Systematic analysis of protein identity between Zika virus and other arthropod-borne viruses.
Identifieur interne : 000C38 ( PubMed/Corpus ); précédent : 000C37; suivant : 000C39Systematic analysis of protein identity between Zika virus and other arthropod-borne viruses.
Auteurs : Hsiao-Han Chang ; Roland G. Huber ; Peter J. Bond ; Yonatan H. Grad ; David Camerini ; Sebastian Maurer-Stroh ; Marc LipsitchSource :
- Bulletin of the World Health Organization [ 1564-0604 ] ; 2017.
English descriptors
- KwdEn :
- Animals, Chikungunya virus (ultrastructure), Databases, Protein, Dengue Virus (ultrastructure), Encephalitis Virus, Japanese (ultrastructure), Flavivirus (ultrastructure), Humans, Insect Vectors, Polymorphism, Genetic, West Nile virus (ultrastructure), Yellow fever virus (ultrastructure), Zika Virus (ultrastructure).
- MESH :
Abstract
To analyse the proportions of protein identity between Zika virus and dengue, Japanese encephalitis, yellow fever, West Nile and chikungunya viruses as well as polymorphism between different Zika virus strains.
DOI: 10.2471/BLT.16.182105
PubMed: 28670016
Links to Exploration step
pubmed:28670016Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Systematic analysis of protein identity between Zika virus and other arthropod-borne viruses.</title><author><name sortKey="Chang, Hsiao Han" sort="Chang, Hsiao Han" uniqKey="Chang H" first="Hsiao-Han" last="Chang">Hsiao-Han Chang</name><affiliation><nlm:affiliation>Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, Massachusetts, 02115, United States of America (USA).</nlm:affiliation></affiliation></author><author><name sortKey="Huber, Roland G" sort="Huber, Roland G" uniqKey="Huber R" first="Roland G" last="Huber">Roland G. Huber</name><affiliation><nlm:affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</nlm:affiliation></affiliation></author><author><name sortKey="Bond, Peter J" sort="Bond, Peter J" uniqKey="Bond P" first="Peter J" last="Bond">Peter J. Bond</name><affiliation><nlm:affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</nlm:affiliation></affiliation></author><author><name sortKey="Grad, Yonatan H" sort="Grad, Yonatan H" uniqKey="Grad Y" first="Yonatan H" last="Grad">Yonatan H. Grad</name><affiliation><nlm:affiliation>Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Camerini, David" sort="Camerini, David" uniqKey="Camerini D" first="David" last="Camerini">David Camerini</name><affiliation><nlm:affiliation>Antigen Discovery Inc., Irvine, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Maurer Stroh, Sebastian" sort="Maurer Stroh, Sebastian" uniqKey="Maurer Stroh S" first="Sebastian" last="Maurer-Stroh">Sebastian Maurer-Stroh</name><affiliation><nlm:affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</nlm:affiliation></affiliation></author><author><name sortKey="Lipsitch, Marc" sort="Lipsitch, Marc" uniqKey="Lipsitch M" first="Marc" last="Lipsitch">Marc Lipsitch</name><affiliation><nlm:affiliation>Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, Massachusetts, 02115, United States of America (USA).</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2017">2017</date><idno type="RBID">pubmed:28670016</idno><idno type="pmid">28670016</idno><idno type="doi">10.2471/BLT.16.182105</idno><idno type="wicri:Area/PubMed/Corpus">000C38</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000C38</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Systematic analysis of protein identity between Zika virus and other arthropod-borne viruses.</title><author><name sortKey="Chang, Hsiao Han" sort="Chang, Hsiao Han" uniqKey="Chang H" first="Hsiao-Han" last="Chang">Hsiao-Han Chang</name><affiliation><nlm:affiliation>Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, Massachusetts, 02115, United States of America (USA).