3D virtual screening of large combinatorial spaces.

A new method for 3D in silico screening of large virtual combinatorial chemistry spaces is described. The software PharmShape screens millions of individual compounds applying a multi-conformational pharmacophore and shape based approach. Its extension, PharmShapeCC, is capable of screening trillions of compounds from tens of thousands of combinatorial libraries. Key elements of PharmShape and PharmShapeCC are customizable pharmacophore features, a composite inclusion sphere, library core intermediate clustering, and the determination of combinatorial library consensus orientations that allow for orthogonal enumeration of libraries. The performance of the software is illustrated by the prospective identification of a novel CXCR5 antagonist and examples of finding novel chemotypes from synthesizing and evaluating combinatorial hit libraries identified from PharmShapeCC screens for CCR1, LTA4 hydrolase, and MMP-13.

[1]  Elizabeth A. Amin,et al.  Design, synthesis and evaluation of analogs of initiation factor 4E (eIF4E) cap-binding antagonist Bn7-GMP. , 2010, European journal of medicinal chemistry.

[2]  Jun Xu,et al.  Drug-like Index: A New Approach To Measure Drug-like Compounds and Their Diversity , 2000, J. Chem. Inf. Comput. Sci..

[3]  J. Sprent,et al.  Emerging cellular networks for regulation of T follicular helper cells. , 2012, Trends in immunology.

[4]  Robert P. Sheridan,et al.  Chemical Similarity Using Physiochemical Property Descriptors , 1996, J. Chem. Inf. Comput. Sci..

[5]  Robert P. Sheridan,et al.  Comparison of Topological, Shape, and Docking Methods in Virtual Screening , 2007, J. Chem. Inf. Model..

[6]  Jesper Z. Haeggström,et al.  Crystal structure of human leukotriene A4 hydrolase, a bifunctional enzyme in inflammation , 2001, Nature Structural Biology.

[7]  R. Förster,et al.  Chemokine Receptor CXCR5 Supports Solitary Intestinal Lymphoid Tissue Formation, B Cell Homing, and Induction of Intestinal IgA Responses , 2009, The Journal of Immunology.

[8]  Ingo Muegge Synergies of virtual screening approaches. , 2008, Mini reviews in medicinal chemistry.

[9]  Dik-Lung Ma,et al.  Drug repositioning by structure-based virtual screening. , 2013, Chemical Society reviews.

[10]  Holger Claussen,et al.  Searching Fragment Spaces with Feature Trees , 2009, J. Chem. Inf. Model..

[11]  Ruiyan Liu,et al.  Novel pyrrolidine ureas as C-C chemokine receptor 1 (CCR1) antagonists. , 2009, Journal of medicinal chemistry.

[12]  Alexander Tropsha,et al.  Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design. , 2011, Methods in molecular biology.

[13]  Michal Vieth,et al.  SDOCKER: a method utilizing existing X-ray structures to improve docking accuracy. , 2004, Journal of medicinal chemistry.

[15]  Matthias Rarey,et al.  Feature trees: A new molecular similarity measure based on tree matching , 1998, J. Comput. Aided Mol. Des..

[16]  Matthias Rarey,et al.  Design of Combinatorial Libraries for the Exploration of Virtual Hits from Fragment Space Searches with LoFT , 2012, J. Chem. Inf. Model..

[17]  C. King,et al.  New insights into the differentiation and function of T follicular helper cells , 2009, Nature Reviews Immunology.

[18]  Dimitris Georgiadis,et al.  Third generation of matrix metalloprotease inhibitors: Gain in selectivity by targeting the depth of the S1' cavity. , 2010, Biochimie.

[19]  Erden Banoglu,et al.  Overview of recent drug discovery approaches for new generation leukotriene A4 hydrolase inhibitors , 2013, Expert opinion on drug discovery.

[20]  Ruben Abagyan,et al.  A natural product-like inhibitor of NEDD8-activating enzyme. , 2011, Chemical communications.

[21]  G. Bemis,et al.  BREED: Generating novel inhibitors through hybridization of known ligands. Application to CDK2, p38, and HIV protease. , 2004, Journal of medicinal chemistry.

