scholarly journals Gaultheria leucocarpa var. yunnanensis for Treating Rheumatoid Arthritis—An Assessment Combining Machine Learning–Guided ADME Properties Prediction, Network Pharmacology, and Pharmacological Assessment

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiuhuan Wang ◽  
Youyi Sun ◽  
Ling Ling ◽  
Xueyang Ren ◽  
Xiaoyun Liu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Machine Learning ◽  
Methyl Salicylate ◽  
Molecular Networks ◽  
Network Pharmacology ◽  
Rheumatic Arthritis ◽  
Qsar Models ◽  
Adme Properties

Background: Dianbaizhu (Gaultheria leucocarpa var. yunnanensis), a traditional Chinese/ethnic medicine (TC/EM), has been used to treat rheumatoid arthritis (RA) for a long time. The anti–rheumatic arthritis fraction (ARF) of G. yunnanensis has significant anti-inflammatory and analgesic activities and is mainly composed of methyl salicylate glycosides, flavonoids, organic acids, and others. The effective ingredients and rudimentary mechanism of ARF remedying RA have not been elucidated to date.Purpose: The aim of the present study is to give an insight into the effective components and mechanisms of Dianbaizhu in ameliorating RA, based on the estimation of the absorption, distribution, metabolism, and excretion (ADME) properties, analysis of network pharmacology, and in vivo and in vitro validations.Study design and methods: The IL-1β–induced human fibroblast-like synoviocytes of RA (HFLS-RA) model and adjuvant-induced arthritis in the rat model were adopted to assess the anti-RA effect of ARF. The components in ARF were identified by using UHPLC-LTQ-Orbitrap-MSn. The quantitative structure–activity relationship (QSAR) models were developed by using five machine learning algorithms, alone or in combination with genetic algorithms for predicting the ADME properties of ARF. The molecular networks and pathways presumably referring to the therapy of ARF on RA were yielded by using common databases and visible software, and the experimental validations of the key targets conducted in vitro.Results: ARF effectively relieved RA in vivo and in vitro. The five optimized QSAR models that were developed showed robustness and predictive ability. The characterized 48 components in ARF had good biological potency. Four key signaling pathways were obtained, which were related to both cytokine signaling and cell immune response. ARF suppressed IL-1β–induced expression of EGFR, MMP 9, IL2, MAPK14, and KDR in the HFLS-RA .Conclusions: ARF has good druggability and high exploitation potential. Methyl salicylate glycosides and flavonoids play essential roles in attuning RA. ARF may partially attenuate RA by regulating the expression of multi-targets in the inflammation–immune system. These provide valuable information to rationalize ARF and other TC/EMs in the treatment of RA.

Revealing the Synergistic Mechanism of Multiple Components in Compound Fengshiding Capsule for Rheumatoid Arthritis Therapeutics by Network Pharmacology

2019 ◽  
Vol 19 (4) ◽  
pp. 303-314 ◽  
Author(s):  
Hong Duan ◽  
Ke-feng Zhai ◽  
Ghulam J. Khan ◽  
Jie Zhou ◽  
Ting-yan Cao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Drug Targets ◽  
The Body ◽  
In Vivo Studies ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Pubmed Database ◽  
Synergistic Mechanism

Background:Compound Fengshiding capsule (CFC), is a Chinese formulation from herbal origin including Alangium platanifolium, Angelicae dahurica, Cynanchum paniculatum and Glycyrrhiza uralensis. CFC is widely used as clinical therapy against rheumatoid arthritis. However, its exact mechanism of action has not been explored yet.Methods:In order to explore the synergistic mechanism of CFC, we designed a study adopting network pharmacology scheme to screen the action targets in relation to the CFC components. The study analyses target facts of salicin, paeonol, liquiritin and imperatorin from PubMed database, and explores the potential pharmacological targets of rheumatoid arthritis, cervical neuralgia and sciatica related diseases for their interaction.Results:The results of boosted metabolic pathway showed that the chemical components of CFC interrupted many immune-related pathways, thus participating in immunity regulation of the body and playing a role in the treatment of rheumatism. Collectively, CFC has apoptotic, oxidative stress modulatory and anti-inflammatory effects that accumulatively serve for its clinical application against rheumatoid arthritis.Conclusion:Conclusively, our findings from present study reconnoiters and compacts systematic theoretical approach by utilizing the network pharmacology mechanism of four effective components for the treatment of rheumatism indicating sufficient potential drug targets associated with CFC against rheumatism. These interesting findings entreaties for further in vitro and in vivo studies on the mechanism of compound active ingredient against rheumatism.

