Jaime Pérez-Villanueva

Structure–activity relationships of benzimidazole derivatives as antiparasitic agents: Dual activity-difference (DAD) maps

Parasitic infections still remain a major health threat in developing countries. Herein we report a systematic characterization of the structure–activity relationships (SAR) of a comprehensive set of benzimidazole derivatives tested against Trichomonas vaginalis and Giardia intestinalis. The analysis was based on pairwise comparisons of the activity similarity and molecular similarity using different molecular representations. Overall, results encourage simultaneous lead optimization efforts for benzimidazole derivatives active against both protozoan. In order to explore the activity profile of the benzimidazoles against the two parasites, we developed the dual activity-difference (DAD) map. DAD map is a complementary approach to systematically characterize the SAR of compound data sets.

Multitarget Structure–Activity Relationships Characterized by Activity-Difference Maps and Consensus Similarity Measure

Dual and triple activity-difference (DAD/TAD) maps are tools for the systematic characterization of structure-activity relationships (SAR) of compound data sets screened against two or three targets. DAD and TAD maps are two- and three- dimensional representations of the pairwise activity differences of compound data sets, respectively. Adding pairwise structural similarity information into these maps readily reveals activity cliff regions in the SAR for one, two, or three targets. In addition, pairs of compounds in the smooth regions of the SAR and scaffold hops are also easily identified in these maps. Herein, DAD and TAD maps are employed for the systematic characterization of the SAR of a benchmark set of 299 compounds screened against dopamine, norepinephrine, and serotonin transporters. To reduce the well-known dependence of the activity landscape on the structural representation, five selected 2D and 3D structure representations were used to characterize the SAR. Systematic analysis of the DAD and TAD maps reveals regions in the landscape with similar SAR for two or the three targets as well as regions with inverse SAR, i.e., changes in structure that increase activity for one target, but decrease activity for the other target. Focusing the analysis on pairs of compounds with high structure similarity revealed the presence of single-, dual-, and triple-target activity cliffs, i.e., small changes in structure with high changes in potency for one, two, or the three targets, respectively. Triple-target scaffold hops are also discussed. Activity cliffs and scaffold hops were also quantified and represented using two recently proposed approaches namely, mean Structure Activity Landscape Index (mean SALI) and Consensus Structure-Activity Similarity (SAS) maps.

Identifying Activity Cliff Generators of PPAR Ligands Using SAS Maps

Structure‐activity relationships (SAR) of compound databases play a key role in hit identification and lead optimization. In particular, activity cliffs, defined as a pair of structurally similar molecules that present large changes in potency, provide valuable SAR information. Herein, we introduce the concept of activity cliff generator, defined as a molecular structure that has a high probability to form activity cliffs with molecules tested in the same biological assay. To illustrate this concept, we discuss a case study where Structure‐Activity Similarity maps were used to systematically identify and analyze activity cliff generators present in a dataset of 168 compounds tested against three peroxisome‐proliferator‐activated receptor (PPAR) subtypes. Single‐target and dual‐target activity cliff generators for PPARα and δ were identified. In addition, docking calculations of compounds that were classified as cliff generators helped to suggest a hot spot in the target protein responsible of activity cliffs and to analyze its implication in ligand‐enzyme interaction.

Synthesis and antiprotozoal activity of novel 2-{[2-(1H-imidazol-1-yl)ethyl]sulfanyl}-1H-benzimidazole derivatives.

A series of 19 new 2-{[2-(1H-imidazol-1-yl)ethyl]sulfanyl}-1H-benzimidazole derivatives was synthesized starting from the properly substituted 1,2-phenylendiamine. These compounds have hydrogen or methyl at position 1; while hydrogen, chlorine, ethoxy or methoxycarbonyl group is at position 5 and/or 6. The novel compounds were tested against protozoa Trichomonas vaginalis, Giardia intestinalis and Entamoeba histolytica. Experimental evaluations revealed strong activity for all tested compounds, having IC50 values in the nanomolar range, which were even better than metronidazole, the drug of choice for these parasites.

Synthesis and in vitro cysticidal activity of new benzimidazole derivatives

Despite albendazole being the drug of choice in neurocysticercosis treatment, its low solubility limits its bioavailability; therefore, more research is required in order to find new molecules with cestocidal activity and adequate aqueous solubility. A set of 13 benzimidazole derivatives were synthesized and their in vitro activities were evaluated against Taenia crassiceps cysts, using albendazole sulfoxide as reference molecule, showing that two of them exhibited good activity. Molecular modelling revealed that the cysticidal efficacy depends on the presence on the molecule of an H in the 1-position, a planar carbamate group at 2-position, and if the substituent in 5-position is voluminous, it should be orthogonal to the benzimidazole ring.

Antiprotozoal activity of proton-pump inhibitors.

