• CELLMED
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• v.3 no.2
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• pp.12.1-12.4
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• 2013

Identification of target protein is an important procedure in the course of drug discovery. Because of complexity, action mechanisms of herbal medicine are rather obscure, unlike small-molecular drugs. Inverse docking simulation is a reverse use of molecular docking involving multiple target searches for known chemical structure. This methodology can be applied in the field of target fishing and toxicity prediction for herbal compounds as well as known drug molecules. The aim of this review is to introduce a series of in silico works for predicting potential drug targets and side-effects based on inverse docking simulations.

• Bulletin of the Korean Chemical Society
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• v.29 no.8
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• pp.1479-1484
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• 2008

Protein tyrosine phosphatase (PTP) 1B is the superfamily of PTPs and a negative regulator of multiple receptor tyrosine kinases (RTKs). Inhibition of protein tyrosine phosphatase 1B (PTP1B) has been proposed as a strategy for the treatment of type 2 diabetes and obesity. Recently, it has been reported that amentoflavone, a biflavonoid extracted from Selaginella tamariscina, inhibited PTP1B. In the present study, docking model between amentoflavone and PTP1B was determined using automated docking study. Based on this docking model and the interactions between the known inhibitors and PTP1B, we determined multiple pharmacophore maps which consisted of five features, two hydrogen bonding acceptors, two hydrogen bonding donors, and one lipophilic. Using receptor-oriented pharmacophore-based in silico screening, we searched the biflavonoid database including 40 naturally occurring biflavonoids. From these results, it can be proposed that two biflavonoids, sumaflavone and tetrahydroamentoflavone can be potent allosteric inhibitors, and the linkage at 5',8''-position of two flavones and a hydroxyl group at 4'-position are the critical factors for their allosteric inhibition. This study will be helpful to understand the mechanism of allosteric inhibition of PTP1B by biflavonoids and give insights to develop potent inhibitors of PTP1B.

• Natural Product Sciences
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• v.27 no.2
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• pp.99-114
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• 2021

Type 2 diabetes mellitus (T2DM) and its complications are important noncommunicable diseases with high mortality rates. Protein tyrosine phosphatase 1B (PTP1B) and aldose reductase inhibitors are recently approached and advanced for T2DM and its complications therapy. Matricaria chamomilla L. is acknowledged as a worldwide medicinal herb that has many beneficial health effects as well as antidiabetic effects. Our research was designed to determine the most potential antidiabetic phytochemicals from M. chamomilla employing in silico study. 142 phytochemicals were obtained from the databases. The first screening employed iGEMdock and Swiss ADME, involving 93 phytochemicals. Finally, 30 best phytochemicals were docked. Molecular docking and visualization analysis were performed using Avogadro, AutoDock 4.2., and Biovia Discovery Studio 2016. Molecular docking results demonstrate that ligand-protein interaction's binding affinities were -5.16 to -7.54 kcal/mol and -5.30 to -12.10 kcal/mol for PTP1B and aldose reductase protein targets respectively. In silico results demonstrate that M. chamomilla has potential antidiabetic phytochemical compounds for T2DM and its complications. We recommended anthecotulide, quercetin, chlorogenic acid, luteolin, and catechin as antidiabetic agents due to their binding affinities against both PTP1B and aldose reductase protein. Those phytochemicals' significant efficacy and potential as antidiabetic must be investigated in further advanced research.

• Biomolecules & Therapeutics
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• v.29 no.5
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• pp.519-526
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• 2021

In a search for effective PPAR-γ agonists, 110 clinical drugs were screened via molecular docking, and 9 drugs, including parecoxib, were selected for subsequent biological evaluation. Molecular docking of parecoxib to the ligand-binding domain of PPAR-γ showed high binding affinity and relevant binding conformation compared with the PPAR-γ ligand/antidiabetic drug rosiglitazone. Per the docking result, parecoxib showed the best PPAR-γ transactivation in Ac2F rat liver cells. Further docking simulation and a luciferase assay suggested parecoxib would be a selective (and partial) PPAR-γ agonist. PPAR-γ activation by parecoxib induced adipocyte differentiation in 3T3-L1 murine preadipocytes. Parecoxib promoted adipogenesis in a dose-dependent manner and enhanced the expression of adipogenesis transcription factors PPAR-γ, C/EBPα, and C/EBPβ. These data indicated that parecoxib might be utilized as a partial PPAR-γ agonist for drug repositioning study.

• Genomics & Informatics
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• v.13 no.2
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• pp.60-67
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• 2015

The leading cause of cancer mortality globally amongst the women is due to human papillomavirus (HPV) infection. There is need to explore anti-cancerous drugs against this life-threatening infection. Traditionally, different natural compounds such as withaferin A, artemisinin, ursolic acid, ferulic acid, (-)-epigallocatechin-3-gallate, berberin, resveratrol, jaceosidin, curcumin, gingerol, indol-3-carbinol, and silymarin have been used as hopeful source of cancer treatment. These natural inhibitors have been shown to block HPV infection by different researchers. In the present study, we explored these natural compounds against E6 oncoprotein of high risk HPV18, which is known to inactivate tumor suppressor p53 protein. E6, a high throughput protein model of HPV18, was predicted to anticipate the interaction mechanism of E6 oncoprotein with these natural inhibitors using structure-based drug designing approach. Docking analysis showed the interaction of these natural inhibitors with p53 binding site of E6 protein residues 108-117 (CQKPLNPAEK) and help reinstatement of normal p53 functioning. Further, docking analysis besides helping in silico validations of natural compounds also helped elucidating the molecular mechanism of inhibition of HPV oncoproteins.

• Bulletin of the Korean Chemical Society
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• v.31 no.8
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• pp.2147-2150
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• 2010

c-Jun N-terminal kinase 1 (JNK1) is involved in apoptosis, cell differentiation and proliferation. It has been reported that a flavonol, quercetin, induces cell apoptosis and JNK inhibition. In order to understand the interactions of quercetin and JNK1, we performed receptor-oriented pharmacophore based in silico screening and determined a binding model of human JNK1 and quercetin at the ATP binding site of JNK1. 5-OH of A-ring and carbonyl oxygen of C-ring of quercetin participated in hydrogen bonding interactions with backbone of E109 and M111. Additionally, 3'-OH of quercetin formed a hydrogen bond with backbone of I32. One hydrophobic interaction is related on the binding of quercetin to JNK1 with I32, N114, and V158. Based on this model, we conducted a docking study with other 8 flavonols to find possible flavonoids inhibitors of JNK1. We proposed that one flavonols, rhamnetin, can be a potent inhibitor of JNK and 5-OH of A-ring and 3'-OH of B-ring of flavonols are the essential features for JNK1 inhibition.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.113-124
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• 2024

Background: The increasing need to minimize animal testing has sparked interest in alternative methods with more humane, cost-effective, and time-saving attributes. In particular, in silico-based computational toxicology is gaining prominence. Adverse outcome pathway (AOP) is a biological map depicting toxicological mechanisms, composed of molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). To understand toxicological mechanisms, predictive models are essential for AOP components in computational toxicology, including molecular structures. Objectives: This study reviewed the literature and investigated previous research cases related to AOP and in silico methodologies. We describe the results obtained from the analysis, including predictive techniques and approaches that can be used for future in silico-based alternative methods to animal testing using AOP. Methods: We analyzed in silico methods and databases used in the literature to identify trends in research on in silico prediction models. Results: We reviewed 26 studies related to AOP and in silico methodologies. The ToxCast/Tox21 database was commonly used for toxicity studies, and MIE was the most frequently used predictive factor among the AOP components. Machine learning was most widely used among prediction techniques, and various in silico methods, such as deep learning, molecular docking, and molecular dynamics, were also utilized. Conclusions: We analyzed the current research trends regarding in silico-based alternative methods for animal testing using AOPs. Developing predictive techniques that reflect toxicological mechanisms will be essential to replace animal testing with in silico methods. In the future, since the applicability of various predictive techniques is increasing, it will be necessary to continue monitoring the trend of predictive techniques and in silico-based approaches.

• Biomolecules & Therapeutics
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• v.32 no.3
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• pp.390-398
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• 2024

FoxO1, a member of the Forkhead transcription factor family subgroup O (FoxO), is expressed in a range of cell types and is crucial for various pathophysiological processes, such as apoptosis and inflammation. While FoxO1's roles in multiple diseases have been recognized, the target has remained largely unexplored due to the absence of cost-effective and efficient inhibitors. Therefore, there is a need for natural FoxO1 inhibitors with minimal adverse effects. In this study, docking, MMGBSA, and ADMET analyses were performed to identify natural compounds that exhibit strong binding affinity to FoxO1. The top candidates were then subjected to molecular dynamics (MD) simulations. A natural product library was screened for interaction with FoxO1 (PDB ID-3CO6) using the Glide module of the Schrödinger suite. In silico ADMET profiling was conducted using SwissADME and pkCSM web servers. Binding free energies of the selected compounds were assessed with the Prime-MMGBSA module, while the dynamics of the top hits were analyzed using the Desmond module of the Schrödinger suite. Several natural products demonstrated high docking scores with FoxO1, indicating their potential as FoxO1 inhibitors. Specifically, the docking scores of neochlorogenic acid and fraxin were both below -6.0. These compounds also exhibit favorable drug-like properties, and a 25 ns MD study revealed a stable interaction between fraxin and FoxO1. Our findings highlight the potential of various natural products, particularly fraxin, as effective FoxO1 inhibitors with strong binding affinity, dynamic stability, and suitable ADMET profiles.

• Journal of Integrative Natural Science
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• v.16 no.4
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• pp.123-131
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• 2023

Breast cancer continues to pose a substantial worldwide health challenge, thereby requiring the development of innovative strategies to discover new therapeutic interventions. Signal Transducer and Activator of Transcription 3 (STAT-3) has been identified as a significant factor in the development of several types of cancer, including breast cancer. This is primarily attributed to its diverse functions in promoting tumour formation and conferring resistance to therapeutic interventions. This study presents an in silico drug repositioning approach that focuses on identifying specific inhibitors of STAT-3 for the purpose of treating breast cancer. We initially examined the structural and functional attributes of STAT-3, thereby elucidating its crucial involvement in cellular signalling cascades. A comprehensive virtual screening was performed on a diverse collection of drugs that have been approved by the FDA from zinc15 database. Various computational techniques, including molecular docking, cross docking, and cDFT analysis, were utilised in order to prioritise potential candidates. This prioritisation was based on their predicted binding energies and outer molecular orbital reactivity. The findings of our study have unveiled a Dihydroergotamine and Paritaprevir that have been approved by the FDA and exhibit considerable promise as selective inhibitors of STAT-3. In conclusion, the utilisation of our in silico drug repositioning approach presents a prompt and economically efficient method for the identification of potential compounds that warrant subsequent experimental validation as selective STAT-3 inhibitors in the context of breast cancer. The present study highlights the considerable potential of employing computational strategies to expedite the drug discovery process. Moreover, it provides valuable insights into novel avenues for targeted therapeutic interventions in the context of breast cancer treatment.

• BMB Reports
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• v.45 no.12
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• pp.736-741
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• 2012

Certain members of the cytochromes P450 superfamily metabolize polyunsaturated long-chain fatty acids to several classes of oxygenated metabolites. An approach based on in silico analysis predicted that Streptomyces peucetius CYP107N3 might be a fatty acid-metabolizing enzyme, showing high homology with epoxidase enzymes. Homology modeling and docking studies of CYP107N3 showed that oleic acid can fit directly into the active site pocket of the double bond of oleic acid within optimum distance of $4.6{\AA}$ from the Fe. In order to confirm the epoxidation activity proposed by in silico analysis, a gene coding CYP107N3 was expressed in Escherichia coli. The purified CYP107N3 was shown to catalyze $C_9-C_{10}$ epoxidation of oleic acid in vitro to 9,10-epoxy stearic acid confirmed by ESI-MS, HPLC-MS and GC-MS spectral analysis.