RMSF Analysis Research Articles

In Silico Structural Insights into a Glucanase from Clostridium perfringens and Prediction of Structural Stability Improvement Through Hydrophobic Interaction Network and Aromatic Interaction.

Glucanases are widely applied in industrial applications such as brewing, biomass conversion, food, and animal feed. Glucanases catalyze the hydrolysis of glucan to produce the sugar hemiacetal through hydrolytic cleavage of glycosidic bonds. Current study aimed to investigate structural insights of a glucanase from Clostridium perfringens through blind molecular docking, site-specific molecular docking, molecular dynamics (MD) simulation, and binding energy calculation. Furthermore, we aimed to enhance structural stabilization through formation of hydrophobic interaction network. The molecular docking results illustrated that residues Glu222 and Asp187 may act as nucleophile acid/base catalyst. Moreover, the MM/PBSA results illustrated a high binding affinity of 108.71 ± 8.5kJ/mol between glucanase and barely glucan during 100 ns simulation. The RMSF analysis illustrated a high flexible surface loop with the highest mobility at position D130. Therefore, the structural engineering was carried out through introducing a double-mutant S125Y/D130P, and the structural stability was improved by forming the hydrophobic interaction network and one π-π aromatic interaction. The spatial distance between the mutation sites and the catalytic pocket attenuates their direct impact on binding interactions within the catalytic pocket.

Benzothiazole-triazole hybrids: Novel anticancer agents inducing cell cycle arrest and apoptosis through Bcl-2 inhibition in triple-negative breast cancer.

In this study, we aim to detail the design and synthesis of a series of benzothiazole tethered triazole compounds that incorporate acetamide chains, with the purpose of investigating their potential as anticancer agents. The structural integrity of the compounds was confirmed through characterization using 1H NMR, 13C NMR, mass spectrometry, and IR spectroscopy. The compounds demonstrated notable cytotoxic effects when tested against a range of cancer cell lines, with a specific inhibition observed in triple-negative breast cancer. Among the compounds, the one with trichloro substitution demonstrated the highest potency, as indicated by an IC50 value of 30.49μM. The compounds were found to trigger cell cycle arrest in the G2/M phase and promote apoptosis, as observed in the mechanistic studies. The Bcl-2 protein exhibited significant binding interactions in molecular docking studies, which were then corroborated through molecular dynamics simulations spanning 100ns. The simulations confirmed the stability of the ligand-protein complex, as supported by RMSD, RMSF, and hydrogen bond analyses, reinforcing the proposed mechanism of Bcl-2-mediated apoptosis.

Targeting necroptosis in MCF-7 breast cancer cells: In Silico insights into 8,12-dimethoxysanguinarine from Eomecon Chionantha through molecular docking, dynamics, DFT, and MEP studies.

Breast cancer remains a significant challenge in oncology, highlighting the need for alternative therapeutic strategies that target necroptosis to overcome resistance to conventional therapies. Recent investigations into natural compounds have identified 8,12-dimethoxysanguinarine (SG-A) from Eomecon chionantha as a potential necroptosis inducer. This study presents the first computational exploration of SG-A interactions with key necroptotic proteins-RIPK1, RIPK3, and MLKL-through molecular docking, molecular dynamics (MD), density functional theory (DFT), and molecular electrostatic potential (MEP) analyses. Molecular docking revealed that SG-A exhibited a stronger affinity for MLKL (-9.40 kcal/mol) compared to the co-crystallized ligand (-6.29 kcal/mol), while its affinity for RIPK1 (-6.37 kcal/mol) and RIPK3 (-7.01 kcal/mol) was lower. MD simulations further demonstrated the stability of SG-A within the MLKL site, with RMSD values stabilizing between 1.4 and 3.3 Å over 300 ns, indicating a consistent interaction pattern. RMSF analysis indicated the preservation of protein backbone flexibility, with average fluctuations under 1.7 Å. The radius of gyration (Rg) results indicated a consistent value of ~15.3 Å across systems, confirming the role of SG-A in maintaining protein integrity. Notably, SG-A maintains two critical H-bonds within the active site of MLKL, reinforcing the stability of the interaction. Principal component analysis (PCA) indicated a significant reduction in MLKL's conformational space upon SG-A binding, implying enhanced stabilization. Dynamic cross-correlation map (DCCM) analysis further revealed that SG-A induced highly correlated motions, reducing internal fluctuations within MLKL compared to the co-crystallized ligand. MM-PBSA revealed the enhanced binding efficacy of SG-A, with a significant binding free energy of -31.03 ± 0.16 kcal/mol against MLKL, surpassing that of the control (23.96 ± 0.11 kcal/mol). In addition, the individual residue contribution analysis highlighted key interactions, with ARG149 showing a significant contribution (-176.24 kcal/mol) in the MLKL-SG-A complex. DFT and MEP studies corroborated these findings, revealing that the electronic structure of SG-A is conducive to stable binding interactions, characterized by a narrow band gap (~0.16 units) and distinct electrostatic potential favourable for necroptosis induction. In conclusion, SG-A has emerged as a compelling inducer of necroptosis for breast cancer therapy, warranting further experimental validation to fully realize its therapeutic potential.

