Estimating structure quality trends in the Protein Data Bank by equivalent resolution
•A method to estimate equivalent resolution for protein structures is presented.•A time-trend in the PDB structures’ quality for the methods is compared.•All five methods show significantly higher e-resolutions for smaller proteins.•The predictions improved on modeling with “1/log(size)” instead of...
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Veröffentlicht in: | Computational biology and chemistry 2013-10, Vol.46, p.8-15 |
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description | •A method to estimate equivalent resolution for protein structures is presented.•A time-trend in the PDB structures’ quality for the methods is compared.•All five methods show significantly higher e-resolutions for smaller proteins.•The predictions improved on modeling with “1/log(size)” instead of “size”.•Over 22,000 X-ray structures were used for training this model.
The quality of protein structures obtained by different experimental and ab-initio calculation methods varies considerably. The methods have been evolving over time by improving both experimental designs and computational techniques, and since the primary aim of these developments is the procurement of reliable and high-quality data, better techniques resulted on average in an evolution toward higher quality structures in the Protein Data Bank (PDB). Each method leaves a specific quantitative and qualitative “trace” in the PDB entry. Certain information relevant to one method (e.g. dynamics for NMR) may be lacking for another method. Furthermore, some standard measures of quality for one method cannot be calculated for other experimental methods, e.g. crystal resolution or NMR bundle RMSD. Consequently, structures are classified in the PDB by the method used. Here we introduce a method to estimate a measure of equivalent X-ray resolution (e-resolution), expressed in units of Å, to assess the quality of any type of monomeric, single-chain protein structure, irrespective of the experimental structure determination method. We showed and compared the trends in the quality of structures in the Protein Data Bank over the last two decades for five different experimental techniques, excluding theoretical structure predictions. We observed that as new methods are introduced, they undergo a rapid method development evolution: within several years the e-resolution score becomes similar for structures obtained from the five methods and they improve from initially poor performance to acceptable quality, comparable with previously established methods, the performance of which is essentially stable. |
doi_str_mv | 10.1016/j.compbiolchem.2013.04.004 |
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The quality of protein structures obtained by different experimental and ab-initio calculation methods varies considerably. The methods have been evolving over time by improving both experimental designs and computational techniques, and since the primary aim of these developments is the procurement of reliable and high-quality data, better techniques resulted on average in an evolution toward higher quality structures in the Protein Data Bank (PDB). Each method leaves a specific quantitative and qualitative “trace” in the PDB entry. Certain information relevant to one method (e.g. dynamics for NMR) may be lacking for another method. Furthermore, some standard measures of quality for one method cannot be calculated for other experimental methods, e.g. crystal resolution or NMR bundle RMSD. Consequently, structures are classified in the PDB by the method used. Here we introduce a method to estimate a measure of equivalent X-ray resolution (e-resolution), expressed in units of Å, to assess the quality of any type of monomeric, single-chain protein structure, irrespective of the experimental structure determination method. We showed and compared the trends in the quality of structures in the Protein Data Bank over the last two decades for five different experimental techniques, excluding theoretical structure predictions. We observed that as new methods are introduced, they undergo a rapid method development evolution: within several years the e-resolution score becomes similar for structures obtained from the five methods and they improve from initially poor performance to acceptable quality, comparable with previously established methods, the performance of which is essentially stable.</description><identifier>ISSN: 1476-9271</identifier><identifier>EISSN: 1476-928X</identifier><identifier>DOI: 10.1016/j.compbiolchem.2013.04.004</identifier><identifier>PMID: 23751279</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Computation ; Data banks ; Databases, Protein - standards ; Equivalence ; Equivalent resolution ; Evolution ; Image Processing, Computer-Assisted - standards ; Image Processing, Computer-Assisted - statistics & numerical data ; Mathematical analysis ; Multiple linear regression ; Multivariate Analysis ; Nuclear magnetic resonance ; PDB ; Protein structure validation ; Proteins ; Proteins - chemistry ; Structure quality ; Trends ; X-ray and NMR</subject><ispartof>Computational biology and chemistry, 2013-10, Vol.46, p.8-15</ispartof><rights>2013 Elsevier Ltd</rights><rights>Copyright © 2013 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c479t-872b625fb64e3d7a81643a1563a8d5dc8529356757104edc1429cf131037b7a73</citedby><cites>FETCH-LOGICAL-c479t-872b625fb64e3d7a81643a1563a8d5dc8529356757104edc1429cf131037b7a73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.compbiolchem.2013.04.004$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23751279$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bagaria, Anurag</creatorcontrib><creatorcontrib>Jaravine, Victor</creatorcontrib><creatorcontrib>Güntert, Peter</creatorcontrib><title>Estimating structure quality trends in the Protein Data Bank by equivalent resolution</title><title>Computational biology and chemistry</title><addtitle>Comput Biol Chem</addtitle><description>•A method to estimate equivalent resolution for protein structures is presented.•A time-trend in the PDB structures’ quality for the methods is compared.•All five methods show significantly higher e-resolutions for smaller proteins.•The predictions improved on modeling with “1/log(size)” instead of “size”.•Over 22,000 X-ray structures were used for training this model.