scholarly journals Bioinformatics Approaches to Natural Product Discovery

2021 ◽  
Vol 41 ◽  
pp. 02004
Author(s):  
Wisnu Ananta Kusuma
Keyword(s):  
Machine Learning ◽  
Natural Products ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Protein Targets ◽  
Link Type ◽  
Topological Features ◽  
Brown Adipose

Introduction: Bioinformatics is a multi-disciplinary field that usually uses approaches in Computer Science such as algorithms and machine learning to solve problems in the domains of Biology, Biochemistry, and other domains involving molecular biology data. This approach can also be used to screen natural products that have certain properties. Jamu or Indonesian herbal medicine works with the principle of multi-component multi-target. This principle focuses on the complex interactions of system components that describe how multi-components (compounds) can work together to affect multi-targets (protein targets). This mechanism is also popularly called Network Pharmacology. In this study, we introduce a workflow to screen herbal compounds based on Network Pharmacology and machine learning approach. Methods: The workflow starts by screening for proteins that have an important role in relation to a certain disease. The screening was conducted by applying clustering and utilizing network topological features which were represented as graphs [1]. Furthermore, we performed enrichment analysis by integrating the protein-protein interaction network with the Gene Ontology (GO) network covering biological processes, molecular functions, and cellular components into k-partite graph and analyzing them using soft clustering method [2]. From the results of this enrichment analysis, we determined which proteins are really relevant and have important role in a certain disease [3]. Next, from these screened proteins, we built a predictive models of compound-protein interactions from drug data collected from the DrugBank and SuperTarget databases and train the models using machine learning or deep learning methods [4]. This model was then used to predict Indonesian herbal compounds from the HerbalDB database (http://herbaldb.farmasi.ui.ac.id/v3/) and IJAH Analytics. Results: To demonstrate the effectiveness of the workflow, we applied it to analize some diseases, such as hyperinflamation in Covid-19 and obesity. We found several potential plants such as Andrographis paniculata (Sambiloto) to reduce the inflammatory effect on Covid-19 and Murraya paniculata (Kemuning) to activate Brown Adipose Tissue (BAT) which has the potential to treat obesity. Certainly all of this requires proof through in vitro, in vivo, and clinical trials. We have also implemented several processes in the workflow into the IJAH Analytics application. Some of the features of IJAH are finding herbal compounds or plant formulas based on specific disease or protein targets; and otherwise looking for the efficacy of several combinations of plants or herbal compounds. In addition, IJAH Analytics can also visualize pharmacological networks from plants-compound-protein-diseases. IJAH is available to the public at https://ijah.apps.cs.ipb.ac.id for free. Conclusion: This study shows the potential of using bioinformatics approaches based on network pharmacology and machine learning in discovering the potential of natural products from Indonesia’s biodiversity. In addition, IJAH Analytics, although still in the refinement stage, can be an alternative application that can support researchers to screen potential Indonesian natural products.

scholarly journals WTD Attenuating Rheumatoid Arthritis via Suppressing Angiogenesis and Modulating the PI3K/AKT/mTOR/HIF-1α Pathway

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Ba ◽  
Ying Huang ◽  
Pan Shen ◽  
Yao Huang ◽  
Hui Wang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cell Proliferation ◽  
Umbilical Vein ◽  
Tube Formation ◽  
Migration And Invasion ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Promising Alternative

Background: Wutou Decoction (WTD), as a classic prescription, has been generally used to treat rheumatoid arthritis (RA) for two thousand years in China. However, the potential protective effects of WTD on rheumatoid arthritis and its possible mechanism have rarely been reported.Purpose: The aim of this study was to explore the possible mechanism of WTD against RA and a promising alternative candidate for RA therapy.Methods: A model of collagen-induced arthritis (CIA) was constructed in rats to assess the therapeutic effects of WTD. Histopathological staining, immunofluorescence, and western blotting of synovial sections were conducted to detect the antiangiogenic effects of WTD. Then, cell viability assays, flow cytometry, scratch healing assays, and invasion assays were conducted to explore the effects of WTD on MH7A human fibroblast-like synoviocyte (FLS) cell proliferation, apoptosis, migration, and invasion in vitro. The ability of WTD to induce blood vessel formation after MH7A cell and human umbilical vein endothelial cell line (HUVEC) coculture with WTD intervention was detected by a tube formation assay. The mechanisms of WTD were screened by network pharmacology and confirmed by in vivo and in vitro experiments.Results: WTD ameliorated the symptoms and synovial pannus hyperplasia of CIA rats. Treatment with WTD inhibited MH7A cell proliferation, migration, and invasion and promoted MH7A apoptosis. WTD could inhibit MH7A cell expression of proangiogenic factors, including VEGF and ANGI, to induce HUVEC tube formation. Furthermore, the PI3K-AKT-mTOR-HIF-1α pathway was enriched as a potential target of WTD for the treatment of RA through network pharmacology enrichment analysis. Finally, it was confirmed in vitro and in vivo that WTD inhibits angiogenesis in RA by interrupting the PI3K-AKT-mTOR-HIF-1α pathway.Conclusion: WTD can inhibit synovial hyperplasia and angiogenesis, presumably by inhibiting the migration and invasion of MH7A cells and blocking the production of proangiogenic effectors in MH7A cells. The possible underlying mechanism by which WTD ameliorates angiogenesis in RA is the PI3K-AKT-mTOR-HIF-1α pathway.

scholarly journals Isopsoralen ameliorates rheumatoid arthritis by targeting MIF

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Yi Han ◽  
Jinguang Wang ◽  
Shufeng Li ◽  
Yi Li ◽  
Yongli Zhang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Therapeutic Potential ◽  
Mechanistic Study ◽  
Network Pharmacology ◽  
In Vivo Models ◽  
Inflammatory Phenotype ◽  
Anti Inflammatory ◽  
Cellular Thermal Shift Assay

Abstract Background Isopsoralen (IPRN), one of the active ingredients of Psoralea corylifolia Linn, has anti-inflammatory properties. We attempted to investigate the inhibitory effects of IPRN on rheumatoid arthritis (RA) and characterize its potential mechanism. Methods RA fibroblast-like synoviocytes (FLSs) and mice with collagen-induced arthritis (CIA) were used as in vitro and in vivo models to analyze the antiarthritic effect of IPRN. Histological analysis of the inflamed joints from mice with CIA was performed using microcomputed tomography (micro-CT) and hematoxylin-eosin (HE) staining. RNA sequencing (RNA-Seq), network pharmacology analysis, molecular docking, drug affinity responsive target stability (DARTS) assay, and cellular thermal shift assay (CETSA) were performed to evaluate the targets of IPRN. Results IPRN ameliorated the inflammatory phenotype of RA FLSs by inhibiting their cytokine production, migration, invasion, and proangiogenic ability. IPRN also significantly reduced the severity of CIA in mice by decreasing paw thickness, arthritis score, bone damage, and serum inflammatory cytokine levels. A mechanistic study demonstrated that macrophage migration inhibitory factor (MIF), a key protein in the inflammatory process, was the specific target by which IPRN exerted its anti-inflammatory effects in RA FLSs. Conclusion Our study demonstrates the antiarthritic effect of IPRN, which suggests the therapeutic potential of IPRN in RA.

Comparison of In Vitro and In Vivo Effects of Infliximab on Cytokine Production in Proliferating CD4+ T Cells in Patients with Rheumatoid Arthritis

2015 ◽  
Vol 1 (2) ◽  
pp. 122-128
Author(s):  
Syuichi Koarada ◽  
Yuri Sadanaga ◽  
Natsumi Nagao ◽  
Satoko Tashiro ◽  
Rie Suematsu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
T Cells ◽  
Cd4 T Cells ◽  
Cytokine Production

scholarly journals Secreted KIAA1199 promotes the progression of rheumatoid arthritis by mediating hyaluronic acid degradation in an ANXA1-dependent manner

