scholarly journals Shogaol, Bisdemethoxycurcumin, and Curcuminoid: Potential Zingiber Compounds Against COVID-19

2021 ◽  
Vol 11 (5) ◽  
pp. 12869-12876
Keyword(s):  
Bioactive Compounds ◽  
Binding Sites ◽  
Active Sites ◽  
Zingiber Officinale ◽  
Amino Acid Residues ◽  
Curcuma Zedoaria ◽  
Rna Dependent Rna Polymerase ◽  
Protein Amino Acid ◽  
Discovery Studio ◽  
Global Pandemic

Coronavirus disease (COVID-19) is a global pandemic in the world. Some treatments, including vaccines and potential drugs, are still developed. This study investigated the bioactive compounds of Zingiber officinale, Kaempferia rotunda, and Curcuma zedoaria as a potential inhibitor for ACE2 and RdRP proteins. Molecular docking was used for screening the bioactive compounds as ACE2 and RdRP inhibitors. Shogaol (CID 5281794), zingerone (CID 31211), chalcone (CID 637760), Ar-turmerone (CID 558221), bisdemothxycurcumin (CID 5315472), and curcuminoid (CID 101341353) interacted with angiotensin-converting enzyme receptor-2/ACE2 (PDB ID 2xd3) and RNA dependent RNA polymerase/RdRP (PDB ID 6xqb), then analyzed using Discovery studio v.19 program. Shogaol, zingerone, chalcone, ar-turmerone, bisdemethoxycurcumin, and curcuminoid bound to ACE2 and RdRP protein in some active sites. Zingerone, chalcone, and ar-turmerone are attached to the ACE-2 and then RdRP protein in similar active sites, suggesting those compounds stabilize the complex ACE-2 and RdRP protein. Shogaol interacted with the RdRP and ACE2 protein amino acid residues in the Shogaol-RdRP+ACE2 complex, indicating shogaol blocks the RdRP-ACE2 interaction. Then, bisdemethoxycurcumin and curcuminoid change the binding sites of ACE2 and RdRP protein when both compounds are bound to RdRP protein. This study suggested that shogaol, bisdemethoxycurcumin, and curcuminoid are potential drugs for COVID-19 prevention.

scholarly journals Studi In Silico: Prediksi Potensi 6-shogaol dalam Zingiber officinale sebagai Inhibitor JNK

Al-Kimia ◽  
2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Sri Sulystyaningsih Natalia Daeng Tiring ◽  
Yohanes Bare ◽  
Andri Maulidi ◽  
Mansur S ◽  
Fitra Arya Dwi Nugraha
Keyword(s):  
Bioactive Compounds ◽  
Antioxidant Properties ◽  
Zingiber Officinale ◽  
Data Bank ◽  
Protein Docking ◽  
Amino Acid Residues ◽  
Discovery Studio ◽  
Cell Dysfunction ◽  
Pubchem Database ◽  
Docking Protein

Type 2 Diabetes Mellitus (T2DM) is a metabolic disease characterized by hyperglycemia and insulin resistance. T2DM therapy against c-Jun N-terminal kinase (JNK) is one of the recovery solutions using bioactive compounds from ginger. 6-shogaol is bioactive compounds of ginger that has antioxidant properties. The purpose of this study is to analyze the potential of 6-shogaol as a JNK inhibitor. JNK protein (ID: 464Y) was obtained from Protein Data Bank (PDB) through 6-shogaol ligand (CID: 5281794) obtained from the PubChem database. Protein docking protein and ligand use Hex 8.0.0 software while visualization and analysis using Discovery Studio client 4.0. The results showed that 6-shogaol was predicted to have potential as a JNK inhibitor. Proving this by finding five amino acid residues (TRY223, LEU210, THR103 ALA214, ARG107) with an energy of -236.29cal/mol. We found the type of hydrogen bonds and the van der waals forces formed. The interaction of ligand and protein successfully inactivates JNK and stops pancreatic β cell dysfunction. 6-shogaol has pharmacological properties as a JNK,T2DM. 

scholarly journals Analysis of molecular interactions of 8-gingerol compounds in Ginger (Zingiber officinale) as ACE Inhibitor

BIOEDUSCIENCE ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 183-187
Author(s):  
Yohanes Bare ◽  
Mansur S ◽  
Aprianus Pani Pili ◽  
Maria Helvina
Keyword(s):  
Amino Acid ◽  
Hydrogen Bonds ◽  
Ace Inhibitor ◽  
Van Der Waals ◽  
Zingiber Officinale ◽  
Van Der Waals Forces ◽  
Amino Acid Residues ◽  
Protein Database ◽  
Discovery Studio ◽  
Software Analysis

Background: Hypertension is a disease with increasing characteristics of blood pressure. The ACE gene has a role in the conversion of ATI to ATII in hypertensive conditions. Healing is done by using the 8-gingerol content contained in ginger. The purpose of this study is to analyze the molecular interaction that occurs between 8-gingerol and ACE. Method: ACE model proteins (ID: 3bkk) were obtained from the Bank Data Protein database (PDB) through 8-gingerol ligands (CID: 168114) obtained from the PubChem database. ACE and 8-gingerol were docked by Discovery Study Client 4.1 software. Analysis of amino acid residues, binding energy, Van der Waals forces, and hydrogen bonds formed using Discovery Studio Client 4.1. Results: The interaction between 8-gingerol and ACE showed that there were seven amino acid residues that interacted with 8-gingerol, also found hydrogen bonds, hydrophobic and Van der Waals forces that strengthen and stabilize these bonds. Conclusion: the interaction of 8-ginger with the active side of ACE is determined as an ACE inhibitor, the inhibition is a significant effect on the obstruction of ACE conversion.

scholarly journals Alkaloids and flavonoids from African phytochemicals as potential inhibitors of SARS-Cov-2 RNA-dependent RNA polymerase: an in silico perspective

2020 ◽  
Vol 28 ◽  
pp. 204020662098407
Author(s):  
Oludare M Ogunyemi ◽  
Gideon A Gyebi ◽  
Abdo A Elfiky ◽  
Saheed O Afolabi ◽  
Olalekan B Ogunro ◽  
...  
Keyword(s):  
Rna Polymerase ◽  
Active Sites ◽  
Virus Disease ◽  
Experimental Studies ◽  
Cation Binding ◽  
Dynamics Simulation ◽  
Amino Acid Residues ◽  
Rna Dependent Rna Polymerase ◽  
Cation Binding Site ◽  
Positive Controls

Corona Virus Disease 2019 (COVID-19) is a pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Exploiting the potentials of phytocompounds is an integral component of the international response to this pandemic. In this study, a virtual screening through molecular docking analysis was used to screen a total of 226 bioactive compounds from African herbs and medicinal plants for direct interactions with SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). From these, 36 phytocompounds with binding affinities higher than the approved reference drugs (remdesivir and sobosivir), were further docked targeting the active sites of SARS-CoV-2, as well as SARS-CoV and HCV RdRp. A hit list of 7 compounds alongside two positive controls (remdesivir and sofosbuvir) and two negative controls (cinnamaldehyde and Thymoquinone) were further docked into the active site of 8 different conformations of SARS-CoV-2 RdRp gotten from molecular dynamics simulation (MDS) system equilibration. The top docked compounds were further subjected to predictive druglikeness and ADME/tox filtering analyses. Drugable alkaloids (10’–hydroxyusambarensine, cryptospirolepine, strychnopentamine) and flavonoids (usararotenoid A, and 12α-epi-millettosin), were reported to exhibit strong affinity binding and interactions with key amino acid residues in the catalytic site, the divalent-cation–binding site, and the NTP entry channel in the active region of the RdRp enzyme as the positive controls. These phytochemicals, in addition to other promising antivirals such as remdesivir and sofosbuvir, may be exploited towards the development of a cocktail of anti-coronavirus treatments in COVID-19. Experimental studies are recommended to validate these study.