The quality of protein structures obtained by different experimental and ab-initio calculation methods varies considerably. The methods have been evolving over time by improving both experimental designs and computational techniques, and since the primary aim of these developments is the procurement of reliable and high-quality data, better techniques resulted on average in an evolution toward higher quality structures in the Protein Data Bank (PDB). Each method leaves a specific quantitative and qualitative “trace” in the PDB entry. Certain information relevant to one method (e.g. dynamics for NMR) may be lacking for another method. Furthermore, some standard measures of quality for one method cannot be calculated for other experimental methods, e.g. crystal resolution or NMR bundle RMSD. Consequently, structures are classified in the PDB by the method used. Here we introduce a method to estimate a measure of equivalent X-ray resolution (e-resolution), expressed in units of Å, to assess the quality of any type of monomeric, single-chain protein structure, irrespective of the experimental structure determination method. We showed and compared the trends in the quality of structures in the Protein Data Bank over the last two decades for five different experimental techniques, excluding theoretical structure predictions. We observed that as new methods are introduced, they undergo a rapid method development evolution: within several years the e-resolution score becomes similar for structures obtained from the five methods and they improve from initially poor performance to acceptable quality, comparable with previously established methods, the performance of which is essentially stable.</description><subject>Computation</subject><subject>Data banks</subject><subject>Databases, Protein - standards</subject><subject>Equivalence</subject><subject>Equivalent resolution</subject><subject>Evolution</subject><subject>Image Processing, Computer-Assisted - standards</subject><subject>Image Processing, Computer-Assisted - statistics & numerical data</subject><subject>Mathematical analysis</subject><subject>Multiple linear regression</subject><subject>Multivariate Analysis</subject><subject>Nuclear magnetic resonance</subject><subject>PDB</subject><subject>Protein structure validation</subject><subject>Proteins</subject><subject>Proteins - chemistry</subject><subject>Structure quality</subject><subject>Trends</subject><subject>X-ray and NMR</subject><issn>1476-9271</issn><issn>1476-928X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkTtP7DAUhC0E4rHwF5BFRbPBbyd0vEFCggIkOstxzl68JPGu7SDtvydouYgOqnOKb2akGYSOKCkooepkXrjQLWofWvcKXcEI5QURBSFiA-1SodW0YuXL5vev6Q7aS2lOCOOEyG20w7iWlOlqFz1fpew7m33_D6ccB5eHCHg52NbnFc4R-iZh3-P8Cvgxhgzjf2mzxee2f8P1CsNy8O-2hT7jCCm0Q_ah30dbM9smOPi6E_R8ffV0cTu9f7i5uzi7nzqhqzwtNasVk7NaCeCNtiVVglsqFbdlIxtXSlZxqbTUlAhoHBWscjPKKeG61lbzCTpe-y5iWA6Qsul8ctC2tocwJEMlJ1WptCh_RwVTZIwZvSfodI26GFKKMDOLOHYUV4YS87mAmZufC5jPBQwRZlxgFB9-5Qx1B8239H_lI3C5BmAs5t1DNMl56B00PoLLpgn-LzkfF6Cdug</recordid><startdate>20131001</startdate><enddate>20131001</enddate><creator>Bagaria, Anurag</creator><creator>Jaravine, Victor</creator><creator>Güntert, Peter</creator><general>Elsevier Ltd</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>7X8</scope><scope>7SC</scope><scope>7U5</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20131001</creationdate><title>Estimating structure quality trends in the Protein Data Bank by equivalent resolution</title><author>Bagaria, Anurag ; Jaravine, Victor ; Güntert, Peter</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c479t-872b625fb64e3d7a81643a1563a8d5dc8529356757104edc1429cf131037b7a73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Computation</topic><topic>Data banks</topic><topic>Databases, Protein - standards</topic><topic>Equivalence</topic><topic>Equivalent resolution</topic><topic>Evolution</topic><topic>Image Processing, Computer-Assisted - standards</topic><topic>Image Processing, Computer-Assisted - statistics & numerical data</topic><topic>Mathematical analysis</topic><topic>Multiple