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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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Evaluating the Efficacy of Clerodendrum minahassae Ethanol Extract on Insulin Regulation in Diabetic Wistar Rats Rumangu, Chrisa P.; Fatimawali, Fatimawali; Manampiring, Aaltje Ellen; Kepel, Billy Johnson; Budiarso, Fona Dwiana Hermina; Bodhi, Widdhi
Malacca Pharmaceutics Vol. 2 No. 1 (2024): March 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i1.137

Abstract

Leilem plant (Clerodendrum minahassae Teisjm & Binn.) from the genus Clerodendrum has the potential as antidiabetic, antihypertensive, anti-inflammatory, antioxidant, antimalarial, antitumor, antidiarrheal, antimicrobial and antihyperlipidemic. This study aimed to see the effect of ethanol extract of Clerodendrum minahassae (CM) leaves on increasing insulin levels in diabetic Wistar rats induced with streptozotocin. This study was conducted in vivo, using 20 rats as experimental animals. The experimental animals were divided into four groups, namely the negative control group (Na-CMC 0.5%), the ethanol extract group of leilem leaves 250 mg and 500 mg, and the positive control group (glibenclamide) as a comparison. Each experimental animal was induced streptozotocin intraperitoneally; then, each solution was given for 14 days according to the test group. After the treatment, the animals were terminated for blood collection; the blood was then centrifuged to obtain blood plasma serum. Blood plasma serum was measured by the ELISA Kit (Rat/Mouse Insulin) method, and then the results were read on a spectrophotometric device. The results of the sample insulin concentration obtained showed that 250 mg/kgBW and 500 mg/kgBW of the CM ethanol extract group could increase insulin levels in diabetic Wistar rats, the same as the positive control group glibenclamide. In contrast, the Na-CMC 0.5% as a negative control group did not show a significant increase in insulin levels. Leilem leaves can be developed for further research on their antidiabetic activity both in vitro, in vivo, and in silico, as well as their toxicity.
Probiotics and Their Role in Decreasing Diarrhea Prevalence in the Elderly Population: A Comprehensive Meta-Analysis Muliana, Devika; Mulia, Vera Dewi; Suardi, Hijra Novia; Puspita, Nanda Ayu; Suryawati, Suryawati
Malacca Pharmaceutics Vol. 2 No. 1 (2024): March 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i1.143

Abstract

Diarrhea is an atypical state of the digestive system characterized by a soft or watery texture in bowel movements. Antibiotic-related diarrhea is common in the elderly due to extensive antibiotic use. Probiotics are vital microorganisms that support the intestinal flora and reduce bacterial colonization in the intestinal wall. This study aimed to assess the effectiveness, type, and dose of probiotics for diarrhea in the elderly. A systematic review with meta-analysis was conducted using PubMed, ScienceDirect, and Google Scholar. Seven records with a total of 2,087 participants were included. A quantitative analysis was carried out using Review Manager version 5 software. A meta-analysis was conducted to assess the frequency of diarrhea. The results showed that using probiotics significantly reduced the risk of antibiotic-related diarrhea 0.53 times compared to the placebo administration (OR 0.53; CI 95% 0.29 to 0.98; I2 = 70%). The type of probiotics frequently given was the genera of Lactobacillus, Bifidobacterium, and Streptococcus, with consumption durations varying from 3 days to a maximum of 4 weeks. The dose of probiotics ranged from a minimum of 1.0 × 10⁶ CFU to a maximum dose of 2 × 10¹⁰ CFU. To conclude, probiotic administration is more effective than placebo in reducing the risk of antibiotic-related diarrhea in the elderly.
The Potent Antimicrobial Spectrum of Patchouli: Systematic Review of Its Antifungal, Antibacterial, and Antiviral Properties Kemala, Pati; Idroes, Rinaldi; Khairan, Khairan; Ramli, Muliadi; Tallei, Trina Ekawati; Helwani, Zuchra; Rahman, Sunarti Abd
Malacca Pharmaceutics Vol. 2 No. 1 (2024): March 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i1.156

