| Project/Area Number |
18590034
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Physical pharmacy
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| Research Institution | The University of Tokushima |
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Principal Investigator |
CHUMAN Hiroshi The University of Tokushima, Graduate School, Institute of Health Bioscieces, Professor (20304545)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,890,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥390,000)
Fiscal Year 2007: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2006: ¥2,200,000 (Direct Cost: ¥2,200,000)
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| Keywords | artition coefficient / log P / ab initio molecular orbital / hydrophobic interaction / chytcrome P450 / HIV-1 protease / uantitative structure-activity relationship / charee transfer / logP / HIV-1-プロテアーゼ / サポートベクターマシン |
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| Research Abstract |
The aim of this research is to develop a novel quantitative prediction method of drug-protein interaction energy based on the hydrophobic and electronic energies, and to apply it in the field of rational drug design as a novel three-dimensional structure based Quantitative Structure-Activity Relationship (QSAR). Predicting enzymatic reactions is a crucial problem of biochemistry and pharmaceutical sciences, many methods to estimate biding properties for protein-ligand complexes have been reported. QSAR is the most widely used among them. However, a structure of target receptor has been usually treated as a "black box" in QSAR analyses. Recently, many three-dimensional structures of biologically important proteins are been solved by means of X-ray and NMR techniques. In this context, using molecular calculations and simulations, we have developed the novel QSAR method based on a complex structure between a drug and its target protein. Being successful in finding some logical links between results of classical QSAR and molecular level simulation for the inhibition of HIV-1 protease and other proteins, we understand how the classical QSAR descriptors can be interpreted in a detailed three-dimensional ligand-protein complex. The novel QSAR will enable us to show what is occurring in the binding processes at atomic and electronic levels and suggest us how to design drugs to control their activities and functions. We have also carried out the related studies using chemo-informatics and bio-pathway methods to obtain information that is difficult to obtain with QSAR- molecular simulation alone.
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