{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T11:53:27Z","timestamp":1767182007845},"reference-count":48,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2020,3,10]],"date-time":"2020-03-10T00:00:00Z","timestamp":1583798400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>In proteins, solvent accessibility of individual residues is a factor contributing to their importance for protein function and stability. Hence one might wish to calculate solvent accessibility in order to predict the impact of mutations, their pathogenicity and for other biomedical applications. A direct computation of solvent accessibility is only possible if all atoms of a protein three-dimensional structure are reliably resolved.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We present SphereCon, a new precise measure that can estimate residue relative solvent accessibility (RSA) from limited data. The measure is based on calculating the volume of intersection of a sphere with a cone cut out in the direction opposite of the residue with surrounding atoms. We propose a method for estimating the position and volume of residue atoms in cases when they are not known from the structure, or when the structural data are unreliable or missing. We show that in cases of reliable input structures, SphereCon correlates almost perfectly with the directly computed RSA, and outperforms other previously suggested indirect methods. Moreover, SphereCon is the only measure that yields accurate results when the identities of amino acids are unknown. A significant novel feature of SphereCon is that it can estimate RSA from inter-residue distance and contact matrices, without any information about the actual atom coordinates.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>https:\/\/github.com\/kalininalab\/spherecon.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Contact<\/jats:title>\n                  <jats:p>alexander.gress@helmholtz-hips.de<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa159","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T12:26:22Z","timestamp":1583497582000},"page":"3372-3378","source":"Crossref","is-referenced-by-count":4,"title":["SphereCon\u2014a method for precise estimation of residue relative solvent accessible area from limited structural information"],"prefix":"10.1093","volume":"36","author":[{"given":"Alexander","family":"Gress","sequence":"first","affiliation":[{"name":"Department of Drug Bioinformatics , Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Campus E8.1, Saarbr\u00fccken 66123, Germany"},{"name":"Graduate School of Computer Science , Saarland University, Saarbr\u00fccken 66123, Germany"}]},{"given":"Olga V","family":"Kalinina","sequence":"additional","affiliation":[{"name":"Department of Drug Bioinformatics , Helmholtz Institute for Pharmaceutical Research Saarland (HIPS), Helmholtz Centre for Infection Research (HZI), Campus E8.1, Saarbr\u00fccken 66123, Germany"},{"name":"Medical Faculty , Saarland University, Homburg 66421, Germany"}]}],"member":"286","published-online":{"date-parts":[[2020,3,10]]},"reference":[{"key":"2023062300081193500_btaa159-B1","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1093\/bioinformatics\/btx781","article-title":"DNCON2: improved protein contact prediction using two-level deep convolutional neural networks","volume":"34","author":"Adhikari","year":"2018","journal-title":"Bioinformatics"},{"key":"2023062300081193500_btaa159-B2","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1006\/jmbi.2001.4870","article-title":"Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking","volume":"311","author":"Aloy","year":"2001","journal-title":"J. Mol. Biol"},{"key":"2023062300081193500_btaa159-B3","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1093\/molbev\/msl040","article-title":"Structural determinants of the rate of protein evolution in yeast","volume":"23","author":"Bloom","year":"2006","journal-title":"Mol. Biol. Evol"},{"key":"2023062300081193500_btaa159-B4","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1016\/0022-2836(90)90087-3","article-title":"Evolution of protein cores: constraints in point mutations as observed in globin tertiary structures","volume":"211","author":"Bordo","year":"1990","journal-title":"J. Mol. Biol"},{"key":"2023062300081193500_btaa159-B5","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1016\/S0006-3495(02)75182-5","article-title":"The effect of core destabilization on the mechanical resistance of I27","volume":"83","author":"Brockwell","year":"2002","journal-title":"Biophys. J"},{"key":"2023062300081193500_btaa159-B6","doi-asserted-by":"crossref","first-page":"14338","DOI":"10.1073\/pnas.94.26.14338","article-title":"Thermodynamic stability of wild-type and mutant p53 core domain","volume":"94","author":"Bullock","year":"1997","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023062300081193500_btaa159-B7","doi-asserted-by":"crossref","first-page":"3066","DOI":"10.1093\/bioinformatics\/bts598","article-title":"Predicting protein residue\u2013residue contacts using deep networks and boosting","volume":"28","author":"Eickholt","year":"2012","journal-title":"Bioinformatics"},{"key":"2023062300081193500_btaa159-B8","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1006\/jmbi.1993.1331","article-title":"A method to configure protein side-chains from the main-chain trace in homology modelling","volume":"231","author":"Eisenmenger","year":"1993","journal-title":"J. Mol. Biol"},{"key":"2023062300081193500_btaa159-B9","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1002\/jcc.21968","article-title":"SPINE X: improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles","volume":"33","author":"Faraggi","year":"2012","journal-title":"J. Comput. Chem"},{"key":"2023062300081193500_btaa159-B10","doi-asserted-by":"crossref","first-page":"1557","DOI":"10.1110\/ps.072856307","article-title":"Local quality assessment in homology models using statistical potentials and support vector machines","volume":"16","author":"Fasnacht","year":"2007","journal-title":"Protein Sci. Publ. Protein Soc"},{"key":"2023062300081193500_btaa159-B11","doi-asserted-by":"crossref","first-page":"e4476","DOI":"10.1371\/journal.pone.0004476","article-title":"Recognition of interaction interface residues in low-resolution structures of protein assemblies solely from the positions of C\u03b1 atoms","volume":"4","author":"Gadkari","year":"2009","journal-title":"PLoS One"},{"key":"2023062300081193500_btaa159-B12","doi-asserted-by":"crossref","first-page":"e380","DOI":"10.1038\/oncsis.2017.79","article-title":"Spatial distribution of disease-associated variants in three-dimensional structures of protein complexes","volume":"6","author":"Gress","year":"2017","journal-title":"Oncogenesis"},{"key":"2023062300081193500_btaa159-B13","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1002\/prot.20379","article-title":"An amino acid has two sides: a new 2D measure provides a different view of solvent exposure","volume":"59","author":"Hamelryck","year":"2005","journal-title":"Proteins Struct. Funct. Bioinf"},{"key":"2023062300081193500_btaa159-B14","doi-asserted-by":"crossref","first-page":"2403","DOI":"10.1093\/bioinformatics\/bty1006","article-title":"Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks","volume":"35","author":"Hanson","year":"2019","journal-title":"Bioinformatics"},{"key":"2023062300081193500_btaa159-B15","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1002\/prot.22458","article-title":"Structure is three to ten times more conserved than sequence\u2013a study of structural response in protein cores","volume":"77","author":"Illerg\u00e5rd","year":"2009","journal-title":"Proteins"},{"key":"2023062300081193500_btaa159-B16","doi-asserted-by":"crossref","first-page":"11259","DOI":"10.1021\/bi00093a001","article-title":"Effect of cavity-creating mutations in the hydrophobic core of chymotrypsin inhibitor 2","volume":"32","author":"Jackson","year":"1993","journal-title":"Biochemistry"},{"key":"2023062300081193500_btaa159-B17","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1002\/prot.24040","article-title":"Structural features that predict real-value fluctuations of globular proteins","volume":"80","author":"Jamroz","year":"2012","journal-title":"Proteins"},{"key":"2023062300081193500_btaa159-B18","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1093\/bioinformatics\/btu791","article-title":"MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins","volume":"31","author":"Jones","year":"2015","journal-title":"Bioinformatics"},{"key":"2023062300081193500_btaa159-B19","doi-asserted-by":"crossref","first-page":"2577","DOI":"10.1002\/bip.360221211","article-title":"Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features","volume":"22","author":"Kabsch","year":"1983","journal-title":"Biopolymers"},{"key":"2023062300081193500_btaa159-B20","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1002\/prot.25823","article-title":"Critical assessment of methods of protein structure prediction (CASP)\u2014round XIII","volume":"87","author":"Kryshtafovych","year":"2019","journal-title":"Proteins