Potensi Sinamaldehid sebagai Anti Hiperpigmentasi secara In Silico

Permasalahan kulit yang sering ditemui yaitu hiperpigmentasi yang terjadi akibat adanya sintesis melanin berlebihan yang menyebabkan penggelapan warna kulit. Hiperpigmentasi dapat diatasi dengan agen anti hiperpigmentasi yang beraktivitas dalam menghambat proses sintesis melanin. Sintesis melanin dapat dihambat dengan berbagai cara salah satunya dengan menghambat aktivitas tyrosinase. Tyrosinase merupakan enzim yang berperan dalam mengkatalisis proses biosintesis melanin. Sinamaldehid merupakan senyawa bahan alam banyak ditemukan pada tanaman Cinnamomum burmanni mempunyai aktivitas sebagai antioksidan. Penelitian ini bertujuan untuk mengetahui potensi sinamaldehid dalam menghambat tyrosinase yang akan dibandingkan dengan native liganya secara in silico. Uji in silico dilakukan secara docking molecular dengan tahapan yaitu preparasi dan optimasi sinamaldehid, preparasi tyrosinase serta validasi dan docking. Metode docking molecular telah dinyatakan valid karena RMSD (root mean square distance) yang diperoleh tidak lebih dari 3 Å. Analisis data dilakukan dengan melihat energi ikatan yang dihasilkan dan ikatan yang terbentuk antara senyawa dengan residu asam amino pada protein. Nilai energi ikatan yang diperoleh antara ikatan sinamaldehid dengan tyrosinase adalah-6,21 kkal/mol. Sedangkan energi ikatan antara tyrosinase dengan native ligandnya -4,79 kkal/mol. Hal tersebut menunjukkan afinitas dari sinamaldehid pada protein tyrosinase lebih besar dibandingkan native ligandnya, sehingga sinamaldehid dikatakan memiliki potensi sebagai anti hiperpigmentasi dengan mekanisme molecular berupa inhibitor protein target tyrosinase sehingga dapat menghambat aktivitas enzim tyrosinase.

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How root-mean-square distance (r.m.s.d.) values depend on the resolution of protein structures that are compared

Journal of Applied Crystallography ◽

10.1107/s0021889802020502 ◽

2003 ◽

Vol 36 (1) ◽

pp. 125-128 ◽

Cited By ~ 28

Author(s):

Oliviero Carugo

Keyword(s):

Protein Structure ◽

Root Mean Square ◽

Protein Pair ◽

Protein Structures ◽

Structural Similarity ◽

Protein Crystal ◽

Mean Square ◽

Root Mean Square Distance ◽

Open Question ◽

Mean Square Distance

The most popular estimator of structural similarity is the root-mean-square distance (r.m.s.d.) between equivalent atoms, computed after optimal superposition of the two structures that are compared. It is known that r.m.s.d. values do not depend only on conformational differences but also on other features, for example the dimensions of the structures that are compared. An open question is how they might depend on the accuracy of the experimentally determined protein structures. Given that the accuracy of the protein crystal structures is generally estimated through the crystallographic resolution, it is important to know the dependence of the r.m.s.d. on the crystallographic resolution of the two structures that are compared. 14458 protein structure pairs of identical sequence were compared and the resulting r.m.s.d. values were normalized to 100-residue length to avoid the bias introduced by the dependence of the r.m.s.d. values on the protein-pair dimensions. On average, smaller r.m.s.d. values are associated with protein structure pairs at better resolution and the r.m.s.d. values tend to increase if the two proteins that are compared have been refined at different resolutions. For crystallographic resolutions ranging between 1.6 and 2.9 Å, both relationships appear to be linear: r.m.s.d. = −0.73 + 0.48 resolution and delta_r.m.s.d. = 0.20 + 0.30 delta_resolution (`delta' indicating difference). Although the linearity of these relationships is not expected to hold outside the 1.6–2.9 Å resolution range, they are useful in making the r.m.s.d. values more reliable.

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Statistical validation of the root-mean-square-distance, a measure of protein structural proximity

Protein Engineering Design and Selection ◽

10.1093/protein/gzl051 ◽

2007 ◽

Vol 20 (1) ◽

pp. 33-37 ◽

Cited By ~ 23

Author(s):

Oliviero Carugo

Keyword(s):

Root Mean Square ◽

Mean Square ◽

Statistical Validation ◽

Root Mean Square Distance ◽

Mean Square Distance

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POTENSI DAUN ASAM JAWA (Tamarindus indica L.) SEBAGAI ALTERNATIF ANTIINFLAMASI: STUDI IN SILICO

Jurnal Kefarmasian Akfarindo ◽

10.37089/jofar.v0i0.68 ◽

2019 ◽

pp. 42-50

Author(s):

