MM-GBSA Calculations Research Articles

Identification of potential inhibitors for MAP4K4 in glaucoma using meta-dynamics-based dissociation free energy calculation

Glaucoma, a prevalent eye ailment causing irreversible vision loss, affects over 295 million individuals globally, necessitating the exploration of novel therapeutic avenues. Despite extensive research on targets like the phosphodiesterase enzyme and rho kinase, the potential of MAP4K4 in glaucoma remains untapped. This study aims to identify potent MAP4K4 inhibitors to counteract retinal cell apoptosis and oxidative stress associated with glaucoma. Using HTVS and XP docking, 911,059 compounds were screened. The MMGBSA calculation and pharmacokinetics analysis were used to shortlist the compounds. After performing 75 molecular dynamics simulations, further meta-dynamics were employed to calculate dissociation-free energy and find potential MAP4K4 inhibitors. Findings indicated that ZINC06717217 and ZINC38836256 exhibited remarkable promise, with docking scores of −9.57 and −11.12 and MMGBSA binding energies of −91.07 kcal/mol and −87.52 kcal/mol, respectively. Comparative analysis with the reference compound Q27453723 underscored their superior stability, requiring dissociation-free energies of −15.11 kcal/mol and −12.46 kcal/mol to disengage from the docked complex. This underscored their robust binding affinity. ZINC06717217 and ZINC38836256 show promising stability and strong binding to the MAP4K4 protein. Hence, these findings are promising in inhibiting MAP4K4 for glaucoma treatment, potentially leading to more effective treatment and curing blindness. Key messagesFirst to incorporate the dissociation-free energy for identifying compounds for glaucoma treatment.In-silico analysis showed that ZINC06717217 and ZINC38836256 are promising compounds for targeting MAP4K4.

An in silico approach uncovering the competency of oncolytic human adenovirus 52 for targeted breast cancer virotherapy

Breast cancer remains a major health threat throughout the world specifically in women above 30 years of age however, it is rarely known to affect men as well. It is characterized by the abnormal division of cells in the breast tissue resulting in the development of breast malignancies. Various risk factors contributing to breast cancer include age, family history, genetic mutations (chiefly in BRCA1 and BRCA2 genes) along with hormonal imbalances (oestrogen, progesterone, HER2). Early detection which can be obtained through frequent rounds of self-examination, mammographic scanning, and clinical assessment plays a crucial role in the prevention of the disease. In addition, appropriate diagnosis assists in better therapeutic responses. This study highlights the considerable health risks associated with the conventional treatment procedures which arise and increased demand of advanced, secure, and risk-free treatment alternatives. Oncolytic viruses are potentially apparent for the aim of improving cancer therapeutics with reduced side effects. These viruses act as the fundamental therapeutic agent themselves that selectively target and kill malignant cells without harm to healthy tissues. The key objective of the research is to provide evidence that Human Adenovirus 52 is a potent oncolytic virus and to highlight its capacity to target and eliminate cancer cells with precision while causing the least amount of harm to healthy tissues. Validating the in-silico method entails evaluating the precision and dependability of the computational modelling by contrasting the in-silico predictions with the findings from the experiments rank as the secondary objective. The workflow of this research utilized in-silico computational drug designing approaches including retrieval of tertiary structures of both the target Breast Cancer Type 1 Susceptibility Protein (BRCA1) and the viral Human Adenovirus 52 protein, their validation generating Ramachandran Plots determining favoured amino acid residue angles and prediction of their active residues. Furthermore, the study focused on the molecular dynamics docking of proteins, interpretation of molecular interactions between the docked complex, as well as the assessment of the molecular dynamic simulations (MD) in addition to their MMGBSA binding energy calculations. A successful docking between BRCA1 and Adenovirus protein provided a significant score of 329.2 +/- 24.3, furthermore, MD simulations showed a high RMSD peak at 2.8 Å, RMSF were maximum at 3.5 Å with highest protein–protein interaction, the radius of gyration was stable throughout the simulation representing elastic stability along with a high energy interaction value of - 7882 kCal/mol. Moreover, the MMGBSA calculation results showed a notable release of binding free energy of - 68.96 kCal/mol demonstrating effective bond formation between the docked complex. These findings propose the effectiveness of Human Adenovirus 52 to treat cancer. The selected oncolytic Human Adenovirus 52 is a potential candidate for the target specific treatment of breast cancer through virotherapy. This computer-aided drug discovery presents significant potential in targeting cancer cells and would assist in the development of potent drug reagents for the cancer therapy.

