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        <datestamp>2023-05-30</datestamp>
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          <dc:identifier>https://doi.org/10.17044/SCILIFELAB.16438206</dc:identifier>
          <dc:title xml:lang="en">Docking Results</dc:title>
          <dc:creator>Gabriele Pozzati</dc:creator>
          <dc:creator>Petras Kundrotas</dc:creator>
          <dc:creator>Arne Elofsson</dc:creator>
          <dc:subject xml:lang="en">Medical and Health Sciences</dc:subject>
          <dc:subject xml:lang="sv">Medicin och hälsovetenskap</dc:subject>
          <dc:subject xml:lang="en">Bioinformatics (Computational Biology)</dc:subject>
          <dc:subject xml:lang="sv">Bioinformatik (beräkningsbiologi)</dc:subject>
          <dc:description xml:lang="en">Results for the study "Improved protein docking by predicted interface residues". Archive contains GRAMM roto-translations of Ligands around the original position of the Receptor. Several set of docking models have been produced considering different set of protein interface constraintsto score GRAMM roto-translations. Also, AACE18 scoring function results are included. For every docking model, DockQ score has been calculated comparing with both bound and unbound native structures. Find detailed methods at https://www.biorxiv.org/content/10.1101/2021.08.25.457642v1</dc:description>
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          <dc:publisher xml:lang="en">Stockholm University</dc:publisher>
          <dc:publisher xml:lang="sv">Stockholms universitet</dc:publisher>
          <dc:date>2021-09-14T00:00:00Z</dc:date>
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