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Title: Computational and experimental studies of putative virulence factors of Mycobacterium tuberculosis H37Rv
Authors: Shahbaaz, Mohd 
Issue Date: 2017
In drug discovery and development of anti-tubercular therapeutics, it is necessary to study the physiology and genetics of the molecular mechanisms present in the Mycobacterium tuberculosis. The virulence of M. tuberculosis is attributed to its unique genome, which contains a high frequency of glycine-rich proteins and genes involved in the metabolism of the fatty acids. Consequently, the presence of a diversity of the pathogenic pathways such as acid tolerance and drug resistance mechanisms in M. tuberculosis makes the treatment of Tuberculosis (TB) challenging. However, the molecular basis of the virulence factors involved in the pathogenesis is not fully understood. Accordingly, the current study focuses on better understanding of the pathogenic proteins present in this bacterium using available computational techniques.
In South Africa, there is an alarming increase in the drug-resistant TB in HIV co-infected patients, which is one of the biggest challenges to the current anti-tubercular therapies. An extensive literature search showed that the mutations in the virulent proteins of M. tuberculosis resulted in the development of drug tolerance in the pathogen. The molecular and genetic studies identified frequently occurring point mutations associated with the drug resistance in proteins of
M. tuberculosis. Despite the efforts, TB infection is still increasing because different pathogenic pathways in the bacterial system are still undiscovered. Therefore, this study involves an in silico approach aimed at the identification of novel drug resistance implicated point mutations. The site- directed mutations leading to the development of resistance against four first-line drugs (Ethambutol, Isoniazid, Rifampicin, and Streptomycin) were studied extensively. In the primary investigation, pathogenic mutational landscapes were classified in the sequences of the studied proteins. The effects of these mutations on the stability of the proteins were studied using diverse computational techniques. The structural basis of the point mutations with the highest

destabilizing effects was analyzed using the principles of the Density Functional Theory (DFT), molecular docking and molecular dynamics (MD) simulation studies. The varied conformational behavior resulted from these predicted substitutions were compared with the experimentally derived mutations reported in the literature. The outcome of this study enabled the identification of the novel drug resistance-associated point mutations which were not previously reported.
Furthermore, a detailed understanding of the conformational behavior of diverse virulent proteins present in M. tuberculosis was also generated in this study. Literature study showed that inside the host’s macrophage cells, the virulent proteins such as isocitrate lyase, lipase lipF, magnesium transporter MgtC, porin protein OmpATb, a protein of two component systems PhoP, Rv2136c and Rv3671c have an established role in the development of the acid tolerance. On the other hand, information regarding their role in the acid resistance is scarce. Accordingly, the structural basis of their role in acid resistance was analyzed using constant pH based MD simulations. In the studied proteins, the lipF and PhoP showed highest structural stability in highly acidic conditions throughout the course of MD simulations. Therefore, these proteins may play a primary role in the process of resistance.
In addition to these pathogenic proteins, there is a need to identify new undiscovered virulent proteins in the genome of M. tuberculosis, which increases the efficiency of the current therapy. The knowledge generated by the analyses of the proteins involved in resistance and pathogenic mechanisms of M. tuberculosis forms the basis for the identification of new virulence factors. Therefore, an in silico protocol was used for the functional annotations and analyses of the virulence characteristics.
M. tuberculosis contains 1000 Hypothetical Proteins (HPs), which are functionally uncharacterized proteins and their existence was not validated at the biochemical level. In this

study, the sequences of the HPs were extensively analyzed and the functions of 662 HPs were successfully predicted. Furthermore, 483 HPs were classified in the category of the enzymes, 141 HPs were predicted to be involved in the diverse cellular mechanisms and 38 HPs may function as transporters and carriers proteins. The 307 HPs among this group of proteins were less precisely predicted because of the unavailability of the reliable functional homologs. An assessment of the virulence characteristics associated with the 1000 HPs enabled the classification of 28 virulent HPs. The structure of six HPs with highest predicted virulence score was analyzed using molecular modelling techniques.
Amongst the predicted virulent HPs, the clone for Rv3906c purchased from the DNASU repository because of the ease of its availability. The gene of Rv3906c was isolated and cloned into a pET-21c expression vector. The analyses of the nucleotide sequence showed that Rv3906c gene (500 bp) encodes a 169 amino acid protein of molecular weight 17.80 kDa (~18.0 kDa). The sequence analyses of Rv3906c showed that the HPs showed high similarities with pullulanase, a thermophilic enzyme. The stability profile at different temperatures for Rv3906c generated using MD simulations showed that Rv3906c maintained its structural identity at higher temperatures. It is expected that this study will result in the design of better therapeutic against the infection of M. tuberculosis, as novel undiscovered virulence factors were classified and analyzed in addition to the conformational profiles of the virulent proteins involved in the resistance mechanisms.
Submitted in fulfillment of the requirements for the degree of Doctor of Philosophy in Chemistry, Durban University of Technology, Durban, South Africa, 2017.
Appears in Collections:Theses and dissertations (Applied Sciences)

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