One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.

In this paper we describe the application in QSPR/QSAR studies of a newgroup of molecular descriptors: atom, atom-type and total linear indices of the molecularpseudograph’s atom adjacency matrix. These novel molecular descriptors were used forthe prediction of boiling point and partition coefficient (log P), specific rate constant (logk), and antibacterial activity of 28 alkyl-alcohols and 34 derivatives of 2-furylethylenes,respectively. For this purpose two quantitative models were obtained to describe thealkyl-alcohols’ boiling points. The first one includes only two total linear indices andshowed a good behavior from a statistical point of view (R² = 0.984, s = 3.78, F = 748.57,q² = 0.981, and s_cv = 3.91). The second one includes four variables [3 global and 1 local(heteroatom) linear indices] and it showed an improvement in the description of physicalproperty (R² = 0.9934, s = 2.48, F = 871.96, q² = 0.990, and s_cv = 2.79). Later, linearmultiple regression analysis was also used to describe log P and log k of the 2-furyl-ethylenes derivatives. These models were statistically significant [(R² = 0.984, s = 0.143, and F = 113.38) and (R² = 0.973, s = 0.26 and F = 161.22), respectively] and showed very good stability to data variation in leave-one-out (LOO) cross-validation experiment [(q² = 0.93.8 and scv = 0.178) and (q² = 0.948 and s_cv = 0.33), respectively]. Finally, a linear discriminant model for classifying antibacterial activity of these compounds was also achieved with the use of the atom and atom-type linear indices. The global percent of good classification in training and external test set obtained was of 94.12% and 100.0%, respectively. The comparison with other approaches (connectivity indices, total and local spectral moments, quantum chemical descriptors, topographic indices and E- state/biomolecular encounter parameters) reveals a good behavior of our method. The approach described in this paper appears to be a very promising structural invariant, useful for QSPR/QSAR studies and computer-aided “rational” drug design.

The tyrosinase enzyme (EC 1.14.18.1) is an oxidoreductase inside the general enzyme classification and is involved in the oxidation and reduction process in the epidermis. These chemical reactions that the enzyme catalyzes are of principal importance in the melanogenesis process. This process of melanogenesis is related to the melanin formation, a heteropolymer of indolic nature that provides the different tonalities in the skin and helps to the protection from the ultraviolet radiation. However, a pigment overproduction, come up by the action of the tyrosinase, can cause different disorders in the skin related to the hyperpigmentation. Several studies mainly focused on the characteristics of the enzyme have been reported. In this work, an approximation to general aspects related to this enzyme is made. Besides, it is treated the researches that have been published in the part of the biochemical anatomy dealing with diseases associated with this protein (melanogenesis), its active place and its physiological states, the molecular mechanism, the methods carried out to detect the inhibitory activity, and the used substrates.