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@article{1681816,
author = {Sabando, María Virginia and Ulbrich, Pavol and Selzer, Matías and Byška, Jan and Mičan, Jan and Ponzoni, Ignacio and Soto, Axel J. and Ganuza, María Luján and Kozlíková, Barbora},
article_number = {2},
doi = {http://dx.doi.org/10.1109/TVCG.2020.3030438},
keywords = {Virtual screening;visual analysis;dimensionality reduction;coordinated views;cheminformatics},
language = {eng},
issn = {1077-2626},
journal = {IEEE Transactions on Visualization and Computer Graphics},
title = {ChemVA: Interactive Visual Analysis of Chemical Compound Similarity in Virtual Screening},
url = {https://ieeexplore.ieee.org/document/9222282},
volume = {27},
year = {2021}
}
TY - JOUR
ID - 1681816
AU - Sabando, María Virginia - Ulbrich, Pavol - Selzer, Matías - Byška, Jan - Mičan, Jan - Ponzoni, Ignacio - Soto, Axel J. - Ganuza, María Luján - Kozlíková, Barbora
PY - 2021
TI - ChemVA: Interactive Visual Analysis of Chemical Compound Similarity in Virtual Screening
JF - IEEE Transactions on Visualization and Computer Graphics
VL - 27
IS - 2
SP - 891-901
EP - 891-901
PB - IEEE
SN - 10772626
KW - Virtual screening;visual analysis;dimensionality reduction;coordinated views;cheminformatics
UR - https://ieeexplore.ieee.org/document/9222282
L2 - https://ieeexplore.ieee.org/document/9222282
N2 - In the modern drug discovery process, medicinal chemists deal with the complexity of analysis of large ensembles of candidate molecules. Computational tools, such as dimensionality reduction (DR) and classification, are commonly used to efficiently process the multidimensional space of features. These underlying calculations often hinder interpretability of results and prevent experts from assessing the impact of individual molecular features on the resulting representations. To provide a solution for scrutinizing such complex data, we introduce ChemVA, an interactive application for the visual exploration of large molecular ensembles and their features. Our tool consists of multiple coordinated views: Hexagonal view, Detail view, 3D view, Table view, and a newly proposed Difference view designed for the comparison of DR projections. These views display DR projections combined with biological activity,selected molecular features, and confidence scores for each of these projections. This conjunction of views allows the user to drill down through the dataset and to efficiently select candidate compounds. Our approach was evaluated on two case studies of finding structurally similar ligands with similar binding affinity to a target protein, as well as on an external qualitative evaluation. The results suggest that our system allows effective visual inspection and comparison of different high-dimensional molecular representations.Furthermore, ChemVA assists in the identification of candidate compounds while providing information on the certainty behind different molecular representations.
ER -
SABANDO, María Virginia, Pavol ULBRICH, Matías SELZER, Jan BYŠKA, Jan MIČAN, Ignacio PONZONI, Axel J. SOTO, María Luján GANUZA and Barbora KOZLÍKOVÁ. ChemVA: Interactive Visual Analysis of Chemical Compound Similarity in Virtual Screening. \textit{IEEE Transactions on Visualization and Computer Graphics}. IEEE, 2021, vol.~27, No~2, p.~891-901. ISSN~1077-2626. Available from: https://dx.doi.org/10.1109/TVCG.2020.3030438.
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