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Malacca Pharmaceutics
Published by PT. Heca Sentra Analitika
ISSN : -     EISSN : 29881064     DOI : https://doi.org/10.60084/mp
Core Subject : Health, Science, Agriculture,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Immunology & microbiology Medicine & Pharmacology
Malacca Pharmaceutics is a premier interdisciplinary platform dedicated to fostering the exchange of cutting edge research and ideas in the rapidly evolving fields of pharmaceutical science and technology. Our mission is to provide a comprehensive and authoritative forum for scientists, researchers, and practitioners from diverse disciplines to share and advance their knowledge in the development, optimization, and application of innovative therapeutic strategies. The scope of the Malacca Pharmaceutics Journal encompasses a wide range of topics, including, but not limited to:Pharmaceutical formulation, delivery and controlled-release systems for drugs, vaccines, and biopharmaceuticals, pharmaceutical process, engineering, biotechnology, and nanotechnology, devices, cells, molecular biology, and materials science related to drugs and drug delivery pharmacogenetics and pharmacogenomics, biopharmaceutics,nanomedicine, drug targeting, drug design, pharmacokinetics, toxicokinetics, pharmacodynamics, drug discovery, drug design, medicinal chemistry, combinatorial chemistry, SAR, structure-property correlations, molecular modeling, pharmacophore, and bioinformatics
Arjuna Subject : Pharmacology, Toxicology and Pharmaceutics - Ilmu Farmasi
Articles 5 Documents
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Search results for , issue "Vol. 3 No. 2 (2025): September 2025" : 5 Documents clear
Antibacterial Potential of Geothermal Plant Extracts from Jaboi Crater, Indonesia: A Thin Layer Chromatography-Bioautography Approach Khairan, Khairan; Mubaraq, Farhil; Maulydia, Nur Balqis; Awang, Khalijah; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 3 No. 2 (2025): September 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i2.312

Abstract

Antimicrobial resistance (AMR) poses an urgent global health concern, prompting the need for alternative therapeutic agents. This study evaluated the antimicrobial potential of ethyl acetate extracts from five medicinal plant species (Memecylon edule, Garcinia dioica, Syzygium sp., Memecylon caeruleum, and Aporosa octandra) collected from the geothermal Jaboi Crater in Aceh, Indonesia. Phytochemical profiling was performed using thin layer chromatography (TLC), and antimicrobial activity was assessed via TLC-bioautography against Escherichia coli, Staphylococcus aureus, and Candida albicans. The results revealed the presence of phenolic and terpenoid compounds, with antibacterial activity observed only against E. coli. No inhibition was detected against S. aureus or C. albicans. The study highlights the selective antimicrobial potential of geothermal plant extracts and underscores the relevance of bioautography as a rapid screening tool. While preliminary, these findings support further investigation into geothermal flora as a source of antibacterial compounds and call for advanced studies to isolate active constituents and explore their mechanisms of action.
Network Pharmacology Identifies AKT1, SRC, and STAT3 as Therapeutic Targets of Tempeh-Derived Peptides in Breast Cancer Takawaian, Agrita Feisilia; Antasionasti, Irma; Tallei, Trina Ekawati
Malacca Pharmaceutics Vol. 3 No. 2 (2025): September 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i2.331

Abstract

Breast cancer remains a major cause of mortality among women, particularly the aggressive subtypes HER2-positive and triple-negative breast cancer (TNBC). Fermented foods such as tempeh contain bioactive peptides with potential therapeutic properties, including anticancer activity, yet their molecular mechanisms in cancer remain unclear. This study aimed to investigate the potential of tempeh-derived peptides as anti-breast cancer agents using a network pharmacology approach integrated with molecular docking. Tempeh peptides were collected from previously published literature. Target genes of tempeh-derived peptides were predicted and compared with breast cancer–associated genes to identify overlapping candidates. These were analyzed through protein–protein interaction networks and subjected to functional and pathway enrichment to uncover key molecular mechanisms. The results showed that tempeh-derived peptides are closely linked to key oncogenic pathways, including PI3K-Akt, ErbB, MAPK, JAK-STAT, and general cancer signaling. Protein–protein interaction network analysis highlighted AKT1, SRC, STAT3, and PIK3CA as central hub proteins with well-established roles in regulating proliferation, migration, angiogenesis, and survival. AKT1 is strongly connected to HER2-driven signaling, SRC is involved in both HER2+ and therapy-resistant TNBC, STAT3 is critically implicated in TNBC biology, and PIK3CA functions as a pivotal upstream regulator of AKT1, underscoring their therapeutic significance. Molecular docking confirmed strong binding affinities of peptides such as Trp-Met-Phe-Asp-Trp, Pro-Phe-Tyr-Phe, and Trp-Met-Gly-Pro-Tyr to these hubs, suggesting disruption of phosphorylation-dependent activation and downstream oncogenic cascades. These findings support the potential of tempeh-derived peptides as multi-target modulators in aggressive breast cancer subtypes and highlight the need for experimental validation to advance their therapeutic application.
Antioxidant Activity of Theobroma cacao L. Husk Ethyl Acetate Fraction in Peel-Off Mask Formulation Measured by the DPPH Assay Rizki, Risnanda Farzia; Aisya, Mauly Rahadatul; Khairan, Khairan
Malacca Pharmaceutics Vol. 3 No. 2 (2025): September 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i2.336

