Improving de novo Protein Binder Design with Deep Learning
Improving de novo Protein Binder Design with Deep Learning
Abstract We explore the improvement of energy-based protein binder design using deep learning. We find that using AlphaFold2 or RoseTTAFold to assess the probability that a designed sequence adopts the designed monomer structure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. We find further that sequence design using ProteinMPNN rather than Rosetta considerably increases computational efficiency.
Coventry Brian、Huang Buwei、De Munck Steven、Savvides Savvas N.、Bennett Nathaniel、Stewart Lance、Baker David、Dauparas Justas、Allen Aza、Goreshnik Inna、Baek Minkyung、Peng Ying Po、DiMaio Frank、Vafeados Dionne
Department of Biochemistry, University of Washington||Institute for Protein Design, University of Washington||Howard Hughes Medical Institute, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of Washington||Department of Bioengineering, University of WashingtonVIB-UGent Center for Inflammation Research||Unit for Structural Biology, Department of Biochemistry and Microbiology, Ghent UniversityVIB-UGent Center for Inflammation Research||Unit for Structural Biology, Department of Biochemistry and Microbiology, Ghent UniversityDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of Washington||Molecular Engineering Graduate Program, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of Washington||Howard Hughes Medical Institute, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of WashingtonDepartment of Biochemistry, University of Washington||Institute for Protein Design, University of Washington
生物科学研究方法、生物科学研究技术生物工程学计算技术、计算机技术
Coventry Brian,Huang Buwei,De Munck Steven,Savvides Savvas N.,Bennett Nathaniel,Stewart Lance,Baker David,Dauparas Justas,Allen Aza,Goreshnik Inna,Baek Minkyung,Peng Ying Po,DiMaio Frank,Vafeados Dionne.Improving de novo Protein Binder Design with Deep Learning[EB/OL].(2025-03-28)[2025-08-02].https://www.biorxiv.org/content/10.1101/2022.06.15.495993.点此复制
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