Computational Tools Play Versatile Role In Designing New TB Drugs From Anti-Tubercular Peptides
Without a doubt, tuberculosis (TB) is a symbolic threat to human health, causing millions of mortalities per year. Developing TB therapy without leading to drug-resistant Mycobacterium tuberculosis is a million-dollar question at present. A plethora of commercially-available drugs with a disparate mode of action and administration have been utilized for TB treatment for five decades.
M. tuberculosis has a unique strategy of defense against anti-tubercular drugs available on the market. Unfortunately, the current trend of TB treatment is the leading factor in the emergence of multidrug-resistant, extensively-resistant, and totally drug-resistant TB. As a matter of fact, the emerging dilemma of drug-resistant bacteria, as well as the complexity and relentless toxicity of the commercially-available conventional drugs, has compelled us to develop new TB drugs from un/less exploited resources.
Tuberculosis is curable, provided that new technologies could be discovered diligently. In the line of promising anti-tubercular agents, peptides isolated from distinct resources might play a pronounced role in TB treatment. Anti-tubercular peptides are gene-encoded peptides that exhibit direct mycobactericidal attributes and devote a pivotal appearance in the host defense process. The mycobactericidal attributes of peptides have been discussed in previously reported comprehensive literature. Peptides of diversified origins, such as human immune cells and non-immune cells, microorganisms, and venoms of reptiles, have been extensively exploited for their pronounced anti-tubercular traits. Peptides represent direct growth inhibition of bacterium and show immune-modulation properties during the infective stage.
Diverse computational tools viz. molecular dynamics, docking, and modeling are often being used to understand protein complexes involved in bacterial infection. In silico studies help to find the potential drug targets through proteomics. The computational web server has served as a substitute for in vitro tests assessing the physicochemical and structural traits of specific proteins. Proteins are present in the outer membrane, the inner membrane, periplasm, cytoplasm, and extracellular of prokaryotes, and, thus, it helps in designing novel mycobactericidal drugs.
The structural modeling of proteins is used to find the most effective surface epitope for drugs, thereby leading to the development of novel anti-tubercular drugs. Several pathways can be investigated for designing and developing rational anti-tubercular drugs. Disparate targets, such as thiamine metabolism, peptidoglycan biosynthesis, polyketide sugar unit biosynthesis, D-Alanine metabolism, fatty acid biosynthesis path1, fatty acid metabolism, phospholipid degradation, glycerolipid metabolism, ubiquinone and menaquinone biosynthesis, lysine biosynthesis, pyrimidine metabolism, purine metabolism, nitrogen metabolism, nucleotide sugar metabolism, inositol phosphate metabolism, and glycerolipid metabolism, have been used for designing an ideal and effective drug against TB.
A new specialized database, namely, PATH (Protein interactions of M. tuberculosis and Human) is used to store predicted interactions and potent proteins. The inter-specific and intra-specific interactions between M. tuberculosis and the human body are supported by this database. This database may be used in developing novel mycobactericidal drugs in the future. PATH was built on an Nginx with Python and a MySQL Server as the back-end. Hyper Text Markup Language, JQuery, and Cascading Style Sheets were applied at the front-end.
In summary, the systematic computational modeling of novel peptides and their modes of action will help to develop novel anti-tubercular drugs in the future that may create a new era, potentially leading to the end of TB. However, further effort is necessary to develop new web servers using computational tools for the discovery of novel drugs towards the effective and short-term treatment of TB during the next few decades.
These findings are described in the article entitled Neoteric advancement in TB drugs and an overview on the anti-tubercular role of peptides through computational approaches, recently published in the journal Microbial Pathogenesis.