In-silico Approach Research Articles

Identification and validation of cross-reactivity of anti-Thailand orthohantavirus nucleocapsid peptides

A Thailand orthohantavirus (THAIV) is endemic in Southeast Asia. This assumption is supported by isolation of THAIV from local small mammals. Also, anti-orthohantavirus antibodies were detected in human serum. However, our understanding of THAIV cross-reactivity with antibodies against other orthohantaviruses remains largely unknown.We used the in-silico approach to identify the cross-reactive immunogenic peptides of THAIV. The immunogenicity of these peptides was tested using convalescent serum from patients infected with Puumala (PUUV), Hantaan (HNTV) and Dobrava (DOBV) orthohantaviruses.We identified three THAIV peptides reacting with orthohantavirus convalescent serum. P1 peptide was reactive with serum from patients infected with PUUV, HNTV and DOBV. These peptides were found to be non-allergenic. Molecular docking and population coverage analysis revealed the potential of selected peptides to interact with diverse HLA alleles worldwide.Our data indicate that THAIV peptides could be used to develop diagnostics for orthohantaviruses circulating in Southeast Asia.

A pan-genomic analysis based multi-epitope vaccine development by targeting Stenotrophomonas maltophilia using reverse vaccinology method: an in-silico approach.

Antibiotic resistance in bacteria leads to high mortality rates and healthcare costs, a significant concern for public health. A colonizer of the human respiratory system, Stenotrophomonas maltophilia is frequently associated with hospital-acquired infections in individuals with cystic fibrosis, cancer, and other chronic illnesses. The importance of this study is underscored by its capacity to meet the critical demand for effective preventive strategies against this pathogen, particularly among susceptible groups of cystic fibrosis and those undergoing cancer treatment. In this study, we engineered a multi-epitope vaccine targeting S. maltophilia through genomic analysis, reverse vaccination strategies, and immunoinformatic techniques by examining a total of 81 complete genomes of S. maltophilia strains. Our investigation revealed 1945 core protein-coding genes alongside their corresponding proteomic sequences, with 191 of these genes predicted to exhibit virulence characteristics. Out of the filtered proteins, three best antigenic proteins were selected for epitope prediction while seven epitopes each from CTL, HTL, and B cell were chosen for vaccine development. The vaccine was refined and validated, showing highly antigenic and desirable physicochemical features. Molecular docking assessments revealed stable binding with TLR-4. Molecular dynamic simulation demonstrated stable dynamics with minor alterations. The originality of this investigation is rooted in the thorough techniques aimed at designing a vaccine that directly targets S. maltophilia, a microorganism of considerable clinical relevance that currently lacks an available vaccine. This study not only responds to a pressing public health crisis but also lays the groundwork for subsequent research endeavors focused on the prevention of S. maltophilia outbreaks. Further evidence from studies in mice models is needed to confirm immune protection against S. maltophilia.

Climate-adaptative management strategies for soybean production under ENSO scenarios in Southern Brazil: An in-silico analysis of crop failure risk

CONTEXTSoybeans (Glycine max L.) are a crucial crop for global food security, and the state of Rio Grande do Sul (RS), Brazil, plays a significant role. However, climate instability, particularly water stress (WS), is a major concern in this region, causing large interannual yield variability. OBJECTIVEThis study aims to address this issue using an in-silico approach to: i) characterize WS and spatial patterns and their frequency within ENSO events; and ii) explore climate-adaptative management strategies such as planting dates and maturity groups to mitigate the risk of crop failure and maximize seed yield and profits. METHODSCrop growth simulations were performed testing three soybean maturity groups (MG, 5.0, 5.8, and 6.4) and eight planting dates (from October 5th to January 20th) over 30 years at 187 locations in RS, Brazil, using APSIM Next Generation. Failure risk was calculated as the percentage of simulations that yielded less than the economic break-even soybean yield in a given scenario. RESULTS AND CONCLUSIONSThe simulated yields were clustered into four regions: Northeast, North, Central, and Southwest. Four WS seasonal patterns were then defined (no stress, early stress, late stress, and whole season stress). On average, WS reduced yields up to 2 Mg ha-1 (∼50 % relative to the maximum). WS varied among regions, with the SW experiencing more frequent and severe stress (up to 50 % of whole season stress during La Nina). ENSO events influenced WS frequency, with El Niño events associated with reduced stress and La Niña events to increased stress. The MG 5.0 resulted in a higher probability of failure risk in all regions. Early planting dates resulted in the highest yield variability (up to 5 Mg ha-1). Climate-adaptative management strategies, such as optimizing planting dates and maturity groups, resulted in a 15 % reduction in crop failure. SIGNIFICANCEOur findings provide valuable insights for developing targeted approaches to enhance soybean yield stability, thereby increasing the resilience of agriculture in the face of future climate uncertainties.

