Absorption, Distribution, Metabolism, Excretion And Toxicity Research Articles

Discovery of Potential Natural STAT3 Inhibitors: An in silico Molecular Docking and Molecular Dynamics Study

Cancer is a mechanistically complex and diverse disease with a plethora of fundamental genetic and epigenetic factors. Signal transducer and activator of transcription-3 (STAT3) is a transcription factor, and its constitutive activation executes promotion of cellular proliferation, cell cycle, angiogenesis, metastasis, immunosuppression, and chemo-resistance in cancer cells. Here, we aimed to design natural potential STAT3 inhibitors. For this purpose, we investigated 92 phytochemical compounds by molecular docking studies because they are diversified, multitargeted, affordable, easily available, and less- or non-toxic. We selected only 6 compounds such as sarsasapogenin (L3), peiminine (L9), solasodine (L10), tormentic acid (L23), obacunone (L29), and echinocystic acid (L34) due to their greater binding affinity than reference STAT3 inhibitor (S3I-201) with STAT3. The study was further continued by molecular dynamic (MD) simulations and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The results of molecular docking showed that all selected ligands exhibited binding affinity range from -9.3 Kcal/mol to -7.9 Kcal/mol and predicted inhibition constant ([Formula: see text].) values range from 0.14 [Formula: see text]M to 1.5 [Formula: see text]M. These compounds showed effective hydrogen bonding and hydrophobic interactions with DNA binding domain as well as SH2-domain of STAT3. The MD simulations performed by nanoscale molecular dynamics (NAMD) calculated root mean square deviations (RMSD), root mean square fluctuations (RMSF), radius of gyration ([Formula: see text]), solvent accessible surface area (SASA) and number of hydrogen bond dynamics. All selected ligands with protein exhibited stability over 120 ns by MD simulation. Moreover, these ligands showed favorable ADMET profiling and drug likeness. So, our current computational investigations showed that these novel drug candidates can be potential STAT3 inhibitors and evoke the scientific interest for their further verification by in vitro and in vivo studies.

In silico Study on Structural Inhibition of Bacterial DNA Gyrase by Major Secondary Metabolites Found in Grape Seed Extract

In the early 20th century, during the era of investigating and identifying essential “vitamins”, scientific research focused on grape seed extracts and their bioactive components, particularly polyphenols. Extensive studies have demonstrated that grape seed extract, rich in proanthocyanidins, offers protection against a wide spectrum of diseases, encompassing inflammation, cardiac ailments, peptic ulcers, hypertension, diabetes, cancer, and microbial infections. To explore potential secondary metabolites within grape seed extract that could serve as structural inhibitors of bacterial DNA Gyrase, molecular docking studies were performed. The docking results revealed that two phytochemicals, namely (-)-catechin and Procyanidin-B2, exhibited the highest potency in inhibiting DNA gyrase subunit B. Subsequent in silico physicochemical and pharmacokinetic parameter predictions were conducted using specialized web servers for the examined phytochemicals. Notably, (-)-catechin displayed superior inhibitory and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) characteristics, suggesting its potential for utilization in synthesizing novel antibacterial compounds.

In-silico studies of some potent hybrid compounds against Alzheimer's disease through virtual screening, simulation techniques, and pharmacokinetic endowment

Complications in the etiology of Alzheimer Disease (AD) as being a concern among the research scientist and medicinal community. Hybrids compounds with multi-targeted property have been reported in the literature to be effective in curing/hindering the menace of this disease. In this research, virtual screenings of potent, non-toxic hybrid compounds will be performed, carrying out simulations on the screened compounds and predicting the druggability of the screened compounds and these were the goals of this study. Computational methods have been used to solve this problem by applying in-silico screening, simulation techniques, and pharmacokinetic prediction of therapeutic inhibitors capable of preventing or hindering the atrocities imposed by this deadly disease. Twenty-five hybrid compounds were subjected to virtual screening, simulation, and pharmacokinetic assessment. Ten of these compounds showed docking scores with strong binding affinities to enzymes and receptors, forming strong contacts with proteins. The inhibitor docking results were far better than those of the reference compound, with a docking score of −26.30 kcal/mol. The interactions showed similar amino acids in the screened compounds, such as ASN349, PHE168, and SER67, which function as brain signal transmitters and neurotransmitters (norepinephrine and dopamine), and in Alzheimer's disease (AD) treatment, which interact with the ligands through hydrogen and hydrophobic bonds. In addition, the pharmacokinetic and absorption, distribution, metabolism, excretion, and toxicity (ADMET-ox) predictions revealed that all the virtually screened compounds were endowed with therapeutic ability as anti-AD agents. The results determined the possible interactions and their characteristics at the atomic level, and the pharmacokinetic predictions were excellent. Neuroscientists should proceed with further clinical tests, such as in-vivo and in-vitro tests, to ascertain whether these inhibitors meet their targets.