Struct. Funct. Bioinf"},{"key":"2023062300081193500_btaa159-B21","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.sbi.2015.01.003","article-title":"Structural and physico-chemical effects of disease and non-disease nsSNPs on proteins","volume":"32","author":"Kucukkal","year":"2015","journal-title":"Curr. Opin. Struct. Biol"},{"key":"2023062300081193500_btaa159-B22","doi-asserted-by":"crossref","first-page":"4324","DOI":"10.1021\/bi00132a025","article-title":"Structural and energetic consequences of disruptive mutations in a protein core","volume":"31","author":"Lim","year":"1992","journal-title":"Biochemistry"},{"key":"2023062300081193500_btaa159-B23","first-page":"25","article-title":"Machine learning approaches for protein\u2013protein interaction hot spot prediction: progress and comparative assessment","volume":"23","author":"Liu","year":"2018","journal-title":"Mol. J. Synth. Chem. Nat. Prod. Chem"},{"key":"2023062300081193500_btaa159-B24","doi-asserted-by":"crossref","first-page":"2592","DOI":"10.1093\/bioinformatics\/btu352","article-title":"SSpro\/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity","volume":"30","author":"Magnan","year":"2014","journal-title":"Bioinformatics"},{"key":"2023062300081193500_btaa159-B25","doi-asserted-by":"crossref","first-page":"e28766","DOI":"10.1371\/journal.pone.0028766","article-title":"Protein 3D structure computed from evolutionary sequence variation","volume":"6","author":"Marks","year":"2011","journal-title":"PLos One"},{"key":"2023062300081193500_btaa159-B26","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1016\/S0022-2836(05)80134-2","article-title":"SCOP: a structural classification of proteins database for the investigation of sequences and structures","volume":"247","author":"Murzin","year":"1995","journal-title":"J. Mol. Biol"},{"key":"2023062300081193500_btaa159-B27","doi-asserted-by":"crossref","first-page":"e09248","DOI":"10.7554\/eLife.09248","article-title":"Large-scale determination of previously unsolved protein structures using evolutionary information","volume":"4","author":"Ovchinnikov","year":"2015","journal-title":"eLife"},{"key":"2023062300081193500_btaa159-B28","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/S0076-6879(96)66033-9","volume-title":"Methods in Enzymology, Computer Methods for Macromolecular Sequence Analysis","author":"Rost","year":"1996"},{"key":"2023062300081193500_btaa159-B29","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1002\/(SICI)1097-0134(1997)1+<192::AID-PROT25>3.0.CO;2-I","article-title":"Better 1D predictions by experts with machines","volume":"29 (Suppl. 1","author":"Rost","year":"1997","journal-title":"Proteins"},{"key":"2023062300081193500_btaa159-B30","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1093\/protein\/12.2.85","article-title":"Twilight zone of protein sequence alignments","volume":"12","author":"Rost","year":"1999","journal-title":"Protein Eng. Des. Sel"},{"key":"2023062300081193500_btaa159-B31","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1093\/bioinformatics\/bty647","article-title":"BIPSPI: a method for the prediction of partner-specific protein\u2013protein interfaces","volume":"35","author":"Sanchez-Garcia","year":"2019","journal-title":"Bioinformatics"},{"key":"2023062300081193500_btaa159-B32","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1002\/(SICI)1097-0282(199603)38:3<305::AID-BIP4>3.0.CO;2-Y","article-title":"Reduced surface: an efficient way to compute molecular surfaces","volume":"38","author":"Sanner","year":"1996","journal-title":"Biopolymers"},{"key":"2023062300081193500_btaa159-B33","doi-asserted-by":"crossref","first-page":"10080","DOI":"10.1073\/pnas.0703737104","article-title":"The selection of acceptable protein mutations","volume":"104","author":"Sasidharan","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023062300081193500_btaa159-B34","doi-asserted-by":"crossref","first-page":"3128","DOI":"10.1093\/bioinformatics\/btu500","article-title":"CCMpred\u2014fast and precise prediction of protein residue\u2013residue contacts from correlated mutations","volume":"30","author":"Seemayer","year":"2014","journal-title":"Bioinformatics"},{"key":"2023062300081193500_btaa159-B35","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1186\/s12864-018-5206-8","article-title":"HseSUMO: Sumoylation site prediction using half-sphere exposures of amino acids residues","volume":"19","author":"Sharma","year":"2019","journal-title":"BMC