Computational investigation of potent inhibitors against SARS-CoV-2 2'-O-methyltransferase (nsp16): Structure-based pharmacophore modeling, molecular docking, molecular dynamics simulations and binding free energy calculations

The inhibitory activities of two compounds from Securidaca longepedunculata Fresen on the acetylcholinesterase from wheat pest Schizaphis graminum Rondani: in silico analysis

Wheat is the third most widely consumed cereal in the world, after maize and rice. However, it is regularly attacked by the wheat aphid (Schizaphis graminum), causing considerable damage to wheat crops. The acetylcholinesterase enzyme, which plays a key role in the transmission of the synaptic cholinergic signal, has emerged as a promising target for the development of pest control strategies. Inhibition of this enzyme leads to the paralysis or even death of the aphid. The objective of this study is to identify the bioactive compounds in Securidaca longepedunculata (S. longepedunculata) that are capable of interacting with acetylcholinesterase from Schizaphis graminum and inhibiting its activity. Furthermore, a computer simulation of these compounds in interaction with the key protein was conducted. First, the secondary metabolites of S. longepedunculata were selected on the basis of GC-MS data available from specific reference sources. Subsequently, the compounds were subjected to virtual screening based on their docking scores in order to identify those with inhibitory properties. The compounds with the highest scores were subjected to molecular dynamics simulation over a 50 ns trajectory. Subsequently, MMGBSA free energy calculations were conducted. The results demonstrated that eight compounds exhibited inhibitory properties, four of which (echimidine, populin, salidroside, and farrerol) demonstrated superior stabilizing effects on proteins compared to the remaining compounds. In terms of free energy by MMGBSA and molecular simulation, it was observed that echimidine and populin formed robust and stable hydrogen bonds with the amino acids of the acetylcholinesterase enzyme. This study identifies and attempts to validate the potential inhibitory activities of echimidine and populin against acetylcholinesterase, with a view to developing potent insecticides and unique treatment strategies.

Synthesizing network pharmacology, bioinformatics, and in vitro experimental verification to screen candidate targets of Salidroside for mitigating Alzheimer's disease

Alzheimer's disease (AD) is a neurological disorder leading to cognitive deficits. Salidroside (Sal), a primary bioactive ingredient extracted from the roots of Rhodiola rosea L., has potent neuroprotective effects in AD. However, studies on potential targets for Sal-anchored AD are limited. In this study, we combined network pharmacology, bioinformatics, and experimental validation to identify potential targets of Sal treating AD. First, we screened 10 pyroptosis-related genes (PRGs) in Sal and AD using public databases. Then, we used Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analysis to explore the biological functions of the shared PRGs (Sal and AD). This finding exhibited that pathways linked to inflammation, like the nucleotide oligomerization domain (NOD)-like receptors signaling pathway, are important for Sal to help fight AD. The GeneMANIA functional results subsequently revealed an association between AD and the processes of inflammasome complex and inflammatory response. Additionally, nine hub genes were identified in the protein-protein interaction network of these shared PRGs. Subsequent analysis of the genes and phenotypes confirmed that these nine hub genes were directly correlated with AD. Subsequently, an in vitro AD model was created using rat adrenal pheochromocytoma cell line (PC12) cells induced by amyloid β-peptide (Aβ) 25-35 (20 µM). Sal significantly reduced the pyroptosis caused by Aβ 25-35 in PC12 cells and decreased the expression levels of IL-1β, CASP1, IL-18, PYCARD, and NLRP3. Furthermore, molecular docking and molecular dynamics simulations confirmed that Sal could stably bind to NLRP3. Druggability analysis revealed that Sal had excellent druggability. These results demonstrated that Sal could alleviate AD by targeting IL-1β, CASP1, IL-18, PYCARD, and NLRP3 to regulate the NLRP3-mediated pyroptosis signaling pathway.

Novel Nordaucane Sesquiterpenoid and Sesquiterpene Lactone From Laserpitium Species: Isolation, Structure Elucidation, In Vitro, In Vivo, and In Silico Evaluation as Anticancer Agents

INTRODUCTION

This study explores the cytotoxic activity-guided isolation of the underground parts of Laserpitium hispidum M. Bieb and Laserpitium petrophilum Boiss. & Heldr., which have not been previously investigated.

OBJECTIVES

The aim is to isolate and evaluate bioactive compounds from Laserpitium L. species with anticancer potential.

MATERIAL AND METHODS

This study involves bioactivity-guided isolation and structural studies of the pure compounds utilizing NMR, UV-Vis, IR spectroscopies, and HRMS. The cytotoxic activity of the isolated compounds was evaluated in vitro and in vivo, whereas molecular modeling, docking, and ADME predictions were conducted using Schrödinger software.

