title: Machine Learning Models and Pathway Genome Data Base for Trypanosoma cruzi Drug Discovery.
abstract: BACKGROUND
  Chagas disease is a neglected tropical disease (NTD) caused by the eukaryotic parasite Trypanosoma cruzi. The current clinical and preclinical pipeline for T. cruzi is extremely sparse and lacks drug target diversity.
  
  
  RESULTS
  In the present study we developed a computational approach that utilized data from several public whole-cell, phenotypic high throughput screens that have been completed for T. cruzi by the Broad Institute, including a single screen of over 300,000 molecules in the search for chemical probes as part of the NIH Molecular Libraries program. We have also compiled and curated relevant biological and chemical compound screening data including (i) compounds and biological activity data from the literature, (ii) high throughput screening datasets, and (iii) predicted metabolites of T. cruzi metabolic pathways. This information was used to help us identify compounds and their potential targets. We have constructed a Pathway Genome Data Base for T. cruzi. In addition, we have developed Bayesian machine learning models that were used to virtually screen libraries of compounds. Ninety-seven compounds were selected for in vitro testing, and 11 of these were found to have EC50 < 10 μM. We progressed five compounds to an in vivo mouse efficacy model of Chagas disease and validated that the machine learning model could identify in vitro active compounds not in the training set, as well as known positive controls. The antimalarial pyronaridine possessed 85.2% efficacy in the acute Chagas mouse model. We have also proposed potential targets (for future verification) for this compound based on structural similarity to known compounds with targets in T. cruzi.
  
  
  CONCLUSIONS
  We have demonstrated how combining chemoinformatics and bioinformatics for T. cruzi drug discovery can bring interesting in vivo active molecules to light that may have been overlooked. The approach we have taken is broadly applicable to other NTDs.
authors.affiliation: Collaborative Drug Discovery, Burlingame, California, United States of America; Collaborations in Chemistry, Fuquay-Varina, North Carolina, United States of America.
authors.forename: Sean
authors.initials: S
authors.lastname: Ekins
authors.affiliation: Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, San Diego, California, United States of America.
authors.forename: Jair Lage
authors.initials: JL
authors.lastname: de Siqueira-Neto
authors.affiliation: Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, San Diego, California, United States of America.
authors.forename: Laura-Isobel
authors.initials: LI
authors.lastname: McCall
authors.affiliation: SRI International, Menlo Park, California, United States of America.
authors.forename: Malabika
authors.initials: M
authors.lastname: Sarker
authors.affiliation: SRI International, Menlo Park, California, United States of America.
authors.forename: Maneesh
authors.initials: M
authors.lastname: Yadav
authors.affiliation: Chemistry, Engineering & Medicine for Human Health (ChEM-H), Stanford, California, United States of America.
authors.forename: Elizabeth L
authors.initials: EL
authors.lastname: Ponder
authors.affiliation: Collaborative Drug Discovery, Burlingame, California, United States of America.
authors.forename: E Adam
authors.initials: EA
authors.lastname: Kallel
authors.affiliation: Department of Pathology, University of California, San Francisco, San Francisco, California, United States of America.
authors.forename: Danielle
authors.initials: D
authors.lastname: Kellar
authors.affiliation: Small Molecule Discovery Center and Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America.
authors.forename: Steven
authors.initials: S
authors.lastname: Chen
authors.affiliation: Small Molecule Discovery Center and Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America.
authors.forename: Michelle
authors.initials: M
authors.lastname: Arkin
authors.affiliation: Collaborative Drug Discovery, Burlingame, California, United States of America.
authors.forename: Barry A
authors.initials: BA
authors.lastname: Bunin
authors.affiliation: Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, San Diego, California, United States of America.
authors.forename: James H
authors.initials: JH
authors.lastname: McKerrow
authors.affiliation: SRI International, Menlo Park, California, United States of America.
authors.forename: Carolyn
authors.initials: C
authors.lastname: Talcott
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D002460:Cell Line; D014355:Chagas Disease / Q000188:drug therapy / Q000469:parasitology*; D019295:Computational Biology; D004195:Disease Models, Animal; D055808:Drug Discovery / Q000379:methods*; D005260:Female; D018503:Genome, Protozoan / Q000235:genetics*; D057166:High-Throughput Screening Assays; D006801:Humans; D000069550:Machine Learning; D053858:Metabolic Networks and Pathways; D051379:Mice; D008807:Mice, Inbred BALB C; D014344:Trypanocidal Agents / Q000302:isolation & purification / Q000494:pharmacology*; D014349:Trypanosoma cruzi / Q000187:drug effects / Q000235:genetics*
chemical_list: D014344:Trypanocidal Agents