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Around 50 % of the worldwide population is affected by dandruff, which is triggered by a variety of factors. The yeast Malassezia globosa has been labeled as the most probable causative agent for the onset of dandruff. The β-carbonic anhydrase (CA) of MgCA was recently validated as an anti-dandruff target, with its inhibition being responsible for in vivo growth defects in the fungus. As classical CA inhibitors of the sulfonamide type give rise to permeability problems through biological membranes, finding non-sulfonamide alternatives for MgCA inhibition is of considerable interest in the cosmetic field. We recently screened a large library of human (h) CA inhibitors for MgCA inhibition, including different chemotypes, such as monothiocarbamates, dithiocarbamates, phenols, and benzoxaboroles. Herein, we expanded the research toward new MgCA inhibitors by considering a set of natural polyphenols (including flavones, flavonols, flavanones, flavanols, isoflavones, and depsides) that exhibited MgCA inhibitory activity in the micromolar range, as well as selectivity for the fungal isozyme over off-target human isoforms. The binding mode of representative derivatives within the MgCA catalytic cleft was investigated by docking studies using a homology-built model.

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A 3D-QSAR modeling was performed on a series of diarylpyrazole-benzenesulfonamide derivatives acting as inhibitors of the metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1). The compounds were collected from two datasets with the same scaffold, and utilized as a template for a new pharmacophore model to screen the ZINC database of commercially available derivatives. The datasets were divided into training, test, and validation sets. As the first step, comparative molecular field analysis (CoMFA), CoMFA region focusing and comparative molecular similarity indices analysis (CoMSIA) in parallel with docking studies were applied to a set of 41 human (h) CA II inhibitors. The validity and the prediction capacity of the resulting models were evaluated by leave-one-out (LOO) cross-validation approach. The reliability of the model for the prediction of possibly new CA inhibitors was also tested.

Isoform diversity, critical physiological roles and involvement in major diseases/disorders such as glaucoma, epilepsy, Alzheimer's disease, obesity, and cancers have made carbonic anhydrase (CA), one of the most interesting case studies in the field of computer aided drug design. Since applying non-selective inhibitors can result in major side effects, there have been considerable efforts so far to achieve selective inhibitors for different isoforms of CA. Using proteochemometrics approach, the chemical interaction space governed by a group of 4-amino-substituted benzenesulfonamides and human CAs has been explored in the present study. Several validation methods have been utilized to assess the validity, robustness and predictivity power of the proposed proteochemometric model. Our model has offered major structural information that can be applied to design new selective inhibitors for distinct isoforms of CA. To prove the applicability of the proposed model, new compounds have been designed based on the offered discriminative structural features.