Cargando…
Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis
Key-based substructural fingerprints are an important element of computer-aided drug design techniques. The usefulness of the fingerprints in filtering compound databases is invaluable, as they allow for the quick rejection of molecules with a low probability of being active. However, this method is...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100401/ https://www.ncbi.nlm.nih.gov/pubmed/29789513 http://dx.doi.org/10.3390/molecules23061242 |
_version_ | 1783348865065287680 |
---|---|
author | Rataj, Krzysztof Czarnecki, Wojciech Podlewska, Sabina Pocha, Agnieszka Bojarski, Andrzej J. |
author_facet | Rataj, Krzysztof Czarnecki, Wojciech Podlewska, Sabina Pocha, Agnieszka Bojarski, Andrzej J. |
author_sort | Rataj, Krzysztof |
collection | PubMed |
description | Key-based substructural fingerprints are an important element of computer-aided drug design techniques. The usefulness of the fingerprints in filtering compound databases is invaluable, as they allow for the quick rejection of molecules with a low probability of being active. However, this method is flawed, as it does not consider the connections between substructures. After changing the connections between particular chemical moieties, the fingerprint representation of the compound remains the same, which leads to difficulties in distinguishing between active and inactive compounds. In this study, we present a new method of compound representation—substructural connectivity fingerprints (SCFP), providing information not only about the presence of particular substructures in the molecule but also additional data on substructure connections. Such representation was analyzed by the recently developed methodology—extreme entropy machines (EEM). The SCFP can be a valuable addition to virtual screening tools, as it represents compound structure with greater detail and more specificity, allowing for more accurate classification. |
format | Online Article Text |
id | pubmed-6100401 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61004012018-11-13 Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis Rataj, Krzysztof Czarnecki, Wojciech Podlewska, Sabina Pocha, Agnieszka Bojarski, Andrzej J. Molecules Article Key-based substructural fingerprints are an important element of computer-aided drug design techniques. The usefulness of the fingerprints in filtering compound databases is invaluable, as they allow for the quick rejection of molecules with a low probability of being active. However, this method is flawed, as it does not consider the connections between substructures. After changing the connections between particular chemical moieties, the fingerprint representation of the compound remains the same, which leads to difficulties in distinguishing between active and inactive compounds. In this study, we present a new method of compound representation—substructural connectivity fingerprints (SCFP), providing information not only about the presence of particular substructures in the molecule but also additional data on substructure connections. Such representation was analyzed by the recently developed methodology—extreme entropy machines (EEM). The SCFP can be a valuable addition to virtual screening tools, as it represents compound structure with greater detail and more specificity, allowing for more accurate classification. MDPI 2018-05-23 /pmc/articles/PMC6100401/ /pubmed/29789513 http://dx.doi.org/10.3390/molecules23061242 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rataj, Krzysztof Czarnecki, Wojciech Podlewska, Sabina Pocha, Agnieszka Bojarski, Andrzej J. Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis |
title | Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis |
title_full | Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis |
title_fullStr | Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis |
title_full_unstemmed | Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis |
title_short | Substructural Connectivity Fingerprint and Extreme Entropy Machines—A New Method of Compound Representation and Analysis |
title_sort | substructural connectivity fingerprint and extreme entropy machines—a new method of compound representation and analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6100401/ https://www.ncbi.nlm.nih.gov/pubmed/29789513 http://dx.doi.org/10.3390/molecules23061242 |
work_keys_str_mv | AT ratajkrzysztof substructuralconnectivityfingerprintandextremeentropymachinesanewmethodofcompoundrepresentationandanalysis AT czarneckiwojciech substructuralconnectivityfingerprintandextremeentropymachinesanewmethodofcompoundrepresentationandanalysis AT podlewskasabina substructuralconnectivityfingerprintandextremeentropymachinesanewmethodofcompoundrepresentationandanalysis AT pochaagnieszka substructuralconnectivityfingerprintandextremeentropymachinesanewmethodofcompoundrepresentationandanalysis AT bojarskiandrzejj substructuralconnectivityfingerprintandextremeentropymachinesanewmethodofcompoundrepresentationandanalysis |