Sani Uba

Quantitative structure-activity relationship and molecular docking studies of a series of quinazolinonyl analogues as inhibitors of gamma amino butyric acid aminotransferase.

Graphical abstract

QSAR Modeling and Molecular Docking Analysis of Some Active Compounds against Mycobacterium tuberculosis Receptor (Mtb CYP121)

A quantitative structure-activity relationship (QSAR) study was performed to develop a model that relates the structures of 50 compounds to their activities against M. tuberculosis. The compounds were optimized by employing density functional theory (DFT) with B3LYP/6-31G⁎. The Genetic Function Algorithm (GFA) was used to select the descriptors and to generate the correlation model that relates the structural features of the compounds to their biological activities. The optimum model has squared correlation coefficient (R2) of 0.9202, adjusted squared correlation coefficient (Radj) of 0.91012, and leave-one-out (LOO) cross-validation coefficient (Qcv2) value of 0.8954. The external validation test used for confirming the predictive power of the built model has R2pred value of 0.8842. These parameters confirm the stability and robustness of the model. Docking analysis showed the best compound with high docking affinity of −14.6 kcal/mol which formed hydrophobic interaction and hydrogen bond with amino acid residues of M. tuberculosis cytochromes (Mtb CYP121). QSAR and molecular docking studies provide valuable approach for pharmaceutical and medicinal chemists to design and synthesize new anti-Mycobacterium tuberculosis compounds.

Distribution Pattern of Metals in Atmospheric Settling Dust along Roads in Kano Metropolis, Nigeria

The sequential extraction of Cd, Cr, Ni, Pb, Cu, and Zn in atmospheric dust particles collected along ten high traffic roads in Kano metropolis was carried out. Analyses of metals in the extracts were done using flame atomic absorption spectrometry (FAAS). The samples analyzed for metals indicated high levels of Cd, Cr, Ni, Pb, Cu, and Zn in the atmospheric dust samples. The sequential extractions that showed significant amount of Cd were associated with and Fe-MnO fractions especially during the dry seasons. For Cr and Ni, their occlusion in crystal lattice of the soil fraction exhibited the highest percentage. Pb in the particulate dust samples is significantly associated with the carbonate bound fraction with range of 8.81–64.69% across the season. The behaviour of Cu is quite different from other metals in that percentage fractions are higher in the organic bound. As for Zn, significant amounts were associated with the residue fractions ranging from 0.96 to 87.50% across the seasons. This study revealed contamination of the particulate dust with Cd and Pb; this implies health risks to human, living or carrying out daily activities along the corridors of these roads.

Effect of Acetylation on Stability to Retrogradation of Starch Extracted from Wild Polynesian Arrowroot (Tacca leontopetaloides (L.) Kuntze) for Utilization as Adhesive on Paper

Starch was isolated from T. leontopetaloides tubers, chemically modified by acetylation with varying amounts of acetic anhydride. Monolayer of the ten acetylated and control starch powders was exposed on roof top for five weeks and pastes of both exposed and unexposed (control) samples were prepared with distilled water (1 : 3 w/w). The effects of acetylation, degree of substitution (DS), and exposure to sunlight were investigated to evaluate the retrogradation tendency of the adhesive pastes from changes in syneresis, tack strength, optical clarity, viscosity, gelation time, and drying time. The results obtained showed that all the adhesive properties studied were affected by both DS and exposure to sunlight. While tack strength, viscosity, and drying time were found to increase with increase in DS, syneresis, optical clarity, and gelation time were found to decrease with increase in DS. Increase in tack strength and reduction in syneresis imply that the acetylation treatment has made T. leontopetaloides starch more suitable for use in remoistenable adhesive applications. The reduction in syneresis, optical clarity, and gelation time with increase in DS was attributed to the strengthening of the bonds between the amylose and amylopectin molecules, preventing water leaching out of the starch granules.

Molecular docking and QSAR analysis of a few Gama amino butyric acid aminotransferase inhibitors

Abstract Molecular docking and quantitative structure–activity relationship (QSAR) studies were carried out on 37 anticonvulsant compounds to develop a robust model for the prediction of anticonvulsant activities against Gama amino butyric acid aminotransferase (GABAAT) and to determine the dominant structural amino acid residues responsible for the binding affinity of the ligand-GABAAT complex. AutoDock Vina of PyRx virtual screening software was used to perform the molecular docking while Genetic function algorithm (GFA) was used to select the descriptors and to generate the correlation models that relate the structural features to the biological activities. The best binding affinity was found to be −11.9 Kcal/mol (compound 5a) while best QSAR model (model 1) was obtained with R2 of 0.970192, an R2adj value of 0.963095, Q2LOO value of 0.947995 and R2pred of 0.813. These confirms the stability, reliability, robustness and predictability of the model. Our research has shown that the binding affinity generated was found to be better than the one reported by another researcher. And the high correlation coefficient, (R2) shows that the model was reliable, robust and predictable. Our QSAR model and molecular docking results corroborate with each other (most especially in the area of binding affinity and atomic electronegativity of the inhibitors) and propose the directions for the design of new inhibitors with better activity against an enzyme that is responsible for epilepsy (GABAAT).

Quantitative structure activity relationship study of anticonvulsant activity of α_substituted acetamido-N-benzylacetamide derivatives

Abstract To develop the quantitative structure–activity relationship (QSAR) for predicting the anticonvulsant activity of α_substituted acetamido-N-benzylacetamide derivatives. Density Functional Theory (B3LYP/6-31G*) quantum chemical calculation method was used to find the optimized geometry of the studied molecules. Nine types of molecular descriptors were used to derive a quantitative relation between anticonvulsant activity and structural properties. The relevant molecular descriptors were selected by genetic algorithm approximation. The high value of the correlation coefficient, (R2) of 0.98, indicates that the model was satisfactory. The proposed model has good stability, robustness, and predictability on verifying with internal and external validation.