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An insilico study was carried out on a series of thirty five (35) sulfonyl-containing compounds for their antifungal activities against Botrytis Cinerea fungi by the employment of Quantitative Structure-Activity Relationship (QSAR) techniques. Spartan 14 software was used to generate the molecular structure of the dataset which were then optimized using Density Function Techniques (DFT/B3LYP/6-31G*) quantum method found available in the software. PaDEL-Descriptor software was used to calculate the molecular descriptors. The calculated descriptors were then subjected to data-Pretreatment and later divided into training and test sets. The training set was used to generate the model while the test set was to validate the built model. The model was developed using Genetic Function Algorithm (GFA). Out of the four models developed, model 1 was selected as the optimum model with good statistical parameters; R2 = 0.954, R2adj =0.941, cross validation R2/ Q2cv = 0.888 and R2pred = 0.839. The model proposed was found to be stable, robust and showed a good internal and external validation. Other statistical analysis such as mean effect, variance inflation factor (VIF), Williams plot among others were also carried out for the applicability domain of the model.

QSAR STUDY OF 2-SUBSTITUTED PHENYL-2-OXO-, 2-HYDROXYL- AND 2-ACYLLOXYETHYLSULFONAMIDES AS FUNGICIDES