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

Machine Learning-Based Virtual Screening of Antibacterial Agents against Methicillin-Susceptible and Resistant Staphylococcus aureus

The application of computer-aided drug discovery (CADD) approaches has enabled the discovery of new antimicrobial therapeutic agents in the past. The high prevalence of methicillin-resistantStaphylococcus aureus(MRSA) strains promoted this pathogen to a high-priority pathogen for drug development. In this sense, modern CADD techniques can be valuable tools for the search for new antimicrobial agents. We employed a combination of a series of machine learning (ML) techniques to select and evaluate potential compounds with antibacterial activity against methicillin-susceptible S. aureus (MSSA) and MRSA strains. In the present study, we describe the antibacterial activity of six compounds against MSSA and MRSA reference (American Type Culture Collection (ATCC)) strains as well as two clinical strains of MRSA. These compounds showed minimal inhibitory concentrations (MIC) in the range from 12.5 to 200 μM against the different bacterial strains evaluated. Our results constitute relevant proven ML-workflow models to distinctively screen for novel MRSA antibiotics.

Bioinformatics-Guided Identification of Ethyl Acetate Extract of Citri Reticulatae Pericarpium as a Functional Food Ingredient with Anti-Inflammatory Potential

Citri Reticulatae Pericarpium (CRP) is one of the most commonly used food supplements and folk medicines worldwide, and possesses cardiovascular, digestive, and respiratory protective effects partially through its antioxidant and anti-inflammatory functions. The unique aromatic flavor and mild side effects make CRP a promising candidate for the development of anti-inflammatory functional food. However, recent studies show that the crude alcoholic extract and some isolated compounds of CRP show compromised anti-inflammatory activity, which became the main factor hindering its further development. To identify the bioactive compounds with anti-inflammatory potential, and improve the anti-inflammatory effects of the extract, a bioinformatics-guided extraction protocol was employed in this study. The potential bioactive candidates were identified by combing network pharmacology analysis, molecular docking, principal components analysis, k-means clustering, and in vitro testing of reference compounds. Our results demonstrated that 66 compounds in CRP could be grouped into four clusters according to their docking score profile against 24 receptors, while the cluster containing flavonoids and phenols might possess a more promising anti-inflammatory function. In addition, in vitro anti-inflammatory tests of the seven reference compounds demonstrated that hesperitin, naringenin, and gardenin B, which were grouped into a cluster containing flavonoids and phenols, significantly decreased LPS-induced NO, TNF-α, and IL-6 production of macrophages. While the compounds outside of that cluster, such as neohesperidin, naringin, hesperidin, and sinensetin showed little effect on alleviating LPS-induced NO and proinflammatory cytokine production. Based on the chemical properties of selected compounds, ethyl acetate (EtOAc) was selected as the solvent for extraction, because of its promising solubility of flavonoids and phenols. Furthermore, the ethanol alcoholic extract was used as a reference. The chemical profiling of EtOAc and crude alcoholic extract by HPLC/MS/MS also demonstrated the decreased abundance of flavonoid glycosides in EtOAc extract but increased abundance of phenols, phenolic acid, and aglycones. In accordance with the prediction, the EtOAc extract of CRP, but not the crude alcoholic extract, significantly decreased the NO, IL-6, and TNF-α production. Taken together, the results suggested selective extraction of phenols and flavonoids rich extract was able to increase the anti-inflammatory potential of CRP partially because of the synergistic effects between flavonoids, phenols, and enriched polymethoxyflavones. Our study might pave the road for the development of ethyl acetate extract of CRP as a novel functional food with anti-inflammatory function.

Advances in computer-aided drug design for type 2 diabetes

INTRODUCTION

The number of diabetic patients is increasing, posing a heavy social and economic burden worldwide. Traditional drug development technology is time-consuming and costly, and the emergence of computer-aided drug design (CADD) has changed this situation. This study reviews the applications of CADD in diabetic drug designing.

