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Calculation of accurate interatomic contact surface areas for the quantitative analysis of non-bonded molecular interactions.
Bioinformatics 2019 January 30
Summary: Intra- and intermolecular contact surfaces are routinely calculated for a large array of applications in bioinformatics but are typically approximated from differential solvent accessible surface area calculations and not calculated directly. These approximations do not properly take the effects of neighboring atoms into account and tend to deviate considerably from the true contact surface. We implemented an extension of the original Shrake-Rupley algorithm to accurately estimate interatomic contact surface areas of molecular structures and complexes. Our extended algorithm is able to calculate the contact area of an atom to all nearby atoms by directly calculating overlapping surface patches, taking into account the possible shielding effects of neighboring atoms. Here, we present a versatile software tool and web server for the calculation of contact surface areas, as well as buried surface areas and solvent accessible surface areas (SASA) for different types of biomolecules, such as proteins, nucleic acids and small organic molecules. Detailed results are provided in tab-separated values format for analysis and Protein Databank files for visualization. Direct contact surface area calculation resulted in improved accuracy in a benchmark with a non-redundant set of 245 protein-DNA complexes. SASA-based approximations underestimated protein-DNA contact surfaces on average by 40%. This software tool may be useful for surface-based intra- and intermolecular interaction analyses and scoring function development.
Availability and implementation: A web server, stand-alone binaries for Linux, MacOS and Windows, and C++ source code are freely available from https://schuellerlab.org/dr_sasa/.
Supplementary information: Supplementary data are available at Bioinformatics online.
Availability and implementation: A web server, stand-alone binaries for Linux, MacOS and Windows, and C++ source code are freely available from https://schuellerlab.org/dr_sasa/.
Supplementary information: Supplementary data are available at Bioinformatics online.
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