Quantitative structureÀ activity relationship(QSAR) modeled the biological activities of 30 cannabinoids with quantum similarity descriptors(QSD) and Comparative Molecular Field Analysis (CoMFA). The PubChem[https://pubchem.ncbi.nlm.nih.gov/] database provided the geometries, binding affinities(K i ) to the cannabinoid receptors type 1(CB1) and 2(CB2), and the median lethal dose(LD 50 ) to breast cancer cells. An innovative quantum similarity approach combining (self)-similarity indexes calculated with different charge-fitting schemes under the Topo-Geometrical Superposition Algorithm(TGSA) were used to obtain QSARs. The determination coefficient(R 2 ) and leave-oneout cross-validation[Q 2 (LOO)] quantified the quality of multiple linear regression and support vector machine models. This approach was efficient in predicting the activities, giving predictive and robust models for each endpoint [pLD 50 : R 2 = 0.9666 and Q 2 (LOO) = 0.9312; pK i (CB1): R 2 = 1.0000 and Q 2 (LOO) = 0.9727, and pK i (CB2): R 2 = 0.9996 and Q 2 (LOO) = 0.9460], where p is the negative logarithm. The descriptors based on the electrostatic potential encrypted better electronic information involved in the interaction. Moreover, the similaritybased descriptors generated unbiased models independent of an alignment procedure. The obtained models showed better performance than those reported in the literature. An additional 3D-QSAR CoMFA analysis was applied to 15 cannabinoids, taking THC as a template in a ligand-based approach. From this analysis, the region surrounding the amino group of the SR141716 ligand is the more favorable for the antitumor activity.

A theoretical study of the ciprofloxacin interactions with glucuronic acid, arabinose, glucosamine, and rhamnose is presented. The most stable complexes were obtained through genetic algorithms starting from the neutral and zwitterion species of ciprofloxacin. The energy at the semiempirical level PM7 of the optimal structures of the complexes was the genetic algorithm‘s fitness function. The resulting complexes’ geometry was optimized at M062X−D3/6‐311++G** level of theory, and non‐covalent interactions were assessed through the reduced density gradient and quantum theory of atoms in molecules. The results show that the zwitterion species of ciprofloxacin favorably complex carbohydrates and can induce proton exchange between them. The molecular complexes from proton exchange are the most stable, followed by the complexes formed by the contact of the zwitterion species and the carbohydrate. The complexes formed by both neutral species were the least stable. The medium strength and strong (assisted by charge) hydrogen bonds, the XH⋅⋅⋅π and lone‐pair⋅⋅π interactions, were mainly present in the complexes. Proton exchange processes strengthen the interactions mentioned above.