Comprehensive In Silico Analysis of Flavonoids in Breast Cancer Using Molecular Docking, ADME, and Molecular Dynamics Simulation Approach

ABSTRACTThe most frequent type of breast cancer in women is infiltrating ductal carcinoma, followed by infiltrating lobular carcinoma and triple‐negative breast cancer, which account for 10%–15% of cases. Since this disease is not aggressive in its early stages and thus does not flee with the breast duct with this perspective, Epidermal Growth Factor Receptor (EGFR) was chosen with its relevance in stage 0 breast cancer as a primary target. The study aimed to evaluate the protective effects of 19 flavonoids against breast cancer. In addition, pharmacokinetics investigations, molecular docking, free energy calculations, and molecular dynamics simulations were used to evaluate the molecular interactions, stability, and draggability between the phytoconstituents and the EGFR. The acquired results showed that myricetin, which has been compared to raloxifene, is the top docked score compound from the list of flavonoids; the docking score is −9.26 kcal/mol, and standard raloxifene showed −5.39 kcal/mol against epidermal growth factor receptor. The ADME profile shows the drug‐like properties. MD simulations revealed that the myricetin complex is more stable than the raloxifene complex, and pharmacophore modeling studies validated the hydrogen bonding interactions. The PASS online program predicted the biological spectrum of flavonoids against the breast cancer‐causing enzyme. Key parameters like RMSD, RMSF, RoG, hydrogen bonds, PCA, DCCM, and FEL analysis indicated better stability for myricetin. These results suggest that myricetin is a promising drug candidate against breast cancer.

Anticancer Activity, DFT, Molecular Docking, ADMET, and Molecular Dynamics Simulations Investigations of Schiff Base Derived From 2,3‐Diaminophenazine and Its Metal Complexes

ABSTRACTIn our previous study, Schiff base (1) complexes derived from 2,3‐diaminophenazine and metal ions Co(II) (2), Ni(II) (3), Cu(II) (4), and Cd(II) (5) were synthesized and characterized, demonstrating a significant biological activity. This study investigates their anticancer potential, specifically against prostate cancer. The complexes exhibited notable reductions in cancer cell viability, with IC50 values of 0.531 μM Ni(II), 0.630 μM Cu(II), and 0.655 μM Co(II), comparable with the standard drug enzalutamide. The Co(II) complex showed the highest efficacy, while Cd(II) displayed the lowest (IC50 = 0.648 μM). The presence of a phenazine ring in these complexes enhances DNA binding, contributing to their anticancer effects. HOMO‐LUMO calculations revealed energy gaps ranging from 2.525 to 3.294 eV, indicating varying reactivity and potential for biological interactions. Molecular docking studies revealed that compound (1) exhibited the highest binding affinity (−9.19 kcal/mol) for the prostate cancer‐related receptor, with significant hydrogen bond interactions. Molecular dynamics simulations over 100 ns demonstrated stable binding, with RMSD values below 1.5 Å, and RMSF analysis provided insights into protein flexibility. ADMET studies revealed favorable drug‐like properties, including good gastrointestinal absorption (> 30%), high blood–brain barrier permeability (LogBBB = 0.64), and high human intestinal absorption (68.47%–88.79%). No inhibition of CYP2D6 was observed, suggesting low risk for drug–drug interactions. These Schiff base‐metal complexes show promising anticancer activity and favorable ADMET profiles, indicating their potential as therapeutic agents for prostate cancer treatment.

