Herbal combination from Moringa oleifera Lam. and Curcuma longa L. as SARS-CoV-2 antiviral via dual inhibitor pathway: A viroinformatics approach

Context: The COVID-19 outbreak is caused by the transmission and infection of SARS-CoV-2 at the end of 2019. It has led many countries to implement lockdown policies to prevent the viral spreading. Problems arise in a COVID-19 patient because of viral infection that leads to a systemic response in the immune system, specifically due to cytokine storm. Moreover, the antiviral drugs that have not been found. Indonesia had a variety of traditional medicines, such as is ‘jamu’. It consists of a mixture of natural ingredients such as Moringa oleifera Lam. and Curcuma longa L. Aims: To identify the activity of dual inhibitors as antiviral and anti-inflammatory agents from herbal combination compounds. Methods: Sample was collected from PubChem (NCBI, USA) and Protein Data Bank (PDB), then drug-likeness analysis using Lipinski rule of five in SCFBIO web server and bioactive probability analysis of bioactive compounds were conducted by PASS web server. Furthermore, the blind docking method was performed using PyRx 0.8 software to determine the binding activity and molecular interaction by PoseView web server and PyMol software v2.4.1 (Schrödinger, Inc, USA). Results: Cryptochlorogenic acid and curcumin have been computationally proven as dual inhibitors for antivirals by inhibiting Mpro SARS-CoV-2 and as anti-inflammatory through inhibition of NFKB1 activity. However, the results are merely computational so that it must be validated through a wet lab research. Conclusions: The combination of Moringa oleifera Lam. and Curcuma longa L. is predicted to have antiviral and anti-inflammatory activity through dual inhibitor mechanism played by cryptochlorogenic acid and curcumi

Antioxidant and Anti-inflammatory Activity of Sea Cucumber ( Active Compounds against KEAP1 and iNOS Protein

Oxidative stress and inflammation have a role in the development of various diseases. Oxidative stress and inflammation are associated with many proteins, including Kelch ECH associating protein 1 (KEAP1) and inducible nitric oxide synthase (iNOS) proteins. The active compounds contained in Holothuria scabra have antioxidant and anti-inflammatory properties. This study aimed to evaluate the antioxidant and anti-inflammatory activity of sea cucumber’s active compounds by targeting KEAP1 and iNOS proteins. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) scavenging activity of H. scabra extract were measured spectrophotometrically. The 3-dimensional (3D) structures of sea cucumber’s active compounds and proteins were obtained from the PubChem and Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) databases. Molecular docking was performed using AutoDock Vina software. Molecular dynamics simulations were carried out using Yet Another Scientific Artificial Reality Application (YASARA) software with environmental parameters according to the cell’s physiological conditions. The membrane permeability test was performed using the PerMM web server. The methanol extract of H. scabra had a weak antioxidant activity against DPPH and strong activity against NO radical. Scabraside and holothurinoside G had the most negative binding affinity values when interacting with the active site of KEAP1 and iNOS proteins. Molecular dynamics simulations also showed that both compounds were stable when interacting with KEAP1 and iNOS. However, scabraside and holothurinoside G were difficult to penetrate the cell plasma membrane, which is seen from the high energy transfer value in the lipid acyl chain region of phospholipids. Scabraside and holothurinoside G are predicted to act as antioxidants and anti-inflammations, but in their implementation to in vitro and in vivo study, it is necessary to have liposomes or nanoparticles, or other delivery methods to help these 2 compounds enter the cell

Molecular docking study of sea urchin (Arbacia lixula) peptides as multi-target inhibitor for non-small cell lung cancer (NSCLC) associated proteins

Context: Lung cancer is a type of cancer that causes the most deaths worldwide. The most common type of lung cancer is non-small cell lung cancer (NSCLC). Sea urchin (Arbacia lixula) has high potential as an antiNSCLC agent. Aims: To analyze the anticancer activity of peptides from A. lixula coelomic fluid in inhibiting the activity of NSCLC-related proteins. Methods: Peptide modeling was performed using the PEP-FOLD3 web server. Proteins that have a crucial role in NSCLC progression were determined using KEGG pathway database. 3D protein structures such as EGFR, PI3K, BRAF V600E, and JAK3 were taken from the RCSB PDB database. Docking was performed using Autodock Vina software. Docking results analysis was carried out using Discovery Studio 2019 software. Results: Some peptides bind to the active sites with low binding affinity. Peptide 10 binds to the active site of the EGFR with a binding affinity of -9 kcal/mol. Peptide 5 binds to the active sites of PI3K and BRAF V600E with binding affinity of -8.2 and -8.1 kcal/mol, respectively. Peptide 11 binds to the active site of JAK3 with a binding affinity of -8.1 kcal/mol. All of these peptides have lower binding affinity than ATP as the native ligand. Besides, these peptides also produce more hydrogen bonds than ATP, so they are predicted to be more stable. Conclusions: Peptides 10, 5, and 11 have high potential as anti-NSCLC agents because they can inhibit the activity of proteins that play an essential role in the growth of NSCLC, namely EGFR, PI3K, BRAF V600E, and JAK3 through the competitive ATP inhibitor mechanism

Exploration of Potentially Bioactive Compounds from Fingerroot (Boesenbergia rotunda L.) as Inhibitor of Atherosclerosis-Related Proteins (CETP, ACAT1, OSC, sPLA2): An in silico Study