AREAS COVERED

In this article, the authors focus on the advance in CADD in diabetic drug design by elaborating the discovery, including peroxisome proliferator-activated receptor (PPAR), G protein-coupled receptor 40 (GPR40), dipeptidyl peptidase-IV (DDP-IV), protein tyrosine phosphatase 1B (PTP1B), sodium-dependent glucose transporter 2 (SGLT-2), and glucokinase (GK). Some drug discovery of these targets is related to CADD strategies.

EXPERT OPINION

There is no doubt that CADD has contributed to the discovery of novel anti-diabetic agents. However, there are still many limitations and challenges, such as lack of co-crystal complex, dynamic simulations, water, and metal ion treatment. In the near future, artificial intelligence (AI) may be a promising strategy to accelerate drug discovery and reduce costs by identifying candidates. Moreover, AlphaFold, a deep learning model that predicts the 3D structure of proteins, represents a considerable advancement in the structural prediction of proteins, especially in the absence of homologous templates for protein structures.

Review of in silico studies dedicated to the nuclear receptor family: Therapeutic prospects and toxicological concerns

Being in the center of both therapeutic and toxicological concerns, NRs are widely studied for drug discovery application but also to unravel the potential toxicity of environmental compounds such as pesticides, cosmetics or additives. High throughput screening campaigns (HTS) are largely used to detect compounds able to interact with this protein family for both therapeutic and toxicological purposes. These methods lead to a large amount of data requiring the use of computational approaches for a robust and correct analysis and interpretation. The output data can be used to build predictive models to forecast the behavior of new chemicals based on their in vitro activities. This atrticle is a review of the studies published in the last decade and dedicated to NR ligands in silico prediction for both therapeutic and toxicological purposes. Over 100 articles concerning 14 NR subfamilies were carefully read and analyzed in order to retrieve the most commonly used computational methods to develop predictive models, to retrieve the databases deployed in the model building process and to pinpoint some of the limitations they faced.

General Perspectives for the Treatment of Atherosclerosis

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Atherosclerosis, a cardiovascular disease, is at the top of the list among the diseases leading to death. Although the biochemical and pathophysiological cascades involved within the development of atherosclerosis have been identified clearly, its nature is quite complex to be treated with a single agent targeting a pathway. Therefore, many natural and synthetic compounds have been suggested for the treatment of the disease. The majority of the drugs employed target one of the single components of the pathological outcomes, resulting in many times less effective and longterm treatments. In most cases, treatment options prevent further worsening of the symptoms rather than a radical treatment. Consequently, the current review has been prepared to focus on the validated and non-validated targets of atherosclerosis as well as the alternative treatment options such as hydroxymethyl glutaryl coenzyme A (HMG-CoA) reductase inhibitors, acyl-CoA cholesterol acyl transferase (ACAT) inhibitors, lipoprotein lipase stimulants, bile acid sequestrants, and some antioxidants. Related to the topic, both synthetic compounds designed employing medicinal chemistry skills and natural molecules becoming more popular in drug development are scrutinized in this mini review.

Co-Incubation with PPARβ/δ Agonists and Antagonists Modeled Using Computational Chemistry: Effect on LPS Induced Inflammatory Markers in Pulmonary Artery