Parasitic diseases are still a major health problem in developing countries. In our effort to find new antiparasitic agents, in this Letter we report the in vitro antiprotozoal activity of omeprazole, lansoprazole, rabeprazole and pantoprazole against Trichomonas vaginalis, Giardia intestinalis and Entamoeba histolytica. Molecular modeling studies were an important tool to highlight the potential antiprotozoal activity of these drugs. Experimental evaluations revealed a strong activity for all compounds tested. Rabeprazole and pantoprazole were the most active compounds, having IC(50) values in the nanomolar range, which were even better than metronidazole, the drug of choice for these parasites.

CASE plots for the chemotype-based activity and selectivity analysis: a CASE study of cyclooxygenase inhibitors.

Structure–activity characterization of molecular databases plays a central role in drug discovery. However, the characterization of large databases containing structurally diverse molecules with several end‐points represents a major challenge. For this purpose, the use of chemoinformatic methods plays an important role to elucidate structure–activity relationships. Herein, a general methodology, namely Chemotype Activity and Selectivity Enrichment plots, is presented. Chemotype Activity and Selectivity Enrichment plots provide graphical information concerning the activity and selectivity patterns of particular chemotypes contained in structurally diverse databases. As a case study, we analyzed a set of 658 compounds screened against cyclooxygenase‐1 and cyclooxygenase‐2. Chemotype Activity and Selectivity Enrichment plots analysis highlighted chemotypes enriched with active and selective molecules against cyclooxygenase‐2; all this in a simple 2D graphical representation. Additionally, the most active and selective chemotypes detected in Chemotype Activity and Selectivity Enrichment plots were analyzed separately using the previously reported dual activity–difference maps. These findings indicate that Chemotype Activity and Selectivity Enrichment plots and dual activity–difference maps are complementary chemoinformatic tools to explore the structure–activity relationships of structurally diverse databases screened against two biological end‐points.

Activity cliffs and activity cliff generators based on chemotype-related activity landscapes

Activity cliffs have large impact in drug discovery; therefore, their detection and quantification are of major importance. This work introduces the metric activity cliff enrichment factor and expands the previously reported activity cliff generator concept by adding chemotype information to representations of the activity landscape. To exemplify these concepts, three molecular databases with multiple biological activities were characterized. Compounds in each database were grouped into chemotype classes. Then, pairwise comparisons of structure similarities and activity differences were calculated for each compound and used to construct chemotype-based structure–activity similarity (SAS) maps. Different landscape distributions among four major regions of the SAS maps were observed for different subsets of molecules grouped in chemotypes. Based on this observation, the activity cliff enrichment factor was calculated to numerically detect chemotypes enriched in activity cliffs. Several chemotype classes were detected having major proportion of activity cliffs than the entire database. In addition, some chemotype classes comprising compounds with smooth structure activity relationships (SAR) were detected. Finally, the activity cliff generator concept was applied to compounds grouped in chemotypes to extract valuable SAR information.Graphic abstract

3D-QSAR studies on purine-carbonitriles as cruzain inhibitors: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA)

Cruzain has been identified as the major cysteine protease of Trypanosoma cruzi, the etiological cause of Chagas disease. For this reason, many efforts have been undertaken to design new inhibitors against this enzyme. Recently, molecules having a purine or triazine nucleus have been reported as potent non-peptidic inhibitors of cruzain. In order to gain an insight into the structural requirements that can lead to the improvement of the activity of these molecules, in this paper we report the CoMFA and CoMSIA studies of a series of purine-carbonitriles as cruzain inhibitors. Quantum semi-empirical calculations of the inhibitors inside the active site of cruzain were used as an approach to obtain reliable conformations for molecular alignment. Two different molecular alignments were used, resulting in 3 CoMFA models and 31 CoMSIA models. These models correspond to all of the possible combinations among five fields: steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor. Highly predictive models were obtained. Based on the q2 values, the best CoMFA model had an r2 = 0.98 and a q2 = 0.73, whereas the best CoMSIA model retrieved an r2 = 0.88 and a q2 = 0.62. All models were validated with a rigorous procedure using an external test set. Contour maps obtained from these models show a preference toward the purine ring and indicate that bulky groups with a negative potential at the 3- and 5-positions of the phenyl ring are important structural requirements for inhibitory activity against cruzain.

Synthesis of Curcuminoids and Evaluation of Their Cytotoxic and Antioxidant Properties

Curcumin (1) and ten derivatives (2–11) were synthesized and evaluated as cytotoxic and antioxidant agents. The results of primary screening by Sulforhodamine B assay against five human cancer cell lines (U-251 MG, glioblastoma; PC-3, human prostatic; HCT-15, human colorectal; K562, human chronic myelogenous leukemia; and SKLU-1, non-small cell lung cancer) allowed us to calculate the half maximal inhibitory concentration (IC50) values for the more active compounds against HCT-15 and K562 cell lines. Compounds 2 and 10 were the most active against both cell lines and were more active than curcumin itself. Thiobarbituric acid reactive substances (TBARS) assay showed that 7 has potent activity; even stronger than curcumin, α-tocopherol, and quercetin.