An in silico platform for predicting, screening and designing of antihypertensive peptides

High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. Peptides from natural origin have been shown recently to be highly effective in lowering blood pressure. In the present study, we have framed a platform for predicting and designing novel antihypertensiv...

Full description

Saved in:

Bibliographic Details
Published in:	Scientific reports Vol. 5; no. 1; p. 12512
Main Authors:	Kumar, Ravi, Chaudhary, Kumardeep, Singh Chauhan, Jagat, Nagpal, Gandharva, Kumar, Rahul, Sharma, Minakshi, Raghava, Gajendra P.S.
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 27.07.2015 Nature Publishing Group
Subjects:	631/114 631/114/2398 631/154/1435/2418 Accuracy Algorithms Amino acid composition Amino Acid Sequence Amino acids Antihypertensive Agents - administration & dosage Antihypertensive Agents - chemistry Antihypertensives Blood pressure Drug Design Drug Evaluation, Preclinical - methods Humanities and Social Sciences Hypertension Molecular Sequence Data multidisciplinary Pattern Recognition, Automated - methods Peptides Peptides - administration & dosage Peptides - chemistry Regression analysis Science Sequence Alignment - methods Sequence Analysis, Protein - methods Software Support Vector Machine
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. Peptides from natural origin have been shown recently to be highly effective in lowering blood pressure. In the present study, we have framed a platform for predicting and designing novel antihypertensive peptides. Due to a large variation found in the length of antihypertensive peptides, we divided these peptides into four categories (i) Tiny peptides, (ii) small peptides, (iii) medium peptides and (iv) large peptides. First, we developed SVM based regression models for tiny peptides using chemical descriptors and achieved maximum correlation of 0.701 and 0.543 for dipeptides and tripeptides, respectively. Second, classification models were developed for small peptides and achieved maximum accuracy of 76.67%, 72.04% and 77.39% for tetrapeptide, pentapeptide and hexapeptides, respectively. Third, we have developed a model for medium peptides using amino acid composition and achieved maximum accuracy of 82.61%. Finally, we have developed a model for large peptides using amino acid composition and achieved maximum accuracy of 84.21%. Based on the above study, a web-based platform has been developed for locating antihypertensive peptides in a protein, screening of peptides and designing of antihypertensive peptides.
AbstractList	High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. Peptides from natural origin have been shown recently to be highly effective in lowering blood pressure. In the present study, we have framed a platform for predicting and designing novel antihypertensive peptides. Due to a large variation found in the length of antihypertensive peptides, we divided these peptides into four categories (i) Tiny peptides, (ii) small peptides, (iii) medium peptides and (iv) large peptides. First, we developed SVM based regression models for tiny peptides using chemical descriptors and achieved maximum correlation of 0.701 and 0.543 for dipeptides and tripeptides, respectively. Second, classification models were developed for small peptides and achieved maximum accuracy of 76.67%, 72.04% and 77.39% for tetrapeptide, pentapeptide and hexapeptides, respectively. Third, we have developed a model for medium peptides using amino acid composition and achieved maximum accuracy of 82.61%. Finally, we have developed a model for large peptides using amino acid composition and achieved maximum accuracy of 84.21%. Based on the above study, a web-based platform has been developed for locating antihypertensive peptides in a protein, screening of peptides and designing of antihypertensive peptides. High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. Peptides from natural origin have been shown recently to be highly effective in lowering blood pressure. In the present study, we have framed a platform for predicting and designing novel antihypertensive peptides. Due to a large variation found in the length of antihypertensive peptides, we divided these peptides into four categories (i) Tiny peptides, (ii) small peptides, (iii) medium peptides and (iv) large peptides. First, we developed SVM based regression models for tiny peptides using chemical descriptors and achieved maximum correlation of 0.701 and 0.543 for dipeptides and tripeptides, respectively. Second, classification models were developed for small peptides and achieved maximum accuracy of 76.67%, 72.04% and 77.39% for tetrapeptide, pentapeptide and hexapeptides, respectively. Third, we have developed a model for medium peptides using amino acid composition and achieved maximum accuracy of 82.61%. Finally, we have developed a model for large peptides using amino acid composition and achieved maximum accuracy of 84.21%. Based on the above study, a web-based platform has been developed for locating antihypertensive peptides in a protein, screening of peptides and designing of antihypertensive peptides.High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. Peptides from natural origin have been shown recently to be highly effective in lowering blood pressure. In the present study, we have framed a platform for predicting and designing novel antihypertensive peptides. Due to a large variation found in the length of antihypertensive peptides, we divided these peptides into four categories (i) Tiny peptides, (ii) small peptides, (iii) medium peptides and (iv) large peptides. First, we developed SVM based regression models for tiny peptides using chemical descriptors and achieved maximum correlation of 0.701 and 0.543 for dipeptides and tripeptides, respectively. Second, classification models were developed for small peptides and achieved maximum accuracy of 76.67%, 72.04% and 77.39% for tetrapeptide, pentapeptide and hexapeptides, respectively. Third, we have developed a model for medium peptides using amino acid composition and achieved maximum accuracy of 82.61%. Finally, we have developed a model for large peptides using amino acid composition and achieved maximum accuracy of 84.21%. Based on the above study, a web-based platform has been developed for locating antihypertensive peptides in a protein, screening of peptides and designing of antihypertensive peptides.
