In-silico Approach Research Articles

Potential Inhibitor of DENV-2 Virus Protease (NS2B-NS3): An In-Silico Studies of Anti-Viral Plants

Dengue virus (DENV) is a mosquito-borne pathogen that affects millions of people worldwide. The DENV-2 protease is a vital enzyme responsible for viral replication and is a promising target for antiviral therapy. The objective of the study is to identify potential inhibitors of DENV-2 protease using In-Silico approaches with phytocompounds from ten antiviral plants. Initially, 133 phytoconstituents were collected with anti-dengue properties from previously reported studies which were virtually screened using SWISS ADME for ADME properties. The DENV-2 protease structure (2FOM) was obtained from the Protein Data Bank and molecular docking was performed using AutoDock Vina. The best-scoring compounds were evaluated and top five potential inhibitors with high binding affinity and stability were selected. The top-scoring compounds were Ligand-91 (Terchebin, -8.1 kcal/mol), Ligand-13 (7-desacetyl-7-benzoylgedunin, -7.8 kcal/mol), Ligand-100 (Triterpenoid, -7.8 kcal/mol), Ligand-12 (7-desacetyl-7-benzoylazadiradione, -7.7 kcal/mol), Ligand-20 (Azadirolic acid, -7.7 kcal/mol), Ref.1 (Doxycycline, -6.6 kcal/mol), Ref.2(Monosdenvir, -7.5 kcal/mol), and Ref.3 (Zanamivir, -5.6 kcal/mol). The result of the study shows that 7-desacetyl-7-benzoylazadiradione and 7-desacetyl-7-benzoylgeduninas compounds with high binding affinity for the target protein. These compounds are found in Azadirachta indica making it a promising candidate for further experimental validation and development of antiviral agents against DENV-2. Keywords: Molecular docking, Anti-dengue, Anti-viral, ADME analysis

Targeting mitochondrial dynamics: an in-silico approach for repurposing antifungal drugs in OSCC treatment

Drug repurposing for cancer treatment is a valuable strategy to identify existing drugs with known safety profiles that could combat the neoplasm, by reducing costs. Oral squamous cell carcinoma, an ulcer-proliferative lesion on the mucosal epithelium, is the most common oral malignancy. About 10% of cancer patients within the Indian subcontinent suffer from OSCC, primarily due to chewing of betel plant derivatives. Concomitant administration of the chemotherapeutic agent (Cisplatin/Paclitaxel) is the treatment of choice. Analysis of the oral mycobiome of OSCC patients has projected the role of Candida albicans in potentiating OSCC. Hence, repurposing antifungal drugs emerges as a promising approach, as these drugs could target both the cancer cells and the infection. Cancer cells often have heightened energy requirements, and targeting mitochondrial proteins to disrupt mitochondrial division and induce dysfunction contributing to cell death, offers a method for treating OSCC. We identified 18 mitochondrial targets playing a crucial role in the maintenance of mitochondrial homeostasis. They were docked against 125 antifungal ligand molecules sourced from PUBCHEM. Ligand profiling was performed using Lipinski’s rule of 5, SwissADME and ProTox. Also, molecular dynamics and MM-PBSA were performed to validate our results. Among all protein ligand interactions, we observed that targeting DRP1 with itraconazole yielded superior binding and stability. Overall, lower toxicity and thumping ADME properties solidified the choice of ligand. We hope this experimental approach will enable us to provide a basis for selecting a lead molecule for a possible novel nano-formulation and validate our finding through in-vitro cell line-based testing.

Probing the interactions of genistein with HMGB1 through multi-spectroscopic and in-silico approaches

Probing the interactions of genistein with HMGB1 through multi-spectroscopic and in-silico approaches

Biosynthesis, characterization, and In-Vitro Anticancer effect of Plant-Mediated Silver Nanoparticles using Acalypha Indica Linn: In-Silico Approach

Biosynthesis, characterization, and In-Vitro Anticancer effect of Plant-Mediated Silver Nanoparticles using Acalypha Indica Linn: In-Silico Approach

Influence of Cataract Causing Mutations on αA-Crystallin: A Computational Approach.