Integrative Machine Learning, Virtual Screening, and Molecular Modeling for BacA-Targeted Anti-Biofilm Drug Discovery Against Staphylococcal Infections

The rise in antibiotic-resistant Staphylococcal infections necessitates innovative approaches to identify new therapeutic agents. This study investigates the application of machine learning models to identify potential phytochemical inhibitors against BacA, a target related to Staphylococcal infections. Active compounds were retrieved from BindingDB while the decoy was generated from DUDE. The RDKit was utilized for feature engineering. Machine learning models such as k-nearest neighbors (KNN), the support vector machine (SVM), random forest (RF), and naive Bayes (NB) were trained on an initial dataset consisting of 226 active chemicals and 2550 inert compounds. Accompanied by an MCC of 0.93 and an accuracy of 96%, the RF performed better. Utilizing the RF model, a library of 9000 phytochemicals was screened, identifying 300 potentially active compounds, of which 192 exhibited drug-like properties and were further analyzed through molecular docking studies. Molecular docking results identified Ergotamine, Withanolide E, and DOPPA as top inhibitors of the BacA protein, accompanied by interaction affinities of −8.8, −8.1, and −7.9 kcal/mol, respectively. Molecular dynamics (MD) was applied for 100 ns to these top hits to evaluate their stability and dynamic behavior. RMSD, RMSF, SASA, and Rg analyses showed that all complexes remained stable throughout the simulation period. Binding energy calculations using MMGBSA analysis revealed that the BacA_Withanolide E complex exhibited the most favorable binding energy profile with significant van der Waals interactions and a substantial reduction in gas-phase energy. It also revealed that van der Waals interactions contributed significantly to the binding stability of Withanolide E, while electrostatic interactions played a secondary role. The integration of machine learning models with molecular docking and MD simulations proved effective in identifying promising phytochemical inhibitors, with Withanolide E emerging as a potent candidate. These findings provide a pathway for developing new antibacterial agents against Staphylococcal infections, pending further experimental validation and optimization.

In Silico and Network Pharmacology Approach for Mechanistic Exploration of Rhododendron arboreum Sm. Leaf in Nonalcoholic Fatty Liver Disease

Rhododendron arboreum Sm. (Burans) (family Ericaceae) has traditionally been used in Indian medicine to treat liver disorders. However, its mechanism against non-alcoholic fatty liver disease (NAFLD) remains elusive. This study utilized in silico methods – network pharmacology, ADMET prediction, molecular docking and molecular dynamics (MD) simulations for mechanistic exploration of Rhododendron arboreum leaves (RAL) in NAFLD. Bioactive compounds were sourced from open databases and assessed for drug-likeness and ADMET profiles. Network pharmacology identified key protein interactions using the STRING platform. GO analysis identified galactose metabolism, pentose and glucuronate interconversions and other processes in treating NAFLD. Molecular docking revealed that amyrin and pectolinarigenin had the highest binding affinities, with dock scores of –12.2 kcal/mol (AKR1C3-amyrin), –10.2 kcal/mol (PI3K-amyrin), –9.3 kcal/mol (AKR1C3-pectolinarigenin) and –9.6 kcal/mol (HSD17B1-pectolinarigenin). MD simulations, focusing on RMSD and RMSF analyses, confirmed the stability of these interactions. The RMSD graphs revealed stable binding pocket regions, highlighted in pink. Notably, the RMSF values for PHE (B:306) in the AKR1C3-amyrin complex and ARG (A:294) in the PI3K-amyrin interaction were 0.623 nm and 0.1586 nm, respectively, indicating stable ligand interactions. Our findings holistically clarify toxicity data, potential bioactives targets and molecular mechanisms of RAL against NAFLD, paving the way for future research.

