Binding Affinity Score Research Articles

Elucidating Molecular Mechanism and Chemical Space of Chalcones through Knowledge Graph and Machine Learning: A Combined Bio-Cheminformatic Pipeline

We developed a bio-cheminformatics method, exploring disease inhibition mechanisms using machine learning-enhanced quantitative structure-activity relationship (ML-QSAR) models and knowledge-driven neural networks. ML-QSAR models were developed using molecular fingerprint descriptors and the Random Forest algorithm to explore the chemical spaces of Chalcones inhibitors against diverse disease properties, including antifungal, anti-inflammatory, anticancer, antimicrobial, and antiviral effects. We generated and validated robust machine learning-based bioactivity prediction models (https://github.com/RatulChemoinformatics/QSAR) for the top genes. These models underwent ROC and applicability domain analysis, followed by molecular docking studies to elucidate the molecular mechanisms of the molecules. Through comprehensive neural network analysis, crucial genes such as AKT1, HSP90AA1, SRC, and STAT3 were identified. The PubChem fingerprint-based model revealed key descriptors: PubchemFP521 for AKT1, PubchemFP180 for SRC, PubchemFP633 for HSP90AA1, and PubchemFP145 and PubchemFP338 for STAT3, consistently contributing to bioactivity across targets. Notably, chalcone derivatives demonstrated significant bioactivity against target genes, with compound RA1 displaying a predictive pIC50 value of 5.76 against HSP90AA1 and strong binding affinities across other targets. Compounds RA5 to RA7 also exhibited high binding affinity scores comparable to or exceeding existing drugs. These findings emphasize the importance of knowledge-based neural network-based research for developing effective drugs against diverse disease properties. These interactions warrant further in vitro and in vivo investigations to elucidate their potential in rational drug design. The presented models provide valuable insights for inhibitor design and hold promise for drug development. Future research will prioritize investigating these molecules for mycobacterium tuberculosis, enhancing the comprehension of effectiveness in addressing infectious diseases.

Comprehensive analysis of water and sediment from holy water body ‘Pokhri’ reveals presence of biomolecules that may educe skin, gastroenterological and neurological dysfunction

‘Pokhri mai’ refers to the natural pond amidst the hilly forest slopes of the Buxa tiger reserve (BTR) nearby Jayanti considered to be sacred by the local ethnic groups serving as the prime source of water for wild animals and occasionally by neighbouring inhabitants. However, the water body is designated to be noxious by a group of native people with no scientific validation. This paper focuses to explore its toxicity status and allied environmental concerns through Pokhri water and sediment sample analysis through physicochemical assessment, in vitro antioxidant assay, microbiological investigation followed by AAS, GC–MS and in silico study. pH of soil and water samples were found to be quite high (>6.8) with organic matter, carbon and available nitrogen content being 1.5308 ± 0.28 %, 0.89 ± 0.17 % and 0.072 ± 0.34 % respectively. Profuse microbial growths were observed in both sediment and water samples with consortia obtained exhibiting tolerance against a range of antifungals and antibiotics. Inhibition zone was absent for sediment consortium whereas consortium of water samples portrayed susceptibility against various heavy metals viz. Cu2+, Pb2+, Zn2+, Fe3+ and Al3+ salts with corresponding AAS quantified values of sediment samples being 133, 223.3, 86.8, 1449 and 481.5 ppm. A summative of 18 metabolites were identified by GC–MS in Pokhri lake sediment among which 13 (occupying 96.35 % peak area) were investigated to be potentially toxic with 2,4-Di-tert-butylphenol (53.38 %) as the major compound. Biomolecular characterization, ADMET test and molecular docking study with dermal, gastrointestinal and neural peptides exhibiting high binding affinity scores (ranging between −2.6 to −8.3 kcal/mol) further affirmed the toxicity attributes of the GC–MS deciphered molecules. The findings clearly justifies the local ‘myth’ of Pokhri water to be deleterious with prospective dermatotoxic, neurotoxic and being evident of gastrointestinal toxicity emphasizing ecological risk to the environment, wildlife and microflora of the adjoining forests.

In Silico and In Vivo Evaluation of Anti-Arthritic Effects of Bakuchiol from Psoralea corylifolia Seeds in Experimental Rat Model.

