Quantitative Structure Activity Relationship (QSAR) are mathematical models that seek to predict complicated physicochemical /biological properties of chemicals from their simpler experimental or calculated properties .QSAR enables the investigator to establishes a reliable quantitative relationship between structure and activity which will be used to derive an insilico model to predict the activity of novel molecules prior to their synthesis. The past few decades have witnessed much advances in the development of computational models for the prediction of a wide span of biological and chemical activities that are beneficial for screening promising compounds with robust properties. This review covers the concept, history of QSAR and also the components involved in the development of QSAR models.

was evaluated. Bacterial species were isolated by settling plate method, using Nutrient and MacConkey agar as the isolating medium. The isolates were fully characterized by standard methods. Isolated bacteria includes; Staphylococcus aureus, Staphylococcus epidermidis, Bacillus megaterium, Bacillus cereus, Streptococcus sp and Bacillus subtilis. The in house disinfectants (Povidone iodine and Izal) used in the operating theatres was obtained and evaluated using Agar ditch diffusion method. Povidone iodine obtained from the operating theatre showed no zones of inhibition in all the isolates tested, Izal solution obtained from the theatres showed appreciable zones of inhibition. Povidone iodine purchased from a pharmacy store in town however produced zones of inhibitions ranging from 7.75 mm to 18.00 mm. Killing rate for the most resistant isolates showed that B. megaterium, S. aureus and B. cereus required 25 to 30 minutes of exposure time for 8% Izal dilution to bring about the death of all resistant isolates. It was concluded that disinfection remain one of the most effective ways of reducing nosocomial pathogens in hospital environment as demonstrated in the results of this research work. However, from time to time potency of the in house used disinfectant must be evaluated in order to keep pace with degradation of disinfectant which normally occurs with time.

This investigation is intended for Chemical Oxygen Demand (COD), Total Dissolved Solid (TDS), Biological Oxygen Demand (BOD), Conductivity, Dissolved oxygen, Absorbance, PH and turbidity reduction from textile industrial produce effluents that are highly complex and characterized. In this study coagulant using Moringa Oliefera seed was used to reduce the suspended and colloidal materials responsible for turbidity of the waste water. The seed powder was used as a natural coagulant to reduce turbidity, the test were carried out using textile effluent with conventional test apparatus. Various result were obtained by increasing dosage of Moringa Oleifera seed powder from 4g to 24g optimum dosage for reduction of COD, BOD, TDS, Turbidity, Conductivity, Absorbance and D.O was determined. It was observed that the highest dose which is 24g has a greater efficiency in reduction of all parameters tested with Ph of 6.48, COD 46mg/L, BOD 12mg/L, and Conductivity 360MSCm-1, TDS 212mg/L, Turbidity 8NTU, DO 4.7 and absorbance of 0.65. Moringa Oleifera seed showed potential in industrial textile effluent treatments among others.

No abstract

Quantitative Structure Activity Relationship (QSAR) study was carried out on Copper Schiff base complexes. Multiple Linear Regression analysis and genetic function algorithms was employed to derive QSAR model for better activity. The derived QSAR model having Squared Correlation Coefficient R 2 = 0.8345, Cross Validation Squared Correlation Coefficient Q 2 = 0.6681 and predicted R squared (R 2 pred)= 0.5980. The robustness of the derived model was confirmed by internal and external cross validation techniques. The QSAR model indicate that the descriptors (MATS4p) Moron autocorrelation of lag 4 weighed by polarizability, (RCI) Ring Complexity index, (G2m) 2 nd component symmetry directional WHIM index/weighted by mass, BI0 [N-O] Presence/absence of N-O at topological distance 10 and (nF) Number of Fluorine atoms plays an important role in predicting the activities against anti-candida albican. The result obtained in this study was used in designing more potent Copper Complexes as anti-candida albican agents.