Conformator: A Novel Method for the Generation of Conformer Ensembles

Computer-aided drug design methods such as docking, pharmacophore searching, 3D database searching, and the creation of 3D-QSAR models need conformational ensembles to handle the flexibility of small molecules. Here, we present Conformator, an accurate and effective knowledge-based algorithm for gen...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of chemical information and modeling 2019-02, Vol.59 (2), p.731-742
Hauptverfasser: Friedrich, Nils-Ole, Flachsenberg, Florian, Meyder, Agnes, Sommer, Kai, Kirchmair, Johannes, Rarey, Matthias
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 742
container_issue 2
container_start_page 731
container_title Journal of chemical information and modeling
container_volume 59
creator Friedrich, Nils-Ole
Flachsenberg, Florian
Meyder, Agnes
Sommer, Kai
Kirchmair, Johannes
Rarey, Matthias
description Computer-aided drug design methods such as docking, pharmacophore searching, 3D database searching, and the creation of 3D-QSAR models need conformational ensembles to handle the flexibility of small molecules. Here, we present Conformator, an accurate and effective knowledge-based algorithm for generating conformer ensembles. With 99.9% of all test molecules processed, Conformator stands out by its robustness with respect to input formats, molecular geometries, and the handling of macrocycles. With an extended set of rules for sampling torsion angles, a novel algorithm for macrocycle conformer generation, and a new clustering algorithm for the assembly of conformer ensembles, Conformator reaches a median minimum root-mean-square deviation (measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers) of 0.47 Å with no significant difference to the highest-ranked commercial algorithm OMEGA and significantly higher accuracy than seven free algorithms, including the RDKit DG algorithm. Conformator is freely available for noncommercial use and academic research.
doi_str_mv 10.1021/acs.jcim.8b00704
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2185871646</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2216267529</sourcerecordid><originalsourceid>FETCH-LOGICAL-a472t-c76e358cea4ee04b1fc0a84795713087252d57fee5a9f7e80d04c87bb4ce244b3</originalsourceid><addsrcrecordid>eNp1kMFLwzAUh4MoTqd3TxLw4sHOlzRpWm9jzClMvSh4C2n2yjraZiat4H9v5zYPgqc8yPf7vcdHyAWDEQPObo0No5Ut61GaAygQB-SESZFFWQLvh_tZZsmAnIawAojjLOHHZBCDEkrGcEKmE9cUztemdf6Ojumz-8SKPmG7dAvaf9B2iXSGDXrTlq6hrqC7BHo6bQLWeYXhjBwVpgp4vnuH5O1--jp5iOYvs8fJeB4ZoXgbWZVgLFOLRiCCyFlhwaRCZVKxGFLFJV9IVSBKkxUKU1iAsKnKc2GRC5HHQ3K97V1799FhaHVdBotVZRp0XdCcpTJVLBFJj179QVeu801_neacJTxRkmc9BVvKeheCx0KvfVkb_6UZ6I1i3SvWG8V6p7iPXO6Ku7zGxW9g77QHbrbAT3S_9N--bxdyhi8</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2216267529</pqid></control><display><type>article</type><title>Conformator: A Novel Method for the Generation of Conformer Ensembles</title><source>MEDLINE</source><source>American Chemical Society Journals</source><creator>Friedrich, Nils-Ole ; Flachsenberg, Florian ; Meyder, Agnes ; Sommer, Kai ; Kirchmair, Johannes ; Rarey, Matthias</creator><creatorcontrib>Friedrich, Nils-Ole ; Flachsenberg, Florian ; Meyder, Agnes ; Sommer, Kai ; Kirchmair, Johannes ; Rarey, Matthias</creatorcontrib><description>Computer-aided drug design methods such as docking, pharmacophore searching, 3D database searching, and the creation of 3D-QSAR models need conformational ensembles to handle the flexibility of small molecules. Here, we present Conformator, an accurate and effective knowledge-based algorithm for generating conformer ensembles. With 99.9% of all test molecules processed, Conformator stands out by its robustness with respect to input formats, molecular geometries, and the handling of macrocycles. With an extended set of rules for sampling torsion angles, a novel algorithm for macrocycle conformer generation, and a new clustering algorithm for the assembly of conformer ensembles, Conformator reaches a median minimum root-mean-square deviation (measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers) of 0.47 Å with no significant difference to the highest-ranked commercial algorithm OMEGA and significantly higher accuracy than seven free algorithms, including the RDKit DG algorithm. Conformator is freely available for noncommercial use and academic research.