Rheumatoid arthritis is an autoimmune disease mainly affecting the joints categorized by inflammation, swelling of the synovium and decrease in the joint movement. Bakuchiol, a meroterpene class of natural product present in Psoralea corylifolia known to possess anti-inflammatory effects by a variety of mechanisms. However, its effects in rheumatoid arthritis still remain unclear. In the present investigation, we studied the anti-arthritic effects of bakuchiol via in silico and in vivo experiments. It also showed antioxidant effects measured using DPPH assay where it showed free radical scavenging activity with IC50 value 468.26 μg/ml. Molecular Docking studies carried out on COX-1 (PDB ID: 3 N8Z), COX-2 (PDB ID: 4PH9) and TNF-α (PDB ID: 7JRA), proteins involved in inflammation in arthritis. Bakuchiol showed the maximum binding affinity for TNF-α with binding affinity score is -7.29 kcal/moland less affinity was observed for COX-1 and 2. In vivo antiarthritic effects were studied in arthritic female wistar rats model prepared by intradermal injection of freund's complete adjuvant. Bakuchiol was administered orally at dose of 10,20 and 40 mg/kg for 21 days. Our treatment showed that bakuchiol at 20 and 40 mg/kg exhibited significant anti-inflammatory effects (p<0.001) showed by significant decrease in paw volume, paw diameter, spleen and thymus weight and increase in pain threshold and body weight in arthritic rat model. A significant decrease in hematological parameters such as total leukocyte count (TLC), platelet count, CRP and rheumatoid arthritis factor (RF) and increase in red blood cells count, ESR and hemoglobin further demonstrated that bakuchiol treatment suppresses the progression of adjuvant induced arthritis (AIA) in arthritic rat model. Histological analysis further revealed that bakuchiol ameliorates the pathological manifestations of AIA and reverse the abnormality induced by AIA in rats shown by protection against bone necrosis involved with low influx of inflammatory cells. Therefore, in silico and in vivo results revealed that bakuchiol has the potential to be developed as potent antiarthritic agent.

Pangenome analysis of five representative Tropheryma whipplei strains following multiepitope-based vaccine design via immunoinformatic approaches.

Whipple disease caused by Tropheryma whipplei a gram-positive bacterium is a systemic disorder that impacts not only the gastrointestinal tract but also the vascular system, joints, central nervous system, and cardiovascular system. Due to the lack of an approved vaccine, this study aimed to utilize immunoinformatic approaches to design multiepitope -based vaccine by utilizing the proteomes of five representative T. whipplei strains. The genomes initially comprised a total of 4,844 proteins ranging from 956 to 1012 proteins per strain. We collected 829 nonredundant lists of core proteins, that were shared among all the strains. Following subtractive proteomics, one extracellular protein, WP_033800108.1, a WhiB family transcriptional regulator, was selected for the chimeric-based multiepitope vaccine. Five immunodominant epitopes were retrieved from the WhiB family transcriptional regulator protein, indicating MHC-I and MHC-II with a global population coverage of 70.61%. The strong binding affinity, high solubility, nontoxicity, nonallergenic properties and high antigenicity scores make the selected epitopes more appropriate. Integration of the epitopes into a chimeric vaccine was carried out by applying appropriate adjuvant molecules and linkers, leading to the vaccine construct having enhanced immunogenicity and successfully eliciting both innate and adaptive immune responses. Moreover, the abilityof the vaccine to bind TLR4, a core innate immune receptor, was confirmed. Molecular dynamics simulations have also revealed the promising potential stability of the designed vaccine at 400 ns. In summary, we have designed a potential vaccine construct that has the ability not only to induce targeted immunogenicity for one strain but also for global T. whipplei strains. This study proposes a potential universal vaccine, reducing Whipple's disease risk and laying the groundwork for future research on multi-strain pathogens.

A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization (WHO) declared it as a global pandemic on 11th March, 2020. Many endeavors have been made to find appropriate medications to restrain the SARS CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating ADMET profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates against the SARS-CoV-2 main protease. The crystallized SARS-CoV-2 main protease structure was collected from the RCSB PDB database (PDB ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Out of 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as our top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. MD simulations disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but for experimental validation, they will require more in vivo trials.

