Compound Screening with Deep Learning for Neglected Diseases: Leishmaniasis

Jonathan A. J. Smith, Hao Xu, Xinran Li, Laurence Yang, Jahir Gutierrez
Proceedings of the 16th Machine Learning in Computational Biology meeting, PMLR 165:47-57, 2022.

Abstract

Deep learning provides a tool for improving screening of candidates for drug re- purposing to treat neglected diseases. We show how a new pipeline can be devel- oped to address the needs of repurposing for Leishmaniasis. In combination with traditional molecular docking techniques, this allows top candidates to be selected and analyzed, including for molecular descriptor similarity.

Cite this Paper

BibTeX
@InProceedings{pmlr-v165-smith22a, title = {Compound Screening with Deep Learning for Neglected Diseases: Leishmaniasis}, author = {Smith, Jonathan A. J. and Xu, Hao and Li, Xinran and Yang, Laurence and Gutierrez, Jahir}, booktitle = {Proceedings of the 16th Machine Learning in Computational Biology meeting}, pages = {47--57}, year = {2022}, editor = {Knowles, David A. and Mostafavi, Sara and Lee, Su-In}, volume = {165}, series = {Proceedings of Machine Learning Research}, month = {22--23 Nov}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v165/smith22a/smith22a.pdf}, url = {https://proceedings.mlr.press/v165/smith22a.html}, abstract = {Deep learning provides a tool for improving screening of candidates for drug re- purposing to treat neglected diseases. We show how a new pipeline can be devel- oped to address the needs of repurposing for Leishmaniasis. In combination with traditional molecular docking techniques, this allows top candidates to be selected and analyzed, including for molecular descriptor similarity.} }
Endnote
%0 Conference Paper %T Compound Screening with Deep Learning for Neglected Diseases: Leishmaniasis %A Jonathan A. J. Smith %A Hao Xu %A Xinran Li %A Laurence Yang %A Jahir Gutierrez %B Proceedings of the 16th Machine Learning in Computational Biology meeting %C Proceedings of Machine Learning Research %D 2022 %E David A. Knowles %E Sara Mostafavi %E Su-In Lee %F pmlr-v165-smith22a %I PMLR %P 47--57 %U https://proceedings.mlr.press/v165/smith22a.html %V 165 %X Deep learning provides a tool for improving screening of candidates for drug re- purposing to treat neglected diseases. We show how a new pipeline can be devel- oped to address the needs of repurposing for Leishmaniasis. In combination with traditional molecular docking techniques, this allows top candidates to be selected and analyzed, including for molecular descriptor similarity.
APA
Smith, J.A.J., Xu, H., Li, X., Yang, L. & Gutierrez, J.. (2022). Compound Screening with Deep Learning for Neglected Diseases: Leishmaniasis. Proceedings of the 16th Machine Learning in Computational Biology meeting, in Proceedings of Machine Learning Research 165:47-57 Available from https://proceedings.mlr.press/v165/smith22a.html.

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