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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
Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks Andreas Roth Thomas Liebig 114 14 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 107 3 0 29 Aug 2023
Leveraging Side Information for Ligand Conformation Generation using Diffusion-Based Approaches Nhat-Khang Ngô Truong-Son Hy Yuan Yao DiffM 64 0 0 02 Aug 2023
Fractional Denoising for 3D Molecular Pre-training Shi Feng Yuyan Ni Yanyan Lan Zhiming Ma Wei-Ying Ma DiffM AI4CE 109 29 0 20 Jul 2023
CoarsenConf: Equivariant Coarsening with Aggregated Attention for Molecular Conformer Generation Danny Reidenbach Aditi S. Krishnapriyan 81 8 0 26 Jun 2023
MoleCLUEs: Molecular Conformers Maximally In-Distribution for Predictive Models Michael R. Maser Natasa Tagasovska Jae Hyeon Lee Andrew Watkins 120 0 0 20 Jun 2023
A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design Zaixin Zhang Jiaxian Yan Qi Liu Enhong Chen Marinka Zitnik 140 1 0 20 Jun 2023
Reinforcement Learning-Driven Linker Design via Fast Attention-based Point Cloud Alignment Rebecca M. Neeser Mehmet Akdel Daniel Kovtun Luca Naef 41 6 0 13 Jun 2023
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning Shuxin Zheng Jiyan He Chang-Shu Liu Yu Shi Ziheng Lu ... Peiran Jin Chi Chen Frank Noé Haiguang Liu Tie-Yan Liu AI4CE 92 41 0 08 Jun 2023
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian Haiyang Yu Zhao Xu X. Qian Xiaoning Qian Shuiwang Ji 114 30 0 08 Jun 2023
Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity Prediction Jiaxian Yan Zhaofeng Ye Ziyi Yang Chengqiang Lu Shengyu Zhang Qi Liu J. Qiu 111 14 0 08 Jun 2023
Infusing Lattice Symmetry Priors in Attention Mechanisms for Sample-Efficient Abstract Geometric Reasoning Mattia Atzeni Mrinmaya Sachan Andreas Loukas LRM 66 3 0 05 Jun 2023
AbODE: Ab Initio Antibody Design using Conjoined ODEs Yogesh Verma Markus Heinonen Vikas Garg 112 20 0 31 May 2023
Group Invariant Global Pooling Kamil Bujel Yonatan Gideoni Chaitanya K. Joshi Pietro Lio 69 0 0 30 May 2023
Geometric Epitope and Paratope Prediction Marco Pegoraro Clémentine Dominé Emanuele Rodolà Petar Velickovic Andreea Deac 74 3 0 28 May 2023
Knowledge-Design: Pushing the Limit of Protein Design via Knowledge Refinement Zhangyang Gao Cheng Tan Stan Z. Li 98 16 0 20 May 2023
CREMP: Conformer-Rotamer Ensembles of Macrocyclic Peptides for Machine Learning Colin A. Grambow Hayley Weir Christian N Cunningham Tommaso Biancalani Kangway V Chuang 84 8 0 14 May 2023
Semi-Equivariant Conditional Normalizing Flows Eyal Rozenberg Daniel Freedman 69 0 0 13 Apr 2023
Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks Bingxin Zhou Outongyi Lv Kai Yi Xinye Xiong P. Tan Liang Hong Yu Wang 88 4 0 13 Apr 2023
A Comprehensive Survey on Deep Graph Representation Learning Wei Ju Zheng Fang Yiyang Gu Zequn Liu Qingqing Long ... Jingyang Yuan Yusheng Zhao Yifan Wang Xiao Luo Ming Zhang GNN AI4TS 195 163 0 11 Apr 2023
Graph Representation Learning for Interactive Biomolecule Systems Xinye Xiong Bingxin Zhou Yu Guang Wang AI4CE GNN 210 0 0 05 Apr 2023
DSDP: A Blind Docking Strategy Accelerated by GPUs Yupeng Huang Hong Zhang Siyuan Jiang Dajiong Yue Xiaohan Lin Jun Zhang Y. Gao 103 22 0 16 Mar 2023
3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction Jiaqi Guan Wesley Wei Qian Xingang Peng Yufeng Su Jian-wei Peng Jianzhu Ma DiffM 104 179 0 06 Mar 2023
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research Arpandeep Khatua Vikram Sharma Mailthody Bhagyashree Taleka Tengfei Ma Xiang Song Wen-mei W. Hwu AI4CE 111 39 0 27 Feb 2023
