Bioinformatics approaches identified dasatinib and bortezomib inhibit the activity of MCM7 protein as a potential treatment against human cancer

In Silico-Based Identification of Natural Inhibitors from Traditionally Used Medicinal Plants that can Inhibit Dengue Infection

Dengue fever (DF) is an endemic disease that has become a public health concern around the globe. The NS3 protease-helicase enzyme is an important target for the development of antiviral drugs against DENV (dengue virus) due to its impact on viral replication. Inhibition of the activity of the NS3 protease-helicase enzyme complex significantly inhibits the infection associated with DENV. Unfortunately, there are no scientifically approved antiviral drugs for its prevention. However, this study has been developed to find natural bioactive molecules that can block the activity of the NS3 protease-helicase enzyme complex associated with DENV infection through molecular docking, MM-GBSA (molecular mechanics-generalized born surface area), and molecular dynamics (MD) simulations. Three hundred forty-two (342) compounds selected from twenty traditional medicinal plants were retrieved and screened against the NS3 protease-helicase protein by molecular docking and MM-GBSA studies, where the top six phytochemicals have been identified based on binding affinities. The six compounds were then subjected to pharmacokinetics and toxicity analysis, and we conducted molecular dynamics simulations on three protein-ligand complexes to validate their stability. Through computational analysis, this study revealed the potential of the two selected natural bioactive inhibitors (CID-440015 and CID-7424) as novel anti-dengue agents.

Fragment-based drug design of novel inhibitors targeting lipoprotein (a) kringle domain KIV-10-mediated cardiovascular disease

Cardiovascular diseases (CVDs) are the leading cause of death globally, attributed to a complex etiology involving metabolic, genetic, and protein-related factors. Lipoprotein(a) (Lp(a)), identified as a genetic risk factor, exhibits elevated levels linked to an increased risk of cardiovascular diseases. The lipoprotein(a) kringle domains have recently been identified as a potential target for the treatment of CVDs, in this study we utilized a fragment-based drug design approach to design a novel, potent, and safe inhibitor for lipoprotein(a) kringle domain. With the use of fragment library (61,600 fragments) screening, combined with analyses such as MM/GBSA, molecular dynamics simulation (MD), and principal component analysis, we successfully identified molecules effective against the kringle domains of Lipoprotein(a). The hybridization process (Breed) of the best fragments generated a novel 249 hybrid molecules, among them 77 exhibiting superior binding affinity (≤ -7 kcal/mol) compared to control AZ-02 (-6.9 kcal/mol), Importantly, the top ten molecules displayed high similarity to the control AZ-02. Among the top ten molecules, BR1 exhibited the best docking energy (-11.85 kcal/mol ), and higher stability within the protein LBS site, demonstrating the capability to counteract the pathophysiological effects of lipoprotein(a) [Lp(a)]. Additionally, principal component analysis (PCA) highlighted a similar trend of motion during the binding of BR1 and the control compound (AZ-02), limiting protein mobility and reducing conformational space. Moreover, ADMET analysis indicated favorable drug-like properties, with BR1 showing minimal violations of Lipinski's rules. Overall, the identified compounds hold promise as potential therapeutics, addressing a critical need in cardiovascular medicine. Further preclinical and clinical evaluations are needed to validate their efficacy and safety, potentially ushering in a new era of targeted therapies for CVDs.

The potential for senotherapy as a novel approach to extend life quality in veterinary medicine

Cellular senescence, a condition where cells undergo arrest and can assume an inflammatory phenotype, has been associated with initiation and perpetuation of inflammation driving multiple disease processes in rodent models and humans. Senescent cells secrete inflammatory cytokines, proteins, and matrix metalloproteinases, termed the senescence associated secretory phenotype (SASP), which accelerates the aging processes. In preclinical models, drug interventions termed "senotherapeutics" selectively clear senescent cells and represent a promising strategy to prevent or treat multiple age-related conditions in humans and veterinary species. In this review, we summarize the current available literature describing in vitro evidence for senotheraputic activity, preclinical models of disease, ongoing human clinical trials, and potential clinical applications in veterinary medicine. These promising data to date provide further justification for future studies identifying the most active senotherapeutic combinations, dosages, and routes of administration for use in veterinary medicine.

