Next Article in Journal
The Anti-Inflammatory Effect of Acidic Mammalian Chitinase Inhibitor OAT-177 in DSS-Induced Mouse Model of Colitis
Previous Article in Journal
TAMpepK Suppresses Metastasis through the Elimination of M2-Like Tumor-Associated Macrophages in Triple-Negative Breast Cancer
Article

EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening

1
Dipartimento di Ingegneria, Università degli Studi di Palermo, 90133 Palermo, Italy
2
Molecular Informatics Group, Fondazione Ri.MED, 90133 Palermo, Italy
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Antonio Rescifina
Int. J. Mol. Sci. 2022, 23(4), 2156; https://doi.org/10.3390/ijms23042156
Received: 19 January 2022 / Revised: 7 February 2022 / Accepted: 8 February 2022 / Published: 15 February 2022
(This article belongs to the Section Molecular Informatics)
In recent years, the debate in the field of applications of Deep Learning to Virtual Screening has focused on the use of neural embeddings with respect to classical descriptors in order to encode both structural and physical properties of ligands and/or targets. The attention on embeddings with the increasing use of Graph Neural Networks aimed at overcoming molecular fingerprints that are short range embeddings for atomic neighborhoods. Here, we present EMBER, a novel molecular embedding made by seven molecular fingerprints arranged as different “spectra” to describe the same molecule, and we prove its effectiveness by using deep convolutional architecture that assesses ligands’ bioactivity on a data set containing twenty protein kinases with similar binding sites to CDK1. The data set itself is presented, and the architecture is explained in detail along with its training procedure. We report experimental results and an explainability analysis to assess the contribution of each fingerprint to different targets. View Full-Text
Keywords: deep learning; drug design; virtual screening; embedding deep learning; drug design; virtual screening; embedding
Show Figures

Graphical abstract

MDPI and ACS Style

Mendolia, I.; Contino, S.; De Simone, G.; Perricone, U.; Pirrone, R. EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening. Int. J. Mol. Sci. 2022, 23, 2156. https://doi.org/10.3390/ijms23042156

AMA Style

Mendolia I, Contino S, De Simone G, Perricone U, Pirrone R. EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening. International Journal of Molecular Sciences. 2022; 23(4):2156. https://doi.org/10.3390/ijms23042156

Chicago/Turabian Style

Mendolia, Isabella, Salvatore Contino, Giada De Simone, Ugo Perricone, and Roberto Pirrone. 2022. "EMBER—Embedding Multiple Molecular Fingerprints for Virtual Screening" International Journal of Molecular Sciences 23, no. 4: 2156. https://doi.org/10.3390/ijms23042156

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop