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Browsing by Author Uba, Sani

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Showing results 3 to 7 of 7

Design, pharmacokinetic profiling, and assessment of kinetic and thermodynamic stability of novel anti-Salmonella typhi imidazole analogues

Authors: Ameji, John Philip; Advisor: -; Participants: Uzairu, Adamu; Shallangwa, Gideon Adamu; Uba, Sani (2023)

Typhoid fever, a disease caused by a gram negative bacterial species known as Salmonella typhi, constitutes a significant cause of morbidity and mortality, especially in developing nations of the world. Antibiotic therapy is the major treatment option currently but the rising incidences of resistance to existing antibiotics has necessitated the search for newer ones. The aim of this study is to apply in silico techniques to design highly potent novel imidazole-based drug candidates that strongly antagonize a cell invasion protein (SipA) of Salmonella typhi.

Docking-based strategy to design novel flavone-based arylamides as potent V600E-BRAF inhibitors with prediction of their drug-likeness and ADMET properties

Authors: Umar, Abdullahi Bello; Advisor: -; Participants: Uzairu, Adamu; Shallangwa, Gideon Adamu; Uba, Sani (2020)

The docking result demonstrates that compound 28 best inhibits V600E-BRAF when compared with other compounds within the dataset. This compound was used as a template in designing novel anticancer compounds by attaching some favorable substituents. The docking results of the designed compounds revealed a good MolDock score (< − 90), which showed that all the compounds can efficiently bind with the active sites of the target, out of which two analogous (N1 and N3) were considered optimal that outperformed vemurafenib, the FDA-approved V600E-BRAF inhibitor. Furthermore, these compounds passed the drug-likeness criteria (Lipinski’s rule) successfully and were found to be orally bioavailab...

In-silico activity prediction, structure-based drug design, molecular docking and pharmacokinetic studies of selected quinazoline derivatives for their antiproliferative activity against triple negative breast cancer (MDA-MB231) cell line

Authors: Abdullahi, Sagiru Hamza; Advisor: -; Participants: Uzairu, Adamu; Shallangwa, Gideon Adamu; Uba, Sani; Umar, Abdullahi Bello (2022)

In this research work Genetic function algorithm was employed to generate the QSAR models due to its ability to produce a vast population of model instead of just a single model. Four models were generated from the model building set and the first one was chosen because of its statistical significance.

QSAR, molecular docking studies, ligand-based design and pharmacokinetic analysis on Maternal Embryonic Leucine Zipper Kinase (MELK) inhibitors as potential anti-triple-negative breast cancer (MDA-MB-231 cell line) drug compounds

Authors: Lawal, Hadiza Abdulrahman; Advisor: -; Participants: Uzairu, Adamu; Uba, Sani (2021)

The QSAR model of the derivatives was highly robust as it also conforms to the least minimum requirement for QSAR model from the statistical assessments of (R2) = 0.6715, (R2adj) = 0.61920, (Q2) = 0.5460 and (R2pred) of 0.5304, and the model parameters (AATS6i and VR1_Dze) were used in designing new derivative compounds with higher potency. The molecular docking studies between the derivative compounds and Maternal Embryonic Leucine Zipper Kinase (MELK) protein target revealed that ligand 2, 9 and 17 had the highest binding affinities of − 9.3, − 9.3 and − 8.9 kcal/mol which was found to be higher than the standard drug adriamycin with − 7.8 kcal/mol. The pharmacokinetics analysis car...

QSAR, molecular docking, and design of novel 4-(N,N-diarylmethyl amines) Furan-2(5H)-one derivatives as insecticides against Aphis craccivora

Authors: Isyaku, Yusuf; Advisor: -; Participants: Uzairu, Adamu; Uba, Sani; Ibrahim, Muhammad Tukur; Umar, Abdullahi Bello (2020)

A computational study was carried out on a series of twenty compounds of novel 4-(N,N-diarylmethylamines) furan-2(5H)-one derivatives against Aphis craccivora insect. Optimization of the compounds was performed with the aid of Spartan 14 software using DFT/B3LYP/6-31G** quantum mechanical method. Using PaDel descriptor software to calculate the descriptors, Generic Function Approximation (GFA) was employed to generate the model. Model 1 found to be the optimal out of four models generated which has the following statistical parameters; R2 = 0.871489, R2adj = 0.83644, cross-validated R2 = 0.790821, and external R2 = 0.550768. Molecular docking study occurred between the compounds and t...