RESUMO
Leukocyte antigen-related (LAR) phosphatase is a receptor-type protein tyrosine phosphatase involved in cellular signaling and associated with human disease including cancer and metabolic disorders. Selective inhibition of LAR phosphatase activity by well characterized and well validated small molecules would provide key insights into the roles of LAR phosphatase in health and disease, but identifying selective inhibitors of LAR phosphatase activity has been challenging. Recently, we described potent and selective inhibition of LAR phosphatase activity by the fungal natural product illudalic acid. Here we provide a detailed biochemical characterization of the adduct formed between LAR phosphatase and illudalic acid. A mass spectrometric analysis indicates that two cysteine residues are covalently labeled by illudalic acid and a related analog. Mutational analysis supports the hypothesis that inhibition of LAR phosphatase activity is due primarily to the adduct with the catalytic cysteine residue. A computational study suggests potential interactions between the illudalic acid moiety and the enzyme active site. Taken together, these data offer novel insights into the mechanism of inhibition of LAR phosphatase activity by illudalic acid.
Assuntos
Cumarínicos , Proteínas Tirosina Fosfatases Classe 2 Semelhantes a Receptores , Humanos , Cumarínicos/química , Cumarínicos/farmacologia , Cisteína/química , Cisteína/genética , Proteínas Tirosina Fosfatases Classe 2 Semelhantes a Receptores/antagonistas & inibidores , Proteínas Tirosina Fosfatases Classe 2 Semelhantes a Receptores/química , Proteínas Tirosina Fosfatases Classe 2 Semelhantes a Receptores/genéticaRESUMO
Two critical steps in drug development are 1) the discovery of molecules that have the desired effects on a target, and 2) the optimization of such molecules into lead compounds with the required potency and pharmacokinetic properties for translation. DNA-encoded chemical libraries (DECLs) can nowadays yield hits with unprecedented ease, and lead-optimization is becoming the limiting step. Here we integrate DECL screening with structure-based computational methods to streamline the development of lead compounds. The presented workflow consists of enumerating a virtual combinatorial library (VCL) derived from a DECL screening hit and using computational binding prediction to identify molecules with enhanced properties relative to the original DECL hit. As proof-of-concept demonstration, we applied this approach to identify an inhibitor of PARP10 that is more potent and druglike than the original DECL screening hit.