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Structure Prediction of G-Protein Coupled Receptors


Cvicek, Vaclav (2015) Structure Prediction of G-Protein Coupled Receptors. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9S46PVG.


G-protein coupled receptors (GPCRs) form a large family of proteins and are very important drug targets. They are membrane proteins, which makes computational prediction of their structure challenging. Homology modeling is further complicated by low sequence similarly of the GPCR superfamily.

In this dissertation, we analyze the conserved inter-helical contacts of recently solved crystal structures, and we develop a unified sequence-structural alignment of the GPCR superfamily. We use this method to align 817 human GPCRs, 399 of which are nonolfactory. This alignment can be used to generate high quality homology models for the 817 GPCRs.

To refine the provided GPCR homology models we developed the Trihelix sampling method. We use a multi-scale approach to simplify the problem by treating the transmembrane helices as rigid bodies. In contrast to Monte Carlo structure prediction methods, the Trihelix method does a complete local sampling using discretized coordinates for the transmembrane helices. We validate the method on existing structures and apply it to predict the structure of the lactate receptor, HCAR1. For this receptor, we also build extracellular loops by taking into account constraints from three disulfide bonds. Docking of lactate and 3,5-dihydroxybenzoic acid shows likely involvement of three Arg residues on different transmembrane helices in binding a single ligand molecule.

Protein structure prediction relies on accurate force fields. We next present an effort to improve the quality of charge assignment for large atomic models. In particular, we introduce the formalism of the polarizable charge equilibration scheme (PQEQ) and we describe its implementation in the molecular simulation package Lammps. PQEQ allows fast on the fly charge assignment even for reactive force fields.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:GPCR; membrane proteins; protein structure prediction; sequence alignment; drug design; GPR81; HCAR1; force field
Degree Grantor:California Institute of Technology
Division:Physics, Mathematics and Astronomy
Major Option:Physics
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Goddard, William A., III
Thesis Committee:
  • Cross, Michael Clifford (chair)
  • Goddard, William A., III
  • Miller, Thomas F.
  • Pine, Jerome
  • Abrol, Ravinder
Defense Date:29 January 2015
Record Number:CaltechTHESIS:02042015-031802985
Persistent URL:
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:8765
Deposited By: Vaclav Cvicek
Deposited On:18 Feb 2015 21:50
Last Modified:04 Oct 2019 00:07

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