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Advancing Membrane-Associated Protein Docking with Improved Sampling and Scoring in Rosetta.

Rituparna Samanta1, Ameya Harmalkar1, Priyamvada Prathima1

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Summary

Rosetta-MPDock accurately predicts membrane protein complex structures, even for flexible proteins. Integrating AlphaFold2-multimer further improves success rates for modeling these crucial biological components.

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Area of Science:

  • Structural biology
  • Computational biology
  • Biophysics

Background:

  • Membrane proteins (MPs) are vital for cellular functions, including signal transduction and immune response, and are key pharmaceutical targets.
  • Experimental determination of MP structures is challenging, limiting understanding of their complexes.
  • Computational docking offers a viable approach for modeling MP complex structures.

Purpose of the Study:

  • To introduce Rosetta-MPDock, a novel computational protocol for flexible transmembrane (TM) protein docking.
  • To assess Rosetta-MPDock's performance in predicting TM protein complex structures, considering binding-induced conformational changes.
  • To evaluate the combined approach of AlphaFold2-multimer and Rosetta-MPDock for enhanced structure prediction.

Main Methods:

  • Developed Rosetta-MPDock, a flexible TM protein docking protocol operating in an implicit membrane environment.
  • Sampled conformational ensembles of flexible monomers for docking.
  • Benchmarked Rosetta-MPDock on 29 TM-protein complexes with varying flexibility (rigid, moderately flexible, flexible).
  • Integrated AlphaFold2-multimer with Rosetta-MPDock for structure determination, docking, and refinement.

Main Results:

  • Rosetta-MPDock successfully predicted correct interfaces for 67% of moderately flexible and 60% of highly flexible TM protein targets in a local docking scenario.
  • These success rates represent a significant improvement over existing membrane protein docking methods.
  • Combining AlphaFold2-multimer with Rosetta-MPDock improved overall success rates from 64% to 73% on benchmark targets.

Conclusions:

  • Rosetta-MPDock enhances the prediction of membrane protein complex structures, accounting for conformational flexibility.
  • The integration with AlphaFold2-multimer further boosts prediction accuracy.
  • This computational approach facilitates the study of key biological questions and functional mechanisms of membrane proteins.