Rational design of some 1,3,4 trisubstituted pyrazole-thiazole derivatives to serve as MtInhA inhibitors using QSAR, ADMET, molecular docking, MM-GBSA, and molecular dynamics simulations approach

Using computational approaches, the potential efficacy and specificity of 1,3,4 trisubstituted pyrazole derivatives as MtInhA inhibitors which will aid in rational drug design for tubercular therapy were forecasted. QSARINS software was used to investigate the ability of compound to inhibit MtInhA. Three noteworthy descriptors with significant correlations and impressive statistical values were identified by the produced QSAR model: Correlation of coefficient(R2)= 0.8789, Cross-validation leave one out correlation coefficient (Q2LOO)= 0.8402, Cross-validation leave-many-out correlation coefficient(Q2LMO)=0.7321, Concordance Correlation Coefficient for cross-validation(CCCtr)=0.9355, CCCext =0.888. The descriptor generated by the QSAR model includes Centered Broto-Moreau autocorrelation weighted by Sanderson electronegativities (ATSC1e), Radial distribution functions at 15.0 and 2.0 Å inter-atomic distances weighted by relative van der Waals volumes (RDF150v), Radial distribution function – 145/weighted by relative I-state (RDF145s). Using these, three descriptor model was developed and the designed compounds were evaluated for their MtInhA inhibitory activity. Further, ADMET prediction and Molecular docking studies were carried out using Schrodinger's Software. ADMET prediction were used to evaluate drug likeliness and molecular docking was used to determine the interactions of designed compounds with the target protein. After the docking studies, the compounds were subjected for MM-GBSA calculations and MD simulation. Among the designed compounds, AP2 had the strongest binding affinity towards the MtInhA enzyme. The result of this work helps to understand the key interactions between 1,3,4 trisubstituted pyrazole derivatives and MtInhA protein that may be necessary to develop new lead compounds against tuberculosis.

Artemisia campestris L. as a promising source of potential antiviral drugs for SARS-CoV-2: Docking and dynamic simulation studies

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been considered as global public health security threats. Due to its rapid spread, high mortality rate and unavailability of treatment, we need to find a potent drug against SARS-CoV-2. Natural products are useful agents for the discovery of new potential drugs to combat coronavirus. Artemisia campestris, an aromatic plant widely used in traditional medicine, particularly in southern region of Algeria, is recognized for its essential oils and phenolics compounds possessing a wide range of biological activities. This study selected sixty-nine compounds from this plant to determine their binding interactions with the SARS-CoV-2 main protease (Mpro) and receptor-binding domain of the spike (S-RBD) protein, by using computational methods. Rutin, isoquercetin, and quercetin-3-O-glucuronide were shown to be the most potent inhibitors for Mpro and S-RBD with docking scores and Ki values ranging from -16.06 to -10.67 Kcal/mol and 0.005 to 30.01 nM, respectively. Evaluation of ADMET pharmacokinetic properties and the drug likeness in silico revealed that only 3,5-dicaffeoylquinic acid, 3–4–5-tricaffeoylquinic acid, isorhamnetin-3-O-glucoside, and rubescensin A could be more effective drugs against COVID-19. Molecular dynamics (MD) simulations (100 ns) and MM-GBSA calculations confirmed the stability of ligand-protein complexes via hydrogen bonding interactions with crucial residues. The analysis of structural parameters (RMSD, RMSF, H-bonds, Rg, and SASA) indicates that 3,4,5-tricaffeoylquinic acid and rubescensin A compounds have good stability and significant binding affinity with the Mpro and S-RBD protein. Taken together, our findings confirm that Artemisia campestris as a plausible source of anti-SARS-COV-2 phytochemicals and suggest that may play important role in this activity.