GC–MS analysis, molecular docking, and pharmacokinetic studies on Dalbergia sissoo barks extracts for compounds with anti-diabetic potential

Diabetes is a metabolic condition defined by abnormal blood sugar levels. Targeting starch-hydrolyzing enzymes and Dipeptidyl Peptidase 4 (DPP-4) expressed on the surface of numerous cells is one of the key strategies to lower the risk of Type-2 diabetes mellitus (T2DM). Dalbergia sissoo Roxb. bark (DSB) extracts have been reported to have anti-diabetic properties. This study intended to scientifically validate use of alcoholic and hydro-alcoholic extracts of DSB for T2DM by conducting preliminary phytochemical investigations, characterising potential phytochemicals using Fourier transform infrared (FT-IR) spectroscopy and Gas chromatography-mass spectrometry (GC–MS) analysis followed by comprehensive in-silico analysis. A qualitative phytochemical evaluation indicated the presence of alkaloids, phenolics, glycosides, conjugated acids and flavonoids. Ethanolic extracts showed highest total phenolic content (TPC) (127.072 ± 14.08031 μg GAE/g dry extract) and total flavonoid content (106.911 ± 5.84516 μg QE /g dry extract). Further FT-IR spectroscopy also revealed typical band values associated with phenol, alcohol, alkene, alkane and conjugated acid functional groups. The GC–MS analysis identified 139 compounds, 18 of which had anti-diabetic potential. In-silico ADMET analysis of potential compounds revealed 15 compounds that followed Lipinski’s rule and demonstrated drug-like properties, as well as good oral bioavailability. Molecular docking was utilised to analyse their potential to interact with three targets: α-amylase, α-glucosidase, and DPP-4, which are crucial in managing diabetes-related problems. Molecular Docking analysis and membrane permeability test utilising the PerMM platform revealed that compounds in the extracts, such as Soyasapogenol B and Corydine, had better interactions and permeability across the plasma membrane than standard drugs in use. Molecular dynamics simulations also showed that selected compounds remained stable upon interaction with α-amylase. Overall, using the in-silico approaches it was predicted that DSB extracts contain potential phytochemicals with diverse anti-diabetic properties. It further needs to be investigated for possible development as formulation or drug of choice for treating T2DM.

Exploring the therapeutic potential of Pongamia pinnata plant extract against skin cancer: In-silico and in-vitro study

Ethnopharmacological relevancePongamia pinnata Linn belonging to the Fabaceae family, holds significance as a crucial remedy in herbal medicine. Aim of the studyThe present study aims to determine the anticancer and antioxidant properties of the plant extract. Material and methodsThe methodology includes extraction of the leaf sample by soxhlet method followed by the phytochemical analysis of leaf extract. Through in-silico approach three anti-cancer receptors were analyzed with 10 ligands which were studied using molecular docking and molecular simulation approach. The prediction outcome of in-silico tests on the petroleum ether plant extract served as a foundation for the subsequent in-vitro studies. Phytochemical profiling of plant extracts using GC-MS analysis, and cytotoxicity testing for A431 skin cell line using MTT Assay. ResultsThe binding affinity of Pongamia pinnata as an anti-cancer agent with respect to the targets EGF, EGFR, ERBB2 was evident. In the in-silico studies, the highest binding affinity with respect to the docked complexes were -8.2 kcal/mol for EGF with Pazopanib, -8.3 kcal/mol for EGFR with pongachromene, -9.5 kcal/mol for ERBB2 with Vitexin. Further these complexes were assessed by molecular simulations and it confirms the stability of these complexes. In in-vitro studies the HPLC results indicated the presence of 0.176 ± 0.001 mg/mL of phenols and 0.159 ± 0.001 mg/mL of flavonoids. The IC50 value was 1.051 which revealed the antioxidant potential. The cytotoxicity studies against the A431 skin cancer cell resulted in an IC50 concentration of 89.59 μg/ml. ConclusionsThese studies show that P. pinnata has the properties to serve as a therapeutic agent for the treatment of skin tumors. The molecular simulation studies approach is a predictor for drug discovery, acting as a basis for testing anti-cancer activity against the skin tumor. As a result, it can be a useful source of crude drug for the treatment of melanomas.

