Discrimination of Native-like States of Membrane Proteins with Implicit Membrane-based Scoring Functions

Bercem Dutagaci, Kitiyaporn Wittayanarakul, Takaharu Mori, Michael Feig

Research output: Contribution to journalArticle

Abstract

A scoring protocol based on implicit membrane-based scoring functions and a new protocol for optimizing the positioning of proteins inside the membrane was evaluated for its capacity to discriminate native-like states from misfolded decoys. A decoy set previously established by the Baker lab (Proteins: Struct., Funct., Genet. 2006, 62, 1010-1025) was used along with a second set that was generated to cover higher resolution models. The Implicit Membrane Model 1 (IMM1), IMM1 model with CHARMM 36 parameters (IMM1-p36), generalized Born with simple switching (GBSW), and heterogeneous dielectric generalized Born versions 2 (HDGBv2) and 3 (HDGBv3) were tested along with the new HDGB van der Waals (HDGBvdW) model that adds implicit van der Waals contributions to the solvation free energy. For comparison, scores were also calculated with the distance-scaled finite ideal-gas reference (DFIRE) scoring function. Z-scores for native state discrimination, energy vs root-mean-square deviation (RMSD) correlations, and the ability to select the most native-like structures as top-scoring decoys were evaluated to assess the performance of the scoring functions. Ranking of the decoys in the Baker set that were relatively far from the native state was challenging and dominated largely by packing interactions that were captured best by DFIRE with less benefit of the implicit membrane-based models. Accounting for the membrane environment was much more important in the second decoy set where especially the HDGB-based scoring functions performed very well in ranking decoys and providing significant correlations between scores and RMSD, which shows promise for improving membrane protein structure prediction and refinement applications. The new membrane structure scoring protocol was implemented in the MEMScore web server (http://feiglab.org/memscore).

LanguageEnglish (US)
Pages3049-3059
Number of pages11
JournalJournal of Chemical Theory and Computation
Volume13
Issue number6
DOIs
StatePublished - Jun 13 2017

Profile

scoring
decoys
discrimination
Membrane Proteins
membranes
proteins
Proteins
Membranes
ranking
ideal gas
Gases
Membrane structures
deviation
Solvation
membrane structures
Electron energy levels
Free energy
positioning
Servers
solvation

ASJC Scopus subject areas

  • Computer Science Applications
  • Physical and Theoretical Chemistry

Cite this

Discrimination of Native-like States of Membrane Proteins with Implicit Membrane-based Scoring Functions. / Dutagaci, Bercem; Wittayanarakul, Kitiyaporn; Mori, Takaharu; Feig, Michael.

In: Journal of Chemical Theory and Computation, Vol. 13, No. 6, 13.06.2017, p. 3049-3059.

Research output: Contribution to journalArticle

Dutagaci, Bercem ; Wittayanarakul, Kitiyaporn ; Mori, Takaharu ; Feig, Michael. / Discrimination of Native-like States of Membrane Proteins with Implicit Membrane-based Scoring Functions. In: Journal of Chemical Theory and Computation. 2017 ; Vol. 13, No. 6. pp. 3049-3059
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