Abstract. Peel-off gel mask is one type of mask that is easy and practical to use and has the uniqueness of containing an adhesive material where the material can form a film layer which can then be cleaned by peeling it off after it dries. Peel-off gel masks contain several important components such as film-forming, gelling agents, and humectants. These components can affect the characteristics of the peel off gel mask. The purpose of this study was to determine the effect of the type and concentration of the peel-off gel mask base on the physical characteristics of the peel-off gel mask so that the best formula could be obtained. This research was conducted using the literature study method from various research journals that have been published both nationally and internationally. Based on literature studies that have been carried out, PVA with a concentration of 12-13.5% is optimum as film-forming, HPMC with a concentration of 3-5% as a gelling agent, and propylene glycol with a concentration of 10-12% as a humectant. The ingredients with these concentrations can affect the characteristics of the peel off gel mask where the higher the concentration of the mask base, the higher the viscosity of the preparation which will cause lower dispersion, longer adhesion, and longer drying time. Abstrak. Masker gel peel off adalah salah satu jenis masker yang penggunaannya mudah dan praktis, serta memiliki keunikan yaitu mengandung bahan yang bersifat adhesive dimana bahan tersebut dapat membentuk lapisan film kemudian dapat dibersihkan dengan cara dikelupas setelah mengering. Masker gel peel off mengandung beberapa komponen penting seperti pembentuk film (film forming), pembentuk gel (gelling agent), dan humektan. Komponen-komponen tersebut dapat mempengaruhi karakteristik masker gel peel off. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh jenis dan konsentrasi basis masker gel peel off terhadap karakteristik fisik masker gel peel off sehingga dapat diperoleh formula terbaik. Penelitian ini dilakukan dengan metode studi literatur dari berbagai jurnal penelitian yang telah dipublikasikan baik nasional maupun internasional. Berdasarkan studi literatur yang telah dilakukan, PVA dengan konsentrasi 12-13,5% optimum sebagai film forming, HPMC dengan konsentrasi 3-5% sebagai gelling agent, dan propilenglikol dengan konsentrasi 10-12% sebagai humektan. Bahan-bahan dengan konsentrasi tersebut mampu mempengaruhi karakteristik masker gel peel off dimana semakin tinggi konsentrasi basis masker maka semakin tinggi viskositas sediaan yang akan menyebabkan daya sebar rendah, daya lekat lebih lama, dan waktu mengering lebih lama.
Background: The emergence of infectious diseases caused by SARS-CoV-2 has resulted in more than 90,000 infections and 3,000 deaths. The coronavirus spike glycoprotein encourages the entry of SARS-CoV-2 into cells and is the main target of antivirals. SARS-CoV-2 uses ACE2 to enter cells with an affinity similar to SARS-CoV, correlated with the efficient spread of SARS-CoV-2 among humans.Objective: In the research, identification, evaluation, and exploration of the structure of SARS-CoV and SARS-CoV-2 spike glycoprotein macromolecules and their effects on Angiotensin-Converting Enzyme 2 (ACE-2) using in silico studies.Methods: The spike glycoproteins of the two coronaviruses were prepared using the BIOVIA Discovery Studio 2020. Further identification of the three-dimensional structure and sequencing of the macromolecular spike glycoprotein structure using Chimera 1.14 and Notepad++. To ensure the affinity and molecular interactions between the SARS-CoV and SARS-CoV-2 spike glycoproteins against ACE-2 protein-protein docking simulations using PatchDock was accomplished. The results of the simulations were verified using the BIOVIA Discovery Studio 2020.Results: Based on the results of the identification of the macromolecular structure of the spike glycoprotein, it was found that there are some similarities in characteristics between SARS-CoV and SARS-CoV-2. Protein-protein docking simulations resulted that SARS-COV-2 spike glycoprotein has the strongest bond with ACE-2, with an ACE score of −1509.13 kJ/mol.Conclusion: Therefore, some information obtained from the results of this research can be used as a reference in the development of SARS-CoV-2 spike glycoprotein inhibitor candidates for the treatment of infectious diseases of COVID-19.