Analysis of damaging non-synonymous SNPs in GPx1 gene associated with the progression of diverse cancers through a comprehensive in silico approach

Glutathione Peroxidase 1 (GPx1) gene has been reported for its role in cellular redox homeostasis, and the dysregulation of its expression is linked with the progression of diverse cancers. Non-synonymous single nucleotide polymorphism (nsSNPs) have been emerged as the crucial factors, playing their role in GPx1 overexpression. To understand the deleterious mutational effects on the structure and function of GPx1 enzyme, we delved deeper into the exploration of possibly damaging nsSNPs using in-silico based approaches. Eight widely utilized computational tools were employed to roughly shortlist the deleterious nsSNPs. Their damaging effects on structure and function of the genes were evaluated by using different bioinformatics tools. Subsequently, the three final proposed deleterious mutants including mutations rs373838463, rs2107818892, and rs763687242, were docked with their reported binder, TNF receptor-associated factor 2 (TRAF2). The lowest binding affinity and stability of the docked mutant complexes as compared to the wild type GPx1 were validated by molecular dynamic simulation. Finally, the comparison of RMSD, RMSF, RoG and hydrogen bond analyses between wild-type and mutant’s complexes validated the deleterious effects of proposed nsSNPs. This study successfully identified and verified the possibly damaging nsSNPs in GPx1 enzyme, which may be linked the progression of various types of cancer. Our findings underscore the value of in-silico approaches in mutational analysis and encourage further preclinical and clinical trials.

Docking and Simulation Studies on Novel Analogues of 3,4,5-Trihydroxy Benzoic Acid as HSP90Alpha Inhibitors

HSP90 assists as a crucial molecular chaperone that responds to environmental stressors and helps in the survival of cells in microorganisms. This protein is integral to the stress response, aiding in the stabilization of various proteins essential for microbial survival. Consequently, the ability of a number of tissues to adjust to endogenous stress depends critically on appropriate chaperone activity. Modulators of chaperone activity, however, have emerged as a novel and developing area of drug discovery due to the association between changed chaperone function and the development of numerous illnesses. Inhibition of HSP90alpha can disrupt proper protein folding, thus impairing growth and virulence in fungi. In this work, we selected novel leads of gallic acid derivatives with the help of OSIRIS Property Explorer and DruLiTo software. Selected leads were subjected to ADME-T studies for further screening. Docking and molecular simulation studies on selected compounds were performed using Schrodinger v21 and GROMACS software to predict the bioactivity of novel leads of 3,4,5 trihydroxy benzoic acid for suppression of the HSP90alpha enzyme. Compounds 4N, 18N, 15N, and 14N showed good docking scores of -6.5, -6.4, -5.91, and -5.98, respectively, which was comparable to standard ciprofloxacin. Compound 4N and compound 14N demonstrated notable binding interactions and were selected for further investigation through molecular dynamics studies with HSP90alpha (PDB ID: 1YC1). RMSD, H BOND, and RMSF analysis confirmed the stable binding of compounds 4N and 14 N with the HSP90 enzyme. The RMSF plot showed less than 0.35 nm fluctuation for the HSP90alpha enzyme in complex with different ligands. It can be concluded that ligand binding can cause stability to the conformation of the protein. Compounds 4N and 14N are considered to be the best theoretical lead, which can further be studied experimentally as HSP90 alpha inhibitors for antimicrobial activity.

Impact of sodium dodecyl sulfate, cetyltrimethylammonium chloride and octyl glucoside surfactants on Aβ dimer conformations: A multiscale approach with MD simulations