N-Sulfonyl-1,2,3,4-tetrahydroisoquinoline Derivatives: Synthesis, Antimicrobial Evaluations, and Theoretical Insights.

Microbial contamination remains a significant economic challenge in the food industry, emphasizing the need for innovative antimicrobial solutions. In this study, we synthesized N-sulfonyl-1,2,3,4-tetrahydroisoquinolines (NSTHIQ) derivatives using an environmentally friendly Preyssler heteropolyacid catalyst, obtaining moderate to high yields (35-91 %) under mild conditions. Two derivatives (5 and 6) exhibited significant antifungal properties against various fungal species, including Aspergillus spp, Penicillium spp, and Botrytis cinerea. ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis revealed the absence of hepatic toxicity in all compounds, making derivatives 2, 3, 4, and 5 potential candidates for further development. However, derivatives 6 and 7 exhibited immunotoxicity. In support of our experimental findings, reactivity indices were computed using Density Functional Theory principles, deriving valuable insights into the chemical properties of these derivatives. This study underscores the potential of NSTHIQ compounds as potent antifungal agents, coupled with the importance of employing environmentally friendly catalysts in drug discovery.

Molecular Docking, Pharmacokinetic and Molecular Simulation Analysis of Novel Mono-Carbonyl Curcumin Analogs as L858R/T790M/C797S Mutant EGFR Inhibitors.

Curcumin, an anticancer natural compound with multiple pharmacological activities, has a weak pharmacokinetic and instability due to diketone moiety. Curcumin's stability challenges can be overcome by removing the diketone moiety and shortening the 7-carbon chain, resulting in mono-carbonyl analogs. Cancer proliferation is caused by the activation of Epidermal Growth Factor (EGFR) pathways. Current available EGFR inhibitors have an issue of resistance. Thus, we aimed to design new mono-carbonyl curcumin derivatives and analyse their drug likeness properties. Further, to investigate them on three distinct crystal structures, namely two wild-type and L858R/T790M/C797S mutant generations for EGFR inhibitory activity. Ten New Molecular Entities (NME's) were designed using literature survey. These molecules were subjected to comparative molecular docking, on the EGFR crystal structures viz. wild-type (PDB: 1M17 and 4I23) and L858R/T790M/C797S mutant (PDB: 6LUD) using Schrodinger software. The molecules were also tested for Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties. The docked complex of the hit molecule was studied for molecular simulation. In molecular docking studies, NMEs 1, 2, and 3 were found to have good binding affinity with 1st , 2nd , and 3rd generation EGFR crystal structures and a greater dock score than standard curcumin. All molecules have shown a good ADMET profile. Since L858R/T790M/C797S is currently being explored more, we decided to take the best molecule, NME 3, for molecular dynamics with 6LUD, and the results were compared with those of the co-crystallized ligand S4 (Osimertinib). It was found that the Relative mean square standard deviation (RMSD) (1.8 Å), Relative mean standard Fluctuation (RMSF) (1.45 Å) and radius of gyration (4.87 Å) values of NME 3 were much lower than those of reference S4. All these confirm that our designed NME 3 is more stable than reference S4. NME 1 and NME 2 have shown better binding against wild type of EGFR. NME 3 have shown comparable binding and more stability as compared to Osimertinib against L858R/T790M/C797S mutated protein structure. The hit compound can be further explored for its Molecular mechanics with generalised Born and surface area solvation (MM-GBSA) and discrete Fourier transform (DFT) studies to find out the energy and atomic level study. In the future, this molecule could be taken for wet lab studies and can be tested for mutated EGFR inhibitory activity.

