Publications by authors named "Iman Mansi"

Background: Angiotensin-converting enzyme 2 (ACE2) is a pivotal molecular nexus linking novel coronavirus disease to breast cancer. In-silico investigations have repurposed carnosine for both these conditions based on its potential ACE2 inhibitory properties.

Methods: Utilizing an ACE2 inhibitor screening kit, we determined the inhibitory range of carnosine doses.

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Background: Phosphoinositide-Dependent Kinase-1 (PDK1) is a serine/threonine kinase, which belongs to AGC kinase family required by cancer cells.

Methods: Pharmacophoric space of 86 PDK1 inhibitors using six diverse sets of inhibitors was explored to identify high-quality pharmacophores. The best combination of pharmacophoric models and physicochemical descriptors was selected by genetic algorithm-based QSAR analysis that can elucidate the variation of bioactivity within the training inhibitors.

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Background: 3-Phosphoinositide Dependent Protein Kinase-1 (PDK1) is being lately considered as an attractive and forthcoming anticancer target. A Protein Data Bank (PDB) cocrystallized crystal provides not only rigid theoretical data but also a realistic molecular recognition data that can be explored and used to discover new hits.

Objective: This incited us to investigate the co-crystallized ligands' contacts inside the PDK1 binding pocket via a structure-based receptor-ligand pharmacophore generation technique in Discovery Studio 4.

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Targeting tropomycin kinase A (TrkA) by small molecule inhibitors is considered as a promising strategy for treating several human cancers. To achieve this goal, a ligand based QSAR model was applied using the Discovery studio 4.5 (DS 4.

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Rosemary ( L.) is a popular herb in cooking, traditional healing, and aromatherapy. The essential oils of were obtained from plants growing in Victoria (Australia), Alabama (USA), Western Cape (South Africa), Kenya, Nepal, and Yemen.

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The pharmacophoric features of the virtual cocrystallized protein of 178 Hsp90 proteins were obtained from the protein data bank and explored to generate 1260 pharmacophores evaluated using the decoy list composed of 1022 compounds. Accordingly, 51 pharmacophores were selected with high receiver operating characteristic (ROC) value for further processing. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing a self-consistent quantitative structure-activity relationship (QSAR) of optimal predictive potential (R = 0.

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The pharmacophoric features of the virtual co-crystallized protein of 17 Akt1 proteins were downloaded from the protein data bank, and explored to end up with 132 generated pharmacophores that had been evaluated using the decoy list composed of 1724 compounds. The areas under the curve of the Receiver-Operating Characteristic (ROC-AUC) were sorted, and the highest ranked pharmacophore 3MV5_2_01 was selected to be used as a searching tool in the National Cancer Institute (NCI) database. The captured hits were mapped based on successful hypotheses and the best fitted compounds were selected.

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Three derivatives of substituted 1,2,3-thia- or 1,2,3-selenadiazole (4a-c) were prepared and characterized by different chemical techniques. These compounds were evaluated for their antimicrobial and antitumor activities. Compounds 4a (propenoxide derivative), 4b (carbaldehyde derivative), and 4c (benzene derivative) were active against the yeast-like fungi Candida albicans.

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