Design of some phthalazine molecules as novel VEGFR-2 target inhibitors through 3D-QSAR modeling, molecular docking and dynamic simulation and pharmacokinetics profiling

AbstractBreast cancer is one of the dominant cause of cancer-related mortality in females, with an incidence of approximately 1.3 million cases annually, necessitating the development of effective therapeutic strategies. In this study, 3D-QSAR models were reported based on Phthalazine derivatives as VEGFR-2 inhibitors. The activities of these derivatives were correlated with the steric (S), electrostatic (E), hydrogen bond acceptor (A), and donor (D), and hydrophobic (H) fields, which served as critical parameters in model development. Statistical studies of these models showed that the best models are; CoMFA_S (Q2 = 0.623, R2 = 0.941), and CoMSIA_E + D (Q2 = 0.615, R2 = 0.977). Based on the insights from the model fields and docking simulation of the template (compound 17), twelve molecules were designed. These novel molecules exhibited stronger potency compared to the template and the standard, Sorafenib. Compound 17A emerged as the most potent, with pIC50 = 5.98, for CoMFA_S and 5.85, for CoMSIA_E + D, and a strong docking affinity of − 97.271 kcal/mol, therefore subjected to a 100-ns MD simulation. Results indicate better interaction and stabilizing potential over Sorafenib, due to the lower RMSD, RMSF, Rg, values and favorable hydrogen bond analyses. These conclusions were validated by Gibbs free energy analysis and MM-GBSA calculations, revealing a more favorable interaction free energy of − 18.48 kcal/mol related to Sorafenib. Furthermore, these designed compounds demonstrated promising pharmacokinetic profiles.

Computational insights into human UCP1 activators through molecular docking, MM-GBSA, and molecular dynamics simulation studies

The prevalence of obesity is rapidly increasing worldwide. Brown adipose tissue activates uncoupling protein 1 (UCP1) to generate heat through bypassing ATP synthesis, offering a potential target for obesity treatment. Targeting UCP1 activation to induce thermogenesis through small molecules presents a promising approach for obesity management. In this study, molecular docking of UCP1 activators, using 2,4-dinitrophenol (DNP) as a reference ligand (PDB ID: 8J1N, docking score: −5.343 kcal/mol), identified seven top-scoring compounds: naringin (-7.284 kcal/mol), quercetin (-6.661 kcal/mol), salsalate (-6.017 kcal/mol), rhein (-5.798 kcal/mol), mirabegron (-5.535 kcal/mol), curcumin (-5.479 kcal/mol), and formoterol (-5.451 kcal/mol). Prime MM-GBSA calculation of the top-scored molecule (i.e., naringin) in the docking study showed ΔGBind of −70.48 kcal/mol. Key interactions of these top 7 activators with UCP1 binding pocket residues Trp280, Arg276, Glu190, Arg83, and Arg91 were observed. Molecular dynamics simulations performed for 100 ns confirmed complex stability, with RMSD values below 6 Å. Additionally, most activators showed favorable intestinal absorption (>90 %) and lipophilicity (LogP 2–4), with pKa values supporting their pharmacological potential as UCP1-targeting therapeutics for obesity. These findings provide a foundation for designing potent UCP1 activators by integrating docking scores, interaction profiles, statistical profiles from MD simulations, and physicochemical assessments to develop effective anti-obesity therapies.

Family Malvaceae: a potential source of secondary metabolites with chemopreventive and anticancer activities supported with in silico pharmacokinetic and pharmacodynamic profiles.