Phytochemicals from Piper betle (L.) as Putative Modulators of a Novel Network-Derived Drug Target for Coronary Artery Disease: An In Silico Study

Coronary artery disease (CAD) is a leading cause of death worldwide. Despite effective anti-CAD drugs, the rising mortality suggests that more pharmacological targets need to be discovered to improve treatment effectiveness. This study explores and evaluates traditional medicinal plant (Piper betle (L.)) compounds against a new target identified through protein network analysis. Our network analysis suggests that the GRB2 protein could be a potential target that links most of the pathological pathway-related proteins in CAD. As a result, we evaluated potential compounds from Piper betle (L.) through ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling, docking, and molecular dynamics (MDs) simulation against the GRB2. The ADMET screening detected 49 druggable phytochemicals in Piper betle (L.). Further, screening through molecular docking showed that piperbetol has a higher predicted affinity towards the dimeric form of GRB2 (−8.10 kcal/mol) than other analyzed phytochemicals. Additionally, MD simulation demonstrated that piperbetol formed a stable complex with GRB2 during the simulation. In conclusion, piperbetol from Piper betle showed favorable binding with the identified CAD target. Further investigations are needed for pharmaceutical translation.

Synthesis, X-Ray, Hirshfeld Surface, DFT, and Molecular Docking Investigation of N-(5H-Dibenzo[a,d][7]Annulen-5-Ylidene)-2-Methylpropane-2-Sulfinamide

Dibenzocycloheptene antidepressants are tricyclic antidepressants (TCAs) that contain the dibenzocycloheptene moiety in their chemical structures. They are used to treat major depressive disorder, anxiety disorders, chronic pain, and addiction. Herein, we report the synthesis of a pure tricyclic antidepressant containing dibenzocycloheptene moiety named N-(5H-dibenzo[a,d][7]annulen-5-ylidene)-2-methylpropane-2-sulfinamide (3) in high chemical yield through condensing (R)-tert-butanesulfinamide with a dibenzosuberon ketone. Its structure is elucidated by employing the X-ray technique, NMR spectroscopy characterization, and DFT calculations at the B3LYP/6-31++G(d,p) level of theory. The geometrical parameters are relatively well reproduced, and the optimized and X-ray geometries are relatively well superimposed. The interconnects in the crystalline form of 3 were identified through the analysis of its Hirshfeld surface (HS) and fingerprint plots. The highest interatomic contacts were found between H…H of 58.2% and C.H of 30.6%. Further, the ADMET (absorption, distribution, metabolism, excretion, and toxicity) pharmacokinetics, and physicochemical properties of 3 were determined, which showed that 3 may act as a carbonic Anhydrase I inhibitor. The binding affinity of 3 into the binding site of carbonic Anhydrase I is investigated using a molecular docking study. It forms a stable complex into the binding site of CA I with a binding energy of −7.12 kcal/mol.

Machine learning small molecule properties in drug discovery

Machine learning (ML) is a promising approach for predicting small molecule properties in drug discovery. Here, we provide a comprehensive overview of various ML methods introduced for this purpose in recent years. We review a wide range of properties, including binding affinities, solubility, and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity). We discuss existing popular datasets and molecular descriptors and embeddings, such as chemical fingerprints and graph-based neural networks. We highlight also challenges of predicting and optimizing multiple properties during hit-to-lead and lead optimization stages of drug discovery and explore briefly possible multi-objective optimization techniques that can be used to balance diverse properties while optimizing lead candidates. Finally, techniques to provide an understanding of model predictions, especially for critical decision-making in drug discovery are assessed. Overall, this review provides insights into the landscape of ML models for small molecule property predictions in drug discovery. So far, there are multiple diverse approaches, but their performances are often comparable. Neural networks, while more flexible, do not always outperform simpler models. This shows that the availability of high-quality training data remains crucial for training accurate models and there is a need for standardized benchmarks, additional performance metrics, and best practices to enable richer comparisons between the different techniques and models that can shed a better light on the differences between the many techniques.

