Desain Molekul Calon Inhibitor Baru Janus Kinase 2 (JAK2) Pada Penyakit Rheumatoid Arthtritis Menggunakan Drugex
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Fakultas Matematika dan Ilmu Pengetahuan Alam
Abstract
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial tissue inflammation, with a global prevalence reaching 24 million cases by 2024. The Janus Activated Kinase-Signal Transduction and Activator of Transcription (JAK-STAT) pathway plays a crucial role in RA pathogenesis through the activation of pro-inflammatory cytokines. However, currently available Janus Kinase inhibitors still cause significant side effects, necessitating the development of new, more selective, and safer Janus Kinase 2 inhibitor candidates. This research aims to design new Janus Kinase 2 inhibitor candidates using a de novo drug design (DNDD) approach based on the DrugEx generative model. Target compound data were obtained from the ChEMBL database with target code ChEMBL2971, and bioactivity and synthetic feasibility were evaluated using QSPRPred, SA Score, Lipinski's Rule of Five, and ADMET analysis. A total of 1.000.000 molecules were generated, with predicted pIC50 activity ranging from 3,35 to 10,50. The molecules with the highest predicted activity shared a pyrrolopyrimidine core, a secondary amine linking two aromatic rings, and a methanesulfonyl-piperidine group, showing substructural similarity to approved Janus Kinase inhibitors. Following SA Score and Lipinski's Rule of Five selection, 821 molecules were evaluated for ADMET properties, of which 629 met the main ADMET parameters (30 failed water solubility, 137 failed BBB permeability, 27 failed CYP2D6 inhibition, and 48 failed AMES toxicity). A total of 629 molecules were generated that passed the Lipinski, SA Score, similarity, novelty, and ADMET evaluations. Based on Lipinski's parameters, SA Score, similarity, novelty, and ADMET properties, the ten molecules with the highest predicted pIC50 activity were recommended as JAK2 inhibitor candidates. The DrugEx model shows strong potential as an effective computational approach for identifying novel JAK2 inhibitor candidates to support rheumatoid arthritis therapy development.
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Validasi dan Finalisasi Ratna 24 Agustus 2026
