Targeting plague virulence factors: A combined machine learning method and multiple conformational virtual screening for the discovery of Yersinia protein kinase A inhibitors

Journal of Medicinal Chemistry

Volumn 50, Issue 17, 2007, Pages 3980-3983

  Hu, Xin ^a   Prehna, Gerd ^a   Stebbins, C Erec ^a  

^a ROCKEFELLER UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CYCLIC AMP DEPENDENT PROTEIN KINASE; CYCLIC AMP DEPENDENT PROTEIN KINASE INHIBITOR; PROTEIN SERINE THREONINE KINASE; VIRULENCE FACTOR;

ANTIBIOTIC RESISTANCE; ARTICLE; DRUG CONFORMATION; ENZYME ACTIVE SITE; ENZYME ACTIVITY; HIGH THROUGHPUT SCREENING; MACHINE LEARNING; NONHUMAN; PATHOGENICITY; PLAGUE; PROTEIN DOMAIN; YERSINIA;

AMINO ACID SEQUENCE; ANTHRAQUINONES; ANTI-BACTERIAL AGENTS; ARTIFICIAL INTELLIGENCE; BACTERIAL PROTEINS; INDOLES; MITOGEN-ACTIVATED PROTEIN KINASES; MODELS, MOLECULAR; MOLECULAR CONFORMATION; MOLECULAR SEQUENCE DATA; PLAGUE; PROTEIN KINASE C; PROTEIN KINASE INHIBITORS; PROTEIN-SERINE-THREONINE KINASES; PYRIMIDINES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SEQUENCE HOMOLOGY, AMINO ACID; VIRULENCE FACTORS; YERSINIA;

EID: 34548141774     PISSN: 00222623     EISSN: None     Source Type: Journal    
DOI: 10.1021/jm070645a     Document Type: Article

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