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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 30 Documents
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Phytochemical Composition and Antioxidant Properties of Avocado (Persea americana) Seed Extract from Aceh, Indonesia: Implications for Antihyperlipidemic Use in Postmenopausal Women Nurbaiti, Nurbaiti; Fitri, Yulia; Fitriani, Fitriani; Humaira, Wardati; Triwibowo, Cecep
Malacca Pharmaceutics Vol. 3 No. 1 (2025): March 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i1.228

Abstract

Avocado (Persea americana) is widely recognized for its high antioxidant capacity. Its rich phytochemical composition is crucial in mitigating oxidative stress and managing chronic conditions such as cardiovascular disease and hyperlipidemia. This study aimed to investigate the phytochemical profile, antioxidant activity, and antihyperlipidemic potential of ethanol extracts derived from avocado seeds. Phytochemical screening and Gas Chromatography-Mass Spectrometry (GC-MS) analysis were conducted to identify key chemical constituents, while antioxidant activity was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. In addition, in-silico techniques were employed to evaluate the antihyperlipidemic potential of the bioactive compounds. Phytochemical analysis revealed a variety of bioactive compounds, including volatile compounds, steroids, and fatty acids, contributing to the extract's biological activity. The extract demonstrated strong antioxidant capacity, with an IC50 value of 20.83 ppm, indicating potent free radical scavenging ability. GC-MS analysis identified significant compounds such as Undec-10-ynoic acid, tetradecyl ester, and 9,12,15-Octadecatrienoic acid, 2-(acetyloxy)-1-[(acetyloxy)methyl] ethyl ester, which were further analyzed through molecular docking studies. These studies indicated their potential as inhibitors of hyperlipidemia-associated proteins, with binding energy values exceeding -6 kcal/mol. Moreover, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis demonstrated favorable pharmacokinetic profiles, including good absorption and low toxicity, positioning these compounds as promising candidates for therapeutic development. The findings of this study underscore the potential of avocado seed extract as a natural source of antioxidants and antihyperlipidemic agents. The identified bioactive compounds offer a promising therapeutic strategy for managing oxidative stress and lipid disorders, particularly in populations at heightened risk, such as postmenopausal women.
Bioactive Phytochemicals from Memecylon edule: Targeting Planktonic and Biofilm States of Pseudomonas aeruginosa Suryawati, Suryawati; Idroes, Rinaldi; Hertiani, Triana; Khairan, Khairan
Malacca Pharmaceutics Vol. 3 No. 1 (2025): March 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i1.258

Abstract

The rise in antimicrobial resistance has prompted the search for potent antimicrobial agents, with plants from unique environments, such as geothermal areas, offering potential due to their diverse phytochemical profiles. This study evaluated the antiplanktonic and antibiofilm activity of M. edule fractions from the geothermal area, Jaboi, Sabang. Crude extracts of M. edule were sequentially fractionated using hexane, ethyl acetate, and ethanol. The resulting fractions were further analyzed for their phytochemical content and antiplanktonic and antibiofilm activities. The ethyl acetate fraction demonstrated superior antiplanktonic and antibiofilm activities compared to other fractions, inhibiting 50% of Pseudomonas aeruginosa planktonic and biofilm formation at a concentration of 10 mg/mL. The most potent fraction exhibited the phenolic content, 672.84 mg GAE/g extract, surpassing the other fractions. The GC-MS analysis shows the presence of pyrogallol, hexadecanoic acid, cedran-diol, and sitosterol. These findings highlight the potential of the ethyl acetate fraction of M. edule as a source of bioactive compounds with promising antiplanktonic and antibiofilm properties, laying the groundwork for future research into its therapeutic applications against biofilm-associated infections.
Evaluation of Machine Learning Methods for Identifying Carbonic Anhydrase-II Inhibitors as Drug Candidates for Glaucoma Noviandy, Teuku Rizky; Imelda, Eva; Idroes, Ghazi Mauer; Suhendra, Rivansyah; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 3 No. 1 (2025): March 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i1.271