Molecular Docking Studies of Synthesized Pyridazinone Scaffolds as Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs)

Pyridazinone derivatives, 6-aryl-pyridazinone (2a–f) and 2-(N-substituted)-6-aryl-pyridazinone (3a–h) derivatives were synthesized and assessed for cytotoxicity action using brine shrimp assessment method and in silico molecular studies. In silico molecular study of pyridazine derivatives used as NNRTIs and Doravirine is used as reference drug. The compounds were investigated for docking modes onto probable binding sites with HIV reverse transcriptase. The majority of these demonstrated favorable binding interactive connections with the active receptor domain. The majority of the compounds exhibited a remarkable docked binding affinity score when compared with the reference drugs. Among the synthesized pyridazine derivatives, compounds 3a and 3c–h exhibited a good docking score. For the designed compounds, in silico ADME assessment indicated the favorable physicochemical properties to be a suitable drug candidate. The synthesized compounds could serve as a novel alternative in designing safe and effective anti-HIV options with reverse transcriptase inhibitor potential. In the cytotoxicity study, all the compounds were evaluated at dose levels 10, and 20 (μg/mL), and potassium dichromate was used as a reference. Compounds 2c and 2e have shown potent lethality through LC50 2.23 and 3.20 μg respectively. Various compounds, including 2a, 2b, 2d, and 2f have demonstrated significant cytotoxicity. Their LC50 values are 7.58, 6.76, 8.91, and 4.46 μg, respectively. Additionally, compounds 3b and 3d exhibited potent lethality with LC50 values of 4.023 and 4.20 μg. Other compounds, namely 3g, 3f, 3c, 3h, 3a, and 3e, displayed noteworthy cytotoxicity ability13.91, 12.58, 11.91, 11.76, 10.58, 9.76, and 7.46 μg, respectively having LC50 values. This study supports the use of in silico molecular design and the brine shrimp bioassay as a suitable, reliable, and simple method for assessing the bioactivity of compounds. It provides further evidence for their use in medicine.

Network pharmacology combined with molecular docking and molecular dynamics to verify the therapeutic potential of mung beans (Vigna radiata) against prostate cancer

BackgroundProstate cancer is the most common oncological disease in men and one of leading causes of death worldwide. Growing evidence has demonstrated the effectiveness of mung bean bioactive compounds in suppressing various cancer cells. However, their effects and underlying mechanisms on prostate cancer have not been verified. The present study aimed to investigate the therapeutical effects and underlying mechanisms of mung bean compounds against prostate cancer.ResultsThe results revealed that 56 proteins related to prostate cancer could be modulated by mung bean, including several vital proteins of SRC (Sarcoma), Mitogen-Activated Protein Kinase 8 (MAPK8), Heat shock protein 90 kDa alpha member A1 (HSP90AA1), and Harvey Rat sarcoma virus (HRAS). It was also found that the potential pathways associated with prostate cancer pathogenesis comprising pyrimidine metabolism, nitrogen metabolism, and prolactin signaling pathways. Of 19 mung bean compounds docked to four key proteins reveal three promising compound (dulcinoside, peonidin-3-glucoside, and chlorogenic acid) with lower binding affinity score of − 7.7, − 12.2, − 9.0, and − 6.5 kcal/mol against SRC, MAPK8, HSP90AA1, and HRAS, respectively in their site of action. Dynamic simulation results also showed values of − 36.52 ± 2.93, − 35.93 ± 1.67, and − 35.77 ± 1.17 kJ/mol for Dulcinoside-SRC, Dulcinoside-MAPK8, and P3G-HSP90AA1 complexes, respectively. The binding of the compound occur in stable and flexible with the proteins. Moreover, all mung bean compounds predicted to have good ADMET properties.ConclusionsThe study concluded that dulcinoside, peonidin-3-glucoside, and chlorogenic acid potentially exhibited anticancer activity against prostate cancer in silico. Nevertheless, further studies such as in vitro and in vivo are needed to optimize and prove the efficacy of the mung brand and its compounds against prostate cancer.Graphical abstract

TC-DTA: Predicting Drug-Target Binding Affinity With Transformer and Convolutional Neural Networks.