ArticleNumber	12512
Author	Kumar, Rahul Kumar, Ravi Raghava, Gajendra P.S. Sharma, Minakshi Nagpal, Gandharva Chaudhary, Kumardeep Singh Chauhan, Jagat
Author_xml	– sequence: 1 givenname: Ravi surname: Kumar fullname: Kumar, Ravi organization: Bioinformatics Centre, CSIR-Institute of Microbial Technology – sequence: 2 givenname: Kumardeep surname: Chaudhary fullname: Chaudhary, Kumardeep organization: Bioinformatics Centre, CSIR-Institute of Microbial Technology – sequence: 3 givenname: Jagat surname: Singh Chauhan fullname: Singh Chauhan, Jagat organization: Bioinformatics Centre, CSIR-Institute of Microbial Technology – sequence: 4 givenname: Gandharva surname: Nagpal fullname: Nagpal, Gandharva organization: Bioinformatics Centre, CSIR-Institute of Microbial Technology – sequence: 5 givenname: Rahul surname: Kumar fullname: Kumar, Rahul organization: Bioinformatics Centre, CSIR-Institute of Microbial Technology – sequence: 6 givenname: Minakshi surname: Sharma fullname: Sharma, Minakshi organization: Bioinformatics Centre, CSIR-Institute of Microbial Technology – sequence: 7 givenname: Gajendra P.S. surname: Raghava fullname: Raghava, Gajendra P.S. organization: Bioinformatics Centre, CSIR-Institute of Microbial Technology
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/26213115$$D View this record in MEDLINE/PubMed
BookMark	eNptkc1uGyEUhVGVKM6PF32BCqmbpqprLjOMmU2kKGrTSJGyaTbZIAZfbKIxTAFHytsX10nkpGEBF_ju0YFzRPZ88EjIR2DfgVVymiIOwAXwD-SQs1pMeMX53k49IuOU7lkZgrc1tAdkxBsOFYA4JHfnnjpPk-udCXTodbYhrmiZ6BBx7kx2fvGNJhMRfSmp9nM6x-QW_3bBloPslo8Dxow-uQekAw7ZFeSE7FvdJxw_rcfk9ueP3xe_Jtc3l1cX59cTU1cyT7ADI8ysQxAzKzqGLZu1AHIGDLRhgMJKDq0WXDDZdMLU3DCDxjbW1lbq6picbXWHdbfCuUGfo-7VEN1Kx0cVtFOvb7xbqkV4ULUA0bC6CHx5EojhzxpTViuXDPa99hjWSUHTtnXLpOQF_fwGvQ_r6MvzFMgNVUxCoT7tOnqx8vztBZhuARNDKgFaZVzW2YWNQdcrYGqTrXrJtnScvul4Fn2P_bplU2H8AuOOyf_gv2Pws9A
CitedBy_id	crossref_primary_10_1016_j_foodchem_2022_132089 crossref_primary_10_1016_j_ab_2024_115523 crossref_primary_10_3390_biom14080930 crossref_primary_10_3390_foods12183480 crossref_primary_10_1002_prot_25763 crossref_primary_10_1007_s12539_022_00521_3 crossref_primary_10_1016_j_foodchem_2022_132889 crossref_primary_10_1371_journal_pone_0287577 crossref_primary_10_1016_j_jmb_2025_169005 crossref_primary_10_3390_foods13223550 crossref_primary_10_3390_molecules26072064 crossref_primary_10_3390_nu14142794 crossref_primary_10_3390_bioengineering10111300 crossref_primary_10_1039_D4FO00405A crossref_primary_10_1016_j_tifs_2024_104578 crossref_primary_10_1016_j_tifs_2021_05_031 crossref_primary_10_3390_ijms20174159 crossref_primary_10_1007_s00726_022_03190_0 crossref_primary_10_1016_j_lwt_2022_114008 crossref_primary_10_1016_j_foodchem_2025_143391 crossref_primary_10_1007_s11030_021_10350_z crossref_primary_10_1016_j_biortech_2022_126932 crossref_primary_10_3390_md20050317 crossref_primary_10_1109_TCBB_2021_3068381 crossref_primary_10_1007_s11030_022_10489_3 crossref_primary_10_1093_bib_bbw025 crossref_primary_10_1016_j_foodres_2024_115651 crossref_primary_10_1186_s12967_019_1813_7 crossref_primary_10_4155_fmc_2017_0300 crossref_primary_10_1016_j_foodchem_2025_143084 crossref_primary_10_3390_nu12113588 crossref_primary_10_1007_s10989_019_09874_8 crossref_primary_10_1016_j_ygeno_2020_03_019 crossref_primary_10_3389_fnut_2022_920945 crossref_primary_10_4155_fmc_2016_0188 crossref_primary_10_1016_j_foodchem_2022_132145 crossref_primary_10_1016_j_idairyj_2025_106265 crossref_primary_10_1080_1062936X_2025_2552141 crossref_primary_10_3390_antibiotics9120854 crossref_primary_10_1016_j_foodchem_2016_12_039 crossref_primary_10_1007_s00216_018_0983_0 crossref_primary_10_1016_j_bbapap_2020_140406 crossref_primary_10_3389_fnut_2022_1118900 crossref_primary_10_3390_foods14020252 crossref_primary_10_1016_j_fbio_2022_102199 crossref_primary_10_3390_ijms20061496 crossref_primary_10_3382_ps_pez430 crossref_primary_10_1016_j_foodres_2023_113836 crossref_primary_10_1016_j_lwt_2020_110502 crossref_primary_10_1016_j_cmpb_2024_108514 crossref_primary_10_1111_cbdd_13617 crossref_primary_10_26599_FSHW_2024_9250377 crossref_primary_10_1007_s11030_021_10277_5 crossref_primary_10_3390_molecules24101973 crossref_primary_10_1039_D5CP00407A crossref_primary_10_3389_fgene_2021_801728 crossref_primary_10_3389_fmicb_2018_02551 crossref_primary_10_1080_10408398_2017_1319795 crossref_primary_10_1016_j_jmb_2025_169448 crossref_primary_10_1007_s10989_022_10414_0 crossref_primary_10_1111_1750_3841_13840 crossref_primary_10_3390_md16100365 crossref_primary_10_1016_j_ijbiomac_2024_137060 crossref_primary_10_1016_j_ymeth_2024_12_005 crossref_primary_10_1016_j_jcs_2020_103130 crossref_primary_10_1093_ijfood_vvae011 crossref_primary_10_3389_fnut_2022_950823 crossref_primary_10_1038_s41598_019_41649_5 