This research investigates the effects of an anionic surfactant, sodium dodecyl sulfate (SDS), a cationic surfactant, cetyltrimethylammonium chloride (CTAC), and a nonionic surfactant, octyl glucoside (OG), on the conformation of beta-amyloid peptide dimer using molecular dynamics simulations to decipher the molecular mechanisms underlying these interactions and their effects on Aβ aggregation and toxicity in Alzheimer’s disease. Four simulation models were crafted, each housing a beta-amyloid peptide dimer, with three models incorporating 60 CTAC, 80 SDS, and 50 OG molecules to surpass the critical micelle concentration. Key findings include significant impacts of SDS, CTAC, and OG on the conformational dynamics of Aβ peptides as evidenced by RMSD and RMSF analyses. SDS notably increased the RMSF of residues 1–10 and had a pronounced effect on the C-termini, disrupting the critical salt bridge between aspartic acid 23 and lysine 28, associated with reduced peptide toxicity. Additionally, SDS disrupted more hydrogen bonds and hydrophobic interactions between the monomers of the Aβ dimer, predominantly in the C-termini region. Free Energy Landscape analysis revealed significant structural changes in the Aβ dimer in the presence of surfactants, with varying distributions of surfactant aggregates. Binding free energy calculations using MM-PBSA demonstrated that SDS exhibited the strongest binding affinity to the Aβ dimer, followed by CTAC and OG, with electrostatic forces playing a pivotal role. These outcomes align with experimental data, suggesting that SDS and CTAC, at concentrations above the CMC, diminish Aβ peptide aggregation and toxicity, whereas OG marginally increases toxicity.

In silico exploration of phytocompounds from AYUSH-64 medicinal plants against SARS CoV-2 RNA-dependent RNA polymerase

BackgroundThe AYUSH 64 formulation helps to treat mild to moderate cases of COVID-19. Although several drugs have been proposed to combat COVID-19, no medication is available for SARS-CoV-2 infection. The RNA-dependent RNA polymerase (RdRp) is the pivotal enzyme of SARS-CoV-2 replication, so it could be considered a better drug target for experimental studies. ObjectiveThe AYUSH-64 formulation plants exhibited multiple therapeutic properties; thus, the present study aims to screen the phytocompounds of these plants against SARS CoV2 RdRp to identify specific compounds that could potentially affect COVID-19 infection. Materials and methodsPatchDock and AutoDock tools were used for docking experiments. MD simulations and Density Functional Theory (DFT) calculations of protein-ligand Picroside-I and Remdesivir complexes were carried out in GROMACS v2019.4 and Gaussian 09 software, respectively. ResultsAmong the tested, five phytocompounds (Picroside I, Oleanolic acid, Arvenin I, II, and III) from AYUSH-64 medicinal plants showed possible binding with RdRp catalytic residues (Ser759, Asp760, and Asp761). Of these, Picroside I exhibited hydrogen bond interactions with NTP entry channel residues (Arg553 and Arg555). The MM-PBSA free energy, RMSD, Rg, PCA, and RMSF analysis suggested that the Picroside I complex showed stable binding interactions with RdRp in the 50 ns simulation. In addition to this, Picroside I revealed its robust and attractive nature toward the target protein, as confirmed by DFT. ConclusionThe results of this study have proposed that Picroside I from AYUSH 64 medicinal plant compounds was the selective binder of catalytic and NTP entry channel residues of SARS-CoV2 RdRp thereby; it may considered as a potential inhibitor of SARS-CoV2 RdRp.

In-silico and in-vitro study of novel antimicrobial peptide AM1 from Aegle marmelos against drug-resistant Staphylococcus aureus

Antimicrobial peptides have garnered increasing attention as potential alternatives due to their broad-spectrum antimicrobial activity and low propensity for developing resistance. This is for the first time; proteome sequences of Aegle marmelos were subjected to in-silico digestion and AMP prediction were performed using DBAASP server. After screening the peptides on the basis of different physiochemical property, peptide sequence GKEAATKAIKEWGQPKSKITH (AM1) shows the maximum binding affinity with − 10.2 Kcal/mol in comparison with the standard drug (Trimethoprim) with − 7.4 kcal/mol and − 6.8 Kcal/mol for DHFR and SaTrmK enzyme respectively. Molecular dynamics simulation performed for 300ns, it has been found that peptide was able to stabilize the protein more effectively, analysed by RMSD, RMSF, and other statistical analysis. Free binding energy for DHFR and SaTrmK interaction from MMPBSA analysis with peptide was found to be -47.69 and − 44.32 Kcal/mol and for Trimethoprim to be -13.85 Kcal/mol and − 11.67 Kcal/mol respectively. Further in-vitro study was performed against Methicillin Susceptible Staphylococcus aureus (MSSA), Methicillin Resistant Staphylococcus aureus (MRSA), Multi-Drug Resistant Staphylococcus aureus (MDR-SA) strain, where MIC values found to be 2, 4, and 8.5 µg/ml lesser in comparison to trimethoprim which has higher MIC values 2.5, 5, and 9.5 µg/ml respectively. Thus, our study provides the insight for the further in-vivo study of the peptides against multi-drug resistant S. aureus.

