Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening

Dissecting the Role of the Hydroxyl Moiety at C14 in (+)-Opioid-Based TLR4 Antagonists via Wet-Lab Experiments and Molecular Dynamics Simulations

Toll-like receptor 4 (TLR4) is pivotal as an innate immune receptor, playing a critical role in mediating neuropathic pain and drug addiction through its regulation of the neuroinflammatory response. The nonclassical (+)-opioid isomers represent a unique subset of TLR4 antagonists known for their effective blood-brain barrier permeability. Despite growing interest in the structure-activity relationship of these (+)-opioid-based TLR4 antagonists, the specific impact of heteroatoms on their TLR4 antagonistic activities has not been fully explored. This study investigated the influence of the hydroxyl group at C14 in six (+)-opioid TLR4 antagonists (1-6) using wet-lab experiments and in silico simulations. The corresponding C14-deoxy derivatives (7-12) were synthesized, and upon comparison with their corresponding counterparts (1-6), it was discovered that their TLR4 antagonistic activities were significantly diminished. Molecular dynamics simulations showed that the (+)-opioid TLR4 antagonists (1-6) possessed more negative binding free energies to the TLR4 coreceptor MD2, which was responsible for ligand recognition. This was primarily attributed to the formation of a hydrogen bond between the hydroxyl group at the C-14 position of the antagonists (1-6) and the R90 residue of MD2 during the binding process. Such an interaction facilitated the entry and subsequent binding of these molecules within the MD2 cavity. In contrast, the C14-deoxy derivatives (7-12), lacking the hydroxyl group at the C-14 position, missed this crucial hydrogen bond interaction with the R90 residue of MD2, leading to their egression from the MD2 cavity during simulations. This study underscores the significant role of the C14 hydroxyl moiety in enhancing the effectiveness of (+)-opioid TLR4 antagonists, which provides insightful guidance for designing future (+)-isomer opioid-derived TLR4 antagonists.

Structure-activity relationship of pharmacophores and toxicophores: the need for clinical strategy

OBJECTIVES

Sometimes clinical efficacy and potential risk of therapeutic and toxic agents are difficult to predict over a long period of time. Hence there is need for literature search with a view to assessing cause of toxicity and less efficacy of drugs used in clinical practice.

METHOD

Hence literatures were searched for physicochemical properties, chemical formulas, molecular masses, pH values, ionization, receptor type, agonist and antagonist, therapeutic, toxic and structure-activity relationship of chemical compounds with pharmacophore and toxicophore, with a view to identifying high efficacious and relative low toxic agents. Inclusion criteria were manuscripts published on PubMed, Scopus, Web of Science, PubMed Central, Google Scholar among others, between 1960 and 2023. Keywords such as pharmacophore, toxicophore, structure-activity-relationship and disease where also searched. The exclusion criteria were the chemicals that lack pharmacophore, toxicophore and manuscripts published before 1960.

RESULTS

Findings have shown that pharmacophore and toxicophore functional groups determine clinical efficacy and safety of therapeutics, but if they overlap therapeutic and toxicity effects go concurrently. Hence the functional groups, dose, co-administration and concentration of drugs at receptor, drug-receptor binding and duration of receptor binding are the determining factors of pharmacophore and toxicophore activity. Molecular mass, chemical configuration, pH value, receptor affinity and binding capacity, multiple pharmacophores, hydrophilic/lipophilic nature of the chemical contribute greatly to functionality of pharmacophore and toxicophore.

CONCLUSION

Daily single therapy, avoidance of reversible pharmacology, drugs with covalent adduct, maintenance of therapeutic dose, and the use of multiple pharmacophores for terminal diseases will minimize toxicity and improve efficacy.

Decoding the κ Opioid Receptor (KOR): Advancements in Structural Understanding and Implications for Opioid Analgesic Development

The opioid crisis in the United States is a significant public health issue, with a nearly threefold increase in opioid-related fatalities between 1999 and 2014. In response to this crisis, society has made numerous efforts to mitigate its impact. Recent advancements in understanding the structural intricacies of the κ opioid receptor (KOR) have improved our knowledge of how opioids interact with their receptors, triggering downstream signaling pathways that lead to pain relief. This review concentrates on the KOR, offering crucial structural insights into the binding mechanisms of both agonists and antagonists to the receptor. Through comparative analysis of the atomic details of the binding site, distinct interactions specific to agonists and antagonists have been identified. These insights not only enhance our understanding of ligand binding mechanisms but also shed light on potential pathways for developing new opioid analgesics with an improved risk-benefit profile.