</nlm:affiliation></affiliation></author><author><name sortKey="Huber, Roland G" sort="Huber, Roland G" uniqKey="Huber R" first="Roland G" last="Huber">Roland G. Huber</name><affiliation><nlm:affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</nlm:affiliation></affiliation></author><author><name sortKey="Bond, Peter J" sort="Bond, Peter J" uniqKey="Bond P" first="Peter J" last="Bond">Peter J. Bond</name><affiliation><nlm:affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</nlm:affiliation></affiliation></author><author><name sortKey="Grad, Yonatan H" sort="Grad, Yonatan H" uniqKey="Grad Y" first="Yonatan H" last="Grad">Yonatan H. Grad</name><affiliation><nlm:affiliation>Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Camerini, David" sort="Camerini, David" uniqKey="Camerini D" first="David" last="Camerini">David Camerini</name><affiliation><nlm:affiliation>Antigen Discovery Inc., Irvine, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Maurer Stroh, Sebastian" sort="Maurer Stroh, Sebastian" uniqKey="Maurer Stroh S" first="Sebastian" last="Maurer-Stroh">Sebastian Maurer-Stroh</name><affiliation><nlm:affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</nlm:affiliation></affiliation></author><author><name sortKey="Lipsitch, Marc" sort="Lipsitch, Marc" uniqKey="Lipsitch M" first="Marc" last="Lipsitch">Marc Lipsitch</name><affiliation><nlm:affiliation>Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, Massachusetts, 02115, United States of America (USA).</nlm:affiliation></affiliation></author></analytic><series><title level="j">Bulletin of the World Health Organization</title><idno type="eISSN">1564-0604</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Chikungunya virus (ultrastructure)</term><term>Databases, Protein</term><term>Dengue Virus (ultrastructure)</term><term>Encephalitis Virus, Japanese (ultrastructure)</term><term>Flavivirus (ultrastructure)</term><term>Humans</term><term>Insect Vectors</term><term>Polymorphism, Genetic</term><term>West Nile virus (ultrastructure)</term><term>Yellow fever virus (ultrastructure)</term><term>Zika Virus (ultrastructure)</term></keywords><keywords scheme="MESH" qualifier="ultrastructure" xml:lang="en"><term>Chikungunya virus</term><term>Dengue Virus</term><term>Encephalitis Virus, Japanese</term><term>Flavivirus</term><term>West Nile virus</term><term>Yellow fever virus</term><term>Zika Virus</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Databases, Protein</term><term>Humans</term><term>Insect Vectors</term><term>Polymorphism, Genetic</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">To analyse the proportions of protein identity between Zika virus and dengue, Japanese encephalitis, yellow fever, West Nile and chikungunya viruses as well as polymorphism between different Zika virus strains.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">28670016</PMID><DateCompleted><Year>2018</Year><Month>04</Month><Day>25</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1564-0604</ISSN><JournalIssue CitedMedium="Internet"><Volume>95</Volume><Issue>7</Issue><PubDate><Year>2017</Year><Month>Jul</Month><Day>01</Day></PubDate></JournalIssue><Title>Bulletin of the World Health Organization</Title><ISOAbbreviation>Bull. World Health Organ.</ISOAbbreviation></Journal><ArticleTitle>Systematic analysis of protein identity between Zika virus and other arthropod-borne viruses.</ArticleTitle><Pagination><MedlinePgn>517-525I</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.2471/BLT.16.182105</ELocationID><Abstract><AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">To analyse the proportions of protein identity between Zika virus and dengue, Japanese encephalitis, yellow fever, West Nile and chikungunya viruses as well as polymorphism between different Zika virus strains.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">We used published protein sequences for the Zika virus and obtained protein sequences for the other viruses from the National Center for Biotechnology Information (NCBI) protein database or the NCBI virus variation resource. We used BLASTP to find regions of identity between viruses. We quantified the identity between the Zika virus and each of the other viruses, as well as within-Zika virus polymorphism for all amino acid <i>k</i>-mers across the proteome, with <i>k</i> ranging from 6 to 100. We assessed accessibility of protein fragments by calculating the solvent accessible surface area for the envelope and nonstructural-1 (NS1) proteins.