Browsing by Subject QSAR

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Showing results 8 to 9 of 9
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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....