[22]  James M. Powers,et al.  CXC Chemokine Ligand 13 Plays a Role in Experimental Autoimmune Encephalomyelitis1 , 2006, The Journal of Immunology.

[23]  Tian Zhu,et al.  Hit identification and optimization in virtual screening: practical recommendations based on a critical literature analysis. , 2013, Journal of medicinal chemistry.

[24]  Andrew C. Good,et al.  New molecular shape descriptors: Application in database screening , 1995, J. Comput. Aided Mol. Des..

[25]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[26]  P. Hawkins,et al.  Comparison of shape-matching and docking as virtual screening tools. , 2007, Journal of medicinal chemistry.

[27]  Jason G. Cyster,et al.  A B-cell-homing chemokine made in lymphoid follicles activates Burkitt's lymphoma receptor-1 , 1998, Nature.

[28]  Robert P. Sheridan,et al.  Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results , 2008, J. Comput. Aided Mol. Des..

[29]  C. Brinckerhoff,et al.  Transcriptional regulation of collagenase (MMP-1, MMP-13) genes in arthritis: integration of complex signaling pathways for the recruitment of gene-specific transcription factors , 2001, Arthritis Research & Therapy.

[30]  Dik-Lung Ma,et al.  Molecular docking for virtual screening of natural product databases , 2011 .

[31]  W. Kabsch A solution for the best rotation to relate two sets of vectors , 1976 .

[32]  Dik-Lung Ma,et al.  Hit identification of IKKβ natural product inhibitor , 2013, BMC Pharmacology and Toxicology.

[33]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[34]  R. Abagyan,et al.  Structure-based discovery of natural-product-like TNF-α inhibitors. , 2010, Angewandte Chemie.

[35]  Fang Yang,et al.  Identification of natural product fonsecin B as a stabilizing ligand of c-myc G-quadruplex DNA by high-throughput virtual screening. , 2010, Chemical communications.

[36]  F. Aloisi,et al.  Lymphoid neogenesis in chronic inflammatory diseases , 2006, Nature Reviews Immunology.

[37]  Riccardo Dalla-Favera,et al.  Germinal centres: role in B-cell physiology and malignancy , 2008, Nature Reviews Immunology.

[38]  Anders Gabrielsen,et al.  Expression of 5-lipoxygenase and leukotriene A4 hydrolase in human atherosclerotic lesions correlates with symptoms of plaque instability. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[39]  Christian Lemmen,et al.  Similarity searching and scaffold hopping in synthetically accessible combinatorial chemistry spaces. , 2008, Journal of medicinal chemistry.

[40]  Uta Lessel,et al.  Identification of new potent GPR119 agonists by combining virtual screening and combinatorial chemistry. , 2012, Journal of medicinal chemistry.

[41]  Ingo Muegge,et al.  Advances in virtual screening , 2006, Drug Discovery Today: Technologies.

[42]  Jung-Mi Hah,et al.  Structure tuning of pyrazolylpyrrole derivatives as ERK inhibitors utilizing dual tools; 3D-QSAR and side-chain hopping. , 2011, Bioorganic & medicinal chemistry letters.

[43]  Qiang Zhang,et al.  Scaffold hopping through virtual screening using 2D and 3D similarity descriptors: ranking, voting, and consensus scoring. , 2006, Journal of medicinal chemistry.

[44]  J. A. Grant,et al.  A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape , 1996, J. Comput. Chem..

[45]  J. A. Grant,et al.  A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction. , 2005, Journal of medicinal chemistry.

[46]  R. Gladue,et al.  CCR1 antagonists: what have we learned from clinical trials. , 2010, Current topics in medicinal chemistry.

[47]  Jin-Ao Duan,et al.  Selective matrix metalloproteinase inhibitors for cancer. , 2009, Current medicinal chemistry.

[48]  Xiang Li,et al.  Fragment-based discovery of indole inhibitors of matrix metalloproteinase-13. , 2011, Journal of medicinal chemistry.

[49]  K Ulrich Wendt,et al.  Structural basis for the highly selective inhibition of MMP-13. , 2005, Chemistry and Biology.