A Global Ramachandran Score Identifies Protein Structures with Unlikely Stereochemistry.
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ABSTRACT:
SUBMITTER: Sobolev OV
PROVIDER: S-EPMC7642142 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundProtein structural data has increased exponentially, such that fast and accurate tools are necessary to access structure similarity search. To improve the search speed, several methods have been designed to reduce three-dimensional protein structures to one-dimensional text strings that are then analyzed by traditional sequence alignment methods; however, the accuracy is usually sacrificed and the speed is still unable to match sequence similarity search tools. Here, we aimed to improve the linear encoding methodology and develop efficient search tools that can rapidly retrieve structural homologs from large protein databases.ResultsWe propose a new linear encoding method, SARST (Structural similarity search Aided by Ramachandran Sequential Transformation). SARST transforms protein structures into text strings through a Ramachandran map organized by nearest-neighbor clustering and uses a regenerative approach to produce substitution matrices. Then, classical sequence similarity search methods can be applied to the structural similarity search. Its accuracy is similar to Combinatorial Extension (CE) and works over 243,000 times faster, searching 34,000 proteins in 0.34 sec with a 3.2-GHz CPU. SARST provides statistically meaningful expectation values to assess the retrieved information. It has been implemented into a web service and a stand-alone Java program that is able to run on many different platforms.ConclusionAs a database search method, SARST can rapidly distinguish high from low similarities and efficiently retrieve homologous structures. It demonstrates that the easily accessible linear encoding methodology has the potential to serve as a foundation for efficient protein structural similarity search tools. These search tools are supposed applicable to automated and high-throughput functional annotations or predictions for the ever increasing number of published protein structures in this post-genomic era.
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Project description:BackgroundDespite the chloride anion is involved in fundamental biological processes, its interactions with proteins are little known. In particular, we lack a systematic survey of its coordination spheres.ResultsThe analysis of a non-redundant set (pairwise sequence identity < 30%) of 1739 high resolution (<2 Å) crystal structures that contain at least one chloride anion shows that the first coordination spheres of the chlorides are essentially constituted by hydrogen bond donors. Amongst the side-chains positively charged, arginine interacts with chlorides much more frequently than lysine. Although the most common coordination number is 4, the coordination stereochemistry is closer to the expected geometry when the coordination number is 5, suggesting that this is the coordination number towards which the chlorides tend when they interact with proteins.ConclusionsThe results of these analyses are useful in interpreting, describing, and validating new protein crystal structures that contain chloride anions.
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