In Silico Prediction and Validation of Oxygen-Regulated Protein N-myc Downstream Regulated Gene 3 and Virtual Screening of Competitive Inhibitors of L-Lactate as Therapeutics

2019 ◽  
Vol 16 (6) ◽  
pp. 637-644
Author(s):  
Hongyu Cao ◽  
Yanhua Wu ◽  
Xingzhi Zhou ◽  
Xuefang Zheng ◽  
Ge Jiang
Keyword(s):  
Active Sites ◽  
Competitive Inhibition ◽  
Hydrophobic Effect ◽  
3D Structure ◽  
Amino Acid Residues ◽  
In Silico Prediction ◽  
Hypoxic Response ◽  
Drug Candidates ◽  
Competitive Inhibitors ◽  
Extracellular Regulated Protein Kinases

Background: N-myc downstream regulated gene 3 (NDRG3) is a newly discovered oxygen-regulated protein which will bind with L-Lactate in hypoxia and further activate Raf (rapidly accelerated fibrosarcoma)-ERK (extracellular regulated protein kinases) pathway, promoting cell growth and angiogenesis. Methods: Competitive inhibition on the binding of NDRG3 and L-Lactate may be potentially a useful strategy for the repression of hypoxic response mediated by NDRG3. The threedimensional (3D) structure of NDRG3 was built by using homology modeling for its crystal structure was not available. Then, L-Lactate was docked into NDRG3, from which we knew it bound with amino acid residues Gln69, His183, Asn189, Ala72 and Pro66 of NDRG3 in the most possible active sites. Approximately 3000 compounds have been virtually screened and the 6 topranked compounds were selected as reference molecules to analyze their interaction relationships, which illustrated that some of them might form electrostatic interaction with Glu70 and Asp187, π-&π stack with Phe75 and Tyr180, hydrogen bonds with Gly71 and Asn189, hydrophobic effect with Ala72 and Ile184. Results: Novel molecules were designed through structural optimization of the 6 top-ranked compounds and subsequently their ADMET properties were predicted. Conclusion: These molecules may be potential drug candidates for the suppression of hypoxic response mediated by NDRG3 and targeted therapy for hypoxia-induced diseases.

1'-methylspiro[indoline-3,4'-piperidine] Derivatives: Design, Synthesis, Molecular Docking and Anti-tumor Activity Studies

2020 ◽  
Vol 17 ◽  
Author(s):  
Junjian Li ◽  
Lianbao Ye ◽  
Yuanyuan Wang ◽  
Ying Liu ◽  
Xiaobao Jin ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Cell Lines ◽  
Active Sites ◽  
Biological Activities ◽  
Significant Inhibition ◽  
Alkaline Condition ◽  
Discovery Studio ◽  
Hela Cell Lines ◽  
Antiproliferative Activities

Background: Spirocyclic indoline compounds widely exist in numerous natural products with good biological activities and some drug molecules in many aspects. In recent years, it has attracted extensive attention as potent anti-tumor agents in the fields of pharmacology and chemistry. Objective: In this study, we focused on designing and synthesizing a set of novel 1'-H-spiro[indole-3,4'-piperidine] derivatives, which were evaluated by preliminary bioactivity experiment in vitro and molecular docking. Method: The key intermediate 1'-methylspiro[indoline-3,4'-piperidine] (B4) reacted with benzenesulfonyl chloride with different substituents under alkaline condition to obtain its sulfonyl derivatives (B5-B10). We evaluated their antiproliferative activities against A549, BEL-7402 and HeLa cells by MTT assay. We performed the CDOCKER module in Discovery Studio 2.5.5 software for molecular modeling of compound B5, and investigated the binding of compound B5 with the target proteins from PDB database. Results: The results indicated that compounds B4-B10 exhibited good antiproliferative activities against the above three types of cells, in which compound B5 with chloride atom as electron-withdrawing substituent on a phenyl ring showed the highest potency against BEL-7402 cells (IC50=30.03±0.43 μg/mL). By binging of the prominent bioactive compound B5 to CDK, c-Met, EGFR protein crystals, The binding energy of B5 with these three types receptors are -44.3583 kcal/mol, - 38.3292 kcal/mol, -33.3653 kcal/mol respectively. Conclusion: Six 1'-methylspiro[indoline-3,4'-piperidine] derivatives were synthesized and evaluated against BEL-7402, A- 549, HeLa cell lines. Compound B5 showed significant inhibition on BEL-7402 cell lines. Molecular docking revealed that B5 showed good affinity by the good fitting between B5 and these three targets with amino acid residues in active sites which encourage us to conduct further evaluation such as the kinase experiment.

