Pharmacophore Modeling of Substituted 1,2,4-Trioxanes for Quantitative Prediction of their Antimalarial Activity

Recent advances in the synthesis and antimalarial activity of 1,2,4-trioxanes

The increasing resistance of various malarial parasite strains to drugs has made the production of a new, rapid-acting, and efficient antimalarial drug more necessary, as the demand for such drugs is growing rapidly. As a major global health concern, various methods have been implemented to address the problem of drug resistance, including the hybrid drug concept, combination therapy, the development of analogues of existing medicines, and the use of drug resistance reversal agents. Artemisinin and its derivatives are currently used against multidrug- resistant P. falciparum species. However, due to its natural origin, its use has been limited by its scarcity in natural resources. As a result, finding a substitute becomes more crucial, and the peroxide group in artemisinin, responsible for the drugs biological action in the form of 1,2,4-trioxane, may hold the key to resolving this issue. The literature suggests that 1,2,4-trioxanes have the potential to become an alternative to current malaria drugs, as highlighted in this review. This is why 1,2,4-trioxanes and their derivatives have been synthesized on a large scale worldwide, as they have shown promising antimalarial activity in vivo and in vitro against Plasmodium species. Consequently, the search for a more convenient, environment friendly, sustainable, efficient, and effective synthetic pathway for the synthesis of 1,2,4-trioxanes continues. The aim of this work is to provide a comprehensive analysis of the synthesis and mechanism of action of 1,2,4-trioxanes. This systematic review highlights the most recent summaries of derivatives of 1,2,4-trioxane compounds and dimers with potential antimalarial activity from January 1988 to 2023.

Identification of 3-((1-(Benzyl(2-hydroxy-2-phenylethyl)amino)-1-oxo-3-phenylpropan-2-yl)carbamoyl)pyrazine-2-carboxylic Acid as a Potential Inhibitor of Non-Nucleosidase Reverse Transcriptase Inhibitors through InSilico Ligand- and Structure-Based Approaches

Non-nucleosidase reverse transcriptase inhibitors (NNRTIs) are highly promising agents for use in highly effective antiretroviral therapy. We implemented a rational approach for the identification of promising NNRTIs based on the validated ligand- and structure-based approaches. In view of our state-of-the-art techniques in drug design and discovery utilizing multiple modeling approaches, we report here, for the first time, quantitative pharmacophore modeling (HypoGen), docking, and in-house database screening approaches in the identification of potential NNRTIs. The validated pharmacophore model with three hydrophobic groups, one aromatic ring group, and a hydrogen-bond acceptor explains the interactions at the active site by the inhibitors. The model was implemented in pharmacophore-based virtual screening (in-house and commercially available databases) and molecular docking for prioritizing the potential compounds as NNRTI. The identified leads are in good corroboration with binding affinities and interactions as compared to standard ligands. The model can be utilized for designing and identifying the potential leads in the area of NNRTIs.

Detection Method of Environmentally Friendly Non-POP PBDEs by Derivatization-Enhanced Raman Spectroscopy Using the Pharmacophore Model

Background:

Polybrominated diphenyl ethers (PBDEs) are dangerous for the environment and human health because of their persistent organic pollutant (POP) characteristics, which have attracted extensive research attention. Raman spectroscopy is a simple highly sensitive detection operation. This study was performed to obtain environmentally friendly non-POP PBDE derivatives with simple detection-based molecular design and provide theoretical support for establishing enhanced Raman spectroscopic detection techniques.

Methods:

A three-dimensional quantitative structure-activity relationship (3DQSAR) pharmacophore model of characteristic PBDE Raman spectral was established using 20 and 10 PBDEs as training and test sets, respectively. Full-factor experimental design was used to modify representative commercial PBDEs, and their flame retardancy and POP characteristics were evaluated.

Results:

The pharmacophore model (Hypo1) exhibited good predictive ability with the largest correlation coefficient (R2) of 0.88, the smallest root mean square (RMS) value of 0.231, and total cost of 81.488 with a configuration value of 12.56 (˂17).74 monosubstituted and disubstituted PBDE derivatives were obtained based on the Hypo 1 pharmacophore model and full-factor experimental design auxiliary. Twenty PBDE derivatives were screened, and their flame-retardant capabilities were enhanced and their migration and bio-concentration were reduced (log(KOW) <5), with unchanged toxicity and high biodegradability. The Raman spectral intensities increased up to 380%. In addition, interference analysis of the Raman peaks by group frequency indicated that the 20 PBDE derivatives were easily detected with no interference in gaseous environments.

Conclusion:

Nine pharmacophore models were constructed in this study; Hypo 1 was the most accurate. Twenty PBDE derivatives showed Raman spectral intensities increased up to 380%; these were classified as new non-POP environmentally friendly flame retardants with low toxicity, low migration, good biodegradability, and low bio-concentrations. 2D QSAR analysis showed that the most positive Milliken charge and lowest occupied orbital energy were the main contributors to the PBDE Raman spectral intensities. Raman peak analysis revealed no interference between the derivatives in gaseous environments.

