Literature DB >> 25012978

Monte Carlo loop refinement and virtual screening of the thyroid-stimulating hormone receptor transmembrane domain.

M Rejwan Ali1, Rauf Latif, Terry F Davies, Mihaly Mezei.   

Abstract

Metropolis Monte Carlo (MMC) loop refinement has been performed on the three extracellular loops (ECLs) of rhodopsin and opsin-based homology models of the thyroid-stimulating hormone receptor transmembrane domain, a class A type G protein-coupled receptor. The Monte Carlo sampling technique, employing torsion angles of amino acid side chains and local moves for the six consecutive backbone torsion angles, has previously reproduced the conformation of several loops with known crystal structures with accuracy consistently less than 2 Å. A grid-based potential map, which includes van der Waals, electrostatics, hydrophobic as well as hydrogen-bond potentials for bulk protein environment and the solvation effect, has been used to significantly reduce the computational cost of energy evaluation. A modified sigmoidal distance-dependent dielectric function has been implemented in conjunction with the desolvation and hydrogen-bonding terms. A long high-temperature simulation with 2 kcal/mol repulsion potential resulted in extensive sampling of the conformational space. The slow annealing leading to the low-energy structures predicted secondary structure by the MMC technique. Molecular docking with the reported agonist reproduced the binding site within 1.5 Å. Virtual screening performed on the three lowest structures showed that the ligand-binding mode in the inter-helical region is dependent on the ECL conformations.

Entities:  

Keywords:  ECL; Metropolis Monte Carlo (MMC); TSHR; class A GPCR; homology modeling; virtual screening

Mesh:

Substances:

Year:  2014        PMID: 25012978      PMCID: PMC4484770          DOI: 10.1080/07391102.2014.932310

Source DB:  PubMed          Journal:  J Biomol Struct Dyn        ISSN: 0739-1102


  51 in total

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Review 7.  Thyrotropin, Hyperthyroidism, and Bone Mass.

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8.  Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations.

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  9 in total

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