KNIME-based scoring functions in Muse 3.0. KNIME User Group Meeting 2013 Fabian Bös
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1 KIME-based scoring functions in Muse 3.0 KIME User Group Meeting 2013 Fabian Bös
2 Certara Mission: End-to-End Model-Based Drug Development Certara was formed by acquiring and integrating Tripos, Pharsight, and Simcyp, complementary companies focused on model-based approaches in different phases of the drug discovery and development cycle. Mission is to provide software and services in support of translational drug development More than 230 employees, including 80 PhD's. ver 6,000 users at more than 3,000 different companies 2
3 Software Portfolio 3
4 Muse: Software for multi-criteria molecular design 34 structure-modifying operators May preserve substructure(s) May tailor evolutionary process May add custom fragment library May exclude undesirable chemistry Seed Structures Invent Result Structures Population of Parents (With Scores) Select Repeat for umber of Generations Population f Parents & Children Population f Children Score Tripos Score using KIME workflow in the background (With Scores) 5
5 TriposScore multi criteria ligand based scoring Tanimoto similarity:
6 TriposScore retrospective example K1 receptor antagonist CP99994 Starting point Muse inventions Known actives Pfizer: W CP99994 Pfizer: W
7 Multi-Criteria Composable Scoring Via KIME
8 Multi-Criteria Composable Scoring Via KIME Read invented compounds, calculate properties, Lipinski filter
9 Multi-Criteria Composable Scoring Via KIME Read invented compounds, calculate properties, Lipinski filter Read bad structures, calculate & compare UITY fingerprints, filter compounds if too close
10 Multi-Criteria Composable Scoring Via KIME Read invented compounds, calculate properties, Lipinski filter Read bad structures, calculate & compare UITY fingerprints, filter compounds if too close Read reference structures, calculate & compare UITY fingerprints
11 Multi-Criteria Composable Scoring Via KIME Read invented compounds, calculate properties, Lipinski filter Read bad structures, calculate & compare UITY fingerprints, filter compounds if too close Read reference structures, calculate & compare UITY fingerprints Flexible 3D shape & pharmacophore similarity, final score building
12 Scoring compounds using shape, volume & scaffold Using a KIME installation with all recent open source nodes installed (CDK, Indigo, RDKit) Read SDF files, calculate similarity to reference using Ultra fast shape similarity (USR 1 ) VABCVolume 3 (fast calculation of van der Waals Volume) Charge weighted topological structure autocorrelation 2 Morgan (circular) fingerprint 5 of Murcko scaffolds 4 Combine the four values using Lilly s Desirability node 1. Bellester, P.J. and Richards, W.G., Ultrafast shape recognition to search compound databases for similar molecular shapes, Journal of Computational Chemistry, 2007, 28: Moreau G. and Broto P., The autocorrelation of a topological structure: A new molecular descriptor, ouveau Journal de Chimie, 1980, Zhao, Yuan H. and Abraham, Michael H. and Zissimos, Andreas M., Fast Calculation of van der Waals Volume as a Sum of Atomic and Bond Contributions and Its Application to Drug Compounds, The Journal of rganic Chemistry, 2003, 68: Bemis, G.W.; Murcko, M.A., The Properties of Known Drugs. 1. Molecular Frameworks, Journal of Medicinal Chemistry, 1996, 39: Rogers, D.; Hahn, M., Extended-Connectivity Fingerprints., J. Chem. Inf. and Model., 2010, 50:742-54
13 Scoring compounds using shape, volume & scaffold 15
14 Scoring compounds using shape, volume & scaffold Starting point Muse inventions Known actives Pfizer: W CP99994 Pfizer: W
15 Thank you.
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