Exploring 2D and 3D QSARs of benzimidazole derivatives as transient receptor potential melastatin 8 (TRPM8) antagonists using MLR and kNN-MFA methodology

TRPM8 is now best known as a cold-and menthol-activated channel implicated in thermosensation. TRPM8 is specifically expressed in a subset of pain-and temperature-sensing neuron. TRPM8 plays a major role in the sensation of cold and cooling substances. TRPM8 is a potential new target for the treatment of painful conditions. Thus, TRPM8 antagonists represent a new, novel and potentially useful treatment strategy to treat various disease states such as urological disorders, asthma, COPD, prostate and colon cancers, and painful conditions related to cold, such as cold allodynia and cold hyperalgesia. Better tools such as potent and specific TRPM8 antagonists are mandatory as high unmet medical need for such progress. To achieve this objective quantitative structure-activity relationship (QSAR) studies were carried out on a series of 25 benzimidazole-containing TRPM8 antagonists to investigate the structural requirements of their inhibitory activity against cTRPM8. The statistically significant best 2D-QSAR model having correlation coefficient r(2) = 0.88 and cross-validated squared correlation coefficient q(2) = 0.64 with external predictive ability of pred_r(2) = 0.69 was developed by SW-MLR. The physico-chemical descriptors such as polarizabilityAHP, kappa2, XcompDipole, +vePotentialSurfaceArea, XKMostHydrophilic were found to show a significant correlation with biological activity in benzimidazole derivatives. Molecular field analysis was used to construct the best 3D-QSAR model using SW-kNN method, showing good correlative and predictive capabilities in terms of q(2) = 0.81 and pred_r(2) = 0.55. Developed kNN-MFA model highlighted the importance of shape of the molecules, i.e., steric & electrostatic descriptors at the grid points S_774 & E_1024 for TRPM8 receptor binding. These models (2D & 3D) were found to yield reliable clues for further optimization of benzimidazole derivatives in the data set. The information rendered by 2D- and 3D-QSAR models may lead to a better understanding of structural requirements of cTRPM8 antagonists and also can help in the design of novel potent cTRPM8 antagonists. (C) 2012 Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).