Cancer is the second most widespread cause of mortality following cardiovascular disorders, and it imposes a heavy global burden. Nowadays, herbal nutraceutical products with a plethora of bioactive metabolites represent a foundation stone for the development of promising chemopreventive and anticancer agents. Certain members of the family Malvaceae have traditionally been employed to relieve tumors. The literature concerning the chemopreventive and anticancer effects of the plant species along with the isolated cytotoxic phytometabolites was reviewed. Based on the findings, comprehensive computational modelling studies were performed to explore the pharmacokinetic and pharmacodynamic profiles of the reported cytotoxic metabolites to present basis for future plant-based anticancer drug discovery. All the available information about the anticancer research in family Malvaceae and its cytotoxic phytometabolites were retrieved from official sources. Extensive search was carried out using the keywords Malvaceae, cancer, cytotoxicity, mechanism and signalling pathway. Pharmacokinetic study was performed on the cytotoxic metabolites using SWISS ADME model. Acute oral toxicity expressed as median lethal dose (LD50) was predicted using Pro Tox 3.0 web tool. The compounds were docked using AutoDock Vina platform against epidermal growth factor receptor (EGFR kinase enzyme) obtained from the Protein Data Bank. Molecular dynamic simulations and MMGBSA calculations were performed using GROMACS 2024.2 and gmx_MMPBSA tool v1.5.2. One hundred forty-five articles were eligible in the study. Several tested compounds showed safe pharmacokinetic properties. Also, the molecular docking study showed that the bioactive metabolites possessed agreeable binding affinities to EGFR kinase enzyme. Tiliroside (25), boehmenan (30), boehmenan H (31), and isoquercetin (22) elicited the highest binding affinity toward the enzyme with a score of -10.4, -10.4, -10.2 and -10.1Kcal/mol compared to the reference drug erlotinib having a binding score equal to -9Kcal/mol. Additionally, compounds 25 and 31 elicited binding free energies equal to -42.17 and -42.68Kcal/mol, respectively, comparable to erlotinib. Overall, the current study presents helpful insights into the pharmacokinetic and pharmacodynamic properties of the reported cytotoxic metabolites belonging to family Malvaceae members. The molecular docking and dynamic simulations results intensify the roles of secondary metabolites from medicinal plants in fighting cancer.

Alpha-Glucosidase Inhibitory Effects of Flavonoids, Phenolic Acids and Iridoids Isolated From Vinca Soneri: In Vitro and In Silico Perspectives.

Various Vinca species have been traditionally used for their antihypertensive, sedative, and hemostatic properties, as well as for treating diabetes. In this study, some flavonoids, phenolic acids and iridoids were isolated from an endemic Vinca species, Vinca soneri for the first time. α-Glucosidase inhibitory effects of the isolates were tested and kaempferol-3-O-α-rhamnopyranosyl (1→6) β-galactopyranoside (1) was found to be the most active one with an IC50 value of 285.73 ±7.35 μM. Enzyme kinetic assay revealed that it inhibited α-glucosidase in competitive manner. Molecular geometry of 1 was predicted and Frontier molecular orbital analysis was performed using Density Functional Theory (DFT) calculations. Molecular docking and MM-GBSA calculations predicted good fit for 1 in the enzyme active site and key interactions with the catalytic residues. As a result, current study identifies 1 as a promising competitive α-glucosidase inhibitor to be developed as a potential antidiabetic drug candidate.

Discovery of novel natural compounds for inhibiting JNK signaling in cancer: Multi-step virtual screening, MM-GBSA calculations, and molecular dynamics simulations

Discovery of novel natural compounds for inhibiting JNK signaling in cancer: Multi-step virtual screening, MM-GBSA calculations, and molecular dynamics simulations

An Integrative Computational Approach for Design and Evaluation of Novel [1,2,4]triazolo[3,4-b][1,3,4]thiadiazole Analogues as Dual-Action Anti-Retroviral and Anti-Bacterial Agents: Insights into Rational Drug Design Strategies

The development of effective antiretroviral inhibitors (HIV-1 Reverse Transcriptase) and glucosamine-6-phosphate (GlcN6P) agents represent a significant challenge for combating viral infections and related diseases. In this study, we employed a multidisciplinary approach to design and evaluate a series of novel triazole analogs as potential candidates for anti-retroviral and glucosamine-6-phosphate agents. Using molecular docking, we explored the binding interactions between the RSA3 analog and the target proteins implicated in viral replication and glucosamine metabolism. Density functional theory (DFT) employing the 6-311++G(d,p) basis set was utilized for computational analysis, with a subsequent examination of the electronic parameters. The HOMO and LUMO orbitals as well as the molecular electrostatic potential map were investigated using DFT to characterize the reactivity of our molecule. Molecular dynamics simulations were performed to investigate the stability and dynamic behavior of the ligand-protein complex (RSA3) over time (300 ns). Furthermore, we employed MM-GBSA calculations of the compound RSA3 (molecular mechanics generalized band surface area) to estimate the binding free energies (−71.30 ± 7.26 kcal/mol and −67.86 ± 7.09 kcal/mol, respectively) and identified the most promising compounds with high affinity for the target proteins. Additionally, predictive absorption, distribution, metabolism, excretion and toxicity (ADMET) studies of compound RSA3 were conducted to assess its drug-like properties and potential safety profiles of the selected compound. Our results revealed that RSA3 has favorable binding interactions, is a stable complex and has significant binding affinity for target proteins. Moreover, predictive ADMET studies indicated that RSA3 possesses desirable drug-like properties, suggesting its potential for further investigation as an anti-retroviral agent and glucosamine-6-phosphate agent. Overall, this integrative computational approach combining molecular docking, DFT analysis, dynamics simulations, MM-GBSA and predictive ADMET studies provides valuable insights into the design and evaluation of novel triazole analogs with potential therapeutic applications, highlighting the importance of rational drug design strategies in the field of antiretroviral and glucosamine research.

