Valerianapraecipitis (Caprifoliaceae), a species new to science and endemic to Central Chile.

The species Valerianapraecipitis (Caprifoliaceae), new to science and endemic to the Ñuble Region, Central Chile, is formally described. Morphological data support its placement in a new species, clearly different from V.philippiana. A detailed description, insights about its habitat and ecology, distribution map and illustration are provided. A table of comparison is also given with the morphological characters discriminating V.praecipitis from V.philippiana. The species is assessed as Endangered (EN) under the IUCN categories.

Towards the understanding of the activity of G9a inhibitors: an activity landscape and molecular modeling approach.

In this work, we analyze the structure-activity relationships (SAR) of epigenetic inhibitors (lysine mimetics) against lysine methyltransferase (G9a or EHMT2) using a combined activity landscape, molecular docking and molecular dynamics approach. The study was based on a set of 251 G9a inhibitors with reported experimental activity. The activity landscape analysis rapidly led to the identification of activity cliffs, scaffolds hops and other active an inactive molecules with distinct SAR. Structure-based analysis of activity cliffs, scaffold hops and other selected active and inactive G9a inhibitors by means of docking followed by molecular dynamics simulations led to the identification of interactions with key residues involved in activity against G9a, for instance with ASP 1083, LEU 1086, ASP 1088, TYR 1154 and PHE 1158. The outcome of this work is expected to further advance the development of G9a inhibitors.

Computational Methods for Epigenetic Drug Discovery: A Focus on Activity Landscape Modeling.

Epigenetic drug discovery is an emerging strategy against several chronic and complex diseases. The increased interest in epigenetics has boosted the development and maintenance of large information on structure-epigenetic activity relationships for several epigenetic targets. In turn, such large databases-many in the public domain-are a rich source of information to explore their structure-activity relationships (SARs). Herein, we conducted a large-scale analysis of the SAR of epigenetic targets using the concept of activity landscape modeling. A comprehensive quantitative analysis and a novel visual representation of the epigenetic activity landscape enabled the rapid identification of regions of targets with continuous and discontinuous SAR. This information led to the identification of epigenetic targets for which it is anticipated an easier or a more difficult drug-discovery program using conventional hit-to-lead approaches. The insights of this work also enabled the identification of specific structural changes associated with a large shift in biological activity. To the best of our knowledge, this work represents the largest comprehensive SAR analysis of several epigenetic targets and contributes to the better understanding of the epigenetic activity landscape.

Synthesis, antiprotozoal activity, and chemoinformatic analysis of 2-(methylthio)-1H-benzimidazole-5-carboxamide derivatives: Identification of new selective giardicidal and trichomonicidal compounds.

A series of twelve new 2-(methylthio)-1H-benzimidazole-5-carboxamide derivatives (1-12) were synthesized and their antiparasitic activity was tested in vitro against Giardia intestinalis, Trichomonas vaginalis and Entamoeba histolytica. Experimental evaluations showed IC50 values within the nanomolar range for all tested compounds, some showing higher activity than metronidazole and albendazole. A chemoinformatic study was used to compare the structure-activity relationship of the synthesized carboxamides with those of 91 previously studied benzimidazoles, and with some Nitazoxanide-N-methylbenzimidazole hybrids recently synthetized by our group. Compounds 1 and 3 were identified as prominent selective compounds against T. vaginalis and G. intestinalis, respectively, while compound 4 was found to be of broad spectrum against the three protozoans.

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.