Abstract
The automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer-aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. This paper will attempt to provide a comprehensive and structured survey that collects the most important proposals made so far along with what we think will be a key player in the future, the recent developments carried out in the deep learning field.
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Pérez-Sianes, J., Pérez-Sánchez, H., DÃaz, F. (2016). Virtual Screening: A Challenge for Deep Learning. In: Saberi Mohamad, M., Rocha, M., Fdez-Riverola, F., DomÃnguez Mayo, F., De Paz, J. (eds) 10th International Conference on Practical Applications of Computational Biology & Bioinformatics. PACBB 2016. Advances in Intelligent Systems and Computing, vol 477. Springer, Cham. https://doi.org/10.1007/978-3-319-40126-3_2
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