AUTHORS

Gabriela Falcón-Cano†, Christophe Molina∥, and Miguel Ángel Cabrera-Pérez †, §, ‡

†Unit of Modeling and Experimental Biopharmaceutics. Centro de Bioactivos Químicos. Universidad Central “Marta Abreu” de las Villas. Santa Clara 54830, Villa Clara, Cuba

∥PIKAÏROS S.A, 31650 Saint Orens de Gameville, France

§Department of Pharmacy and Pharmaceutical Technology, University of Valencia, Burjassot 46100, Valencia, Spain

‡Department of Engineering, Area of Pharmacy and Pharmaceutical Technology, Miguel Hernández University, 03550 Sant Joan d’Alacant, Alicante, Spain

ABSTRACT

In-silico prediction of human oral bioavailability is a relevant tool for the selection of potential drug candidates and for the rejection of those molecules with less probability of success during the early stages of drug discovery and development. However, the high variability and com-plexity of oral bioavailability and the limited experimental data in public domain have mainly restricted the development of reliable in-silico models to predict this property from the chemi-cal structure. In this study we present a KNIME automated workflow to predict human oral bio-availability of new drug and drug-like molecules, based on five machine learning approaches combined into an ensemble model. The workflow is freely accessible and allows the quickly and easily prediction of oral bioavailability for new molecules, where users do not require any knowledge or advanced experience in machine learning or statistical modeling to automatically obtain their predictions, increasing the potential use of the present proposal.

JOURNAL

Journal of Chemical Information and Modeling ( https://pubs.acs.org/doi/10.1021/acs.jcim.0c00019)

SUPPORTING INFORMATION

How to install and start with KNIME : https://www.knime.com/knime

KNIME WORKFLOW : Available at  https://pikairos.eu/download/HOB-classification  (445 Mbytes)

Please get in touch with us through our Contact Page to request access to the KNIME Workflow.

Workflow Available under the Revised BSD License

Copyright (c) 2020, Gabriela Falcón-Cano, Christophe Molina, Miguel Ángel Cabrera-Pérez & Pikaïros.

All rights reserved.   Redistribution and use in source and binary forms of this workflow, with or without modification, are permitted provided that the following conditions are met:

  • Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
  • Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
  • Neither the name of Pikaïros nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.  

THIS WORKFLOW IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.