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All Journal The Journal of Pure and Applied Chemistry Research Majalah Obat Tradisional Herb-Medicine Journal Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Jamu Indonesia Majalah Patologi Indonesia Narra J Jurnal Sehat Indonesia (JUSINDO) Indonesian Journal of Medical Chemistry and Bioinformatics Jurnal Tumbuhan Obat Indonesia Indonesian Journal of Jamu

Aryo Tedjo

Departemen Kimia Kedokteran, Fakultas Kedokteran Universitas Indonesia, Indonesia

Author-ID : 234542

Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Energy Engineering Environmental Science Health Professions Immunology & microbiology Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary Other

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Minyak Ikan dari Limbah Pengalengan Ikan Berpotensi Menurunkan Ekspresi Penanda Inflamasi pada Proses Keganasan Kolon Mencit yang Diinduksi Azoksimetan dan Dextran Sodium Sulfate Kusmardi1; Aryo Tedjo
Majalah Patologi Indonesia Vol 28 No 2 (2019): MPI
Publisher : Perhimpunan Dokter Spesialis Patologi Indonesia (IAPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (332.934 KB)

ABSTRAKStudi epidemiologi yang menghubungkan diet minyak ikan diet dengan risiko kanker kolorektal telah banyakdilaporkan walaupun hasinya tidak konsisten. Kebanyakan laporan menunjukkan adanya hubungan yangpositif. Penelitian ini dilakukan untuk memahami efek penghambatan minyak ikan yang diperoleh dari sisaproduk pengalengan ikan pada ekspresi penanda inflamasi dari preneoplasia kolorektal mencit yang diinduksioleh azoxymetane (AOM) dan dekstran natrium sulfat (DSS). Dalam penelitian ini, mencit Balb/c diinduksidengan AOM 10 mg/kg berat badan diikuti dengan pemberian 1% DSS selama seminggu. Minyak ikandiberikan secara oral dengan dosis 1,5 mg, 3 mg, dan 6 mg pada setiap mencit percobaan per hari. EkspresiPGE2 diamati pada sel epitel kripta pada mukosa kolon. Pada bulan kedua, ekspresi PGE2 menurun denganpemberian dosis sedang (3 mg/hari) dan tinggi (6 mg/hari) minyak ikan. Sedangkan pada bulan ketiga dankeempat, penurunan ekspresi PGE2 diamati karena pemberian minyak ikan dosis rendah, sedang dan tinggi(p=0,010 dan 0,005 m). Kesimpulannya, pemberian dosis sedang minyak ikan pada mencit yang diinduksiAOM/DSS telah menurunkan ekspresi PGE2 pada bulan kedua adalah dosis yang paling efektif.

Peran Sel T Memori dalam Pengendalian Pandemi Covid-19 Kusmardi; Dimas Ramadhian N; Irandi P Pratomo; Aryo Tedjo
Majalah Patologi Indonesia Vol 30 No 2 (2021): MPI
Publisher : Perhimpunan Dokter Spesialis Patologi Indonesia (IAPI)

ABSTRACTEvaluation of changes in antibody orders is a common exclusion in vaccination strategies because of the method ofanalysis. The fact that protection by antibodies produced by the Severe Acute Respiratory Syndrome Coronavirus-2(Sars-Cov-2) infection both naturally and through vaccines will decrease in less than one year, is a challenge for acountry with a large population like Indonesia to run its vaccination program. The main challenge is whether thevaccination strategy adopted will overcome the vaccine barrier and the race between the rate of vaccination and therate of viral mutation and antibody reduction. In addition to antibodies, the adaptive immune system is also run by Tcells that are included in the cell-mediated immune system (CMI) group. In patients with asymptomatic or mildsymptoms of Coronavirus 2019 (Covid-19), T and CMI responses are known to appear in some patients who are notknown to have been exposed to Sars-Cov-2 before. This evidence suggests that the adaptive catastrophe for SarsCov-2 has been acquired by ordering memory T cells and may last longer than previously thought. For countries withlarge populations, this will certainly help overcome the limitations of vaccines and the time needed to implement theirvaccination strategies.

