Evaluation of the Therapeutic Properties of Mastoparan- and Sifuvirtide- Derivative Antimicrobial Peptides Using Chemical Structure-Function Relationship - in vivo and in silico Approaches

Title:Evaluation of the Therapeutic Properties of Mastoparan- and Sifuvirtide- Derivative Antimicrobial Peptides Using Chemical Structure-Function Relationship - in vivo and in silico Approaches

Volume: 13 Issue: 2

Author(s): Speranta Avram, Maria Mernea, Florin Borcan and Dan Mihailescu

Affiliation:

Keywords: QSAR, antimicrobial peptides, mastoparan, sifuvirtide.

Abstract: Antimicrobial peptides, also called body defense peptides, are chemical structures widely distributed across the animal and vegetal kingdoms that have a fundamental role as part of the immune system. These peptides are used against a wide range of pathogens, such as Gram-negative and - positive bacteria, fungi and viruses, etc. Their action spectrum makes them important for the pharmaceutical industry, as they could represent templates for the design of new and more potent structures by using drug design and drug delivery systems. Here we present the antimicrobial activity against Bacillus subtilis (expressed as minimal inhibitory concentration values) for 33 mastoparan analogs and their new derivatives by quantitative structure–activity relationship method (2D, aligned and also non-aligned 3D-QSAR). We establish the contribution to antimicrobial activity of molecular descriptors like hydrophobicity, hydrogen bond donor and steric hindrance, correlated with contributions from the membrane environment (sodium, potassium, chloride ions). Also the studies of HIV-1 fusion inhibitor sifuvirtide and its analogs are presented in context of interaction with lipid structures during fusion and delivery of these drugs.

Cite this article as:

Avram Speranta, Mernea Maria, Borcan Florin and Mihailescu Dan, Evaluation of the Therapeutic Properties of Mastoparan- and Sifuvirtide- Derivative Antimicrobial Peptides Using Chemical Structure-Function Relationship - in vivo and in silico Approaches, Current Drug Delivery 2016; 13 (2) . https://dx.doi.org/10.2174/1567201813666151113122139