 Sep 2023
AtomSurf : Surface Representation for Learning on Protein Structures Vincent Mallet Souhaib Attaiki M. Ovsjanikov 34 3 0 28 Sep 2023
Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks Andreas Roth Thomas Liebig 41 11 0 31 Aug 2023
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks Haoran Liu Bokun Wang Jianling Wang Xiangjue Dong Tianbao Yang James Caverlee AAML 26 3 0 29 Aug 2023