Boesenbergia rotunda L., commonly known as fingerroot, is recognized as one of Indonesia's medicinal plants with significant potential for treating various diseases, including atherosclerosis. This study aims to analyze the anti-atherosclerosis potential of bioactive compounds found in fingerroot by assessing their inhibitory effects on four proteins associated with atherosclerosis (CETP, ACAT1, OSC, and sPLA2). Bioactive compounds from B. rotunda were retrieved from the KnapSack database. The drug-likeness properties were predicted using the SwissADME web server, and the bioactivity of the compounds was assessed using the PASSOnline server. The identification of active sites on proteins and the validation of protein structures were performed using the SCFBio web server and Autodock Vina. Specific docking simulations between fingerroot compounds and the target proteins were carried out using AutoDock Vina. The analysis revealed that fingerroot contains 20 bioactive compounds with favorable drug-like properties. Among these, dihydrochrysin, sakuranetin, isopimaric acid, 2S-pinocembrin, 5,7-dihydroxy-8-C-geranylflavanone, 7,4'-dihydroxy-5-methoxyflavanone, and 5,7-dihydroxy-8,7-methoxy-5-hydroxy-8-geranylflavanone were predicted to exhibit anti-atherosclerosis activities. In the interactions with CETP, rubranine and (-)-4-hydroxypanduratin A showed the lowest binding affinity scores. Meanwhile, in interactions with ACAT1, OSC, and sPLA2, rubranine and 5,7-dihydroxy-8-C-geranylflavanone displayed the lowest binding affinities. In conclusion, fingerroot exhibits high potential as an anti-atherosclerosis agent through the inhibition of four proteins associated with atherosclerosis, as predicted through in silico analysis

Prediction of Aflatoxin-B1 (AFB1) Molecular Mechanism Network and Interaction to Oncoproteins Growth Factor in Hepatocellular Carcinoma

Aflatoxin-B1 (AFB1) is a common contaminant for staple foods during the storage process. Chronic exposure to AFB1 is widely known to induce the development of hepatocellular carcinoma (HCC). However, there is a lack of understanding of AFBi role in HCC mechanism. This research aims to identify protein(s) in HCC that might interact with AFB1 and to predict the pathway effected by AFB1. Analyses were performed using bioinformatics tools. SMILES notation of AFB1 was submitted into Swiss Target Prediction. Interaction among predicted proteins were analyzed by using STRING. The 3D structure of target protein was constructed by homology modeling. Reverse docking was performed, and the result was ranked based on binding affinity score. Furthermore, protein interaction network was constructed and analyzed by using Cytoscape. Results showed that three protein groups were predicted as target of AFB1, such as kinases, phosphatases, and G protein-coupled receptor with probability of 46.7%, 20%, and 6.7%, respectively. Seven proteins of kinases were strongly related to HCC, including RAF1, MAPK1, MAPK3, AKT1, EGFR, GSK3B, and mTOR. Reverse docking considered the AKT1-AFB1 as the most potential complex with the lowest affinity score -10.2 kcal.mol-1. It has hydrophobic bonds in Trp80, Val270, Tyr272, Asp292, Thr211, Leu210, Leu264, and Lys268 residues, whereas hydrogen bond in Ser205 residues. Moreover, further analysis demonstrated that interaction of AKT1-AFB1 is related to the metastasis pathway in HCC mechanism

Biological activity of kencur (Kaempferia galanga L.) against SARS-CoV-2 main protease: In silico study

COVID-19 is a syndrome affecting pulmonary function but rather in serious conditions leads to death. Kencur (Kaempferia galanga L.) is a type of rhizome plant in Indonesia that is used as an herbal medicine called Jamu because it is believed to be able to cure various types of diseases. One of which is for anti-virus. The goal of this study was to see how effective the compounds in kencur are against COVID-19 with a molecular docking strategy. Kencur biological activities were obtained from the library and the design of the Acute Respiratory Syndrome Main protease (Mpro) has been gained from the protein data bank website. In addition, the biological activities in kencur were examined utilizing Lipinski's five-point concept was used to evaluate their substance molecular characteristics. Molecular docking analysis was performed with the PyRx Virtual Screening Tool software. The PyRx program was used for molecular docking simulation. While, the Discovery Studio Visualizer program was used to visualize the interaction between SARS-CoV-2 (Mpro) and the pharmacologically active metabolites in kencur. The docking evaluation on three antiviral substances revealed that Quercetin had the lowest binding energy when bound with Mpro and thus had the greatest potential as a viral inhibitor

In Silico Study of Entry Inhibitor from Moringa oleifera Bioactive Compounds against SARS-CoV-2 Infection

The aim of this study is to screen the content of bioactive compounds of Moringa oleifera and to identify its potential as an antiviral against COVID 19 through an entry inhibitor mechanism using bioinformatics tools. The sample was obtained from PubChem database. Amino acis sequences were obtained from the NCBI. Protein modeling is made through the SWISSMODEL site. The target proteins for this study were SARS-CoV-2 M pro and RdRp. The protein-inhibitory interaction of the drug from M. oleifera bioactive compounds to SARS-CoV-2 was predicted by molecular docking with PyRx software. The result shows that M. oleifera was a potential antiviral candidate for SARS-CoV-2 with an entry inhibitor mechanism through a compound, especially quercetin. The RFMS value of both interactions between Mpro and quercetion and RdRp with quercetin were not higher than 1.05. This result still needed further research to prove this prediction