A Simple Photometer and Chemometrics Analysis for Quality Control of Sambiloto (Andrographis paniculata) Raw Material Rudi Heryanto; Derry Permana; Aryo Tedjo; Eti Rohaeti; Mohamad Rafi; Latifah Kosim Darusman
The Journal of Pure and Applied Chemistry Research Vol 6, No 3 (2017): Edition of September - December 2017
Publisher : Chemistry Department, The University of Brawijaya

In this paper, we described the use of a light emitting diode (LED)-based photometer and chemometric analysis for quality control of king of bitter or sambiloto (Andrographis paniculata) raw material. The quality of medicinal plants is determined by their chemical composition. The quantities of chemical components in medicinal plants can be assessed using spectroscopic technique. We used an “in house” photometer to generate spectra of sambiloto. The spectra were analyzed by chemometric methods, i.e. principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA), with the aim of herbal quality classification based on the harvesting time. From the results obtained, based on thin layer chromatography analysis, sambiloto with different collection times (1, 2, and 3 months) contained different amounts of active compounds. Evaluation of sambiloto, using its spectra and chemometric analysis has successfully differentiated its quality based on harvesting time. PCA with the first two PC’s (PC-1 = 60% and PC-2 = 35%) was able to differentiate according to the harvesting time of sambiloto. Three models were obtained by PLS-DA and could be used to predict unknown sample of sambiloto according to the harvesting time

Potensi Curcumin dan 4 Herbal Empon-Empon Dalam Memodulasi Kekebalan Sel T Terhadap Covid-19 Aryo Tedjo; Dimas Noor; Rudi Heryanto
Herb-Medicine Journal: Terbitan Berkala Ilmiah Herbal, Kedokteran dan Kesehatan Vol 4, No 3 (2021): Herb-Medicine Journal Juli 2021
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/hmj.v4i3.10209

Longer immunity to Severe Acute Respiratory Syndrome-CoronaVirus-2 (SARS-CoV-2) infection is thought to occur through memory cellular responses by activity of specific T lymphocytes. However, most patients with Coronavirus disease-19 (Covid-19) experienced a decrease in the number of T lymphocytes or lymphopenia. Agents that help maintain T cell counts such as Curcumin appear to have played an important role during the Covid-19 pandemic. Curcumin is known to provide a balance between T cell effectiveness and T cell autoaggressiveness, as well as restoring memory T cell function as observed in tumor-induced mice. The mixture of 4 herbal extracts of empon-empon which is commonly used as herbal medicine, namely temulawak, ginger, lemongrass, and turmeric, is thought to have the same effect as curcumin. This is known from the tracing of a plant-protein-compound database which shows that there are not many compounds other than curcumin that can modulate T cells. It is necessary to study the role of Curcumin and a mixture of 4 herbal empon-empon in modulating T cells in cases of infection by the SARS-Cov-2 antigen.

Penentuan Aktivitas Gabungan Ekstrak Etanol Pulosari (Alyxia reinwardtii) dan Secang (Sappan Lignum) Sebagai Inhibitor Tirosinase Yang Potensial Untuk Bahan Kosmetik Melalui Pendekatan In Silico dan In Vitro Fadilah Fadilah; Aryo Tedjo; Rudi Heryanto
Jurnal Jamu Indonesia Vol. 1 No. 1 (2016): Jurnal Jamu Indonesia
Publisher : Tropical Biopharmaca Research Center, IPB University

Tirosinase atau fenol oksidase adalah enzim utama yang terlibat dalam biosintesis melanin. Untuk menghindari produksi melanin secara berlebihan pada lapisan epidermal, maka dicari senyawa yang mampu menghambat tirosinase sehingga dapat digunakan sebagai bahan pemutih kulit. Inhibitor enzim tirosinase dapat diperoleh dari senyawa bahan alam diantaranya, polifenol, kumarin, stilben sebagai pengganti senyawa sintetik. Tirosinase telah diketahui struktur molekular sehingga dapat diketahui mekanisme kerjanya melaui uji in-silico dan pembuktian secara in-vitro. Penelitian ini digunakan untuk mendeteksi keefektifan gabungan dari ekstrak etanol pulosari (Alyxia reinwardtii) dan secang (Sappan lignum) sebagai inhibitor tirosinase. Dari hasil in-silico pengujian aktivitas inhibisi tirosinase menggunakan software MOE 2008 menunjukkan bahwa dalam ekstrak etanol dari secang yaitu senyawa brazilin dan rhamnitin berturut-turut memiliki nilai ∆G -15.6582 kkal/mol, -13.3378 kkal/mol dengan inhibisi 10.021 μM, 8.331 μM dan Hdon-acc 6, 8. Sedangkan dalam ektrak etanol dari pulosari dengan senyawa scopoletin dan zhebeiresinol berturut-turut memiliki nilai ∆G -12.1661 kkal/mol; -13.8982 kkal/mol dengan inhibisi 7.279 μM; 9.104 μM dan Hdon-acc 5 dan 6. Sedangkan senyawa parameter L-DOPA dan pembanding asam kojat berturut-turut memiliki nilai ∆G -9.8247 kkal/mol; -8.8047 kkal/mol dengan inhibisi 5.592 μM; 4.976 μM dan Hdon-acc 3; 3. Dari pembuktian secara in-vitro menunjukkan bahwa uji aktivitas inhibisi tirosinase berturut-turut dari secang (Sl), pulosari (Ar), gabungan Sl dan Ar dengan pembanding asam kojat memiliki nilai IC50 berturut-turut 797.090 ppm, 1962.934 ppm, 571.352 ppm dan 93.557 ppm. Sehingga dari hasil in-silico dan in-vitro disimpulkan bahwa penggabungan antara pulosari dan secang memiliki tingkat IC50 lebih baik dibandingkan pemberian masing-masing ekstrak.

