Prediction of Bioactivity, Molecular Targets, and ADMET Properties of Chlorogenic Acid Derived from Coffee Beans (Coffea liberica)

Yuneka Saristiana; Fendy Prasetyawan; M Wahyu Ariawan; Lisa Savitri; Saiful Musttaqin; Herman

doi:10.30872/jtpc.v9i3.318

Authors

Yuneka Saristiana Pharmacist Professional Education Study Program, Faculty of Health Sciences, Kadiri University Author
Fendy Prasetyawan Pharmacist Professional Education Study Program, Faculty of Health Sciences, Kadiri University Author
M Wahyu Ariawan Pharmacist Study Program, Faculty of Pharmacy, Mulawarman University Author
Lisa Savitri Medical Laboratory Technology Study Program, Faculty of Health Sciences, Kadiri University Author
Saiful Musttaqin Medical Laboratory Technology Study Program, Faculty of Health Sciences, Kadiri University Author
Herman Pharmacist Study Program, Faculty of Health Sciences, Kadiri University Author

DOI:

https://doi.org/10.30872/jtpc.v9i3.318

Abstract

Chlorogenic acid is a major polyphenolic compound present in coffee beans and has been widely recognized for its diverse pharmacological properties. However, comprehensive information regarding its bioactivity spectrum, molecular targets, and pharmacokinetic characteristics remains limited, particularly for chlorogenic acid derived from Coffea liberica. This study aimed to evaluate the bioactivity, molecular targets, and ADMET properties of chlorogenic acid using an integrated in silico approach. Bioactivity prediction was performed using the Way2Drug platform to identify potential pharmacological activities. Molecular target identification was conducted using SwissTargetPrediction to determine probable protein targets relevant to human biology. Pharmacokinetic and toxicity profiles were assessed using the pkCSM web server to evaluate absorption, distribution, metabolism, excretion, and toxicity parameters. The bioactivity analysis revealed strong predicted antioxidant, membrane-protective, anti-inflammatory, and anticarcinogenic activities. Target prediction indicated interactions with multiple protein classes, predominantly enzymes and proteases, including aldo-keto reductases, matrix metalloproteinases, carbonic anhydrases, and proteins associated with metabolic, inflammatory, oncogenic, and neurodegenerative pathways. ADMET analysis demonstrated moderate oral absorption, limited central nervous system penetration, low risk of cytochrome P450–mediated drug–drug interactions.

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