crossref_primary_10_1016_j_fufo_2025_100648 crossref_primary_10_1038_s41598_017_02114_3 crossref_primary_10_3390_fermentation9020152 crossref_primary_10_1016_j_foodchem_2021_131919 crossref_primary_10_1002_med_21764 crossref_primary_10_1016_j_compbiomed_2025_109821 crossref_primary_10_1002_widm_1437 crossref_primary_10_1016_j_tifs_2019_08_017 crossref_primary_10_1111_ics_12635 crossref_primary_10_1039_D3FO01703F crossref_primary_10_1049_syb2_70002 crossref_primary_10_1002_jsfa_13474 crossref_primary_10_3389_feduc_2023_1290287 crossref_primary_10_1016_j_heliyon_2024_e28060 crossref_primary_10_1016_j_foodchem_2025_144432 crossref_primary_10_3389_fmicb_2018_00476 crossref_primary_10_1002_pro_70026 crossref_primary_10_1016_j_foodres_2022_111549 crossref_primary_10_3389_fgene_2022_883766 crossref_primary_10_3390_genes14061194 crossref_primary_10_1016_j_tifs_2022_06_014 crossref_primary_10_1016_j_addr_2022_114322 crossref_primary_10_1016_j_compbiomed_2024_108926 crossref_primary_10_1016_j_jfca_2025_107483 crossref_primary_10_1007_s43393_022_00125_4 crossref_primary_10_1088_1755_1315_967_1_012017 crossref_primary_10_3390_pharmaceutics14010122 crossref_primary_10_1371_journal_pone_0228265 crossref_primary_10_3390_ijms23052439 crossref_primary_10_1016_j_compbiomed_2023_107386 crossref_primary_10_1016_j_compbiomed_2025_110528 crossref_primary_10_18632_oncotarget_20365 crossref_primary_10_1186_s43141_022_00330_7 crossref_primary_10_1631_jzus_B2000520 crossref_primary_10_3389_fmicb_2018_00725 crossref_primary_10_1007_s10989_018_09802_2 crossref_primary_10_1002_jsfa_8908 crossref_primary_10_1016_j_foodres_2023_112706 crossref_primary_10_3390_ijms25031798 crossref_primary_10_3390_molecules28020651 crossref_primary_10_1016_j_tifs_2021_07_018 crossref_primary_10_3390_molecules28134901 crossref_primary_10_1089_cmb_2022_0241 crossref_primary_10_3390_app11052316 crossref_primary_10_1002_med_21658 crossref_primary_10_1371_journal_pone_0196829 crossref_primary_10_1016_j_jff_2019_103636 crossref_primary_10_1016_j_bbrc_2019_03_064
Cites_doi	10.1177/026119290503300508 10.1093/nar/gkn823 10.1021/ci500172z 10.1073/pnas.73.11.3942 10.1016/j.meatsci.2012.02.007 10.1093/nar/gkm998 10.1002/qsar.200610151 10.1002/jcc.21707 10.1186/1479-5876-11-74 10.1007/s00894-010-0862-x 10.1093/nar/gkt1008 10.1186/1471-2105-11-125 10.1371/journal.pcbi.1002101 10.1016/j.cis.2010.11.001 10.1371/journal.pone.0067863 10.1007/978-0-387-74087-4_12 10.1016/j.vaccine.2004.02.005 10.1021/ci300004n 10.1021/cr3004339 10.1186/1758-2946-6-32 10.1080/10408398.2012.664829 10.1111/1541-4337.12051 10.1016/j.foodchem.2013.05.140 10.1093/bioinformatics/bth261 10.1093/bioinformatics/16.5.412 10.1177/026119290503300209 10.1371/journal.pone.0035187 10.1093/database/bas015 10.2174/1381612033454883 10.1371/journal.pone.0018476 10.1371/journal.pone.0061437 10.1093/jn/134.4.980S 10.1021/ci800151m 10.1002/minf.201100053 10.1093/nar/gku1141 10.7551/mitpress/1130.003.0015 10.1093/jaoac/91.4.965 10.1093/nar/gku892 10.1093/database/bau051 10.1038/srep01607
ContentType	Journal Article
Copyright	The Author(s) 2015 Copyright Nature Publishing Group Jul 2015 Copyright © 2015, Macmillan Publishers Limited 2015 Macmillan Publishers Limited
Copyright_xml	– notice: The Author(s) 2015 – notice: Copyright Nature Publishing Group Jul 2015 – notice: Copyright © 2015, Macmillan Publishers Limited 2015 Macmillan Publishers Limited
DBID	C6C AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7X7 7XB 88A 88E 88I 8FE 8FH 8FI 8FJ 8FK ABUWG AEUYN AFKRA AZQEC BBNVY BENPR BHPHI CCPQU DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M2P M7P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS Q9U 7X8 5PM
DOI	10.1038/srep12512
DatabaseName	SpringerOpen Free (Free internet resource, activated by CARLI) CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Health & Medical Collection ProQuest Central (purchase pre-March 2016) Biology Database (Alumni Edition) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest SciTech Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni Edition) ProQuest One Sustainability ProQuest Central UK/Ireland ProQuest Central Essentials - QC Biological Science Collection ProQuest Central Natural Science Collection ProQuest One Community College ProQuest Central Korea Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) ProQuest Biological Science Collection Health & Medical Collection (Alumni Edition) Medical Database Science Database Biological Science Database Proquest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic MEDLINE - Academic PubMed Central (Full Participant titles)
DatabaseTitle	CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Publicly Available Content Database ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Central China ProQuest Biology Journals (Alumni Edition) ProQuest Central ProQuest One Applied & Life Sciences ProQuest One Sustainability ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic
DatabaseTitleList	MEDLINE - Academic CrossRef Publicly Available Content Database MEDLINE
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Biology
EISSN	2045-2322
ExternalDocumentID	PMC4515604 26213115 10_1038_srep12512
Genre	Research Support, Non-U.S. Gov't Journal Article
GroupedDBID	0R~ 3V. 4.4 53G 5VS 7X7 88A 88E 88I 8FE 8FH 8FI 8FJ AAFWJ AAJSJ AAKDD ABDBF ABUWG ACGFS ACSMW ACUHS ADBBV ADRAZ AENEX AEUYN AFKRA AJTQC ALIPV ALMA_UNASSIGNED_HOLDINGS AOIJS AZQEC BAWUL BBNVY BCNDV BENPR BHPHI BPHCQ BVXVI C6C CCPQU DIK DWQXO EBD EBLON EBS EJD ESX FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE KQ8 LK8 M0L M1P M2P M48 M7P M~E NAO OK1 PIMPY PQQKQ PROAC PSQYO RNT RNTTT RPM SNYQT UKHRP AASML AAYXX AFFHD AFPKN CITATION PHGZM PHGZT PJZUB PPXIY PQGLB CGR CUY CVF ECM EIF NPM 7XB 8FK K9. PKEHL PQEST PQUKI PRINS Q9U 7X8 PUEGO 5PM
ID	FETCH-LOGICAL-c438t-eb1c5c7be157f5b0e90791187101ac01e5f8219a525086b5c42c0cecf6ff4f8a3
IEDL.DBID	M7P
ISICitedReferencesCount	132
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000358545300002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2045-2322
IngestDate	Tue Nov 04 01:59:03 EST 2025 Wed Oct 01 14:50:34 EDT 2025 Tue Oct 07 07:10:19 EDT 2025 Mon Jul 21 05:56:40 EDT 2025 Sat Nov 29 05:07:20 EST 2025 Tue Nov 18 22:37:35 EST 2025 Fri Feb 21 02:39:33 EST 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	1
Language	English
License	This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c438t-eb1c5c7be157f5b0e90791187101ac01e5f8219a525086b5c42c0cecf6ff4f8a3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 These authors contributed equally to this work.
OpenAccessLink	https://www.proquest.com/docview/1899492501?pq-origsite=%requestingapplication%
PMID	26213115
PQID	1899492501
PQPubID	2041939
ParticipantIDs	pubmedcentral_primary_oai_pubmedcentral_nih_gov_4515604 proquest_miscellaneous_1699490882 proquest_journals_1899492501 pubmed_primary_26213115 crossref_citationtrail_10_1038_srep12512 crossref_primary_10_1038_srep12512 springer_journals_10_1038_srep12512
PublicationCentury	2000
PublicationDate	2015-07-27
PublicationDateYYYYMMDD	2015-07-27
PublicationDate_xml	– month: 07 year: 2015 text: 2015-07-27 day: 27
PublicationDecade	2010
PublicationPlace	London
PublicationPlace_xml	– name: London – name: England
PublicationTitle	Scientific reports
PublicationTitleAbbrev	Sci Rep
PublicationTitleAlternate	Sci Rep
PublicationYear	2015
Publisher	Nature Publishing Group UK Nature Publishing Group
Publisher_xml	– name: Nature Publishing Group UK – name: Nature Publishing Group
References	Netzeva (CR21) 2005; 33 Sheridan (CR25) 2012; 52 Ling, Burgus, Guillemin (CR1) 1976; 73 Wang (CR17) 2011; 17 Sanders, Johnston, Bridges, Burgess, Willeford (CR29) 2011; 7 Kitts, Weiler (CR15) 2003; 9 CR19 Jaworska, Nikolova-Jeliazkova, Aldenberg (CR22) 2005; 33 CR16 CR37 Escudero, Toldrá, Sentandreu, Nishimura, Arihara (CR14) 2012; 91 Gautam (CR28) 2013; 11 Frank, Hall, Trigg, Holmes, Witten (CR34) 2004; 20 Shahlaei (CR33) 2013; 113 Gautam (CR7) 2014; 42 Hernández-Ledesma, del Mar Contreras, Recio (CR10) 2011; 165 Gramatica (CR20) 2007; 26 Baldi, Brunak, Chauvin, Andersen, Nielsen (CR38) 2000; 16 Carrió, Pinto, Ecker, Sanz, Pastor (CR26) 2014; 54 Zhou, Yang, Ren, Wang, Tian (CR18) 2013; 141 Wang (CR30) 2011; 6 Kumar, Raghava (CR31) 2013; 8 Garg, Tewari, Raghava (CR35) 2010; 11 Saito (CR13) 2008; 606 Kawashima (CR36) 2008; 36 FitzGerald, Murray, Walsh (CR12) 2004; 134 CR6 CR8 Soto, Vazquez, Strickert, Ponzoni (CR24) 2011; 30 Bhasin, Raghava (CR41) 2004; 22 Wang, Li, Wang (CR5) 2009; 37 Wei, Dunbrack (CR40) 2013; 8 CR9 CR27 Gautam (CR3) 2012; 2012 Iwaniak, Minkiewicz, Darewicz (CR2) 2014; 13 Puchalska, Marina Alegre, García López (CR11) 2015; 55 Yap (CR32) 2011; 32 Tetko (CR23) 2008; 48 Kurczab, Smusz, Bojarski (CR39) 2014; 6 Kapoor (CR4) 2012; 7 P Baldi (BFsrep12512_CR38) 2000; 16 AJ Soto (BFsrep12512_CR24) 2011; 30 P Puchalska (BFsrep12512_CR11) 2015; 55 A Garg (BFsrep12512_CR35) 2010; 11 P Gramatica (BFsrep12512_CR20) 2007; 26 T Saito (BFsrep12512_CR13) 2008; 606 M Shahlaei (BFsrep12512_CR33) 2013; 113 RP Sheridan (BFsrep12512_CR25) 2012; 52 BFsrep12512_CR37 BFsrep12512_CR16 CW Yap (BFsrep12512_CR32) 2011; 32 BFsrep12512_CR19 Q Wei (BFsrep12512_CR40) 2013; 8 E Escudero (BFsrep12512_CR14) 2012; 91 G Wang (BFsrep12512_CR5) 2009; 37 A Gautam (BFsrep12512_CR28) 2013; 11 X Wang (BFsrep12512_CR17) 2011; 17 P Wang (BFsrep12512_CR30) 2011; 6 P Zhou (BFsrep12512_CR18) 2013; 141 P Carrió (BFsrep12512_CR26) 2014; 54 BFsrep12512_CR9 BFsrep12512_CR8 R Kumar (BFsrep12512_CR31) 2013; 8 P Kapoor (BFsrep12512_CR4) 2012; 7 A Gautam (BFsrep12512_CR7) 2014; 42 BFsrep12512_CR27 IV Tetko (BFsrep12512_CR23) 2008; 48 M Bhasin (BFsrep12512_CR41) 2004; 22 B Hernández-Ledesma (BFsrep12512_CR10) 2011; 165 TI Netzeva (BFsrep12512_CR21) 2005; 33 J Jaworska (BFsrep12512_CR22) 2005; 33 DD Kitts (BFsrep12512_CR15) 2003; 9 A Gautam (BFsrep12512_CR3) 2012; 2012 RJ FitzGerald (BFsrep12512_CR12) 2004; 134 R Kurczab (BFsrep12512_CR39) 2014; 6 N Ling (BFsrep12512_CR1) 1976; 73 BFsrep12512_CR6 A Iwaniak (BFsrep12512_CR2) 2014; 13 WS Sanders (BFsrep12512_CR29) 2011; 7 E Frank (BFsrep12512_CR34) 2004; 20 S Kawashima (BFsrep12512_CR36) 2008; 36
