scholarly journals Study in Silico Compounds In 96% Ethanol Extract of Chrysanthemum cinerariifolium (Trev.) Leaves Towards Alfa Estrogen Receptors

2020 ◽  
Vol 11 (3) ◽  
pp. 144
Author(s):  
Roihatul Mutiah ◽  
Yen Yen Indrawijaya ◽  
Dwi Puspita
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptors ◽  
Metabolic Profiling ◽  
In Silico ◽  
Lethal Dose ◽  
Ethanol Extract ◽  
Good Activity ◽  
In Silico Prediction ◽  
Test Compound ◽  
Molegro Virtual Docker

Chrysanthemum cinerariifolium (Trev.) is a plant that has potential as an anticancer. This study aimed to predict the inhibitor of estrogen alpha and toxicity of compounds in 96% ethanol extract of C. cinerariifolium leaves in silico. Prediction of the activity of metabolic profiling compounds produced by UPLC QToF MS/MS ethanol extract 96% of C. cinerariifolium leaves towards alpha estrogen receptors (ER-α) (5W9C) was carried out using Molegro Virtual Docker. The docking results showed that the compound (2-Methyl-1,4-piperazinediyl) bis-[(3,4,5-trimethoxyphenyl)-methanone and Azoxystrobin have good activity compared to Tamoxifen, because these compounds have a lower Rerank Score. The activity of the test compound is also shown by the bonding of active amino acids (Arg 394, Asp351, Glu 353, and Val 533). As for the toxicity class based on Globally Harmonized System (GHS) and Lethal Dose 50 (LD50) values, the ten docking compounds had a relatively low toxicity.Keywords: C. cinerariifolium, breast cancer, alpha estrogen, cytotoxic activity, toxicity

In silico prediction of Anti-apoptotic BCL-2 proteins Modulation by Afzelin in MDA-MB-231 Breast cancer cell

2020 ◽  
Vol 13 (2) ◽  
pp. 905
Author(s):  
Eva Rachmi ◽  
Basuki Bambang Purnomo ◽  
Agustina Tri Endharti ◽  
Loeki Enggar Fitri
Keyword(s):  
Breast Cancer ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
In Silico ◽  
In Silico Prediction

scholarly journals In Silico Prediction of Inhibition of Promiscuous Breast Cancer Resistance Protein (BCRP/ABCG2)

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e90689 ◽  
Author(s):  
Yi-Lung Ding ◽  
Yu-Hsuan Shih ◽  
Fu-Yuan Tsai ◽  
Max K. Leong
Keyword(s):  
Breast Cancer ◽  
In Silico ◽  
Breast Cancer Resistance Protein ◽  
Cancer Resistance ◽  
In Silico Prediction ◽  
Resistance Protein

scholarly journals HKSA secara In-Silico Senyawa 1-Benzil-3- Benzoilurea dan Analognya sebagai Penghambat Reseptor Bruton Tyrosine Kinase (BTK)

2021 ◽  
Vol 3 (1) ◽  
pp. 35-47
Author(s):  
Denis Cristian Sudarno ◽  
Farida Suhud ◽  
Siswandono
Keyword(s):  
Tyrosine Kinase ◽  
Physicochemical Properties ◽  
In Silico ◽  
Quantitative Structure Activity Relationship ◽  
Tyrosine Kinase Receptor ◽  
Test Compound ◽  
Molegro Virtual Docker ◽  
Non Hodgkin Lymphoma ◽  
Bruton Tyrosine Kinase ◽  
Docking Approach

Abstract—In this study, a new anticancer drug design for non-Hodgkin’s lymphoma was carried out, with a molecular docking approach from the compound 1-benzyl-3-benzoylurea parent and its analog as an anticancer compound. The purpose of the study was to obtain the best quantitative structure-activity relationship (QSAR). The in-silico activity test was carried out on the new 1-benzyl-3-benzoilurea and its analog compound against the Bruton Tyrosine Kinase receptor (BTK) PDB code (5FBN) by using the Molegro Virtual Docker 5.5 program and producing a RS (Rerank Score) value for the test compound and Acalabrutinib was used as a comparison. This study also conducted bioavailability by predicting the value of F (intestinal human absorption) in the pkCSM program and toxicity studies by predicting LD50 values using the Protox II program. Correlation and regression were performed using the RS, F, and LD50 values that we obtained on the physicochemical properties of the test compound using the IBM SPSS version 24 program. The best equation is obtained as follows: (1) F = 0.851 Es Taft - 6.116 σ - 1.969 π² + 3.620 π + 90.809;  (2) RS = 4.376 Es Taft - 88.802; (3) LD50 = 672.518 CMR - 669.385 ClogP - 813.806. From the results of the best equation is obtained that the activity is influenced by the parameters of steric physicochemical properties (Es Taft). Keywords: 1-benzyl-3-benzoylurea, code pdb:5fbn, in-silico, non-hodgkin lymphoma Abstrak—Pada penelitian ini dilakukan rancangan obat baru antikanker Limfoma non-Hodgkin, dengan pendekatan penambatan molekul dari senyawa induk 1-benzil-3-benzoilurea dan analognya sebagai senyawa antikanker.Tujuan penelitian ini untuk mendapatkan persamaan hubungan struktur aktivitas (HKSA) terbaik. Uji aktivitas in-silico dilakukan terhadap senyawa baru 1-benzil-3-benzoilurea dan analognya terhadap reseptor Bruton Tyrosine Kinase (BTK) kode PDB 5FBN dengan menggunakkan program Molegro Virtual Docker 5.5 dan menghasilkan nilai RS (Rerank Score) untuk senyawa uji dan Acalabrutinib digunakan sebagai pembanding. Penelitian ini juga dilakukan studi bioavaibilitas dengan memprediksi nilai F (intestinal human absorbtion) pada program pkCSM dan studi toksisitas dengan memprediksi nilai LD50 menggunakan program Protox II. Korelasi dan regresi dilakukan menggunakan nilai RS, F dan LD50 yang telah diperoleh terhadap parameter sifat fisikokimia senyawa uji menggunakan program IBM SPSS versi 24. Persamaan terbaik yang diperoleh sebagai berikut: (1) F = - 1.969 π² + 0.851 Es Taft - 6.116 σ + 3.620 π + 90.809 (2) RS = 4.376 Es Taft - 88.802 (3) LD50 = 672.518 CMR - 669.385 ClogP - 813.806. Dari hasil persamaan terbaik tersebut diperoleh bahwa aktivitas dipengaruhi oleh parameter sifat fisikokimia sterik (Es Taft). Kata kunci: 1-benzil-3-benzoilurea, in-silico, kode pdb: 5fbn, limfoma non-hodgkin

