| Autor: |
SHRESTHA, NRIPENDRA L., KAWAGUCHI, YOUHEI, OHKAWA, TAKENAO |
| Předmět: |
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| Zdroj: |
International Journal of Computational Intelligence & Applications; Dec2004, Vol. 4 Issue 4, p431-449, 19p |
| Abstrakt: |
Protein surface motifs, which can be defined as commonly appearing patterns of shape and physical properties in protein molecular surfaces, can be considered "possible active sites". We have developed a system for mining surface motifs: SUMOMO which consists of two phases: surface motif extraction and surface motif filtering. In the extraction phase, a given set of protein molecular surface data is divided into small surfaces called unit surfaces. After extracting several common unit surfaces as candidate motifs, they are repetitively merged into surface motifs. However, a large amount of surface motifs is extracted in this phase, making it difficult to distinguish whether the extracted motifs are significant to be considered active sites. Since active sites from proteins with a particular function have similar shape and physical properties, proteins can be classified based on similarity among local surfaces. Thus, in the filtering phase, local surfaces extracted from proteins of the same group are considered significant motifs, and the rest are filtered out. The proposed method was applied to discover surface motifs from 15 proteins belonging to four function groups. Motifs corresponding to all 4 known functional sites were recognised. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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