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Background: HIV-1 produces Tat, a crucial protein for transcription, viral replication, and CNS neurotoxicity. Tat interacts with TAR, enhancing HIV reverse transcription. Subtype C Tat variants (C31S, R57S, Q63E) are associated with reduced transactivation and neurovirulence compared to subtype B. However, their precise impact on Tat-TAR binding is unclear. This study investigates how these substitutions affect Tat-TAR interaction., Methods: We utilized molecular modelling techniques, including MODELLER, to produce precise three-dimensional structures of HIV-1 Tat protein variants. We utilized Tat subtype B as the reference or wild type, and generated Tat variants to mirror those amino acid variants found in Tat subtype C. Subtype C-specific amino acid substitutions were selected based on their role in the neuropathogenesis of HIV-1. Subsequently, we conducted molecular docking of each Tat protein variant to TAR using HDOCK, followed by molecular dynamic simulations., Results: Molecular docking results indicated that Tat subtype B (TatWt) showed the highest affinity for the TAR element (-262.07), followed by TatC31S (-261.61), TatQ63E (-256.43), TatC31S/R57S/Q63E (-238.92), and TatR57S (-222.24). However, binding free energy analysis showed higher affinities for single variants TatQ63E (-349.2 ± 10.4 kcal/mol) and TatR57S (-290.0 ± 9.6 kcal/mol) compared to TatWt (-247.9 ± 27.7 kcal/mol), while TatC31S and TatC31S/R57SQ/63E showed lower values. Interactions over the protein trajectory were also higher for TatQ63E and TatR57S compared to TatWt, TatC31S, and TatC31S/R57SQ/63E, suggesting that modifying amino acids within the Arginine/Glutamine-rich region notably affects TAR interaction. Single amino acid mutations TatR57S and TatQ63E had a significant impact, while TatC31S had minimal effect. Introducing single amino acid variants from TatWt to a more representative Tat subtype C (TatC31S/R57SQ/63E) resulted in lower predicted binding affinity, consistent with previous findings., Conclusions: These identified amino acid positions likely contribute significantly to Tat-TAR interaction and the differential pathogenesis and neuropathogenesis observed between subtype B and subtype C. Additional experimental investigations should prioritize exploring the influence of these amino acid signatures on TAR binding to gain a comprehensive understanding of their impact on viral transactivation, potentially identifying them as therapeutic targets., (© 2024. The Author(s).)

Background: The Integrase (IN) strand transfer inhibitor (INSTI), Dolutegravir (DTG), has been given the green light to form part of first-line combination antiretroviral therapy (cART) by the World Health Organization (WHO). DTG containing regimens have shown a high genetic barrier against HIV-1 isolates carrying specific resistance mutations when compared with other class of regimens., Methods: We evaluated the HIV-1 CRF02_AG IN gene sequences from Cameroon for the presence of resistance-associated mutations (RAMs) against INSTIs and naturally occurring polymorphisms (NOPs), using study sequences (n = 20) and (n = 287) sequences data derived from HIV Los Alamos National Laboratory database. The possible impact of NOPs on protein structure caused by HIV-1 CRF02_AG variations was addressed within the context of a 3D model of the HIV-1 IN complex and interaction analysis was performed using PyMol to validate DTG binding to the Wild type and seven mutant structures., Results: We observed 12.8% (37/287) sequences to contain RAMs, with only 1.0% (3/287) of the sequences having major INSTI RAMs: T66A, Q148H, R263K and N155H. Of these,11.8% (34/287) of the sequences contained five different IN accessory mutations; namely Q95K, T97A, G149A, E157Q and D232N. NOPs occurred at a frequency of 66% on the central core domain (CCD) position, 44% on the C-terminal domain (CTD) position and 35% of the N-terminal domain (NTD) position. The interaction analysis revealed that DTG bound to DNA, 2MG ions and DDE motif residues for T66A, T97A, Q148H, N155H and R263K comparable to the WT structure. Except for accessory mutant structure E157Q, only one MG contact was made with DTG, while DTG had no MG ion contacts and no DDE motif residue contacts for structure D232N., Conclusions: Our analysis indicated that all RAM's that resulted in a change in the number of interactions with encompassing residues does not affect DTG binding, while accessory mutations E157Q and D232N could affect DTG binding leading to possible DTG resistance. However, further experimental validation is required to validate the in silico findings of our study.

Background: Increasing resistance to anti-tuberculosis drugs has driven the need for developing new drugs. Resources such as the tropical disease research (TDR) target database and AssessDrugTarget can help to prioritize putative drug targets. Hower, these resources do not necessarily map to metabolic pathways and the targets are not involved in dormancy. In this study, we specifically identify drug resistance pathways to allow known drug resistant mutations in one target to be offset by inhibiting another enzyme of the same metabolic pathway. One of the putative targets, Rv1712, was analysed by modelling its three dimensional structure and docking potential inhibitors., Results: We mapped 18 TB drug resistance gene products to 15 metabolic pathways critical for mycobacterial growth and latent TB by screening publicly available microarray data. Nine putative targets, Rv1712, Rv2984, Rv2194, Rv1311, Rv1305, Rv2195, Rv1622c, Rv1456c and Rv2421c, were found to be essential, to lack a close human homolog, and to share >67 % sequence identity and >87 % query coverage with mycobacterial orthologs. A structural model was generated for Rv1712, subjected to molecular dynamic simulation, and identified 10 compounds with affinities better than that for the ligand cytidine-5'-monophosphate (C5P). Each compound formed more interactions with the protein than C5P., Conclusions: We focused on metabolic pathways associated with bacterial drug resistance and proteins unique to pathogenic bacteria to identify novel putative drug targets. The ten compounds identified in this study should be considered for experimental studies to validate their potential as inhibitors of Rv1712.