Prediction of Tyrosinase Inhibition Activity Using Atom‐Based Bilinear Indices

Abstract

A set of novel atom-based molecular fingerprints is proposed based on a bilinear map similar to that defined in linear algebra. These molecular descriptors (MDs) are proposed as a new means of molecular parametrization easily calculated from 2D molecular information. The nonstochastic and stochastic molecular indices match molecular structure provided by molecular topology by using the kth nonstochastic and stochastic graph-theoretical electronic-density matrices, M(k) and S(k), respectively. Thus, the kth nonstochastic and stochastic bilinear indices are calculated using M(k) and S(k) as matrix operators of bilinear transformations. Chemical information is coded by using different pair combinations of atomic weightings (mass, polarizability, vdW volume, and electronegativity). The results of QSAR studies of tyrosinase inhibitors using the new MDs and linear discriminant analysis (LDA) demonstrate the ability of the bilinear indices in testing biological properties. A database of 246 structurally diverse tyrosinase inhibitors was assembled. An inactive set of 412 drugs with other clinical uses was used; both active and inactive sets were processed by hierarchical and partitional cluster analyses to design training and predicting sets. Twelve LDA-based QSAR models were obtained, the first six using the nonstochastic total and local bilinear indices and the last six with the stochastic MDs. The discriminant models were applied; globally good classifications of 99.58 and 89.96 % were observed for the best nonstochastic and stochastic bilinear indices models in the training set along with high Matthews correlation coefficients (C) of 0.99 and 0.79, respectively, in the learning set. External prediction sets used to validate the models obtained were correctly classified, with accuracies of 100 and 87.78 %, respectively, yielding C values of 1.00 and 0.73. This subset contains 180 active and inactive compounds not considered to fit the models. A simulated virtual screen demonstrated this approach in searching tyrosinase inhibitors from compounds never considered in either training or predicting series. These fitted models permitted the selection of new cycloartane compounds isolated from herbal plants as new tyrosinase inhibitors. A good correspondence between theoretical and experimental inhibitory effects on tyrosinase was observed; compound CA6 (IC(50)=1.32 microM) showed higher activity than the reference compounds kojic acid (IC(50)=16.67 microM) and L-mimosine (IC(50)=3.68 microM).

Variations in IC50 Values with Purity of Mushroom Tyrosinase

“…Crude extracts of MT appeared to contain latent tyrosinase and assays were conducted in the presence of 0.1% SDS to account for latent and active enzyme present (data not shown). We arranged these inhibitors into groups based on IC 50 value similarities between the different tyrosinase samples and to IC 50 values for commercial and/or purified MT reported in the literature (Table 1 and references therein [18–31]).…”

“…Many investigators use kojic acid as a reference inhibitor, and it is surprising that IC 50 values for kojic acid vary over such a wide range (Table 1, [18]). Our IC 50 values are within the lower end of these ranges.…”

Novel Tyrosinase Inhibitors From Natural Resources - Their Computational Studies

“…The derived models were used in the discovery of new inhibitors, such as: cycloartane [103,104], diterpenoidal alkaloids [105], tetraketones [106], and so on. The derived models were used in the discovery of new inhibitors, such as: cycloartane [103,104], diterpenoidal alkaloids [105], tetraketones [106], and so on.…”

Atom-based stochastic and non-stochastic 3D-chiral bilinear indices and their applications to central chirality codification

“…The atom-based bilinear indices were defined in analogy to the bilinear mathematical maps. These new MDs have been successfully employed in the prediction of the chem-physical properties of organic compounds [48], and in the fast-track experimental discovery of novel tyrosinase inhibitors [49] as well as in the rational discovery of new trichomonacidal drugs.…”