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Diverse computational tools towards the understanding of HIV targets and design of potential drug candidates.

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HIV/AIDS still remains to be a challenging epidemic infecting millions of individuals worldwide. The morbidity and mortality rates of HIV-infected patients has been well documented over the years. Despite on-going HIV/AIDS research and access to antiretroviral therapy, to date still no cure exists for this deliberating disease. In recent years, computational approaches have emerged as close counterparts to experiments in modern drug discovery process and in understanding complex biological phenomena. An array of in-silico computational techniques were implemented ranging from molecular dynamic (MD) simulations, de-novo design, hybrid structure-based and pharmacophore-based virtual screening, quantitative structure-activity relationship (QSAR), homology modeling, principle component analysis (PCA), residue interaction network analysis (RIN), substrate envelope analysis (SEA), to molecular mechanics and quantum mechanics. The first report (Chapter 4), demonstrated a unique strategy for developing dual acting inhibitors against HIV-1 protease (PR) and reverse transcriptase (RT). The designed targets exhibited binding affinities and dual inhibiting activity comparable to, and in some cases better than, known active reference drugs. The second study (Chapter 5), reported the activity of flexible hydroquinone-based compounds as non-nucleoside reverse transcriptase inhibitors (NNRTIs), as proposed by Bruccoleri, where no experimental or computational work supported his proposal. Results concluded that the novel flexible hydroquinone-based compounds showed improved binding affinity as compared to FDA-approved prototype drugs and more specifically potent potential mutant-resistant NNRT inhibitor activity. The third report (Chapter 6), explored the activity of novel CCR5 antagonists as potential HIV- 1 entry inhibitors. Ten scaffolds were identified as novel CCR5 antagonists or potential HIV-1 entry inhibitors. Furthermore, from the generated atom-based 3D-QSAR model, all of the parameters showed certain reliability and feasible predictability to help us design new and high selectivity CCR5 inhibitors. The fourth study (Chapter 7), explored the atomistic basis of why the M184I single mutation renders complete resistance of HIV-1 RT to lamivudine. Multiple molecular dynamics simulations, binding free energy calculations, principle component analysis (PCA) and residue interaction network (RIN) analyses adequately clarified the effect of the M184I mutation on drug resistance to lamvudine. Results presented in this study verified that M184I mutation decreased drug binding affinity, distorted ligand optimum orientation in RT active site and affected the overall protein conformational landscape. The results also provided some potential clues for further design of novel inhibitors that are less susceptible to drug resistance. In the fifth study (Chapter 8), we identified potential HIV-Nef inhibitors by exploiting the structural features of B9 using an integrated computational tools framework. The top identified hit compounds demonstrated comparatively better binding affinities and relatable binding modes compared to the prototype antagonist, B9. Top identified hits were proposed as new potential novel leads targeting HIV-Nef with a detailed analysis of their respective binding modes. The sixth report (Chapter 9), aimed to reveal the dimer packing and unpacking phenomena of HIV-Nef in its apo and inhibitor bound conformations using molecular dynamic simulations. Results verified a more conformational flexible nature of HIV-Nef dimer in the absence of an compared to B9 bound conformation of HIV-Nef, which was found to be more conformationally rigid with a lesser inter-dimeric association. We believe that the results obtained from these several studies could be of great benefit in the development of more effective therapeutic interventions for the treatment and cure of HIV/AIDS.


Ph. D. University of KwaZulu-Natal, Durban 2014.


Protease inhibitors., Protease inhibitors--Data processing., HIV (Viruses)--Treatment., AIDS (Disease)--Treatment., Theses--Pharmacy and pharmacology.