Browsing by Subject QSAR

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Showing results 1 to 9 of 9
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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 th...

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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...

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  • Authors: Ejeh, Stephen;  Advisor: -;  Participants: Uzairu, Adamu; Shallangwa, Gideon Adamu; Abechi, Stephen E. (2021)

  • The model obtained by in-silico method have the following statistical records, coefficient of determination (r2) of 0.7704, cross-validation (q2LOO = 0.6914); external test set (r2(pred) = 0.7049) and Y-randomization assessment (cR2p = 0.7025). The results from the model were used to identify 12 new potential human HCV NS3/4A protease inhibitors, and it was observed that the identified molecule is well-fixed when docked with the receptor and was found to have the lowest binding energy of − 10.7, compared to approved direct-acting antiviral agents (Telaprevir, Simeprevir, and Voxilaprevir) with − 9.5, − 10.0, − 10.5 binding energy, respectively.

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  • Authors: Mahmud, Aliyu Wappah;  Advisor: -;  Participants: Shallangwa, Gideon Adamu; Uzairu, Adamu (2020)

  • Predictive and robust QSAR model was generated using Genetic Function Algorithm. The model was statistically validated to have internal and external squared correlation coefficient, R2 of 0.982 and 0.735 respectively; predictive squared correlation coefficient, R2pred of 0.599; adjusted squared correlation coefficient, Radj of 0.974; and leave-one-out cross-validation coefficient, Q2cv of 0.966. It was found out that the antiplasmodium activities of 2,5-disubstituted furans relied on the parameters: GATS5c, minsCl RDF130m, RDF75p, and RDF115s descriptors. All the descriptors except minsCl influenced the antiplasmodium activities of the compounds negatively. That is, their increase dec...

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  • Authors: Obadawo, Babatunde Samuel;  Advisor: -;  Participants: Asogwa, Uchenna; Ali, Abdualbaset Ahmed (2022)

  • Coxsackievirus group B (CVBs) are common enteroviruses associated with several diseases from etiologically to inflammatory cardiomyopathies and constitute a severe cause of mortality in newborn resulting in severe meningitis, fulminant infection, myocarditis, and encephalitis. While Berberian (BBR) is an effective antivirus and possesses potentials of suppressing CVB replication, Zeng et al. explored a structural modification of BBR by incorporating a substituted primary amine enhance antiviral potency and safety. Based on data set from Zeng et al., we attempted to propose a QSAR model that can predict the bioactivity of unknown compounds as anti-CVB1.

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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 t...

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  • Authors: Ugbe, Fabian Audu;  Advisor: -;  Participants: Shallangwa, Gideon Adamu; Uzairu, Adamu; Abdulkadir, Ibrahim (2022)

  • Leishmaniasis is a neglected tropical disease caused by a group of protozoan of the genus Leishmania and transmitted to humans majorly through the bite of the female sand fly. It is prevalent in the tropical regions of the world especially in Africa and estimated to affect a population of about 12 million people annually. This theoretical study was therefore conducted in support of the search for more effective drug candidates for the treatment of leishmaniasis. This study focuses on the in silico activity prediction of twenty-eight (28) maleimides, structure-based design, molecular docking study and pharmacokinetics analysis of the newly designed maleimides. All the studied compounds...

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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....