TISBE: A Public Web Platform for the Consensus-Based Explainable Prediction of Developmental Toxicity.

Journal: Chemical research in toxicology
PMID:

Abstract

Despite being extremely relevant for the protection of prenatal and neonatal health, the developmental toxicity (Dev Tox) is a highly complex endpoint whose molecular rationale is still largely unknown. The lack of availability of high-quality data as well as robust nontesting methods makes its understanding even more difficult. Thus, the application of new explainable alternative methods is of utmost importance, with Dev Tox being one of the most animal-intensive research themes of regulatory toxicology. Descending from TIRESIA (Toxicology Intelligence and Regulatory Evaluations for Scientific and Industry Applications), the present work describes TISBE (TIRESIA Improved on Structure-Based Explainability), a new public web platform implementing four fundamental advancements for analyses: a three times larger dataset, a transparent XAI (explainable artificial intelligence) framework employing a fragment-based fingerprint coding, a novel consensus classifier based on five independent machine learning models, and a new applicability domain (AD) method based on a double top-down approach for better estimating the prediction reliability. The training set (TS) includes as many as 1008 chemicals annotated with experimental toxicity values. Based on a 5-fold cross-validation, a median value of 0.410 for the Matthews correlation coefficient was calculated; TISBE was very effective, with a median value of sensitivity and specificity equal to 0.984 and 0.274, respectively. TISBE was applied on two external pools made of 1484 bioactive compounds and 85 pediatric drugs taken from ChEMBL (Chemical European Molecular Biology Laboratory) and TEDDY (Task-Force in Europe for Drug Development in the Young) repositories, respectively. Notably, TISBE gives users the option to clearly spot the molecular fragments responsible for the toxicity or the safety of a given chemical query and is available for free at https://prometheus.farmacia.uniba.it/tisbe.

Authors

  • Fabrizio Mastrolorito
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125Bari, Italy.
  • Maria Vittoria Togo
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125Bari, Italy.
  • Nicola Gambacorta
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125Bari, Italy.
  • Daniela Trisciuzzi
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125Bari, Italy.
  • Viviana Giannuzzi
    Fondazione per la Ricerca Farmacologica Gianni Benzi Onlus Bari Italy.
  • Fedele Bonifazi
    Fondazione per la Ricerca Farmacologica Gianni Benzi Onlus Bari Italy.
  • Antonella Liantonio
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy.
  • Paola Imbrici
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy.
  • Annamaria De Luca
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy.
  • Cosimo Damiano Altomare
    Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125Bari, Italy.
  • Fulvio Ciriaco
    Dipartimento di Chimica, Università degli Studi di Bari Aldo Moro, 70125, Bari, Italy.
  • Nicola Amoroso
    Dipartimento Interateneo di Fisica "M. Merlin", Università degli studi di Bari "A. Moro", Bari, Italy; Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Bari, Italy. Electronic address: nicola.amoroso@ba.infn.it.
  • Orazio Nicolotti
    Department of Pharmacy- Drug Sciences, University of Bari "Aldo Moro", Via Orabona 4, 70125 Bari, Italy.