Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer.

Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show upregulation and are linked to angiogenesis and lymphangiogenesis. This research aims to employ in-silico methods to target tyrosine kinase receptor proteins-VEGFR-1, VEGFR-2, and VEGFR-3, and identify novel inhibitors for Vascular Endothelial Growth Factors receptors (VEGFRs). A comprehensive literary study was conducted which identified 26 established inhibitors for VEGFR-1, VEGFR-2, and VEGFR-3 receptor proteins. Compounds with high-affinity scores, including PubChem ID-25102847, 369976, and 208908 were chosen from pre-existing compounds for creating Deep Learning-based models. RD-Kit, a Deep learning algorithm, was used to generate 43 million compounds for VEGFR-1, VEGFR-2, and VEGFR-3 targets. Molecular docking studies were conducted on the top 10 molecules for each target to validate the receptor-ligand binding affinity. The results of Molecular Docking indicated that PubChem IDs-71465,645 and 11152946 exhibited strong affinity, designating them as the most efficient molecules. To further investigate their potential, a Molecular Dynamics Simulation was performed to assess conformational stability, and a pharmacophore analysis was also conducted for indoctrinating interactions.

Real-world evidence: Risdiplam in a patient with spinal muscular atrophy type I with a novel splicing mutation and one SMN2 copy.

Spinal muscular atrophy (SMA), which results from the deletion or/and mutation in the SMN1 gene, is an autosomal recessive neuromuscular disorder that leads to weakness and muscle atrophy. SMN2 is a paralogous gene of SMN1. SMN2 copy number affects the severity of SMA, but its role in patients treated with disease modifying therapies is unclear. The most appropriate individualized treatment for SMA has not yet been determined. Here, we reported a case of SMA type I with normal breathing and swallowing function. We genetically confirmed that this patient had a compound heterozygous variant: one deleted SMN1 allele and a novel splice mutation c.628-3T>G in the retained allele, with one SMN2 copy. Patient-derived sequencing of 4 SMN1 cDNA clones showed that this intronic single transversion mutation results in an alternative exon (e)5 3' splice site, which leads to an additional 2 nucleotides (AG) at the 5' end of e5, thereby explaining why the patient with only one copy of SMN2 had a mild clinical phenotype. Additionally, a minigene assay of wild type and mutant SMN1 in HEK293T cells also demonstrated that this transversion mutation induced e5 skipping. Considering treatment cost and goals of avoiding pain caused by injections and starting treatment as early as possible, risdiplam was prescribed for this patient. However, the patient showed remarkable clinical improvements after treatment with risdiplam for 7 months despite carrying only one copy of SMN2. This study is the first report on the treatment of risdiplam in a patient with one SMN2 copy in a real-world setting. These findings expand the mutation spectrum of SMA and provide accurate genetic counseling information, as well as clarify the molecular mechanism of careful genotype-phenotype correlation of the patient.

Evaluation of chalcones as new glycogen phosphorylase inhibitors - an in-vitro and in-silico approach.

Diabetes mellitus (DM) remains one of the pivotal diseases that have drawn the attention of researchers recently and during the last few decades. Due to its devastating symptoms, attempts to develop new drugs with mild side effects have resulted in a number of drugs that are functioning through various mechanisms. Among these, Glycogen phosphorylase (GP) inhibitors emerged as a new strategy for combating DM. GP is an enzyme that regulates blood glucose levels; it catalyses the breakdown of glycogen to glucose-1-phosphate in the liver and tissues with high and fluctuating energy demands. In the present research, we evaluate the possibility of type 2 diabetes therapy with the help of chalcones which are known to have antidiabetic activities. For this purpose, 29 chalcones were modelled, synthesised and investigated for their inhibitory activity against GP using in-vitro methods. Compounds 1, 2, and 3 were found to be the most potent compounds with IC50 values 26.6, 57.1 and 75.6 µM respectively. The observed results were further validated using in-silico methods. Molecular docking simulation revealed interaction patterns that explain the structure-activity relationships of the compounds with GP. Molecular dynamic (MD) simulation demonstrated a stable complex formation between compound 1 and GP through lower value and uniformity in root mean square deviation (RMSD) of the complex and root mean square fluctuation (RMSF) of the protein Cα.