scholarly journals Crystal structures of aconitase X enzymes from bacteria and archaea provide insights into the molecular evolution of the aconitase superfamily

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Seiya Watanabe ◽  
Yohsuke Murase ◽  
Yasunori Watanabe ◽  
Yasuhiro Sakurai ◽  
Kunihiko Tajima
Keyword(s):  
Molecular Evolution ◽  
Agrobacterium Tumefaciens ◽  
Crystal Structures ◽  
Epr Spectroscopy ◽  
Binding Sites ◽  
Active Sites ◽  
Type I ◽  
Type Ii ◽  
Thermococcus Kodakarensis ◽  
Evolutionary Scenario

AbstractAconitase superfamily members catalyze the homologous isomerization of specific substrates by sequential dehydration and hydration and contain a [4Fe-4S] cluster. However, monomeric and heterodimeric types of function unknown aconitase X (AcnX) have recently been characterized as a cis-3-hydroxy-L-proline dehydratase (AcnXType-I) and mevalonate 5-phosphate dehydratase (AcnXType-II), respectively. We herein elucidated the crystal structures of AcnXType-I from Agrobacterium tumefaciens (AtAcnX) and AcnXType-II from Thermococcus kodakarensis (TkAcnX) without a ligand and in complex with substrates. AtAcnX and TkAcnX contained the [2Fe-2S] and [3Fe-4S] clusters, respectively, conforming to UV and EPR spectroscopy analyses. The binding sites of the [Fe-S] cluster and substrate were clearlydifferent from those that were completely conserved in other aconitase enzymes; however, theoverall structural frameworks and locations of active sites were partially similar to each other.These results provide novel insights into the evolutionary scenario of the aconitase superfamilybased on the recruitment hypothesis.

scholarly journals Machine learning differentiates enzymatic and non-enzymatic metals in proteins

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ryan Feehan ◽  
Meghan W. Franklin ◽  
Joanna S. G. Slusky
Keyword(s):  
Machine Learning ◽  
Metal Binding ◽  
Binding Sites ◽  
Active Sites ◽  
De Novo ◽  
Enzyme Design ◽  
Metal Binding Sites ◽  
Ensemble Machine Learning ◽  
Machine Learning Model ◽  
Physicochemical Features

AbstractMetalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme reactions. Because of the physicochemical similarities between the active sites of metalloenzymes and inactive metal binding sites, it is challenging to differentiate between them. Yet distinguishing these two classes is critical for the identification of both native and designed enzymes. Because of similarities between catalytic and non-catalytic  metal binding sites, finding physicochemical features that distinguish these two types of metal sites can indicate aspects that are critical to enzyme function. In this work, we develop the largest structural dataset of enzymatic and non-enzymatic metalloprotein sites to date. We then use a decision-tree ensemble machine learning model to classify metals bound to proteins as enzymatic or non-enzymatic with 92.2% precision and 90.1% recall. Our model scores electrostatic and pocket lining features as more important than pocket volume, despite the fact that volume is the most quantitatively different feature between enzyme and non-enzymatic sites. Finally, we find our model has overall better performance in a side-to-side comparison against other methods that differentiate enzymatic from non-enzymatic sequences. We anticipate that our model’s ability to correctly identify which metal sites are responsible for enzymatic activity could enable identification of new enzymatic mechanisms and de novo enzyme design.

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