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.

A multifaceted approach to investigate interactions of thifluzamide with haemoglobin

This study explores the interaction between the pesticide thifluzamide (TF) and haemoglobin (Hb) to understand potential structural changes that might affect Hb's function. Using a combination of UV–Visible and fluorescence spectroscopy, circular dichroism (CD), molecular docking, molecular dynamics (MD) simulations, and electrochemical methods, we investigated these interactions in detail. Spectroscopy results indicated the formation of a stable TF-Hb complex, with a binding constant of 6.64 × 105 M−1 at 298 K and a 1:1 binding ratio. The stability of this complex was confirmed by a free energy change (∆G) of −34.491 kJ mol−1. CD spectroscopy was employed to confirm structural changes in Hb due to thifluzamide binding. Molecular docking studies revealed that TF interacts with specific amino acids in Hb like ALA, HIS, VAL, LYS, and LEU, with a binding energy of −25.10 kJ mol−1. MD simulations supported these findings by showing conformational changes in Hb upon TF binding, as indicated by RMSD and RMSF analyses. Electrochemical experiments further confirmed the interaction, evidenced by a consistent decrease in the TF's peak in the presence of Hb. Overall, our findings shed light to understand the binding of TF with Hb, causing structural changes that could potentially impact its normal function. This research enhances our understanding of the biochemical effects of TF on Hb, which could have significant implications for biological systems.

Investigating the role of natural flavonoids in VEGFR inhibition: Molecular modelling and biological activity in A549 lung cancer cells

Genetics, lifestyle, and hormones influence lung cancer, the most common malignancy in the world. VEGFR plays a key role in tumor growth and metastasis by promoting angiogenesis. While anti-angiogenic therapies targeting VEGFR show potential, resistance remains a challenge, and elevated VEGFR levels are associated with aggressive tumors and poor outcomes. This research explores using natural flavonoids to inhibit VEGFR activity in lung cancer, focusing on computational studies and in-vitro assays with the A549 cell line. Molecular docking revealed that 18 flavonoids outperformed axitinib and 26 surpassed sorafenib in effectiveness. Molecular dynamics simulation showed system stabilization after 80 ns with RMSD between 2 and 4 Å RMSF analysis revealed fluctuations in the activation loop and hinge region. Hydrogen bonds, especially with GLU 149, were key to the complex's stability. PCA highlighted conformational changes, and MM/GBSA calculated a binding free energy of -34.72 kcal/mol. In particular, quercetin had a lower IC50 value (6.24 ± 0.42 µM) than axitinib (7.85 ± 0.59 µM), which means it had stronger effects on lung cancer cells. Other flavonoids like taxifolin and luteolin showed similar efficacy. The findings suggest potential for tailored therapies that could enhance personalized treatment approaches for lung cancer.

Phytochemistry, antioxidant and anti-diabetic activities of Sterculia villosa in-vitro