scholarly journals In Silico Screening of Schleichera oleosa Phytocompounds as Estrogen Receptors Alpha Inhibitors for Breast Cancer

JSMARTech ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 014-021
Author(s):  
Radita Intan Aisyah Pratiwi ◽  
◽  
Tintrim Rahayu ◽  
Nurul Jadid Mubarakati ◽  
◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptors ◽  
In Silico ◽  
In Silico Screening ◽  
Schleichera Oleosa

Speciation of cultivated temperate and tropical Pleurotus species –an in silico prediction using conserved sequences

2019 ◽  
Vol 28 (1) ◽  
Author(s):  
Anupam Barh ◽  
V P Sharma ◽  
Shwet Kamal ◽  
Mahantesh Shirur ◽  
Sudheer Kumar Annepu ◽  
...  
Keyword(s):  
In Silico ◽  
In Silico Prediction ◽  
Conserved Sequences ◽  
Pleurotus Species

Phytoestrogens and Mitochondrial Biogenesis in Breast Cancer. Influence of Estrogen Receptors Ratio

2014 ◽  
Vol 20 (35) ◽  
pp. 5594-5618 ◽  
Author(s):  
Pilar Roca ◽  
Jorge Sastre-Serra ◽  
Mercedes Nadal-Serrano ◽  
Daniel Pons ◽  
Ma Blanquer-Rossello ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptors ◽  
Mitochondrial Biogenesis

In silico Discovery of Resveratrol Analogues as Potential Agents in Treatment of Metabolic Disorders

2019 ◽  
Vol 25 (35) ◽  
pp. 3776-3783
Author(s):  
Nebojša Pavlović ◽  
Maja Đanić ◽  
Bojan Stanimirov ◽  
Svetlana Goločorbin-Kon ◽  
Karmen Stankov ◽  
...  
Keyword(s):  
In Silico ◽  
Metabolic Disorders ◽  
Partial Agonist ◽  
Aqueous Solubility ◽  
Structural Similarity ◽  
Data Bank ◽  
Docking Studies ◽  
Binding Energies ◽  
Molegro Virtual Docker ◽  
Ppar Γ

Background: Resveratrol was demonstrated to act as partial agonist of PPAR-γ receptor, which opens up the possibility for its use in the treatment of metabolic disorders. Considering the poor bioavailability of resveratrol, particularly due to its low aqueous solubility, we aimed to identify analogues of resveratrol with improved pharmacokinetic properties and higher binding affinities towards PPAR-γ. Methods: 3D structures of resveratrol and its analogues were retrieved from ZINC database, while PPAR-γ structure was obtained from Protein Data Bank. Docking studies were performed using Molegro Virtual Docker software. Molecular descriptors relevant to pharmacokinetics were calculated from ligand structures using VolSurf+ software. Results: Using structural similarity search method, 56 analogues of resveratrol were identified and subjected to docking analyses. Binding energies were ranged from -136.69 to -90.89 kcal/mol, with 16 analogues having higher affinities towards PPAR-γ in comparison to resveratrol. From the calculated values of SOLY descriptor, 23 studied compounds were shown to be more soluble in water than resveratrol. However, only two tetrahydroxy stilbene derivatives, piceatannol and oxyresveratrol, had both better solubility and affinity towards PPAR-γ. These compounds also had more favorable ADME profile, since they were shown to be more metabolically stable and wider distributed in body than resveratrol. Conclusion: Piceatannol and oxyresveratrol should be considered as potential lead compounds for further drug development. Although experimental validation of obtained in silico results is required, this work can be considered as a step toward the discovery of new natural and safe drugs in treatment of metabolic disorders.

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