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Comparison of similarity method to improve retrieval performance for chemical data

Drug discovery is the process through which new drugs are discovered. One of the most common techniques in drug discovery is similarity searching based on virtual screening that involves comparing the similarity between molecule structures in chemical database using established similarity methods. T...

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Main Authors: Suhaila Zainudin,, Nevy Rahmi Nurjana,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:http://journalarticle.ukm.my/17758/1/08.pdf
http://journalarticle.ukm.my/17758/
https://www.ukm.my/apjitm/articles-year.php
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spelling my-ukm.journal.177582021-12-24T08:38:53Z http://journalarticle.ukm.my/17758/ Comparison of similarity method to improve retrieval performance for chemical data Suhaila Zainudin, Nevy Rahmi Nurjana, Drug discovery is the process through which new drugs are discovered. One of the most common techniques in drug discovery is similarity searching based on virtual screening that involves comparing the similarity between molecule structures in chemical database using established similarity methods. The objective of this study is to identify the similarity of the structure in chemical dataset using Mean Pairwise Similarity (MPS) calculation and to determine the best coefficient to be used in similarity searching which involves of molecular descriptor ECFP2 fingerprint and three types of similarity coefficient which are Tanimoto, Soergel and Euclidean. From the results, it was deduced that Tanimoto and Soergel coefficients has a better performance than Euclidean coefficient. For future work, different combinations of fingerprints such as Daylight, BCI, Unity MDL and similarity coefficient can be studied further. Penerbit Universiti Kebangsaan Malaysia 2018-06 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/17758/1/08.pdf Suhaila Zainudin, and Nevy Rahmi Nurjana, (2018) Comparison of similarity method to improve retrieval performance for chemical data. Asia-Pacific Journal of Information Technology and Multimedia, 7 (1). pp. 91-98. ISSN 2289-2192 https://www.ukm.my/apjitm/articles-year.php
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Drug discovery is the process through which new drugs are discovered. One of the most common techniques in drug discovery is similarity searching based on virtual screening that involves comparing the similarity between molecule structures in chemical database using established similarity methods. The objective of this study is to identify the similarity of the structure in chemical dataset using Mean Pairwise Similarity (MPS) calculation and to determine the best coefficient to be used in similarity searching which involves of molecular descriptor ECFP2 fingerprint and three types of similarity coefficient which are Tanimoto, Soergel and Euclidean. From the results, it was deduced that Tanimoto and Soergel coefficients has a better performance than Euclidean coefficient. For future work, different combinations of fingerprints such as Daylight, BCI, Unity MDL and similarity coefficient can be studied further.
format Article
author Suhaila Zainudin,
Nevy Rahmi Nurjana,
spellingShingle Suhaila Zainudin,
Nevy Rahmi Nurjana,
Comparison of similarity method to improve retrieval performance for chemical data
author_facet Suhaila Zainudin,
Nevy Rahmi Nurjana,
author_sort Suhaila Zainudin,
title Comparison of similarity method to improve retrieval performance for chemical data
title_short Comparison of similarity method to improve retrieval performance for chemical data
title_full Comparison of similarity method to improve retrieval performance for chemical data
title_fullStr Comparison of similarity method to improve retrieval performance for chemical data
title_full_unstemmed Comparison of similarity method to improve retrieval performance for chemical data
title_sort comparison of similarity method to improve retrieval performance for chemical data
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2018
url http://journalarticle.ukm.my/17758/1/08.pdf
http://journalarticle.ukm.my/17758/
https://www.ukm.my/apjitm/articles-year.php
_version_ 1720437887066963968
score 13.211869

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