Pharmacokinetics and drug-likeness of anti-cancer traditional Chinese medicine: molecular docking and molecular dynamics simulation study

MCM7 (Minichromosome Maintenance Complex Component 7) is a component of the DNA replication licensing factor, which controls DNA replication. The MCM7 protein is linked to tumor cell proliferation and has a function in the development of several human cancers. Several types of cancer may be treated by inhibiting the protein, as it is strongly produced throughout this process. Significantly, Traditional Chinese Medicine (TCM), which has a long history of clinical adjuvant use against cancer, is rapidly gaining traction as a valuable medical resource for the development of novel cancer therapies, including immunotherapy. Therefore, the goal of the research was to find small molecular therapeutic candidates against the MCM7 protein that may be used to treat human cancers. A computational-based virtual screening of 36,000 natural TCM libraries is carried out for this goal using a molecular docking and dynamic simulation technique. Thereby, ∼8 novel potent compounds i.e., ZINC85542762, ZINC95911541, ZINC85542617, ZINC85542646, ZINC85592446, ZINC85568676, ZINC85531303, and ZINC95914464 were successfully shortlisted, each having the capacity to penetrate the cell as potent inhibitors for MCM7 to curb this disorder. These selected compounds were found to have high binding affinities compared to the reference (AGS compound) i.e. < -11.0 kcal/mol. ADMET and pharmacological properties showed that none of these 8 compounds poses any toxic property (carcinogenicity) and have anti-metastatic, and anticancer activity. Additionally, MD simulations were run to assess the compounds' stability and dynamic behavior with the MCM7 complex for about 100 ns. Finally, ZINC95914464, ZINC95911541, ZINC85568676, ZINC85592446, ZINC85531303, and ZINC85542646 are identified as highly stable within the complex throughout the 100 ns simulations. Moreover, the results of binding free energy suggested that the selected virtual hits significantly bind to the MCM7 which implied these compounds may act as a potential MCM7 inhibitor. However, in vitro testing protocols are required to further support these results. Further, assessment through various lab-based trial methods can assist with deciding the action of the compound that will give options in contrast to human cancer immunotherapy.Communicated by Ramaswamy H. Sarma.

Potential of Gut Microbial Metabolites in Treating Osteoporosis and Obesity: A Network Pharmacology and Bioinformatics Approach

BACKGROUND The gut microbial metabolites demonstrate significant activity against metabolic diseases including osteoporosis (OP) and obesity, but active compounds, targets, and mechanisms have not been fully identified. Hence, the current investigation explored the mechanisms of active metabolites and targets against OP and obesity by using network pharmacology approaches. MATERIAL AND METHODS The gutMGene database was used to collect gut microbial targets-associated metabolites; DisGeNET and OMIM databases were used to identify targets relevant to OP and obesity. A total of 63 and 89 overlapped targets were considered the final OP and obesity targets after creating a Venn diagram of metabolites-related targets and disease-related targets. Furthermore, the top 20% of degrees, betweenness, and closeness were used to form the sub-network of protein-protein interaction of these targets. Finally, the biotransformation-increased receptors and biological mechanisms were identified and validated using ADMET properties analysis, molecular docking, and molecular dynamic simulation. RESULTS GO, KEGG pathway analysis, and protein-protein interactions were performed to establish metabolites and target networks. According to the enrichment analysis, OP and obesity are highly linked to the lipid and atherosclerosis pathways. Moreover, ADMET analysis depicts that the major metabolites have drug-likeliness activity and no or less toxicity. Following that, the molecular docking studies showed that compound K and TP53 target have a remarkable negative affinity (-8.0 kcal/mol) among all metabolites and targets for both diseases. Finally, the conformity of compound K against the targeted protein TP53 was validated by 250ns MD simulation. CONCLUSIONS Therefore, we summarized that compound K can regulate TP53 and could be developed as a therapy option for OP and obesity.

