Indanylacetic acids as PPAR-delta activator insulin sensitizers

Development of a Robust Read-Across Model for the Prediction of Biological Potency of Novel Peroxisome Proliferator-Activated Receptor Delta Agonists

A robust predictive model was developed using 136 novel peroxisome proliferator-activated receptor delta (PPARδ) agonists, a distinct subtype of lipid-activated transcription factors of the nuclear receptor superfamily that regulate target genes by binding to characteristic sequences of DNA bases. The model employs various structural descriptors and docking calculations and provides predictions of the biological activity of PPARδ agonists, following the criteria of the Organization for Economic Co-operation and Development (OECD) for the development and validation of quantitative structure-activity relationship (QSAR) models. Specifically focused on small molecules, the model facilitates the identification of highly potent and selective PPARδ agonists and offers a read-across concept by providing the chemical neighbours of the compound under study. The model development process was conducted on Isalos Analytics Software (v. 0.1.17) which provides an intuitive environment for machine-learning applications. The final model was released as a user-friendly web tool and can be accessed through the Enalos Cloud platform's graphical user interface (GUI).

Arylcarboxylation of unactivated alkenes with CO2 via visible-light photoredox catalysis

Photocatalytic carboxylation of alkenes with CO₂ is a promising and sustainable strategy to synthesize high value-added carboxylic acids. However, it is challenging and rarely investigated for unactivated alkenes due to their low reactivities. Herein, we report a visible-light photoredox-catalyzed arylcarboxylation of unactivated alkenes with CO₂, delivering a variety of tetrahydronaphthalen-1-ylacetic acids, indan-1-ylacetic acids, indolin-3-ylacetic acids, chroman-4-ylacetic acids and thiochroman-4-ylacetic acids in moderate-to-good yields. This reaction features high chemo- and regio-selectivities, mild reaction conditions (1 atm, room temperature), broad substrate scope, good functional group compatibility, easy scalability and facile derivatization of products. Mechanistic studies indicate that in situ generation of carbon dioxide radical anion and following radical addition to unactivated alkenes might be involved in the process.

Nickel-Catalyzed Chemo- and Regioselective Benzylarylation of Unactivated Alkenes with o-Bromobenzyl Chlorides

Chemo- and regioselectively nickel-catalyzed reductive benzylarylation of unactivated alkenes with o-bromobenzyl chlorides is disclosed herein, in which electrophiles participate through a single-component double-site approach. Moreover, its utility is underscored by the concise synthesis of bioactive Indane compounds and postreaction functionalizations leading to structurally diverse scaffolds. Preliminary mechanistic investigations suggest a radical chain reaction mechanism.

Structure-based virtual screening and discovery of New PPARδ/γ dual agonist and PPARδ and γ agonists

Peroxisome proliferator-activated receptors (PPARs) are involved in the control of carbohydrate and lipid metabolism and are considered important targets to treat diabetes mellitus and metabolic syndrome. The available PPAR ligands have several side effects leading to health risks justifying the search for new bioactive ligands to activate the PPAR subtypes, in special PPARδ, the less studied PPAR isoform. Here, we used a structure-based virtual screening protocol in order to find out new PPAR ligands. From a lead-like subset of purchasable compounds, we identified 5 compounds with potential PPAR affinity and, from preliminary in vitro assays, 4 of them showed promising biological activity. Therefore, from our in silico and in vitro protocols, new PPAR ligands are potential candidates to treat metabolic diseases.

Identification of novel multitargeted PPARα/γ/δ pan agonists by core hopping of rosiglitazone

The thiazolidinedione class peroxisome proliferator-activated receptor gamma (PPARγ) agonists are restricted in clinical use as antidiabetic agents because of side effects such as edema, weight gain, and heart failure. The single and selective agonism of PPARγ is the main cause of these side effects. Multitargeted PPARα/γ/δ pan agonist development is the hot topic in the antidiabetic drug research field. In order to identify PPARα/γ/δ pan agonists, a compound database was established by core hopping of rosiglitazone, which was then docked into a PPARα/γ/δ active site to screen out a number of candidate compounds with a higher docking score and better interaction with the active site. Further, absorption, distribution, metabolism, excretion, and toxicity prediction was done to give eight compounds. Molecular dynamics simulation of the representative Cpd#1 showed more favorable binding conformation for PPARs receptor than the original ligand. Cpd#1 could act as a PPARα/γ/δ pan agonist for novel antidiabetic drug research.

Identification of distant drug off-targets by direct superposition of binding pocket surfaces

Correctly predicting off-targets for a given molecular structure, which would have the ability to bind a large range of ligands, is both particularly difficult and important if they share no significant sequence or fold similarity with the respective molecular target ("distant off-targets"). A novel approach for identification of off-targets by direct superposition of protein binding pocket surfaces is presented and applied to a set of well-studied and highly relevant drug targets, including representative kinases and nuclear hormone receptors. The entire Protein Data Bank is searched for similar binding pockets and convincing distant off-target candidates were identified that share no significant sequence or fold similarity with the respective target structure. These putative target off-target pairs are further supported by the existence of compounds that bind strongly to both with high topological similarity, and in some cases, literature examples of individual compounds that bind to both. Also, our results clearly show that it is possible for binding pockets to exhibit a striking surface similarity, while the respective off-target shares neither significant sequence nor significant fold similarity with the respective molecular target ("distant off-target").

Molecular features related to the binding mode of PPARδ agonists from QSAR and docking analyses

Diabetes affects approximately 4% of world's population and metabolic syndrome has been directly related to obesity. There is a class of nuclear receptors, peroxisome proliferator-activated receptors (PPARs), which controls the metabolism of carbohydrates and lipids. It has been considered an attractive target to treat diabetes and metabolic syndrome. Accordingly, the primary objective of this study was to employ molecular modelling techniques to understand the factors involved in PPARδ activation. The QSAR models obtained showed good internal and external consistency and presented good validation coefficients (QSAR: q(2) = 0.83, r(2) = 0.87; HQSAR: q(2) = 0.73, r(2) = 0.90; CoMFA: q(2) = 0.88, r(2) = 0.94). The selected properties and the contour maps described the possible interactions between the PPARδ receptor and its agonists. From these findings, it is possible to propose molecular modifications to design new compounds with improved biological properties.