Judul: Studi Literatur Senyawa Bioaktif yang Berpotensi dalam Pengobatan Covid-19
Abstrak: Covid-19 menyebabkan banyak korban jiwa karena ketersediaan rumah sakit yang terbatas. Saat ini belum ada obat yang terbukti ampuh untuk mengobati penyakit tersebut sehingga perlu obat, salah satunya dari bahan alam. Penelitian ini bertujuan meninjau berbagai literatur mengenai senyawa alam yang dapat meningkatkan imunitas tubuh dan mengobati Covid-19 beserta mekanismenya. Bahan alam yang paling sering digunakan masyarakat untuk pencegahan dan pengobatan, yang juga direkomendasikan oleh Pemerintah Indonesia ialah temulawak (Curcuma longa), jahe merah (Zingiber officinale Roscoe var Rubrum), dan jambu biji (Psidium guajava). Berdasarkan studi in silico, senyawa bioaktif kurkumin dari temulawak tidak menunjukkan potensi yang nyata dalam pengobatan Covid-19. Berbeda dengan kurkumin, senyawa bioaktif xantoangelol E, papiriflavonol A, isobavakalkon, dan 4́-O-metilbavakalkon menunjukkan potensiny dengan nilai IC50 terhadap protein SARS-CoV yang rendah. Namun, perlu studi klinis untuk mengevaluasi lebih lanjut potensi senyawa tersebut dalam pengobatan Covid-19., Covid-19 caused much mortality due to the limited availability of hospitals. However, there is no proven drug to treat the disease, so it is necessary to look for drugs, derived from natural compounds. This study aims to review various literature on natural compounds that can increase the body's immune system and treat Covid-19 and its mechanisms. The natural ingredients that are most often used by society to prevent and treat Covid-19, which the Indonesian government also recommends, are temulawak (Curcuma longa), red ginger (Zingiber officinale Roscoe var Rubrum), and guava (Psidium guajava). Based on in silico studies, curcumin of temulawak does not show significant potential in treating Covid-19. In contrast, xanthoangelol E, papiriflavonol A, isobavachalcone, and 4́’-O-methylbavachalcone showed potential in treating Covid-19 with a low IC50 value against SARS-CoV protein. However, further clinical studies are needed to evaluate the potential of these compounds in the treatment of Covid-19.
Keyword: antivirus, Covid-19, natural compounds, SARS-CoV-2

Judul: Active Compounds of Natural Products as Covid-19 Antivirus Candidates Using Molecular Docking and Dynamics Studies
Abstrak: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) adalah virus penyebab Coronavirus 2019 (COVID-19) yang menjadi pusat perhatian global pada tahun 2020. Hingga saat ini, belum ada obat yang terbukti efektif untuk pengobatan atau pencegahan COVID-19. Kajian pengembangan inhibitor virus dilakukan dengan metode virtual screening dan simulasi molecular docking. Enam protein esensial yang berperan dalam perkembangan virus, seperti protein 3CL-Pro, PL-Pro, Helikase, Protein N, E, dan M digunakan sebagai protein target. Tujuan dari penelitian ini adalah untuk mendapatkan model interaksi ligan senyawa alam aktif terhadap protein reseptor yang dikode oleh genom SARS-CoV-2 dan energi ikat bebasnya sehingga dapat mengusulkan senyawa aktif dari produk alam yang berpotensi sebagai obat untuk COVID-19. Autodock Vina, Autodock 4.2, PSOVina, dan Amber20 digunakan dalam penelitian ini. Berdasarkan nilai energi ikat bebas dan interaksi protein-ligan, diperoleh kandidat senyawa dengan nilai terbaik untuk setiap protein target. Korilagin (-14,42 kkal/mol), Skutelarein 7-rutinosida (-13,2 kkal/mol), Genistein 7-O-glukuronida (- 10,52 kkal/mol), Basa Biflavonoid-flavon + 3O dan basa flavanon + 2O + 1MeO (- 11 ,88 dan -9,61 kkal/mol), dan Enoksolon (-6,96 kkal/mol) memiliki nilai energi bebas terbaik pada setiap protein target yang menunjukkan bahwa senyawa tersebut berpotensi sebagai inhibitor protein virus untuk diteliti lebih lanjut. Penelitian ini terbatas pada simulasi komputer, dimana hasil yang diperoleh masih berupa prediksi. Diperlukan penelitian lebih lanjut untuk menguji aktivitas ligan terpilih yang memiliki nilai energi bebas terendah dari keenam protein target. Pada uji stabilitas dengan simulasi dinamika molekul, kompleks 3CL-Pro – Korilagin merupakan kompleks yang paling stabil dibandingkan kompleks lainnya, sehingga korilagin merupakan senyawa yang paling direkomendasikan untuk diteliti lebih lanjut., Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the virus that causes Coronavirus 2019 (COVID-19) which has become the center of global attention in 2020. To date, there has been no proven effective drug for the treatment or prevention of COVID-19. A study on the development of inhibitors for this virus is carried out using virtual screening and molecular docking simulation methods. Six essential proteins that play a role in virus development, such as 3CL-Pro, PL-Pro, Helicase, N, E, and M protein were used as protein targets. The purpose of this study was to obtain a model of ligands interactions of active natural compounds against the receptor protein encoded by the SARS-CoV- 2 genome and their free binding energy so that it can propose active compounds from natural products that have potential as a drug for COVID-19.Autodock Vina, Autodock 4.2, PSOVina, and Amber20 were used in this study. Based on the value of free binding energy and protein-ligand interactions, the candidate compounds with the best value are obtained for each target protein. Corilagin (-14,42 kcal/mol), Scutellarein 7-rutinoside (-13,2 kcal/mol), Genistein 7-O-glucuronide (-10,52 kcal/mol), Biflavonoid-flavone base + 3O and flavanone base + 2O + 1MeO (-11,88 and -9,61 kcal/mol), and Enoxolone (-6,96 kcal/mol) has the best free energy value at each protein target indicating that the compound has the potential as a viral protein inhibitor for further investigation. This research is limited to computer simulations, where the results obtained are still a prediction. Further research is needed to test the selected ligand activity, which has the lowest
Keyword: covid-19, molecular docking, molecular dynamic, natural compound, sars-cov-2, virtual screening

Judul: Analysis of Unequal Income Distribution with Cobb-Douglas Production Function
Abstrak: This paper studies the economic growth model by Moav (2002). Moav model shows the existence of unequal income distribution between low-income with high-income community. That kind of unequal income distribution is caused by uneven distribution of income. On this Moav model, there is one area called the threshold. Threshold becomes a benchmark to determining whether a society is categorized into low- or high- income community. The production function used in this paper is the Cobb-Douglas function. The dynamics of this model is described as difference equation of low-income, threshold, and high-income community. Simulation study on the model is carried out using Maple 13 and Mathematica 7.0 software. Overall, from the observed case, high-income community will reach a stable condition earlier, followed by the threshold, and then the low-income community.
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