Identification of Peregrin inhibitors-modulators by harnessing the computational prowess of molecular simulation and machine learning algorithms

Peregrin is marked as a potential drug target due to its pivotal role in the epigenetic maintenance of cellular metabolism. It is counted among those of the bromodomain-containing protein family. The protein binds to the acetylated lysine of N-terminus histone proteins of the nucleosomes. This bound form neutralizes the otherwise positively charged histone and, thus, crucially impacts the DNA replication mechanism. In several diseases like cancer, bone loss, and leukemia, this peregrin binding impacts the genes’ overexpression. Hence, the present study, computational screening of the bromodomain-specific inhibitors from a library of 5430 compounds retrieved from the ChemDiv database. Two different scoring functions based molecular docking studies have been employed for molecular interaction analysis. Followed by an artificial intelligence-based absolute binding affinity prediction has been confirmed through KDeep, which follows a machine learning step to obtain a precise binding energy score for the set of best compounds in the screening process. The resultant compounds were then screened for pharmacokinetics and drug-likeliness properties. Using molecular dynamics (MD) simulation analysis, the dynamic behavior of the four suggested compounds and Peregrin has been investigated for a 100 ns period. Identified compounds are found to be sufficiently effective in holding their strong interaction affinity toward Peregrin for an adequate time span, and structural integrity is also found to be comparable with the standard compound considered in the study. Mostly, all four potent compounds (K788-9421, S357-0084, S357-0893, S357-0915) are hydrophobic and evaluated for thermodynamics property analysis using MM-GBSA and free energy landscape (FEL) calculations. However, among all, K788-9421 shows comparatively better and energetically most favorable interactions with peregrin. Overall, study findings can lead to further research in developing next-generation broad-spectrum Peregrin inhibitors-modulators; they need extensive experimental validation for considering the compounds for clinical-trial application for being an excellent drug-candidate entity against Peregrin protein.

Computer-aided design, synthesis, and biological evaluation of 4-chloro-N-(2-oxo-3-(2-pyridin-4-yl)hydrazineylidene)indolin-5yl)benzamide and 1-(4-bromobenzyl)-5-indoline-2,3-dione against SARS-CoV-2 spike/ACE2

The emergence of the severe acute respiratory syndrome 2 (SARS-CoV-2) as a global threat has driven the urgent need for the identification of bioactive molecules capable of controlling or completely eradicating this virus. Our group has been investigating isatin hybrids that block the binding of the human angiotensin-converting enzyme 2 (ACE2) and the viral spike protein. This work describes the synthesis and biological evaluation of two derivatives of isatin (indol-2,3-dione) based on a computational approach. Isatin, a secondary metabolite of tryptophan, has been used as the core structure and is a versatile and favorable precursor and as a privileged scaffold against this enzyme complex. The new compound scaffolds AVS-01 and AVS-02 were designed by modifications at the C-3 and N-1 positions, respectively, according to the various reagents available in our lab. Molecular docking of the designed compounds was used to explore their interactions with the target protein complex. The two designed compound scaffolds shown in this article showed quite distinct docking glide scores (GScore = −3.657 and −4.534 for AVS-01 and AVS-02, respectively). Several analogs were synthesized and tested in the quest to find a plausible scaffold for further synthesis. While compound AVS-02 showed inhibition of spike/ACE2 binding with an IC50 value of 8.8 µM, the reference compound hopeaphenol inhibited the interaction with an IC50 of 0.3 µM. Compound AVS-01 rather showed no inhibition of the SARS-CoV-2 spike/host ACE2 interaction with an IC50 > 32 µM. An estimation of their binding free energy (ΔGbind), and free energy of solvation (ΔGsolv) MM-GBSA calculations was carried out to re-evaluate the affinity to the target protein to gain further insights into the observed activity and non-activity. MM-GBSA calculation showed that ΔGbind = −35.91 kcal/mol and-25.32 kcal/mol for AVS-01 and AVS-02, respectively, and ΔGsolv = 25.56 kcal/mol and 16.92 kcal/mol for AVS-01 and AVS-02, respectively. This leads to the conclusion that the N-1 position of the indole-2,3-dione moiety favors the blockage of SARS-CoV-2 spike/ACE2 interactions compared to the C-3 position. Analysis of GScores, per-residue interaction energies, and free energies of binding and solvation showed that van der Waals interactions should favor the binding towards the spike/ACE2 complex.

Targeting Monkeypox Virus Methyltransferase: Virtual Screening of Natural Compounds from Middle-Eastern Medicinal Plants.

Monkeypox is an infectious disease resulting from the monkeypox virus, and its fatality rate varies depending on the virus clade and the location of the outbreak. In monkeypox virus, methyltransferase (MTase) plays a crucial role in modifying the cap structure of viral mRNA. This alteration assists the virus in evading the host's immune system, enhances viral protein synthesis, and ultimately enables successful infection and replication within host cells. Given the significance of MTase in viral infection and spread within the host, our study aimed to identify a natural inhibitor for this enzyme using docking and molecular dynamic (MD) simulations. We collected a total of 12,971 natural compounds from 200 medicinal plants in the Middle East. After eliminating duplicate compounds, we had 5,749 unique ligand conformers, which we then subjected to high-throughput virtual screening against MTase. The most promising hits were further evaluated using the extra-precision (XP) tool. The affinity of these hits was also assessed by Prime-Molecular Mechanics/Generalized Born Surface Area (MMGBSA) tool. The analysis revealed that two standard controls (sinefungin and TO1119) and two Middle-Eastern compounds (folic acid and 1,2,4,6-tetragalloylglucose) exhibited the best XP docking scores. According to Prime MMGBSA calculations, the Middle-Eastern compounds showed higher affinities, with values of -60.61 kcal/mol for 1,2,4,6-tetragalloylglucose and -51.87 kcal/mol for folic acid, surpassing the controls (TO1119 at -35.71 kcal/mol and sinefungin at -31.51 kcal/mol). In the majority of Molecular dynamic (MD) simulations, folic acid exhibited demonstrated greater stability than sinefungin. Further investigation revealed that folic acid occupied a critical position in the active site of MTase, which reduced its interaction with the mRNA substrate. Based on these findings, it can be concluded that folic acid is a highly promising natural compound for potential use in the cost-effective treatment of monkeypox virus. The identification of folic acid as a potential antiviral agent highlights the importance of nature in providing new therapeutic uses that have significant implications for global health, particularly in regions where monkeypox viral outbreaks are prevalent. However, it is essential to note that further wet-lab validations are necessary to confirm its efficacy for treatment in a medical context.

Rational design of glycosaminoglycan binding cyclic peptides using cPEPmatch

Cyclic peptides present a robust platform for drug design, offering high specificity and stability due to their conformationally constrained structures. In this study, we introduce an updated version of the Cyclic Peptide Matching program (cPEPmatch) tailored for the identification of cyclic peptides capable of mimicking protein-glycosaminoglycan (GAG) binding sites. We focused on engineering cyclic peptides to replicate the GAG-binding affinity of antithrombin III (ATIII), a protein that plays a crucial role in modulating anticoagulation through interaction with the GAG heparin. By integrating computational and experimental methods, we successfully identified a cyclic peptide binder with promising potential for future optimization. MD simulations and MM-GBSA calculations were used to assess binding efficacy, supplemented by umbrella sampling to approximate free energy landscapes. The binding specificity was further validated through NMR and ITC experiments. Our findings demonstrate that the computationally designed cyclic peptides effectively target GAGs, suggesting their potential as novel therapeutic agents. This study advances our understanding of peptide-GAG interactions and lays the groundwork for future development of cyclic peptide-based therapeutics.