RESULTS

The study isolated phenylpropanoids (laserine (1), latifolone (2), myristicin (3)), sterol (stigmasterol (4)), polyenes (falcarindiol (5)), sesquiterpene lactone (11-hydroxybadkhyzin (6)), and nordaucane sesquiterpene (norlasidiol angelate (7)) from L. hispidum, whereas L. petrophilum yielded 10β-acetoxy-8α-angeloyloxy-6αH,7αH-guaian-3-en-12,6-olide (8), 10β-acetoxy-8α-senecioyloxy-6αH,7αH-guaian-3-en-6,12-olide (9) and acetylisomontanolide (10). Molecular docking simulations revealed stable interactions between compounds 7 and 9 with estrogen receptor α (ERα) and vascular endothelial growth factor receptor 2 (VEGFR2), with compound 7 showing superior stability and binding affinity. In silico ADME predictions indicated favorable pharmacokinetic properties, including high oral absorption.

CONCLUSION

Compounds 7 and 9, representing new nordaucane and sesquiterpene lactones, have not been previously reported. In vitro cytotoxicity revealed that compound 7 exhibits potent anti-cancer activity against MCF-7 cells, whereas compound 9 showed reduced cytotoxicity. In vivo testing in Caenorhabditis elegans supported these findings, suggesting safety and efficacy in organisms. In silico results emphasize the potential of these compounds, with compound 7 promising due to its stability and strong binding affinity.

LC-MS and GC-MS Analyses on Green Algae Penicillus Capitatus: Cytotoxic, Antimicrobial and Anticholinesterase Activity Screening Enhanced by Molecular Docking & Dynamics and ADME Studies

In this comprehensive screening study, the chemical composition, and cytotoxic, antimicrobial, and anticholinergic activities of the green algae Penicillus capitatus, collected from Antalya-Türkiye, were determined as in vitro and in silico. GC-MS analysis of the hexane extract revealed a high content of fatty acids, with hexadecanoic acid constituting half of the total fatty acid content. LC-HRMS analysis of the DCM:MeOH extract identified ascorbic acid as the most abundant compound, followed by (-)-epigallocatechin and salicylic acid. The DCM:MeOH extract exhibited potent cytotoxicity against MDA-MB-231 and MCF7 breast cancer cell lines, outperforming doxorubicin with lower IC50 values and a higher selectivity index. Additionally, the extract demonstrated significant antimicrobial activity against Staphylococcus aureus, Escherichia coli, and Candida albicans, along with selective inhibition of acetylcholinesterase (hAChE) over butyrylcholinesterase (hBChE). Molecular docking and dynamics studies revealed that apigenin-7-O-glucoside and epigallocatechin form stable interactions with estrogen receptor alpha (ERα) and hAChE, suggesting their potential as inhibitors. In silico ADME studies indicated favorable pharmacokinetic profiles for the detected compounds, supporting their potential as drug candidates. The promising cytotoxic activity of the P. capitatus extracts, coupled with significant antimicrobial properties and selective hAChE inhibition, highlights their therapeutic potential for breast cancer treatment, infection management, and neurodegenerative disease intervention.

Cheminformatics approach to identify andrographolide derivatives as dual inhibitors of methyltransferases (nsp14 and nsp16) of SARS-CoV-2

The Covid-19 pandemic outbreak has accelerated tremendous efforts to discover a therapeutic strategy that targets severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to control viral infection. Various viral proteins have been identified as potential drug targets, however, to date, no specific therapeutic cure is available against the SARS-CoV-2. To address this issue, the present work reports a systematic cheminformatic approach to identify the potent andrographolide derivatives that can target methyltransferases of SARS-CoV-2, i.e. nsp14 and nsp16 which are crucial for the replication of the virus and host immune evasion. A consensus of cheminformatics methodologies including virtual screening, molecular docking, ADMET profiling, molecular dynamics simulations, free-energy landscape analysis, molecular mechanics generalized born surface area (MM-GBSA), and density functional theory (DFT) was utilized. Our study reveals two new andrographolide derivatives (PubChem CID: 2734589 and 138968421) as natural bioactive molecules that can form stable complexes with both proteins via hydrophobic interactions, hydrogen bonds and electrostatic interactions. The toxicity analysis predicts class four toxicity for both compounds with LD50 value in the range of 500-700 mg/kg. MD simulation reveals the stable formation of the complex for both the compounds and their average trajectory values were found to be lower than the control inhibitor and protein alone. MMGBSA analysis corroborates the MD simulation result and showed the lowest energy for the compounds 2734589 and 138968421. The DFT and MEP analysis also predicts the better reactivity and stability of both the hit compounds. Overall, both andrographolide derivatives exhibit good potential as potent inhibitors for both nsp14 and nsp16 proteins, however, in-vitro and in vivo assessment would be required to prove their efficacy and safety in clinical settings. Moreover, the drug discovery strategy aiming at the dual target approach might serve as a useful model for inventing novel drug molecules for various other diseases.

Cross-talk between Vimentin and autophagy regulates blood-testis barrier disruption induced by cadmium

The blood-testis barrier (BTB) plays a vital role in mammalian spermatogenesis by separating the seminiferous epithelium into an adluminal and a basal compartment. Cadmium (Cd) is a toxic heavy metal that is widely present in the environment. We observed that Cd can induce BTB disruption, leading to apoptosis of testicular cells. However, the molecular mechanisms contributing to BTB injury induced by Cd have not yet been fully clarified. Vimentin (Vim) is an important desmosome-like junction protein that mediates robust adhesion in the BTB. In this study, we investigated how Vim responds to Cd. We found that Cd treatment led to a significant decrease in Vim expression, accompanied by a marked increase in LC3-II expression and a higer number of autophagosomes. Interestingly, we also observed that Cd-induced autophagy was associated with decreased Vim activity and enhanced apoptosis of testicular cells. To further investigate the role of autophagy in Vim regulation under Cd exposure, we treated cells with an autophagy inhibitor called 3-MA. We found that 3-MA treatment enhanced Vim expression and improved the disruption of the BTB under Cd exposure. Additionally, the inhibition of Vim confirmed the role of autophagy in modulating Vim expression. These results reveal a previously unknown regulatory mechanism of Cd involving the interplay between a heavy metal and a protein.

Docking and other computing tools in drug design against SARS-CoV-2

The use of computer simulation methods has become an indispensable component in identifying drugs against the SARS-CoV-2 coronavirus. There is a huge body of literature on application of molecular modelling to predict inhibitors against target proteins of SARS-CoV-2. To keep our review clear and readable, we limited ourselves primarily to works that use computational methods to find inhibitors and test the predicted compounds experimentally either in target protein assays or in cell culture with live SARS-CoV-2. Some works containing results of experimental discovery of corresponding inhibitors without using computer modelling are included as examples of a success. Also, some computational works without experimental confirmations are also included if they attract our attention either by simulation methods or by databases used. This review collects studies that use various molecular modelling methods: docking, molecular dynamics, quantum mechanics, machine learning, and others. Most of these studies are based on docking, and other methods are used mainly for post-processing to select the best compounds among those found through docking. Simulation methods are presented concisely, information is also provided on databases of organic compounds that can be useful for virtual screening, and the review itself is structured in accordance with coronavirus target proteins.

Synthesis and Anticancer Activity of Novel Derivatives of α,β-Unsaturated Ketones Based on Oleanolic Acid: in Vitro and in Silico Studies against Prostate Cancer Cells

Herein, new derivatives of α,β-unsaturated ketones based on oleanolic acid (4 a-i) were designed, synthesized, characterized, and tested against human prostate cancer (PC3). According to the in vitro cytotoxic study, title compounds (4 a-i) showed significantly lower toxicity toward healthy cells (HUVEC) in comparison with the reference drug doxorubicin. The compounds with the lowest IC50 values on PC3 cell lines were 4 b (7.785 μM), 4 c (8.869 μM), and 4 e (8.765 μM). The results of the ADME calculations showed that the drug-likeness parameters were within the defined ranges according to Lipinski's and Jorgensen's rules. For the most potent compounds 4 b, 4 c, and 4 e, a molecular docking analysis using the induced fit docking (IFD) protocol was performed against three protein targets (PARP, PI3K, and mTOR). Based on the IFD scores, compound 4 b had the highest calculated affinity for PARP1, while compound 4 c had higher affinities for mTOR and PI3K. The MM-GBSA calculations showed that the most potent compounds had high binding affinities and formed stable complexes with the protein targets. Finally, a 50 ns molecular dynamics simulation was performed to study the behavior of protein target complexes under in silico physiological conditions.

In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

The coronavirus disease 2019 (COVID-19) is a severe worldwide pandemic. Due to the emergence of various SARS-CoV-2 variants and the presence of only one Food and Drug Administration (FDA) approved anti-COVID-19 drug (remdesivir), the disease remains a mindboggling global public health problem. Developing anti-COVID-19 drug candidates that are effective against SARS-CoV-2 and its various variants is a pressing need that should be satisfied. This systematic review assesses the existing literature that used in silico models during the discovery procedure of anti-COVID-19 drugs. Cochrane Library, Science Direct, Google Scholar, and PubMed were used to conduct a literature search to find the relevant articles utilizing the search terms "In silico model," "COVID-19," "Anti-COVID-19 drug," "Drug discovery," "Computational drug designing," and "Computer-aided drug design." Studies published in English between 2019 and December 2022 were included in the systematic review. From the 1120 articles retrieved from the databases and reference lists, only 33 were included in the review after the removal of duplicates, screening, and eligibility assessment. Most of the articles are studies that use SARS-CoV-2 proteins as drug targets. Both ligand-based and structure-based methods were utilized to obtain lead anti-COVID-19 drug candidates. Sixteen articles also assessed absorption, distribution, metabolism, excretion, toxicity (ADMET), and drug-likeness properties. Confirmation of the inhibitory ability of the candidate leads by in vivo or in vitro assays was reported in only five articles. Virtual screening, molecular docking (MD), and molecular dynamics simulation (MDS) emerged as the most commonly utilized in silico models for anti-COVID-19 drug discovery.