Screening of potent inhibitor from Aquilaria malaccensis Lam. against arachidonic inflammatory enzymes: an insight from molecular docking, ADMET, molecular dynamics simulation and MM-PBSA approaches

The three primary enzymes COX (cyclooxygenase), LOX (lipoxygenase) and CYT-P450 (cytochrome P450), which are part of the arachidonic inflammatory pathway, play crucial role in the development of asthma, rheumatoid arthritis and cardiovascular diseases. Ethnomedicinally, plant-derived chemicals have a major role in the treatment of fatal illnesses. Aquilaria malaccensis Lam. widely known as agarwood is prized for its fragrance and therapeutic properties. The phytochemicals and extracts of this plant have significant healing properties in the treatment of serious illnesses. In the current work, an in-silico approach including molecular docking, ADMET (absorption, distribution, metabolism, excretion and toxicity), molecular dynamics (MD) simulation and molecular mechanics/Poisson–Boltzmann surface area (MM-PBSA) was performed to screen 33 bioactive compounds from this plant against COX-2 and 5-LOX in order to find the most effective inhibitor. 2-(2-Phenylethyl)chromone was found to inhibit both 5-LOX and COX-2, showing the highest binding affinities (−9.1 kcal/mol and −9.0 kcal/mol, respectively) than standard Ibuprofen and nordihydroguaiaretic acid (NDGA). 2-(2-Phenylethyl)chromone showed the highest drug-likeness score and low risk of toxicity compared to other phytochemicals. MD modeling and MM-PBSA calculations showed that 2-(2-Phenylethyl)chromone had a strong persistent binding interaction with 5-LOX than COX-2, and this interaction is comparable to the bounded standards Ibuprofen and NDGA. From this study, we may infer that the 2-(2-Phenylethyl)chromone can serve as a potent inhibitor and has scope to be employed in the treatment of inflammatory ailments. Communicated by Ramaswamy H. Sarma

Machine learning study of the extended drug-target interaction network informed by pain related voltage-gated sodium channels.

Pain is a significant global health issue, and the current treatment options for pain management have limitations in terms of effectiveness, side effects, and potential for addiction. There is a pressing need for improved pain treatments and the development of new drugs. Voltage-gated sodium channels, particularly Nav1.3, Nav1.7, Nav1.8, and Nav1.9, play a crucial role in neuronal excitability and are predominantly expressed in the peripheral nervous system. Targeting these channels may provide a means to treat pain while minimizing central and cardiac adverse effects. In this study, we construct protein-protein interaction (PPI) networks based on pain-related sodium channels and develop a corresponding drug-target interaction network to identify potential lead compounds for pain management. To ensure reliable machine learning predictions, we carefully select 111 inhibitor data sets from a pool of more than 1000 targets in the PPI network. We employ 3 distinct machine learning algorithms combined with advanced natural language processing (NLP)-based embeddings, specifically pretrained transformer and autoencoder representations. Through a systematic screening process, we evaluate the side effects and repurposing potential of more than 150,000 drug candidates targeting Nav1.7 and Nav1.8 sodium channels. In addition, we assess the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of these candidates to identify leads with near-optimal characteristics. Our strategy provides an innovative platform for the pharmacological development of pain treatments, offering the potential for improved efficacy and reduced side effects.

Exploring Medicinal Herbs' Therapeutic Potential and Molecular Docking Analysis for Compounds as Potential Inhibitors of Human Acetylcholinesterase in Alzheimer's Disease Treatment.