Discovery of Melittin as Triple-Action Agent: Broad-Spectrum Antibacterial, Anti-Biofilm, and Potential Anti-Quorum Sensing Activities

The development of antibiotic-resistant microorganisms is a major global health concern. Recently, there has been an increasing interest in antimicrobial peptides as a therapeutic option. This study aimed to evaluate the triple-action (broad-spectrum antibacterial, anti-biofilm, and anti-quorum sensing activities) of melittin, a membrane-active peptide present in bee venom. The minimum inhibitory concentration and minimum bactericidal concentration of the melittin were determined using the microdilution method and agar plate counting. Growth curve analysis revealed that melittin showed a concentration-dependent antibacterial activity. Scanning electron microscope analysis revealed that melittin treatment altered the morphology. Confocal laser scanning microscope revealed that melittin increased the membrane permeability and intracellular ROS generation in bacteria, all of which contribute to bacterial cell death. In addition, the crystal violet (CV) assay was used to test the anti-biofilm activity. The CV assay demonstrated that melittin inhibited biofilm formation and eradicated mature biofilms. Biofilm formation mediated by quorum sensing (QS) plays a major role in this regard, so molecular docking and molecular dynamics analysis confirmed that melittin interacts with LasR receptors through hydrogen bonds, and further evaluates the anti-QS activity of melittin through the production of virulence factors (pyocyanin, elastase, and rhamnolipid), exopolysaccharides secretion, and bacterial motility, that may be the key to inhibiting the biofilm formation mechanism. The present findings highlight the promising role of melittin as a broad-spectrum antibacterial, anti-biofilm agent, and potential QS inhibitor, providing a new perspective and theoretical basis for the development of alternative antibiotics.

Potent multi-target natural inhibitors against SARS-CoV-2 from medicinal plants of the Himalaya: a discovery from hybrid machine learning, chemoinformatics, and simulation assisted screening

The emergence and immune evasion ability of SARS-CoV-2 Omicron strains, mainly BA.5.2 and BF.7 and other variants of concern have raised global apprehensions. With this context, the discovery of multitarget inhibitors may be proven more comprehensive paradigm than its one-drug-to-one target counterpart. In the current study, a library of 271 phytochemicals from 25 medicinal plants from the Indian Himalayan Region has been virtually screened against SARS-CoV-2 by targeting nine virus proteins, viz., papain-like protease, main protease, nsp12, helicase, nsp14, nsp15, nsp16, envelope, and nucleocapsid for screening of a multi-target inhibitor against the viral replication. Initially, 94 phytochemicals were screened by a hybrid machine learning model constructed by combining 6 confirmatory bioassays against SARS-CoV-2 replication using an instance-based learner lazy k-nearest neighbour classifier. Further, 25 screened compounds with excellent drug-like properties were subjected to molecular docking. The phytochemical Cepharadione A from the plant Piper longum showed binding potential against four proteins with the highest binding energy of -10.90 kcal/mol. The compound has acceptable absorption, distribution, metabolism, excretion, and toxicity properties and exhibits stable binding behaviour in terms of root mean square deviation (0.068 ± 0.05 nm), root-mean-square fluctuation, hydrogen bonds, solvent accessible surface area (83.88-161.89 nm2), and molecular mechanics Poisson-Boltzmann surface area during molecular dynamics simulation of 200 ns with selected target proteins. Concerning the utility of natural compounds in the therapeutics formulation, Cepharadione A could be further investigated as a remarkable lead candidate for the development of therapeutic drugs against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Potential Effect of Baobab's Polyphenols as Antihyperlipidemic Agents: In Silico Study

Adansonia digitata L. is an African tree commonly called baobab. This tree is effectively used in traditional medicine to treat cardiovascular disorders. Hyperlipidemia is a well-known cardiovascular risk factor associated with the increased incidence of mortality worldwide. This study aimed to demonstrate the mechanism of baobab polyphenols in the activities of hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase and pancreatic lipase as lipid metabolic enzymes. Molecular docking and an incentive for drug design showed that all the polyphenols in baobab bound to the proteins with higher affinity and a lower binding energy compared with simvastatin as the positive control (ΔG: from -5.5 kcal/mol to -6.5 kcal/mol). The same polyphenols exhibited a considerable binding affinity to pancreatic lipase (ΔG: from -7.5 kcal/mol to -9.8 kcal/mol) in comparison with the control and HMG-CoA reductase. Quercetin showed the best docking score from the selected Baobab polyphenols (ΔG = -9.8 kcal/mol). The root mean square deviation (RMSD) results indicated that stable epicatechin and quercetin complexes were demonstrated with HMG-CoA reductase, and other less stable complexes were developed using rutin and chlorogenic acid. Moreover, the analysis of the root mean square fluctuation (RMSF) simulation results was consistent with that of the RMSD. The RMSF value for all the baobab polyphenols, including the crystal control ligand, was kept between 0.80 and 8.00 Å, similarly to simvastatin, and less than 4.8 Å for pancreatic lipase. Chlorogenic acid, quercetin, epicatechin, and rutin had negative ΔG binding scores from highest to lowest. The same ligands displayed more negative ΔG binding scores than those observed in HMG-CoA reductase and crystal control ligand (methoxyundecyl phosphinic acid) in their simulation with pancreatic lipase. In conclusion, baobab polyphenols interact with HMG-CoA reductase and pancreatic lipase to inhibit their substrate binding and block their activity.

