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All Journal Majalah Kedokteran Bandung Althea Medical Journal Indonesian Journal of Pharmaceutical Science and Technology Global Medical and Health Communication Jurnal Media Gizi Indonesia (MGI) Molecular and Cellular Biomedical Sciences (MCBS) AcTion: Aceh Nutrition Journal Jurnal Gizi Klinik Indonesia Jurnal Pendidikan dan Pelayanan Kebidanan Indonesia (Indonesian Journal of Education and Midwifery Care) Journal of the Indonesian Medical Association : Majalah Kedokteran Indonesia Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Health Sains Jurnal Ilmu Faal Olahraga Indonesia Penelitian Gizi dan Makanan (The Journal of Nutrition and Food Research)
Gaga Irawan Nugraha
Fakultas Kedokteran Universitas Padjadjaran
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Dentistry Economics, Econometrics & Finance Education Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Veterinary

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Journal : Indonesian Journal of Pharmaceutical Science and Technology

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Machine Learning Based QSAR Model for Screening PPAR-gamma Stimulator Nirwana, Edwin; Nugraha, Gaga Irawan; Ariyanto, Eko Fuji; Sanjaya, Ardo
Indonesian Journal of Pharmaceutical Science and Technology Vol 12, No 3 (2025)
Publisher : Indonesian Journal of Pharmaceutical Science and Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/ijpst.v12i3.46916

Abstract

Type-2 diabetes (DM2) is still growing into a global problem. Decreased insulin sensitivity is the main mechanism causing DM2. PPAR-gamma has been shown to have a direct relationship with insulin sensitivity. This study aimed to develop a machine-learning model to evaluate phytochemical compounds’ activity as a PPAR-gamma agonist. The dataset used for modeling was procured from the ChEMBL database. A total of 3668 substances were retained after null and duplicate values were removed. Canonical SMILES were collected and described to generate an extended connectivity fingerprint, which was then used to predict the pEC50 value. The machine learning-generated model was then used to predict 2846 phytochemical compounds from the KEGG database. This study uses the Light gradient-based machine learning method. The performance of the model was evaluated using Root Mean Square Error (RMSE) and R-square (R2) of 0.63 and 0.73, respectively. Afterward, the model was used to predict phytochemical compounds. Five compounds with the lowest EC50 were obtained: Pedilstatin (60.05 nM), Gnididin (64.29 nM), Paclitaxel (98.93 nM), Vincristine (113.9 nM), and Camellidin II (129.72 nM). Further research regarding the direct effect of PPAR-gamma needs to be tested on these five compounds. Machine learning models will save time and resources for drug discovery or repurposing previously used drugs.
Co-Authors - Yusnita, - Achadiyani Ambrosius Purba Ambrosius Purba Ambrosius Purba Ardo Sanjaya Armijn Firman Armijn Firman, Armijn Bashari, Muhammad Hasan Budi Setiabudiawan Cafrina, Gabriella Dany Hilmanto Dewi, Ni Wayan Eka Rahayu Dida Akhmad Gurnida Dida Akhmad Gurnida Dwi Agustian Eko Fuji Ariyanto Elissa Evanti Widjaja Farid Husin Farid Husin Firman Fuad Wirakusumah Gabriella Cafrina Gloria Kartika Gurid PE Mulyo Henni Djuhaeni Hikmat Permana Husin, Farid I Made Jawi Irma Ruslina Defi Kamilah, Mutiara Mila Kartika, Gloria Kasmanto, Hendro Kavita Arumugam Kavita Arumugam, Kavita Kusnandi Rusmil Kusnandi Rusmil Lasiyati Yuswo Yani Leva B Akbar Lia Faridah Lisda Amalia Lola Ilona Lukman Pura Lynna Lidyana Lynna Lidyana Martasari, Bellia Loranthifolia Mieke Hemiawati Satari Mieke Hemiawati Satari Monita Sugianto Nirwana, Edwin Oki Suwarsa Putri Tessa Radhiyanti Rachmat Soelaeman Rezah Andriani Ria Bandiara Rudi Supriyadi Savira Ekawardhani Sefti Atletika Asiani Sefti Atletika Asiani Seni Rahayu Setiawan Setiawan Siti Nur Fatimah Siti Nur Fatimah Siti Nur Fatimah Sri Hartini K. S. Kariadi Stephanus Kristianto Witono Sudigdo Adi Sunarjati Sudidgo Adi Sunarjati Sudigdoadi Sunarjati Sudigdoadi Sunarjati Sudigdoadi Susiarno, Hadi Tiara Aulia Maisyarah Tiara Aulia Maisyarah Titing Nurhayati Vita Murniati Tarawan Vita Murniati Tarawan Vitriana Vitriana Yenni Zuhairini Yesi Herawati Yudi Mulyana Hidayat Yuliarni, Dinda Zulmansyah , Zulmansyah