Integrated Immuno and bioinformatics assisted novel epitope vaccine against HIV infection: a study based on complete genome.

Background: As the HIV-based complication is still going on with the high infection and mortality rate, it requires a novel strategy to combat this infection due to the unavailability of proper therapeutic. Therefore, we utilize integrated immuno and bioinformatics approaches in this study to design a peptide vaccine against HIV infection by targeting its complete genome.

Methods: The complete genome sequence was analyzed, and the potential B and T cells were predicted.

In-silico analysis of deleterious non-synonymous SNPs in the human AVPR1a gene linked to autism.

Single nucleotide polymorphisms are the most prevalent type of DNA variation occurring at a single nucleotide within the genomic sequence. The AVPR1a gene exhibits genetic polymorphism and is linked to neurological and developmental problems, including autism spectrum disorder. Due to the difficulties of studying all non-synonymous single nucleotide polymorphisms (nsSNPs) of the AVPR1a gene in the general population, our goal is to use a computational approach to identify the most detrimental nsSNPs of the AVPR1a gene.

Computational analysis of lupenone derivatives as potential inhibitor of human papillomavirus oncoprotein E6 associated cervical cancer.

Cervical cancer remains a major global health challenge, largely driven by persistent infections with high-risk human papillomavirus (HPV). Although preventive vaccines have reduced cervical cancer incidence in some settings, effective therapeutic strategies for established HPV-associated malignancies remain limited. High-risk HPV types (particularly 16 and 18) utilize their E6 oncoprotein to promote ubiquitin-mediated degradation of the tumor suppressor p53, thereby facilitating uncontrolled cell proliferation and immune evasion.

Identification of promising SARS-CoV-2 main protease inhibitor through molecular docking, dynamics simulation, and ADMET analysis.

The COVID-19 pandemic caused by SARS-CoV-2 continues to pose a major challenge to global health. Targeting the main protease of the virus (Mpro), which is essential for viral replication and transcription, offers a promising approach for therapeutic intervention. In this study, advanced computational techniques such as molecular docking and molecular dynamics simulations were used to screen a series of antiviral compounds for their potential inhibitory effect on the SARS-CoV-2 Mpro.

Identification of AChE targeted therapeutic compounds for Alzheimer's disease: an in-silico study with DFT integration.

Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by cognitive deterioration and changes in behavior. Acetylcholinesterase (AChE), which hydrolyzes acetylcholine, is a key drug target for treating AD. This research aimed to identify new AChE inhibitors using the IMPPAT database.