3D pharmacophore based virtual screening of T-type calcium channel blockers

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.

Computational methods in drug discovery

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

5-HT1A receptor pharmacophores to screen for off-target activity of α1-adrenoceptor antagonists

The α1-adrenoceptors (α1-ARs), in particular the α1A-AR subtype, are current therapeutic targets of choice for the treatment of urogenital conditions, such as benign prostatic hyperplasia (BPH). Due to the similarity between the transmembrane domains of the α1-AR subtypes, and the serotonin receptor subtype 1A (5-HT1A-R), currently used α1-AR subtype-selective drugs to treat BPH display considerable off-target affinity for the 5-HT1A-R, leading to side effects. We describe the construction and validation of pharmacophores for 5-HT1A-R agonists and antagonists. Through the structural diversity of the training sets used in their development, these pharmacophores define the properties of a compound needed to bind to 5-HT1A receptors. Using these and previously published pharmacophores in virtual screening and profiling, we have identified unique chemical compounds (hits) that fit the requirements to bind to our target, the α1A-AR, selectively over the off-target, the 5-HT1A-R. Selected hits have been obtained and their affinities for α1A-AR, α1B-AR and 5-HT1A-R determined in radioligand binding assays, using membrane preparations which contain human receptors expressed individually. Three of the tested hits demonstrate statistically significant selectivity for α1A-AR over 5-HT1A-R. All seven tested hits bind to α1A-AR, with two compounds displaying K i values below 1 μM, and a further two K i values of around 10 μM. The insights and knowledge gained through the development of the new 5-HT1A-R pharmacophores will greatly aid in the design and synthesis of derivatives of our lead compound, and allow the generation of more efficacious and selective ligands.

Synthesis and pharmacological evaluation of 1-alkyl-N-[(1R)-1-(4-fluorophenyl)-2-methylpropyl]piperidine-4-carboxamide derivatives as novel antihypertensive agents

We synthesized and evaluated inhibitory activity against T-type Ca(2+) channels for a series of 1-alkyl-N-[(1R)-1-(4-fluorophenyl)-2-methylpropyl]piperidine-4-carboxamide derivatives. Structure-activity relationship studies have revealed that the isopropyl substituent at the benzylic position plays an important role in exerting potent inhibitory activity, and the absolute configuration of the benzylic position was found to be opposite that of mibefradil, which was first launched as a new class of T-type Ca(2+) channel blocker. Oral administration of N-[(1R)-1-(4-fluorophenyl)-2-methylpropyl]-1-[2-(3-methoxyphenyl)ethyl]piperidine-4-carboxamide (17f) lowered blood pressure in spontaneously hypertensive rats without inducing reflex tachycardia, an adverse effect often caused by traditional L-type Ca(2+) channel blockers.

Pyridyl amides as potent inhibitors of T-type calcium channels

A novel series of amide T-type calcium channel antagonists were prepared and evaluated using in vitro and in vivo assays. Optimization of the screening hit 3 led to identification of the potent and selective T-type antagonist 37 that displayed in vivo efficacy in rodent models of epilepsy and sleep.

Comparison of three preprocessing filters efficiency in virtual screening: identification of new putative LXRbeta regulators as a test case

In silico screening methodologies are widely recognized as efficient approaches in early steps of drug discovery. However, in the virtual high-throughput screening (VHTS) context, where hit compounds are searched among millions of candidates, three-dimensional comparison techniques and knowledge discovery from databases should offer a better efficiency to finding novel drug leads than those of computationally expensive molecular dockings. Therefore, the present study aims at developing a filtering methodology to efficiently eliminate unsuitable compounds in VHTS process. Several filters are evaluated in this paper. The first two are structure-based and rely on either geometrical docking or pharmacophore depiction. The third filter is ligand-based and uses knowledge-based and fingerprint similarity techniques. These filtering methods were tested with the Liver X Receptor (LXR) as a target of therapeutic interest, as LXR is a key regulator in maintaining cholesterol homeostasis. The results show that the three considered filters are complementary so that their combination should generate consistent compound lists of potential hits.

Synthesis and biological evaluation of 1,4-diazepane derivatives as T-type calcium channel blockers

We have synthesized and biologically evaluated 1,4-diazepane derivatives as T-type calcium channel blockers. In this study, we discovered compound 4s, a potential T-type calcium channel blocker with good selectivity over hERG and N-type calcium channels. In addition, it exhibited favorable pharmacokinetic characteristics for further investigation of T-type calcium channel related diseases.