A New Advanced Approach: Design and Screening of Affinity Peptide Ligands Using Computer Simulation Techniques

Peptides acquire target affinity based on the combination of residues in their sequences and the conformation formed by their flexible folding, an ability that makes them very attractive biomaterials in therapeutic, diagnostic, and assay fields. With the development of computer technology, computer-aided design and screening of affinity peptides has become a more efficient and faster method. This review summarizes successful cases of computer-aided design and screening of affinity peptide ligands in recent years and lists the computer programs and online servers used in the process. In particular, the characteristics of different design and screening methods are summarized and categorized to help researchers choose between different methods. In addition, experimentally validated sequences are listed, and their applications are described, providing directions for the future development and application of computational peptide screening and design.

Three-Dimensional Structural Insights Have Revealed the Distinct Binding Interactions of Agonists, Partial Agonists, and Antagonists with the µ Opioid Receptor

The United States is experiencing the most profound and devastating opioid crisis in history, with the number of deaths involving opioids, including prescription and illegal opioids, continuing to climb over the past two decades. This severe public health issue is difficult to combat as opioids remain a crucial treatment for pain, and at the same time, they are also highly addictive. Opioids act on the opioid receptor, which in turn activates its downstream signaling pathway that eventually leads to an analgesic effect. Among the four types of opioid receptors, the µ subtype is primarily responsible for the analgesic cascade. This review describes available 3D structures of the µ opioid receptor in the protein data bank and provides structural insights for the binding of agonists and antagonists to the receptor. Comparative analysis on the atomic details of the binding site in these structures was conducted and distinct binding interactions for agonists, partial agonists, and antagonists were observed. The findings in this article deepen our understanding of the ligand binding activity and shed some light on the development of novel opioid analgesics which may improve the risk benefit balance of existing opioids.

Application of computational methods for class A GPCR Ligand discovery

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development due to their role in transmitting cellular signals in a multitude of biological processes. Of the six classes categorizing GPCR (A, B, C, D, E, and F), class A contains the largest number of therapeutically relevant GPCR. Despite their importance as drug targets, many challenges exist for the discovery of novel class A GPCR ligands serving as drug precursors. Though knowledge of the structural and functional characteristics of GPCR has grown significantly over the past 20 years, a large portion of GPCR lack reported, experimentally determined structures. Furthermore, many GPCR have no known endogenous and/or synthetic ligands, limiting further exploration of their biochemical, cellular, and physiological roles. While many successes in GPCR ligand discovery have resulted from experimental high-throughput screening, computational methods have played an increasingly important role in GPCR ligand identification in the past decade. Here we discuss computational techniques applied to GPCR ligand discovery. This review summarizes class A GPCR structure/function and provides an overview of many obstacles currently faced in GPCR ligand discovery. Furthermore, we discuss applications and recent successes of computational techniques used to predict GPCR structure as well as present a summary of ligand- and structure-based methods used to identify potential GPCR ligands. Finally, we discuss computational hit list generation and refinement and provide comprehensive workflows for GPCR ligand identification.

Multi-stage virtual screening of natural products against p38α mitogen-activated protein kinase: predictive modeling by machine learning, docking study and molecular dynamics simulation

p38α is a mitogen-activated protein kinase (MAPK), and the signaling pathways involved are closely related to the inflammation, apoptosis and differentiation of cells, which also makes it an attractive target for drug discovery. With the high efficiency and low cost, virtual screening technology is becoming an indispensable part of drug development. In this study, a novel multi-stage virtual screening method based on machine learning, molecular docking and molecular dynamics simulation was developed to identify p38α MAPK inhibitors from natural products in ZINC database, which improves the prediction accuracy by considering and utilizing both ligand and receptor information compared to any individual approach. Ultimately, we screened out two candidate inhibitors with acceptable ADMET properties (ZINC4260400 and ZINC8300300). Among the generated machine learning models, Random Forest (RF) and Support Vector Machine (SVM) performed better, with the area under the receiver operating characteristic curve (AUC) values of 0.932 and 0.931 on the test set, as well as 0.834 and 0.850 on the external validation set. In addition, the results of molecular docking and ADMET prediction showed that two compounds with appropriate pharmacokinetic properties had binding free energies less than −8.0 kcal/mol for the target protein, and the results of molecular dynamics simulations further confirmed that they were stable during the process of inhibition.

Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design

Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry—many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry–virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.

In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands

The kappa opioid receptor (KOR) represents an attractive target for the development of drugs as potential antidepressants, anxiolytics and analgesics. A robust computational approach may guarantee a reduction in costs in the initial stages of drug discovery, novelty and accurate results. In this work, a virtual screening workflow of a library consisting of ~6 million molecules was set up, with the aim to find potential lead compounds that could manifest activity on the KOR. This in silico study provides a significant contribution in the identification of compounds capable of interacting with a specific molecular target. The main computational techniques adopted in this experimental work include: (i) virtual screening; (ii) drug design and leads optimization; (iii) molecular dynamics. The best hits are tripeptides prepared via solution phase peptide synthesis. These were tested in vivo, revealing a good antinociceptive effect after subcutaneous administration. However, further work is due to delineate their full pharmacological profile, in order to verify the features predicted by the in silico outcomes.

Direct interaction between ABCA1 and HIV-1 Nef: Molecular modeling and virtual screening for inhibitors

HIV-1 infection impairs cellular cholesterol efflux by downmodulating the cholesterol transporter ABCA1, leading to metabolic co-morbidities like cardio-vascular disease. The main mechanism of this effect is impairment by the HIV-1 protein Nef of the ABCA1 interaction with the endoplasmic reticulum chaperone calnexin, which leads to a block in ABCA1 maturation followed by its degradation. However, ABCA1 is also downmodulated by Nef delivered with the extracellular vesicles, suggesting involvement of a direct Nef:ABCA1 interaction at the plasma membrane. Here, we present an optimized model of the Nef:ABCA1 interaction, which identifies interaction sites and provides an opportunity to perform a virtual screening for potential inhibitors. Interestingly, the predicted sites on Nef involved in the ABCA1 interaction overlap with those involved in the interaction with calnexin. The compounds previously shown to block Nef:calnexin interaction were among the top ranking ligands in docking simulations with ABCA1-interacting sites on Nef, suggesting the possibility that both interactions can be inhibited by the same chemical compounds. This study identifies a series of compounds for potential development as inhibitors of Nef-mediated co-morbidities of HIV infection.

Endogenous opiates and behavior: 2019

This paper is the forty-second consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2019 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

Identification of potential inhibitors of Schistosoma mansoni purine nucleoside phosphorylase from neolignan compounds using molecular modelling approaches

Schistosomiasis is a parasitic disease that is part of the neglected tropical diseases (NTDs), which cause significant levels of morbidity and mortality in millions of people throughout the world. The enzyme purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) represents a potential target for discovering new agents, and neolignans stand out as an important class of compounds. In this work, molecular modeling studies and biological assays of a set of neolignans were conducted against the PNP enzymes of the parasite and the human homologue (HssPNP). The results of the molecular docking described that the neolignans showed good complementarity by the active site of SmPNP. Molecular dynamics (MD) studies revealed that both complexes (Sm/HssPNP - neolignan compounds) were stable by analyzing the root mean square deviation (RMSD) values, and the binding free energy values suggest that the selected structures can interact and inhibit the catalytic activity of the SmPNP. Finally, the biological assay indicated that the selected neolignans presented a better molecular profile of inhibition compared to the human enzyme, as these ligands did not have the capacity to inhibit enzymatic activity, indicating that these compounds are promising candidates and that they can be used in future research in chemotherapy for schistosomiasis.Communicated by Ramaswamy H. Sarma.

Effects of N-Substituents on the Functional Activities of Naltrindole Derivatives for the δ Opioid Receptor: Synthesis and Evaluation of Sulfonamide Derivatives

We have recently reported that N-alkyl and N-acyl naltrindole (NTI) derivatives showed activities for the δ opioid receptor (DOR) ranging widely from full inverse agonists to full agonists. We newly designed sulfonamide-type NTI derivatives in order to investigate the effects of the N-substituent on the functional activities because the side chain and S=O part in the sulfonamide moiety located in spatially different positions compared with those in the alkylamine and amide moieties. Among the tested compounds, cyclopropylsulfonamide 9f (SYK-839) was the most potent full inverse agonist for the DOR, whereas phenethylsulfonamide 9e (SYK-901) showed full DOR agonist activity with moderate potency. These NTI derivatives are expected to be useful compounds for investigation of the molecular mechanism inducing these functional activities.

