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Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening?

ABSTRACT: Recent highly expected structural characterizations of agonist-bound and antagonist-bound beta-2 adrenoreceptor (?2AR) by X-ray crystallography have been widely regarded as critical advances to enable more effective structure-based discovery of GPCRs ligands. It appears that this very important development may have undermined many previous efforts to develop 3D theoretical models of GPCRs. To address this question directly, we have compared several historical ?2AR models versus the inactive state and nanobody-stabilized active state of ?2AR crystal structures in terms of their structural similarity and effectiveness of use in virtual screening for ?2AR specific agonists and antagonists. Theoretical models, incluing both homology and de novo types, were collected from five different groups who have published extensively in the field of GPCRs modeling. All models were built before X-ray structures became available. In general, ?2AR theoretical models differ significantly from the crystal structure in terms of TMH definition and the global packing. Nevertheless, surprisingly, several models afforded hit rates resulting from virtual screening of large chemical library enriched by known ?2AR ligands that exceeded those using X-ray structures. The hit rates were particularly higher for agonists. Furthemore, the screening performance of models is associated with local structural quality, such as the RMSDs for binding pocket residues and the ability to capture accurately, most if not all critical protein/ligand interactions. These results suggest that carefully built models of GPCRs could capture critical chemical and structural features of the binding pocket, and thus may be even more useful for practical structure-based drug discovery than X-ray structures.

SUBMITTER: Tang H

PROVIDER: S-EPMC4133977 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

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Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening?

Tang Hao H Wang Xiang Simon XS Hsieh Jui-Hua JH Tropsha Alexander A

Proteins 20120313 6

Recent highly expected structural characterizations of agonist-bound and antagonist-bound beta-2 adrenoreceptor (β2AR) by X-ray crystallography have been widely regarded as critical advances to enable more effective structure-based discovery of GPCRs ligands. It appears that this very important development may have undermined many previous efforts to develop 3D theoretical models of GPCRs. To address this question directly, we have compared several historical β2AR models versus the inactive stat ...[more]

PMID: 22275072

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Project description:We have developed FINDSITE(X), an extension of FINDSITE, a protein threading based algorithm for the inference of protein binding sites, biochemical function and virtual ligand screening, that removes the limitation that holo protein structures (those containing bound ligands) of a sufficiently large set of distant evolutionarily related proteins to the target be solved; rather, predicted protein structures and experimental ligand binding information are employed. To provide the predicted protein structures, a fast and accurate version of our recently developed TASSER(VMT), TASSER(VMT)-lite, for template-based protein structural modeling applicable up to 1000 residues is developed and tested, with comparable performance to the top CASP9 servers. Then, a hybrid approach that combines structure alignments with an evolutionary similarity score for identifying functional relationships between target and proteins with binding data has been developed. By way of illustration, FINDSITE(X) is applied to 998 identified human G-protein coupled receptors (GPCRs). First, TASSER(VMT)-lite provides updates of all human GPCR structures previously modeled in our lab. We then use these structures and the new function similarity detection algorithm to screen all human GPCRs against the ZINC8 nonredundant (TC < 0.7) ligand set combined with ligands from the GLIDA database (a total of 88,949 compounds). Testing (excluding GPCRs whose sequence identity > 30% to the target from the binding data library) on a 168 human GPCR set with known binding data, the average enrichment factor in the top 1% of the compound library (EF(0.01)) is 22.7, whereas EF(0.01) by FINDSITE is 7.1. For virtual screening when just the target and its native ligands are excluded, the average EF(0.01) reaches 41.4. We also analyze off-target interactions for the 168 protein test set. All predicted structures, virtual screening data and off-target interactions for the 998 human GPCRs are available at http://cssb.biology.gatech.edu/skolnick/webservice/gpcr/index.html .

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Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening?

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Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening?

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