SiteMine: Large-scale binding site similarity searching in protein structure databases

被引:1
作者
Reim, Thorben [1 ]
Ehrt, Christiane [1 ]
Graef, Joel [1 ]
Guenther, Sebastian [2 ]
Meents, Alke [2 ]
Rarey, Matthias [1 ]
机构
[1] Univ Hamburg, ZBH Ctr Bioinformat, Albert Einstein Ring 8-10, D-22761 Hamburg, Germany
[2] Ctr Free Electron Laser Sci CFEL, Deutsch Elektronen Synchrotron DESY, Hamburg, Germany
关键词
binding site comparison; cathepsin L; drug repurposing; off-target prediction; structure-based drug design; INTERACTION PATTERNS; PREDICTION; SEQUENCE; POCKETS; VISUALIZATION; SARS-COV-2; ALGORITHM; ALIGN; INDEX;
D O I
10.1002/ardp.202300661
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Drug discovery and design challenges, such as drug repurposing, analyzing protein-ligand and protein-protein complexes, ligand promiscuity studies, or function prediction, can be addressed by protein binding site similarity analysis. Although numerous tools exist, they all have individual strengths and drawbacks with regard to run time, provision of structure superpositions, and applicability to diverse application domains. Here, we introduce SiteMine, an all-in-one database-driven, alignment-providing binding site similarity search tool to tackle the most pressing challenges of binding site comparison. The performance of SiteMine is evaluated on the ProSPECCTs benchmark, showing a promising performance on most of the data sets. The method performs convincingly regarding all quality criteria for reliable binding site comparison, offering a novel state-of-the-art approach for structure-based molecular design based on binding site comparisons. In a SiteMine showcase, we discuss the high structural similarity between cathepsin L and calpain 1 binding sites and give an outlook on the impact of this finding on structure-based drug design. SiteMine is available at . SiteMine, an all-in-one database-driven, alignment-providing binding site similarity search tool to tackle the most challenging comparisons, is introduced, showcasing the highly similar cathepsin L and calpain 1 binding sites. Fulfilling all quality criteria for reliable binding site similarity search, SiteMine offers a novel state-of-the-art approach for structure-based molecular design based on binding site comparisons. image
引用
收藏
页数:15
相关论文
共 72 条
  • [1] PLIC: protein-ligand interaction clusters
    Anand, Praveen
    Nagarajan, Deepesh
    Mukherjee, Sumanta
    Chandra, Nagasuma
    [J]. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION, 2014,
  • [2] The Recognition of Identical Ligands by Unrelated Proteins
    Barelier, Sarah
    Sterling, Teague
    O'Meara, Matthew J.
    Shoichet, Brian K.
    [J]. ACS CHEMICAL BIOLOGY, 2015, 10 (12) : 2772 - 2784
  • [3] Batista J., 2014, J CHEMINFORMATICS, V6, DOI DOI 10.1186/1758-2946-6-S1-P57
  • [4] KNIME-CDK: Workflow-driven cheminformatics
    Beisken, Stephan
    Meinl, Thorsten
    Wiswedel, Bernd
    de Figueiredo, Luis F.
    Berthold, Michael
    Steinbeck, Christoph
    [J]. BMC BIOINFORMATICS, 2013, 14
  • [5] The Protein Data Bank
    Berman, HM
    Westbrook, J
    Feng, Z
    Gilliland, G
    Bhat, TN
    Weissig, H
    Shindyalov, IN
    Bourne, PE
    [J]. NUCLEIC ACIDS RESEARCH, 2000, 28 (01) : 235 - 242
  • [6] Site2Vec: a reference frame invariant algorithm for vector embedding of protein-ligand binding sites
    Bhadra, Arnab
    Yeturu, Kalidas
    [J]. MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 2021, 2 (01):
  • [7] From cheminformatics to structure-based design: Web services and desktop applications based on the NAOMI library
    Bietz, Stefan
    Inhester, Therese
    Lauck, Florian
    Sommer, Kai
    von Behren, Mathias M.
    Faehrrolfes, Rainer
    Flachsenberg, Florian
    Meyder, Agnes
    Nittinger, Eva
    Otto, Thomas
    Hilbig, Matthias
    Schomburg, Karen T.
    Volkamer, Andrea
    Rarey, Matthias
    [J]. JOURNAL OF BIOTECHNOLOGY, 2017, 261 : 207 - 214
  • [8] Protoss: a holistic approach to predict tautomers and protonation states in protein-ligand complexes
    Bietz, Stefan
    Urbaczek, Sascha
    Schulz, Benjamin
    Rarey, Matthias
    [J]. JOURNAL OF CHEMINFORMATICS, 2014, 6
  • [9] Can We Rely on Computational Predictions To Correctly Identify Ligand Binding Sites on Novel Protein Drug Targets? Assessment of Binding Site Prediction Methods and a Protocol for Validation of Predicted Binding Sites
    Broomhead, Neal K.
    Soliman, Mahmoud E.
    [J]. CELL BIOCHEMISTRY AND BIOPHYSICS, 2017, 75 (01) : 15 - 23
  • [10] Calenoff Emanuel, 2012, ISRN Neurol, V2012, P851541, DOI 10.5402/2012/851541