In-silico approaches in designing new drug candidates (THICAPA and POET) for alzheimer’s disease

Background: Memory and cognitive regression are the first symptoms of Alzheimer’s Disease (AD), which may progress to speech and mobility challenges which affecting around 35% of those who over the age of 80 years old. Preliminary study shows THICAPA and Palm Oil Extracted Tocotrienol (POET) is effective in reducing AD symptoms in Dorosophila melagnoster. Objective: The purpose of this study is to elucidate the binding interaction between THICAPA and POET towards APP and PS1 at the molecular level. Method: The binding of THICAPA and POET towards APP (PDB ID: 6SZF), PS1 (PDB ID: 7D8X), and their genetic mutation variations (APP variant n = 6, PS1 variant n = 200) have been studied using in-sillico molecular docking (Autodock 4.2) approaches and comparing the Binding Free Energy (BFE) of the binding interactions. Result: From the 416 dockings (n = 100 per docking, ∑n = 41,600), we revealed that all dockings had negative BFE which showed the low BFE towards both APP (E22K variant ΔG THICAPA = -6.20 kcal/mol, D23N variant ΔG POET = -7.25 kcal/mol) and PS1 (A413V variant ΔG THICAPA = -8.34 kcal/mol, L174M variant ΔG POET = -10.94 kcal/mol). Conclusion: THICAPA and POET showed a negative BFE with APP and PS1. Thus, the result suggesting that THICAPA and POET may be the potential drug candidates for treating AD.

In Silico Studies for Multi-Targeting Justicia Secund Phytochemicals Against Ovarian Cancer

ntroduction/Background of study: Ovarian cancer is the fifth leading cause of cancer deaths among women, accounting for more deaths than any other female gynaecological cancer, which includes cervical, uterine, vaginal and vulvar cancers. Current treatment options include surgery, platinum-based chemotherapy, radiation therapy and the use of targeted therapy such as poly ADP-ribose polymerase (PARP inhibitors), as well as immunotherapy. These therapy options, however, are subject to high rates of resistance and many side effects. AIM/ OBJECTIVES: This research aims to study other viable drug targets for ovarian cancer treatment, as well as new phytocompounds that can serve as new drug options using the in-silico approach. Materials/Methods: The ethanolic leaf extract of Justicia secunda was obtained using conventional methods. Liquid Liquid-liquid fractionation was performed with N-hexane, ethyl acetate and butanol solvents to obtain their fractions alongside the aqueous fraction. Vacuum Liquid Chromatography was performed with the N-hexane fraction and gradient mixtures of N-hexane/ethyl acetate and Dichloromethane/Methanol in various ratios to obtain the subfractions. The compounds were identified using Gas Chromatography-Mass Spectrometry (GC-MS). Full pharmacognostic profiling was performed on the J.secunda leaves. The identified compounds were downloaded from Pubchem and subjected to Molecular docking simulations to obtain their binding affinities with the receptors of interest. Drug-likeness and toxicity assessments were performed on frontrunner compounds. Results: After assessment of the frontrunner compounds, four multitargeting J.secunda phytochemicals were identified: Luteolin, Diosmetin, 5H-Quindoline and 10H-Quindoline.

Evaluation of antiviral efficacy of graphene oxide nanosheets on dengue virus-infected Vero cells: in-vitro and in-silico approaches

Emerging viral diseases have led to an increased demand for novel therapeutic medicines. Graphene nanostructures exhibit excellent inhibitory antiviral effects owing to their unique physic-chemical properties. In this study we have investigated the potential of graphene oxide (GO) nanostructures for antiviral activity. GO was synthesized by Modified Hummer’s method and fully characterized using several chemical-physical techniques to confirm the structure, morphology, optical properties, chemical composition and oxidation states. The antiviral property of the GO was investigated against serotype-2 dengue virus. The results suggest that the antiviral action is attributed to the negative charge of the graphene sheets due to the presence of oxygenated functional groups. Dengue virus −2 infection was suppressed by 90% with GO in a dose-dependent manner. Cytotoxic features of GO against Vero cells were observed when treated at higher concentrations (>75 μg ml−1 IC 50 concentration). The in-silico investigation showed that the interaction between GO nanosheets and serotype-2 dengue virus occurred within the ligand-protein complex as confirmed by molecular docking studies. These results emphasize that GO has strong antiviral activity against serotype-2 dengue virus.