Abstract

ntention towards natural essential oils from medicinal plants has increased rapidly over the past decade as these oils have antimicrobial and antioxidant properties against various chronic diseases. One essential oil source with antimicrobial properties is the essential oil from Pogostemon cablin (Blanco) Benth. This review aims to provide information on using patchouli oil as an antimicrobial against bacterial, fungal, and viral pathogens in the last five years. There were 37 articles found in the PUBMED database by June 15, 2023. After searching, 6 of them were duplicates. A total of 2 papers were inaccessible, 4 were not research articles, and five were excluded because they were irrelevant to the scope of this study. This review shows that research related to patchouli as an antimicrobial in the last five years involves Pogostemon cablin leaf samples as silver nanoparticle bioreductors. Patchouli oil is used in membrane, nanocomposite film, and starch hydrogel manufacturing. Patchouli oil is a prestigious antimicrobial agent because it can fight numerous pathogenic microbes from bacteria, fungi, and viruses.
A Comprehensive Network Pharmacology Study on the Diabetes-Fighting Capabilities of Yacon Leaf Extract Wawo, Arsianita Ester; Simbala, Herny Emma Inonta; Fatimawali, Fatimawali; Tallei, Trina Ekawati
Malacca Pharmaceutics Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i2.161

Abstract

Indonesia ranks fourth in the world for the number of diabetes mellitus (DM) sufferers. DM is a group of metabolic disorders characterized by hyperglycemia due to insulin abnormalities. This research employs Network Pharmacology analysis to examine the target proteins and pharmacological network profiles predicted to be influenced by compounds in the leaves of Smallanthus sonchifolius (yacon) for their anti-diabetic effects. Gas chromatography-mass spectrometry (GC-MS) identified 41 secondary metabolite compounds in yacon leaves, seven of which have a Pa value > 0.5. Compound C28 has the highest Pa value as an insulin promoter, at 0.662. A total of 129 target proteins were found for the secondary metabolite compounds in yacon leaves, and 5,112 target proteins were identified for Type 2 Diabetes Mellitus (T2DM). The intersection analysis between yacon leaves and T2DM revealed 32 common proteins. Network analysis highlighted 10 top proteins: ESR1, PPAR-α, HMGCR, CYP19A1, PPARD, PTP1N, GRIN2B, FYN, AR, and SHBG. Among these, PPAR-α shows great potential and promising prospects as a target for further exploration. Considering several parameters, it can be concluded that PPAR-α is a promising protein and a potential target for new drug candidates for T2DM.
Network Pharmacology Approach to Understanding the Antidiabetic Effects of Pineapple Peel Hexane Extract Pendong, Christa Hana Angle; Suoth, Elly Juliana; Fatimawali, Fatimawali; Tallei, Trina Ekawati
Malacca Pharmaceutics Vol. 2 No. 1 (2024): March 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i1.162

Abstract

The increased interest in exploring alternative treatments for type 2 diabetes mellitus is accompanied by a rise in the prevalence of type 2 diabetes mellitus. Pineapple peel is one of the by-products of pineapple fruit and is known to possess potential for anti-diabetic activity. In this study, the n-hexane extract of pineapple peel was analyzed using network pharmacology methods to ascertain its potential in treating type 2 diabetes mellitus. The GC-MS analysis of the n-hexane extract of pineapple peel revealed the presence of 42 compounds, with 8 of them considered safe as they met the Lipinski Rule of Five criteria for drug-likeness and were classified as safe with toxicity levels in classes IV and V. The pineapple peel extract targeted 55 proteins related to type 2 diabetes mellitus (DMT2), potentially affecting DMT2 through the AGE-RAGE pathway in diabetes complications and insulin resistance. Network pharmacology analysis identified five genes targeted by pineapple peel, namely MAPK1, JAK2, MAPK8, PRKCD, and PPARA. Among these genes, MAPK1 exhibited a higher overall score than the others. Apart from its role in diabetes, MAPK1 is also implicated in cancer.
Exploring the Medicinal Potential of Blumea balsamifera: Insights from Molecular Docking and Molecular Dynamics Simulations Analyses Maulydia, Nur Balqis; Khairan, Khairan; Tallei, Trina Ekawati; Salaswati, Salaswati; Musdalifah, Annisa; Nabila, Fiki Farah; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 2 No. 1 (2024): March 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i1.168