Peroxisome proliferator activated receptor beta/delta (PPARβ/δ) is a nuclear receptor ubiquitously expressed in cells, whose signaling controls inflammation. There are large discrepancies in understanding the complex role of PPARβ/δ in disease, having both anti- and pro-effects on inflammation. After ligand activation, PPARβ/δ regulates genes by two different mechanisms; induction and transrepression, the effects of which are difficult to differentiate directly. We studied the PPARβ/δ-regulation of lipopolysaccharide (LPS) induced inflammation (indicated by release of nitrite and IL-6) of rat pulmonary artery, using different combinations of agonists (GW0742 or L-165402) and antagonists (GSK3787 or GSK0660). LPS induced release of NO and IL-6 is not significantly reduced by incubation with PPARβ/δ ligands (either agonist or antagonist), however, co-incubation with an agonist and antagonist significantly reduces LPS-induced nitrite production and Nos2 mRNA expression. In contrast, incubation with LPS and PPARβ/δ agonists leads to a significant increase in Pdk-4 and Angptl-4 mRNA expression, which is significantly decreased in the presence of PPARβ/δ antagonists. Docking using computational chemistry methods indicates that PPARβ/δ agonists form polar bonds with His287, His413 and Tyr437, while antagonists are more promiscuous about which amino acids they bind to, although they are very prone to bind Thr252 and Asn307. Dual binding in the PPARβ/δ binding pocket indicates the ligands retain similar binding energies, which suggests that co-incubation with both agonist and antagonist does not prevent the specific binding of each other to the large PPARβ/δ binding pocket. To our knowledge, this is the first time that the possibility of binding two ligands simultaneously into the PPARβ/δ binding pocket has been explored. Agonist binding followed by antagonist simultaneously switches the PPARβ/δ mode of action from induction to transrepression, which is linked with an increase in Nos2 mRNA expression and nitrite production.

To Probe Full and Partial Activation of Human Peroxisome Proliferator-Activated Receptors by Pan-Agonist Chiglitazar Using Molecular Dynamics Simulations

Chiglitazar is a promising new-generation insulin sensitizer with low reverse effects for the treatment of type II diabetes mellitus (T2DM) and has shown activity as a nonselective pan-agonist to the human peroxisome proliferator-activated receptors (PPARs) (i.e., full activation of PPARγ and a partial activation of PPARα and PPARβ/δ). Yet, it has no high-resolution complex structure with PPARs and its detailed interactions and activation mechanism remain unclear. In this study, we docked chiglitazar into three experimentally resolved crystal structures of hPPAR subtypes, PPARα, PPARβ/δ, and PPARγ, followed by 3 μs molecular dynamics simulations for each system. Our MM-GBSA binding energy calculation revealed that chiglitazar most favorably bound to hPPARγ (-144.6 kcal/mol), followed by hPPARα (-138.0 kcal/mol) and hPPARβ (-135.9 kcal/mol), and the order is consistent with the experimental data. Through the decomposition of the MM-GBSA binding energy by residue and the use of two-dimensional interaction diagrams, key residues involved in the binding of chiglitazar were identified and characterized for each complex system. Additionally, our detailed dynamics analyses support that the conformation and dynamics of helix 12 play a critical role in determining the activities of the different types of ligands (e.g., full agonist vs. partial agonist). Rather than being bent fully in the direction of the agonist versus antagonist conformation, a partial agonist can adopt a more linear conformation and have a lower degree of flexibility. Our finding may aid in further development of this new generation of medication.

Therapeutic potential of PPARγ natural agonists in liver diseases

Peroxisome proliferator‐activated receptor gamma (PPARγ) is a vital subtype of the PPAR family. The biological functions are complex and diverse. PPARγ plays a significant role in protecting the liver from inflammation, oxidation, fibrosis, fatty liver and tumours. Natural products are a promising pool for drug discovery, and enormous research effort has been invested in exploring the PPARγ‐activating potential of natural products. In this manuscript, we will review the research progress of PPARγ agonists from natural products in recent years and probe into the application potential and prospects of PPARγ natural agonists in the therapy of various liver diseases, including inflammation, hepatic fibrosis, non‐alcoholic fatty liver and liver cancer.

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations. Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors. Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor-ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS's position in pharmaceutical research.

