Two dimensional quantitative structure activity relationship models for 5alpha-reductase type 2 inhibitors

2015 ◽  
Vol 45 (3) ◽  
pp. 293-299
Author(s):  
Urvashi Balekundri ◽  
Shrishailnath S. Sajjan ◽  
Shivakumar B. Madagi
Keyword(s):  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Two Dimensional ◽  
Quantitative Structure ◽  
Structure Activity

STRUCTURAL FEATURE STUDY OF FUROXAN DERIVATIVES AS POTENT ANTI-TRYPANOSOMATID AGENTS: QSAR APPROACH

INDIAN DRUGS ◽  
2016 ◽  
Vol 53 (09) ◽  
pp. 12-21
Author(s):  
M. C. Sharma ◽  
Keyword(s):  
Cross Validation ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Two Dimensional ◽  
Quantitative Structure ◽  
Property A ◽  
Qsar Studies ◽  
Structure Activity

Two-dimensional quantitative structure–activity relationship (QSAR) studies of anti-trypanosomatid, furoxan alkylnitrate derivatives have been carried out. This study aims at establishing a quantitative structure activity relationship between furoxan alkylnitrate molecule and their anti-trypanosomatid property. A statistically best QSAR model was obtained with a correlation coefficient r2 of 0.8559, cross validation coefficient, q2 of 0.8072 and pred_r2 value of 0.8217. Various 2D descriptors were calculated and used in the present analysis. The descriptors SdssS (sulfone) count and SdsNE-index suggested that sulphone and NO2 groups at the R1 and R2 positions of furoxan moiety will increases anti-trypanosomatid activity. It will be useful to build a QSAR model to correlate the properties of new untested furoxan derivatives with their anti-trypanosomatid activity.

scholarly journals Predictive Quantitative Structure–Activity Relationship Modeling of the Antifungal and Antibiotic Properties of Triazolothiadiazine Compounds

2020 ◽  
Vol 4 (1) ◽  
pp. 2
Author(s):  
Michael Appell ◽  
David L. Compton ◽  
Kervin O. Evans
Keyword(s):  
Density Functional Theory ◽  
Predictive Models ◽  
Density Functional ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Two Dimensional ◽  
Quantitative Structure ◽  
Functional Theory ◽  
Structure Activity

Predictive models were developed using two-dimensional quantitative structure activity relationship (QSAR) methods coupled with B3LYP/6-311+G** density functional theory modeling that describe the antimicrobial properties of twenty-four triazolothiadiazine compounds against Aspergillus niger, Aspergillus flavus and Penicillium sp., as well as the bacteria Staphylococcus aureus, Bacillus subtilis, Escherichia coli, and Pseudomonas aeruginosa. B3LYP/6-311+G** density functional theory calculations indicated the triazolothiadiazine derivatives possess only modest variation between the frontier orbital properties. Genetic function approximation (GFA) analysis identified the topological and density functional theory derived descriptors for antimicrobial models using a population of 200 models with one to three descriptors that were crossed for 10,000 generations. Two or three descriptor models provided validated predictive models for antifungal and antibiotic properties with R2 values between 0.725 and 0.768 and no outliers. The best models to describe antimicrobial activities include descriptors related to connectivity, electronegativity, polarizability, and van der Waals properties. The reported method provided robust two-dimensional QSAR models with topological and density functional theory descriptors that explain a variety of antifungal and antibiotic activities for structurally related heterocyclic compounds.

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