Abstract

Blumea balsamifera from the Ie-Jue geothermal area in Aceh Province, Indonesia, has been reported to have a variety of secondary metabolites. However, there is limited information about the activity of these chemical metabolites from B. balsamifera. The aim of this study is to evaluate the therapeutic potential of these compounds using molecular docking and molecular dynamics simulations. Six selective compounds were thoroughly evaluated using molecular docking techniques for their inhibitory effects on both Coronavirus protease and human interleukin receptors. Additionally, druglikeness assessments based on the Lipinski rule of five were performed to evaluate these six ligands. Our results show that stigmasterol, a key component of B. balsamifera, has demonstrated low binding free energy values across four receptors. Furthermore, molecular dynamics simulations confirmed the stability of the top ligand-receptor complex, particularly stigmasterol-1IRA, based on five parameters, indicating its stability as an inhibitor. This research highlights the potential of stigmasterol as a therapeutic agent derived from medicinal plants of B. balsamifera and underscores the value of our molecular approach in identifying opportunities for pharmaceutical development.
Hybrid Handwash with Silver Nanoparticles from Calotropis gigantea Leaves and Patchouli Oil: Development and Properties Salsabila, Indah; Khairan, Khairan; Kemala, Pati; Idroes, Ghifari Maulana; Isnaini, Nadia; Maulydia, Nur Balqis; El-Shazly, Mohamed; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i2.206

Abstract

When washing hands, handwashing is one way to prevent diseases caused by bacteria such as Staphylococcus aureus and Escherichia coli, the most common bacteria that can cause infections. The production of handwash utilizing silver nanoparticles as an active antibacterial agent remains a relatively infrequent practice. The synthesis of silver nanoparticles from the leaves of Calotropis gigantea, which grows in the geothermal area of Ie Seu-um Aceh Besar, has been carried out using the green synthesis method and hybrid green synthesis with patchouli oil. Handwash with active ingredients such as silver nanoparticles was successfully formulated, evaluated, and tested against S. aureus and E. coli. The organoleptic characteristics, pH, viscosity, foam height measurements, density, irritation, and antibacterial activity against S. aureus and E. coli were evaluated. The results showed that the organoleptic properties of the handwash with silver nanoparticles were not changed during a 30-day storage period, with pH values in the range of 9.7-10.3, and did not cause irritation upon using silver nanoparticle handwash. The best formula for handwashing with silver nanoparticles in inhibiting the growth of S. aureus and E. coli bacteria was F2, with inhibition zones of 12.9 ± 2.85 mm and 10.95 ± 0.8 mm, respectively. The formulated handwash with silver nanoparticles met the requirements of good liquid soap according to the Indonesian National Standard (SNI) with potent antibacterial activity.
Therapeutic Potential of Aceh's Syzygium polyanthum in Reducing Uric Acid in Rattus Norvegicus Nasrullah, Nasrullah; Siregar, Masra Lena; Suryawati, Suryawati
Malacca Pharmaceutics Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i2.210

