Experimental and QSAR Studies on Antimicrobial Activity of Benzimidazole Derivatives

Abstract

Twenty eight analogues of benzimidazoles had been synthesized and tested for their antimicrobial activity against four bacteria (Staphylococcus auerus, Escherichia coli, Bacillus pumilus and Proteus vulgaris) and two fungi (Aspergillus flavus and Aspergilus niger). Compounds with R as C 6 H 4 NO 2 and R as SO 2 C 6 H 4 -CH 3 (p), with R as C 6 H 4 OCH 3 and R as SO 2 C 6 H 4 -CH 3 (p), and with R as CH 2 C 6 H 5 and R as CH 2 (CH 2 ) 9 Cl exhibited comparable or higher antibacterial activity than Ciprofloxacin against S. auerus and E. coli and, higher activity than Nystatin against A. flavus. Several other compounds showed better activity than the standard antibiotic for E. coli. Compounds with R as CCl 3 and R as SO 2 C 6 H 4 -CH 3 (p) or COC 6 H 5 exhibited the lowest activity against all the organisms. Addition of methylene groups in the R position increased activity. Many of the compounds showed better activity than Ciprofloxacin for one or more organisms. Compound with R as CH 2 OC 6 H 5 and R as CH 2 (CH 2 ) 9 Cl exhibited higher activity against both the fungii than the control Nystatin. Quantitative structure activity relationships (QSARs) developed were good for all the organisms (R 2 ‫56.0؍‬ to 0.88; R 2 adj ‫36.0؍‬ to 0.86) and the predictive capability of the developed models was also reasonable (q 2 ‫25.0؍‬ to 0.83). The models had two to three independent variables. The data for the models which had three independent variables were divided into training and test/validation sets. The former set was used to develop the QSAR and these developed models were used to predict the activity of the test set data. In all the three cases the predictive capability of the models was good. The molecular descriptors identified were predominantly log P, electronic parameters, molecular size, shape and area. A positive correlation existed between the antibacterial activity and the first principal component.

Synthesis, QSAR and docking studies of 5HT2A receptor antagonising thiazolo[3,2-a]pyrimidines as antipsychotic agents

“…As indicated, both QSAR models were found to be statistically significant and predictive in terms of r 2 , q 2 , F and pred_r 2 values (19)(20)(21)(22)(23).…”

2-Methyl-5-nitro-1H-benzimidazole monohydrate

“…For general background to and the potential biological activity of benzimidazole derivatives, see: Puratchikody et al (2008); Tonelli et al (2010); Shingalapur et al (2010); Refaat (2010); Lazer et al (1987). For the preparation of the title compound, see: Umare et al (2008); Singh & Pathak (2008).…”

“…Data collection: APEX2 (Bruker, 2009); cell refinement: SAINT (Bruker, 2009); data reduction: SAINT; program(s) used to solve structure: SHELXTL (Sheldrick, 2008); program(s) used to refine structure: SHELXTL; molecular graphics: SHELXTL; software used to prepare material for publication: SHELXTL and PLATON (Spek, 2009). Tonelli, M., Simone, M., Tasso, B., Novelli, F., Boido, V., Sparatore, F., Paglietti, G., Pricl, S., Giliberti, G., Blois, S., Ibba, C., Sanna, G., Loddo, R. & La Colla, P. (2010) (Puratchikody et al, 2008), antiviral (Tonelli et al, 2010, anticancer (Refaat, 2010), anti-inflammatory (Lazer et al, 1987) and anti-diabetic (Shingalapur et al, 2010) agents.…”

Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans

“…1 These variables have been correlated in many QSAR studies applying various chemometric regression methods, as linear regression (LR), multiple linear regression (MLR), polynomial regression (PR), artificial neural networks (ANN), partial least squares regression (PLS), principal component regression (PCR), etc. [2][3][4][5][6][7][8] Any high-quality model obtained by aforementioned chemometric techniques may be used by the chemist in order to facilitate the synthesis of more effective drugs. A high-quality QSAR model must be based on reasonable number of tested compounds, characterized by good values of statistical parameters, defined for particular application domain and suitably validated by internal and external validation approaches.…”