Genomics"},{"key":"2023062300081193500_btaa159-B36","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1006\/jmbi.1997.0959","article-title":"Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions","volume":"268","author":"Simons","year":"1997","journal-title":"J. Mol. Biol"},{"key":"2023062300081193500_btaa159-B37","doi-asserted-by":"crossref","first-page":"3919","DOI":"10.1016\/j.jmb.2013.07.014","article-title":"Molecular mechanisms of disease-causing missense mutations","volume":"425","author":"Stefl","year":"2013","journal-title":"J. Mol. Biol"},{"key":"2023062300081193500_btaa159-B38","doi-asserted-by":"crossref","first-page":"W515","DOI":"10.1093\/nar\/gkp305","article-title":"NNcon: improved protein contact map prediction using 2D-recursive neural networks","volume":"37","author":"Tegge","year":"2009","journal-title":"Nucleic Acids Res"},{"key":"2023062300081193500_btaa159-B39","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1016\/j.jmb.2010.09.060","article-title":"Pathogenic mutations in the hydrophobic core of the human prion protein can promote structural instability and misfolding","volume":"404","author":"van der Kamp","year":"2010","journal-title":"J. Mol. Biol"},{"key":"2023062300081193500_btaa159-B40","doi-asserted-by":"crossref","first-page":"e43847","DOI":"10.1371\/journal.pone.0043847","article-title":"FunSAV: predicting the functional effect of single amino acid variants using a two-stage random forest model","volume":"7","author":"Wang","year":"2012","journal-title":"PLoS One"},{"key":"2023062300081193500_btaa159-B41","doi-asserted-by":"crossref","first-page":"W430","DOI":"10.1093\/nar\/gkw306","article-title":"RaptorX-property: a web server for protein structure property prediction","volume":"44","author":"Wang","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2023062300081193500_btaa159-B42","doi-asserted-by":"crossref","first-page":"e1005324","DOI":"10.1371\/journal.pcbi.1005324","article-title":"Accurate de novo prediction of protein contact map by ultra-deep learning model","volume":"13","author":"Wang","year":"2017","journal-title":"PLoS Comput. Biol"},{"key":"2023062300081193500_btaa159-B43","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1002\/humu.22","article-title":"SNPs, protein structure, and disease","volume":"17","author":"Wang","year":"2001","journal-title":"Hum. Mutat"},{"key":"2023062300081193500_btaa159-B44","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1038\/nchembio.546","article-title":"Gain of function of mutant p53 by coaggregation with multiple tumor suppressors","volume":"7","author":"Xu","year":"2011","journal-title":"Nat. Chem. Biol"},{"key":"2023062300081193500_btaa159-B45","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1002\/prot.25810","article-title":"Analysis of distance-based protein structure prediction by deep learning in CASP13","volume":"87","author":"Xu","year":"2019","journal-title":"Proteins"},{"key":"2023062300081193500_btaa159-B46","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1038\/nrg.2017.8","article-title":"Functional variomics and network perturbation: connecting genotype to phenotype in cancer","volume":"18","author":"Yi","year":"2017","journal-title":"Nat. Rev. Genet"},{"key":"2023062300081193500_btaa159-B47","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1002\/prot.24979","article-title":"COMSAT: residue contact prediction of transmembrane proteins based on support vector machines and mixed integer linear programming","volume":"84","author":"Zhang","year":"2016","journal-title":"Proteins Struct. Funct. Bioinf"},{"key":"2023062300081193500_btaa159-B48","doi-asserted-by":"crossref","first-page":"e49716","DOI":"10.1371\/journal.pone.0049716","article-title":"An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteins","volume":"7","author":"Zheng","year":"2012","journal-title":"PLoS One"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa159\/33151268\/btaa159.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/11\/3372\/50670629\/bioinformatics_36_11_3372.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/11\/3372\/50670629\/bioinformatics_36_11_3372.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T18:14:19Z","timestamp":1687630459000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/36\/11\/3372\/5802464"}},"subtitle":[],"editor":[{"given":"Arne","family":"Elofsson","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,3,10]]},"references-count":48,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2020,6,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa159","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,6]]},"published":{"date-parts":[[2020,3,10]]}}}