title: E-novo: an automated workflow for efficient structure-based lead optimization.
abstract: An automated E-Novo protocol designed as a structure-based lead optimization tool was prepared through Pipeline Pilot with existing CHARMm components in Discovery Studio. A scaffold core having 3D binding coordinates of interest is generated from a ligand-bound protein structural model. Ligands of interest are generated from the scaffold using an R-group fragmentation/enumeration tool within E-Novo, with their cores aligned. The ligand side chains are conformationally sampled and are subjected to core-constrained protein docking, using a modified CHARMm-based CDOCKER method to generate top poses along with CDOCKER energies. In the final stage of E-Novo, a physics-based binding energy scoring function ranks the top ligand CDOCKER poses using a more accurate Molecular Mechanics-Generalized Born with Surface Area method. Correlation of the calculated ligand binding energies with experimental binding affinities were used to validate protocol performance. Inhibitors of Src tyrosine kinase, CDK2 kinase, beta-secretase, factor Xa, HIV protease, and thrombin were used to test the protocol using published ligand crystal structure data within reasonably defined binding sites. In-house Respiratory Syncytial Virus inhibitor data were used as a more challenging test set using a hand-built binding model. Least squares fits for all data sets suggested reasonable validation of the protocol within the context of observed ligand binding poses. The E-Novo protocol provides a convenient all-in-one structure-based design process for rapid assessment and scoring of lead optimization libraries.
authors: Bristol-Myers Squibb, Computer-Assisted Drug Design, 5 Research Parkway, Wallingford, Connecticut 06492, USA. bradley.pearce@bms.com
authors: Bradley C
authors: BC
authors: Pearce
authors: David R
authors: DR
authors: Langley
authors: Jia
authors: J
authors: Kang
authors: Hongwei
authors: H
authors: Huang
authors: Amit
authors: A
authors: Kulkarni
mesh_terms: D053829:Amyloid Precursor Protein Secretases / Q000037:antagonists & inhibitors / Q000737:chemistry / Q000378:metabolism; D000818:Animals; D001665:Binding Sites; D018360:Crystallography, X-Ray; D051357:Cyclin-Dependent Kinase 2 / Q000037:antagonists & inhibitors / Q000737:chemistry / Q000378:metabolism; D015195:Drug Design; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000378:metabolism*; D015951:Factor Xa / Q000737:chemistry / Q000378:metabolism; D065427:Factor Xa Inhibitors; D016333:HIV Protease / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D015394:Molecular Structure; D011485:Protein Binding; D011506:Proteins / Q000037:antagonists & inhibitors* / Q000737:chemistry / Q000378:metabolism*; D012136:Respiratory Syncytial Viruses / Q000187:drug effects; D013816:Thermodynamics; D013917:Thrombin / Q000037:antagonists & inhibitors / Q000737:chemistry / Q000378:metabolism; D019061:src-Family Kinases / Q000037:antagonists & inhibitors / Q000737:chemistry / Q000378:metabolism
chemical_list: D004791:Enzyme Inhibitors; D065427:Factor Xa Inhibitors; D008024:Ligands; D011506:Proteins; D019061:src-Family Kinases; D051357:Cyclin-Dependent Kinase 2; D053829:Amyloid Precursor Protein Secretases; D013917:Thrombin; D015951:Factor Xa; D016333:HIV Protease