Abstract

Glaucoma is a leading cause of irreversible blindness, primarily managed by lowering intraocular pressure (IOP). Carbonic Anhydrase-II (CA-II) inhibitors play a crucial role in this treatment by reducing aqueous humor production. However, existing CA-II inhibitors often suffer from poor selectivity, side effects, and limited bioavailability, highlighting the need for more efficient and targeted drug discovery approaches. This study uses machine learning-driven Quantitative Structure-Activity Relationship (QSAR) modeling to predict CA-II inhibition based on molecular descriptors, significantly enhancing screening efficiency over traditional experimental methods. By evaluating multiple machine learning models, including Support Vector Machine, Gradient Boosting, and Random Forest, we identify SVM as the most effective classifier, achieving the highest accuracy (83.70%) and F1-score (89.36%). Class imbalance remains challenging despite high sensitivity, necessitating further improvements through resampling and hyperparameter optimization. Our findings underscore the potential of machine learning-based virtual screening in accelerating CA-II inhibitor identification and advocate for integrating AI-driven approaches with traditional drug discovery techniques. Future directions include deep learning enhancements and hybrid machine learning-docking frameworks to improve prediction accuracy and facilitate the development of more potent and selective glaucoma treatments.
Appraisal of Antioxidant Potential in Broccoli Microgreens under Different Drying Techniques Utilizing In Vitro and in Silico Methods Tallei, Trina Ekawati; Wungouw, Herlina Ineke Surjane; Kepel, Billy Johnson; Fatimawali, Fatimawali; Celik, Ismail; Niode, Nurdjannah Jane; Barasarathi , Jayanthi
Malacca Pharmaceutics Vol. 3 No. 1 (2025): March 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i1.259

Abstract

Broccoli microgreens, rich in bioactive compounds, offer health benefits aligned with SDG 3: “Good Health and Well-Being.” Their antioxidants combat oxidative stress tied to chronic diseases, but drying can affect their activity. This study assessed the antioxidant capacities of fresh, microwave-dried, and air-fryer-dried broccoli microgreens using in vitro (DPPH assay) and in silico (molecular docking and dynamics) methods. The microgreens were cultivated under controlled conditions and dried using microwave and air-fryer techniques. Antioxidant activity was evaluated using the DPPH assay using ethanolic extracts. The bioactive compounds of fresh microgreens, detected through GC-MS, were analyzed in silico to evaluate their interactions with the target proteins CYP2C9 and NOX2. The findings revealed that air-fryer-dried microgreens demonstrated the highest DPPH activity, followed by fresh microgreens, while microwave-dried samples exhibited the lowest activity. GC-MS analysis of fresh samples revealed the presence of various compounds, including acids, ketones, sulfides, heterocycles, alcohols, esters, aromatic compounds, phthalate ester, and aldehydes. Molecular docking revealed strong interactions of certain compounds in fresh samples and CYP2C9 and NOX2, suggesting therapeutic potential against oxidative stress. Molecular dynamics simulations (MDS) showed stable binding for the CYP2C9-Methyl myristate complex, while the NOX-(Z)-1,2-Diphenylethene complex displayed weaker stability. In conclusion, broccoli microgreens show potential in mitigating oxidative stress, with air-fryer drying slightly enhancing their antioxidant activity. The antioxidant capacity of fresh microgreens is comparable to that of air-fryer-dried microgreens. In silico analyses demonstrate stable interactions between compounds in fresh microgreens and key proteins implicated in oxidative stress.
Targeting Prostate Cancer with Rambutan Peel-Derived Compounds via Network Pharmacology Utami, Wulandari Putri; Tallei, Trina Ekawati; Turalaki, Grace Lendawati Amelia; Tendean, Lydia Estelina Naomi; Kaseke, Martha Marie; Purwanto, Diana Shintawati
Malacca Pharmaceutics Vol. 3 No. 1 (2025): March 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v3i1.262

Abstract

Prostate cancer is a prevalent malignancy in men, originating in the prostate gland and often driven by genetic alterations and hormonal dysregulation. Rambutan (Nephelium lappaceum L.) peel, a byproduct of fruit consumption, has demonstrated potential anticancer activity. This study employed a network pharmacology-based in silico approach to evaluate the therapeutic potential of rambutan peel extract in prostate cancer treatment. Bioactive compounds were identified through database searches, and their biological activities were predicted using PASS Online. Pharmacokinetic and toxicity profiles were assessed using ADMETLab 3.0 and Protox 3.0 to evaluate safety and drug-like properties. Potential target proteins were identified via SwissTargetPrediction and GeneCards, while protein-protein interaction networks were constructed using STRING. The pharmacological networks were visualized using Cytoscape to elucidate molecular mechanisms of action. The analysis identified 28 bioactive compounds in rambutan peel extract, with 11 demonstrating activity against prostate cancer (Pa > 0.5). These compounds were deemed safe based on Lipinski's Rule of Five (Ro5) and categorized within toxicity classes V and VI. Rambutan peel extract was found to target 501 proteins associated with prostate cancer, including key pathways involved in resistance to EGFR tyrosine kinase inhibitors. Network pharmacology analysis highlighted several key target genes, including SRC, GNAI1, PIK3CA, PIK3CD, MAPK1, MAPK3, AKT1, GNAI3, PRKCA, and HSP90AA1. Among these, SRC exhibited the highest centrality score, underscoring its pivotal role in disrupting tumorigenic and metastatic signaling pathways, suppressing cancer cell proliferation, and enhancing therapeutic responses. These findings suggest that rambutan peel extract holds promise as a natural therapeutic agent for prostate cancer, warranting further experimental and clinical validation.
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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