Background and Objectives: Alzheimer's disease (AD) stands as a pervasive neurodegenerative ailment of global concern, necessitating a relentless pursuit of remedies. This study aims to furnish a comprehensive exposition, delving into the intricate mechanistic actions of medicinal herbs and phytochemicals. Furthermore, we assess the potential of these compounds in inhibiting human acetylcholinesterase through molecular docking, presenting encouraging avenues for AD therapeutics. Materials and Methods: Our approach entailed a systematic exploration of phytochemicals like curcumin, gedunin, quercetin, resveratrol, nobiletin, fisetin, and berberine, targeting their capability as human acetylcholinesterase (AChE) inhibitors, leveraging the PubChem database. Diverse bioinformatics techniques were harnessed to scrutinize molecular docking, ADMET (absorption, distribution, metabolism, excretion, and toxicity), and adherence to Lipinski's rule of five. Results: Results notably underscored the substantial binding affinities of all ligands with specific amino acid residues within AChE. Remarkably, gedunin exhibited a superior binding affinity (-8.7 kcal/mol) compared to the reference standard. Conclusions: These outcomes accentuate the potential of these seven compounds as viable candidates for oral medication in AD treatment. Notably, both resveratrol and berberine demonstrated the capacity to traverse the blood-brain barrier (BBB), signaling their aptitude for central nervous system targeting. Consequently, these seven molecules are considered orally druggable, potentially surpassing the efficacy of the conventional drug, donepezil, in managing neurodegenerative disorders.

Recent Studies of Artificial Intelligence on In Silico Drug Absorption.

Absorption is an important area of research in pharmacochemistry and drug development, because the drug has to be absorbed before any drug effects can occur. Furthermore, the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profile of drugs can be directly and considerably altered by modulating factors affecting absorption. Many drugs in development fail because of poor absorption. The research and continuous efforts of researchers in recent years have brought many successes and promises in drug absorption property prediction, especially in silico, which helps to reduce the time and cost significantly for screening undesirable drug candidates. In this report, we explicitly provide an overview of recent in silico studies on predicting absorption properties, especially from 2019 to the present, using artificial intelligence. Additionally, we have collected and investigated public databases that support absorption prediction research. On those grounds, we also proposed the challenges and development directions of absorption prediction in the future. We hope this review can provide researchers with valuable guidelines on absorption prediction to facilitate the development of newer approaches in drug discovery.

Mechanistic insights and therapeutic implications of novel pyrazoline derivatives on antioxidant and enzymatic inhibitory activities

One of the major features of medicinal chemistry, is the synthesis of novel compounds, and the assessment of their biological activities for potential therapeutic applications. As a contribution to this filed of interest, the present work examines the effects of newly synthesized pyrazoline derivatives. To this end, four pyrazoline derivatives were synthesized and evaluated for their antioxidant activities and enzymatic inhibitory in vitro against acetylcholinesterase (AChE) and tyrosinase. All the synthetized compounds 2a–2d all displayed a moderate to potent antioxidant activity. For the enzymatic inhibitory activity, compound 2a exerted the most potent acetylcholinesterase inhibition with an IC50 value of (IC50 = 3.93 ± 0.52 µM) which is twice greater than the standard drug, Galantamine (IC50 = 6.27 ± 1.15 µM), whereas, compound 2a was determined as the best inhibitor among the synthesized compounds for the tyrosinase enzyme with an IC50 value of (32.65 ± 2.30 μM). Density Functional Theory (DFT) calculations were performed to determine the compound's properties, and molecular docking studies were conducted to discuss potential interactions between the most active compound (2a) and active sites of proteins AChE (PDB: 1ACL) and tyrosinase (PDB: 2Y9X). Based on in silico predictions of Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and pharmacokinetic parameters, it is suggested that these compounds could potentially exhibit favorable oral bioavailability. The paper offers promising insights into the therapeutic potential of these pyrazoline derivatives, particularly compound 2a. It encourages further investigation into the practical application of these findings, possibly leading to new therapeutic avenues in the treatment of diseases associated with acetylcholinesterase and tyrosinase.