A five-cuproptosis-related LncRNA Signature: predicting prognosis, assessing immune function & drug sensitivity in lung squamous cell carcinoma

Lung squamous cell carcinoma has so far lacked effective targets for diagnosis and treatment. In cancer research, long noncoding RNAs (LncRNAs) emerge as novel therapeutic targets and biomarkers. Cuprophosis is a new death type involving multiple biological processes in tumor cells. Here, we aimed to explore whether Cuprophosis-related lncRNAs could be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients. The Cancer Genome Map (TCGA) was used to obtain genome and clinical data, and Cuprophosis-relevant genes were found in the literature. A cuproptosis-related lncRNA risk model was built using co-expression analysis, univariate/multivariate Cox regression, and LASSO analysis. The survival analysis was used to assess the model's prognostic value. The univariate and multivariate Cox regression analyses were performed to determine whether risk score, age, gender, or clinical stages could be used as independent prognostic factors. Gene Set Enrichment Analysis and mutation analysis were performed on differentially expressed mRNA between high-risk and low-risk groups. The (TIDE) algorithm was used to conduct immunological functional analysis and drug sensitivity testing. Five cuproptosis-related LncRNAs were identified, and the selected LncRNAs constructed a prognosis model. According to the Kaplan-Meier survival analysis, the overall survival time for patients in the high-risk group was shorter than for those in the low-risk group. For LUSC patients, the risk score serves as an independent prognostic indicator. The GO and KEGG enrichment analysis revealed that the differentially expressed mRNAs between the high- and low-risk groups were enriched in several immune-related processes. The enrichment score of differentially expressed mRNAs in the high-risk group is higher than that of the low-risk group in multiple immune function pathways, including the IFN-γ and MHC I pathways. The Tumor Immune Dysfunction and Exclusion (TIDE) test revealed that the high-risk group was more likely to experience immune escape. The drug sensitivity analysis showed that patients with low-risk ratings were likely to respond to GW441756 and Salubrinal. In contrast, patients with higher risk scores were more responsive to dasatinib and Z-LLNIe CHO. The 5-Cuprophosis-related lncRNA signature can be used to predict prognosis, assess immune function, and test drug sensitivity in LUSC patients.

Molecular Dynamic Analysis of Carbapenem-Resistant Klebsiella pneumonia’s Porin Proteins with Beta Lactam Antibiotics and Zinc Oxide Nanoparticles

To prevent the rapidly increasing prevalence of bacterial resistance, it is crucial to discover new antibacterial agents. The emergence of Klebsiella pneumoniae carbapenemase (KPC)-producing Enterobacteriaceae has been associated with a higher mortality rate in gulf union countries and worldwide. Compared to physical and chemical approaches, green zinc oxide nanoparticle (ZnO-NP) synthesis is thought to be significantly safer and more ecofriendly. The present study used molecular dynamics (MD) to examine how ZnO-NPs interact with porin protein (GLO21), a target of β-lactam antibiotics, and then tested this interaction in vitro by determining the zone of inhibition (IZ), minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC), as well as the alteration of KPC’s cell surface. The nanoparticles produced were characterized by UV-Vis spectroscopy, zetasizer, Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). In silico investigation was conducted using a variety of computational techniques, including Autodock Vina for protein and ligand docking and Desmond for MD simulation. The candidate ligands that interact with the GLO21 protein were biosynthesized ZnO-NPs, meropenem, imipenem, and cefepime. Analysis of MD revealed that the ZnO-NPs had the highest log P value (−9.1 kcal/mol), which indicates higher permeability through the bacterial surface, followed by cefepime (−7.9 kcal/mol), meropenem (−7.5 kcal/mol), and imipenem (−6.4 kcal/mol). All tested compounds and ZnO-NPs possess similar binding sites of porin proteins. An MD simulation study showed a stable system for ZnO-NPs and cefepime, as confirmed by RMSD and RMSF values during 100 ns trajectories. The test compounds were further inspected for their intersection with porin in terms of hydrophobic, hydrogen, and ionic levels. In addition, the stability of these bonds were measured by observing the protein–ligand contact within 100 ns trajectories. ZnO-NPs showed promising results for fighting KPC, represented in MIC (0.2 mg/mL), MBC (0.5 mg/mL), and ZI (24 mm diameter). To draw the conclusion that ZnO-NP is a potent antibacterial agent and in order to identify potent antibacterial drugs that do not harm human cells, further in vivo studies are required.