Pharmacophore Modeling, Molecular Docking, and ADMET Approach for Identification of Anti-Cancer Agents Targeting the C-Jun N-Terminal Kinase (JNK) Protein Nur Ayu Ramadanti; Linda Erlina; Rafika Indah Paramita; Aryo Tedjo; Fadillah Fadillah; Surya Dwira
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 01 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol24-iss01/391

One of the most prevalent cancers in Indonesia is breast cancer, based on Indonesia's pathological-based registration. Breast cancer is a complex, heterogeneous disease classified into hormone-receptor-positive, human epidermal growth factor receptor-2 overexpressing (HER2+) and triple-negative breast cancer (TNBC) based on histological features. Patients with HR+, HER2- Early Breast Cancer (EBC) do not experience recurrence or recurrence for a long time with currently available standard therapy [11]. However, up to 30% of patients with high-risk clinical and/or pathological features may experience a relapse in the first few years. This results in the need for research and development regarding updates in medicine both in terms of treatment and targets and drug compounds used. The c-Jun N-terminal kinase (JNK) protein functions in signaling and influences the apoptotic pathway as well as cancer cell survival. In this study, an insilico screening experiment of inhibitory compounds was carried out on the JNK protein receptor target by screening compounds and molecular docking of compounds for breast cancer therapy.Two novel herbal compounds, Mangostin and ent-Copalyl Dyphospate, have the potential to be turned into medicines that may cause apoptosis through JNK protein targets according to an in-silico-based molecular simulation technique

Metabolite Biomarker Discovery for Lung Cancer Using Machine Learning Fajarido, Ariski; Erlina, Linda; Tedjo, Aryo; Fadilah, Fadilah; Arozal, Wawaimuli
Indonesian Journal of Medical Chemistry and Bioinformatics Vol. 3, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Lung cancer is the leading cause of cancer death worldwide. About 2.1 million lung cancer patients were diagnosed in 2018, accounting for about 11.6% of all newly diagnosed cancer cases. For lung cancer, blood is the first choice as a source of screening biomarker candidates. Blood biomarkers provide a snapshot of the patient's entire body, including the primary tumor, metastatic disease, immune response, and peritumoral stroma. However, sputum sampling, bronchial lavage or aspiration, exhaled breath (EB), and airway epithelial sampling represent unique samples for lung cancer and other airway cancers as potential sources for alternative biomarkers. Metabolites are products of cell metabolism that are unique biomarkers in a disease. In this article, we aim to find metabolite biomarkers using machine learning. Metabolite data were obtained from Metabolomic workbench, while detection and identification were performed in silico. From 82 samples, controls and cancers, we found 158 metabolites and analyzed them. From the analysis, we found 3 metabolites that play an important role in lung cancer and found 1 metabolite that is the most influential. From there we found that glutamic acid is one of the best biomarker candidates we provide for detecting lung cancer. However, this simulation still needs to be improved in order to find other biomarkers that can provide a better detection of lung cancer

Moringa oleifera Leaves Ethanol Extract Inhibits HT-29 Cells and COX-2 Expression Predictably Through PPARγ Activation Tedjo, Aryo; Aprilliyani, Ifana; Kusmardi, Kusmardi; Megawati, Ajeng; Noor, Dimas Ramadhian
Majalah Obat Tradisional Vol 29, No 2 (2024)
Publisher : Faculty of Pharmacy, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/mot.89037

Colorectal cancer is the second leading cause of death among all cancer cases worldwide. Cancer cells often exhibit overexpression of cyclooxygenase-2 (COX-2), producing prostaglandin E2 (PEG2) and subsequent inflammation and neoplasia. Moringa oleifera is rich in bioactive compounds such as polyphenols, flavonoids, and saponins, known for their anti-inflammatory and antioxidant properties. This study aimed to investigate the inhibitory effects of M. oleifera leaves ethanol extract on COX-2 expression in HT-29 cells. Dried M. oleifera leaves (5 g) were ethanol-macerated for 24 hours, yielding a 10 mg ethanol extract. MTT inhibition is used for immunocytochemistry evaluation of COX-2 expression. Molecular docking of phenolic compounds from the extract on PPARγ indicated an agonistic potential. The ethanol extract of M. oleifera leaves demonstrated anticancer activity with an IC50 value of 114.8 µg/ml, with a significant reduction in COX-2 expression observed at a dose of 100 ppm, resulting in an H-score of 111.83 ± 2.21. Peroxisome proliferator-activated receptor-gamma (PPARγ) activity is thought to be the first step in suppressing COX-2 expression. Three phenolic compounds found in M. oleifera are predicted to be PPARγ agonists: rutin, naringin, and hesperidin, according to the molecular docking simulations.