</AbstractText><AbstractText Label="FINDINGS" NlmCategory="RESULTS">In total, we identified 294 Zika virus protein fragments with both low proportion of identity with other viruses and low levels of polymorphisms among Zika virus strains. The list includes protein fragments from all Zika virus proteins, except NS3. NS4A has the highest number (190 <i>k</i>-mers) of protein fragments on the list.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">We provide a candidate list of protein fragments that could be used when developing a sensitive and specific serological test to detect previous Zika virus infections.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Chang</LastName><ForeName>Hsiao-Han</ForeName><Initials>HH</Initials><AffiliationInfo><Affiliation>Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, Massachusetts, 02115, United States of America (USA).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Huber</LastName><ForeName>Roland G</ForeName><Initials>RG</Initials><AffiliationInfo><Affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bond</LastName><ForeName>Peter J</ForeName><Initials>PJ</Initials><AffiliationInfo><Affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Grad</LastName><ForeName>Yonatan H</ForeName><Initials>YH</Initials><AffiliationInfo><Affiliation>Department of Immunology and Infectious Diseases, Harvard TH Chan School of Public Health, Boston, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Camerini</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Antigen Discovery Inc., Irvine, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Maurer-Stroh</LastName><ForeName>Sebastian</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Bioinformatics Institute (BII), Agency for Science, Technology and Research (ASTAR), Singapore.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lipsitch</LastName><ForeName>Marc</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, Massachusetts, 02115, United States of America (USA).</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>T32 AI007061</GrantID><Acronym>AI</Acronym><Agency>NIAID NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>U54 GM088558</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2016</Year><Month>07</Month><Day>18</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Bull World Health Organ</MedlineTA><NlmUniqueID>7507052</NlmUniqueID><ISSNLinking>0042-9686</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002646" MajorTopicYN="N">Chikungunya virus</DescriptorName><QualifierName UI="Q000648" MajorTopicYN="Y">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D030562" MajorTopicYN="Y">Databases, Protein</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003716" MajorTopicYN="N">Dengue Virus</DescriptorName><QualifierName UI="Q000648" MajorTopicYN="N">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D004664" MajorTopicYN="N">Encephalitis Virus, Japanese</DescriptorName><QualifierName UI="Q000648" MajorTopicYN="N">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005416" MajorTopicYN="N">Flavivirus</DescriptorName><QualifierName UI="Q000648" MajorTopicYN="Y">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007303" MajorTopicYN="N">Insect Vectors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011110" MajorTopicYN="N">Polymorphism, Genetic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014902" MajorTopicYN="N">West Nile virus</DescriptorName><QualifierName UI="Q000648" MajorTopicYN="N">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015005" MajorTopicYN="N">Yellow fever virus</DescriptorName><QualifierName UI="Q000648" MajorTopicYN="N">ultrastructure</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000071244" MajorTopicYN="N">Zika Virus</DescriptorName><QualifierName UI="Q000648" MajorTopicYN="N">ultrastructure</QualifierName></MeshHeading></MeshHeadingList><OtherAbstract Type="Publisher" Language="fre"><AbstractText Label="OBJECTIF" NlmCategory="UNASSIGNED">Analyser les pourcentages de similarité protéique entre le virus Zika et les virus de la dengue, de l'encéphalite japonaise, de la fièvre jaune, du Nil occidental et du chikungunya, ainsi que le polymorphisme entre différentes souches du virus Zika.