## 6 Pro et Contra Connected with Presently Employed in Silico Tools
Indeed, there was definitely a broad room for the use of other open-source computational platforms such as Mordred [251] or PaDEL-DDPredictor [252]. The significance of generated 2D and 3D descriptors through Mordred [251], a Python-based code, was generally well accepted, its performance was reported to be rather extraordinary; Mordred might calculate an entire molecular descriptor twice as fast as PaDEL-DDPredictor. The installation of Mordred could be achieved using only a single command. However, the proper functioning of such a software tool might require the installation of an additional environment [251], for example, Anaconda or RDKit. In fact, this process might sometimes be considered 'an obstacle' for students, lecturers, or researchers who prefer a more straightforward way to generate the desired descriptors and whose computer skills might be not so advanced. Similar conclusions are drawn considering the PaDEL-DDPredictor tool [252]. The interface might be regarded as convenient and relatively simple to use. However, the calculations require additional procedures, that is, the installation of the Java Runtime Environment (as in the case of predictors preferred in the current research), proper manual creation of relevant output file(s), as well as proper setup of required directories and files. This predictor allows the calculation of a broad palette of 'classic' descriptors, in fact, including _MW_, _MR_, \(V_{\text{vdW}}\), \(n_{\text{robot}}\), \(n_{\text{r}}\), \(n_{\text{OHNH}}\), \(n_{\text{ON}}\), several lipophilicity parameters, or _tPSA_. However, it does not serve as a platform for generating the PK, biochemical, or toxicological characteristics. The web-based SMARTCyp tool [253] allows free prediction of biotransformation sites in the structure of numerous compounds. On the other hand, only the isoenzymes CYP3A4, CYP2G, and CYP2D6 are currently considered in this applet. Specific web-based platforms, which previously offered a wide palette of parameters to be calculated for free [254; 255], were notably modified, and comprehensive calculations or even the servers themselves were no longer available to be utilized. The possibility of calculating several absolutely crucial descriptors very frequently employed in Medicinal Chemistry, including the acid-base p\(K_{\text{a}}\) values or different biochemical constants, was markedly restricted in freely available computational apples in recent years. In addition, these free tools might focus on a single specific property or model. The opportunity to generate and obtain the desired values was mainly connected with commercial software [256], and that factor is very limited (not only) in the academic sphere. In addition, the freely available MolGpKa web server [156] offers the possibility to conveniently predict the p\(K_{\text{a}}\) descriptor. Therefore, the combination of the SwissADME [66], ADMETlab ver. 3.0 [67], ALOGPS/VCCLAB [95], Molnispiration Cheminformatics [97], Enalos Cloud Platform [132], and MolGpKa [156] prediction tools for the majority of the current calculations seems to be reasonable and maybe'more convenient' for the wider scientific community or the community of academic and university lecturers. Moreover, the ADMETlab ver. 3.0 tool [67] is regarded as the one providing the best accuracy and precision in the predictions [256]. Several details on accessibility, calculated descriptors, and particular prediction principles of particular computational tools are listed in Supplementary Materials. The use of the given web-based interactive predictors [66; 67; 95; 97; 132; 156] was not connected only with benefits, but several issues could also be mentioned. In general, the confidentiality of the calculated data could not always be guaranteed for such a type of computational tools, and the risk of unauthorized use of investigated compounds could be significant.