Boosting Convolutional Neural Networks' Protein Binding Site Prediction Capacity Using SE(3)-invariant transformers, Transfer Learning and Homology-based Augmentation Dae Lee Jeunghyun Byun Bonggun Shin OOD ViT 61 0 0 20 Feb 2023
Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking? Yuejiang Yu Shuqi Lu Zhifeng Gao Hang Zheng Guolin Ke 58 30 0 14 Feb 2023
Geometry-Complete Diffusion for 3D Molecule Generation and Optimization Alex Morehead Jianlin Cheng DiffM 102 30 0 08 Feb 2023
Towards fully covariant machine learning Soledad Villar D. Hogg Weichi Yao George A. Kevrekidis Bernhard Schölkopf AI4CE 116 11 0 31 Jan 2023
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation Wengong Jin Siranush Sarkizova Xun Chen N. Hacohen Caroline Uhler 60 23 0 25 Jan 2023
Everything is Connected: Graph Neural Networks Petar Velickovic GNN AI4CE 120 190 0 19 Jan 2023
Structure-based drug discovery with deep learning Rıza Özçelik D. V. Tilborg José Jiménez-Luna F. Grisoni AI4CE 74 38 0 26 Dec 2022
Integration of Pre-trained Protein Language Models into Geometric Deep Learning Networks Fang Wu Yujun Tao Dragomir R. Radev Jinbo Xu Stan Z. Li AI4CE 105 34 0 07 Dec 2022
DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries Kirill Shmilovich Benson Chen Theofanis Karaletos Mohammad M. Sultan 54 12 0 30 Nov 2022
Learnable Spectral Wavelets on Dynamic Graphs to Capture Global Interactions Anson Bastos Abhishek Nadgeri Kuldeep Singh Toyotaro Suzumura Manish Singh 82 8 0 22 Nov 2022
Semi-Equivariant Continuous Normalizing Flows for Target-Aware Molecule Generation Eyal Rozenberg Daniel Freedman 81 0 0 09 Nov 2022
Recent Developments in Structure-Based Virtual Screening Approaches C. Gorgulla 29 0 0 06 Nov 2022
Interpretable Geometric Deep Learning via Learnable Randomness Injection Siqi Miao Yunan Luo Miaoyuan Liu Pan Li 64 25 0 30 Oct 2022
Changes from Classical Statistics to Modern Statistics and Data Science Kai Zhang Shan-Yu Liu M. Xiong 92 0 0 30 Oct 2022
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network Yi Yi Xu Wan Kangfei Zhao Ou-Yang Le Pei-Ying Zhao 70 1 0 27 Oct 2022
Structure-based Drug Design with Equivariant Diffusion Models Arne Schneuing Yuanqi Du Charles Harris Arian R. Jamasb Ilia Igashov ... Pietro Lio Carla P. Gomes Max Welling Michael M. Bronstein B. Correia DiffM 158 229 0 24 Oct 2022
Structure-based drug design with geometric deep learning Clemens Isert Kenneth Atz G. Schneider 105 111 0 19 Oct 2022
An efficient graph generative model for navigating ultra-large combinatorial synthesis libraries Aryan Pedawi P. Gniewek Chao-Ling Chang Brandon M. Anderson H. V. D. Bedem 70 5 0 19 Oct 2022
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking Gabriele Corso Hannes Stärk Bowen Jing Regina Barzilay Tommi Jaakkola DiffM 273 451 0 04 Oct 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 DiffM 106 98 0 30 Sep 2022
Machine learning and invariant theory Ben Blum-Smith Soledad Villar AI4CE 112 18 0 29 Sep 2022
PiFold: Toward effective and efficient protein inverse folding Zhangyang Gao Cheng Tan Pablo Chacón Stan Z. Li AI4CE 173 116 0 22 Sep 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 164 29 0 12 Sep 2022
Learning Hierarchical Protein Representations via Complete 3D Graph Networks Limei Wang Haoran Liu Yi Liu Jerry Kurtin Shuiwang Ji GNN 75 60 0 26 Jul 2022
Evaluating Self-Supervised Learning for Molecular Graph Embeddings Hanchen Wang Jean Kaddour Shengchao Liu Jian Tang Joan Lasenby Qi Liu 121 23 0 16 Jun 2022
Torsional Diffusion for Molecular Conformer Generation Bowen Jing Gabriele Corso Jeffrey Chang Regina Barzilay Tommi Jaakkola DiffM BDL 117 277 0 01 Jun 2022