Effecacy of Black Sugarcane Leaves (Saccharum officinarum L.) as Anti-Dysmenorrhea In Silico Based On Molecular Docking

Abstract

Dysmenorrhea is menstrual pain in women that interferes with daily activities. Dysmenorrhea causes decreased productivity, performance, sleep disturbances, and quality of life. The use of antidysmenorrhoea drugs such as non-steroidal anti-inflammatory drugs, oral contraceptive pills have many side effects in the form of nerve disorders, blood vessels, and even heart failure. Therefore, the exploration of natural medicines is essential. One of the traditional medicinal ingredients that is thought to have efficacy in relieving menstrual pain is black sugarcane leaves (Saccharum officinarum L.). Testing the efficacy of this medicinal ingredient can be done in silico using computational biology technology. This in silico study is effective in drug discovery efforts because it is cost and time-efficient. This study aims to analyze the ability of black sugarcane leaf phytochemical compounds to inhibit the dysmenorrhea pathway's activation based on molecular docking. This observational study is based on bioinformatics using the molecular docking method. Research data were obtained from analysis using software computing programs such as the National Center for Biotechnology Information, prediction of activity spectra of substances, Lipinski rule of five tests, pyrx, and discovery studio. The research data were analyzed based on the binding affinity value and visualization of the molecular docking results. Black sugarcane leaves contain 27 phytochemical compounds based on GCMS analysis with various bioactivities related to anti-dysmenorrhea (menstrual pain). 16 compounds have activity probability values (Pa) > 0.7, which indicates that their bioactivity is analogous to that of commercial drugs (natural effective drug candidates). The hexadecanoic acid compound is the best anti-dysmenorrhea drug candidate compared to other phytochemical compounds in black sugarcane leaves because it has the lowest binding affinity value of -6 kcal/mol.

Dismenorea merupakan nyeri menstruasi pada wanita yang mengganggu aktivitas sehari-hari. Dismenorea menyebabkan penurunan produktivitas, penurunan prestasi, gangguan tidur, dan penurunan kualitas hidup. Penggunaan obat antidismenorea seperti antiinflamasi non steroid, pil kontrasepsi oral memiliki banyak efek samping berupa gangguan saraf, pembuluh darah, bahkan gagal jantung. Oleh karena itu, eksplorasi obat berbahan alami sangat diperlukan. Salah satu bahan obat tradisional yang diduga memiliki khasiat dalam meredakan nyeri menstruasi yaitu daun tebu ireng (Saccharum officinarum L.). Pengujian khasiat bahan obat ini dapat dilakukan secara in silico menggunakan teknologi biologi komputasi. Kajian secara in silico ini efektif digunakan dalam upaya penemuan obat karena efisien biaya dan waktu. Penelitian ini bertujuan untuk menganalisis kemampuan senyawa fitokimia daun tebu ireng dalam menghambat aktivasi jalur dismenorea berdasarkan molecular docking. Penelitian ini merupakan penelitian observasi berbasis bioinformatika dengan menggunakan metode molecular docking. Data penelitian diperoleh dari analisis menggunakan program komputasi software seperti National Center for Biotechnology Information, prediction of activity spectra of substances, lipinski rule of five test, pyrx, dan discovery studio. Data hasil penelitian dianalisis berdasarkan nilai binding affinity dan visualisasi hasil molecular docking. Daun tebu ireng mengandung 27 senyawa fitokimia berdasarkan analisis GCMS yang memiliki berbagai bioaktivitas terkait dengan anti-dismenorea (nyeri menstruasi). 16 senyawa memiliki nilai probabilitas activity (Pa) > 0,7 yang mengindikasikan bahwa bioaktivitasnya analog dengan obat komersil (kandidat obat efektif alami). Senyawa hexadecanoic acid merupakan kandidat obat anti-dismenorea terbaik dibandingkan senyawa fitokimia lainnya pada daun tebu ireng karena memiliki nilai binding affinity terendah yaitu -6 kkal/mol.