ObjectiveAs ongoing research continues, many anti-diabetic agents still have a multitude of side effects which is the reason why more and more people resort to traditional medicines such as Traditional Chinese Medicine (TCM). There are many Therapeutic Species of Sterculia spp. that are commonly used in TCM practices. Here, we have studied one of such TCM herbal plants, namely Sterculia villosa Roxb. (Chinese: 绒毛苹婆), for its anti-diabetic potential. In this way, the study intends to assess its effectiveness and examine its suitability as a raw natural medicine for diabetes management in traditional medicine. MethodIn-vitro anti-diabetic property was evaluated by α-amylase and α-glucosidase enzyme inhibition and glucose uptake assays. Metabolomic profiling by GC–MS was conducted to determine the probable phyto-constituents in S. villosa. These phyto-compounds were further subjected to in-silico molecular docking studies, identifying stigmasterol as the most potent anti-diabetic phyto-compound. Glucose uptake efficacy was estimated by a fluorescence microplate reader employing glucose analog, 2-NBDG. Molecular dynamic studies (MDS) were carried out with GROMACS to comprehend the protein-ligand binding stability. ResultsStigmasterol showed enhanced enzyme inhibition for both α-amylase (IC50 23.84±1.37 μM) and α-glucosidase (IC50 39.56±1.5 μM). Line-weaver Burk plot revealed competitive and mixed modes of inhibition for α-amylase and α-glucosidase, respectively. The GC-–MS analysis identified 23 vital phyto-compounds present in the methanolic extract of the S. villosa leaves. Upon screening against crucial anti-diabetic proteins by in-silico molecular docking, stigmasterol followed by lupeol, Stigmasta-3,5-diene, and γ-sitosterol were found to be the most effective lead compounds. Stigmasterol also showed potent hypoglycaemic efficacy, as evidenced by augmentation of 2-NBDG glucose uptake in 3T3-L1 cells. The docking and simulation studies against four crucial anti-diabetic targets, α-amylase, α-glucosidase, GLUT 4, and IRS-1, predicted that stigmasterol exhibits a multi-pronged anti-diabetic activity mediated by α-amylase inhibition and activation of IRS1 pathway, simultaneously. The MDS studies highlighted that stigmasterol showed stable interactions with these four proteins, as evidenced by the RMSD, RMSF and hydrogen bond analysis. ConclusionThe results of this study are intriguing, as they identify stigmasterol, sourced from the medicinal plant S. villosa, as a potential breakthrough in the field of diabetic remediation. This discovery paves the way for further research and development of stigmasterol as a more effective and safer treatment for diabetes.

Insights into the binding recognition and computational design of IL-2 muteins with enhanced predicted binding affinity to the IL-2 receptor α

Interleukin-2 (IL-2) is an immune system regulator that has received approval for cancer treatment. However, high-dose IL-2 therapy has seen restricted use due to its low efficacy and on-target toxicity. To enhance the effectiveness of IL-2 therapy, it is essential to engineer IL-2 molecules to enhance their specificity toward target cell populations. In this study, molecular dynamics (MD) simulations and Rosetta software were utilized to design novel high-affinity IL-2Rα-binding IL-2 muteins. MD simulations were used to identify the target residues of IL-2 for design, and Rosetta software were then employed to predict potential IL-2 muteins with higher binding affinity toward IL-2Rα. Rosetta generated two potential designed IL-2 muteins. The results of the MD validation and MM/GBSA analysis indicated that both designed IL-2 muteins exhibited greater predicted binding affinities toward IL-2Rα than that of the native proteins. RMSF analysis demonstrated that the structural fluctuations of free IL-2 and designed muteins were similar, indicating that the mutations did not alter the intramolecular force responsible for IL-2's stability and folding. These designed IL-2 muteins may have potential benefits for cancer immunotherapy.

Widely-targeted in silico and in vitro evaluation of veratrum alkaloid analogs as FAK inhibitors and dual targeting of FAK and Hh/SMO pathways for cancer therapy: A critical analysis

Focal Adhesive Kinase (FAK), a key player in aggressive cancers, mediates signals crucial for progression, invasion, and metastasis. Despite advances in targeted therapies, drug resistance is still a challenge, and survival rates remain low, particularly for late-stage patients, emphasizing the need for innovative cancer therapeutics. Cyclopamine, a veratrum alkaloid, has shown promising anti-tumor properties, but the search for more potent analogs with enhanced affinity for the biological target continues.This study employs a hybrid virtual screening approach combining pharmacophore model-based virtual screening (PB-VS) and docking-based virtual screening (DB-VS) to identify potential inhibitors of the FAK catalytic domain. PB-VS on the PubChem database yielded a set of hits, which were then docked with the FAK catalytic domain in two stages (1st and 2nd DB-VS). Hits were ranked based on docking scores and interactions with the active site. The top three compounds underwent molecular dynamics simulations, alongside two control compounds (SMO inhibitor(s) and FAK inhibitor(s)), to assess stability through RMSD, RMSF, Rg, and SASA analyses. ADMET properties were evaluated, and compounds were filtered based on drug-likeness criteria.Molecular dynamics simulations demonstrated the stability of compounds when complexed with the FAK catalytic domain. Compounds 16 (−25 kcal/mol), 87 (−27.47 kcal/mol), and 88 (−18.94 kcal/mol) exhibited comparable docking scores, interaction profiles, stability, and binding energies, indicating their potential as lead candidates. However, further validation and optimization through quantitative structure-activity relationship (QSAR) studies are essential to refine their efficacy and therapeutic potential. The in vitro cell-based assay demonstrated that compound 101PF, a FAK inhibitor, significantly inhibited the proliferation and migration of A549 cells. However, the results regarding the combined effects of FAK and SMO inhibitors were inconclusive, highlighting the need for further investigation. This study contributes to developing more effective anti-cancer drugs by improving the understanding of potential cyclopamine-based veratrum alkaloid analogs with enhanced interactions with the FAK catalytic domain.

