Bioinformatics-Based Identification of Selective Cationic Amphipatic Antibacterial Peptides: Aurein 1.2 Variants Case

被引：0

作者：

Polanco, Carlos ^{[1
]}

Huberman, Alberto ^{[2
]}

Uversky, Vladimir N. ^{[3
,4
,5
]}

Andres, Leire ^{[6
]}

Buhse, Thomas ^{[7
]}

Castanon-Gonzalez, Jorge Alberto ^{[8
]}

Diaz-Gonzalez, Juan Luciano ^{[9
]}

机构：

[1] Univ Nacl Autonoma Mexico, Fac Sci, Dept Math, Mexico City 04510, DF, Mexico

[2] Inst Nacl Ciencias Med & Nutr Salvador Zubiran, Dept Biochem, Mexico City 14080, DF, Mexico

[3] Univ S Florida, Morsani Coll Med, Dept Mol Med, Tampa, FL 33647 USA

[4] Univ S Florida, Morsani Coll Med, USF Hlth Byrd Alzheimers Res Inst, Tampa, FL 33647 USA

[5] Russian Acad Sci, Fed Res Ctr Pushchino Sci Ctr Biol Res Russian Ac, Prot Res Grp, Inst Biol Instrumentat, Pushchino 142290, Moscow Region, Russia

[6] Hosp Cruces, Dept Pathol, Baracaldo 48903, Spain

[7] Univ Autonoma Estado Morelos, Chem Res Ctr, Cuernavaca 62209, Morelos, Mexico

[8] Hosp Juarez Mexico, Dept Crit Care Med, Mexico City 07760, DF, Mexico

[9] Univ Nacl Autonoma Mexico, Inst Ciencias Nucl, Dept Comp Sci, Mexico City 04510, DF, Mexico

来源：

CURRENT PROTEOMICS | 2021年 / 18卷 / 04期

关键词：

Selective cationic amphipathic antibacterial peptides; antimicrobial peptides; structural proteomics; bioinformatics; intrinsic disorder predisposition; PIM (R) profile; ANTIMICROBIAL PEPTIDES; INTRINSIC DISORDER; MODEL MEMBRANES; PROTEINS; PREDICTION; SEQUENCE;

D O I：

10.2174/1570164617999201116151451

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Background: Selective Cationic Amphipathic Antibacterial Peptides (SCAAPs) occupy a prominent place in the production of new drugs on account of their high toxicity towards bacteria and low toxicity towards mammalian cells, low hemolytic activity, and contribution to the protection of the human immune system. Introduction: their number in nature is very low, and experimental tests are very protracted and costly. Therefore, it would be useful to have bioinformatics tools that would identify them in the existing databases and also propose new synthetic SCAAPs. Methods: In order to reduce the costs of identification and/or chemical synthesis and to know the physicochemical characteristics of SCAAPs at a residues level and to obtain a "bioiformatics fingerprint" suitable for their selection , we have modified the Polarity Index Method (R) (PIM (R)) and the alpha-helical configuration of each sequence is included in determining their individual "PIM (R) profile". We have also used a set of the computer program to determine their "Intrinsic Disorder Predisposition". This information was then compared with other protein groups , such as bacteria, fungi, virus and cell-penetrating peptides (CPP) from the UniProt database and a set of intrinsically disordered proteins. Once the "fingerprint" of SCAAPs was obtained , it was used for searching among the 559228 "reviewed" proteins from the UniProt database and a set of synthetic SCAAPs characterized by the predefined "PIM (R) profile" selected. Results: Our results showed that the metric named "PIM (R) profile" can identify, with a high level of accuracy , a group of bacterial SCAAPs. This bioinformatics study was supported at residues level , using the in-house bioinformatics system Polarity Index Method, the commonly used algorithm for predicting intrinsic disorder predisposition, PONDR (R) FIT. Conclusions: The Polarity Index Method seems highly efficient in identifying SCAAP candidates.

引用

页码：505 / 518

页数：14