Bioinformatics is a rapidly evolving field that applies computational methods to analyze and interpret biological data. A key task in bioinformatics is identifying novel drug-target interactions (DTIs), which plays a crucial role in drug discovery. Most computational approaches treat DTI prediction as a binary classification problem, determining whether drug-target pairs interact. However, with the growing availability of drug-target binding affinity data, this binary task can be reframed as a regression problem focused on drug-target affinity (DTA). DTA quantifies the strength of drug-target binding, offering more detailed insights than DTI and serving as a valuable tool for virtual screening in drug discovery. Accurately predicting compound interactions with targets can accelerate the drug development process. In this study, we introduce a deep learning model named TC-DTA for DTA prediction, leveraging convolutional neural networks (CNN) and the encoder module of the transformer architecture. We begin by extracting raw drug SMILES strings and protein amino acid sequences from the dataset, which are then represented using various encoding methods. Subsequently, we employ CNN and the transformer's encoder module to extract features from the drug SMILES strings and protein sequences, respectively. Finally, the feature information is concatenated and input into a multi-layer perceptron to predict binding affinity scores. We evaluated our model on two benchmark DTA datasets, Davis and KIBA, comparing it with methods such as KronRLS, SimBoost, and DeepDTA. Our model, TC-DTA, outperformed these baseline methods based on evaluation metrics like Mean Squared Error (MSE), Concordance Index (CI), and Regression towards the Mean Index ( rm2 ). These results highlight the effectiveness of the Transformer's encoder and CNN in extracting meaningful representations from sequences, thereby enhancing DTA prediction accuracy. This deep learning model can accelerate drug discovery by identifying drug candidates with high binding affinity to specific targets. Compared to traditional methods, machine learning technology offers a more effective and efficient approach to drug discovery.

Identification and molecular modelling of potential drugs targeting the genes involved in the progression of lung cancer in patients with idiopathic pulmonary fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is characterized by progressive fibrosis in the lung parenchyma. Given the fact that IPF patients are at significant risk of developing lung cancer (LC), the overlapping gene signatures between IPF and LC need to be explored. MethodsTwo datasets (GSE79544 and GSE103888) were procured from the Gene Expression Omnibus repository and used to determine the overlapping genes between IPF and LC. Next, the prediction ability of these genes in differentiating the diseased group from controls was explored using two machine learning (ML) models (random forest and k-nearest neighbor). Potential drugs targeting the candidate genes were identified, and advanced structural analysis was conducted to determine the binding affinity between the candidate drug and target receptor. ResultA total of ten common genes (CCL13, CXCL2, MALT1, MARCKS, PLA2G7, SEMA6B, SFTPB, SPARC, SPP1, and TLCD2) are differentially expressed in IPF and LC as compared to the controls. PLA2G7 demonstrated promising potential in differentiating between IPF, LC, and controls. The increased expression correlated with poor survival in patients with LC. The expression of PLA2G7 indicated a similar trend in the validation dataset. Darapladib, a selective inhibitor that belongs to toxicity class 4 and lethal dose50 value of 800 mg/kg exhibited maximum potential in targeting PLA2G7 with a binding affinity score of −9.2 kcal/mol (chain A) and −9.3 kcal/mol (chain B), respectively. ConclusionThe present study is the first of its kind that combines in-silico and ML algorithms to identify the gene signatures and promising drugs for treating the progression of LC in patients with IPF.

Pharmacological insights into Laurus nobilis: HPLC profiling and evaluation of its anti-Toxoplasma, antioxidant, and anti-hemolytic properties

Toxoplasma gondii (T. gondii) poses significant risks, especially to those with weakened immune systems, highlighting the need for new, less toxic treatments. Laurus nobilis L. (L. nobilis), known for its beneficial properties including antiparasitic and antioxidant effects, offers potential for innovative therapies. This study assessed the anti-Toxoplasma, cytotoxic, antioxidant, and anti-hemolytic effects of L. nobilis's aqueous and ethanolic extracts both in vitro and in silico, including a phytochemical analysis. HPLC analysis identified a range of phenolic compounds, notably syringic acid, ferulic acid, gallic acid, caffeine, and quercetin. Both extracts exhibited an inhibitory effect on the growth of T. gondii tachyzoites in vitro and caused less cytotoxicity to host cells. In silico studies revealed that rutin and quercetin were the most potent compounds, with binding affinity scores for the DHFR enzyme of −10.6 and −9.3 kcal/mol, respectively. Antioxidant studies demonstrated that both extracts displayed antioxidant effects in the DPPH•, ABTS•+, NO•, β-carotene-linoleic acid system, FRP, and TAC assays. Additionally, they provided significant protection to erythrocytes against H2O2-induced hemolysis. These findings, suggests that L. nobilis exhibits significant potential as a source of therapeutic agents for combating T. gondii infection and managing its associated adverse effects.