CRISPR-Cas9 guided RNA-based model for the silencing of spinal bulbar muscular atrophy: A functional genetic disorder.

This study explores a novel therapeutic approach for spinal bulbar muscular atrophy (SBMA), a neurodegenerative disorder caused by a mutation in the Androgen Receptor (AR) gene. The aim is to investigate the potential of CRISPR-Cas9 technology in targeting the mutant AR gene to inhibit its production. The objectives include assessing the accuracy and efficacy of CRISPR-Cas9 guided RNAs in silencing the mutant gene and evaluating the feasibility of this approach as a treatment for SBMA. Computational and in-silico approaches are used to evaluate the feasibility of using CRISPR-Cas9 technology for treating SBMA. Computational analysis is used to design CRISPR-Cas9 guided RNAs targeting the mutant AR gene, assessing their on-target and off-target scores, GC content, and structural accuracy. In-silico simulations predict the potential therapeutic outcomes of the CRISPR-Cas9 approach in an artificial environment. Three guided RNA (gRNA) sequences were designed using the CHOPCHOP tool, targeting specific regions of the AR gene with high efficiency and 100% match. These gRNAs demonstrated effective targeting with minimal off-target scores and optimal GC content. Additionally, lentiCRISPR v2 plasmids were designed for the delivery of CRISPR materials, enabling high-efficiency multiplex genome editing of the AR gene. Thermodynamic ensemble predictions indicated favorable secondary structure stability of the designed gRNAs, further supporting their suitability for gene editing. The evaluation of designed gRNAs confirmed their strong binding ability to the target sequences, validating their potential as effective tools for genome editing. The study highlights the potential of CRISPR-Cas9 technology for targeting the Androgen Receptor gene associated with spinal bulbar muscular atrophy (SBMA). The findings support the feasibility of this approach for gene editing and suggest further exploration in preclinical and clinical settings. Recommendations include continued research to optimize CRISPR-Cas9 delivery methods and enhance specificity for therapeutic applications in SBMA.

An in-silico approach to the dynamics of proliferation potential in stem cells and the study of different therapies in cases of ovarian dysfunction

A discrete mathematical model based on ordinary differential equations and the associated continuous model formed by a partial differential equation, which simulate the generational and temporal evolution of a stem cell population, are proposed. The model parameters are the maximum proliferation potential and the rates of mitosis, death events and telomerase activity. The mean proliferation potential at each point in time is suggested as an indicator of population aging. The model is applied on hematopoietic stem cells (HSCs), with different telomerase activity rates, in a range of variation of maximum proliferation potential in healthy individuals, to study the temporal evolution of aging. HSCs express telomerase, however not at levels that are sufficient for maintaining constant telomere length with aging [1,2]. Women with primary ovarian insufficiency (POI) are known to have low telomerase activity in granulosa cells and peripheral blood mononuclear cells [3]. Extrapolating this to hematopoietic stem cells, the mathematical model shows the differences in proliferation potential of the cell populations when telomerase expression is activated using sexual steroids, though the endogenous promoter or with gene therapy using exogenous, stronger promoters within the adeno-associated virus. In the first case, proliferation potential of cells from POI condition increases, but when adeno-associated viruses are used, the proliferation potential reaches the levels of healthy cell populations.

An integrated In-Silico-In-Chemico-In-Vitro (iSiCiV) Approach to identify biomarkers to predict the skin sensitisation potential of phytochemicals

