Drug repurposing is a more inexpensive and shorter approach than the traditional drug discovery and development process. The concept of identifying a potent molecule from a library of pre-existing molecules or an already approved drug has become a go-to tactic to accelerate the identification of drugs that can prevent COVID-19. This seemingly uncontrollable disease is caused by SARS-CoV-2. It is a novel virus of the Betacoronavirus genus, exhibiting similarities to the previously reported SAR-CoV genome structure and viral pathogenesis. The emergence of SARS-CoV-2 and the rapid outbreak of COVID-19 have resulted in a global pandemic. Researchers are hard-pressed to develop new drugs for total containment of the disease, thus making the cost-effective drug repurposing a much more feasible approach. Therefore, the current review attempts to collate both the experimental and computational drug repurposing strategies that have been utilized against significant drug targets of SARS-CoV-2. Along with the strategies, the available druggable targets shall also be discussed. However, the occurrence of frequent recombination of the viral genome and time-bound primary analysis, resulting in insignificant data, are two major challenges that drug repurposing still faces.

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Malaria is one of the most devastating infectious diseases which have infected hundreds of millions of people worldwide. Although several anti‐malarial drugs are in clinical use, there is an urgent need for new drugs acting through novel mechanisms of action due to rapid development of resistance. A lipid kinase, phosphatidylinositol‐4‐OH kinase (PI(4)K) type IIIβ has been recently identified as the target of imidazopyrazines. However, due to the absence of a crystal structure of PfPI(4)KIIIβ, the process of in‐silico drug development has not been possible. Here, we have modeled the plasmodial PI(4)KIIIβ using homology modeling approach. The model has been validated and further, stabilized using molecular dynamics (MD) simulations. A total of 178 compounds were retrieved from PubChem database. These compounds were screened on the basis of hERG liability and toxicity. Molecular docking calculations were performed using two softwares to study the interaction of the selected molecules with the model protein. Docking studies helped us to identify a few molecules with better binding modes. The dynamical movement of five selected molecules were studied and the protein‐ligand interactions were analysed. Our results showed that out of the five molecules, three compounds are stable within the binding cavity of the protein and have the potential to inhibit the PfPI(4)KIIIβ. Our work provides a strategy for the design of specific inhibitors that could potentially target plasmodial PI(4)KIIIβ and would prove to be instrumental in eradicating malaria.

The potential biomedical application of carbon nanotubes (CNTs) pertinent to drug delivery is highly manifested considering the remarkable electronic and structural properties exhibited by CNT. To simulate the interaction of nanomaterials with biomolecular systems, we have performed density functional calculations on the interaction of pyrazinamide (PZA) drug with functionalized single-wall CNT (fSWCNT) as a function of nanotube chirality and length using two different approaches of covalent functionalization, followed by docking simulation of fSWCNT with pncA protein. The functionalization of pristine SWCNT facilitates in enhancing the reactivity of the nanotubes and formation of such type of nanotube-drug conjugate is thermodynamically feasible. Docking studies predict the plausible binding mechanism and suggests that PZA loaded fSWCNT facilitates in the target specific binding of PZA within the protein following a lock and key mechanism. Interestingly, no major structural deformation in the protein was observed after binding with CNT and the interaction between ligand and receptor is mainly hydrophobic in nature. We anticipate that these findings may provide new routes towards the drug delivery mechanism by CNTs with long term practical implications in tuberculosis chemotherapy.

Tuberculosis caused by Mycobacterium tuberculosis is an infectious bacterial disease which is a leading cause of mortality affecting more than 9 million people worldwide. The current standard regimens that are available for the treatment of TB are severely hampered due to the occurrence of multidrug-resistant (MDR-TB) and extensively drug-resistant (XDR-TB) strains of Mycobacterium tuberculosis. In the past few years, a huge and constantly expanding effort has been developed to understand the chemical-biological interaction of many new anti-tubercular drugs and their targets in mathematical terms. Here, we have elected to review only those studies concerning 2D and 3D QSAR models that contain different DFT based descriptors as their parameters.