| Poster C05 |
| HOMOLOGY MODELING AND MOLECULAR DYNAMICS OF THE MONILIPHOTHORA PERNICIOSA CHITIN SYNTHASE ACTIVE SITE, THE AGENT OF WITCHES’ BROOM DISEASE OF COCOA |
| Bruno Andrade- State University of Feira de Santana |
| Catiane Souza (State University of Feira de Santana, Biological Sciences); Alex Taranto (State University of Feira de Santana, Health Sciences); Aristóteles Góes-Neto (State University of Feira de Santana, Biological Sciences); Sandra Assis (State University of Feira de Santana, Health Sciences); Rafaela Galante (State University of Feira de Santana, Health Sciences); Júlio Cascardo (State University of Santa Cruz, Biological Sciences); |
| Short Abstract: Chitin synthases (CHS) are the main component of the fungal cell wall and highly specific molecular targets for drugs. In this work, a model of Moniliophthora perniciosa CHS active site was constructed using Homology Modeling approach, and it was refined by a set of Molecular Mechanics and Molecular Dynamics. |
| Long Abstract: Click Here |
|
| Poster C06 |
| Automated tracking of proteome-wide drug target opportunities |
| Stephen Campbell- Pfizer |
| Sid Martin (Pfizer, Computational Sciences); Anna Gaulton (Pfizer, Computational Sciences); Dmitri Bichko (Pfizer, Computational Sciences); Robert Hernandez (Pfizer, Computational Sciences); Markella Skempri (Pfizer, Computational Sciences); Cory Brouwer (Pfizer, Computational Sciences); Lee Harland (Pfizer, Computational Sciences); |
| Short Abstract: Vast databanks of information present an ever-increasing challenge to drug discovery scientists. A novel data reduction and visualisation method assembles virtual maps of drug target opportunities. High impact incoming information can be detected and alerted on, according to the degree with which it alters the map. |
| Long Abstract: Click Here |
|
| Poster C07 |
| Real-time ray tracing of complex molecular scenes with BALLView and RTfact |
| Anna Dehof- Saarland University |
| Anne Dehof (Saarland University, Center for Bioinformatics); Iliyan Georgiev (Saarland University, Computer Graphics); Lukas Marsalek (Saarland University, Computer Graphics); Daniel Stoeckel (Saarland University, Center for Bioinformatics); Stefan Nickels (Saarland University, Center for Bioinformatics); Hans-Peter Lenhof (Saarland University, Center for Bioinformatics); Philipp Slusallek (Saarland University, Computer Graphics); Andreas Hildebrandt (Saarland University, Center for Bioinformatics); |
| Short Abstract: Molecular visualization is one of the cornerstones of structural bioinformatics,computational chemistry, and related fields. We present the first integration of a general purpose real-time ray tracingarchitecture into a molecular viewing and modelling tool by integratingthe RTfact library into BALLView, a versatile molecular viewing and editing tool. |
| Long Abstract: Click Here |
|
| Poster C08 |
| Leveraging Ligand-Protein Cross-interaction Information for In Silico Prediction of CYP Inhibition: Critical Assessment with In Vitro Assays |
| Teppei Ogawa- Kyoto University |
| Yohsuke Minowa (National Institute of Biomedical Innovation, Toxicogenomics-Informatics Project); Tetsuya Adachi (Kyoto University, Graduate School of Pharmaceutical Sciences); Chunlai Feng (Kyoto University, Graduate School of Pharmaceutical Sciences); Satoshi Niijima (Kyoto University, Graduate School of Pharmaceutical Sciences); Shinya Oishi (Kyoto University, Graduate School of Pharmaceutical Sciences); Nobutaka Fujii (Kyoto University, Graduate School of Pharmaceutical Sciences); Yasushi Okuno (Kyoto University, Graduate School of Pharmaceutical Sciences); |
| Short Abstract: We propose a comprehensive model for predicting CYP inhibition by leveraging ligand-CYP cross-interaction information. The proposed model was compared with existing models in terms of predictive ability and extracted features using large-scale interaction data. More importantly, we conducted in vitro bioassays to critically assess the general applicability of current techniques. |
| Long Abstract: Click Here |
|
| Poster C10 |
| Similarity of Chemical Mechanisms in Functionally Analogous Enzymes |
| Daniel Almonacid- University of California San Francisco |
| Emmanuel R Yera (University of California San Francisco, Department of Bioengineering and Therapeutic Sciences); John BO Mitchell (University of Cambridge, Department of Chemistry); Patricia C Babbitt (University of California San Francisco, Department of Bioengineering and Therapeutic Sciences); |
| Short Abstract: We compared 95 pairs of functionally analogous enzymes (enzymes that catalyze similar chemical transformations but do not share common ancestry) from the MACiE database. We conclude that functional analogues that catalyze similar overall transformations have commonly converged to use similar catalytic mechanisms, with several pairs sharing identical mechanistic steps. |
| Long Abstract: Click Here |
|
| Poster C12 |
| Tools for Validation of Predicted Pathways |
| Lynda Ellis- University of Minnesota |
| Junfeng Gao (University of Minnesota, Institute for Health Informatics); Larry Wackett (University of Minnesota, Biochemistry, Molecular Biology, and Biophysics); |
| Short Abstract: The UM-BBD Pathway Prediction System (http://umbbd.msi.umn.edu/predict/) predicts microbial catabolism of organic compounds. Predictions are validated using tools to test rules against all UM-BBD compounds, and aid manual examination of predicted pathways. In January 2009, 82% of 50 user-entered compounds received a reasonable number of plausible predictions. |
| Long Abstract: Click Here |
|