Novel Insights into the Antimicrobial and Antibiofilm Activity of Pyrroloquinoline Quinone (PQQ); In Vitro, In Silico, and Shotgun Proteomic Studies.

Microbial infections pose a significant global health threat, affecting millions of individuals and leading to substantial mortality rates. The increasing resistance of microorganisms to conventional treatments requires the development of novel antimicrobial agents. Pyrroloquinoline quinone (PQQ), a natural medicinal drug involved in various cellular processes, holds promise as a potential antimicrobial agent. In the present study, our aim was, for the first time, to explore the antimicrobial activity of PQQ against 29 pathogenic microbes, including 13 fungal strains, 8 Gram-positive bacteria, and 8 Gram-negative bacteria. Our findings revealed potent antifungal properties of PQQ, particularly against Syncephalastrum racemosum, Talaromyces marneffei, Candida lipolytica, and Trichophyton rubrum. The MIC values varied between fungal strains, and T. marneffei exhibited a lower MIC, indicating a greater susceptibility to PQQ. In addition, PQQ exhibited notable antibacterial activity against Gram-positive and -negative bacteria, with a prominent inhibition observed against Staphylococcus epidermidis, Proteus vulgaris, and MRSA strains. Remarkably, PQQ demonstrated considerable biofilm inhibition against the MRSA, S. epidermidis, and P. vulgaris strains. Transmission electron microscopy (TEM) studies revealed that PQQ caused structural damage and disrupted cell metabolism in bacterial cells, leading to aberrant morphology, compromised cell membrane integrity, and leakage of cytoplasmic contents. These findings were further affirmed by shotgun proteomic analysis, which revealed that PQQ targets several important cellular processes in bacteria, including membrane proteins, ATP metabolic processes, DNA repair processes, metal-binding proteins, and stress response. Finally, detailed molecular modeling investigations indicated that PQQ exhibits a substantial binding affinity score for key microbial targets, including the mannoprotein Mp1P, the transcriptional regulator TcaR, and the endonuclease PvuRTs1I. Taken together, our study underscores the effectiveness of PQQ as a broad-spectrum antimicrobial agent capable of combating pathogenic fungi and bacteria, while also inhibiting biofilm formation and targeting several critical biological processes, making it a promising therapeutic option for biofilm-related infections.

Repurposing FDA approved drugs against Sterol C-24 methyltransferase of Leishmania donovani: A dual in silico and in vitro approach

Leishmaniasis is a disease caused by the parasite Leishmania donovani affecting populations belonging to developing countries. The present study explores drug repurposing as an innovative strategy to identify new uses for approved clinical drugs, reducing the time and cost required for drug discovery. The three-dimensional structure of Leishmania donovani Sterol C-24 methyltransferase (LdSMT) was modeled and 1615 FDA-approved drugs from the ZINC database were computationally screened to identify the potent leads. Fulvestrant, docetaxel, indocyanine green, and iohexol were shortlisted as potential leads with the highest binding affinity and fitness scores for the concerned pathogenic receptor. Molecular dynamic simulation studies showed that the macromolecular complexes of indocyanine green and iohexol with LdSMT remained stable throughout the simulation and can be further evaluated experimentally for developing an effective drug. The proposed leads have further demonstrated promising safety profiles during cytotoxicity analysis on the J774.A1 macrophage cell line. Mechanistic analysis with these two drugs also revealed significant morphological alterations in the parasite, along with reduced intracellular parasitic load. Overall, this study demonstrates the potential of drug repurposing in identifying new treatments for leishmaniasis and other diseases affecting developing countries, highlighting the importance of considering approved clinical drugs for new applications.

Differential Interactions of Flavonoids with the Aryl Hydrocarbon Receptor In Silico and Their Impact on Receptor Activity In Vitro.