Erma Yunita ◽

Siti Fatimah ◽

Deni Yulianto ◽

Vedy Trikuncahyo ◽

Zihan Khodijah

Keyword(s):

Molecular Docking ◽

Root Mean Square ◽

Root Mean Square Deviation ◽

In Silico ◽

Mean Square ◽

Mean Square Deviation ◽

Tamarindus Indica ◽

Protein Target ◽

Cox 2 ◽

Cox 1

Daun asam jawa (Tamarindus indica L.) merupakan tanaman yang memiliki banyak khasiat. Kandungan senyawa kimia yang terkandung salah satunya Kuersetin. Kuersetin merupakan senyawa flavonoid yang dapat digunakan sebagai anti inflamasi. Penelitian ini bertujuan untuk mengetahui potensi aktivitas Kuersetin dari daun asam jawa sebagai anti inflamasi terhadap protein COX-1 dan COX-2 secara in silico. Ekstrak daun asam jawa diperoleh dengan maserasi bertingkat menggunakan heksan dan etanol. Kadar Kuersetinnya dihitung secara spektrofotometri UVVis. Konfirmasi aktivitas antiinflamasi dilakukan secara in silico. Protein yang digunakan adalah 6COX, 3PGH, dan 1EQH. Kuersetin sebagai senyawa aktif sedangkan Aspirin digunakan sebagai zat pembanding. Preparasi ligan Kuersetin menggunakan MarvinSketch kemudian preparasi protein target 6COX, 1EQH, dan 3PGH menggunakan YASARA. Selanjutnya melakukan molecular docking menggunakan program PLANTS. Parameter evaluasi validasi dapat dilihat dari nilai Root Mean Square Deviation (RMSD), dimana nilai RMSD yang diterima adalah kurang dari 2Å. Kadar Kuersetin yang diperoleh dalam ekstrak dalam daun asam jawa sebesar 31,26 mg/g. Hasil docking menunjukkan bahwa Kuersetin mampu berinteraksi dengan 1EQH, 3PGH, dan 6COX dimana skor dockingnya masing-masing adalah -77,6195; -75,1344; dan -82,2454, sedangkan hasil docking Aspirin masing-masing adalah -69,8784; -75,2421; dan - 72,0884. Kuersetin memiliki potensi sebagai anti inflamasi yang lebih baik dibandingkan dengan Aspirin namun memiliki resiko lebih tinggi menyebabkan ulkus lambung dibanding Aspirin.

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Percentile-based spread: a more accurate way to compare crystallographic models

Acta Crystallographica Section D Biological Crystallography ◽

10.1107/s0907444910027927 ◽

2010 ◽

Vol 66 (9) ◽

pp. 970-978 ◽

Cited By ~ 15

Author(s):

Edwin Pozharski

Keyword(s):

Crystal Structures ◽

Root Mean Square ◽

Conformational Changes ◽

Alternative Measure ◽

Mean Square ◽

Root Mean Square Distance ◽

Average Variation ◽

Model Ensembles ◽

Mean Square Distance

The comparison of biomacromolecular crystal structures is traditionally based on the root-mean-square distance between corresponding atoms. This measure is sensitive to the presence of outliers, which inflate it disproportionately to their fraction. An alternative measure, the percentile-based spread (p.b.s.), is proposed and is shown to represent the average variation in atomic positions more adequately. It is discussed in the context of isomorphous crystal structures, conformational changes and model ensembles generated by repetitive automated rebuilding.

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Luteolin and abyssinone II as potential inhibitors of SARS-CoV-2: an in silico molecular modeling approach in battling the COVID-19 outbreak

Bulletin of the National Research Centre ◽

10.1186/s42269-020-00479-6 ◽

2021 ◽

Vol 45 (1) ◽

Author(s):

Mohammad Mahfuz Ali Khan Shawan ◽

Sajal Kumar Halder ◽

Md. Ashraful Hasan

Keyword(s):