Fludarabine, a Potential DNA-Dependent RNA Polymerase Inhibitor, as a Prospective Drug against Monkeypox Virus: A Computational Approach

Monkeypox is a zoonotic contagious disease that has recently re-emerged in different countries worldwide. Due to the lack of an effective treatment that eliminates the virus, there is an urgent need to find effective drugs to stop the spread of the multi-country outbreak. The current study aimed to use computational methods to quickly identify potentially effective drugs against the Monkeypox virus (MPXV). Three MPXV proteins were targeted in this study due to their essential role in viral replication (a DNA-Dependent RNA Polymerase subunit (A6R)), a protein involved in cell entry (D8L), and a protein catalyzing the envelopment of intracellular mature virus particles (F13L). We virtually screened a library of 1615 FDA-approved compounds, utilizing different in-silico approaches including computational modeling, molecular docking, molecular dynamic (MD) simulation, and MM-GBSA. The compound Fludarabine was found to have the best docking score (−7.53 kcal/mol) in relation to the MPXV A6R protein. Additionally, Fludarabine showed in-silico activity on the D8L and F13L proteins. During the whole period of the 100 ns MD simulation, the complex of A6R and Fludarabine exhibited the best stability. This stability was reflected in a good score of MM-GBSA, with an average value of −44.62 kcal/mole in a range between −53.26 and −35.49 and a low value of standard deviation (3.76). Furthermore, Fludarabine blocked efficiently the Asn175 residue which has an important role in the attachment of the virus to a host cell. The results of this study recommend more in vitro studies on this compound, as a starting point to develop a novel treatment against MPXV.

The Potential Role of Nigella sativa Seed Oil as Epigenetic Therapy of Cancer

Nigella sativa oil, commonly known as black seed oil (BSO), is a well-known Mediterranean food, and its consumption is associated with beneficial effects on human health. A large number of BSO's therapeutic properties is attributed to its pharmacologically active compound, thymoquinone (TQ), which inhibits cell proliferation and induces apoptosis by targeting several epigenetic players, including the ubiquitin-like, containing plant homeodomain (PHD) and an interesting new gene, RING finger domains 1 (UHRF1), and its partners, DNA methyltransferase 1 (DNMT1) and histone deacetylase 1 (HDAC1). This study was designed to compare the effects of locally sourced BSO with those of pure TQ on the expression of the epigenetic complex UHRF1/DNMT1/HDAC1 and the related events in several cancer cells. The gas chromatographs obtained from GC-MS analyses of extracted BSO showed that TQ was the major volatile compound. BSO significantly inhibited the proliferation of MCF-7, HeLa and Jurkat cells in a dose-dependent manner, and it induced apoptosis in these cell lines. BSO-induced inhibitory effects were associated with a significant decrease in mRNA expression of UHRF1, DNMT1 and HDAC1. Molecular docking and MD simulation showed that TQ had good binding affinity to UHRF1 and HDAC1. Of note, TQ formed a stable metal coordinate bond with zinc tom, found in the active site of the HDAC1 protein. These findings suggest that the use of TQ-rich BSO represents a promising strategy for epigenetic therapy for both solid and blood tumors through direct targeting of the trimeric epigenetic complex UHRF1/DNMT1/ HDAC1.