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Overview of Key ICM Features NIBR - Emeryville July 10-11 2012.

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Presentation on theme: "Overview of Key ICM Features NIBR - Emeryville July 10-11 2012."— Presentation transcript:

1 Overview of Key ICM Features NIBR - Emeryville July 10-11 2012

2 Introduction to MolSoft Established in 1994 Privately owned Worldwide customer base in academia, pharma and biotech Many published success stories in comp bio & chem

3 Support E-mail Call: 858-625-2000 x108

4 Molecule Visualization Store in a single file: – Representations – Lighting/Depth – Multiple Slides – Multiple Viewpoints – Annotation – Rendering – Parametric Animations – Alignments – Chemical Tables Product: ICM-Browser & ActiveICM

5 iMolview for the iPad and iPhone

6 Bioinformatics Fully interactive alignments Trees Sequence and alignments directly linked to 3D structure Rich alignment editor Sequence search PDB, Uniprot etc…

7 Structure Analysis Calculate – RMSD – Contact Areas – Surface Areas Measure distances and angles (planar, dihedral) Fully interactive Ramachandran Plots Protein Superposition

8 Structure Prediction Identify closed cavities Identify ligand binding sites (An et al 2005 & Kufareva et al 2012) Identify protein-protein interaction sites (Fernandez-Recio et al 2005) Protein health An, J., Totrov, M., and Abagyan, R. (2005). Pocketome Via Comprehensive Identification and Classification of Ligand Binding Envelopes. Mol Cell Proteomics 4, 752–761. Kufareva I, Ilatovskiy AV, Abagyan R. Pocketome: an encyclopedia of small-molecule binding sites in 4D. Nucleic Acids Res. 2012 Jan;40(Database issue):D535-40. Fernandez-Recio J, Totrov M, Skorodumov C, Abagyan R. Optimal docking area: a new method for predicting protein- protein interaction sites. Proteins. 2005 Jan 1;58(1):134-43

9 Crystallographic Analysis Neighbors Cell Biomolecule generator Display and contour electron density maps

10 Homology Modeling Build homology models (Katritch et al 2010) Refine models Predict and/or design loop conformation Search loop databases New loop modeling force-field (Arnautova et al 2011) Arnautova YA, Abagyan RA, Totrov M. Development of a new physics- based internal coordinate mechanics force field and its application to protein loop modeling. Proteins. 2011 Feb;79(2):477-98. Katritch V, Rueda M, Lam PC, Yeager M, Abagyan R. GPCR 3D homology models for ligand screening: lessons learned from blind predictions of adenosine A2a receptor complex. Proteins. 2010 Jan;78(1):197-211

11 3D Interactive Ligand Editor Interactively edit a ligand bound to a receptor in 3D. Screen for best replacement group Join fragments by linkers. Edit ligand in 2D molecular editor. Delete atoms and bonds. Convenient undo and redo modification feature. Dock and/or minimize edited ligand. Fragment docking. Multiple receptor docking Restrain atoms during docking

12 Cheminformatics 2D ligand sketcher Fully interactive chemical spreadsheets and plots Chemical clustering Chemical searching Library enumeration Pharmacophore searching

13 Atomic Property Fields A continuous, multi-component 3D potential that reflects preferences for various atomic properties at each point in space. Totrov M. Ligand binding site superposition and comparison based on Atomic Property Fields: identification of distant homologues, convergent evolution and PDB-wide clustering of binding sites. BMC Bioinformatics. 2011 Feb 15;12 Suppl 1:S35. Grigoryan AV, Kufareva I, Totrov M, Abagyan RA. Spatial chemical distance based on atomic property fields. J Comput Aided Mol Des. 2010 Mar;24(3):173-82. Totrov M. Atomic property fields: generalized 3D pharmacophoric potential for automated ligand superposition, pharmacophore elucidation and 3D QSAR. Chem Biol Drug Des. 2008 Jan;71(1):15-27.

14 Docking & Screening Small molecule docking Protein-protein docking Template docking Induced Fit Docking – Multiple Receptors – Explicit Groups Tethered Docking Virtual Screening – Structure-based – Ligand- based APF See: for success stories

15 ICMDB What is it? – A single, unified client for data entry, mining and manipulation built into a powerful chemistry and bio-enabled platform Prerequisites – One or multiple (possibly existing) relational databases with research data related to biology and chemistry Deployment – A cross-platform client – Installs transparently on top of existing databases

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