🔥 awesome-molecular-modeling-and-drug-discovery

A curated list of awesome Molecular Modeling And Drug Discovery

Table of Contents

• Table of Contents
• Resources
  • Research articles
    • Year 2022
    • Year 2021
    • Year 2020
    • Year 2019
    • Year 2018
    • Year 2017
  • Community
  • conference
  • Tutorials
  • Jobs
  • Other software and resources
    • Platforms
    • DevTools

Resources

Research articles

Year 2022

1. Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
   Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, etc, ... ICLR 2022 paper
2. Harnessing protein folding neural networks for peptide–protein docking
   Tomer Tsaban, Julia K. Varga, Orly Avraham, Ziv Ben-Aharon, etc, ... Nature 2022 paper
3. Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
   Wenhao Gao, Rocío Mercado, Connor W. Coley Arxiv 2021 paper
4. Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations
   Keir Adams, Lagnajit Pattanaik, Connor Coley ICLR paper
5. Crystal Diffusion Variational Autoencoder for Periodic Material Generation
   Tian Xie, Xiang Fu, Octavian-Eugen Ganea, Regina Barzilay, Tommi Jaakkola ICLR 2022 paper
6. 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
7. An RNA-based theory of natural universal computation
   HessameddinAkhlaghpour Journal of Theoretical Biology 2022 paper
8. GeneDisco: A Benchmark for Experimental Design in Drug Discovery
   Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, etc, ... ICLR 2022 paper
9. ChemicalX: A Deep Learning Library for Drug Pair Scoring
   Rozemberczki, Benedek and Hoyt, Charles Tapley and Gogleva, etc, ... KDD 2022 paper
10. Enhanced sampling methods for molecular dynamics simulations
    Jérôme Hénin, Tony Lelièvre, Michael R. Shirts, Omar Valsson, Lucie Delemotte ArXiv 2022 paper
11. GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation
    Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang ICLR 2022 paper
12. Deep sharpening of topological features for de novo protein design
    Zander Harteveld, Joshua Southern, Michaël Defferrard, Andreas Loukas, etc, ... ICLR Workshop 2022 paper
13. Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models
    Namrata Anand and Tudor Achim ArXiv 2022 paper
14. ColabFold: making protein folding accessible to all
    Milot Mirdita, Konstantin Schütze, Yoshitaka Moriwaki, Lim Heo, etc, ... Nature paper
15. Design of protein-binding proteins from the target structure alone
    Longxing Cao, Brian Coventry, Inna Goreshnik, Buwei Huang, etc, ... Nature paper
16. EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
    Hannes Stärk, Octavian-Eugen Ganea, Lagnajit Pattanaik, Regina Barzilay, Tommi Jaakkola ICML 2022 paper
17. RITA: a Study on Scaling Up Generative Protein Sequence Models
    Daniel Hesslow, Niccoló Zanichelli, Pascal Notin, Iacopo Poli, Debora Marks ArXiv 2022 paper
18. QMugs, quantum mechanical properties of drug-like molecules
    Clemens Isert, Kenneth Atz, José Jiménez-Luna & Gisbert Schneider Nature 2022 paper
19. 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

Year 2021

1. Geometric Deep Learning on Molecular Representations
   Kenneth Atz, Francesca Grisoni, Gisbert Schneider Nature 2021 paper
2. Highly accurate protein structure prediction with AlphaFold
   John Jumper, Richard Evans, Alexander Pritzel, Tim Green, etc, ... Nature 2021 paper
3. Accurate prediction of protein structures and interactions using a three-track neural network
   MINKYUNG BAEK, DIMAIO, ANISHCHENKO, DAUPARAS, etc, ... Science 2021 paper
4. Learning from Protein Structure with Geometric Vector Perceptrons
   Bowen Jing, Stephan Eismann∗, Patricia Suriana, Raphael J.L. T, etc, ... ICLR 2021 paper
5. 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
6. Learning Gradient Fields for Molecular Conformation Generation
   Chence Shi, Shitong Luo, Minkai Xu, Jian Tang ICML 2021 paper
7. Gaussian Process Regression for Materials and Molecules
   Volker L. Deringer*, Albert P. Bartók*, Noam Bernstein, etc, ... Chemical Reviews 2021 paper
8. GemNet: Universal Directional Graph Neural Networks for Molecules
   Johannes Gasteiger, Florian Becker, Stephan Günnemann, etc, ... NeurIPS 2021 paper
9. Do Large Scale Molecular Language Representations Capture Important Structural Information?
   Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, etc, ... Arxiv 2021 paper
10. 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
11. Disease variant prediction with deep generative models of evolutionary data
    Jonathan Frazer, Pascal Notin, Mafalda Dias, Aidan Gomez, etc, ... Nature 2021 paper

Year 2020

1. SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
   Fabian Fuchs, Daniel Worrall, Volker Fischer, Max Welling NeurIPS 2020 paper

Year 2019

Year 2018

Year 2017

1. Structure in neural population recordings: an expected byproduct of simpler phenomena?
   Gamaleldin F Elsayed & John P Cunningham Nature 2022 paper

Community

1. M2D2: Molecular Modeling And Drug Discovery Link
2. OpenFold：Democratizing AI for Biology Link
3. LoGaG: Learning on Graphs and Geometry Reading Group Link

Conference

1. AI Cures Drug Discovery Conference Link

Tutorials

1. DeepMind's AlphaFold 2 Explained! AI Breakthrough in Protein Folding! What we know (& what we don't) Video
2. AlphaFold and the Grand Challenge to solve protein folding Video
3. Michelle Gill - Artificial Intelligence Driven Drug Discovery Video
4. AI for Drug Design - Lecture 16 - Deep Learning in the Life Sciences (Spring 2021) Video
5. Deep Learning for Drug Discovery Video
6. An Introduction to Computational Drug Discovery Video
7. Data Science for Computational Drug Discovery using Python (Part 1) Video
8. Data Science for Computational Drug Discovery using Python (Part 2 with PyCaret) Video
9. DeepMind solves protein folding | AlphaFold 2 Video
10. FS-Mol: Bringing Deep Learning to Early-Stage Drug Discovery Blog
11. Open Source Initiatives to get you Started with AI in Drug Discovery Video
12. Bayesian Modelling of Synergistic Drug Combination Effects in Cancer Using Gaussian Processes Video
13. Simulate Time-integrated Coarse-grained Molecular Dynamics with Geometric ML Video
14. The hype on AlphaFold keeps growing with this new preprint Blog
15. What's next for AlphaFold and the AI protein-folding revolution Blog

Jobs

1. Somorphic Labs — Current Job Openings Apply

Other software and resources

Platforms

1. ColabFold: making protein folding accessible to all Link
2. TheBioProgrammingLab：combines mammalian synthetic biology with de novo protein design Link

DevTools

1. 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
2. exmol: Explainer for black box models that predict molecule properties Link
3. ChemicalX: A Deep Learning Library for Drug Pair Scoring Link
4. GeneDisco: A Benchmark for Experimental Design in Drug Discovery Link