References_xml	– volume: 33 start-page: 445 year: 2005 end-page: 459 ident: CR22 article-title: QSAR applicabilty domain estimation by projection of the training set descriptor space: a review publication-title: Altern. Lab. Anim. doi: 10.1177/026119290503300508 – volume: 37 start-page: D933 year: 2009 end-page: D937 ident: CR5 article-title: APD2: the updated antimicrobial peptide database and its application in peptide design publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkn823 – volume: 54 start-page: 1500 year: 2014 end-page: 1511 ident: CR26 article-title: Applicability Domain ANalysis (ADAN): a robust method for assessing the reliability of drug property predictions publication-title: J. Chem. Inf. Model. doi: 10.1021/ci500172z – volume: 73 start-page: 3942 year: 1976 end-page: 3946 ident: CR1 article-title: Isolation, primary structure and synthesis of alpha-endorphin and gamma-endorphin, two peptides of hypothalamic-hypophysial origin with morphinomimetic activity publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.73.11.3942 – volume: 91 start-page: 382 year: 2012 end-page: 384 ident: CR14 article-title: Antihypertensive activity of peptides identified in the gastrointestinal digest of pork meat publication-title: Meat Sci. doi: 10.1016/j.meatsci.2012.02.007 – ident: CR16 – volume: 36 start-page: D202 year: 2008 end-page: D205 ident: CR36 article-title: AAindex: amino acid index database, progress report 2008 publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkm998 – ident: CR37 – volume: 26 start-page: 694 year: 2007 end-page: 701 ident: CR20 article-title: Principles of QSAR models validation: internal and external publication-title: QSAR Comb. Sci. doi: 10.1002/qsar.200610151 – volume: 32 start-page: 1466 year: 2011 end-page: 1474 ident: CR32 article-title: PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints publication-title: J. Comput. Chem. doi: 10.1002/jcc.21707 – volume: 11 start-page: 74 year: 2013 ident: CR28 article-title: In silico approaches for designing highly effective cell penetrating peptides publication-title: J. Transl. Med. doi: 10.1186/1479-5876-11-74 – volume: 17 start-page: 1599 year: 2011 end-page: 1606 ident: CR17 article-title: QSAR study on angiotensin-converting enzyme inhibitor oligopeptides based on a novel set of sequence information descriptors publication-title: J. Mol. Model. doi: 10.1007/s00894-010-0862-x – ident: CR6 – volume: 42 start-page: D444 year: 2014 end-page: D449 ident: CR7 article-title: Hemolytik: a database of experimentally determined hemolytic and non-hemolytic peptides publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkt1008 – volume: 11 start-page: 125 year: 2010 ident: CR35 article-title: KiDoQ: using docking based energy scores to develop ligand based model for predicting antibacterials publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-11-125 – ident: CR8 – volume: 7 start-page: e1002101 year: 2011 ident: CR29 article-title: Prediction of cell penetrating peptides by support vector machines publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1002101 – volume: 165 start-page: 23 year: 2011 end-page: 35 ident: CR10 article-title: Antihypertensive peptides: production, bioavailability and incorporation into foods publication-title: Adv. Colloid Interface Sci. doi: 10.1016/j.cis.2010.11.001 – volume: 8 start-page: e67863 year: 2013 ident: CR40 article-title: The role of balanced training and testing data sets for binary classifiers in bioinformatics publication-title: PLoS One doi: 10.1371/journal.pone.0067863 – volume: 606 start-page: 295 year: 2008 end-page: 317 ident: CR13 article-title: Antihypertensive peptides derived from bovine casein and whey proteins publication-title: Adv. Exp. Med. Biol. doi: 10.1007/978-0-387-74087-4_12 – ident: CR27 – volume: 22 start-page: 3195 year: 2004 end-page: 3204 ident: CR41 article-title: Prediction of CTL epitopes using QM, SVM and ANN techniques publication-title: Vaccine doi: 10.1016/j.vaccine.2004.02.005 – ident: CR19 – volume: 52 start-page: 814 year: 2012 end-page: 823 ident: CR25 article-title: Three useful dimensions for domain applicability in QSAR models using