BackgroundSkin sensitisation is one of the important regulatory endpoints used to determine whether a given test chemical can elicit an allergic response in susceptible individuals. The in-vitro approaches for predicting skin sensitisation potential for chemicals have been well-developed and widely accepted. Continuous efforts are being made to identify novel solutions to overcome the limitations of the existing approaches. PurposeThe herbal preparations used in dermal therapeutics are frequently found to elicit skin sensitisation, requiring caution. The herbal preparations tend to contain more than one phytochemical. The expected active ingredient may not possess skin sensitisation. However, the other phytochemical traces could pose synergistic and potentiating effects towards enhanced/suppressed skin sensitisation. In this regard, isolation, purification, yield, and in-vitro / in-vivo evaluation of skin sensitisation for all the traces would be time, cost, and animal-consuming. Hence, the regulatory agencies appreciate using computational tools to substantiate in-vitro methods. The regulators have also endorsed using in-silico approaches like quantitative structure-activity relationships (QSAR) and read-across. These approaches are limited to structure-based predictions and in combination with system-level approaches, which comprehensively facilitate a better understanding of complex biological systems. Study designIn the present study, 603 phytochemicals were screened in-silico using OECD QSAR Toolbox. The limitations of the QSAR Toolbox in predicting skin sensitisers were identified. MethodThe systems biology-based approach to complement the QSAR-based prediction was developed, and 41 biomarkers were identified as a determinant of skin sensitisation. The molecules attributed to these biomarkers were predicted as skin sensitisers. ResultsAs a result, 31 phytochemicals were predicted as skin sensitisers. Acrolein, eugenol, formaldehyde, and glycerol were selected for experimental validation of the in-silico predictions using direct peptide reactivity assay (DPRA), KeratinoSens™, and h-CLAT assays representing each key event in skin sensitisation. Further, identified biomarkers were validated in THP-1 and KeratinoSens cell lines using qRT-PCR. Among all genes, IL-8 and CCL4 were upregulated by 6.4 and 5.6 folds, respectively, in THP-1, while AKR1C2 and AKR1C3 were upregulated by 7.8 and 11.1 folds, respectively, in KeratinoSens. IL-8 level was analysed by ELISA and found to be in line with qRT-PCR results. ConclusionThe study proposes a possible strategy based on the “iSiCiV” approach to enhance the prediction of the dermal sensitisation potential of a test compound. The approach offers a robust platform and highlights an opportunity to shift the paradigm of skin sensitisation assay with a better understanding of toxicology mechanisms.

Discovery of novel CDK4/6 inhibitors from fungal secondary metabolites

The development of targeted therapies for breast cancer, particularly those focusing on cyclin-dependent kinases 4/6 (CDK4/6), has significantly improved patient outcomes. However, the currently approved CDK4/6 inhibitors are associated with various side effects, underscoring the need for novel compounds with enhanced efficacy and safety profiles. This study aimed to identify potential CDK4/6 inhibitors from MeFSAT, a database of fungal secondary metabolites using an in-silico screening approach. The virtual screening process incorporated drug-likeness filters, ADME and toxicity predictions, consensus molecular docking, and 200 ns molecular dynamics simulations. Out of 411 initial compounds, two molecules demonstrated favorable binding interactions and stability with the CDK4/6 protein complex. The MTT assay showed that MSID000025 had dose-dependent cytotoxicity against MCF7 breast cancer cells. This suggests that MSID000025 could be a good candidate CDK4/6 inhibitor for treating breast cancer. Our study highlights the potential of fungal secondary metabolites as a source of novel compounds for drug discovery. It provides a framework for identifying CDK4/6 inhibitors with improved therapeutic properties.

In-silico Assessment of Polyherbal Oils as Anti-diabetic Therapeutics.

Diabetes mellitus (DM) is characterized by elevated blood glucose levels either due to insufficient insulin production, defective insulin action, or both. It affects nearly 537 million individuals worldwide. Pharmacological treatment involves the use of oral antidiabetic agents as mono or combination therapy that effectively aids in controlling hyperglycemia. Despite providing therapeutic benefits, these medications limit their use owing to adverse side effects. Certain natural products, including essential oils, have promising anti-diabetic properties. The present study explores the effectiveness of two polyherbal oils and their compound towards the treatment of DM based on an In-silico approach to drug investigations Methods: Compounds present in the polyherbal oil formulation were identified using GCMS/ MS analysis. Selected compounds undergo molecular docking with the receptor, and proteins play an important role in DM. The potential compounds showing higher interactions than the known inhibitors or inducers were evaluated using molecular dynamic simulations RMSD value. The compounds identified through GC-MS analysis possess anti-diabetic and antiinflammatory properties. With the aid of in silico prediction methods, compounds such as geraniol, cinnamaldehyde, anethole, caryophyllene, terpinyl acetate, cymene, linalool, menthol, Phenol,2-methoxy-3-(2-propenyl), and 2,6- octadienal,3,7-dimethyl were identified as strong binders of GLUT4 and insulin receptor proteins. Geraniol and Phenol,2-methoxy-3-(2-propenyl) interaction with GLUT4 were of particular importance owing to their conformational stability. Our data suggest an agonistic effect of compounds on target proteins aiding in enhanced insulin activity and could serve as a potential anti-diabetic agent.

