Viral infections are known to hijack the transcription and translation of the host cell. However, the extent to which viral proteins coordinate these perturbations remains unclear. Here we used a model system, the human T-cell leukemia virus type 1 (HTLV-1), and systematically analyzed the transcriptome and interactome of key effectors oncoviral proteins Tax and HBZ. We showed that Tax and HBZ target distinct but also common transcription factors. Unexpectedly, we also uncovered a large set of interactions with RNA-binding proteins, including the U2 auxiliary factor large subunit (U2AF2), a key cellular regulator of pre-mRNA splicing. We discovered that Tax and HBZ perturb the splicing landscape by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia/lymphoma (ATLL) samples from two independent patient cohorts, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinated by Tax and HBZ to reprogram the transcriptome.

Protein–protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

The aim of this study was to purify and characterize α-amylase of Paenibacillus species D9 and cloned α-amylase in Escherichia coli transformants. Optimal growth and production of D9 α-amylase were obtained after the 24-h incubation period, at pH 7, 30 °C and 200 rpm, using starch as the sole carbon source. Sodium nitrate stimulated α-amylase production by 3 folds while urea had an inhibitory effect comparing with yeast extract as the control. Characterization results of the crude and purified enzyme were similar. Purified D9 α-amylase possessed 97% residual activity after incubation at 30 °C for 120 min while 50% at 45 °C and 27% at 60 °C, respectively, under the same condition. The presence of Ca²⁺ ions enhanced the activity, while EDTA and Fe³⁺ had an inhibitory effect. Kinetic parameters were obtained having values of 37.3 mM, 19.8 U/mg and 4.84 s⁻¹ for K_m, V_max and k_cat, respectively. The α-amylase gene (amyS) of Paenibacillus sp. D9 was amplified using polymerase chain reaction (1482 bp), cloned into PSF-OXB20 vector and expressed in E. coli BL21 DE3 (pLysS) after transformation. The α-amylase purified from the transformant using a Hispur Cobalt column possessed 1.4 folds (450.8 U/mg) higher specific activity than the purified α-amylase from the wild type. Cloned α-amylase was more thermostable at 45 °C and at 60 °C, but less pH stable at pH 5 and 6. All other biochemical properties of the native and recombinant α-amylase show no significant differences. In conclusion, α-amylase of Paenibacillus sp. D9 was purified, cloned and characterized. The potential biotechnological application(s) of α-amylase may be explored.

Herein, we report the effect of nine FDA approved protease inhibitor drugs against a new HIV-1 subtype C mutant protease, E35D↑G↑S. The mutant has five mutations, E35D, two insertions, position 36 (G and S), and D60E. Kinetics, inhibition constants, vitality, Gibbs free binding energies are reported. The variant showed a decreased affinity for substrate and low catalytic efficiency compared to the wild type. There was a significant decrease in the binding of seven FDA approved protease inhibitors against the mutant (p < .0001). Amprenavir and ritonavir showed the least decrease, but still significant reduced activity in comparison to the wildtype (4 and 5 folds, respectively, p = .0021 and .003, respectively). Nelfinavir and atazanavir were the worst inhibitors against the variant as seen from the IC₅₀, with values of 1401 ± 3.0 and 685 ± 3.0 nM, respectively. Thermodynamics data showed less favourable Gibbs free binding energies for the protease inhibitors to the mutant.