Browsing by Author "Kamal, Mohammad A"

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Application of Artificial Intelligence in Drug Discovery
(Daffodil International University, 21-04-12) Chopra, Hitesh; Baig, Atif A; Gautam, Rupesh K; Kamal, Mohammad A
Due to the heap of data sets available for drug discovery, modern drug discovery has taken the shape of big data. Usage of Artificial intelligence (AI) can help to modify drug discovery based on big data to precised, knowledgeable data. The pharmaceutical companies have already geared their departments for this and started a race to search for new novel drugs. The AI helps to predict the molecular structure of the compound and its in-vivo vs. in-vitro characteristics without hampering life, thus saving time and economic loss. Clinical studies, electronic records, and images act as a helping hand for the development. The data mining and curation techniques help explore the data with a single click. AI in big data analysis has paved the red carpet for future rational drug development and optimization. This review's objective is to familiarise readers with various advances in the AI field concerning software, firms, and other tools working in easing out the labor of the drug discovery journey.
Molecular Interaction of Cryptophycin 52 With Caspase 8 for the Management of Lung Cancer During Coronavirus Outbreak
(Scopus, 22-06-30) Bajrai, Leena Hussein; Sohrab, Sayed Sartaj; Khalid, Mohammad; Kamal, Mohammad A; Azhar, Esam Ibraheem
It has been seen that, during COVID-19 outbreak lung cancer (LC) patients are noted as a high-risk population which make a more challenging to treatment of the LC patients. The active form of caspase-8 is involved in lung carcinogenesis in both humans and mice. In this study, the virtual screening was performed among 200 compounds retrieved from several resources for the searching of potent lead against Caspase 8 (Casp8). Cryptophycin 52 was found to have a strong inhibiting efficacy based on the free energy of binding with the active site of Casp8. The lowest binding energy was found to be -8.05 kcal/mole and was further analyzed for molecular dynamic simulation. Casp8 enzyme was determined to interact with cryptophycin 52 through twelve amino acid residues, specifically ARG260, SER316, GLY318, ASP319, THR337, VAL354, PHE355, PHE356, ILE357, GLN358, ALA359 and CYS360 along with six hydrogen bond particular, ILE357:N-UNK1: O7, UNK1: O14-PHE355:O, UNK1: C25-PHE355:O, UNK1: C35-THR337:O, UNK1: H65-HE355:O and UNK1: C25-PHE356. In addition, MD simulations for 50ns were performed for optimization, flexibility estimation and assessment of Casp8-cryptophycin 52 complex stability. This complex was seen as reasonably stable according to the RMSD, RMSF, and radius of gyration graph. Results obtained indicate cryptophycin 52 may be a lead compound with significant anti-cancer ability against Casp8. Further experimental work, however, is expected to support the compound's anti-cancer viewpoint.
Proteomic Signature and mRNA Expression in Hippocampus of SAMP8 and SAMR1 Mice during Aging
(Scopus, 22-12-01) Reale, Marcella; Costantini, Erica; Aielli, Lisa; Giuseppe, Fabrizio Di; Angelucci, Stefania; Kamal, Mohammad A; Greig, Nigel H
Aging is a complex process often accompanied by cognitive decline that represents a risk factor for many neurodegenerative disorders including Alzheimer's and Parkinson's disease. The molecular mechanisms involved in age-related cognitive decline are not yet fully understood, although increased neuroinflammation is considered to play a significant role. In this study, we characterized a proteomic view of the hippocampus of the senescence-accelerated mouse prone-8 (SAMP8), a model of enhanced senescence, in comparison with the senescence-accelerated-resistant mouse (SAMR1), a model of normal aging. We additionally investigated inflammatory cytokines and cholinergic components gene expression during aging in the mouse brain tissues. Proteomic data defined the expression of key proteins involved in metabolic and cellular processes in neuronal and glial cells of the hippocampus. Gene Ontology revealed that most of the differentially expressed proteins are involved in the cytoskeleton and cell motility regulation. Molecular analysis results showed that both inflammatory cytokines and cholinergic components are differentially expressed during aging, with a downward trend of cholinergic receptors and esterase enzymes expression, in contrast to an upward trend of inflammatory cytokines in the hippocampus of SAMP8. Together, our results support the important role of the cholinergic and cytokine systems in the aging of the murine brain.
The Role of Non-coding RNAs in Alzheimer’s Disease: Pathogenesis, Novel Biomarkers, and Potential Therapeutic Targets
(Bentham Science Publishers Ltd., 2023-06-13) Saleh, Othman; Albakri, Khaled; Altiti, Abdalrahmn; Abutair, Iser; Shalan, Suhaib; Mohd, Omar Bassam; Negida, Ahmed; Mushtaq, Gohar; Kamal, Mohammad A
Long non-coding RNAs (IncRNAs) are regulatory RNA transcripts that have recently been associated with the onset of many neurodegenerative illnesses, including Alzheimer's disease (AD). Several IncRNAs have been found to be associated with AD pathophysiology, each with a distinct mechanism. In this review, we focused on the role of IncRNAs in the pathogenesis of AD and their potential as novel biomarkers and therapeutic targets. Searching for relevant articles was done using the PubMed and Cochrane library databases. Studies had to be published in full text in English in order to be considered. Some IncRNAs were found to be upregulated, while others were downregulated. Dysregulation of IncRNAs expression may contribute to AD pathogenesis. Their effects manifest as the synthesis of beta-amyloid (Aβ) plaques increases, thereby altering neuronal plasticity, inducing inflammation, and promoting apoptosis. Despite the need for more investigations, IncRNAs could potentially increase the sensitivity of early detection of AD. Until now, there has been no effective treatment for AD. Hence, InRNAs are promising molecules and may serve as potential therapeutic targets. Although several dysregulated AD-associated lncRNAs have been discovered, the functional characterization of most lncRNAs is still lacking.