A new fingerprint to predict nonribosomal peptides activity

被引：10

作者：

Abdo, Ammar ^{[1
,2
,3
]}

Caboche, Segolene ^{[1
,2
,4
]}

Leclere, Valerie ^{[4
]}

Jacques, Philippe ^{[4
]}

Pupin, Maude ^{[1
,2
]}

机构：

[1] Univ Lille 1, CNRS, LIFL, UMR 8022, F-59655 Villeneuve Dascq, France

[2] INRIA Lille Nord Europe, F-59655 Villeneuve Dascq, France

[3] Hodeidah Univ, Dept Comp Sci, Al Hudaydah, Yemen

[4] Univ Lille 1 Sci & Technol, PolytechLille, UPRES EA 1026, ProBioGEM, F-59655 Villeneuve Dascq, France

来源：

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN | 2012年 / 26卷 / 10期

关键词：

Nonribosomal peptides; Target Prediction; Similarity searching; Drug discovery; NATURAL-PRODUCTS; DRUG DISCOVERY; ADENYLATION DOMAINS; GENE CLUSTERS; SYNTHETASE; IDENTIFICATION; GENOME;

D O I：

10.1007/s10822-012-9608-4

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

070307 [化学生物学]; 071010 [生物化学与分子生物学];

摘要：

Bacteria and fungi use a set of enzymes called nonribosomal peptide synthetases to provide a wide range of natural peptides displaying structural and biological diversity. So, nonribosomal peptides (NRPs) are the basis for some efficient drugs. While discovering new NRPs is very desirable, the process of identifying their biological activity to be used as drugs is a challenge. In this paper, we present a novel peptide fingerprint based on monomer composition (MCFP) of NRPs. MCFP is a novel method for obtaining a representative description of NRP structures from their monomer composition in fingerprint form. Experiments with Norine NRPs database and MCFP show high prediction accuracy (> 93 %). Also a high recall rate (> 82 %) is obtained when MCFP is used for screening NRPs database. From this study it appears that our fingerprint, built from monomer composition, allows an effective screening and prediction of biological activities of NRPs database.

引用

页码：1187 / 1194

页数：8

共 33 条

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