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Development of GRAMM Method and Software for Protein-Protein Docking

Development of GRAMM Method and Software for Protein-Protein Docking
蛋白质-蛋白质对接的 GRAMM 方法和软件的开发
批准号:
9808093
负责人:
Ilya Vakser
金额:
$30.92万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-09-15 至 2001-11-30

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中文摘要
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英文摘要
The main goal of this project is to obtain a method which will produce an accurate model of a protein-protein complex from two separate, flexible, and possible inaccurate protein structures. A distinguishing feature of this new docking procedure is that it searches through the conformation of each protein in addition to the relative positions of the two proteins. This project involves the further development of GRAMM (Global RAnge Molecular Matching) docking methodology and software for protein docking. GRAMM is used at low resolution to predict the structures of complexes in the non-redundant database of protein complexes using both actual individual structures from the complexes and their models. The flexible docking procedure is expected to be more accurate and more robust with respect to the inaccuracies in the initial approximate structures of the interacting proteins than are the currently prevalent rigid docking procedures. The approach will be especially useful in view of the rate of advance in the human genome project, since it will allow a rapid evaluation of functions for a large number of predicted protein structures. Thus, the combination of protein structure prediction and protein docking is expected to increase greatly the usefulness of molecular modeling.
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UKRI/BBSRC - NSF/BIO: Modeling of protein interactions to predict phenotypic effects of genetic mutations
Bilateral BBSRC-NSF/BIO: CIBR: Structural modeling of interactome to assess phenotypic effects of genetic variation.
Bilateral BBSRC-NSF/BIO: ABI Innovation: Modeling protein interactions to interpret genetic variation
ABI Innovation: Target - template structural and functional relationships in modeling of protein - protein interactions
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