## 6 Pro et Contra Connected with Presently Employed in Silico Tools
The SwissADME applet [66] was one of the exceptions; the development company of this web-based software, the Swiss Institute of Bioinformatics, provided the information that it was committed to ensuring the privacy and confidentiality of user personal data. The obstacle was not directly related to the current research because the structure of all of the analyzed compounds was already published in scientific papers, as listed in Section 5.1. The web-based SMARTCyp tool [253] also allowed free prediction of biotransformation sites in the structure of numerous compounds. However, only the limited number of isoenzymes were considered in this applet, as mentioned. Numerous predictors offered the calculation of the 1D or 2D descriptors that could not be completely relevant for the evaluation considering the complexity of a 3D space, i.e., stereochemical properties of investigated compounds, experiments under in vitro or in vivo conditions, as well as a very complex biological environment, with all their specificities. However, appropriately chosen in silico approaches could be rather beneficial, especially in the initial stages of the complex evaluation of pharmacologically effective compounds or prospective drug candidates, because they might considerably limit the number of animal studies [257; 258]. Some predictor tools provided a broad spectrum of PD, structural, physicochemical, PK, or 'biological' data, the adequate interpretation of which might not be trivial and efficient translation of the knowledge obtained to Medicinal Chemistry would not be enabled. In addition, several descriptors could not be satisfactorily predicted via given computational tools because of their complexity. The aqueous solubility, as one of the strategic parameters in Medicinal Chemistry, is mentioned as a suitable example in this regard [259]. There might be a general lack of experimental values for all considered types of descriptors related to investigated molecules, including viniferins and viniferin-based compounds. Therefore, it is not possible to correlate the experimentally estimated data and calculated parameters (for example, particular lipophilicity descriptors, several biochemical or toxicological 'values') and to absolutely precisely evaluate the significance of predicted outputs. The threshold value of \(MW\) for the calculations related to the small molecules had to be taken into consideration if they would be evaluated via these web-based in silico tools. The fundamental condition for such an investigation was the generation of a correct SMILES code. For example, the structurally more complex oligomeric molecules [260; 261] based on the molecular framework of **RSV (1)** even with \(MW\) > 1500.00 Da, **pauciflorl D** (\(MW\) = 1586.47 Da; heptamer), for example, might be successfully analyzed [66; 67] because their correct SMILES codes were generated. On the other hand, the use of the given type of predictor tools for the evaluation of structurally more complex molecules, inorganic compounds, or highly reactive molecules [66] would not be possible. The in silico and experimental techniques employed today provide highly valuable information on particular biological and biochemical processes at the molecular level [262; 263], including protein(s)-protein(s), drug-(desired) biological target(s), or drug-drug interactions. However, considering the frequent immersion complexity of natural systems, the coherent comprehension of such processes via the in silico and/or in vitro evaluations could not be entirely sufficient. In general, the appropriate modeling of heterogeneous and highly structured biological environments is still a fairly challenging task. Simulations in silico have been accepted by the scientific community mainly from the perspective of complementing clinical studies in real clinical conditions. In fact, the most essential step is to constantly improve the robustness and reliability of proposed predictive models to align with real clinical data as closely as possible [264].