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Computational modeling, ligand-based drug design, drug-likeness and ADMET properties studies of series of chromen-2-ones analogues as anti-cancer agents

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...

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.

Chemo-informatics activity prediction, ligand based drug design, Molecular docking and pharmacokinetics studies of some series of 4, 6-diaryl-2-pyrimidinamine derivatives as anti-cancer agents

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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