In Silico Study of Bioactive Compounds From Sungkai (Peronema Canescens) as Immunomodulator

Abstract

Objective: This study aims to predict a bioactive compound from Peronema canescens (PC) with mechanisms inhibitor interleukin 6 (IL-6) and tumor necrosis factor-alpha (TNF-α) potential as an immunomodulatory using in silico approach.
 Methods: Autodock 4 was used to accomplish computer-assisted drug design with molecular docking simulation to discover binding energy, inhibition constant, and interactions with an amino acid in bioactive compounds from PC against IL-6 and TNF-α receptors. Lipinski predicts the drug-likeness of a bioactive compound for the oral route of administration. ADMET profiling of bioactive compounds to predict pharmacokinetic properties with pkCSM ADMET.
 Results: The results showed that the best binding energy, inhibition constant, and interactions with an amino acid of peronemin C1 against IL-6 and TNF-α receptors were (-7.19 kcal/mol; 5.39 nM; Arg 179, Arg 182, Gln 175), and (-8.86 kcal/mol; 320.42 nM; Tyr 119, Tyr 59, and Gly 121), respectively. All bioactive compounds from PC met Lipinski's rule of five requirements for oral administration. ADMET prediction results all bioactive compounds from PC are non-mutagenic, except peronemin D1 is mutagenic.
 Conclusion: The peronemin C1 bioactive compounds from PC have good immunomodulatory potential, effectively inhibiting human IL-6 and TNF-α receptors using in silico approach.

Unleashing Black Sea Cucumber's Potential: Identifying Anti-Cancer Compounds Through In Silico Drug Discovery

“…The analysis results indicated that all the compounds met the criteria of the Lipinski rule-of-five. This result suggests that the identified compounds possess favourable pharmacokinetic properties for drug development and can be administered orally [56]. The Lipinski rule-of-five consists of five criteria, including a molecular weight of fewer than five hundred Daltons, no more than five hydrogen bond donors, no more than ten hydrogen bond acceptors, and a partition coefficient (LogP) of less than five [57].…”

Kajian in Silico Daun Sungkai (Peronema canescens) dalam Menghambat Enzim lanosterol 14-α demethylase Jamur Candida albicans

“…Tumbuhan Sungkai termasuk dalam salah satu tanaman etnobotani yang dimanfaatkan oleh Suku Dayak di Kalimantan Timur. Tumbuhan ini dapat ditemukan di Sumetra bagian Selatan dan Kalimantan [6,7]. Tumbuhan Sungkai termasuk dalam suku Verbenaceae.…”

“…Kajian in silico memiliki peranan yang sangat penting dalam merancang dan mengoptimasi bioaktivitas senyawa dalam proses pengembangan obat. Berdasarkan uraian tersebut penulis terdorong untuk melakukan kajian in silico golongan senyawa tepenoid, flavonoid dan fenol yang terdapat pada daun sungkai untuk diinteraksikan dengan enzim Lanosterol 14-α demethylase [6]. Sehingga penulis dapat mengetahui potensi ataupun aktivitas komponen senyawa pada daun sungkai yang berpotensi menghambat pertumbuhan jamur Candida.…”