A curated list of awesome Molecular Modeling And Drug Discovery
- Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, etc, ... ICLR 2022 paper - Harnessing protein folding neural networks for peptide–protein docking
Tomer Tsaban, Julia K. Varga, Orly Avraham, Ziv Ben-Aharon, etc, ... Nature 2022 paper - Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
Wenhao Gao, Rocío Mercado, Connor W. Coley Arxiv 2021 paper - Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations
Keir Adams, Lagnajit Pattanaik, Connor Coley ICLR paper - Crystal Diffusion Variational Autoencoder for Periodic Material Generation
Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi Jaakkola ICLR 2022 paper - AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor
Feng Ren, Xiao Ding, Min Zheng, Mikhail Korzinkin, Xin Cai ArXiv 2022 paper - An RNA-based theory of natural universal computation
HessameddinAkhlaghpour Journal of Theoretical Biology 2022 paper - GeneDisco: A Benchmark for Experimental Design in Drug Discovery
Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, etc, ... ICLR 2022 paper - ChemicalX: A Deep Learning Library for Drug Pair Scoring
Rozemberczki, Benedek and Hoyt, Charles Tapley and Gogleva, etc, ... KDD 2022 paper - Enhanced sampling methods for molecular dynamics simulations
Jérôme Hénin, Tony Lelièvre, Michael R. Shirts, Omar Valsson, Lucie Delemotte ArXiv 2022 paper - GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang ICLR 2022 paper - Deep sharpening of topological features for de novo protein design
Zander Harteveld, Joshua Southern, Michaël Defferrard, Andreas Loukas, etc, ... ICLR Workshop 2022 paper - Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models
Namrata Anand and Tudor Achim ArXiv 2022 paper - ColabFold: making protein folding accessible to all
Milot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki, Lim Heo, etc, ... Nature paper - Design of protein-binding proteins from the target structure alone
Longxing Cao, Brian Coventry, Inna Goreshnik, Buwei Huang, etc, ... Nature paper - EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
Hannes Stärk, Octavian-Eugen Ganea, Lagnajit Pattanaik, Regina Barzilay, Tommi Jaakkola ICML 2022 paper - RITA: a Study on Scaling Up Generative Protein Sequence Models
Daniel Hesslow, Niccoló Zanichelli, Pascal Notin, Iacopo Poli, Debora Marks ArXiv 2022 paper - QMugs, quantum mechanical properties of drug-like molecules
Clemens Isert, Kenneth Atz, José Jiménez-Luna & Gisbert Schneider Nature 2022 paper - Asymmetric Proton Transfer Catalysis by Stereocomplementary Old Yellow Enzymes for C═C Bond Isomerization Reaction
Marina S. Robescu, Laura Cendron, Arianna Bacchin, Karla Wagner, Tamara Reiter, etc, ... Chemical Reviews 2021 paper
- Geometric Deep Learning on Molecular Representations
Kenneth Atz, Francesca Grisoni, Gisbert Schneider Nature 2021 paper - Highly accurate protein structure prediction with AlphaFold
John Jumper, Richard Evans, Alexander Pritzel, Tim Green, etc, ... Nature 2021 paper - Accurate prediction of protein structures and interactions using a three-track neural network
MINKYUNG BAEK, DIMAIO, ANISHCHENKO, DAUPARAS, etc, ... Science 2021 paper - Learning from Protein Structure with Geometric Vector Perceptrons
Bowen Jing, Stephan Eismann∗, Patricia Suriana, Raphael J.L. T, etc, ... ICLR 2021 paper - An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, etc, ... PMLR 2021 paper - Learning Gradient Fields for Molecular Conformation Generation
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang ICML 2021 paper - Gaussian Process Regression for Materials and Molecules
Volker L. Deringer*, Albert P. Bartók*, Noam Bernstein, etc, ... Chemical Reviews 2021 paper - GemNet: Universal Directional Graph Neural Networks for Molecules
Johannes Gasteiger, Florian Becker, Stephan Günnemann, etc, ... NeurIPS 2021 paper - Do Large Scale Molecular Language Representations Capture Important Structural Information?
Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, etc, ... Arxiv 2021 paper - Using AlphaFold to predict the impact of single mutations on protein stability and function
Marina A. Pak1, Karina A. Markhieva2, Mariia S. Novikova, etc, ... BioRxiv 2021 paper - Disease variant prediction with deep generative models of evolutionary data
Jonathan Frazer, Pascal Notin, Mafalda Dias, Aidan Gomez, etc, ... Nature 2021 paper
- SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
Fabian Fuchs, Daniel Worrall, Volker Fischer, Max Welling NeurIPS 2020 paper
- Structure in neural population recordings: an expected byproduct of simpler phenomena?
Gamaleldin F Elsayed & John P Cunningham Nature 2022 paper
- M2D2: Molecular Modeling And Drug Discovery Link
- OpenFold：Democratizing AI for Biology Link
- LoGaG: Learning on Graphs and Geometry Reading Group Link
- AI Cures Drug Discovery Conference Link
- DeepMind's AlphaFold 2 Explained! AI Breakthrough in Protein Folding! What we know (& what we don't) Video
- AlphaFold and the Grand Challenge to solve protein folding Video
- Michelle Gill - Artificial Intelligence Driven Drug Discovery Video
- AI for Drug Design - Lecture 16 - Deep Learning in the Life Sciences (Spring 2021) Video
- Deep Learning for Drug Discovery Video
- An Introduction to Computational Drug Discovery Video
- Data Science for Computational Drug Discovery using Python (Part 1) Video
- Data Science for Computational Drug Discovery using Python (Part 2 with PyCaret) Video
- DeepMind solves protein folding | AlphaFold 2 Video
- FS-Mol: Bringing Deep Learning to Early-Stage Drug Discovery Blog
- Open Source Initiatives to get you Started with AI in Drug Discovery Video
- Bayesian Modelling of Synergistic Drug Combination Effects in Cancer Using Gaussian Processes Video
- Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric ML Video
- The hype on AlphaFold keeps growing with this new preprint Blog
- What's next for AlphaFold and the AI protein-folding revolution Blog
- Somorphic Labs — Current Job Openings Apply
- ColabFold: making protein folding accessible to all Link
- TheBioProgrammingLab：combines mammalian synthetic biology with de novo protein design Link
- STK: a Python library which allows construction and manipulation of complex molecules, as well as automatic molecular design, and the creation of molecular, and molecular property, databases Link
- exmol: Explainer for black box models that predict molecule properties Link
- ChemicalX: A Deep Learning Library for Drug Pair Scoring Link
- GeneDisco: A Benchmark for Experimental Design in Drug Discovery Link