Determination of the antioxidant and enzyme-inhibiting activities and evaluation of selected terpenes' ADMET properties: in vitro and in silico approaches

The in vitro antioxidant capacity of eugenol, eucalyptol, linalool, and carvacrol was performed using six test systems: phosphomolybdenum, DPPH (2,2′-diphenyl-1-picrylhydrazyl radical), ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate), CUPRAC (cupric ion reducing antioxidant capacity), FRAP (Ferric reducing ability of plasma), and metal chelating effect. Their inhibitory activities on cholinesterases, α-amylase, α-glucosidase, and tyrosinase were assessed as well. Molecular docking helped to explain the obtained outcomes while in silico ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction served for assessing the physicochemical and pharmacokinetic profiles. Our findings showed that the examined terpenes have promising antioxidative activity with eugenol and carvacrol displaying the highest efficiency. Linalool presented the highest anti-AChE and anti-tyrosinase activities (7.931 ± 0.034 mg GALAE/g and 58.707 ± 5.120 mg KAE/g, respectively). Eucalyptol exhibited the strongest anti-BChE activity (2.704 ± 0.025 mg GALAE/g), while carvacrol exhibited the highest rates for α-glucosidase and α-amylase inhibition (1.414 ± 0.042 and 1.023 ± 0.054 mM ACAE/g, respectively). Molecular docking revealed that all compounds interacted in varied ways with the five enzymes’ active sites. Excellent binding profiles and greatest inhibitory activity to AChE (−7.4 kcal/mol), α-glucosidase (−6.5 kcal/mol), and α-amylase (−6.5 kcal/mol) was attributed to carvacrol. As regards to tyrosinase, eugenol (−6.2 kcal/mol) was the potent one whereas carvacrol and eugenol (−6.5 kcal/mol for both) strongly interacted with BChE. Furthermore, in silico ADMET-related physicochemical and pharmacokinetic properties revealed good profiles. To sum up, here we demonstrate the powerful antioxidant potency and enzymatic inhibitory effects of the four terpenes which may enable the discovery of lead compounds that are extremely potent antioxidants and enzyme inhibitors.

Identification of PPA1 inhibitor candidates for potential repurposing in cancer medicine.

Inorganic pyrophosphatase 1 (PPA1) is pivotal to cellular metabolism as it facilitates the hydrolysis of PPi-a by-product of various metabolic processes that influence cell growth and differentiation. Overexpression of PPA1 enzyme has been linked to diminished patient survival and was shown to influence tumor cell dynamics, thereby positioning it as a potential therapy target for a variety of cancers including colorectal cancer, diffuse large B-cell lymphoma, and lung adenocarcinoma. Despite this therapeutic promise, there are no known inhibitors of PPA1 as of today. In this study, we searched for potential PPA1 inhibitors using a molecular docking screen of 30 470 compounds with a history of clinical trials and/or US Food and Drug Administration approval. We specifically targeted the active pocket that coincides with the established catalytic domain. Our screen identified promising hits, which we further subjected to ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering. Subsequent molecular dynamics (MD) analyses were conducted on devazepide, quinotolast, and tarazepide-the three substances that successfully navigated all filters. MD analyses reinforced the stability of the protein-ligand complexes and confirmed ligand binding, as substantiated by our root mean square deviation, radius of gyration and secondary structures of proteins analyses. Furthermore, Molecular Mechanics Poisson-Boltzmann Surface Area calculations post-MD identified devazepide and quinotolast as showing higher binding affinities; being supported by principal component analysis, free energy landscape, and dynamic cross-correlation matrix results. Overall, our study reveals devazepide and quinotolast as potential candidates for PPA1 inhibition which could be considered for repurposing studies that need further experimental validation. These results not only reveal a potential for clinical repurposing for PPA1 inhibition but they also offer valuable insights into the development of future compounds for targeting the crucial PPA1 enzyme.

