kinCSM: Using graph-based signatures to predict small molecule CDK2 inhibitors.
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| Title: | kinCSM: Using graph-based signatures to predict small molecule CDK2 inhibitors. |
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| Authors: | Zhou Y; School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia.; Structural Biology and Bioinformatics, Department of Biochemistry, University of Melbourne, Melbourne, Victoria, Australia.; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia., Al-Jarf R; Structural Biology and Bioinformatics, Department of Biochemistry, University of Melbourne, Melbourne, Victoria, Australia.; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia., Alavi A; Structural Biology and Bioinformatics, Department of Biochemistry, University of Melbourne, Melbourne, Victoria, Australia.; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia., Nguyen TB; School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia.; Structural Biology and Bioinformatics, Department of Biochemistry, University of Melbourne, Melbourne, Victoria, Australia.; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia., Rodrigues CHM; School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia.; Structural Biology and Bioinformatics, Department of Biochemistry, University of Melbourne, Melbourne, Victoria, Australia.; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia., Pires DEV; School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia.; Structural Biology and Bioinformatics, Department of Biochemistry, University of Melbourne, Melbourne, Victoria, Australia.; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.; School of Computing and Information Systems, University of Melbourne, Melbourne, Victoria, Australia., Ascher DB; School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia.; Structural Biology and Bioinformatics, Department of Biochemistry, University of Melbourne, Melbourne, Victoria, Australia.; Systems and Computational Biology, Bio21 Institute, University of Melbourne, Melbourne, Victoria, Australia.; Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia. |
| Source: | Protein science : a publication of the Protein Society [Protein Sci] 2022 Nov; Vol. 31 (11), pp. e4453. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Cold Spring Harbor Laboratory Press Country of Publication: United States NLM ID: 9211750 Publication Model: Print Cited Medium: Internet ISSN: 1469-896X (Electronic) Linking ISSN: 09618368 NLM ISO Abbreviation: Protein Sci Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1469-896X |
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| DOI: | 10.1002/pro.4453 |