</AbstractText><AbstractText Label="MÉTHODES" NlmCategory="UNASSIGNED">Nous avons utilisé les séquences protéiques publiées du virus Zika et avons obtenu les séquences protéiques des autres virus dans la banque protéique du National Center for Biotechnology Information (NCBI) ou dans la base de données Virus Variation du NCBI. Nous avons utilisé BLASTP pour identifier les régions de similarité entre les virus. Nous avons quantifié la similarité entre le virus Zika et chacun des autres virus ainsi que le polymorphisme du virus Zika pour tous les <i>k</i>-mers d'acides aminés, dans tout le protéome, avec <i>k</i> allant de 6 à 100. Nous avons étudié l'accessibilité des fragments protéiques en calculant la surface accessible au solvant pour les protéines d'enveloppe et non structurale-1 (NS1).</AbstractText><AbstractText Label="RÉSULTATS" NlmCategory="UNASSIGNED">Au total, nous avons identifié 294 fragments protéiques du virus Zika qui présentent à la fois un faible degré de similarité avec les autres virus et un faible degré de polymorphisme entre les souches du virus Zika. Notre liste comprend des fragments protéiques issus de toutes les protéines du virus Zika, à l'exception de la protéine NS3. Le plus grand nombre de fragments protéiques de notre liste (190 <i>k</i>-mers) correspond à la protéine NS4A.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Nous proposons une liste de fragments protéiques candidats, qui pourraient être utilisés pour concevoir un test sérologique sensible et spécifique pour dépister les infections antérieures par le virus Zika.</AbstractText></OtherAbstract><OtherAbstract Type="Publisher" Language="spa"><AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">Analizar las proporciones de identidad proteica entre el virus de Zika y los virus del dengue, la encefalitis japonesa, la fiebre amarilla, el Nilo Occidental y el chikungunya, así como el polimorfismo entre las distintas cepas del virus de Zika.</AbstractText><AbstractText Label="MÉTODOS" NlmCategory="UNASSIGNED">Se utilizaron secuencias de proteínas publicadas para el virus de Zika y secuencias de proteínas obtenidas para los otros virus de la base de datos de proteínas del Centro Nacional para la Información Biotecnológica (NCBI) o la fuente de información sobre la variación de virus del NCBI. Se utilizó el programa BLASTP para encontrar regiones de identidad entre los virus. Se cuantificó la identidad entre el virus de Zika y cada uno de los otros virus, así como el polimorfismo del virus de Zika para todos los <i>k</i>-mers de aminoácidos a través del proteoma, con una variación de <i>k</i> de 6 a 100. Se evaluó la accesibilidad de los fragmentos proteicos calculando la superficie accesible solvente para las proteínas de envoltura y no estructurales 1 (NS1).</AbstractText><AbstractText Label="RESULTADOS" NlmCategory="UNASSIGNED">En total, se identificaron 294 fragmentos proteicos del virus de Zika con una proporción escasa de identidad con otros virus y con niveles bajos de polimorfismos entre las distintas cepas del virus de Zika. En la lista se incluyen fragmentos proteicos de todas las proteínas del virus de Zika, salvo la NS3. La NS4A cuenta con el mayor número (190 <i>k</i>-mers) de fragmentos proteicos de la lista.</AbstractText><AbstractText Label="CONCLUSIÓN" NlmCategory="UNASSIGNED">Se proporcionó una lista de posibles fragmentos proteicos que podrían utilizarse para desarrollar una prueba serológica sensible y específica para detectar infecciones del virus de Zika anteriores.</AbstractText></OtherAbstract><OtherAbstract Type="Publisher" Language="ara"><AbstractText Label="الغرض" NlmCategory="UNASSIGNED">تحليل مقدار تماثل البروتين بين فيروس زيكا وحمى الضنك، والتهاب الدماغ الياباني، وحمى الصفراء، وفيروس غرب النيل، وشيكونغونيا فضلاً عن تعددية الأشكال بين سلالات فيروس زيكا.