Investigating the Potential of 2-Ethylbutyl-(Phenoxy)phosphoryl-D-Alaninate Against RNA-Dependent RNA Polymerase (RdRp) of SARS-CoV-2.

There was an emergency call globally when COVID-19 was detected in December 2019. The SARS-CoV-2 virus, a modified virus, causes this contagious disease. Although research is being conducted throughout the world, the main target is still to find the promising candidate to target RNA-dependent RNA polymerase (RdRp) to provide possible drug against COVID-19. Aim of this work is to find a molecule to inhibit the translational process of viral protein synthesis. Density Functional Theory calculations revealed information about the formation of the desired ligand (RD). Molecular docking of RD with RdRp was performed and compared with some reported molecules and the data revealed that RD had the best docking score with RdRp (-6.7 kcal/mol). Further, molecular dynamics (MD) simulations of RD with RdRp of SARS-CoV-2 revealed the formation of stable complex with a maximum number of seven hydrogen bonds. Root mean square deviations values are in acceptable range and root mean square fluctuations are also low, indicating stable complex formation. Further, based on MM-GBSA calculation, RD formed a stable complex with RdRp of nCoV with ΔG° of -12.28 kcal mol-1.

Exploring Plant-Derived Bioactive Compounds in Olea Europaea L. Leaves as Potent Inhibitors of PTP-1B Using an In silico Approach

In this study, we focus on exploring the medicinal potential of Olea Europaea L., a commonly used plant with diverse indigenous medicinal applications. The main aim is to identify promising phytoconstituents from Olea Europaea L. leaves that can act as inhibitors for the PTP-1B target, utilizing an in silico approach. The phytoconstituents were sourced from the IMMPAT database, and molecular docking was employed to assess their binding affinities. The docking results revealed that rutin (−10.05 kcal/mol) and quercetin (−8.28 kcal/mol) displayed the highest binding scores against PTP-1B, outperforming reference compounds. Furthermore, MM-GBSA calculations indicated favorable free binding energy. To ensure stability, 200 ns Molecular Dynamics simulations were conducted on the 2QBS-Rutin complex. The results revealed that the 2QBS-Rutin complex showed stable conformation throughout the simulation, maintaining consistency with RMSD values below 1 Å. This study highlights rutin and quercetin as promising phytoconstituents from Olea Europaea L. leaves, demonstrating potent-binding affinities against PTP-1B inhibitors.

A computational workflow to determine drug candidates alternative to aminoglycosides targeting the decoding center of E. coli ribosome

The global antibiotic resistance problem necessitates fast and effective approaches to finding novel inhibitors to treat bacterial infections. In this study, we propose a computational workflow to identify plausible high-affinity compounds from FDA-approved, investigational, and experimental libraries for the decoding center on the small subunit 30S of the E. coli ribosome. The workflow basically consists of two molecular docking calculations on the intact 30S, followed by molecular dynamics (MD) simulations coupled with MM-GBSA calculations on a truncated ribosome structure. The parameters used in the molecular docking suits, Glide and AutoDock Vina, as well as in the MD simulations with Desmond were carefully adjusted to obtain expected interactions for the ligand-rRNA complexes. A filtering procedure was followed, considering a fingerprint based on aminoglycoside's binding site on the 30S to obtain seven hit compounds either with different clinical usages or aminoglycoside derivatives under investigation, suggested for in vitro studies. The detailed workflow developed in this study promises an effective and fast approach for the estimation of binding free energies of large protein-RNA and ligand complexes.