</description><identifier>ISSN: 1549-9596</identifier><identifier>EISSN: 1549-960X</identifier><identifier>DOI: 10.1021/acs.jcim.8b00704</identifier><identifier>PMID: 30747530</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Algorithms ; Angles (geometry) ; CAD ; Cluster Analysis ; Clustering ; Computer aided design ; Docking ; Drug Design ; Macrocyclic Compounds - chemistry ; Models, Molecular ; Molecular Conformation ; Pharmacology ; Proteins ; Quantitative Structure-Activity Relationship ; Searching ; Three dimensional models ; Time Factors</subject><ispartof>Journal of chemical information and modeling, 2019-02, Vol.59 (2), p.731-742</ispartof><rights>Copyright American Chemical Society Feb 25, 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a472t-c76e358cea4ee04b1fc0a84795713087252d57fee5a9f7e80d04c87bb4ce244b3</citedby><cites>FETCH-LOGICAL-a472t-c76e358cea4ee04b1fc0a84795713087252d57fee5a9f7e80d04c87bb4ce244b3</cites><orcidid>0000-0003-2667-5877 ; 0000-0002-8983-388X ; 0000-0002-9553-6531 ; 0000-0001-8519-5780 ; 0000-0001-7051-8719 ; 0000-0003-1866-8247</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/acs.jcim.8b00704$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/acs.jcim.8b00704$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>314,776,780,2751,27055,27903,27904,56716,56766</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30747530$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Friedrich, Nils-Ole</creatorcontrib><creatorcontrib>Flachsenberg, Florian</creatorcontrib><creatorcontrib>Meyder, Agnes</creatorcontrib><creatorcontrib>Sommer, Kai</creatorcontrib><creatorcontrib>Kirchmair, Johannes</creatorcontrib><creatorcontrib>Rarey, Matthias</creatorcontrib><title>Conformator: A Novel Method for the Generation of Conformer Ensembles</title><title>Journal of chemical information and modeling</title><addtitle>J. Chem. Inf. Model</addtitle><description>Computer-aided drug design methods such as docking, pharmacophore searching, 3D database searching, and the creation of 3D-QSAR models need conformational ensembles to handle the flexibility of small molecules. Here, we present Conformator, an accurate and effective knowledge-based algorithm for generating conformer ensembles. With 99.9% of all test molecules processed, Conformator stands out by its robustness with respect to input formats, molecular geometries, and the handling of macrocycles. With an extended set of rules for sampling torsion angles, a novel algorithm for macrocycle conformer generation, and a new clustering algorithm for the assembly of conformer ensembles, Conformator reaches a median minimum root-mean-square deviation (measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers) of 0.47 Å with no significant difference to the highest-ranked commercial algorithm OMEGA and significantly higher accuracy than seven free algorithms, including the RDKit DG algorithm. Conformator is freely available for noncommercial use and academic research.</description><subject>Algorithms</subject><subject>Angles (geometry)</subject><subject>CAD</subject><subject>Cluster Analysis</subject><subject>Clustering</subject><subject>Computer aided design</subject><subject>Docking</subject><subject>Drug Design</subject><subject>Macrocyclic Compounds - chemistry</subject><subject>Models, Molecular</subject><subject>Molecular Conformation</subject><subject>Pharmacology</subject><subject>Proteins</subject><subject>Quantitative Structure-Activity Relationship</subject><subject>Searching</subject><subject>Three dimensional models</subject><subject>Time Factors</subject><issn>1549-9596</issn><issn>1549-960X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kMFLwzAUh4MoTqd3TxLw4sHOlzRpWm9jzClMvSh4C2n2yjraZiat4H9v5zYPgqc8yPf7vcdHyAWDEQPObo0No5Ut61GaAygQB-SESZFFWQLvh_tZZsmAnIawAojjLOHHZBCDEkrGcEKmE9cUztemdf6Ojumz-8SKPmG7dAvaf9B2iXSGDXrTlq6hrqC7BHo6bQLWeYXhjBwVpgp4vnuH5O1--jp5iOYvs8fJeB4ZoXgbWZVgLFOLRiCCyFlhwaRCZVKxGFLFJV9IVSBKkxUKU1iAsKnKc2GRC5HHQ3K97V1799FhaHVdBotVZRp0XdCcpTJVLBFJj179QVeu801_neacJTxRkmc9BVvKeheCx0KvfVkb_6UZ6I1i3SvWG8V6p7iPXO6Ku7zGxW9g77QHbrbAT3S_9N--bxdyhi8</recordid><startdate>20190225</startdate><enddate>20190225</enddate><creator>Friedrich, Nils-Ole</creator><creator>Flachsenberg, Florian</creator><creator>Meyder, Agnes</creator><creator>Sommer, Kai</creator><creator>Kirchmair, Johannes</creator><creator>Rarey, Matthias</creator><general>American Chemical Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-2667-5877</orcidid><orcidid>https://orcid.org/0000-0002-8983-388X</orcidid><orcidid>https://orcid.org/0000-0002-9553-6531</orcidid><orcidid>https://orcid.org/0000-0001-8519-5780</orcidid><orcidid>https://orcid.org/0000-0001-7051-8719</orcidid><orcidid>https://orcid.org/0000-0003-1866-8247</orcidid></search><sort><creationdate>20190225</creationdate><title>Conformator: A Novel Method for the