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Authors: Abdullahi, Sagiru Hamza; Advisor: -; Participants: Uzairu, Adamu; Shallangwa, Gideon Adamu; Uba, Sani; Umar, Abdullahi Bello (2022) - Four QSAR models were developed from the training set data using genetic function algorithm (GFA) coupled with multi linear regression (MLR), and their expressions are presented below:Model 1
Y = 0.342327907 * apol + 0.002006877 * ATSC8m + 0.021947183 * ATSC7s − 2.110146447 * SM1_Dzm − 0.027702443 * SpAbs_Dzs + 0.122940438 * ZMIC4 − 9.882891756.
Model 2
Y = 0.333966562 * apol + 0.001909583 * ATSC8m + 0.019049122 * ATSC7s − 2.079324191 * SM1_DzZ − 0.027112784 * SpAbs_Dzs + 0.119956742 * ZMIC4 − 9.456381109.
Model 3
Y = 0.342932868 * apol + 0.002004154 * ATSC8m + 0.021734174 * ATSC7s − 2.067273713 * SM1_Dzm − 0.027821824 * SpAD_Dzs + 0.122642435 * ZMIC4 − 9.889860694.
Model 4
Y = 0.334437304 * apol + 0.001906343 * ATSC8m + 0.018877487 * ATSC7s − 2.033875692 * SM1_DzZ − 0...
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Authors: Ibrahim, Muhammad Tukur; Advisor: -; Participants: Tahir, Salisu Muhammad; Umar, Abdullahi Bello; Abdulfatai, Usman (2020) - At 8% glycerol concentration, FP1 has significantly (P > 0.05) the highest percentage motility (73.33%) compared to FPs 2, 3, and 4 (56.68, 50.00, and 23.33% respectively). At 10% glycerol, FP2 had the highest motility (48.33%) and HOST (64.00%). At 15% glycerol, FP4 (fast freezing) had the highest percentage motility (71.67%), viability (76.33%), and HOST (71.67%). At 8%, DMSO concentrations FP4 had the highest significant (P > 0.05) motility, viability, and HOST. Ten percent and 15% DMSO revealed no significant (P > 0.05) difference in most parameters among all the FPS. DMSO performed better than glycerol irrespective of concentrations in all FPS on most parameters evaluated.
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Authors: Ibrahim, Muhammad Tukur; Advisor: -; Participants: Tahir, Salisu Muhammad; Umar, Abdullahi Bello; Abdulfatai, Usman (2020) - Theoretical investigation via QSAR modeling on 30 indole derivatives was performed to build a model which could be used to predict the activity of the indole derivatives. QSAR was carried out using multi-linear regression (MLR) method utilizing genetic function approximation (GFA) to develop the QSAR models. A very high predictive QSAR model was reported based on its statistical fitness with good internal and external validation parameters: R2trng = 0.954942, Qcv2 = 0.925462, R2test = 0.855393, and LOF = 0.042924. Molecular docking on the 30 indole derivatives was also performed to screen and identify the lead compound that would be used as template for designing new indole compounds. The docking investigation reveals that ligand 10 binds very tight in the binding pocket of β-glucur...
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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 the complex crystal structure of the acetylcholine (protein AChBP) (PDB CODE 2zju) in which compound ...
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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.
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Authors: Aminu, Khalifa Sunusi; Advisor: -; Participants: Uzairu, Adamu; Umar, Abdullahi Bello; Ibrahim, Muhammad Tukur (2022) - The experimental activities of the datasets were normalized to pIC50. Also, the predicted pIC50(s) of the compounds was determined (Table 1). The differences between the experimental and predicted activities of the compounds (residual values) were further calculated (Table 1).
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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 bioavailable. Also, the designed compounds were found to have good pharmacokinetics absorption, distribution, ...
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Authors: Abdullahi, Sagiru Hamza; Advisor: -; Participants: Uzairu, Adamu; Ibrahim, Muhammad Tukur; Umar, Abdullahi Bello (2021) - The first model was selected as the best because of its fitness statistically with the following assessment parameters: R2train = 0.832, R2adj = 0.79, R2ext = 0.62, Q2 = 0.68, and LOF = 0.14509. Compound 11 was selected as a template to design new powerful compounds based on its low residual and high pIC50 values. Majority of the designed compounds has predicted pIC50 greater than that of the lead compound and the standard drug (Sunitinib) used as reference. Molecular docking studies results of the designed compounds revealed that they have higher docking scores than the template and the reference drug (Sunitinib) and are found to bind to the VEGFR-2 receptor in a similar manner to the reference drug. Pharmacokinetics and ADMET properties revealed that the designed compounds passed ...
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