Molecular dynamic analyses of the interaction of SARS-CoV-1 or 2 variants with various angiotensin-converting enzyme-2 species.

The transmembrane glycoprotein angiotensin-converting enzyme 2 (ACE2) is a key component of the renin-angiotensin system (RAS). It was shown to be the receptor of severe acute respiratory syndrome coronavirus 2 in the COVID-19 outbreak (SARS-COV-2). Furthermore, ACE2 aids in the transport of amino acids across the membrane. ACE2 is lost from the membrane, resulting in soluble ACE2 (sACE2). We aim to examine the structural conformation alterations between SARS-CoV-1 or 2 variants at various periods with ACE2 from various sources, particularly in the area where it interacts with the viral protein and the receptor. It is important to study the molecular dynamics of ACE2/SARS-COV RBD when the structure is available on the database. Here we analyzed the crystal structure of ACE2 from Human, Dog, Mus, Cat, and Bat ACE2 in complex with RBD from SARS-COV-1 and SARS-COV-2. The result shows, there is a variation in the type of residues, number of contact atoms and hydrogen bonds in ACE2 and RBD during the interaction interfaces. By using molecular dynamics simulation, we can measure RMSD, RMSF, SASA, Rg and the difference in the percentage of α helix and ß strand. As bat ACE2 & SARS-CoV-2 RBD found to have a high amount of ß strand compared to another structure complex, while hACE2 & SARS-CoV-1 RBD has fewer amounts of ß strand. Our study provides a deep view of the structure which is available and a summary of many works around ACE2/SARS-CoV RBD interaction.Communicated by Ramaswamy H. Sarma.

Explainable artificial intelligence-assisted virtual screening and bioinformatics approaches for effective bioactivity prediction of phenolic cyclooxygenase-2 (COX-2) inhibitors using PubChem molecular fingerprints.

Cyclooxygenase-2 (COX-2) inhibitors are nonsteroidal anti-inflammatory drugs that treat inflammation, pain and fever. This study determined the interaction mechanisms of COX-2 inhibitors and the molecular properties needed to design new drug candidates. Using machine learning and explainable AI methods, the inhibition activity of 1488 molecules was modelled, and essential properties were identified. These properties included aromatic rings, nitrogen-containing functional groups and aliphatic hydrocarbons. They affected the water solubility, hydrophobicity and binding affinity of COX-2 inhibitors. The binding mode, stability and ADME properties of 16 ligands bound to the Cyclooxygenase active site of COX-2 were investigated by molecular docking, molecular dynamics simulation and MM-GBSA analysis. The results showed that ligand 339,222 was the most stable and effective COX-2 inhibitor. It inhibited prostaglandin synthesis by disrupting the protein conformation of COX-2. It had good ADME properties and high clinical potential. This study demonstrated the potential of machine learning and bioinformatics methods in discovering COX-2 inhibitors.

Inhibition of respiratory syncytial virus by Daclatasvir and its derivatives: synthesis of computational derivatives as a new drug development.

The most common cause of respiratory tract illness in newborns and young children is the respiratory syncytial virus (RSV). There is no approved vaccination or specific antiviral medication for RSV infections. Here, an attempt has been made to explore the potential of currently marketed drugs as well as their probable derivatives to improve the possibility of developing stronger medications against RSV. From the 100 synthetic drug compounds library, the best drug molecule was identified through drug-likeness properties, toxicity, molecular docking and molecular dynamics simulations. Molecular Mechanics Generalized Born Surface Area (MM-GBSA) was also a method that was applied in this study. Daclatasvir showed the highest binding energy and appeared as the best drug to inhibit matrix protein and a fusion protein of RSV. Based on Daclatasvir, 40 computational derivatives were made. D28, D34 and D40 showed far better results than the actual drug. Changes in lipophilicity character increase the binding energy of derivatives. Molecular dynamic simulations showed their non-deviated, non-fluctuated and stable complex formation with target proteins. The high number of amino acid contacts throughout the trajectory increases the stability and effectiveness of derivatives. The key to producing a novel medicine to eradicate RSV is provided by derivatives. Daclatasvir will be employed as a potential RSV inhibitor up until that point.Communicated by Ramaswamy H. Sarma.