The new coronavirus (SARS-CoV-2), which caused the global pandemic Coronavirus Disease-2019 (COVID-2019), has infected nearly 206 countries. There is still little information about molecular compounds that can inhibit the development of infections caused by this disease. It is crucial to achieving the discovery of competent natural inhibitor candidates, such as antiviral peptides, because they have a variety of biological activities and have evolved to target biochemical machinery from different pathogens or host cell structures. In silico studies will be carried out, including protein-peptide docking and protein-protein docking, to identify, evaluate, and explore the affinity and molecular interactions of the Magainin-1 and Magainin-2 peptide molecules derived from frog skin (Xenopus laevis) to the main protease macromolecule (Mpro) SARS-CoV-2, and its effect on the ACE-2 receptor (Angiotensin Converting Enzyme-2 Receptor). Protein-peptide docking simulations show that both peptide molecules have a good affinity for the active site area of the SARS-CoV-2 Mpro macromolecule. These results were then confirmed using protein-protein docking simulations to observe the ability of the peptide molecule in preventing attachment to the ACE-2 receptor surface area. In silico studies show that Magainin-2 has the best affinity, with a bond free energy value of −3054.53 kJ/mol. Then the protein-protein docking simulation provided Magainin-2 was able to prevent the attachment of ACE-2 receptors, with an ACE score of 1697.99 kJ/mol. Thus, through in silico research, it is hoped that the Magainin peptide molecule can be further investigated in the development of new antiviral peptides for the treatment of infectious diseases of COVID-19.
Protease utama (Mpro) merupakan bagian utama pembentuk karakteristik coronavirus (SARS-CoV dan SARS-CoV-2). Kemajuan teknologi telah membuka peluang untuk menemukan kandidat molekul inhibitor baru yang mampu mencegah dan mengendalikan infeksi COVID-19 melalui penghambatan Mpro SARS-CoV-2. Penelitian ini bertujuan untuk mengidentifikasi, mengevaluasi, dan mengeksplorasi struktur makromolekul Mpro dari kedua coronavirus tersebut secara in silico. Makromolekul Mpro terlebih dahulu dilakukan preparasi dengan menggunakan perangkat lunak BIOVIA Discovery Studio 2020. Konformasi tiga dimensi dan sekuensing dari struktur makromolekul Mpro yang telah dipreparasi kemudian diamati dan dibandingkan dengan menggunakan perangkat lunak Chimera 1.14 dan Notepad ++. Bagian sisi aktif dari makromolekul Mpro kemudian diidentifikasi dengan menggunakan perangkat lunak BIOVIA Discovery Studio 2020. Prediksi molekul inhibitor makromolekul Mpro dilakukan dengan menggunakan perangkat lunak MGLTools 1.5.6 yang dilengkapi dengan AutoDock 4.2. Berdasarkan hasil identifikasi terhadap makromolekul Mpro diperoleh hasil bahwa terdapat kemiripan struktur dan situs aktif pengikatan dari kedua makromolekul Mpro tersebut. Diprediksi bentuk molekul inhibitor dari kedua makromolekul Mpro juga identik. Dengan demikian, beberapa referensi tersebut dapat digunakan sebagai acuan dalam pengembangan kandidat inhibitor kompetitif Mpro SARS-CoV-2 untuk pengobatan penyakit infeksi COVID-19. Kata kunci: Protease utama (Mpro), SARS-CoV, SARS-CoV-2, COVID-19, in silico.
Beberapa peptida yang terkandung dalam racun kalajengking (Lychas mucronatus) menunjukkan beragam aktivitas biologis dengan spesifisitas tinggi terhadap target. Peptida ini memiliki efek potensial terhadap mikroba dan menunjukkan potensi untuk memodulasi berbagai mekanisme biologis yang terlibat dalam imunitas, saraf, kardiovaskular, dan penyakit neoplastik. Keragaman struktural dan fungsional yang penting dari peptida tersebut membuktikan bahwa peptida dari racun kalajengking dapat digunakan dalam pengembangan obat spesifik baru. Melalui penelitian ini akan dilakukan identifikasi, evaluasi, dan eksplorasi terhadap stabilitas peptida Mucroporin yang diproduksi dari racun kalajengking dengan menggunakan simulasi dinamika molekular. Sekuens molekul peptida Mucroporin dimodelkan dengan menggunakan server PEPstrMOD. Konformasi terbaik hasil pemodelan dipilih untuk diamati stabilitasnya dengan menggunakan software Gromacs 2016.3. Trajektori yang terbentuk kemudian dianalisis berdasarkan visulasiasi dengan menggunakan software VMD 1.9.4 serta dilakukan analisis grafik RMSD dan RMSF. Hasil analisis trajektori dari simulasi dinamika molekular membuktikan bahwa molekul peptida Mucroporin-S2 memiliki stabilitas yang paling baik. Dengan demikian, molekul peptida tersebut diprediksi dapat dipilih sebagai kandidat obat berbasis peptida.
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