In silico screening and identifying phytoconstituents of Withania somnifera as potent inhibitors of BRCA1 mutants: A therapeutic against breast cancer

Breast CAncer gene 1 (BRCA1) is an anti-oncogene that helps the cell repair damaged DNA and preserve genetic material. BRCA1 also acts as a cell growth suppressor and produces tumor suppressor gene (TSG) proteins, i.e., BRCA1 protein. Remarkably, BRCA1 mutations account for 90 % of hereditary breast cancer and a majority of hereditary ovarian cancer. Hence, we have considered three mutants of BRCA1 (R1699W, R1699Q, T1700A) in this study and adopted an in-silico approach to find the best possible phytochemical to inhibit these mutated proteins, enabling early breast cancer diagnosis. Perceiving the importance, many natural molecules from ancient medicinal plants are considered for molecular docking. Our findings suggest that though many molecules bind actively with the receptor's active site, the top three phytoconstituents (27-Deoxy-14-hydroxywithaferin A, Withacoagulin, Somniferanolide) of Withania somnifera, commonly known as Ashwagandha, have high binding affinities and suitable pharmacokinetic properties, making these natural compounds potential drug candidates. Further, molecular dynamics (MD) simulation and the binding free energy calculation show stability and thermodynamically favourable. We can, therefore, draw the conclusion that these lead compounds act as potential inhibitors against BRCA1. However, wet lab experiments and clinical trials are recommended to ascertain its efficacy, hence the development of novel BRCA1 inhibitors.

Design and In-silico Study of ¹³¹Iodium Radiolabeled of Thiourea derivatives for Breast Cancer Treatment

Breast cancer is a serious challenge in both developed and developing countries, with current therapies still limited and potentially producing adverse side effects. To optimize breast cancer drug development, this study adopted an in-silico design approach. The aim is to develop radiopharmaceutical drugs with minimal side effects. Methods involved molecular docking analysis, molecular dynamics, drug scan, and pharmacokinetic profile prediction of the original ligan as well as the radioligand. Results showed that the radioligand had better binding energy and inhibition constant than tamoxifen as a comparator drug which is -11.31 kcal/mol and 0.00511 µM. Molecular dynamics analysis revealed that the radioligand compound exhibits comparable RMSD, RMSF, and stability metrics to the native ligand at the GRPR receptor with average RMSD and RMSF of 5.263 Å and 2.285 Å, respectively. By considering the results of these various methods, the radioligand compound shows potential as an effective radiopharmaceutical drug in breast cancer therapy.

Investigation of dual inhibition of antibacterial and antiarthritic drug candidates using combined approach including molecular dynamics, docking and quantum chemical methods

Emerging antibiotic resistance in bacteria threatens immune efficacy and increases susceptibility to bone degradation and arthritic disorders. In our current study, we utilized a three-layer in-silico screening approach, employing quantum chemical methods, molecular docking, and molecular dynamic methods to explore the novel drug candidates similar in structure to floroquinolone (ciprofloxacin). We investigated the interaction of novel similar compounds of ciprofloxacin with both a bacterial protein S. aureus TyrRS (1JIJ) and a protein associated with gout arthritis Neutrophil collagenase (3DPE). UTIs and gout are interconnected through the elevation of uric acid levels. We aimed to identify compounds with dual functionality: antibacterial activity against UTIs and antirheumatic properties. Our screening based on several methods, sorted out six promising ligands. Four of these (L1, L2, L3, and L6) demonstrated favorable hydrogen bonding with both proteins and were selected for further analysis. These ligands showed binding affinities of −8.3 to −9.1 kcal/mol with both proteins, indicating strong interaction potential. Notably, L6 exhibited highest binding energies of −9.10 and −9.01 kcal/mol with S. aureus TyrRS and Neutrophil collagenase respectively. Additionally, the pkCSM online database conducted ADMET analysis on all lead ligand suggested that L6 might exhibit the highest intestinal absorption and justified total clearance rate. Moreover, L6 showed a best predicted inhibition constant with both proteins. The average RMSF values for all complex systems, namely L1, L2, L3 and L6 are 0.43 Å, 0.57 Å, 0.55 Å, and 0.51 Å, respectively where the ligand residues show maximum stability. The smaller energy gap of 3.85 eV between the HOMO and LUMO of the optimized molecule L1 and L6 suggests that these are biologically active compound. All the selected four drugs show considerable stabilization energy ranging from 44.78 to 103.87 kcal/mol, which means all four compounds are chemically and physically stable. Overall, this research opens exciting avenues for the development of new therapeutic agents with dual functionalities for antibacterial and antiarthritic drug designing.