LigMatch: a multiple structure-based ligand matching method for 3D virtual screening

We have developed a new virtual screening (VS) method called LigMatch and evaluated its performance on 13 protein targets using a filtered and clustered version of the directory of useful decoys (DUD). The method uses 3D structural comparison to a crystallographically determined ligand in a bioactive 'template' conformation, using a geometric hashing method, in order to prioritize each database compound. We show that LigMatch outperforms several other widely used VS methods on the 13 DUD targets. We go on to demonstrate that improved VS performance can be gained from using multiple, structurally diverse templates rather than a single template ligand for a particular protein target. In this case, a 2D fingerprint-based method is used to select a ligand template from a set of known bioactive conformations. Furthermore, we show that LigMatch performs well even in the absence of 2D similarity to the template ligands, thereby demonstrating its robustness with respect to purely 2D methods and its potential for scaffold hopping.

3D QSAR studies on 3,4-dihydroquinazolines as T-type calcium channel blocker by comparative molecular similarity indices analysis (CoMSIA)

A comparative molecular similarity indices analysis (CoMSIA) of a set of 42 3,4-dihydroquinazolines have been performed to find out the pharmacophore elements for T-type calcium channel blocking activity. The most potent compound, 33 (KYS05090) was used to align the molecules. As a result, we obtained 3D QSAR model which provided good predictivity for the training set (q(2)=0.642, r(2)=0.874) and the test set (r(pred)(2)=0.884). This model would guide the design of new chemical entities potentially having high potency.

Discovery of potent inhibitors for phosphodiesterase 5 by virtual screening and pharmacophore analysis

AIM

To explore the potent inhibitor from one of the Traditional Chinese medicine (TCM), Epimedium sagittatum.

METHODS

We predicted the potent compound, ES03b, de novo evolution from the four Epimedium sagittatum components were verified by molecular docking, pharmacophore analysis, and analysis of quantitative structure-activity relationship (QSAR) model, which was constructed by multiple linear regression.

RESULTS

ES03b was chosen to undergo drug modification via de novo evolution. By analyzing the pharmacophore features, we found that the hydrophobic core in the binding site and the hydrogen bond generated at Asn663 played key roles in designing PDE5 inhibitors. ES03b generated 49 diversities (Evo01-49). Evo48 had high activity in prediction. Although the value of prediction was overestimated, Evo48 was suggested as the potent lead.

CONCLUSION

In this study, we showed that the hydrophobic core in the binding site and hydrogen bond production on Asn663 played key roles to design PDE5 inhibitors. From several require validation analysis, Evo48 was suggested to be a potent inhibitor.

Lead Discovery Using Virtual Screening

The practice of virtual screening (VS) to identify chemical leads to known or novel targets is becoming a core function of the computational chemist within industry. By employing a range of techniques, when attempting to identify compounds with activity against a biological target, a small focused subset of a larger collection of compounds can be identified and tested, often with results much better than selecting a similar number of compounds at random. We will review the key methods available, their relative success, and provide practical insights into best practices and key gaps. We will also argue that the capability of VS methods has grown to a point where fuller integration with experimental methods, including HTS, could increase the effectiveness of both.

Discovery of potent T-type calcium channel blocker

The intensive SAR study of 3,4-dihydroquinazoline series led to the most potent compound 10 (KYS05090: IC(50)=41+/-1 nM) against T-type calcium channel and its potency is nearly comparable to that of Kurtoxin. As a small organic molecule, this compound showed the highest blocking activity reported to date.

Towards the discovery of novel T-type calcium channel blockers

Despite their presence in many tissues and their potential implication in various disease states, low-voltage activated T-type calcium channels (T-channels) have only recently become targets of interest. Unfortunately, the lack of selective T-channel blockers has hampered further characterisation of these channels. The recent availability of cloned T-channels, the Ca(V)3 proteins, facilitates identification of novel T-channel blockers. Also, studies performed in knockout animals have fostered novel interest. Selective inhibition of T-channels may have clinical importance in cardiovascular diseases, some forms of epilepsy, sleep disorders, pain and possibly cancer. This review focuses on novel research approaches to discover potent and selective T-channel modulators. These molecules may be potential drugs for treating human diseases, as well as important tools to decipher the physiological role of these channels.

MED-SuMoLig: A New Ligand-Based Screening Tool for Efficient Scaffold Hopping

The identification of small molecules with selective bioactivity, whether intended as potential therapeutics or as tools for experimental research, is central to progress in medicine and in the life sciences. To facilitate such study, we have developed a ligand-based program well-suited for effective screening of large compound collections. This package, MED-SuMoLig, combines a SMARTS-driven substructure search aiming at 3D pharmacophore profiling and computation of the local atomic density of the compared molecules. The screening utility was then investigated using 52 diverse active molecules (against CDK2, Factor Xa, HIV-1 protease, neuraminidase, ribonuclease A, and thymidine kinase) merged to a library of about 40,000 putative inactive (druglike) compounds. In all cases, the program recovered more than half of the actives in the top 3% of the screened library. We also compared the performance of MED-SuMoLig with that of ChemMine or of ROCS and found that MED-SuMoLig outperformed both methods for CDK2 and Factor Xa in terms of enrichment rates or performed equally well for the other targets.