Constituents of Stachys plants as potential dual inhibitors of AChE and NMDAR for the treatment of Alzheimer's disease: a molecular docking and dynamic simulation study.

Alzheimer's disease (AD) is a chronic neurodegenerative condition characterized by progressive cognitive impairment. While the formation of ß-amyloid plaques and neurofibrillary tangles are the hallmarks features of AD, the downstream consequence of these byproducts is the disruption of the cholinergic and glutamatergic neural systems. Growing evidence for the existence of interplay between AChE and NMDARs has opened up new venues for the discovery of novel ligands endowed with anticholinesterase and NMDAR-blocking activity. Plants belonging to the stachys genus have been extensively explored for having a broad range of therapeutic applications and have been used traditionally for millennia, to treat various CNS-related disorders, which makes them the ideal source of novel therapeutics. The present study was designed to identify natural dual-target inhibitors for AChE and NMDAR deriving from stachys genus for their potential use in AD. Using molecular docking, drug-likeness-profiling, MD simulation and MMGBSA calculations, an in-house database of biomolecules pertaining to the stachys genus was shortlisted based on their binding affinity, overall stability and critical ADMET parameters. Pre- and post-MD analysis revealed that Isoorientin effectively binds to AChE and NMDAR with various vital interactions, exhibits a stable behavior with minor fluctuations relative to two clinical drugs used as positive control, and displays strong and consistent interactions that lasted for the majority of the simulation. Findings from this study have elucidated the rationale behind the traditional use of Stachys plants for the treatment of AD and could provide new impetus for the development of novel dual-target therapeutics for AD treatment.Communicated by Ramaswamy H. Sarma.

Potential honey bee (Apis mellifera) allergens associated with IgE-mediated allergy- An In-silico study.

Allergies due to honeybee venom (HBV) are reported to be the second most common form of allergy to Hymenoptera venom that occurs after being stung. Indeed, 15-20% of people test IgE positive after being stung. However, accurate data on the incidence of honey bee allergens is missing and estimated to be less than 0.001%. Beekeeping is an ancient and widely practiced activity across the Kingdom of Saudi Arabia. Still, studies on the allergenic effect of the different subspecies of honey bees are very rare in Saudi Arabia. Hence, in this study, using the In-silico approach, we aimed to study and evaluate the effect of allergens from honey bees in Ha'il City, Saudi Arabia on IgE-mediated allergies. A list of potential allergens from Apis mellifera was prepared, and the 3D structure was prepared using the SWISS-MODEL web server and the PDB database was used for retrieving the structure of the immunoglobulin E- fragment antigen-binding (IgE-Fab) region. Molecular docking (clusPro webserver) and molecular dynamics (Schrödinger) results revealed that the B2D0J5 protein from Apis mellifera might be the key protein associated with IgE-mediated allergic response. Overall, the identified knowledge can be used for exploring prophylactic vaccine candidates and improving the diagnosis of allergic reactions to honey bees in the Ha'il region of Saudi Arabia.

Development and optimization of film forming non-pressurized liquid bandage for wound healing by Box-Behnken statistical design.

The goal of the current investigation was to develop a non-pressurized liquid bandage to promote the healing of wounds by using silver sulfadiazine. A three-factor three level box-behnken statistical design was employed to optimize the drug-loaded liquid bandage. Film-forming liquid bandage was developed by using ethyl-cellulose, dibutyl sebacate, and glycerol. For optimization, ethyl cellulose, dibutyl sebacate, and isopropyl myristate were taken as independent variables while tensile strength, water vapor absorption value, and drying time were taken as dependent variables. The film-forming liquid bandage was evaluated for various parameters like tensile strength, water vapor absorption value, drying time, viscosity, pH, in-vitro drug release studies, in-vivo wound healing studies, and stability studies. The optimized formulation was found with the tensile strength of 68.24 ± 0.24 MPa, water vapor absorption value of 2.00 ± 0.25 %, drying time of 1.75 ± 0.14 min, viscosity of 60 ± 0.5 cPs, pH of 6.0 ± 0.5 and good physicochemical properties with satisfactory film-forming ability. The in-vitro study shows that the release of test formulations was better than the marketed formulation. After 6 h of study, the liquid bandage and marketed formulation showed 41.02 % and 29.32 % of drug release respectively. Significant results were obtained for the in-vivo wound healing studies. Upon comparison with the control group (2.61 mm) and marketed formulation (1.44 mm), rats treated with the optimized formulation exhibited a noticeable improvement in wound contraction (0.8 mm). The liquid bandage after three months of stability testing was found to be stable with optimum. The film-forming liquid bandage was found to be an effective alternative to conventional topical preparations as it develops a thin polymeric layer on the wound and the skin around it and improves comfort for the patient by protecting the wound from external factors and physical harm.

Cheminformatics-based discovery of new organoselenium compounds with potential for the treatment of cutaneous and visceral leishmaniasis.

Leishmaniasis affects more than 12 million humans globally and a further 1 billion people are at risk in leishmaniasis endemic areas. The lack of a vaccine for leishmaniasis coupled with the limitations of existing anti-leishmanial therapies prompted this study. Cheminformatic techniques are widely used in screening large libraries of compounds, studying protein-ligand interactions, analysing pharmacokinetic properties, and designing new drug molecules with great speed, accuracy, and precision. This study was undertaken to evaluate the anti-leishmanial potential of some organoselenium compounds by quantitative structure-activity relationship (QSAR) modeling, molecular docking, pharmacokinetic analysis, and molecular dynamic (MD) simulation. The built QSAR model was validated (R2train = 0.8646, R2test = 0.8864, Q2 = 0.5773) and the predicted inhibitory activity (pIC50) values of the newly designed compounds were higher than that of the template (Compound 6). The new analogues (6a, 6b, and 6c) showed good binding interactions with the target protein (Pyridoxal kinase, PdxK) while also presenting excellent drug-likeness and pharmacokinetic profiles. The results of density functional theory, MD simulation, and molecular mechanics generalized Born surface area (MM/GBSA) analyses suggest the favourability and stability of protein-ligand interactions of the new analogues with PdxK, comparing favourably well with the reference drug (Pentamidine). Conclusively, the newly designed compounds could be synthesized and tested experimentally as potential anti-leishmanial drug molecules.Communicated by Ramaswamy H. Sarma.

Identification of novel dual acting ligands targeting the adenosine A2A and serotonin 5-HT1A receptors.

GPCRs are a family of transmembrane receptors that are profoundly linked to various neurological disorders, among which is Parkinson's disease (PD). PD is the second most ubiquitous neurological disorder after Alzheimer's disease, characterized by the depletion of dopamine in the central nervous system due to the impairment of dopaminergic neurons, leading to involuntary movements or dyskinesia. The current standard of care for PD is Levodopa, a dopamine precursor, yet the chronic use of this agent can exacerbate motor symptoms. Recent studies have investigated the effects of combining A2AR antagonist and 5-HT1A agonist on dyskinesia and motor complications in animal models of PD. It has been proved that the drug combination has significantly improved involuntary movements while maintaining motor activity, highlighting as a result new lines of therapy for PD treatments, through the regulation of both receptors. Using a combination of ligand-based pharmacophore modelling, virtual screening, and molecular dynamics simulation, this study intends on identifying potential dual-target compounds from IBScreen. Results showed that the selected models displayed good enrichment metrics with a near perfect receiver operator characteristic (ROC) and Area under the accumulation curve (AUAC) values, signifying that the models are both specific and sensitive. Molecular docking and ADMET analysis revealed that STOCK2N-00171 could be potentially active against A2AR and 5-HT1A. Post-MD analysis confirmed that the ligand exhibits a stable behavior throughout the simulation while maintaining crucial interactions. These results imply that STOCK2N-00171 can serve as a blueprint for the design of novel and effective dual-acting ligands targeting A2AR and 5-HT1A.Communicated by Ramaswamy H. Sarma.