random forest publication-title: J. Chem. Inf. Model. doi: 10.1021/ci300004n – volume: 113 start-page: 8093 year: 2013 end-page: 8103 ident: CR33 article-title: Descriptor selection methods in quantitative structure-activity relationship studies: a review study publication-title: Chem. Rev. doi: 10.1021/cr3004339 – volume: 6 start-page: 32 year: 2014 ident: CR39 article-title: The influence of negative training set size on machine learning-based virtual screening publication-title: J. Cheminform. doi: 10.1186/1758-2946-6-32 – volume: 55 start-page: 521 year: 2015 end-page: 551 ident: CR11 article-title: Isolation and characterization of peptides with antihypertensive activity in foodstuffs publication-title: Crit. Rev. Food Sci. Nutr. doi: 10.1080/10408398.2012.664829 – volume: 13 start-page: 114 year: 2014 end-page: 134 ident: CR2 article-title: Food-Originating ACE Inhibitors, Including Antihypertensive Peptides, as Preventive Food Components in Blood Pressure Reduction publication-title: Compr. Rev. Food Sci. Food Saf. doi: 10.1111/1541-4337.12051 – volume: 141 start-page: 2967 year: 2013 end-page: 2973 ident: CR18 article-title: What are the ideal properties for functional food peptides with antihypertensive effect? A computational peptidology approach publication-title: Food Chem. doi: 10.1016/j.foodchem.2013.05.140 – volume: 20 start-page: 2479 year: 2004 end-page: 2481 ident: CR34 article-title: Data mining in bioinformatics using Weka publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth261 – volume: 16 start-page: 412 year: 2000 end-page: 424 ident: CR38 article-title: Assessing the accuracy of prediction algorithms for classification: an overview publication-title: Bioinformatics doi: 10.1093/bioinformatics/16.5.412 – ident: CR9 – volume: 33 start-page: 155 year: 2005 end-page: 173 ident: CR21 article-title: Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52 publication-title: Altern. Lab. Anim. doi: 10.1177/026119290503300209 – volume: 7 start-page: e35187 year: 2012 ident: CR4 article-title: TumorHoPe: a database of tumor homing peptides publication-title: PLoS One doi: 10.1371/journal.pone.0035187 – volume: 2012 start-page: bas015 year: 2012 ident: CR3 article-title: CPPsite: a curated database of cell penetrating peptides publication-title: Database (Oxford). doi: 10.1093/database/bas015 – volume: 9 start-page: 1309 year: 2003 end-page: 1323 ident: CR15 article-title: Bioactive proteins and peptides from food sources. Applications of bioprocesses used in isolation and recovery publication-title: Curr. Pharm. Des. doi: 10.2174/1381612033454883 – volume: 6 start-page: e18476 year: 2011 ident: CR30 article-title: Prediction of antimicrobial peptides based on sequence alignment and feature selection methods publication-title: PLoS One doi: 10.1371/journal.pone.0018476 – volume: 8 start-page: e61437 year: 2013 ident: CR31 article-title: Hybrid approach for predicting coreceptor used by HIV-1 from its V3 loop amino acid sequence publication-title: PLoS One doi: 10.1371/journal.pone.0061437 – volume: 134 start-page: 980S year: 2004 end-page: 988SS ident: CR12 article-title: Hypotensive peptides from milk proteins publication-title: J. Nutr. doi: 10.1093/jn/134.4.980S – volume: 48 start-page: 1733 year: 2008 end-page: 1746 ident: CR23 article-title: Critical assessment of QSAR models of environmental toxicity against Tetrahymena pyriformis: focusing on applicability domain and overfitting by variable selection publication-title: J. Chem. Inf. Model. doi: 10.1021/ci800151m – volume: 30 start-page: 779 year: 2011 end-page: 789 ident: CR24 article-title: Target-Driven Subspace Mapping Methods and Their Applicability Domain Estimation publication-title: Mol. Inform. doi: 10.1002/minf.201100053 – volume: 7 start-page: e1002101 year: 2011 ident: BFsrep12512_CR29 publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1002101 – volume: 16 start-page: 412 year: 2000 ident: BFsrep12512_CR38 publication-title: Bioinformatics doi: 10.1093/bioinformatics/16.5.412 – volume: 8 start-page: e67863 year: 2013 ident: BFsrep12512_CR40 publication-title: PLoS One doi: 10.1371/journal.pone.0067863 – volume: 165 start-page: 23 year: 2011 ident: BFsrep12512_CR10 publication-title: Adv. Colloid Interface Sci. doi: 10.1016/j.cis.2010.11.001 – ident: BFsrep12512_CR16 doi: 10.1093/nar/gku1141 – volume: 33 start-page: 445 year: 2005 ident: BFsrep12512_CR22 publication-title: Altern. Lab. Anim. doi: 10.1177/026119290503300508 – volume: 2012 start-page: bas015 year: 2012 ident: BFsrep12512_CR3 publication-title: Database (Oxford). doi: 10.1093/database/bas015 – volume: 7 start-page: e35187 year: 2012 ident: BFsrep12512_CR4 publication-title: PLoS One doi: 10.1371/journal.pone.0035187 – volume: 13 start-page: 