3D modelling of the pathogenic Leptospira protein LipL32: A bioinformatics approach

Autor: Rukman Awang Hamat, Palanisamy Arulselvan, Hiba Alsaeedy, Mok Pooi Ling, Giovanni Benelli, Teh Seoh Wei, K. Poorani, S. Sakinah, Akon Higuchi, Mohd Faizal Abu Bakar, Amira Peli, Vasantha Kumari Neela, Mariappan Rajan, Abdullah A. Alarfaj, S. Suresh Kumar, Shuhaila Mat-Sharani, Hirzahida Mohd-Padil, Sharmilah Kumari Kumaran
Rok vydání: 2017
Předmět:
Zdroj: Acta Tropica. 176:433-439
ISSN: 0001-706X
DOI: 10.1016/j.actatropica.2017.09.011
Popis: Leptospirosis is a widespread zoonotic disease caused by pathogenic Leptospira species (Leptospiraceae). LipL32 is an abundant lipoprotein from the outer membrane proteins (OMPs) group, highly conserved among pathogenic and intermediate Leptospira species. Several studies used LipL32 as a specific gene to identify the presence of leptospires. This research was aimed to study the characteristics of LipL32 protein gene code, to fill the knowledge gap concerning the most appropriate gene that can be used as antigen to detect the Leptospira. Here, we investigated the features of LipL32 in fourteen Leptospira pathogenic strains based on comparative analyses of their primary, secondary structures and 3D modeling using a bioinformatics approach. Furthermore, the physicochemical properties of LipL32 in different strains were studied, shedding light on the identity of signal peptides, as well as on the secondary and tertiary structure of the LipL32 protein, supported by 3D modelling assays. The results showed that the LipL32 gene was present in all the fourteen pathogenic Leptospira strains used in this study, with limited diversity in terms of sequence conservation, hydrophobic group, hydrophilic group and number of turns (random coil). Overall, these results add basic knowledge to the characteristics of LipL32 protein, contributing to the identification of potential antigen candidates in future research, in order to ensure prompt and reliable detection of pathogenic Leptospira species.
Databáze: OpenAIRE