</AbstractText><AbstractText Label="الطريقة" NlmCategory="UNASSIGNED">استخدمنا تسلسلات البروتين المنشورة لفيروس زيكا وحصلنا على تسلسلات البروتين لغيره من الفيروسات من قاعدة البيانات الخاصة بالبروتين للمركز الوطني لمعلومات التقانة الحيوية (NCBI) أو مورد اختلاف الفيروسات لمركز NCBI. كما استخدمنا أداة BLASTP للعثور على مناطق التماثل بين الفيروسات. وقمنا بإجراء تحديد كمي لمقدار التماثل بين فيروس زيكا وكلٍ من الفيروسات الأخرى فضلاً عن تعددية الأشكال في فيروس زيكا نفسه لكل ميرات <i>k</i> للأحماض الأمينية السائدة عبر البروتيوم، حيث تتراوح <i>k</i> من 6 إلى 100. وقمنا بتقييم إمكانية الوصول إلى شظايا البروتين من خلال حساب المساحة السطحية التي يمكن للمذيبات الوصول من خلالها للبروتينات المغلفة والبروتين اللابنيوي-1 (NS1).</AbstractText><AbstractText Label="النتائج" NlmCategory="UNASSIGNED">إجمالاً، قمنا بتحديد 294 شظية من شظايا البروتين الخاص بفيروس زيكا مع انخفاض نسبة التماثل مع الفيروسات الأخرى وانخفاض مستويات تعدد الأشكال بين سلالات فيروس زيكا. وتتضمن القائمة شظايا البروتين من جميع بروتينات فيروس زيكا باستثناء بروتين NS3. ويتمتع بروتين NS4A بالرقم الأكبر (190 من ميرات <i>k</i> ) من شظايا البروتين الواردة في القائمة.</AbstractText><AbstractText Label="الاستنتاج" NlmCategory="UNASSIGNED">قمنا بإنشاء قائمة مرشحين لشظايا البروتين والتي يمكن استخدامها عند تطوير اختبار مصلي حساس ومحدد لاكتشاف الحالات السابقة للإصابة بفيروس زيكا.</AbstractText></OtherAbstract><OtherAbstract Type="Publisher" Language="chi"><AbstractText Label="目的" NlmCategory="UNASSIGNED">旨在分析寨卡病毒、登革热、流行性乙型脑炎、黄热病、西尼罗河以及基孔肯雅热病毒之间的蛋白质识别率以及不同寨卡病毒株之间的多态性。.</AbstractText><AbstractText Label="方法" NlmCategory="UNASSIGNED">我们使用已公布的寨卡病毒蛋白质序列，并从国家生物技术信息中心 (NCBI) 蛋白质数据库或国家生物技术信息中心 (NCBI) 病毒变异资源中获取了其他病毒的蛋白质序列。 我们使用 BLASTP 来找出病毒之间的识别区域。 我们量化了寨卡病毒和其他各种病毒之间的蛋白质识别以及寨卡病毒内部多态性，以识别蛋白质组中的所有氨基酸 <i>k</i>-mer，其中 <i>k</i> 的变化范围为 6 到 100。通过计算外膜蛋白和非结构蛋白 1 (NS1) 的溶剂可及表面，我们对蛋白质片段的可及性进行了评估。.</AbstractText><AbstractText Label="结果" NlmCategory="UNASSIGNED">我们共识别出 294 个寨卡病毒蛋白质片段，相较于其他病毒，其识别率较低，且寨卡病毒株之间的多态性程度较低。 上述清单包括所有寨卡病毒蛋白质的蛋白质片段，非结构蛋白 3 (NS3) 除外。 清单中，非结构蛋白 4A (NS4A) 的蛋白质片段数目（190 个 <i>k</i>-mer）最高。.</AbstractText><AbstractText Label="结论" NlmCategory="UNASSIGNED">我们提供了一份蛋白质片段补充目录，可在开发敏感的特殊血清学测试时使用，以检测之前的寨卡病毒感染情况。.</AbstractText></OtherAbstract><OtherAbstract Type="Publisher" Language="rus"><AbstractText Label="Цель" NlmCategory="UNASSIGNED">Проанализировать пропорции белковой идентичности между вирусом Зика и вирусами лихорадки денге, японского энцефалита, желтой лихорадки, лихорадки Западного Нила и лихорадки чикунгунья, а также полиморфизм между различными штаммами вируса Зика.</AbstractText><AbstractText Label="Методы" NlmCategory="UNASSIGNED">Мы использовали опубликованные последовательности белка для вируса Зика и получили последовательности белка для других вирусов из базы данных Национального центра биотехнологической информации (NCBI) или ресурса вирусных вариаций NCBI. Мы использовали программу BLASTP, чтобы найти области идентичности между вирусами. Мы провели количественную оценку идентичности между вирусом Зика и каждым из других вирусов, а также оценку полиморфизма между различными штаммами вируса Зика для всех <i>k</i>-меров аминокислот всего протеома, где <i>k</i> находится в пределах от 6 до 100. Мы оценили доступности фрагментов белка путем расчета доступной для растворителя области поверхности для белков оболочки и неструктурного белка-1 (NS1).</AbstractText><AbstractText Label="Результаты" NlmCategory="UNASSIGNED">В целом мы идентифицировали 294 фрагмента белка вируса Зика с низкой долей идентичности с другими вирусами и низкими уровнями полиморфизма среди штаммов вируса Зика. Этот список включает белковые фрагменты от всех белков вируса Зика, за исключением NS3. В этом списке NS4A имеет самое большое количество (190 <i>k</i>-меров) фрагментов белка.</AbstractText><AbstractText Label="Вывод" NlmCategory="UNASSIGNED">Мы подготовили список белковых фрагментов-кандидатов, которые можно использовать при разработке чувствительного и специфического серологического теста для выявления ранее обнаруженных инфекций, вызываемых вирусом Зика.</AbstractText></OtherAbstract></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2016</Year><Month>07</Month><Day>14</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2016</Year><Month>11</Month><Day>22</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>01</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>7</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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