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Identifying molecular structural features by pattern recognition methods
Identification of molecular structural features is a central part of computational chemistry. It would be beneficial if pattern recognition techniques could be incorporated to facilitate the identification. Currently, the quantification of the structural dissimilarity is mainly carried out by root-m...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Royal Society of Chemistry
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192268/ https://www.ncbi.nlm.nih.gov/pubmed/35765452 http://dx.doi.org/10.1039/d2ra00764a |
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author | Lu, Qing |
author_facet | Lu, Qing |
author_sort | Lu, Qing |
collection | PubMed |
description | Identification of molecular structural features is a central part of computational chemistry. It would be beneficial if pattern recognition techniques could be incorporated to facilitate the identification. Currently, the quantification of the structural dissimilarity is mainly carried out by root-mean-square-deviation (RMSD) calculations such as in molecular dynamics simulations. However, the RMSD calculation underperforms for large molecules, showing the so-called “curse of dimensionality” problem. Also, it requires consistent ordering of atoms in two comparing structures, which needs nontrivial effort to fulfill. In this work, we propose to take advantage of the point cloud recognition using convex hulls as the basis to recognize molecular structural features. Two advantages of the method can be highlighted. First, the dimension of the input data structure is largely reduced from the number of atoms of molecules to the number of atoms of convex hulls. Therefore, the dimensionality curse problem is avoided, and the atom ordering process is saved. Second, the construction of convex hulls can be used to define new molecular descriptors, such as the contact area of molecular interactions. These new molecular descriptors have different properties from existing ones, therefore they are expected to exhibit different behaviors for certain machine learning studies. Several illustrative applications have been carried out, which provide promising results for structure–activity studies. |
format | Online Article Text |
id | pubmed-9192268 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-91922682022-06-27 Identifying molecular structural features by pattern recognition methods Lu, Qing RSC Adv Chemistry Identification of molecular structural features is a central part of computational chemistry. It would be beneficial if pattern recognition techniques could be incorporated to facilitate the identification. Currently, the quantification of the structural dissimilarity is mainly carried out by root-mean-square-deviation (RMSD) calculations such as in molecular dynamics simulations. However, the RMSD calculation underperforms for large molecules, showing the so-called “curse of dimensionality” problem. Also, it requires consistent ordering of atoms in two comparing structures, which needs nontrivial effort to fulfill. In this work, we propose to take advantage of the point cloud recognition using convex hulls as the basis to recognize molecular structural features. Two advantages of the method can be highlighted. First, the dimension of the input data structure is largely reduced from the number of atoms of molecules to the number of atoms of convex hulls. Therefore, the dimensionality curse problem is avoided, and the atom ordering process is saved. Second, the construction of convex hulls can be used to define new molecular descriptors, such as the contact area of molecular interactions. These new molecular descriptors have different properties from existing ones, therefore they are expected to exhibit different behaviors for certain machine learning studies. Several illustrative applications have been carried out, which provide promising results for structure–activity studies. The Royal Society of Chemistry 2022-06-14 /pmc/articles/PMC9192268/ /pubmed/35765452 http://dx.doi.org/10.1039/d2ra00764a Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Lu, Qing Identifying molecular structural features by pattern recognition methods |
title | Identifying molecular structural features by pattern recognition methods |
title_full | Identifying molecular structural features by pattern recognition methods |
title_fullStr | Identifying molecular structural features by pattern recognition methods |
title_full_unstemmed | Identifying molecular structural features by pattern recognition methods |
title_short | Identifying molecular structural features by pattern recognition methods |
title_sort | identifying molecular structural features by pattern recognition methods |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9192268/ https://www.ncbi.nlm.nih.gov/pubmed/35765452 http://dx.doi.org/10.1039/d2ra00764a |
work_keys_str_mv | AT luqing identifyingmolecularstructuralfeaturesbypatternrecognitionmethods |