Pyrazine and Furan Derivative Activity Prediction on Type 2 Diabetic Mellitus: In silico Study

Diabetes Mellitus (DM) is a chronic disease that occurs when the pancreas does not produce enough insulin, or the body cannot use insulin effectively. Type 2 DM treatment can be done using antidiabetic drugs, but the continuous use of synthetic drugs will cause side effects. Empirically, the people of Nias Indonesia use palm juice (Arenga pinnata Merr.) as an antidiabetic, which can reduce blood glucose levels. This study aimed to find the active compounds in palm juice that can potentially be an antidiabetic type 2 using an in silico approach. The methods used were toxicity screening, profile pharmacokinetics, drug scanning, docking, and molecular dynamics simulation. Screening, molecular docking, and molecular dynamics of 30 compounds generated from pyrazine and furan revealed that two compounds, PF 16 and PF 30, can bind to receptors and produce lower ∆G values than metformin HCl. Molecular dynamics simulation results using the MM-GBSA calculation method showed that the PF 16 compound was more selective than the 2PDY (aldose reductase) with a value of -39.23 kcal/mol, while compound PF 30 was more selective to 1Z89 (aldose reductase) with a value of -7.36 kcal/mol. It can be concluded that the level of affinity of the PF 30 compound to the 1Z89 receptor and the PF 16 compound to the 2PDY were predicted to have the potential as antidiabetic (DM type 2).

An insight for the inhibition of anxiolytic and anti-convulsant effects in zebrafish using the curcumins via exploring molecular docking and molecular dynamics simulations.

In the contemporary landscape, anxiety and seizures stand as major areas of concern, prompting researchers to explore potential drugs against them. While numerous drugs have shown the potential to treat these two neurological conditions, certain adverse effects emphasize the need for development of safer alternatives. This study seeks to employ an in silico approach to evaluate natural compounds, particularly curcumins, as potential inhibitors of GABA-AT to mitigate anxiety and seizures. The proposed methodology includes generating a compound library, minimizing energy, conducting molecular docking using AutoDock, molecular dynamics simulations using Amber, and MM-GBSA calculations. Remarkably, CMPD50 and CMPD88 exhibited promising binding affinities of - 9.0kcal/mol and - 9.1kcal/mol with chains A and C of GABA-AT, respectively. Further, MM-GBSA calculations revealed binding free energies of - 10.88kcal/mol and - 10.72kcal/mol in CMPD50 and CMPD88, respectively. ADME analysis showed that these compounds contain drug-likeness properties and might be considered as potential drug candidates. The findings from this study will have practical applications in the field of drug discovery for the development of safer and effective drugs for treatment of anxiety and seizures. Overall, this study will lay the groundwork for providing valuable insights into the potential therapeutic effects of curcumins in alleviating anxiety and seizures, establishing a computational framework for future experimental validation.

Identification of Genes Hub Associated with Triple-Negative Breast Cancer and Cannabidiol Analogs Potential Inhibitory Agents: An In-silico Study.

Triple-negative breast cancer presents a significant challenge in oncology due to its complex treatment and aggressive nature. This subtype lacks common cancer cell receptors like estrogen, progesterone, and human epidermal growth factor receptor 2 receptors. This study aimed to identify, through bioinformatic analysis, the key genes associated with triple-negative breast cancer. In addition, CBD analogs with potential inhibitory effects on these genes were evaluated through docking and molecular dynamics. Gene expression profiles from the GSE178748 dataset were analyzed, focusing on MDA-MB-231 breast cancer cell lines. Differentially expressed genes were determined through protein-protein interaction networks and subsequently validated. Additionally, the inhibitory effects of cannabidiol analogs on these hub genes were assessed using molecular docking and dynamics. Analysis of the hub highlighted RPL7A, NHP2L1, and PSMD11 as significant players in TNBC regulation. Ligand 44409296 showed the best affinity energy with RPL7A, while 166505341 exhibited the highest affinity with NHP2L1 and PSMD11, surpassing CBD. Analyses of RMSD, RMSF, SASA, and Gyration Radius indicated structural stability and interactions of the proteins with ligands over time. MMGBSA calculations showed favorable binding energies for the ligands with the target proteins. In conclusion, this study identified key genes, namely RPL7A, NHP2L1, and PSMD11, associated with triple-negative breast cancer and demonstrated promising interactions with cannabidiol analogs, particularly 44409296 and 166505341. These findings suggest potential therapeutic targets and highlight the relevance of further clinical investigations. Additionally, the ligands exhibited favorable ADME properties and low toxicity, underscoring their potential in future drug development for TNBC treatment.