Insight into (Z)-ethyl-2-(2-((E)-2,4-dinitro benzylidene amino)-4-oxo-3-phenylthiazolidin-5-ylidene) acetate in-silico anti-SARS-CoV-2 performance: Synthesis, structural-spectral characterizations and DFT computations

This study reports on the synthesis of a 4-thiazolidinone derivative (EN2Th), namely, (Z)-Ethyl-2-(2-((E)-2,4-dinitro benzylidene amino)-4-oxo-3-phenylthiazolidin-5-ylidene) acetate. Its crystal structure has been determined by single crystal X-ray diffraction and the spectral characterizations were carried out by means of 1H and 13C NMR, and FT-IR techniques. The molecule of EN2Th crystallizes in the monoclinic P21/c symmetry and its crystal structure consists of a herringbone packing along [100]. The density functional theory (DFT) at the B3LYP/6-311G (d,p) level has been employed for structure optimization, the results confirm a good consistency between the theoretical and the experimental geometrical data. Hirshfeld surface and 2D fingerprints indicate C−H···O (29.7%) and H···H (24.5%) as the most relevant intermolecular interactions in the crystal packing of EN2Th. According to the reduced density gradient (RDG) analysis, EN2Th exhibits vdW to weak repulsive regions with low electron densities. The theoretical electronic circular dichroism (ECD) spectrum displays an exciton coupled transitions associated with the Z-configuration of the thiazolidin-4-one moiety reflecting the steric effect of the ester group. Charge transfer inside the 4-thiazolidinone derivative EN2Th was considered via the frontier molecular orbitals (FMOs) and natural bond orbital (NBO) investigations along with molecular electrostatic potential (MEP) distribution maps. The HOMO and LUMO energies allowed the estimation of the chemical reactivity descriptors. In accordance with the NBO results, the predicted hyperpolarizabilities indicate a strong donor to acceptor π-electrons delocalization in EN2Th. The anti-viral performance of EN2Th was evaluated in silico against SARS-CoV-2 main protease (MPro) via molecular docking simulations. Finally, ADMET (absorption, distribution, metabolism, excretion and toxicity) online software tools were utilized to uncover the title compound's potential cytotoxicity.

Antimalarial drug discovery against malaria parasites through haplopine modification: An advanced computational approach.

The widespread emergence of antimalarial drug resistance has created a major threat to public health. Malaria is a life-threatening infectious disease caused by Plasmodium spp., which includes Apicoplast DNA polymerase and Plasmodium falciparum cysteine protease falcipain-2. These components play a critical role in their life cycle and metabolic pathway, and are involved in the breakdown of erythrocyte hemoglobin in the host, making them promising targets for anti-malarial drug design. Our current study has been designed to explore the potential inhibitors from haplopinederivatives against these two targets using an in silico approach. A total of nine haplopine derivatives were used to perform molecular docking, and the results revealed that Ligands 03 and 05 showed strong binding affinity compared to the control compound atovaquone. Furthermore, these ligand-protein complexes underwent molecular dynamics simulations, and the results demonstrated that the complexes maintained strong stability in terms of RMSD (root mean square deviation), RMSF (root mean square fluctuation), and Rg (radius of gyration) over a 100 ns simulation period. Additionally, PCA (principal component analysis) analysis and the dynamic cross-correlation matrix showed positive outcomes for the protein-ligand complexes. Moreover, the compounds exhibited no violations of the Lipinski rule, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) predictions yielded positive results without indicating any toxicity. Finally, density functional theory (DFT) and molecular electrostatic potential calculations were conducted, revealing that the mentioned derivatives exhibited better stability and outstanding performance. Overall, this computational approach suggests that these haplopine derivatives could serve as a potential source for developing new, effective antimalarial drugs to combat malaria. However, further in vitro or in vivo studies might be conducted to determine their actual effectiveness.

Implementation of computational strategies to combat drug resistance in Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB) is an infectious pathogen that causes tuberculosis (TB). Even though it is curable, the first-line anti-TB medication rifampicin has been a source of rising concern for human health across the globe. However, rifampicin resistance results from mutations in the RNA polymerase's binding site of the target protein. This infectious pathogen can survive in macrophages and can induce a long-lasting latent infection. The prolonged survival of mycobacterial species was achieved with the aid of serine/threonine protein kinase G (PknG) which performs a preventive role in this situation. Thus, PknG is believed to be an essential target to prevent the pathogen from entering the latency stage. The present investigation was oriented towards molecular-based virtual screening carried out using AutoDock for the FDA-approved and nutraceutical subsets of compounds from the DrugBank repository. Initially, a total of 3035 compounds were screened based on their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties. The screened molecules were taken for docking purposes after which post-docking analysis was performed by calculating the random forest (RF) score. Further, the structural characterization of hit compounds was validated using interaction studies and in silico bioactivity prediction studies. Finally, the anti-myotubular activity prediction was carried out in the search for potential inhibitors. Importantly, four potential ligands, namely DB00080, DB00807, DB06249 and DB06274 were preferred after a thorough investigation. These ligands showed significant structural and protein-ligand interactions, suggesting that they might be potentially used as therapeutic candidates to combat MTB.