Abstract

Cocoa fruit (Theobroma cacao) is one of Indonesia's most important commodities and is widely used as a raw material in various industries. Until now, cocoa fruit has primarily been used for its seeds, while its skin has not been widely explored. This study aims to formulate a peel-off mask from cacao husk and determine its antioxidant activity. The antioxidant test method used was the DPPH (2,2-diphenyl-1-picrylhydrazyl) assay. Analysis results showed that the ethyl acetate fraction contained secondary metabolites, including flavonoids, tannins, and steroids. However, the peel-off mask formulation made with a combination of the ethyl acetate fraction of cocoa husk and polyvinyl alcohol was unstable due to changes in its characteristics during storage. Nevertheless, the resulting peel-off mask exhibited relatively strong antioxidant activity, with IC₅₀ values of 6.819 ppm for the ethyl acetate fraction and 11.596 ppm for the mask. These results suggest that cocoa husk contains bioactive compounds that support strong antioxidant activity. Therefore, cocoa husk has great potential as an active ingredient in cosmetic formulations. However, further formula optimization is needed to improve the formulation's stability while maintaining optimal antioxidant activity.
Antioxidant Potential of Ethanol Extracts from Zingiberaceae Plant Leaves Maulana, Addrian; Thahar, Aufa Sabrina; Khairan, Khairan
Malacca Pharmaceutics Vol. 3 No. 2 (2025): September 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i2.337

Abstract

The development of disease related to oxidative stress must be addressed immediately. An approach is to identify natural antioxidant compounds in plants commonly used by communities. This study measured the potential antioxidant activity of ethanol extracts from three Zingiberaceae species leaves: ginger (Zingiber officinale var. Amarum), turmeric (Curcuma domestica Val), and temulawak (Curcuma xanthorrhiza). Phytochemical profiling was performed using specific reagents, FT-IR analysis, and GC-MS, while antioxidant activity was evaluated using DPPH and ABTS methods. The result showed the presence of saponins, flavonoids, steroids, alkaloids, tannins, fatty acid derivatives, and phytol. The IC50 values of the extracts, determined using the DPPH method, were found to be 28.75 ppm for ginger, 65.86 ppm for turmeric, and 51.41 ppm for temulawak. Using the ABTS method, the IC50 values were 35.4 ppm for ginger, 75.9 ppm for turmeric, and 58.9 ppm for temulawak. The strongest antioxidant activity of ethanol leaf extracts from Zingiberaceae family was found in ginger leaf extract with the lowest value of IC50. These results provide preliminary evidence that Zingiberaceae leaves, which are less studied compared to their rhizomes, possess notable antioxidant potential. Further studies, including the isolation of active compounds and in vivo evaluation, are required to validate these findings and explore their possible applications in the future.
Interpretable Machine Learning QSAR Models for Classification and Screening of VEGFR-2 Inhibitors in Anticancer Drug Discovery Noviandy, Teuku Rizky; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 3 No. 2 (2025): September 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i2.339

Abstract

Cancer remains a major global health burden, with angiogenesis playing a central role in tumor growth and progression. Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) is a key mediator of angiogenesis and an attractive therapeutic target, but existing inhibitors are limited by reduced efficacy, toxicity, and resistance, creating a need for more effective predictive models in drug discovery. In this study, an interpretable machine learning based QSAR approach was developed using a curated dataset of 10,221 VEGFR-2 inhibitors from ChEMBL represented by 164 molecular descriptors. Four algorithms, kNN, AdaBoost, Random Forest, and XGBoost, were compared, and XGBoost achieved the best results with an accuracy of 83.67 percent, sensitivity of 91.38 percent, specificity of 71.73 percent, F1-score of 87.17 percent, and AUC of 0.9009. Model interpretation with LIME identified molecular descriptors related to hydrogen bonding, electrostatics, and lipophilicity as key contributors to activity. These results indicate that interpretable ensemble models can combine strong predictive performance with mechanistic insights, supporting rational design and optimization of novel VEGFR-2 inhibitors for anticancer therapy.

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