Literature DB >> 34890135

Side-chain Packing Using SE(3)-Transformer.

Akhil Jindal1, Sergei Kotelnikov, Dzmitry Padhorny, Dima Kozakov, Yimin Zhu, Rezaul Chowdhury, Sandor Vajda.   

Abstract

Predicting protein side-chains is important for both protein structure prediction and protein design. Modeling approaches to predict side-chains such as SCWRL4 have become one of the most widely used tools of its type due to fast and highly accurate predictions. Motivated by the recent success of AlphaFold2 in CASP14, our group adapted a 3D equivariant neural network architecture to predict protein side-chain conformations, specifically within a protein-protein interface, a problem that has not been fully addressed by AlphaFold2.

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Year:  2022        PMID: 34890135      PMCID: PMC8887833     

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  10 in total

1.  SIDEpro: a novel machine learning approach for the fast and accurate prediction of side-chain conformations.

Authors:  Ken Nagata; Arlo Randall; Pierre Baldi
Journal:  Proteins       Date:  2011-11-09

2.  PISCES: a protein sequence culling server.

Authors:  Guoli Wang; Roland L Dunbrack
Journal:  Bioinformatics       Date:  2003-08-12       Impact factor: 6.937

3.  Knowledge-based prediction of protein structures.

Authors:  F Kaden; I Koch; J Selbig
Journal:  J Theor Biol       Date:  1990-11-07       Impact factor: 2.691

4.  Minimizing and learning energy functions for side-chain prediction.

Authors:  Chen Yanover; Ora Schueler-Furman; Yair Weiss
Journal:  J Comput Biol       Date:  2008-09       Impact factor: 1.479

5.  De novo protein design: fully automated sequence selection.

Authors:  B I Dahiyat; S L Mayo
Journal:  Science       Date:  1997-10-03       Impact factor: 47.728

6.  A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions.

Authors:  Maxim V Shapovalov; Roland L Dunbrack
Journal:  Structure       Date:  2011-06-08       Impact factor: 5.006

7.  Minimal ensembles of side chain conformers for modeling protein-protein interactions.

Authors:  Dmitri Beglov; David R Hall; Ryan Brenke; Maxim V Shapovalov; Roland L Dunbrack; Dima Kozakov; Sandor Vajda
Journal:  Proteins       Date:  2011-11-22

8.  Improved prediction of protein side-chain conformations with SCWRL4.

Authors:  Georgii G Krivov; Maxim V Shapovalov; Roland L Dunbrack
Journal:  Proteins       Date:  2009-12

9.  Updates to the Integrated Protein-Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2.

Authors:  Thom Vreven; Iain H Moal; Anna Vangone; Brian G Pierce; Panagiotis L Kastritis; Mieczyslaw Torchala; Raphael Chaleil; Brian Jiménez-García; Paul A Bates; Juan Fernandez-Recio; Alexandre M J J Bonvin; Zhiping Weng
Journal:  J Mol Biol       Date:  2015-07-29       Impact factor: 5.469

10.  Highly accurate protein structure prediction with AlphaFold.

Authors:  John Jumper; Richard Evans; Alexander Pritzel; Tim Green; Michael Figurnov; Olaf Ronneberger; Kathryn Tunyasuvunakool; Russ Bates; Augustin Žídek; Anna Potapenko; Alex Bridgland; Clemens Meyer; Simon A A Kohl; Andrew J Ballard; Andrew Cowie; Bernardino Romera-Paredes; Stanislav Nikolov; Rishub Jain; Demis Hassabis; Jonas Adler; Trevor Back; Stig Petersen; David Reiman; Ellen Clancy; Michal Zielinski; Martin Steinegger; Michalina Pacholska; Tamas Berghammer; Sebastian Bodenstein; David Silver; Oriol Vinyals; Andrew W Senior; Koray Kavukcuoglu; Pushmeet Kohli
Journal:  Nature       Date:  2021-07-15       Impact factor: 49.962

  10 in total

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