Abstract

This research aims to evaluate the anti-hyperuricemic activity of Syzygium polyanthum ethanolic extract in hyperuricemic male rats (Rattus norvegicus) induced by liver juice.  A total of 25 animals were divided into five groups: a negative control group, a positive control group, and three treatment groups receiving S. polyanthum extract at doses of 150, 200, and 250 mg/kg body weight, respectively. The result showed that the dose of 250 mg/kg body weight resulted in the highest decrease of uric acid plasma, measuring 3.44 ± 2.03 mg/dL. This reduction is comparable to the effect of allopurinol, which showed a decrease of 3.70 ± 1.54 mg/dL. A minimum dose-dependent activity was observed. To conclude, the administration of ethanolic extract of S. polyanthum for 14 days significantly reduced uric acid levels. Further exploration of higher doses or a long-term treatment period to enhance its effectiveness is needed.
Application of Ensemble Machine Learning Methods for QSAR Classification of Leukotriene A4 Hydrolase Inhibitors in Drug Discovery Noviandy, Teuku Rizky; Idroes, Ghifari Maulana; Mohd Fauzi, Fazlin; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i2.217

Abstract

Inflammatory diseases such as asthma, rheumatoid arthritis, and cardiovascular conditions are driven by overproduction of leukotriene B4 (LTB4), a potent inflammatory mediator. Leukotriene A4 hydrolase (LTA4H) plays a critical role in converting leukotriene A4 into LTB4, making it a prime target for drug discovery. Despite ongoing efforts, developing effective LTA4H inhibitors has been challenging due to the complex binding properties of the enzyme and the structural diversity of potential inhibitors. Traditional drug discovery methods, like high-throughput screening (HTS), are often time-consuming and inefficient, prompting the need for more advanced approaches. Quantitative Structure-Activity Relationship (QSAR) modeling, enhanced by ensemble machine learning techniques, provides a promising solution by enabling accurate prediction of compound bioactivity based on molecular descriptors. In this study, six ensemble machine learning methods—AdaBoost, Extra Trees, Gradient Boosting, LightGBM, Random Forest, and XGBoost—were employed to classify LTA4H inhibitors. The dataset, comprising 636 compounds labeled as active or inactive based on pIC50 values, was processed to extract 450 molecular descriptors after feature engineering. The results show that the LightGBM model achieved the highest classification accuracy (83.59%) and Area Under the Curve (AUC) value (0.901), outperforming other models. XGBoost and Random Forest also demonstrated strong performance, with AUC values of 0.890 and 0.895, respectively. The high sensitivity (95.24%) of the XGBoost model highlights its ability to accurately identify active compounds, though it exhibited slightly lower specificity (61.36%), indicating a higher false-positive rate. These findings suggest that ensemble machine learning models, particularly LightGBM, are highly effective in predicting bioactivity, offering valuable tools for early-stage drug discovery. The results indicate that ensemble methods significantly enhance QSAR model accuracy, making them viable for identifying promising LTA4H inhibitors, potentially accelerating the development of anti-inflammatory therapies.
QSAR Modeling for Predicting Beta-Secretase 1 Inhibitory Activity in Alzheimer's Disease with Support Vector Regression Noviandy, Teuku Rizky; Idroes, Ghifari Maulana; Tallei, Trina Ekawati; Handayani, Dian; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v2i2.226

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline, with the accumulation of β-amyloid (Aβ) plaques playing a key role in its progression. Beta-Secretase 1 (BACE1) is a crucial enzyme in Aβ production, making it a prime therapeutic target for AD treatment. However, designing effective BACE1 inhibitors has been challenging due to poor selectivity and limited blood-brain barrier permeability. To address these challenges, we employed a machine learning approach using Support Vector Regression (SVR) in a Quantitative Structure-Activity Relationship (QSAR) model to predict the inhibitory activity of potential BACE1 inhibitors. Our model, trained on a dataset of 7,298 compounds from the ChEMBL database, accurately predicted pIC50 values using molecular descriptors, achieving an R² of 0.690 on the testing set. The model's performance demonstrates its utility in prioritizing drug candidates, potentially accelerating drug discovery. This study highlights the effectiveness of computational approaches in optimizing drug discovery and suggests that further refinement could enhance the model’s predictive power for AD therapeutics.

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