Jurnal Ilmu Medis Indonesia

Evaluasi Potensi Antikanker Senyawa Daun Kelor melalui Kimia Medisinal

Saeful Amin — 2025-09-06

Purpose: This study aimed to assess the potential of bioactive compounds found in moringa (Moringa oleifera) leaves as agents to treat breast cancer using a medicinal chemistry approach.

Methodology/approach: This study was conducted using a descriptive and qualitative literature review approach, utilizing data sources from various relevant scientific journals published in the last five years.

Results/findings: This study showed that four key compounds, moringin, kaempferol, quercetin, and nanoquercetin, have significant biological potential in inhibiting the growth and spread of breast cancer cells through various molecular mechanisms. The combination of these compounds provides a synergistic and selective therapeutic approach and shows potential in the development of more effective cancer therapies with minimal side effects. However, challenges related to pharmacokinetic limitations, especially in quercetin, can be overcome through technological innovations, such as nano-based delivery systems.

Conclusions: This study concludes that bioactive compounds in Moringa oleifera leaves possess promising anticancer properties against breast cancer through diverse molecular mechanisms. Their synergistic potential highlights the relevance of natural compounds in the development of selective and effective cancer therapies.

Limitations: The study was limited by its reliance on secondary data from literature sources and lack of experimental validation. Additionally, pharmacokinetic challenges, especially for quercetin, necessitate further research on delivery system optimization.

Contributions: This research adds valuable insights into the medicinal chemistry of natural compounds, particularly in the Indonesian context. It also encourages the development of innovative drug delivery technologies to enhance the clinical applications of plant-derived anticancer agents.

Eksplorasi Senyawa Alami sebagai Lead Antikanker Payudara dengan Pendekatan In Silico

Saeful Amin — 2025-09-05

Purpose: This study aimed to explore the potential of natural compounds as lead candidates for breast cancer therapy through a medicinal chemistry framework using in silico methods, with the goal of identifying safer and more effective alternatives to conventional treatments.

Methodology: A qualitative library-based research design was employed using a systematic literature review of 15 primary national and international journal articles published between 2020 and 2025. The computational tools used in the study included AutoDock Vina and PyRx for molecular docking and virtual screening, SwissADME and pkCSM for ADMET predictions, and GROMACS for molecular dynamics simulations.

Results: Several natural compounds, including berberine, ellagic acid, camptothecin, and kaempferol, exhibited strong binding affinities toward key breast cancer molecular targets, such as estrogen receptor (ER), progesterone receptor (PR), HER2, and PD-L1. These compounds formed stable ligand–receptor complexes and showed favorable pharmacokinetic properties, conforming to Lipinski’s Rule of Five, thereby suggesting their viability as lead candidates for further development.

Conclusions: This study highlights the promising potential of selected natural compounds as lead structures for breast cancer drug development. The integration of molecular docking, pharmacokinetic prediction, and dynamic simulation provides a robust platform for early phase drug discovery.

Limitations: The primary limitation of this study is that in silico simulations do not fully capture complex biological interactions within the human body, including metabolic pathways and immune system responses.

Contribution: his study contributes to the fields of medicinal chemistry and pharmaceutical sciences by offering updated insights into the utility of natural compounds as anti-breast cancer agents.

Potensi Senyawa Turunan Terpenoid sebagai Agen Anti-Kanker

Saeful Amin — 2025-09-01

Purpose: This study aimed to analyze the potential of terpenoid derivatives as anti-cancer agents by reviewing various molecular mechanisms involved, findings from preclinical and clinical studies, and the challenges faced in their development.

Methodology: A literature review approach was used, involving the collection, analysis, and synthesis of data from credible sources, to present a comprehensive understanding of the pharmacological properties and mechanisms of action of terpenoids. Critical evaluation of the selected studies was carried out to identify key findings and trends..

Results: This review shows that terpenoids have significant potential in cancer therapy through diverse molecular mechanisms, both as monotherapies and in combination with conventional treatments. Advances in drug delivery technologies, such as the use of nanoparticles and liposomes, have enhanced the stability and bioavailability of compounds, paving the way for more effective therapeutic applications.

Conclusions: Terpenoid-based drug development shows strong promise in cancer treatment. Structural modifications have improved their efficacy and selectivity toward cancer cells, and innovative delivery systems have addressed challenges in bioavailability, supporting their role as safe and effective therapeutic alternatives.

Limitations: This review was based on secondary data and lacked direct clinical validation. It does not provide detailed pharmacokinetic or pharmacodynamic profiles, and its potential interactions with standard chemotherapeutic agents remain underexplored.

Contribution: This article synthesizes the molecular mechanisms and therapeutic potential of terpenoid derivatives as anticancer agents. This highlights the advances in delivery technologies and structural optimization, offering valuable insights for future drug development strategies.

Review Artikel: Pendekatan in Silico dalam Kimia Medisinal tentang Resistensi Antibiotik

Saeful Amin — 2025-09-07

Purpose: This study aimed to explore the utilization of in silico approaches in medicinal chemistry to address the global challenge of antibiotic resistance through faster, more efficient, and innovative drug discovery methods..

Methodology: A systematic literature review was conducted using the Google Scholar, SINTA, PubMed, and ScienceDirect databases. The selected articles highlight computational techniques such as molecular docking, machine learning, and Perturbation Theory and Machine Learning (PTML) models for the identification, screening, and optimization of novel antibiotic candidates.

Results: This review reveals that in silico methods significantly accelerate the discovery of potential antibiotics, facilitate the identification of compounds with novel mechanisms of action, improve ligand–target binding predictions, and support the modulation of resistance-related gene expression. The synergy between computational simulations and experimental validation enhances the reliability and efficiency of drug development pipelines.

Conclusions In silico approaches offer effective, rapid, and cost-efficient solutions for the discovery of next-generation antibiotics that play a crucial role in the ongoing battle against antimicrobial resistance.

Limitations: Despite their advantages, in silico methods have limitations in accurately predicting pharmacokinetics and toxicity profiles, as well as in modelling protein flexibility and complexity of biological systems.

Contribution: This study contributes to medicinal chemistry, pharmaceutical science, and biotechnology by providing an integrative framework that supports innovative and resource-efficient strategies for antibiotic development and resistance mitigation.

Perkembangan Terkini dalam Desain Obat Berbasis Kimia Medisinal

Saeful Amin — 2025-09-08

Purpose: This study aims to describe recent approaches and innovations in drug design rooted in medicinal chemistry, with particular emphasis on the contributions of computational methods and the exploration of natural compounds in the development of new drug candidates.

Methodology/Approach: This literature review synthesizes current research on in silico techniques such as molecular docking, QSAR (Quantitative Structure–Activity Relationship), and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) prediction. It also examines the integration of natural product screening, synthetic compound optimization, and interdisciplinary approaches involving bioinformatics and pharmacogenomics.

Results/Findings: Computational approaches have proven effective in reducing time and costs during the early phases of drug discovery. Natural products provide structurally diverse scaffolds with promising biological activities, particularly in the development of anticancer agents. The combination of medicinal chemistry with interdisciplinary fields enhances mechanistic understanding and supports the rational design of novel therapeutics.

Conclusions: The convergence of computational innovation and interdisciplinary research significantly enhances the efficiency, precision, and scope of modern drug design, paving the way for more personalized and targeted therapies.

Limitations: This study is based solely on secondary data from published literature and does not include empirical validation through laboratory experiments.

Contribution: This review offers a comprehensive overview of emerging trends in medicinal chemistry and serves as a valuable reference for researchers, pharmaceutical scientists, and interdisciplinary teams seeking to advance drug discovery efforts.