The molecular mechanisms underlying the observed anticancer effects of flavonoids remain unclear. Increasing evidence shows that the aryl hydrocarbon receptor (AHR) plays a crucial role in neoplastic disease progression, establishing it as a potential drug target. This study evaluated the potential of hydroxy flavonoids, known for their anticancer properties, to interact with AHR, both in silico and in vitro, aiming to understand the mechanisms of action and identify selective AHR modulators. A PAS-B domain homology model was constructed to evaluate in silico interactions of chrysin, naringenin, quercetin apigenin and agathisflavone. The EROD activity assay measured the effects of flavonoids on AHR's activity in human breast cancer cells (MCF7). Simulations showed that chrysin, apigenin, naringenin, and quercetin have the highest AHR binding affinity scores (-13.14 to -15.31), while agathisflavone showed low scores (-0.57 and -5.14). All tested flavonoids had the potential to inhibit AHR activity in a dose-dependent manner in the presence of an agonist (TCDD) in vitro. This study elucidates the distinct modulatory effects of flavonoids on AHR, emphasizing naringenin's newly described antagonistic potential. It underscores the importance of understanding flavonoid's molecular mechanisms, which is crucial for developing novel cancer therapies based on these molecules.

Exploring the Therapeutic Potential of Petiveria alliacea L. Phytochemicals: A Computational Study on Inhibiting SARS-CoV-2's Main Protease (Mpro).

The outbreak of SARS-CoV-2, also known as the COVID-19 pandemic, is still a critical risk factor for both human life and the global economy. Although, several promising therapies have been introduced in the literature to inhibit SARS-CoV-2, most of them are synthetic drugs that may have some adverse effects on the human body. Therefore, the main objective of this study was to carry out an in-silico investigation into the medicinal properties of Petiveria alliacea L. (P. alliacea L.)-mediated phytocompounds for the treatment of SARS-CoV-2 infections since phytochemicals have fewer adverse effects compared to synthetic drugs. To explore potential phytocompounds from P. alliacea L. as candidate drug molecules, we selected the infection-causing main protease (Mpro) of SARS-CoV-2 as the receptor protein. The molecular docking analysis of these receptor proteins with the different phytocompounds of P. alliacea L. was performed using AutoDock Vina. Then, we selected the three top-ranked phytocompounds (myricitrin, engeletin, and astilbin) as the candidate drug molecules based on their highest binding affinity scores of -8.9, -8.7 and -8.3 (Kcal/mol), respectively. Then, a 100 ns molecular dynamics (MD) simulation study was performed for their complexes with Mpro using YASARA software, computed RMSD, RMSF, PCA, DCCM, MM/PBSA, and free energy landscape (FEL), and found their almost stable binding performance. In addition, biological activity, ADME/T, DFT, and drug-likeness analyses exhibited the suitable pharmacokinetics properties of the selected phytocompounds. Therefore, the results of this study might be a useful resource for formulating a safe treatment plan for SARS-CoV-2 infections after experimental validation in wet-lab and clinical trials.

Exploring the phytochemical profile and therapeutic investigations on Moringa concanensis Nimmo pod husk extracts: An integrated in vitro and in silico approach

The present study aimed to determine the chemical profiling, antidiabetic, antioxidant, and antibacterial activity of Moringa concanensis pod husk (MCPH) by in vitro and in silico methods. Phytochemical analysis displayed significant ratios of secondary metabolites in all the extracts MPCH. Major compounds recorded during chemical profiling are 2,5-dimethylfuran-3,4(2H,5H)-dione (19.2%), oleic acid (13.4%) and campesterol (9%), pyranone (5.7%), monomethyl succinate (5.7%), and 1,2-cyclopentanedione (5.4%). In vitro pharmacological studies revealed that methanolic extract of MCPH had a significant effect on α-amylase (IC50 of 78.98 ± 0.58 μg/mL), α-glucosidase (IC50 of 40.80 ± 0.53 μg/mL) enzyme inhibition assays and antioxidant (IC50 of 54.60 ± 0.5 μg/mL for NO) activity. Antibacterial activity was evaluated against various bacterial strains and the ethyl acetate (MIC of 59.30 μg/mL), methanol (MIC of 14.84 μg/mL) and aqueous (MIC of 118.70 μg/mL) extracts of MCPH possessed potent inhibition effect against all the tested bacteria. Molecular docking investigation revealed that α-tocopherol acetate, palmitone, α-tocopherol, oleamide, β-sitosterol, and heptagonal had maximum binding affinity and docking score for all enzyme targets studied. Simulation studies indicate that α-tocopherol acetate could potentially be used as an activator to manage the enzymatic activity of α-amylase. The results showed that Moringa concanensis pod husk extracts are potential biological source of myriad phytoconstituents with pharmacological properties that can be further regulated for the discovery of novel drugs for the mankind.