Bioactive Compounds from Natural Products as RHOA/ROCK and VEGFR1 Inhibitors: An In-silico Approach for Developing Therapeutics for ALI/ARDS

Acute Respiratory Distress Syndrome (ARDS) is a dangerous lung condition characterised by non-cardiogenic pulmonary edoema caused by various factors, including inflammation and hypoxia. It is a more severe and evolved form of Acute Lung Injury (ALI) and requires the patient to be on mechanical ventilation for survival. Several medicinal plants, herbs, oils, and natural extracts have been studied for their anti-inflammatory properties and their targeted action on respiratory disorders. The target of the current study is to elaborate on the target-specific action of bioactive compounds from natural products by Molecular Docking and study their drug-likeness along with their other important pharmacokinetic properties. Bioactive compounds (total 71) from Zingiber officinale (ginger), Trifolium pratense (red clover), Curcuma longa (turmeric), Melaleuca alternifolia (tea tree), Ocimum tenuiflorum (Tulsi), Chlorophytum borivilianum (Safed Musli), Cinnamomum cassia (cinnamon), Elettaria cardamomum (cardamom), and Glycine max (soybean) were selected to be investigated and were screened against RhoA and VEGFR1. The ADMET properties and drug-likeness of the bioactive compounds were studied using Molinspiration and ADMETlab 2.0. Docking studies revealed that Hecogenin (-8.4 and -10.3 kcal/mol), Neotigogenin (-7.7 and -9.8 kcal/mol), and Neohecogenin (-7.6 and -9.7 kcal/mol) produced the best docking results, showing the lowest binding energies for RhoA and VEGFR1, respectively. These energies were found to be comparable to the standard ligands Fasudil (-7.3 kcal/mol for RhoA) and Pazopanib (-8.0 kcal/mol for VEGFR1) for the selected targets. Moreover, Stigmasterol (-7.6 kcal/mol) and Genistein (-8.4 kcal/mol) showed a good binding affinity with RhoA and VEGFR1, respectively. The ADME properties of these molecules were also studied. Thus, the best-docked ligands mentioned above can be used as potential novel compounds against these two targets to develop therapeutics against ARDS. Further in-vitro and in-vivo experiments are required to cement these claims and prepare next-generation natural therapeutics for ARDS.

Molecular docking and dynamics simulation of farnesol as a potential anticancer agent targeting mTOR pathway.

Farnesol is a natural acyclic sesquiterpene alcohol, found in various essential oils such as, lemon grass, citronella, tuberose, neroli, and musk. It has a molecular mass of 222.372g/mol and chemical formula of C₁₅H₂₆O. The main objective of this study was to assess the effect of farnesol on mTOR and its two downstream effectors, p70S6K and eIF4E, which are implicated in the development of cancer, via molecular dynamic simulation, and docking analysis in an in silico study. A multilayer, primarily computer-based analysis was conducted to assess farnesol's anticancer potential, with a focus on primary cancer targets. From the calculations performed, farnesol showed a binding affinity of - 9.66kcal/mol, followed by binding affinity of - 7.4kcal/mol and - 7.8kcal/mol for mTOR, p70S6K and eIF4E respectively. Rapamycin showed the binding affinity of - 10.45kcal/mol for mTOR, for p70S6K and eIF4E the calculated binding affinity was - 10.65kcal/mol and 8.16kcal/mol respectively. The binding affinity of farnesol was comparable to the standard drug rapamycin indicating its potential as an mTOR inhibitor. Molecular dynamics simulations suggest that the ligands (farnesol and rapamycin) were well trapped within the active site of the protein over a time gap of 50 ns. It is clear that farnesol showed relatively stable MD simulation results, with minor fluctuations and maintains a consistent binding orientation, suggesting a strong and stable interaction with the target proteins when compared to simulation data of standard drug. This study explores the potential of farnesol as an anticancer agent through an in-silico approach, focusing on its interaction with mTOR and its downstream effectors. Inhibition of mTOR signaling pathway may be responsible for the anticancer effect of farnesol. As this pathway plays a crucial role in cell proliferation and survival, making it a significant target in cancer research.

