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Design of drug-like hepsin inhibitors against prostate cancer and kidney stones.
Blay, Vincent; Li, Mu-Chun; Ho, Sunita P; Stoller, Mashall L; Hsieh, Hsing-Pang; Houston, Douglas R.
Afiliação
  • Blay V; Division of Biomaterials and Bioengineering, School of Dentistry, University of California San Francisco, San Francisco, CA 94143, USA.
  • Li MC; Department of Urology, School of Medicine, University of California San Francisco, San Francisco, CA 94143, USA.
  • Ho SP; Institute of Biotechnology and Pharmaceutical Research, National Health Research Institutes, Zhunan, Taiwan 350, China.
  • Stoller ML; Division of Biomaterials and Bioengineering, School of Dentistry, University of California San Francisco, San Francisco, CA 94143, USA.
  • Hsieh HP; Department of Urology, School of Medicine, University of California San Francisco, San Francisco, CA 94143, USA.
  • Houston DR; Division of Biomaterials and Bioengineering, School of Dentistry, University of California San Francisco, San Francisco, CA 94143, USA.
Acta Pharm Sin B ; 10(7): 1309-1320, 2020 Jul.
Article em En | MEDLINE | ID: mdl-32874830
ABSTRACT
Hepsin, a transmembrane serine protease abundant in renal endothelial cells, is a promising therapeutic target against several cancers, particularly prostate cancer. It is involved in the release and polymerization of uromodulin in the urine, which plays a role in kidney stone formation. In this work, we design new potential hepsin inhibitors for high activity, improved specificity towards hepsin, and promising ADMET properties. The ligands were developed in silico through a novel hierarchical pipeline. This pipeline explicitly accounts for off-target binding to the related serine proteases matriptase and HGFA (human hepatocyte growth factor activator). We completed the pipeline incorporating ADMET properties of the candidate inhibitors into custom multi-objective optimization functions. The ligands designed show excellent prospects for targeting hepsin via the blood stream and the urine and thus enable key experimental studies. The computational pipeline proposed is remarkably cost-efficient and can be easily adapted for designing inhibitors against new drug targets.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos