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All Journal BIOEDUSCIENCE Journal of Tropical Pharmacy and Chemistry
Mentari Luthfika Dewi
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Education Medicine & Pharmacology Public Health

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Identifikasi Interaksi Molekuler Peptida Antimikrobial dari Lendir Kulit Ikan Lele Kuning (Pelteobagrus fulvidraco) terhadap Penicillin-Binding Protein 3 (PBP3) pada Escherichia coli secara In silico Taufik Muhammad Fakih; Mentari Luthfika Dewi
BIOEDUSCIENCE Vol 4 No 1 (2020): BIOEDUSCIENCE
Publisher : Universitas Muhammadiyah Prof. Dr. Hamka

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1010.794 KB) | DOI: 10.29405/j.bes/4148-554951

Abstract

Background: Lendir kulit ikan baru-baru ini dikenal sebagai sumber potensial peptida antimikrobial yang berfungsi untuk memberikan pertahanan pertama terhadap bakteri patogen, seperi Escherichia coli. Beberapa peptida antimikrobial yang dihasilkan oleh lendir kulit ikan lele kuning (Pelteobagrus fulvidraco) terbukti mampu menghambat Penicillin-Binding Protein 3 (PBP3) pada Escherichia coli, antara lain Pelteobagrin, Myxinidin, Pleurocidin, dan Pardaxin-P1. Metode: Penelitian ini bertujuan untuk melakukan identifikasi, evaluasi, dan eksplorasi terhadap interaksi molekuler antara molekul peptida antimikrobial dengan Penicillin-Binding Protein 3 (PBP3) pada Escherichia coli menggunakan motode penambatan molekuler berbasis protein-peptida. Sekuensing peptida antimikrobial terlebih dahulu dimodelkan ke dalam bentuk konformasi 3D menggunakan server PEP-FOLD. Konformasi terbaik hasil pemodelan dipilih untuk selanjutnya dilakukan studi interaksi terhadap makromolekul Penicillin-Binding Protein 3 (PBP3) pada Escherichia coli menggunakan perangkat lunak PatchDock. Interaksi yang terbentuk kemudian diamati lebih lanjut menggunakan perangkat lunak BIOVIA Discovery Studio 2020. Hasil: Hasil dari penambatan molekuler menunjukkan bahwa peptida Pardaxin-P1 memiliki afinitas paling baik, yaitu dengan ACE score −1402,39 kJ/mol. Kesimpulan: Dengan demikian, peptida antimikrobial tersebut diprediksi dapat dipilih sebagai kandidat antimikroba alami.
Analysis of SARS-CoV-2 Spike Protein as The Key Target in the Development of Antiviral Candidates for COVID-19 through Computational Study Taufik Muhammad Fakih; Mentari Luthfika Dewi
Journal of Tropical Pharmacy and Chemistry Vol. 5 No. 4 (2021): Journal of Tropical Pharmacy and Chemistry
Publisher : Faculty of Pharmacy, Universitas Mulawarman, Samarinda, Indonesia, 75117, Gedung Administrasi Fakultas Farmasi Jl. Penajam, Kampus UNMUL Gunung Kelua, Samarinda, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25026/jtpc.v5i4.254

Abstract

The recent public health crisis is threatening the world with the emergence of the spread of the new coronavirus 2019 (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus originates from bats and is transmitted to humans through unknown intermediate animals in Wuhan, China in December 2019. Advances in technology have opened opportunities to find candidates for natural compounds capable of preventing and controlling COVID-19 infection through inhibition of spike proteins of SARS-CoV-2. This research aims to identify, evaluate, and explore the structure of spike protein macromolecules from three coronaviruses (SARS-CoV, MERS-CoV, and SARS-CoV-2) and their effects on Angiotensin-Converting Enzyme 2 (ACE-2) using computational studies. Based on the identification of the three spike protein macromolecules, it was found that there was a similarity between the active binding sites of ACE-2. These observations were then confirmed using a protein-docking simulation to observe the interaction of the protein spike to the active site of ACE-2. SARS-COV-2 spike protein has the strongest bond to ACE-2, with an ACE score of ?1341.85 kJ/mol. Therefore, some of this information from the results of this research can be used as a reference in the development of competitive inhibitor candidates for SARS-CoV-2 spike proteins for the treatment of COVID-19 infectious diseases.
Co-Authors Taufik Muhammad Fakih