The αA-crystallin protein plays a vital role in maintaining the refractive index and transparency of the eye lens. Significant clinical studies have emerged as the αA-crystallin is prone to aggregation, resulting in the formation of cataracts with varied etiologies due to mutations. This work aims to comprehend the structural and functional role of cataract-causing mutations in αA-crystallin, particularly at N-Terminal and α-Crystallin Domains, using in-silico approaches including molecular dynamics simulation. About 19 mutants of αA-crystallin along with native structure were simulated for 100 ns and the post-simulations analyses reveal pronounced dynamics of αA-crystallin due to the enhanced structure flexibility as its native compactness was lost and is witnessed mainly by the mutants R12L, R21L, R21Q, R54L, R65Q, R116C and R116H. It is observed that αA-crystallin discloses the NTD motions as the dominant one and the same was endorsed by the linear variation between Rg and the center-of-mass of αA-crystallin. Interestingly, such enhanced dynamics of αA-crystallin mutants associated with the structure flexibility is internally modulated by the dynamic exchange of secondary structure elements β-sheets and coils (R2 = 0.619) during simulation. Besides, the observed pronounced dynamics of dimer interface region (β3-L6-β4 segment) of ACD along with CTD dynamics also gains importance. Particularly, the highly dynamic mutants are also characterized by enhanced non-covalent and hydrophobic interactions which renders detrimental effects towards its stability, and favours possible protein unfolding mechanisms. Overall, this study highlights the mutation-mediated structural distortions in αA-crystallin and demands the need for further potential development of inhibitors against cataract formation.

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.

Deciphering Plasmodium Condensin Core Subunits of Structural Maintenance of Chromosomes 2 (SMC2) as a Putative Drug Target for Antimalarial Drug

Background: The structural maintenance of chromosomes (SMC) proteins plays a noteworthy role in chromosome dynamics. Several recent studies reported that the condensin core subunits of structural maintenance of chromosomes 2 (SMC2) play important roles in the atypical mitosis of the Plasmodium life cycle and may perform different functions during different proliferative stages. For eukaryotes, the structural maintenance of chromosomes (SMC) proteins are divided into six subunits and form three heterodimers of structural maintenance of chromosomes (SMC1/3) cohesion complex, structural maintenance of chromosomes (SMC2/4) condensin complex, and structural maintenance of chromosomes (SMC5/6) complex for chromosome cohesion, condensation, and DNA damage repair, respectively. Objective: The objective of this study was to investigate the structural maintenance of chromosomes 2 (SMC2) protein of P. falciparum as a putative drug target of malariacausing Plasmodium falciparum. Methods: In this study, we investigated the structural maintenance of chromosomes 2 (SMC2) protein of P. falciparum as a putative drug target of malaria-causing P. falciparum by using in-silico approaches like Homology modeling, in-silico evaluation of the modeled structure, molecular docking study to investigate the interaction of receptor-ligand, and molecular dynamic simulation study with MM calculation. Results: We reported the structural maintenance of chromosomes 2 (SMC2) protein of P. falciparum as a potent drug target that can pave the way for novel drug discovery to mitigate malaria. Conclusion: In-silico-based studies play a significant role in understanding any protein for potential drug development.

Evaluation of Rhus Tox, a homeopathic formulation for treatment of Parkinson’s and Alzheimer’s disease: a network pharmacology and ex-vivo approach

Rhus toxicodendron, commonly known as Rhus tox, is a potent homeopathic medication widely used in the treatment of rheumatoid arthritis and is claimed to have potential benefits for neurodegenerative disorders. Given the ability of homeopathic medications to address the root causes of diseases, our study aimed to evaluate Rhus tox for Parkinson’s Disease (PD) and Alzheimer’s Disease (AD) using in-silico, ex-vivo, and network pharmacology approaches to obtain comprehensive information on its multi-component and multi-target effects. Phytoconstituents of Rhus tox were collected from PubMed and screened for ADMET properties. Targets for these constituents were predicted using the Binding Database and DisGeNET, resulting in 61 targets for Parkinsonism and 85 targets for alzhiemer’s disease. Protein-protein interactions (PPIs) were analysed using the STRING database. A Venn diagram was constructed for all these targets, and 5 out of 13 common targets were selected for docking studies. From these analyses, kaempferol and quercetin were identified as promising neuroprotective agents with good blood-brain barrier (BBB) permeation. The docking studies validated these predictions as most of the constituents showed good binding affinity with EGFR, SNCA and MAO-B. It was further validated using MAO inhibition assay, in which Quercetin was found to be highly efficacious, with an IC50 value of 32.69 μg/mL among the other flavonoids studied for MAO inhibition assay. The Rhus Tox also showed MAO inhibition assay similar to the standard seligiline. To conclude, we can propose that Rhus Tox primarily acts on the dopaminergic pathway, serotonergic pathway, and EGFR signaling pathway. Further in vitro and in vivo studies are needed to confirm the mechanism action and efficacy of Rhus Tox for treatment of neurodegenerative diseases.

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.