Discovering potential asthma therapeutics targeting hematopoietic prostaglandin D2 synthase: An integrated computational approach

Allergic asthma, a chronic inflammatory illness that affects millions worldwide, has serious economic and health consequences. Despite advances in therapy, contemporary treatments have poor efficacy and negative effects. This study investigates hematopoietic prostaglandin D2 synthase (HPGDS) as a potential target for novel asthma therapies. Targeting HPGDS may provide innovative treatment methods. A library of phytochemicals was used to find putative HPGDS inhibitors by structure-based and ligand-based virtual screening. Among the 2295 compounds screened, four compounds (ZINC208828240, ZINC95627530, ZINC14727536, and ZINC14711790) demonstrated strong binding affinities of −10.4, −10.3, −9.2, −9.1 kcal/mol respectively with key residues, suggesting their potential as a highly effective HPGDS inhibitor. Molecular dynamics (MD) simulations and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) computations were further performed to evaluate the stability and binding affinity of the complexes. MD simulations and MMPBSA confirmed that compound ZINC14711790 showed high stability and binding affinity (binding energy −31.52 kcal/mol) than other compounds, including HQL-79, suggesting that this compound might be used as promising inhibitors to treat asthma. RMSD and RMSF analysis also revealed that ZINC14711790 exhibited strong dynamic stability. The findings of this study show the efficacy of ZINC14711790 as HPGDS inhibitors with high binding affinity, dynamic stability, and appropriate ADMET profile.

Identification of Potent Inhibitors of Akt Kinases inhibitors from natural sources for Therapeutic Targeting of Oral Squamous Cell Carcinoma

BackgroundPlant-based natural compounds are effective cancer cell proliferation inhibitors. Consequently, the quest for these compounds for the treatment of cancer has become increasingly competitive and has opened up new avenues for drug development. The current investigation extensively addressed the virtual screening and structure-based prediction of compounds derived from natural products against Protein kinase B-alpha (PKBα, also known as Ak/4GV1).Material and MethodsIn this study, we conducted a thorough screening of putative PKBα inhibitors from a natural products library, and subsequently performed molecular modeling.ResultsThis research identified Irciniastatin B, Irciniastatin A, Pseudoceroxime D, (1'S)-7-chloroaverantin as the top four potential PKBα inhibitors from the library of natural products, whose Glide docking scores range from -10.689 to -7.567 kcal/mol. The RMSD and RMSF analysis reveals that all four ligands remain stable and maintain their interaction throughout the simulation time. The MM/GBSA (ranging from -37.26 to -51.02 kcal/mol) predicted binding affinities are in strong co-relation with that of the docking score, which not only supports the docking results but also suggests that Irciniastatin B exhibits superior binding affinity towards PKBα amongst all four studied compounds. Moreover, the interaction analysis also indicates that Irciniastatin B establishes at least 12 interactions with the neighbouring residues whereas, Irciniastatin A, Pseudoceroxime D, and (1'S)-7-chloroaverantin compounds were able to establish 8-9 interactions in the binding cavity of PKBα. ADMET assessment of the selected compounds was also noted to be within acceptable ranges.ConclusionKeeping in view these findings, Irciniastatin B might be a promising candidate for drug discovery against PKBα inhibitors.