Novel hydrazones derived from anthranilic acid as potent cholinesterases and α-glycosidase inhibitors: Synthesis, characterization, and biological effects.

N-substitued anthranilic acid derivatives are commonly found in the structure of many biologically active molecules. In this study, new members of hydrazones derived from anthranilic acid (1-15) were synthesized and investigated their effect on some metabolic enzymes such as acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and α-glycosidase (α-Gly). Results indicated that all the molecules exhibited potent inhibitory effectsagainst all targets as compared to the standard inhibitors, revealed by IC50 values. Ki values of compounds for AChE, BChE, and α-Glyenzymes were obtained in the ranges 66.36 ± 8.30-153.82 ± 13.41, 52.68 ± 6.38-113.86, and 2.13 ± 0.25-2.84 nM, respectively. The molecular docking study was performed for the most active compounds to the determination of ligand-enzyme interactions. Binding affinities of the most active compound were found at the range of -9.70 to-9.00 kcal/mol for AChE, -11.60to-10.60 kcal/mol for BChE, and -10.30 to-9.30 kcal/mol for α-Gly. Molecular docking simulations showed that the novel compounds had preferential interaction with AChE, BChE, and α-Gly. Drug-likeness properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analyzes of all synthesized compounds (1-15) were estimated and their toxic properties were evaluated as well as their therapeutic properties. Moreover, molecular dynamics simulations were carried out to understand the accuracy of the most potent derivatives of docking studies.

Indapamide analogue a promising drug: Synthesis, a novel crystal structure, HSA/DFT/XRD, greener pastures biological study

A new indoline derivative, N-allyl-4-chloro-3-(N,N-diallylsulfamoyl)-N-(2-methylindolin-1-yl)benzamide (ASIB), indapamide analogue, has been synthesized via the N-allylation reaction and characterized by ESI-MS, IR, 1H & 13C NMR. The geometric parameters of the title compound, whose crystallographic structure has been defined by X-ray diffraction, have been calculated by Density Functional Theory (DFT), B3LYP, 6–311++G(d,p) basis set. For these operations, the data obtained by X-ray diffraction was used as initial values, and the calculated geometric parameters and experimental results were compared. In order to understand intermolecular interactions, Molecular Electrostatic Potential (MEP) and Hirshfeld Surface Analysis (HSA) studies were figured out for the molecule. Frontier Molecular Orbitals (FMO's) were created, and Energy Gap between Lowest Unoccupied Molecular Orbital (LUMO) and Highest Occupied Molecular Orbital (HOMO) was calcculated. Adapting Greener Pastures Biological Study (GPBS) aims to conduct a fair comparative study using accessible computer-aided software. ASIB, Indapamide, Asunaprevir, Danoprevir, and Vaniprevir were docked together using the same conditions and parameters to ensure a fair comparison. The binding scores against 6LU7 were −6.6, −7.1, −8.4, 7.6, and −7.9 kcal/mol−1 for ASIB, Indapamide, Asunaprevir, Danoprevir, and Vaniprevir, respectively. A relation between the molecule's binding score was due to the hydrophobic and hydrogen interactions between the ligand and the receptor's active amino acid residues. Worth pointing out here that the free energy and environmentally friendly in Silico molecular docking method aims mainly to rank ASIB, and Indapamide with respect to the approved drugs used in this study. Results support further investigation of ASIB as non-toxic a Diuretic, anti-COVID-19 and powerful antiviral drug as an indapamide derivative. Way2drug-PASS, Pro Tox-II and SwissADME are online software tools used in this study. Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of ASIB and its starting material (Indapamide) were compared.