Molecular docking, 3D-QSAR and structural optimization on imidazo-pyridine derivatives dually targeting AT1 and PPARg

Telmisartan, a bifunctional agent of blood pressure lowering and glycemia reduction, was previously reported to antagonize angiotensin II type 1 (AT1) receptor and partially activate peroxisome proliferator-activated receptor γ (PPARγ) simultaneously. Through the modification to telmisartan, researchers designed and obtained imidazo-\pyridine derivatives with the IC₅₀s of 0.49∼94.1 nM against AT1 and EC₅₀s of 20∼3640 nM towards PPARγ partial activation. For minutely inquiring the interaction modes with the relevant receptor and analyzing the structure-activity relationships, molecular docking and 3D-QSAR (Quantitative structure-activity relationships) analysis of these imidazo-\pyridines on dual targets were conducted in this work. Docking approaches of these derivatives with both receptors provided explicit interaction behaviors and excellent matching degree with the binding pockets. The best CoMFA (Comparative Molecular Field Analysis) models exhibited predictive results of q²=0.553, r²=0.954, SEE=0.127, r²_pred=0.779 for AT1 and q²=0.503, r²=1.00, SEE=0.019, r²_pred=0.604 for PPARγ, respectively. The contour maps from the optimal model showed detailed information of structural features (steric and electrostatic fields) towards the biological activity. Combining the bioisosterism with the valuable information from above studies, we designed six molecules with better predicted activities towards AT1 and PPARγ partial activation. Overall, these results could be useful for designing potential dual AT1 antagonists and partial PPARγ agonists.

Design, sythesis and evaluation of a series of 3- or 4-alkoxy substituted phenoxy derivatives as PPARs agonists

Peroxisome proliferators-activated receptors (PPARα, γ and δ) are potentially effective targets for Type 2 diabetes mellitus therapy. The severe effects of known glitazones and the successfully approved agents (saroglitazar and lobeglitazone) motivated us to study novelly potent PPARs drugs with improved safety profile. In this work, we received 15 carboxylic acids based on the combination principle to integrate the polar head of bezafibrate with the hydrophobic tail of pioglitazone. Another 12 tetrazoles based on the bioisosterism principle were obtained accordingly. Furthermore, in vitro PPARs transactivation assays on these 3- or 4-alkoxy substituted phenoxy derivatives afforded six compounds. Interactions and binding stability from the docking analysis and 20 ns molecular dynamic simulations confirmed the representative compounds to be suitable and plausible for PPARs pockets. The above-mentioned results demonstrated that the compounds may be used as reference for further optimization for enhanced PPARs activities and wide safety range.

Identification of Potent Chloride Intracellular Channel Protein 1 Inhibitors from Traditional Chinese Medicine through Structure-Based Virtual Screening and Molecular Dynamics Analysis

Chloride intracellular channel 1 (CLIC1) is involved in the development of most aggressive human tumors, including gastric, colon, lung, liver, and glioblastoma cancers. It has become an attractive new therapeutic target for several types of cancer. In this work, we aim to identify natural products as potent CLIC1 inhibitors from Traditional Chinese Medicine (TCM) database using structure-based virtual screening and molecular dynamics (MD) simulation. First, structure-based docking was employed to screen the refined TCM database and the top 500 TCM compounds were obtained and reranked by X-Score. Then, 30 potent hits were achieved from the top 500 TCM compounds using cluster and ligand-protein interaction analysis. Finally, MD simulation was employed to validate the stability of interactions between each hit and CLIC1 protein from docking simulation, and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis was used to refine the virtual hits. Six TCM compounds with top MM-GBSA scores and ideal-binding models were confirmed as the final hits. Our study provides information about the interaction between TCM compounds and CLIC1 protein, which may be helpful for further experimental investigations. In addition, the top 6 natural products structural scaffolds could serve as building blocks in designing drug-like molecules for CLIC1 inhibition.