linear regression</topic><topic>Multivariate Analysis</topic><topic>Nuclear magnetic resonance</topic><topic>PDB</topic><topic>Protein structure validation</topic><topic>Proteins</topic><topic>Proteins - chemistry</topic><topic>Structure quality</topic><topic>Trends</topic><topic>X-ray and NMR</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bagaria, Anurag</creatorcontrib><creatorcontrib>Jaravine, Victor</creatorcontrib><creatorcontrib>Güntert, Peter</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Computer and Information Systems Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology 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><jtitle>Computational biology and chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bagaria, Anurag</au><au>Jaravine, Victor</au><au>Güntert, Peter</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating structure quality trends in the Protein Data Bank by equivalent resolution</atitle><jtitle>Computational biology and chemistry</jtitle><addtitle>Comput Biol Chem</addtitle><date>2013-10-01</date><risdate>2013</risdate><volume>46</volume><spage>8</spage><epage>15</epage><pages>8-15</pages><issn>1476-9271</issn><eissn>1476-928X</eissn><abstract>•A method to estimate equivalent resolution for protein structures is presented.•A time-trend in the PDB structures’ quality for the methods is compared.•All five methods show significantly higher e-resolutions for smaller proteins.•The predictions improved on modeling with “1/log(size)” instead of “size”.•Over 22,000 X-ray structures were used for training this model.
The quality of protein structures obtained by different experimental and ab-initio calculation methods varies considerably. The methods have been evolving over time by improving both experimental designs and computational techniques, and since the primary aim of these developments is the procurement of reliable and high-quality data, better techniques resulted on average in an evolution toward higher quality structures in the Protein Data Bank (PDB). Each method leaves a specific quantitative and qualitative “trace” in the PDB entry. Certain information relevant to one method (e.g. dynamics for NMR) may be lacking for another method. Furthermore, some standard measures of quality for one method cannot be calculated for other experimental methods, e.g. crystal resolution or NMR bundle RMSD. Consequently, structures are classified in the PDB by the method used. Here we introduce a method to estimate a measure of equivalent X-ray resolution (e-resolution), expressed in units of Å, to assess the quality of any type of monomeric, single-chain protein structure, irrespective of the experimental structure determination method. We showed and compared the trends in the quality of structures in the Protein Data Bank over the last two decades for five different experimental techniques, excluding theoretical structure predictions. We observed that as new methods are introduced, they undergo a rapid method development evolution: within several years the e-resolution score becomes similar for structures obtained from the five methods and they improve from initially poor performance to acceptable quality, comparable with previously established methods, the performance of which is essentially stable.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>23751279</pmid><doi>10.1016/j.compbiolchem.2013.04.004</doi><tpages>8</tpages></addata></record> |
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subjects | Computation Data banks Databases, Protein - standards Equivalence Equivalent resolution Evolution Image Processing, Computer-Assisted - standards Image Processing, Computer-Assisted - statistics & numerical data Mathematical analysis Multiple linear regression Multivariate Analysis Nuclear magnetic resonance PDB Protein structure validation Proteins Proteins - chemistry Structure quality Trends X-ray and NMR |
title | Estimating structure quality trends in the Protein Data Bank by equivalent resolution |
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