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wei Zhang ◽  
Guoyu Yin ◽  
Heping Zhao ◽  
Hanzhi Ling ◽  
Zhen Xie ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Hyaluronic Acid ◽  
Dependent Manner ◽  
Collagen Induced Arthritis ◽  
Intracellular Degradation ◽  
Main Pathway ◽  
First Time

AbstractIn inflamed joints, enhanced hyaluronic acid (HA) degradation is closely related to the pathogenesis of rheumatoid arthritis (RA). KIAA1199 has been identified as a hyaladherin that mediates the intracellular degradation of HA, but its extracellular function remains unclear. In this study, we found that the serum and synovial levels of secreted KIAA1199 (sKIAA1199) and low-molecular-weight HA (LMW-HA, MW < 100 kDa) in RA patients were significantly increased, and the positive correlation between them was shown for the first time. Of note, treatment with anti-KIAA1199 mAb effectively alleviated the severity of arthritis and reduced serum LMW-HA levels and cytokine secretion in collagen-induced arthritis (CIA) mice. In vitro, sKIAA1199 was shown to mediate exogenous HA degradation by attaching to the cell membrane of RA fibroblast-like synoviosytes (RA FLS). Furthermore, the HA-degrading activity of sKIAA1199 depended largely on its adhesion to the membrane, which was achieved by its G8 domain binding to ANXA1. In vivo, kiaa1199-KO mice exhibited greater resistance to collagen-induced arthritis. Interestingly, this resistance could be partially reversed by intra-articular injection of vectors encoding full-length KIAA1199 instead of G8-deleted KIAA119 mutant, which further confirmed the indispensable role of G8 domain in KIAA1199 involvement in RA pathological processes. Mechanically, the activation of NF-κB by interleukin-6 (IL-6) through PI3K/Akt signaling is suggested to be the main pathway to induce KIAA1199 expression in RA FLS. In conclusion, our study supported the contribution of sKIAA1199 to RA pathogenesis, providing a new therapeutic target for RA by blocking sKIAA1199-mediated HA degradation.

scholarly journals Phaseolin Attenuates Lipopolysaccharide-Induced Inflammation in RAW 264.7 Cells and Zebrafish

Biomedicines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 420
Author(s):  
Su-Jung Hwang ◽  
Ye-Seul Song ◽  
Hyo-Jong Lee
Keyword(s):  
Nitric Oxide ◽  
Nuclear Translocation ◽  
Raw 264.7 Cells ◽  
Network Pharmacology ◽  
Raw 264.7 ◽  
Dependent Manner ◽  
Bioactive Constituents

Kushen (Radix Sophorae flavescentis) is used to treat ulcerative colitis, tumors, and pruritus. Recently, phaseolin, formononetin, matrine, luteolin, and quercetin, through a network pharmacology approach, were tentatively identified as five bioactive constituents responsible for the anti-inflammatory effects of S. flavescentis. However, the role of phaseolin (one of the primary components of S. flavescentis) in the direct regulation of inflammation and inflammatory processes is not well known. In this study, the beneficial role of phaseolin against inflammation was explored in lipopolysaccharide (LPS)-induced inflammation models of RAW 264.7 macrophages and zebrafish larvae. Phaseolin inhibited LPS-mediated production of nitric oxide (NO) and the expression of inducible nitric oxide synthase (iNOS), without affecting cell viability. In addition, phaseolin suppressed pro-inflammatory mediators such as cyclooxygenase 2 (COX-2), interleukin-1β (IL-1β), tumor necrosis factor α (TNF-α), monocyte chemoattractant protein-1 (MCP-1), and interleukin-6 (IL-6) in a dose-dependent manner. Furthermore, phaseolin reduced matrix metalloproteinase (MMP) activity as well as macrophage adhesion in vitro and the recruitment of leukocytes in vivo by downregulating Ninjurin 1 (Ninj1), an adhesion molecule. Finally, phaseolin inhibited the nuclear translocation of nuclear factor-kappa B (NF-κB). In view of the above, our results suggest that phaseolin could be a potential therapeutic candidate for the management of inflammation.

scholarly journals Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2505
Author(s):  
Raheem Remtulla ◽  
Sanjoy Kumar Das ◽  
Leonard A. Levin
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
In Silico ◽  
Disulfide Bonds ◽  
Oral Absorption ◽  
In Vivo Studies ◽  
Drug Candidates ◽  
In Silico Methods

Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated in the downstream effects of axonal injury. A difficulty in using standard in silico methods for studying these drugs is that most computational tools are not designed for borane-containing compounds. Using in silico and machine learning methodologies, the absorption-distribution properties of these unique compounds were assessed. Features examined with in silico methods included cellular permeability, octanol-water partition coefficient, blood-brain barrier permeability, oral absorption and serum protein binding. The resultant neural networks demonstrated an appropriate level of accuracy and were comparable to existing in silico methodologies. Specifically, they were able to reliably predict pharmacokinetic features of known boron-containing compounds. These methods predicted that phosphine-borane compounds and their metabolites meet the necessary pharmacokinetic features for orally active drug candidates. This study showed that the combination of standard in silico predictive and machine learning models with neural networks is effective in predicting pharmacokinetic features of novel boron-containing compounds as neuroprotective drugs.

Lipidated Methotrexate Microbubbles: A Promising Rheumatoid Arthritis Theranostic Medicine Manipulated via Ultrasonic Irradiation

2021 ◽  
Vol 17 (7) ◽  
pp. 1293-1304
Author(s):  
Zhuofei Zhao ◽  
Xiaona Lin ◽  
Lulu Zhang ◽  
Xia Liu ◽  
Qingwen Wang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
De Novo ◽  
Low Ph ◽  
Curative Effect ◽  
Inflammatory Microenvironment ◽  
Raw 264.7 Cell ◽  
Infection Focus ◽  
Raw 264.7 Cell Line

De novo designed lipidated methotrexate was synthesized and self-assembled into microbubbles for targeted rheumatoid arthritis theranostic treatment. Controlled lipidatedmethotrexate delivery was achieved by ultrasound-targetedmicrobubble destruction technique. Methotrexate was dissociated inflammatory microenvironment of synovial cavity, owing to representive low pH and enriched leucocyte esterase. We first manipulated methotrexate controlled release with RAW 264.7 cell line in vitro and further verified with rheumatoid arthritis rabbits in vivo. Results showed that lipidated methotrexate microbubbles precisely affected infection focus and significantly enhanced rheumatoid arthritis curative effect comparing with dissociative methotrexate. This study indicates that lipidated methotrexate microbubbles might be considered as a promising rheumatoid arthritis theranostics medicine.

In-silico Molecular Docking of Coumarin and Naphthalene Derivatives from Pyrenacantha volubilis with the Pathological Mediators of Rheumatoid Arthritis

2021 ◽  
pp. 5121-5125
Author(s):  
Anjali P ◽  
Vimalavathini R
Keyword(s):  
Rheumatoid Arthritis ◽  
Symptomatic Relief ◽  
In Vivo Studies ◽  
Gas Chromatography Mass Spectrometry ◽  
Therapeutic Drugs ◽  
Herbal Plants ◽  
In Silico Molecular Docking ◽  
Inflammatory Autoimmune Disease

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease which mainly targets synovial membrane during its disease pathogenesis. Available therapeutic drugs for the treatment of RA provide only symptomatic relief and are associated with severe side effects. Herbal plants comprise many active biological compounds that cure the disease with minimal adverse effects. Pyrenacantha volubilis is a climber and member of Icacinaceae family. Gas chromatography- mass spectrometry (GC-MS) analysis of ethanolic extracts of leaves of Pyrenacantha volubilis (EEPV) reveals the presence of 2-isopropyl-5-methylcyclohexyl 3-(1-(4- chlorophenyl)-3-oxobutyl)-coumarin-4-yl carbonate and 1-naphthalenepropanol, alpha-ethyldecahydro-5- (hydroxymethyl)-alpha,5,8A-trimethyl-2-methyl phytoconstitutents. Hence these compounds were docked with various pathological mediators of RA using Autodock 4.2. The docking results unveils that these compounds had better binding energy against inflammatory, oxidative stress and receptor for advanced glycation end products (RAGE) mediators that plays a pivotal role in the progression of RA. However, this study warrants further in- vitro and in-vivo studies to be carried out to establish the anti-inflammatory and anti-arthritic activity of selected phytoconstitutents.

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