In silico identification of potential drug compound against Peroxisome proliferator-activated receptor-gamma by virtual screening and toxicity studies for the treatment of Diabetic Nephropathy

Diabetic Nephropathy is a serious complication of diabetes mellitus. Current therapeutic strategies of Diabetic Nephropathy are based on control of modifiable risks like hypertension, glucose levels, and dyslipidemia. Peroxisome proliferator activated receptor-gamma (PPAR-γ) is implicated in several metabolic syndromes including Diabetic Nephropathy, besides obesity, insulin insensitivity, dislipidemia, inflammation, and hypertension. In the present study, virtual screening of 617 compounds from two different public databases was done against PPAR-γ with an objective to find a possible lead compound. Two softwares, PyRx and iGEMDOCK, were used to achieve the docking accuracy in order to avoid loss of candidate compounds. Rosiglitazone (used to treat Diabetic Nephropathy) was taken as the standard compound. A total of 30 compounds with good binding affinity with PPAR-γ were selected for further filtering, on the basis of absorption, distribution, metabolism, excretion, and toxicity (ADMET). The interaction profiling of these 30 compounds, showed a minimum of one and maximum of three interactions with reference to rosiglitazone (SER-289, HIS-449, HIS-323, TYR-473). The fulfilling of ADMET analysis criteria of 30 compounds led to the selection of four compounds (ZINC ID 00181552, 00276456, 00298314, 00448009). Molecular dynamics simulation of these lead compounds in complex with PPAR-γ revealed that three of the four compounds formed a stable complex in the ligand-binding pocket of PPAR-γ during 20-ns simulation. Hence, these three (ZINC ID 00181552, 00276456, 00298314) of the four compounds are potential candidates for experimental validation of biological activity against PPAR-γ in future drug discovery studies.

Deciphering the Roles of Thiazolidinediones and PPAR in Bladder Cancer

The use of thiazolidinedione (TZD) therapy in type II diabetic patients has proven useful in the lowering of blood glucose levels. However, recent investigations have shown that there may be potential health concerns associated, including the risk of developing bladder cancer as well as complications in the cardiovasculature. TZDs are ligands for the nuclear receptor PPARγ, and activation causes lipid uptake and insulin sensitization, both of which are critical processes for diabetic patients whose bodies are unable to utilize insulin effectively. Several studies have shown that PPARγ/TZDs decrease IGF-1 levels and, thus, reduce cancer growth in carcinomas such as the pancreas, colon, liver, and prostate. However, other studies have shed light on the potential of the receptor as a biomarker for uroepithelial carcinomas, particularly due to its stimulatory effect on migration of bladder cancer cells. Furthermore, PPARγ may provide the tumor-promoting microenvironment by de novo synthesis of nutrients that are needed for bladder cancer development. In this review, we closely examine the TZD class of drugs and their effects on PPARγ in patient studies along with additional molecular factors that are positive modulators, such as protein phosphatase 5 (PP5), which may have considerable implications for bladder cancer therapy.

Effects of Tocotrienols on Insulin Secretion-Associated Genes Expression of Rat Pancreatic Islets in a Dynamic Culture

Tocotrienols (T3) are well-known for their antioxidant properties besides showing therapeutic potential in clinical complications such as hyperlipidemia induced by diabetes. The aim of this study was to determine the effects of δ-T3, γ-T3, and α-T3 on insulin secretion-associated genes expression of rat pancreatic islets in a dynamic culture. Pancreatic islets freshly isolated from male Wistar rats were treated with T3 for 1 h at 37°C in a microfluidic system with continuous operation. The cells were collected for total RNA extraction and reverse-transcribed, followed by measurement of insulin secretion-associated genes expression using quantitative real-time polymerase chain reaction. Molecular docking experiments were performed to gain insights on how the T3 bind to the receptors. Short-term exposure of δ- and γ-T3 to pancreatic β cells in a stimulant glucose condition (16.7 mM) significantly regulated preproinsulin mRNA levels and insulin gene transcription. In contrast, α-T3 possessed less ability in the activation of insulin synthesis level. Essentially, potassium chloride (KCl), a β cell membrane depolarising agent added into the treatment further enhanced the insulin production. δ- and γ-T3 revealed significantly higher quantitative expression in most of the insulin secretion-associated genes groups containing 16.7 mM glucose alone and 16.7 mM glucose with 30 mM KCl ranging from 600 to 1200 μM (p < 0.05). The findings suggest the potential of δ-T3 in regulating insulin synthesis and glucose-stimulated insulin secretion through triggering pathway especially in the presence of KCl.