Generation of Conformer Ensembles</title><author>Friedrich, Nils-Ole ; Flachsenberg, Florian ; Meyder, Agnes ; Sommer, Kai ; Kirchmair, Johannes ; Rarey, Matthias</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a472t-c76e358cea4ee04b1fc0a84795713087252d57fee5a9f7e80d04c87bb4ce244b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Angles (geometry)</topic><topic>CAD</topic><topic>Cluster Analysis</topic><topic>Clustering</topic><topic>Computer aided design</topic><topic>Docking</topic><topic>Drug Design</topic><topic>Macrocyclic Compounds - chemistry</topic><topic>Models, Molecular</topic><topic>Molecular Conformation</topic><topic>Pharmacology</topic><topic>Proteins</topic><topic>Quantitative Structure-Activity Relationship</topic><topic>Searching</topic><topic>Three dimensional models</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Friedrich, Nils-Ole</creatorcontrib><creatorcontrib>Flachsenberg, Florian</creatorcontrib><creatorcontrib>Meyder, Agnes</creatorcontrib><creatorcontrib>Sommer, Kai</creatorcontrib><creatorcontrib>Kirchmair, Johannes</creatorcontrib><creatorcontrib>Rarey, Matthias</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of chemical information and modeling</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Friedrich, Nils-Ole</au><au>Flachsenberg, Florian</au><au>Meyder, Agnes</au><au>Sommer, Kai</au><au>Kirchmair, Johannes</au><au>Rarey, Matthias</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Conformator: A Novel Method for the Generation of Conformer Ensembles</atitle><jtitle>Journal of chemical information and modeling</jtitle><addtitle>J. Chem. Inf. Model</addtitle><date>2019-02-25</date><risdate>2019</risdate><volume>59</volume><issue>2</issue><spage>731</spage><epage>742</epage><pages>731-742</pages><issn>1549-9596</issn><eissn>1549-960X</eissn><abstract>Computer-aided drug design methods such as docking, pharmacophore searching, 3D database searching, and the creation of 3D-QSAR models need conformational ensembles to handle the flexibility of small molecules. Here, we present Conformator, an accurate and effective knowledge-based algorithm for generating conformer ensembles. With 99.9% of all test molecules processed, Conformator stands out by its robustness with respect to input formats, molecular geometries, and the handling of macrocycles. With an extended set of rules for sampling torsion angles, a novel algorithm for macrocycle conformer generation, and a new clustering algorithm for the assembly of conformer ensembles, Conformator reaches a median minimum root-mean-square deviation (measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers) of 0.47 Å with no significant difference to the highest-ranked commercial algorithm OMEGA and significantly higher accuracy than seven free algorithms, including the RDKit DG algorithm. Conformator is freely available for noncommercial use and academic research.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>30747530</pmid><doi>10.1021/acs.jcim.8b00704</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-2667-5877</orcidid><orcidid>https://orcid.org/0000-0002-8983-388X</orcidid><orcidid>https://orcid.org/0000-0002-9553-6531</orcidid><orcidid>https://orcid.org/0000-0001-8519-5780</orcidid><orcidid>https://orcid.org/0000-0001-7051-8719</orcidid><orcidid>https://orcid.org/0000-0003-1866-8247</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1549-9596
ispartof Journal of chemical information and modeling, 2019-02, Vol.59 (2), p.731-742
issn 1549-9596
1549-960X
language eng
recordid cdi_proquest_miscellaneous_2185871646
source MEDLINE; American Chemical Society Journals
subjects Algorithms
Angles (geometry)
CAD
Cluster Analysis
Clustering
Computer aided design
Docking
Drug Design
Macrocyclic Compounds - chemistry
Models, Molecular
Molecular Conformation
Pharmacology
Proteins
Quantitative Structure-Activity Relationship
Searching
Three dimensional models
Time Factors
title Conformator: A Novel Method for the Generation of Conformer Ensembles
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T11%3A56%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Conformator:%20A%20Novel%20Method%20for%20the%20Generation%20of%20Conformer%20Ensembles&rft.jtitle=Journal%20of%20chemical%20information%20and%20modeling&rft.au=Friedrich,%20Nils-Ole&rft.date=2019-02-25&rft.volume=59&rft.issue=2&rft.spage=731&rft.epage=742&rft.pages=731-742&rft.issn=1549-9596&rft.eissn=1549-960X&rft_id=info:doi/10.1021/acs.jcim.8b00704&rft_dat=%3Cproquest_cross%3E2216267529%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2216267529&rft_id=info:pmid/30747530&rfr_iscdi=true