Relationship between gut microbiota dysbiosis and immune indicator in children with sepsis.

Sepsis is a life-threatening multiple-organ injury caused by disordered host immune response to microbial infection. However, the correlation between gut microbiota dysbiosis and immune indicators remains unexplored. To address this gap in knowledge, we carried out 16 S rDNA sequencing, analyzed clinical fecal samples from children with sepsis (n = 30) and control children (n = 25), and obtained immune indicators, including T cell subtypes (CD3+, CD3+CD4+, CD3+CD8+, and CD4/CD8), NK cells, cytokines (IL-2, IL-4, IL-6, IL-10, TNF-α and IFN-γ), and immunoglobulin indices (IgA, IgE, IgM and IgG). In addition, we analyzed the correlation between gut microbiota dysbiosis and immune indicators, and evaluated the clinical discriminatory power of discovered bacterial biomarkers. We found that children with sepsis exhibited gut bacterial dysbiosis and low alpha diversity. The Spearman's rank correlation coefficient suggested that Rhodococcus erythropolis had a significantly positive correlation with IFN-γ and CD3+ T cells. Klebsiella pneumoniae and Streptococcus mitis were significantly correlated with NK cells. Bacteroides uniformis was significantly positively correlated with IgM and erythrocyte sedimentation rate, and Eubacterium eligens was significantly positively correlated with IL-4 and CD3+CD8+ T cells. The biomarkers discovered in this study had strong discriminatory power. These changes in the gut microbiome may be closely related to immunologic dysfunction and to the development or exacerbation of sepsis. However, a large sample size is required for verification.

Promising Experimental Anti-SARS-CoV-2 Agent "SLL-0197800": The Prospective Universal Inhibitory Properties against the Coming Versions of the Coronavirus.

Isoquinoline derivatives having some nucleosidic structural features are considered as candidate choices for effective remediation of the different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and their following disease, the coronavirus disease 2019 (COVID-19). SLL-0197800 is a recently discovered isoquinoline compound with potential strong universal anticoronaviral activities against SARS-CoV-2 and its previous strains. SLL-0197800 nonspecifically hits the main protease (Mpro) enzyme of the different coronaviruses. Herein in the present study, we tested the probability of the previous findings of this experimental agent to be extended to comprise any coronavirus through concurrently disrupting the mutable-less replication enzymes like the RNA-dependent RNA polymerase (RdRp) protein as well as the 3'-to-5' exoribonuclease (ExoN) protein. The in vitro anti-RdRp/ExoN assay revealed the potent inhibitory activities of SLL-0197800 on the coronaviral replication with minute values of anti-RdRp and anti-RdRp/ExoN EC50 (about 0.16 and 0.27 µM, respectively). The preliminary in silico outcomes significantly supported these biochemical findings. To put it simply, the present important results of these extension efforts greatly reinforce and extend the SLL-0197800's preceding findings, showing that the restraining/blocking actions (i.e., inhibitory activities) of this novel investigational anti-SARS-CoV-2 agent against the Mpro protein could be significantly extended against other copying and multiplication enzymes such as RdRp and ExoN, highlighting the potential use of SLL-0197800 against the coming versions of the homicidal coronavirus (if any), i.e., revealing the probable nonspecific anticoronaviral features and qualities of this golden experimental drug against nearly any coronaviral strain, for instance, SARS-CoV-3.

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.

Acute necrotizing encephalopathy in children with COVID-19: a retrospective study of 12 cases.

Background: Acute necrotizing encephalopathy (ANE) is a devastating neurologic condition that can arise following a variety of systemic infections, including influenza and SARS-Cov-2. The clinical features of COVID-19-associated ANE in pediatric patients based on multi-case data have not yet been described and remain obscure. We reviewed 12 pediatric patients to better describe the clinical features of ANE with COVID-19. Methods: We retrospectively collected and summarized the clinical features of ANE in children with COVID-19. Clinical data were collected from 12 children, including their general status, clinical symptoms, laboratory tests, and neuroimaging features. Results: Among the subjects, 10 were over 5 years old and they accounted for 83.33%. A large percentage of those affected (66.67%) were females. The major manifestations included fever (100%), impaired consciousness (100%), and convulsions (75%). We determined that increased interleukin (IL)-6 and IL-10, and tumor necrosis factor-α and interferon gamma were not predictive of severe ANE and mortality in children with COVID-19 in this study. All children presented with abnormal neuroimaging with multiple and symmetrically distributed lesions, involving the thalamus, basal ganglia, cerebellum, and brain hemispheres. Eight of the 12 children died, resulting in a mortality rate of 66.67%, and 75% of these children were females. Importantly, we found the timely administration of mannitol after an acute onset of convulsions or disturbance of consciousness may be decreased the high mortality induced by ANE children with COVID-19. Conclusion: COVID-19 associated with ANE in children is characterized by sudden symptom onset, rapid disease progression, and high mortality.

In-silico screening of Acacia pennata and Bridelia retusa reveals pinocembrin-7-O-ß-D-glucopyranoside as a promising ß-lactamase inhibitor to combat antibiotic resistance.

The ß-lactamase of Pseudomonas aeruginosa is known to degrade ß-lactam antibiotics such as penicillins, cephalosporins, monobactams, and carbapenems. With the discovery of an extended-spectrum ß-lactamase in a clinical isolate of P. aeruginosa, the bacterium has become multi-drug resistant. In this study, we aim to identify new ß-lactamase inhibitors by virtually screening a total of 43 phytocompounds from two Indian medicinal plants. In the molecular docking studies, pinocembrin-7-O-ß-D-glucopyranoside (P7G) (-9.6 kcal/mol) from Acacia pennata and ellagic acid (EA) (-9.2 kcal/mol) from Bridelia retusa had lower binding energy than moxalactam (-8.4 kcal/mol). P7G and EA formed 5 (Ser62, Asn125, Asn163, Thr209, and Ser230) and 4 (Lys65, Ser123, Asn125, and Glu159) conventional hydrogens bonds with the active site residues. 100 ns MD simulations revealed that moxalactam and P7G (but not EA) were able to form a stable complex. The binding free energy calculations further revealed that P7G (-59.6526 kcal/mol) formed the most stable complex with ß-lactamase when compared to moxalactam (-46.5669 kcal/mol) and EA (-28.4505 kcal/mol). The HOMO-LUMO and other DFT parameters support the stability and chemical reactivity of P7G at the active site of ß-lactamase. P7G passed all the toxicity tests and bioavailability tests indicating that it possesses drug-likeness. Among the studied compounds, we identified P7G of A. pennata as the most promising phytocompound to combat antibiotic resistance by potentially inhibiting the ß-lactamase of P. aeruginosa.Communicated by Ramaswamy H. Sarma.

Metformin as a promising target for DPP4 expression: computational modeling and experimental validation.

Metformin is a regularly prescribed and low-cost generic medication. Metformin has been proposed as a target for Dipeptidyl-peptidase 4 (DPP4) expression in various clinical disorders. We provide insilco investigations on molecular docking and dynamic modeling of metformin and DPP4 potential interactions. Moreover, we conducted bioinformatic studies to highlight the clinical significance of DPP4 expression and mutation in various types of malignancies, as well as the invasion of different immune cells into the tumor microenvironment. We believe the present proposal's findings have crucial implications for understanding how metformin may confer health advantages by targeting DPP4 expression in malignancies.