Unveiling the molecular basis of paracetamol-induced hepatotoxicity: Interaction of N-acetyl-p-benzoquinone imine with mitochondrial succinate dehydrogenase

Background and aimN-acetyl-p-benzoquinoneimine (NAPQI), a toxic byproduct of paracetamol (Acetaminophen, APAP), can accumulate and cause liver damage by depleting glutathione and forming protein adducts in the mitochondria. These adducts disrupt the respiratory chain, increasing superoxide production and reducing ATP. The goal of this study was to provide computational proof that succinate dehydrogenase (SDH), a subunit of complex II in the mitochondrial respiratory chain, is a favorable binding partner for NAPQI in this regard. MethodMolecular docking, molecular dynamics simulation, protein-protein interaction networks (PPI), and KEGG metabolic pathway analysis were employed to identify binding characteristics, interaction partners, and their associations with metabolic pathways. A lipid membrane was added to the experimental apparatus to mimic the natural cellular environment of SDH. This modification made it possible to develop a context for investigating the role and interactions of SDH within a cellular ecosystem that was more realistic and biologically relevant. ResultThe molecular binding affinity score for APAP and NAPQI with SDH was predicted −6.5 and −6.7 kcal/mol, respectively. Furthermore, RMSD, RMSF, and Rog from the molecular dynamics simulations study revealed that NAPQI has slightly higher stability and compactness compared to APAP at 100 ns timeframe with mitochondrial SDH. ConclusionThis study serves to predict the mechanistic process of paracetamol toxicity by using different computational approaches. In addition, this study will provide information about the drug target against APAP hepatotoxicity.

In silico Assessment of Efficacy Against the Zoonotic Parasite Echinococcus granulosus, Pharmacokinetic and Toxicity Predictions for the Siddha Formulation Murukkanvithai Mathirai

Background: Thioredoxin glutathione reductase (TGR) is essential for survival of the zoonotic tapeworm Echinococcus granulosus. Albendazole is the only promising drug for the treatment of cystic echinococcosis. To avoid the development of resistance to albendazole in the parasite, an herbal alternative to albendazole is the need-of-the-hour to combat the development of resistance. Aim: This study aimed to identify active compounds against the parasite Echinococcus granulosus from Murukkan Vithai Mathirai, an anthelmintic formulation used in Siddha practice. Objectives: To evaluate the efficacy of Murukkan Vithai Mathirai (MVM), a Siddha formulation against Echinococcus granulosus, a tapeworm of carnivores, by molecular docking, and to evaluate its ADMET properties using in silico tools. Materials and Methods: The 3D structure of Echinococcus granulosus-thioredoxin-glutathione systems (egTGR) and the phytoconstituents of Piper nigrum, Zingiber officinalis, Piper longum, Cuminum syminum, Coptis teeta, Butea monosperma, and Croton tiglium were obtained from a curated database of Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT). 12 promising phytocompounds were selected based on their physicochemical properties, drug-likeness, bioavailability scores, and medicinal chemistry properties. These phytochemicals were docked individually with the egTGR using Autodock vina and binding affinity (kcal/mol) was recorded for each compound and compared with albendazole, a positive control drug. The results of docking were read using the Biovia Discovery studio visualizer. The ADMET properties of the phytochemicals were analysed using pkCSM and VEGA-QSAR tools. The toxicity score for each phytochemical was calculated by assigning weightage to the toxicities predicted and the weighted average was calculated to compare with the albendazole's weighted average. The geometric mean of NOAELs predicted for MVM phytochemicals was compared with the predicted NOAEL of albendazole. Results: The binding affinity (G) scores of the selected phytocompounds were found to be higher than the albendazole and the phytocompounds with G &gt; -8.0 are as follows, aristolodione, berberastine and pluviatilol of Piper longum, apigenin of Cuminum syminum and prunetin of Butea monosperma, whereas the G of albendazole was -6.7. The calculated toxicity score for MVM (0.56) was significantly lower than albendazole (1.08) and the predicted NOAELs was significantly higher (26.63 mg/kg) than albendazole (3.49), indicating that MVM is less toxic than albendazole. Conclusion: Murukkan Vithai Mathirai is a promising and safe anthelmintic in in silico studies, however, it needs to be validated by in vitro and in vivo studies.