Molecular Dynamics ◽

Root Mean Square ◽

In Silico ◽

Binding Free Energy ◽

Biologically Active ◽

Dynamics Simulation ◽

Mean Square ◽

Efficient Treatment ◽

Target Proteins

Abstract Background At present, the entire world is in a war against COVID-19 pandemic which has gradually led us toward a more compromised “new normal” life. SARS-CoV-2, the pathogenic microorganism liable for the recent COVID-19 outbreak, is extremely contagious in nature resulting in an unusual number of infections and death globally. The lack of clinically proven therapeutic intervention for COVID-19 has dragged the world’s healthcare system into the biggest challenge. Therefore, development of an efficient treatment scheme is now in great demand. Screening of different biologically active plant-based natural compounds could be a useful strategy for combating this pandemic. In the present research, a collection of 43 flavonoids of 7 different classes with previously recorded antiviral activity was evaluated via computational and bioinformatics tools for their impeding capacity against SARS-CoV-2. In silico drug likeness, pharmacophore and Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) profile analysis of the finest ligands were carried out using DataWarrior, DruLiTo and admetSAR programs, respectively. Molecular docking was executed by AutoDock Vina, while molecular dynamics simulation of the target protein–ligand bound complexes was done using nanoscalable molecular dynamics and visual molecular dynamics software package. Finally, the molecular target analysis of the selected ligands within Homo sapiens was conducted with SwissTargetPredcition web server. Results Out of the forty-three flavonoids, luteolin and abyssinone II were found to develop successful docked complex within the binding sites of target proteins in terms of lowest binding free energy and inhibition constant. The root mean square deviation and root mean square fluctuation values of the docked complex displayed stable interaction and efficient binding between the ligands and target proteins. Both of the flavonoids were found to be safe for human use and possessed good drug likeness properties and target accuracy. Conclusions Conclusively, the current study proposes that luteolin and abyssinone II might act as potential therapeutic candidates for SARS-CoV-2 infection. In vivo and in vitro experiments, however, should be taken under consideration to determine the efficiency and to demonstrate the mechanism of action.

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Identification of Potential SARS-CoV-2 Main Protease and Spike Protein Inhibitors from the Genus Aloe: An In Silico Study for Drug Development

Molecules ◽

10.3390/molecules26061767 ◽

2021 ◽

Vol 26 (6) ◽

pp. 1767

Author(s):

Mohamed E. Abouelela ◽

Hamdy K. Assaf ◽

Reda A. Abdelhamid ◽

Ehab S. Elkhyat ◽

Ahmed M. Sayed ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

Drug Development ◽

Root Mean Square ◽

In Silico ◽

Dynamics Simulation ◽

Spike Protein ◽

Energy Calculation ◽

Mean Square ◽

Main Protease

Severe acute respiratory syndrome coronavirus (SARS-CoV-2) disease is a global rapidly spreading virus showing very high rates of complications and mortality. Till now, there is no effective specific treatment for the disease. Aloe is a rich source of isolated phytoconstituents that have an enormous range of biological activities. Since there are no available experimental techniques to examine these compounds for antiviral activity against SARS-CoV-2, we employed an in silico approach involving molecular docking, dynamics simulation, and binding free energy calculation using SARS-CoV-2 essential proteins as main protease and spike protein to identify lead compounds from Aloe that may help in novel drug discovery. Results retrieved from docking and molecular dynamics simulation suggested a number of promising inhibitors from Aloe. Root mean square deviation (RMSD) and root mean square fluctuation (RMSF) calculations indicated that compounds 132, 134, and 159 were the best scoring compounds against main protease, while compounds 115, 120, and 131 were the best scoring ones against spike glycoprotein. Compounds 120 and 131 were able to achieve significant stability and binding free energies during molecular dynamics simulation. In addition, the highest scoring compounds were investigated for their pharmacokinetic properties and drug-likeness. The Aloe compounds are promising active phytoconstituents for drug development for SARS-CoV-2.

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Identification of Terpenoids From Abrus precatorius Against Parkinson’s Disease Proteins Using In Silico Approach

Bioinformatics and Biology Insights ◽

10.1177/11779322211050757 ◽

2021 ◽

Vol 15 ◽

pp. 117793222110507

Author(s):

Damilola Alex Omoboyowa ◽

Toheeb Adewale Balogun ◽

Oluwaseun Motunrayo Omomule ◽

Oluwatosin A Saibu

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Root Mean Square ◽

Root Mean Square Deviation ◽

In Silico ◽

High Performance ◽

Md Simulation ◽

Mean Square ◽

Mean Square Deviation ◽

Abrus Precatorius

Parkinson’s disease (PD) is the second major neuro-degenrative disorder that causes morbidity and mortality among older populations. Terpenoids were reported as potential neuro-protective agents. Therefore, this study seeks to unlock the inhibitory potential of terpenoids from Abrus precatorius seeds against proteins involve in PD pathogenesis. In this study, in silico molecular docking of 5 terpenoids derived from high-performance liquid chromatography (HPLC) analysis of A. precatorius seeds against α-synuclein, catechol-o-methyltransferase, and monoamine oxidase B which are markers of PD was performed using Autodock vina. The absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) of the hits were done using Swiss ADME predictor and molecular dynamic (MD) simulation of the hit-protein complex was performed using Desmond Schrodinger software. Five out of 6 compounds satisfied the ADME/Tox parameters and showed varying degrees of binding affinities with selected proteins. Drimenin-α-synuclein complex showed the lowest binding energy of −9.1 kcal/mol followed by interaction with key amino acid residues necessary for α-synuclein inhibition. The selection of this complex was justified by its stability in MD simulation conducted for 10 ns and exhibited stable interaction in terms of root mean square deviation (RMSD) and root mean square deviation error fluctuation (RMSF) values.

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