114 year: 2014 ident: BFsrep12512_CR2 publication-title: Compr. Rev. Food Sci. Food Saf. doi: 10.1111/1541-4337.12051 – volume: 26 start-page: 694 year: 2007 ident: BFsrep12512_CR20 publication-title: QSAR Comb. Sci. doi: 10.1002/qsar.200610151 – volume: 54 start-page: 1500 year: 2014 ident: BFsrep12512_CR26 publication-title: J. Chem. Inf. Model. doi: 10.1021/ci500172z – volume: 606 start-page: 295 year: 2008 ident: BFsrep12512_CR13 publication-title: Adv. Exp. Med. Biol. doi: 10.1007/978-0-387-74087-4_12 – volume: 33 start-page: 155 year: 2005 ident: BFsrep12512_CR21 publication-title: Altern. Lab. Anim. doi: 10.1177/026119290503300209 – volume: 6 start-page: 32 year: 2014 ident: BFsrep12512_CR39 publication-title: J. Cheminform. doi: 10.1186/1758-2946-6-32 – volume: 6 start-page: e18476 year: 2011 ident: BFsrep12512_CR30 publication-title: PLoS One doi: 10.1371/journal.pone.0018476 – volume: 22 start-page: 3195 year: 2004 ident: BFsrep12512_CR41 publication-title: Vaccine doi: 10.1016/j.vaccine.2004.02.005 – volume: 32 start-page: 1466 year: 2011 ident: BFsrep12512_CR32 publication-title: J. Comput. Chem. doi: 10.1002/jcc.21707 – volume: 113 start-page: 8093 year: 2013 ident: BFsrep12512_CR33 publication-title: Chem. Rev. doi: 10.1021/cr3004339 – volume: 36 start-page: D202 year: 2008 ident: BFsrep12512_CR36 publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkm998 – volume: 48 start-page: 1733 year: 2008 ident: BFsrep12512_CR23 publication-title: J. Chem. Inf. Model. doi: 10.1021/ci800151m – volume: 17 start-page: 1599 year: 2011 ident: BFsrep12512_CR17 publication-title: J. Mol. Model. doi: 10.1007/s00894-010-0862-x – ident: BFsrep12512_CR9 – volume: 30 start-page: 779 year: 2011 ident: BFsrep12512_CR24 publication-title: Mol. Inform. doi: 10.1002/minf.201100053 – volume: 52 start-page: 814 year: 2012 ident: BFsrep12512_CR25 publication-title: J. Chem. Inf. Model. doi: 10.1021/ci300004n – volume: 37 start-page: D933 year: 2009 ident: BFsrep12512_CR5 publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkn823 – volume: 55 start-page: 521 year: 2015 ident: BFsrep12512_CR11 publication-title: Crit. Rev. Food Sci. Nutr. doi: 10.1080/10408398.2012.664829 – volume: 9 start-page: 1309 year: 2003 ident: BFsrep12512_CR15 publication-title: Curr. Pharm. Des. doi: 10.2174/1381612033454883 – volume: 20 start-page: 2479 year: 2004 ident: BFsrep12512_CR34 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth261 – volume: 134 start-page: 980S year: 2004 ident: BFsrep12512_CR12 publication-title: J. Nutr. doi: 10.1093/jn/134.4.980S – ident: BFsrep12512_CR37 doi: 10.7551/mitpress/1130.003.0015 – volume: 91 start-page: 382 year: 2012 ident: BFsrep12512_CR14 publication-title: Meat Sci. doi: 10.1016/j.meatsci.2012.02.007 – ident: BFsrep12512_CR19 doi: 10.1093/jaoac/91.4.965 – volume: 11 start-page: 74 year: 2013 ident: BFsrep12512_CR28 publication-title: J. Transl. Med. doi: 10.1186/1479-5876-11-74 – ident: BFsrep12512_CR6 doi: 10.1093/nar/gku892 – volume: 42 start-page: D444 year: 2014 ident: BFsrep12512_CR7 publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkt1008 – ident: BFsrep12512_CR8 doi: 10.1093/database/bau051 – volume: 141 start-page: 2967 year: 2013 ident: BFsrep12512_CR18 publication-title: Food Chem. doi: 10.1016/j.foodchem.2013.05.140 – ident: BFsrep12512_CR27 doi: 10.1038/srep01607 – volume: 11 start-page: 125 year: 2010 ident: BFsrep12512_CR35 publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-11-125 – volume: 8 start-page: e61437 year: 2013 ident: BFsrep12512_CR31 publication-title: PLoS One doi: 10.1371/journal.pone.0061437 – volume: 73 start-page: 3942 year: 1976 ident: BFsrep12512_CR1 publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.73.11.3942
SSID	ssj0000529419
Score	2.5167978
Snippet	High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. Peptides from natural origin have been shown recently to be...
SourceID	pubmedcentral proquest pubmed crossref springer
SourceType	Open Access Repository Aggregation Database Index Database Enrichment Source Publisher
StartPage	12512
SubjectTerms	631/114 631/114/2398 631/154/1435/2418 Accuracy Algorithms Amino acid composition Amino Acid Sequence Amino acids Antihypertensive Agents - administration & dosage Antihypertensive Agents - chemistry Antihypertensives Blood pressure Drug Design Drug Evaluation, Preclinical - methods Humanities and Social Sciences Hypertension Molecular Sequence Data multidisciplinary Pattern Recognition, Automated - methods Peptides Peptides - administration & dosage Peptides - chemistry Regression analysis Science Sequence Alignment - methods Sequence Analysis, Protein - methods Software Support Vector Machine
Title	An in silico platform for predicting, screening and designing of antihypertensive peptides