Antinociceptive Activity of Chemical Components of Essential Oils That Involves Docking Studies: A Review

INTRODUCTION

Pain is considered an unpleasant sensory and emotional experience, being considered as one of the most important causes of human suffering. Computational chemistry associated with bioinformatics has stood out in the process of developing new drugs, through natural products, to manage this condition.

OBJECTIVE

To analyze, through literature data, recent molecular coupling studies on the antinociceptive activity of essential oils and monoterpenes.

DATA SOURCE

Systematic search of the literature considering the years of publications between 2005 and December 2019, in the electronic databases PubMed and Science Direct.

ELIGIBILITY CRITERIA

Were considered as criteria of 1) Biological activity: non-clinical effects of an OE and/or monoterpenes on antinociceptive activity based on animal models and in silico analysis, 2) studies with plant material: chemically characterized essential oils and/or their constituents isolated, 3) clinical and non-clinical studies with in silico analysis to assess antinociceptive activity, 4) articles published in English. Exclusion criteria were literature review, report or case series, meta-analysis, theses, dissertations, and book chapter.

RESULTS

Of 16,006 articles, 16 articles fulfilled all the criteria. All selected studies were non-clinical. The most prominent plant families used were Asteraceae, Euphorbiaceae, Verbenaceae, Lamiaceae, and Lauraceae. Among the phytochemicals studied were α-Terpineol, 3-(5-substituted-1,3,4-oxadiazol-2-yl)-N'-[2-oxo-1,2-dihydro-3H-indol-3-ylidene] propane hydrazide, β-cyclodextrin complexed with citronellal, (-)-α-bisabolol, β-cyclodextrin complexed with farnesol, and p-Cymene. The softwares used for docking studies were Molegro Virtual Docker, Sybyl®X, Vlife MDS, AutoDock Vina, Hex Protein Docking, and AutoDock 4.2 in PyRx 0.9. The molecular targets/complexes used were Nitric Oxide Synthase, COX-2, GluR2-S1S2, TRPV1, β-CD complex, CaV1, CaV2.1, CaV2.2, and CaV2.3, 5-HT receptor, delta receptor, kappa receptor, and MU (μ) receptor, alpha adrenergic, opioid, and serotonergic receptors, muscarinic receptors and GABAA opioid and serotonin receptors, 5-HT3 and M2 receptors. Many of the covered studies used molecular coupling to investigate the mechanism of action of various compounds, as well as molecular dynamics to investigate the stability of protein-ligand complexes.

CONCLUSIONS

The studies revealed that through the advancement of more robust computational techniques that complement the experimental studies, they may allow some notes on the identification of a new candidate molecule for therapeutic use.

Pereira C, Stefanucci A, Mollica A, Zengin G, Llorent-Martínez EJ, Castilho PC, Custódio L. Phenolic Profile, Toxicity, Enzyme Inhibition, In Silico Studies, and Antioxidant Properties of Cakile maritima Scop. (Brassicaceae) from Southern Portugal

Cakile maritima Scop. (sea rocket) is an edible halophyte plant with several ethnomedicinal uses. This work reports the chemical profile and bioactivities of food grade extracts from sea rocket organs. Toxicity was determined on mammalian cells, and phenolic profiling and the quantitation of the main metabolites were made by high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS). Enzymatic inhibition was determined towards acetyl- and butyrylcholinesterase (AChE, BuChE), α-glucosidase, α-amylase, and tyrosinase. Docking studies were performed to tyrosinase, on the major metabolites, and samples were tested for antioxidant properties. Extracts were not toxic, were constituted mainly by flavonoids, and some compounds (roseoside and oleuropein) are here described for the first time in the species. The aerial organs' ethanol extract had relevant activity towards 2,2-diphenyl-1-picrylhydrazyl [DPPH, half maximal inhibitory concentration (IC50) = 0.59 mg/mL], and ferric-reducing activity power (FRAP, IC50 = 0.99 mg/mL). All samples were more active towards AChE than on BuChE. The ethanol fruits' extract inhibited α-glucosidase [2.19 mmol of equivalent of acarbose (ACAE)/g]. Samples were active against tyrosinase, especially the aerial organs' ethanol extracts [25.9 mg of equivalent of kojic acid (KAE)/g]. Quercetin and kaempferol glycosides fit well into the enzymatic pocket of tyrosinase. Our results suggest sea rocket as a candidate to be further explored as a source of bioactive products.