Masa Depan Penemuan Obat Melalui Pendekatan In Silico, Senyawa Alami, dan strategi PROTAC

Penulis

  • Risma Universitas Bakti Tunas Husada Penulis
  • Saeful Amin Universitas Bakti Tunas Husada Penulis

DOI:

https://doi.org/10.71417/galen.v2i2.108

Kata Kunci:

Ai, Penemuan obat, In Silico, PROTAC, Senyawa Alami

Abstrak

Kimia medisinal merupakan bidang multidisipliner yang terus berkembang pesat, mengintegrasikan pendekatan kimia, biologi, dan teknologi informasi untuk penemuan dan pengembangan obat baru. Artikel ini meninjau 20 publikasi terkini yang mencakup pendekatan in silico, pengembangan senyawa alami, strategi PROTAC, peptida terapeutik, prodrug, dan eksplorasi ruang kimia makrosiklik. Literatur diperoleh dari basis data internasional dan nasional termasuk PubMed, Scopus, dan Neliti, dengan fokus pada artikel yang diterbitkan antara 2020–2025. Analisis menunjukkan pergeseran tren menuju penggunaan kecerdasan buatan (AI), integrasi desain berbasis struktur dan sifat fisikokimia, serta peningkatan pemanfaatan scaffold baru. Review ini diharapkan menjadi referensi bagi peneliti dalam mengidentifikasi peluang riset dan strategi optimasi dalam kimia medisinal modern.

Unduhan

Data unduhan tidak tersedia.

Referensi

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Amin, S., Mustafidah, S., Nabila, N. S., & Maharani, C. (2024). Review Artikel: Pendekatan in Silico dalam Kimia Medisinal tentang Resistensi Antibiotik. Jurnal Ilmu Medis Indonesia, 4(1), 83–91.https://doi.org/10.35912/jimi.v4i1.4561

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Ancuceanu, R., Lascu, B. E., Drăgănescu, D., & Dinu, M. (2025). In Silico ADME Methods Used in the Evaluation of Natural Products. Pharmaceutics, 17(8), 1002. https://doi.org/10.3390/pharmaceutics17081002

Apprato, G., D’Agostini, G., Rossetti, P., Ermondi, G., & Caron, G. (2023). In Silico Tools to Extract the Drug Design Information Content of Degradation Data: The Case of PROTACs Targeting the Androgen Receptor. Molecules,

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Ben Geoffrey, A. S., Agrawal, D., Kulkarni, N. M., Vetrivel, R., & Gurram, K. (2023). PROTAC-Design-Evaluator (PRODE): An Advanced Method for In- Silico PROTAC Design. ACS Omega. https://doi.org/10.1021/acsomega.3c07318

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de Souza, M. M., Gini, A. L. R., Moura, J. A., Scarim, C. B., Chin, C. M., & dos Santos, J. L. (2025). Prodrug Approach as a Strategy to Enhance Drug Permeability. Pharmaceuticals, 18(3). https://doi.org/10.3390/ph18030297

Desantis, J., Mammoli, A., Eleuteri, M., Coletti, A., Croci, F., Macchiarulo, A., & Goracci, L. (2022). PROTACs bearing piperazine-containing linkers: what effect on their protonation state? RSC Advances, 12(34), 21968–21977. https://doi.org/10.1039/d2ra03761k

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Ermondi, G., Jimenez, D. G., Rossi Sebastiano, M., Kihlberg, J., & Caron, G. (2023). Conformational Sampling Deciphers the Chameleonic Properties of a VHL-Based Degrader. Pharmaceutics, 15(1). https://doi.org/10.3390/pharmaceutics15010272

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Sasso, J. M., Tenchov, R., Wang, D. S., Johnson, L. S., Wang, X., & Zhou, Q. A. (2023). Molecular Glues: The Adhesive Connecting Targeted Protein Degradation to the Clinic. Biochemistry, 62(3), 601–623. https://doi.org/10.1021/acs.biochem.2c00245

Vegad, U. G., Gajjar, N. D., Nagar, P. R., Chauhan, S. P., Pandya, D. J., & Dhameliya, T. M. (2023). In silico screening, ADMET analysis and MD simulations of phytochemicals of Onosma bracteata Wall. as SARS CoV-2 inhibitors. 3 Biotech, 13(7), 1–15. https://doi.org/10.1007/s13205-023-

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Wei, M. (2023). In Silico Tools in PROTACs design. http://arxiv.org/abs/2307.01320

Wu, J., Wang, W., & Leung, C. H. (2023). Computational strategies for PROTAC drug discovery. Acta Materia Medica, 2(1), 42–53. https://doi.org/10.15212/AMM-2022-0041

Zagidullin, A., Milyukov, V., Rizvanov, A., & Bulatov, E. (2020). Novel approaches for the rational design of PROTAC linkers. Exploration of Targeted Anti-Tumor Therapy, 1(5), 381–390. https://doi.org/10.37349/etat.2020.00023

Diterbitkan

2026-04-08

Cara Mengutip

Masa Depan Penemuan Obat Melalui Pendekatan In Silico, Senyawa Alami, dan strategi PROTAC. (2026). Galen: Jurnal Riset Ilmu Farmasi Dan Kesehatan, 2(2), 111-128. https://doi.org/10.71417/galen.v2i2.108