Computational study demonstrated anti-diabetic potencies of Diosgenin and Multiflorenol as peroxisome proliferator-activated receptor gamma agonist

The prevalence of diabetes mellitus continues to rise on a global basis, making this entity one of the most pressing issues facing public health nowadays. Generally, diabetes mellitus is characterized by increased blood sugar levels caused by insulin secretion or action abnormalities. Natural products have become more popular in treating various types of diseases, including diabetes mellitus, due to their minimal adverse effects. Promoting the peroxisome proliferator-activated receptor γ (PPARG) activation is an anti-diabetic strategy due to its biological function for adipocyte storage, mobilization, differentiation, and insulin sensitivity. This study aims to evaluate diosgenin and multiflorenol in silico as anti-diabetic drug candidates by targeting PPARG. Several analyses, such as molecular docking, protein target prediction, biological function prediction, protein-protein interaction, and pharmacokinetics analyses were carried out in this study. Computational prediction showed PPARG have involved in several activities, such as fat cell differentiation, fatty acid oxidation, fatty acid transport, and cellular response to fatty acid. The binding affinity score revealed that diosgenin and multiflorenol have a higher value than the control drug. Other characteristics, such as chemical interaction, amino acid residues, and physicochemical properties, demonstrated supportive drug development outcomes. Therefore, based on our findings, we suggested that diosgenin and multiflorenol, both of which target PPARG, would hold promise as potential candidates for an anti-diabetic drug.

Rational design of MIPs for the detection of Myxovirus resistance protein A (MxA), a biomarker for viral infection

Accurate diagnosis is crucial for effective patient care and the containment of antimicrobial resistance outbreaks. The intricate challenge of distinguishing bacterial from viral infections, coupled with limited diagnostic tools and overlapping symptoms has driven the utilization of molecular imprinting techniques. This study focuses on developing cost-effective, chemically stable antibody analogs for the interferon-induced protein myxovirus resistance protein A (MxA). MxA is an intracellular, cytoplasmic GTPase having activity against a wide range of viruses and serves as a distinctive biomarker for viral infections. We utilized computational design to guide the polymer assembly, centering on epitope imprinting to target MxA-specific regions crucial for interaction. Molecular docking calculations, alongside a pioneering multi-monomer simultaneous docking (MMSD) protocol, efficiently elucidate cooperativity during pre-polymerization. Monomer binding affinity scores, such as for APTMS, exhibited notable increase, ranging from −3.11 to −13.03 kcal/mol across various MMSD combinations compared to a maximum of −2.78 kcal/mol in single monomer docking, highlighting the capacity of MMSD in elucidating crucial monomer-monomer interactions. This computational approach provides a theoretical alternative to labor-intensive experimental optimization, streamlining the development process for synthetic receptors. Simulations reveal unique interactions enhancing MIP-peptide complementarity, yielding optimized receptors selectively binding to MxA epitopes. The obtained MIPs demonstrated a maximum adsorption capacity of approximately 12 mg/g and captured 1.6 times more epitope and 2.6 times more epitope containing MxA protein than corresponding NIPs. A proof-of-concept study demonstrates MxA protein binding to synthetic receptors, highlighting the potential of MIPs, analogous to antibodies, in overcoming current diagnostic challenges for precise detection of viral infection.

Metabolomic Profiling of Leptadenia reticulata: Unveiling Therapeutic Potential for Inflammatory Diseases through Network Pharmacology and Docking Studies.

Medicinal plants have been utilized since ancient times for their therapeutic properties, offering potential solutions for various ailments, including epidemics. Among these, Leptadenia reticulata, a member of the Asclepiadaceae family, has been traditionally employed to address numerous conditions such as diarrhea, cancer, and fever. In this study, employing HR-LCMS/MS(Q-TOF) analysis, we identified 113 compounds from the methanolic extract of L. reticulata. Utilizing Lipinski's rule of five, we evaluated the drug-likeness of these compounds using SwissADME and ProTox II. SwissTarget Prediction facilitated the identification of potential inflammatory targets, and these targets were discerned through the Genecard, TTD, and CTD databases. A network pharmacology analysis unveiled hub proteins including CCR2, ICAM1, KIT, MPO, NOS2, and STAT3. Molecular docking studies identified various constituents of L. reticulata, exhibiting high binding affinity scores. Further investigations involving in vivo testing and genomic analyses of metabolite-encoding genes will be pivotal in developing efficacious natural-source drugs. Additionally, the potential of molecular dynamics simulations warrants exploration, offering insights into the dynamic behavior of protein-compound interactions and guiding the design of novel therapeutics.