“Top-down Design of Protein Nanomaterials With Reinforcement Learning”, Lutz Et Al 2022

“Top-down design of protein nanomaterials with reinforcement learning”⁠, Isaac D. Lutz, Shunzhi Wang, Christoffer Norn, Andrew J. Borst, Yan Ting Zhao, Annie Dosey, Longxing Cao2022-09-25 (model-based RL; similar)

“Genome-wide Prediction of Disease Variants With a Deep Protein Language Model”, Brandes Et Al 2022

“Genome-wide prediction of disease variants with a deep protein language model”⁠, Nadav Brandes, Grant Goldman, Charlotte H. Wang, Chun Jimmie Ye, Vasilis Ntranos2022-08-26 (rare genes; similar)

“Accurate Prediction of Transition Metal Ion Location via Deep Learning”, Dürr Et Al 2022

“Accurate prediction of transition metal ion location via deep learning”⁠, Simon L. Dürr, Andrea Levy, Ursula Rothlisberger2022-08-22 (similar)

“HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model As an Alternative”, Fang Et Al 2022

“HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternative”⁠, Xiaomin Fang, Fan Wang, Lihang Liu, Jingzhou He, Dayong Lin, Yingfei Xiang, Xiaonan Zhang, Hua Wu, Hui Li2022-07-28 (similar)

“OmegaFold: High-resolution De Novo Structure Prediction from Primary Sequence”, Wu Et Al 2022

“OmegaFold: High-resolution de novo structure prediction from primary sequence”⁠, Ruidong Wu, Fan Ding, Rui Wang, Rui Shen, Xiwen Zhang, Shitong Luo, Chenpeng Su, Zuofan Wu, Qi Xie, Bonnie Berger2022-07-22 (similar)

“ESMfold: Language Models of Protein Sequences at the Scale of Evolution Enable Accurate Structure Prediction”, Lin Et Al 2022

“ESMfold: Language models of protein sequences at the scale of evolution enable accurate structure prediction”⁠, Zeming Lin, Halil Akin, Roshan Rao, Brian Hie, Zhongkai Zhu, Wenting Lu, Allan dos Santos Costa, Maryam Fazel-Zarandi2022-07-21 (AI scaling; similar)

“HelixFold: An Efficient Implementation of AlphaFold2 Using PaddlePaddle”, Wang Et Al 2022

“HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddle”⁠, Guoxia Wang, Xiaomin Fang, Zhihua Wu, Yiqun Liu, Yang Xue, Yingfei Xiang, Dianhai Yu, Fan Wang, Yanjun Ma2022-07-12 (similar; bibliography)

“State-of-the-Art Estimation of Protein Model Accuracy Using AlphaFold”, Roney & Ovchinnikov2022

“State-of-the-Art Estimation of Protein Model Accuracy using AlphaFold”⁠, James P. Roney, Sergey Ovchinnikov2022-03-12 (similar)

“FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours”, Cheng Et Al 2022

“FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours”⁠, Shenggan Cheng, Ruidong Wu, Zhongming Yu, Binrui Li, Xiwen Zhang, Jian Peng, Yang You2022-03-02 (AI scaling; similar; bibliography)

“AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery: Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small Molecule Inhibitor”, Ren Et Al 2022

“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, Wei Zhu, Alexey Mantsyzov, Alex Aliper, Vladimir Aladinskiy2022-01-21 (similar)

“The Accuracy of Protein Structures in Solution Determined by AlphaFold and NMR”, Fowler & Williamson2022

“The accuracy of protein structures in solution determined by AlphaFold and NMR”⁠, Nicholas J. Fowler, Mike P. Williamson2022-01-20 (similar)

“Protein Structure Predictions to Atomic Accuracy With AlphaFold”, Jumper & Hassabis2022

“Computed Structures of Core Eukaryotic Protein Complexes”, Humphreys Et Al 2021

“Computed structures of core eukaryotic protein complexes”⁠, Ian R. Humphreys, Jimin Pei, Minkyung Baek, Aditya Krishnakumar, Ivan Anishchenko, Sergey Ovchinnikov2021-11-11 (similar; bibliography)

“Towards a Structurally Resolved Human Protein Interaction Network”, Burke Et Al 2021

“Towards a structurally resolved human protein interaction network”⁠, David F. Burke, Patrick Bryant, Inigo Barrio-Hernandez, Danish Memon, Gabriele Pozzati, Aditi Shenoy2021-11-09 (similar)

“A Structural Biology Community Assessment of AlphaFold 2 Applications”, Akdel Et Al 2021

“A structural biology community assessment of AlphaFold 2 applications”⁠, Mehmet Akdel, Douglas E. V. Pires, Eduard Porta Pardo, Jürgen Jänes, Arthur O. Zalevsky, Bálint Mészáros2021-09-26 (similar)

“Single-sequence Protein Structure Prediction Using Language Models from Deep Learning”, Chowdhury Et Al 2021

“Single-sequence protein structure prediction using language models from deep learning”⁠, Ratul Chowdhury, Nazim Bouatta, Surojit Biswas, Charlotte Rochereau, George M. Church, Peter K. Sorger2021-08-04 (similar; bibliography)

“Can AlphaFold2 Predict Protein-peptide Complex Structures Accurately?”, Ko & Lee2021

“Can AlphaFold2 predict protein-peptide complex structures accurately?”⁠, Junsu Ko, Juyong Lee2021-07-28 (similar)

“Deep Neural Language Modeling Enables Functional Protein Generation across Families”, Madani Et Al 2021

“Deep neural language modeling enables functional protein generation across families”⁠, Ali Madani, Ben Krause, Eric R. Greene, Subu Subramanian, Benjamin P. Mohr, James M. Holton, Jose Luis Olmos2021-07-18 (backlinks; similar)

“Accurate Prediction of Protein Structures and Interactions Using a 3-track Network”, Baek Et Al 2021

“Accurate prediction of protein structures and interactions using a 3-track network”⁠, Minkyung Baek, Frank DiMaio, Ivan Anishchenko, Justas Dauparas, Sergey Ovchinnikov, Gyu Rie Lee, Jue Wang2021-06-15 (backlinks; similar)

“Deep Learning Methods in Protein Structure Prediction”, Torrisi Et Al 2020

“Deep learning methods in protein structure prediction”⁠, Mirko Torrisi, Gianluca Pollastri, Quan Le2020 (similar)

“Predicting Protein Structures With a Multiplayer Online Game”, Cooper Et Al 2010

“Predicting protein structures with a multiplayer online game”⁠, Cooper, Seth Khatib, Firas Treuille, Adrien Barbero, Janos Lee, Jeehyung Beenen, Michael Leaver-Fay, Andrew Baker2010 (backlinks; similar)

Wikipedia

1. AlphaFold

2. Critical Assessment of Techniques for Protein Structure Prediction

3. Protein structure prediction

4. Proteome

5. Transformer (machine learning model)