In Silico Study of Acetogenin Compounds from Soursop (Annona muricata) Leaves as Sodium-Glucose Cotransporter-2 (SGLT2) Inhibitors: Studi In Silico Senyawa Acetogenin dari Daun Sirsak (Annona muricata) Sebagai Inhibitor Sodium-Glucose Cotransporter-2 (SGLT2) Tedjo, Aryo
Jurnal Tumbuhan Obat Indonesia Vol. 17 No. 1 (2024): July 2024
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/jtoi.v17i1.1156

Acetogenin derived from soursop (Annona muricata) leaves are known to have antidiabetic and anticancer activities. Nevertheless, there has been no study related to the compounds found in A. muricata leaves, such as acetogenin, as SGLT2 inhibitors. This research aims to investigate the activity of acetogenin compounds as SGLT2 inhibitors while maintaining low selectivity against SGLT1 using molecular docking methods using Molegro Virtual Docker (MVD). Based on the Rerank score, five acetogenin compounds, namely muricin H, annonacin A, annopentocin B, murihexocin C, and corossolone, are predicted to be SGLT2 inhibitors with better selectivity compared to empagliflozin. Among these five compounds, muricin H and corossolone exhibit the most similarity in interaction with amino acid residues in the SGLT2 A-chain compared to empagliflozin. In silico ADMET analysis results indicate that both compounds have absorption, distribution, and metabolism capabilities, similar to empagliflozin. However, it should be noted that both compounds are more toxic, with muricin H predicted to have hepatotoxic properties.

The Implementation of Machine Learning Algorithms for Breast Cancer Biomarker Validation in Metabolomics Studies Ratnaningayu, Nindhyana Diwaratri; Tedjo, Aryo; Sonar Soni Panigoro
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 25 No. 04 (2024): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol25-iss04/553

Breast cancer is a heterogeneous disease characterized by distinct molecular and metabolic characteristics, making its diagnostics and treatment challenging. The existence of metabolic reprogramming in breast cancer underscores the potential to identify biomarkers through metabolomics studies, offering new avenues for personalized therapeutic approaches. Machine learning algorithms are now increasingly used to uncover complex patterns in metabolomics data. A comprehensive analysis of in silico metabolomics had successfully identified 24 significant metabolites after rigorous univariate and multivariate tests. Pathway analysis highlighted the apparent involvement of glycerolphosphate in glycerophospholipid and glycerolipid metabolism, indicating its potential role in breast cancer pathology. Validation of these 24 metabolites using machine learning algorithms provided superior results, with Neural Network achieving an AUC of 0.979 and a precision of 93%, Logistic Regression showing an AUC of 0.945 and a precision of 95.7%, as well as Random Forest reporting an AUC of 0.974 and a precision of 95.7% in predictive performance. These findings demonstrate the remarkable ability of machine learning to improve biomarker validation accuracy in metabolomics, facilitating better diagnostic strategies for breast cancer.

Co-Authors Ade Arsianti Akmal P. Suprapto Anis Karuniawati Anwar S. Ibrahim Anwar S. Ibrahim Anwar S. Ibrahim Anwar S. Ibrahim Aprilliyani, Ifana Azizah, Norma N. Berna Elya Dendi Priyanto Derry Permana Dimas Noor Dimas Ramadhian N Dondin Sajuthi Erfi Prafiantini Erlina, Linda Eti Rohaeti Fadilah Fadilah Fadilah Fadilah, Fadilah Fadillah Fadillah Fajarido, Ariski Fajrin, Ajeng M. Fariska, Andrias Bayu Hamdani Zain Hashim, Najihah BM. Heryanto, Rudy Irandi Putra Pratomo Kezia, Immanuelle Kusmardi Kusmardi Kusmardi1 Latifah K. Darusman Latifah Kosim Darusman Linda Erlina Linda Erlina Megawati, Ajeng Mohamad Rafi Noor, Dimas Noor, Dimas Ramadhian Nur Ayu Ramadanti Peni Kistijani Samsuria Prawoto Prawoto Rafika Indah Paramita Ramadanti, Nur A. Ratnaningayu, Nindhyana Diwaratri Rino Patiatta Rosmalena, Rosmalena Rudi Heryanto Siti Nurbaya Sonar Soni Panigoro Subari A. Riyanto Subari A. Riyanto Surya Dwira Surya Dwira Wawaimuli Arozal

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