URI	https://link.springer.com/article/10.1038/srep12512 https://www.ncbi.nlm.nih.gov/pubmed/26213115 https://www.proquest.com/docview/1899492501 https://www.proquest.com/docview/1699490882 https://pubmed.ncbi.nlm.nih.gov/PMC4515604
Volume	5
WOSCitedRecordID	wos000358545300002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2045-2322 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000529419 issn: 2045-2322 databaseCode: DOA dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources (ISSN International Center) customDbUrl: eissn: 2045-2322 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000529419 issn: 2045-2322 databaseCode: M~E dateStart: 20110101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Biological Science Database customDbUrl: eissn: 2045-2322 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000529419 issn: 2045-2322 databaseCode: M7P dateStart: 20110101 isFulltext: true titleUrlDefault: http://search.proquest.com/biologicalscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Health & Medical Collection (ProQuest) customDbUrl: eissn: 2045-2322 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000529419 issn: 2045-2322 databaseCode: 7X7 dateStart: 20110101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 2045-2322 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000529419 issn: 2045-2322 databaseCode: BENPR dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 2045-2322 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000529419 issn: 2045-2322 databaseCode: PIMPY dateStart: 20110101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVPQU databaseName: Science Database customDbUrl: eissn: 2045-2322 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000529419 issn: 2045-2322 databaseCode: M2P dateStart: 20110101 isFulltext: true titleUrlDefault: https://search.proquest.com/sciencejournals providerName: ProQuest
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3da9RAEB9sq-BL_dZoPdaPBx8MTTabbO5JqrQo2COIyulL2OwHDRy59C4V_O-d2Uui14ovviyX24EMzO585zcAL6UyghuehVWVVKFQVRWiEVahsQr9j6nVwqPzf_0oZ7N8Pp8WfcJt3bdVDjrRK2qz1JQjP4wxMCAgvSh-056HNDWKqqv9CI0d2COUhMS37hVjjoWqWCKeDoBCSX6IZqf1Jn3bDF3xLa-2SF6qk3rzc3Lrfxm_Dfu948mONiflDlyzzV24sRlF-fMefD9qWN2wdb3Ao8HaherIm2W4sHZFxRxqj37NUMlg4Is_mWoMM779g56WDv_o6jOMald9TzxrqWEGSe7Dl5Pjz-_eh_3chVCLJO9CVN861bKycSpdWkUWA-gpjSXH66t0FNvU5ajoFFVE86xKteA60la7zDnhcpU8gN1m2dhHwHQcGeMcl05EQkZ86nJTWYJgTLVJIx7Aq0EMpe5ByWk2xqL0xfEkL0eJBfB8JG03SBx_IzoYhFD2l3Fd_pZAAM_GbbxGVBtRjV1eIE1GNBRvBPBwI_rxLTzjHpQoALl1KEYCguje3mnqMw_VLVL6Ul0E8GI4Pn-wdZn5x_9m_gncRG8tpcQylwew260u7FO4rn909Xo1gR05l37NJ7D39nhWfJr4BAOup7yY-JuBO8WH0-LbL8wGGOE
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Jb9UwEB6VAoIL-xIoYDaJA1ETx9kOCFVA1aqPpx4KqrgEx4sa6SkvvJeC-qf4jcw4C7wWceuBS5TEo8SJx7N4xt8AvEilFlzzxC_LqPSFLEsflbD0tZFof-RGCYfO_3mSTqfZ4WG-vwY_h70wlFY5yEQnqPVc0Rr5ZoiOAQHpBeHb5ptPVaMoujqU0OjYYs-c_ECXbflm9z2O70vOtz8cvNvx-6oCvhJR1voonFSs0tKEcWrjMjDoHuZUdBuZU6ogNLHNcBpLivdlSRkrwVWgjLKJtcJmMsLnXoCLaEbwzKUK7o9rOhQ1E2E-ABhF2SaqucaZEKtq74wtezYl81Rc1qm77ev_24-6Add6w5ptdTPhJqyZ-hZc7kptntyGL1s1q2q2rGbI-qyZyZasdYYH1iwoWEXp368ZClF07PGUyVoz7dJb6Gpu8UZbHaHXvuhz_llDCUFIcgc-ncuH3YX1el6b-8BUGGhtLU-tCEQa8NxmujQEMRkrHQfcg1fDsBeqB12n2h-zwgX_o6wYOcSDZyNp0yGN_I1oYxj0ohc2y-L3iHvwdGxGMUGxH1mb-THSJERD_pQH9zpWG9_CE-5AlzxIV5hwJCAI8tWWujpyUOQipp34woPnA7v-0a3TnX_w784_gSs7Bx8nxWR3uvcQrqJlGtMiOk83YL1dHJtHcEl9b6vl4rGbdQy-njf3_gKaBm72
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VAhUX3oVAAfOSOBBt4jivA0IVZUXVarUHQBWX4PihRlplw24K6l_j1zHjTQLbIm49cInyGCVO8nk84xl_A_AilVpwzRO_LKPSF7IsfRyEpa-NRPsjN0o4dv7Ph-lkkh0d5dMN-NmvhaG0yl4nOkWt54rmyEchOgZEpBeEI9ulRUz3xm-bbz5VkKJIa19OYwWRA3P6A9235Zv9PfzXLzkfv__47oPfVRjwlYiy1kdFpWKVliaMUxuXgUFXMacC3AhUqYLQxDbDLi0p9pclZawEV4EyyibWCpvJCO97CS6nRFru0ganw_wORdBEmPdkRlE2wiGvcebE-hB4zq49n555Jkbrhr7xjf_5o92E653BzXZXPeQWbJj6NlxdleA8vQNfdmtW1WxZzbBLsGYmW7LiGW5Ys6AgFqWFv2aoXNHhx10ma820S3uho7nFE211jN78olsLwBpKFEKRu_DpQl5sGzbreW3uA1NhoLW1PLUiEGnAc5vp0hD1ZKx0HHAPXvUQKFRHxk41QWaFSwqIsmJAiwfPBtFmxUDyN6GdHgBFp4SWxe-_78HT4TKqD4oJydrMT1AmIRnyszy4t4Ld8BSecEfG5EG6BshBgKjJ16_U1bGjKBcxrdAXHjzvoftHs842_sG_G_8EthC0xeH-5OAhXEODNaa5dZ7uwGa7ODGP4Ir63lbLxWPXARl8vWjw_gIEK3ez
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=An+in+silico+platform+for+predicting%2C+screening+and+designing+of+antihypertensive+peptides&rft.jtitle=Scientific+reports&rft.au=Kumar%2C+Ravi&rft.au=Chaudhary%2C+Kumardeep&rft.au=Singh+Chauhan%2C+Jagat&rft.au=Nagpal%2C+Gandharva&rft.date=2015-07-27&rft.issn=2045-2322&rft.eissn=2045-2322&rft.volume=5&rft.spage=12512&rft_id=info:doi/10.1038%2Fsrep12512&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2045-2322&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2045-2322&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2045-2322&client=summon