Multitargeted bioactive ligands for PPARs discovered in the last decade

Type 2 diabetes took insulin resistance as the main clinical manifestation. PPARs have been reported to be the therapeutic targets of metabolic disorders, such as obesity, hypertension, diabetes, and cardiovascular disease. Previously, PPARγ agonist rosiglitazone was restricted in clinic due to cardiomyocytes infarction, weight gain, and other serious side-effects, which were mainly due to the single and selective PPARγ agonism. In recent years, multitarget-directed PPAR agonists with synergistic reaction as well as fewer side-effect have been the hot topic in designing promising agents. In this review, we updated and generalized the development of PPARγ partial agonists, PPARγ antagonists, PPARα/γ dual agonists, PPARδ partial agonists, PPARδ antagonists, PPARα/δ dual agonists, PPARγ/δ dual agonists, and PPARα/γ/δ pan-agonists published in recent decade. Most of these molecules were modified from known structures or came from high-throughput screening. Among these molecules, some were expected to be promising drugs against metabolic disorders, while others seemed to provide new insight for designing novel PPAR agents.

Ligands for the Nuclear Peroxisome Proliferator-Activated Receptor Gamma

Nuclear receptors are ligand-activated transcription factors, which represent a primary class of drug targets. The nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ) is a key player in various biological processes. PPARγ is widely known as the target protein of the thiazolidinediones for treating type 2 diabetes. Moreover, PPARγ ligands can induce anti-inflammatory and potentially additional beneficial effects. Recent mechanistic insights of PPARγ modulation give hope the next generation of efficient PPARγ-based drugs with fewer side effects can be developed. Furthermore, chemical approaches that make use of synergistic action of combinatorial ligands are promising alternatives for providing tailored medicine. Lessons learned from fine-tuning the action of PPARγ can provide avenues for efficient molecular intervention via many other nuclear receptors to combat common diseases.

In silico modelling of prostacyclin and other lipid mediators to nuclear receptors reveal novel thyroid hormone receptor antagonist properties

Prostacyclin (PGI2) is a key mediator involved in cardiovascular homeostasis, acting predominantly on two receptor types; cell surface IP receptor and cytosolic peroxisome proliferator activated receptor (PPAR) β/δ. Having a very short half-life, direct methods to determine its long term effects on cells is difficult, and little is known of its interactions with nuclear receptors. Here we used computational chemistry methods to investigate the potential for PGI2, beraprost (IP receptor agonist), and GW0742 (PPARβ/δ agonist), to bind to nuclear receptors, confirmed with pharmacological methods. In silico screening predicted that PGI2, beraprost, and GW0742 have the potential to bind to different nuclear receptors, in particular thyroid hormone β receptor (TRβ) and thyroid hormone α receptor (TRα). Docking analysis predicts a binding profile to residues thought to have allosteric control on the TR ligand binding site. Luciferase reporter assays confirmed that beraprost and GW0742 display TRβ and TRα antagonistic properties; beraprost IC50 6.3 × 10(-5)mol/L and GW0742 IC50 4.9 × 10(-6) mol/L. Changes to triiodothyronine (T3) induced vasodilation of rat mesenteric arteries measured on the wire myograph were measured in the presence of the TR antagonist MLS000389544 (10(-5) mol/L), beraprost (10(-5) mol/L) and GW0742 (10(-5) mol/L); all significantly inhibited T3 induced vasodilation compared to controls. We have shown that both beraprost and GW0742 exhibit TRβ and TRα antagonist behaviour, and suggests that PGI2 has the ability to affect the long term function of cells through binding to and inactivating thyroid hormone receptors.