## 1 Introduction  
Accurate modeling of small molecules is a useful starting point in stereochemical structure identification. This approach substantially reduces the logistical and time-consuming effort to discover and then obtain chemicals with various applications. For example, molecular symmetry/asymmetry is essentially involved in the intermolecular interactions that give rise to biological activity. In turn, identifying the configuration of asymmetric carbon atoms in diastereomers may be decisive in structure-based drug design. Recent studies show such investigations, especially those related to the biological interactions of chiral phytochemicals for the rapid discovery of potential drugs in SARS-CoV-2 [1]. The transfer of the biologically active structure from in silico to in vitro requires precise analytical methods to discriminate it from its isomers. Quantitative structure-fragmentation relationship (QSFR) techniques based on mass spectrometry could be a solution for controlling the bioactive structure along the entire path from synthesis to its use. The continuous increase in the number of chemical compounds and their isomers in databases makes their recognition and tracing increasingly subtle and difficult to achieve. Chemical analysis methods must cope with the identification of more and more similar structures to eliminate false-positive candidates. In the case of establishing the isomer symmetry, no orthogonal analytical method is superfluous because only the convergence of as many analytical results as possible can provide structural certainty [2; 3; 4]. Chromatography and mass spectrometry (MS) are orthogonal methods of analysis because they are based on different physicochemical processes. The coupling of chromatography with mass spectrometry has offered the possibility of analyzing complex mixtures of analytes [5]. In addition to the classical use of standards, they use new variants of data processing and interpretation, which have been effectively translated to computational molecular simulation approaches [6; 7; 8]. In some QSFR analytical techniques using mass-energy profiles in mass spectrometry, the experimental profile resulting from the mass spectrum is compared with the calculated profiles for the candidate structures. Maximum fit for the proper structure should be obtained if the calculated energy descriptors correctly describe the fragmentation [7; 8]. For these techniques, the use of elements of the \"lock and key\" concept of enzymology ([PERSON]) [9] can be intuitive and productive. In this approach, the \"lock\" would describe the fragmentation mass-energy profile associated with the mass spectrum of the analyte, and the \"keys\" would be the computed mass-energy profiles for the candidate structures. However, breakdown graphs show that the relativity of ionic intensities in the mass spectrum is in a continuous dynamic depending on the impact energies [10]. Many other factors may influence this relativity. Therefore, it is to be expected that, even for the true structure, the maximum matching of the calculated and experimental mass-energy profiles will be achieved only under certain conditions, or maybe not at all. This situation leads to an analytical impossibility because there are many profiles (keys) that can be calculated for a certain structure; on the other hand, the profile of the lock is not stable, whereby, for a structure, many mass spectra can be obtained, containing different ionic relativities. Another concept in enzymology, \"induced fit\" ([PERSON]), could provide a solution to this situation by using the matching score of the profiles [9]. Such matching scores can be calculated for all possible key-lock pairs generated by the factors that influence the dynamics of the calculated and experimental profiles. The maximum score should correspond to the actual structure.