NDLI: Knowledge-based search and multi-objective filters: proposed structural models of GPCR dimerization

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Knowledge-based search and multi-objective filters: proposed structural models of GPCR dimerization

Content Provider	ACM Digital Library
Author	Veltri, Daniel Kabbani, Nadine Hashmi, Irina Shehu, Amarda
Abstract	Many experimental studies point to the ubiquitous role of protein complexation in the cell while lamenting the lack of structural models to permit structure-function studies. This scarcity is due to persisting challenges in protein-protein docking. Methods based on energetic optimization have to handle vast and high-dimensional configuration spaces and inaccurate energy functions only to arrive at the wrong interface. Methods that employ learned models to replace or precede energetic evaluations are limited by the generality of these models. Computational approaches designed to be general often fail to provide realistic models on protein classes of interest in the wet laboratory. One such class are G protein-coupled receptors, which wet-lab studies suggest undergo complexation, possibly affecting drug efficacy. In this paper, we propose a computational protocol to address the unique challenges posed by these receptors. To deal with challenges, such as receptor size and inaccuracy of energy functions, the protocol takes a geometry-driven approach and integrates in the search geometric constraints posed by the environment where the receptors operate. Various filters are designed to handle the computational cost of energetic evaluation, and analysis techniques based on new scoring strategies, including multi-objective analysis, are employed to reduce the sampled ensemble to a few credible structural models. We demonstrate that dimeric models of the Dopamine D2 receptor targeted to treat psychotic disorders reproduce macroscopic knowledge extracted in the wet-laboratory and can be employed to further spur detailed structure-function studies.
Starting Page	279
Ending Page	288
Page Count	10
File Format	PDF
ISBN	9781450328944
DOI	10.1145/2649387.2649391
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-09-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Geometry-driven search Dopamine d2 receptor dimerization Protein-protein docking Pareto-based comparison Multi-objective analysis G protein-coupled receptor assembly
Content Type	Text
Resource Type	Article

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