Elevated α-1,2-mannosidase MAN1C1 in glioma stem cells and its implications for immunological changes and prognosis in glioma patients

Glioblastoma multiforme (GBM) is the most aggressive type of primary brain tumor, and the presence of glioma stem cells (GSCs) has been linked to its resistance to treatments and recurrence. Additionally, aberrant glycosylation has been implicated in the aggressiveness of cancers. However, the influence and underlying mechanism of N-glycosylation on the GSC phenotype and GBM malignancy remain elusive. Here, we performed an in-silico analysis approach on publicly available datasets to examine the function of N-glycosylation-related genes in GSCs and gliomas, accompanied by a qRT-PCR validation experiment. We found that high α-1,2-mannosidase MAN1C1 is associated with immunological functions and worse survival of glioma patients. Differential gene expression analysis and qRT-PCR validation revealed that MAN1C1 is highly expressed in GSCs. Furthermore, higher MAN1C1 expression predicts worse outcomes in glioma patients. Also, MAN1C1 expression is increased in the perinecrotic region of GBM and is associated with immunological and inflammatory functions, a hallmark of the GBM mesenchymal subtype. Further analysis confirmed that MAN1C1 expression is closely associated with infiltrating immune cells and disrupted immune response in the GBM microenvironment. These suggest that MAN1C1 is a potential biomarker for gliomas and may be important as an immunotherapeutic target for GBM.

Unveiling the therapeutic potential of Canavalia rosea leaves: Exploring antioxidant, anti-inflammatory, anti-arthritic, and cytotoxic activities through biological and molecular docking evaluation with DFT analysis

BackgroundCanavalia rosea is a common tropical seacoast flowering plant from the family of Fabaceae which is reported as bay bean and coastal jack bean; has a wide range of therapeutic and nutraceutical properties. AimThe present research aims to explore some pharmacological insights of the methanol extract C. rosea of leaves (MECR) and its chloroform fraction (CFCR) and n-hexane fraction (NFCR) through in-vitro and in-silico approaches. MethodsDifferent fractions of C. rosea were subjected to ferric reduction assay and total phenolic and flavonoid content assay to explore their antioxidant potential. The anti-inflammatory activity was assessed on the hypotonic-induced human erythrocyte-lysis model, while the protein denaturation method was applied for screening anti-arthritis properties of plant extract; and the cytotoxic activity was evaluated by brine shrimp lethality bioassay. In the in-silico study, molecular docking, pass prediction and ADME/T, analysis was used to investigate anti-arthritic, anti-inflammatory, antioxidant and cytotoxic potency of five selected compounds of C. rosea. Finally, the quantum chemical density functional test analysis was applied to investigate the chemical and physical properties of those compounds. ResultsAll the soluble organic extracts of C. rosea demonstrated moderate toxicity with strong antioxidants potential, in which MECR manifested the peak level of scavenging activity (2.49) on ferric reduction assay. MECR, CFCR & NFCR significantly protected lysis of human erythrocyte membrane induced by hypotonic solution, whereas MECR and CFCR were exhibited partially equal inhibitory activity. The in-vitro anti-arthritis assay, MECR, NFCR and CFCR showed strongly significant (p˂0.001) inhibitory potency at 500 μg/mL & 1000 μg/mL concentrations. The molecular docking simulations revealed strong binding of all compounds to specific receptors, with Rutin showing the highest biological reactivity followed by Daucosterol, β-Sitosterol, Stigmasterol, and Guanidine. All the compounds showed favorable reactivity patterns, with O and H atoms poised for nucleophilic and electrophilic attacks in chemical density functional calculations. ConclusionThe recent investigation suggests that C. rosea could have the potential source of antioxidant, anti-inflammatory, anti-arthritis and cytotoxic activity, prompting further investigation into their mechanisms.