New Antitrichomonal Drug-like Chemicals Selected by Bond (Edge)-Based TOMOCOMD-CARDD Descriptors

Abstract

Bond-based quadratic indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis (LDA) were used to discover novel lead trichomonacidals. The obtained LDA-based quantitative structure-activity relationships (QSAR) models, using nonstochastic and stochastic indices, were able to classify correctly 87.91% (87.50%) and 89.01% (84.38%) of the chemicals in training (test) sets, respectively. They showed large Matthews correlation coefficients of 0.75 (0.71) and 0.78 (0.65) for the training (test) sets, correspondingly. Later, both models were applied to the virtual screening of 21 chemicals to find new lead antitrichomonal agents. Predictions agreed with experimental results to a great extent because a correct classification for both models of 95.24% (20 of 21) of the chemicals was obtained. Of the 21 compounds that were screened and synthesized, 2 molecules (chemicals G-1, UC-245) showed high to moderate cytocidal activity at the concentration of 10 mg/ml, another 2 compounds (G-0 and CRIS-148) showed high cytocidal activity only at the concentration of 100 mg/ml, and the remaining chemicals (from CRIS-105 to CRIS-153, except CRIS-148) were inactive at these assayed concentrations. Finally, the best candidate, G-1 (cytocidal activity of 100% at 10 mg/ml) was in vivo assayed in ovariectomized Wistar rats achieving promising results as a trichomonacidal drug-like compound. (Journal of Biomolecular Screening 2008:785-794).

Antiparasitic activity of furanyl N-acylhydrazone derivatives against Trichomonas vaginalis: in vitro and in silico analyses

“…However, to the best of authors' knowledge there are no prior reports of compounds containing the N-acylhydrazone moiety being active against T. vaginalis, or a species of the genus Trichomonas. As for the furan moiety, previous studies have shown that compounds containing this pharmacophoric group are active against T. vaginalis and Giardia lamblia [42,43]. These studies substantiate the antiprotozoan potential of furanyl N-acylhydrazone derivatives demonstrated in our results.…”

Identification In Silico and In Vitro of Novel Trypanosomicidal Drug‐Like Compounds

“…On the other hand, the same group of chemicals used in this work was recently tested against other protozoan parasite, Trichomonas vaginalis , and all compounds were found inactive at all assayed concentrations, with exception of compound CRIS 148 (47). Therefore, we can say that the antitrypanosomal activity, predicted and experimentally corroborated in this work, is quite specific for this group of compounds.…”

<strong>Multi-viral targets entropy QSAR for antiviral drugs </strong>

“…The elements 1 pij(s) of the 1-step drug-target interaction stochastic matrix are the binding probabilities with which a j-th atom bind to a structure less molecular receptor given that other i-th atoms have been interacted before at time t1 = 1 (considering t0 = 0) (18, 24, 41, 43): By using, φ(s), 1 (s) and chapmankolgomorov equations one can describe the further evolution of the system. [10][11][12][13][14][15][16][17] summing up all the atomic free energies of interaction 0 θj(s) pre-multiplied by the absolute probabilities of drug-target interaction a pk(j,s) one can derive the average changes in entropies k θs of the gradual interaction between the drug and the receptor at a specific time k in a given microbial species (s) (24):…”

“…Unfortunately, almost QSAR studies, including those for antiviral activity and others, use limited databases of structurally parent compounds acting against one single fungus species (2). One important step in the evolution of this field was the introduction of QSAR models for heterogeneous series of antimicrobial compounds; see for instance the works of Cronin, de Juliá n-Ortiz, Galvé z, Gá rcí a-Domenech, Gosalbez, Marrero-Ponce, Torrens, et al and others (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15). As a result, researchers may predict very heterogeneous series of compounds but often need to use/develop as many QSAR equations as microbial species are necessary to be predicted.…”