Intelligent design and synthesis of nucleobase and amino acid-based ligands to inhibit the JAK2 enzyme to treat rheumatoid arthritis.

Rheumatoid arthritis is the most prevalent form of autoimmune arthritis. In modern drug development, computer-aided drug design plays a crucial role not only in discovering new therapeutic compounds but also in assessing their potential efficacy. This study employs ligand-based pharmacophore modeling to identify novel drug candidates without requiring an initial target protein structure. Essential chemical features were extracted from nucleotides, amino acids, and sulfonylaziridine derivatives to construct potential drug scaffolds. Ligands exhibiting similar structural characteristics were then screened for promising chemical interactions. Using MATLAB software, the initial pool of 4,000 candidates was narrowed down to 330, which was further reduced to 58 and finally to 8 through AutoDock screening. These top candidates were further analyzed using molecular docking (static analysis) and molecular dynamics simulations (dynamic analysis). Among them, the compound CPROSCP demonstrated favorable dynamic stability, an appropriate hydrodynamic radius, minimal distortion of protein structure, and advantageous binding energy. The synthesized drug candidate achieved a yield of approximately 92%, with IR and NMR spectroscopy confirming its successful synthesis and high purity.