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Molecular

分子

基本信息

批准号：
8335541
负责人：
MICHAEL V. SEIDEN
金额：
$ 2.67万
依托单位：
FOX CHASE CANCER CENTER
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-07-21 至 2014-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8335541
关键词：
Affect Amino Acid Sequence Binding Binding Proteins Binding Sites Biological Biological Process Biological Testing Biology Cancer Center Support Grant Charge Chemicals Comprehensive Cancer Center Computational Technique Computer Assisted Computer Simulation Computer software Computing Methodologies DNA Data Databases Disease Docking Drug Design Fox Chase Cancer Center Foxes Funding General Population Genes Genetic Polymorphism Genome Homo Homologous Protein Homology Modeling Human Hydrophobicity Inherited Instruction Intervention Knowledge Lead Left Ligands Location Maps Methods Modeling Molecular Molecular Models Mutagenesis Mutation Nuclear Magnetic Resonance Patients Pattern Peer Review Peptide Hydrolases Peptide Sequence Determination Peptides Phosphotransferases Phylogenetic Analysis Positioning Attribute Principal Investigator Process Protein Family Protein Region Protein Sequence Analysis Protein Structure Initiative Proteins Protocols documentation Research Research Personnel Resources Sequence Alignment Sequence Analysis Services Side Site Specificity Structural Models Structure Technology Time Translational Research Trees Two-Dimensional Gel Electrophoresis Vertebral column X-Ray Crystallography alpha helix base beta pleated sheet comparative complex biological systems design graphical user interface inhibitor/antagonist insertion/deletion mutation interest molecular modeling physical property programs protein complex protein folding protein structure protein structure function research study small molecule src Homology Region 2 Domain three dimensional structure three-dimensional modeling tool yeast two hybrid system

项目摘要

PROJECT SUMMARY (See instructions): The Molecular Modeling Facility (MMF) provides state-of-the-art services in protein sequence analysis and structure prediction to Fox Chase Cancer Center (FCCC) investigators. These services include database searches, multiple sequence alignments, phylogenetic tree comparisons, secondary structure predictions, transmembrane, coiled-coil and disordered region predictions, homology modeling of single proteins and complexes, protein-protein and protein-ligand docking, and ligand design. The Facility has been operating since 2003, and was approved as a CCSG resource at the last review. Currently, at least one-half of sequenced proteins are homologous at least in part to a protein of known structure. Homology modeling methods use known structures to build three-dimensional models of target proteins and protein complexes of unknown structure. These models can be used to predict functional interactions with other molecules, to explain existing experimental data, to generate testable hypotheses, and in some cases to become the basis for design of specific inhibitors for translational research. The Facility has performed services for 48 principal investigators with peer-reviewed funding in all five Research Programs since 2005. The Facility and the Facility Director's research group have developed new software for automating the modeling process to allow Facility staff more time to concentrate on the biological problem under study. In particular, they have developed methods for predicting the structures of protein homo- and heterooligomers, which comprise many important functional interactions. This software is extensible, so that it allows new tools to be incorporated into the same graphical user interface as they become available. As technologies such as two-hybrid interaction mapping and two-dimensional gel electrophoresis allow investigators to identify functional and physical Interactions of larger numbers of proteins, the demand for detailed structural information will grow rapidly. The use of this Facility is therefore expected to grow significantly over the next five years. The services of the Facility will provide increasingly important information for understanding complex biological systems.

项目概述（见说明）：