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.

Identification of potent inhibitors of DNA methyltransferase 1 (DNMT1) through a pharmacophore-based virtual screening approach

DNA methylation is an epigenetic change that results in the addition of a methyl group at the carbon-5 position of cytosine residues. DNA methyltransferase (DNMT) inhibitors can suppress tumour growth and have significant therapeutic value. However, the established inhibitors are limited in their application due to their substantial cytotoxicity. Additionally, the standard drugs for DNMT inhibition are non-selective cytosine analogues with considerable cytotoxic side-effects. In the present study, we have designed a workflow by integrating various ligand-based and structure-based approaches to discover new agents active against DNMT1. We have derived a pharmacophore model with the help of available DNMT1 inhibitors. Utilising this model, we performed the virtual screening of Maybridge chemical library and the identified hits were then subsequently filtered based on the Naïve Bayesian classification model. The molecules that have returned from this classification model were subjected to ensemble based docking. We have selected 10 molecules for the biological assay by inspecting the interactions portrayed by these molecules. Three out of the ten tested compounds have shown DNMT1 inhibitory activity. These compounds were also found to demonstrate potential inhibition of cellular proliferation in human breast cancer MDA-MB-231 cells. In the present study, we have utilized a multi-step virtual screening protocol to identify inhibitors of DNMT1, which offers a starting point to develop more potent DNMT1 inhibitors as anti-cancer agents.

Malarial kinases: novel targets for in silico approaches to drug discovery

Malaria, the disease caused by infection with protozoan parasites from the genus Plasmodium, claims the lives of nearly 1 million people annually. Developing nations, particularly in the African Region, bear the brunt of this malaria burden. Alarmingly, the most dangerous etiologic agent of malaria, Plasmodium falciparum, is becoming increasingly resistant to current first-line antimalarials. In light of the widespread devastation caused by malaria, the emergence of drug-resistant P. falciparum strains, and the projected decrease in funding for malaria eradication that may occur over the next decade, the identification of promising new targets for antimalarial drug design is imperative. P. falciparum kinases have been proposed as ideal drug targets for antimalarial drug design because they mediate critical cellular processes within the parasite and are, in many cases, structurally and mechanistically divergent when compared with kinases from humans. Identifying a molecule capable of inhibiting the activity of a target enzyme is generally an arduous and expensive process that can be greatly aided by utilizing in silico drug design techniques. Such methods have been extensively applied to human kinases, but as yet have not been fully exploited for the exploration and characterization of antimalarial kinase targets. This review focuses on in silico methods that have been used for the evaluation of potential antimalarials and the Plasmodium kinases that could be explored using these techniques.

Toward the identification of a reliable 3D QSAR pharmacophore model for the CCK2 receptor antagonism

The present study describes application of computational approaches to identify a validated and reliable 3D QSAR pharmacophore model for the CCK-2R antagonism through integrated ligand and structure based studies using anthranilic sulfonamide and 1,3,4-benzotriazepine based CCK-2R antagonists. The best hypothesis consisted five features viz. two aliphatic hydrophobic, one aromatic hydrophobic, one H-bond acceptor, and one ring aromatic feature with an excellent correlation for 34 training set (r²(training) = 0.83) and 58 test set compounds (r²(test) = 0.74). This model was validated through F-test and docking studies at the active site of the plausible CCK-2R where the 99% significance and well corroboration with the pharmacophore model respectively describes the model's reliability. The model also predicts well to other known clinically effective CCK-2R antagonists. Therefore, the developed model may useful in finding new scaffolds that may aid in design and develop new chemical entities (NCEs) as potent CCK-2R antagonists before their synthesis.

Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation

The present study describes a successful application of computational approaches to identify novel Leishmania donovani (Ld) AdoHcyase inhibitors utilizing the differences for Ld AdoHcyase NAD(+) binding between human and Ld parasite. The development and validation of the three-dimensional (3D) structures of Ld AdoHcyase using the L. major AdoHcyase as template has been carried out. At the same time, cloning of the Ld AdoHcyase gene from clinical strains, its overexpression and purification have been performed. Further, the model was used in combined docking and molecular dynamics studies to validate the binding site of NAD in Ld. The hierarchical structure based virtual screening followed by the synthesis of five active hits and enzyme inhibition assay has resulted in the identification of novel Ld AdoHcyase inhibitors. The most potent inhibitor, compound 5, may serve as a "lead" for developing more potent Ld AdoHcy hydrolase inhibitors as potential antileishmanial agents.

3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors

Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating "Hypo1", it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC(50)) data thus successfully validating "Hypo1" by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors.