A sequence space search engine for computational protein design to modulate molecular functionality

De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Ca...

Full description

Saved in:

Bibliographic Details
Published in:	Journal of biomolecular structure & dynamics Vol. 41; no. 7; pp. 2937 - 2946
Main Authors:	Malik, Ayush, Banerjee, Anupam, Pal, Abantika, Mitra, Pralay
Format:	Journal Article
Language:	English
Published:	England Taylor & Francis 03.05.2023
Subjects:	altering molecular functionality Amino Acid Sequence Computer Simulation high native sequence recapitulation Monte-Carlo parallel search algorithm Protein design protein sequence-structure compatibility Proteins - chemistry Search Engine Solvents Monte-Carlo parallel search algorithm protein sequence-structure compatibility high native sequence recapitulation Protein design altering molecular functionality
ISSN:	0739-1102, 1538-0254, 1538-0254
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds. Communicated by Ramaswamy H. Sarma
AbstractList	De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds. Communicated by Ramaswamy H. Sarma De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds.Communicated by Ramaswamy H. Sarma.De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds.Communicated by Ramaswamy H. Sarma. protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence space search engine for effective convergence in computational protein design. We propose a greedy simulated annealing-based Monte-Carlo parallel search algorithm for better sequence-structure compatibility probing in protein design. The guidance provided by the evolutionary profile, the greedy approach, and the cooling schedule adopted in the Monte Carlo simulation ensures sufficient exploration and exploitation of the search space leading to faster convergence. On evaluating the proposed algorithm, we find that a dataset of 76 target scaffolds report an average root-mean-square-deviation (RMSD) of 1.07 Å and an average TM-Score of 0.93 with the modeled designed protein sequences. High sequence recapitulation of 48.7% (59.4%) observed in the design sequences for all (hydrophobic) solvent-inaccessible residues again establish the goodness of the proposed algorithm. A high (93.4%) intra-group recapitulation of hydrophobic residues in the solvent-inaccessible region indicates that the proposed protein design algorithm preserves the core residues in the protein and provides alternative residue combinations in the solvent-accessible regions of the target protein. Furthermore, a COFACTOR-based protein functional analysis shows that the design sequences exhibit altered molecular functionality and introduce new molecular functions compared to the target scaffolds.Communicated by Ramaswamy H. Sarma.
Author	Banerjee, Anupam Pal, Abantika Mitra, Pralay Malik, Ayush
Author_xml	– sequence: 1 givenname: Ayush surname: Malik fullname: Malik, Ayush organization: Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur – sequence: 2 givenname: Anupam orcidid: 0000-0002-2859-7705 surname: Banerjee fullname: Banerjee, Anupam organization: School of Medical Science and Technology, Indian Institute of Technology Kharagpur – sequence: 3 givenname: Abantika surname: Pal fullname: Pal, Abantika organization: Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur – sequence: 4 givenname: Pralay orcidid: 0000-0003-4119-3788 surname: Mitra fullname: Mitra, Pralay organization: Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/35220920$$D View this record in MEDLINE/PubMed
BookMark	eNp9kU1v2zAMhoWhxZJ-_IQNOu7ilPqwYt8WBP0CCvTSngVFpjsNtpRJMob8-8pI2mMvJEE8JMj3vSBnPngk5AeDFYMGbmAtWsaArzjwOUguGvWNLFktmgp4Lc_IcmaqGVqQi5T-AnDG1uw7WYiac2g5LInd0IT_JvQWadqbOaKJ9g9F_-Y80j5EasO4n7LJLngz0H0MGZ2nHSb35mkOdAzdNJiMpRjQljLSfvL2yLt8uCLnvRkSXp_yJXm9u33ZPlRPz_eP281TZYViuTI1IDDR1ty2YJveKMVhB1J25cWdZK2qO2BG9EIq1pc2KGm5bNfW7lTbgLgkv457y4nlpZT16JLFYTAew5Q0V0LWRYKWF_TnCZ12I3Z6H91o4kF_CFOA-gjYGFKK2H8iDPRsgP4wQM8G6JMBZe73cc75It1o_oc4dDqbwxBiH423Lmnx9Yp3xHCLbw
Cites_doi	10.1073/pnas.0811070106 10.1007/978-3-540-24767-8_41 10.1016/B978-0-12-394292-0.00006-0 10.1093/nar/gks372 10.1002/prot.26263 10.1016/j.bbagen.2019.04.015 10.1109/TCBB.2019.2928809 10.1371/journal.pcbi.1005659 10.1073/pnas.0900266106 10.1006/jmbi.1999.3211 10.1093/bioinformatics/btt055 10.1039/c3cs60137d 10.1126/science.aaf8818 10.1126/science.278.5335.82 10.1038/nmeth.3213 10.1016/j.jmb.2004.11.062 10.1016/j.sbi.2007.03.006 10.1016/j.sbi.2018.04.007 10.1038/356539a0 10.1110/ps.0226603 10.1093/nar/gkl163 10.1093/nar/gkt384 10.1021/ct500864r 10.1126/science.1136782 10.1073/pnas.97.19.10383 10.1093/bioinformatics/btaa234 10.1093/nar/gki387 10.1093/nar/gkl971 10.1038/srep02619 10.1371/journal.pcbi.1003298 10.1126/science.abj8754 10.1002/pro.5560030405 10.1073/pnas.1118082108 10.1021/acs.jproteome.0c00473 10.1021/ja00214a001 10.1016/j.jmb.2011.02.017 10.1016/j.jmb.2018.12.016 10.1038/nature23912 10.1093/bioinformatics/btab496 10.1371/journal.pcbi.0020085 10.1093/nar/gki524
ContentType	Journal Article
Copyright	2022 Informa UK Limited, trading as Taylor & Francis Group 2022
Copyright_xml	– notice: 2022 Informa UK Limited, trading as Taylor & Francis Group 2022
DBID	AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8
DOI	10.1080/07391102.2022.2042386
DatabaseName	CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic
DatabaseTitle	CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic
DatabaseTitleList	MEDLINE - Academic 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: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Biology
EISSN	1538-0254
EndPage	2946
ExternalDocumentID	35220920 10_1080_07391102_2022_2042386 2042386
Genre	Research Article Journal Article
GroupedDBID	--- -~X .QJ 0BK 0R~ 30N 4.4 5GY AAENE AAGDL AAHBH AAHIA AAJMT AALDU AAMIU AAPUL AAQRR ABCCY ABFIM ABJNI ABLIJ ABPAQ ABPEM ABTAI ABXUL ABXYU ACGFS ACTIO ADCVX ADGTB AEISY AENEX AEOZL AEPSL AEYOC AFRVT AGDLA AGMYJ AHDZW AIJEM AIYEW AKBVH AKOOK ALMA_UNASSIGNED_HOLDINGS ALQZU AQRUH AQTUD AVBZW AWYRJ BLEHA CCCUG DGEBU DKSSO EBS EMOBN E~A E~B F5P GTTXZ H13 HZ~ H~P IPNFZ J.P KYCEM LJTGL M4Z NX0 O9- P2P RIG RNANH ROSJB RTWRZ S-T SJN SNACF TASJS TBQAZ TDBHL TEI TFL TFT TFW TQWBC TTHFI TUROJ UT5 ZGOLN ~KM ~S~ AAYXX CITATION 07X 53G AAGME AAOAP ABFMO ABTAA ACBBU ACDHJ ACQMU ACZPZ ADGTR ADOPC ADYSH AFDYB AFFVI AI. AMATQ APNXG AURDB BFWEY C0. CGR CUY CVF CWRZV DLOXE ECM EIF EJD HGUVV JEPSP NPM NUSFT OWHGL PCLFJ S70 VH1 7X8
ID	FETCH-LOGICAL-c361t-a50e013952c90c8fa6620b044d202b41965d01a3f3461f44d064c2497ccb69803
IEDL.DBID	TFW
ISICitedReferencesCount	3
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000762815200001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0739-1102 1538-0254
IngestDate	Fri Sep 05 12:35:05 EDT 2025 Wed Feb 19 02:25:02 EST 2025 Sat Nov 29 02:07:42 EST 2025 Mon Oct 20 23:46:15 EDT 2025
IsDoiOpenAccess	false
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	7
Keywords	Monte-Carlo parallel search algorithm protein sequence-structure compatibility high native sequence recapitulation Protein design altering molecular functionality
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c361t-a50e013952c90c8fa6620b044d202b41965d01a3f3461f44d064c2497ccb69803
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ORCID	0000-0003-4119-3788 0000-0002-2859-7705
OpenAccessLink	https://figshare.com/articles/journal_contribution/A_sequence_space_search_engine_for_computational_protein_design_to_modulate_molecular_functionality/19242582
PMID	35220920
PQID	2634521192
PQPubID	23479
PageCount	10
ParticipantIDs	proquest_miscellaneous_2634521192 crossref_primary_10_1080_07391102_2022_2042386 pubmed_primary_35220920 informaworld_taylorfrancis_310_1080_07391102_2022_2042386
PublicationCentury	2000
PublicationDate	2023-05-03
PublicationDateYYYYMMDD	2023-05-03
PublicationDate_xml	– month: 05 year: 2023 text: 2023-05-03 day: 03
PublicationDecade	2020
PublicationPlace	England
PublicationPlace_xml	– name: England
PublicationTitle	Journal of biomolecular structure & dynamics
PublicationTitleAlternate	J Biomol Struct Dyn
PublicationYear	2023
Publisher	Taylor & Francis
Publisher_xml	– name: Taylor & Francis
References	CIT0030 CIT0010 CIT0032 CIT0031 CIT0012 CIT0034 CIT0011 CIT0033 Banerjee A. (CIT0005) 2018; 17 Leaver-Fay A. (CIT0025) 2011; 487 CIT0014 CIT0036 CIT0013 CIT0035 CIT0016 CIT0038 CIT0015 CIT0037 CIT0018 CIT0017 CIT0039 CIT0019 CIT0041 CIT0040 CIT0021 CIT0043 CIT0020 CIT0042 CIT0001 CIT0023 CIT0022 CIT0003 CIT0002 CIT0024 CIT0027 CIT0004 CIT0026 CIT0007 CIT0029 CIT0006 CIT0028 CIT0009 CIT0008
References_xml	– ident: CIT0029 doi: 10.1073/pnas.0811070106 – ident: CIT0001 doi: 10.1007/978-3-540-24767-8_41 – ident: CIT0024 doi: 10.1016/B978-0-12-394292-0.00006-0 – ident: CIT0035 doi: 10.1093/nar/gks372 – ident: CIT0031 doi: 10.1002/prot.26263 – ident: CIT0034 doi: 10.1016/j.bbagen.2019.04.015 – ident: CIT0006 doi: 10.1109/TCBB.2019.2928809 – ident: CIT0016 doi: 10.1371/journal.pcbi.1005659 – ident: CIT0011 doi: 10.1073/pnas.0900266106 – ident: CIT0022 doi: 10.1006/jmbi.1999.3211 – ident: CIT0033 doi: 10.1093/bioinformatics/btt055 – ident: CIT0010 doi: 10.1039/c3cs60137d – ident: CIT0003 doi: 10.1126/science.aaf8818 – ident: CIT0013 doi: 10.1126/science.278.5335.82 – ident: CIT0041 doi: 10.1038/nmeth.3213 – ident: CIT0036 doi: 10.1016/j.jmb.2004.11.062 – ident: CIT0009 doi: 10.1016/j.sbi.2007.03.006 – ident: CIT0017 doi: 10.1016/j.sbi.2018.04.007 – ident: CIT0014 doi: 10.1038/356539a0 – volume: 17 start-page: 392 issue: 6 year: 2018 ident: CIT0005 publication-title: Briefings in Functional Genomics – ident: CIT0039 doi: 10.1110/ps.0226603 – volume: 487 start-page: 545 volume-title: Methods in enzymology year: 2011 ident: CIT0025 – ident: CIT0026 doi: 10.1093/nar/gkl163 – ident: CIT0028 doi: 10.1093/nar/gkt384 – ident: CIT0030 doi: 10.1021/ct500864r – ident: CIT0042 doi: 10.1126/science.1136782 – ident: CIT0023 doi: 10.1073/pnas.97.19.10383 – ident: CIT0018 doi: 10.1093/bioinformatics/btaa234 – ident: CIT0037 doi: 10.1093/nar/gki387 – ident: CIT0008 doi: 10.1093/nar/gkl971 – ident: CIT0040 doi: 10.1038/srep02619 – ident: CIT0027 doi: 10.1371/journal.pcbi.1003298 – ident: CIT0002 doi: 10.1126/science.abj8754 – ident: CIT0019 doi: 10.1002/pro.5560030405 – ident: CIT0032 doi: 10.1073/pnas.1118082108 – ident: CIT0004 doi: 10.1021/acs.jproteome.0c00473 – ident: CIT0020 doi: 10.1021/ja00214a001 – ident: CIT0007 doi: 10.1016/j.jmb.2011.02.017 – ident: CIT0038 doi: 10.1016/j.jmb.2018.12.016 – ident: CIT0012 doi: 10.1038/nature23912 – ident: CIT0021 doi: 10.1093/bioinformatics/btab496 – ident: CIT0015 doi: 10.1371/journal.pcbi.0020085 – ident: CIT0043 doi: 10.1093/nar/gki524
SSID	ssj0021171
Score	2.3493843
Snippet	De-novo protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient... protein design explores the untapped sequence space that is otherwise less discovered during the evolutionary process. This necessitates an efficient sequence...
SourceID	proquest pubmed crossref informaworld
SourceType	Aggregation Database Index Database Publisher
StartPage	2937
SubjectTerms	altering molecular functionality Amino Acid Sequence Computer Simulation high native sequence recapitulation Monte-Carlo parallel search algorithm Protein design protein sequence-structure compatibility Proteins - chemistry Search Engine Solvents
Title	A sequence space search engine for computational protein design to modulate molecular functionality
URI	https://www.tandfonline.com/doi/abs/10.1080/07391102.2022.2042386 https://www.ncbi.nlm.nih.gov/pubmed/35220920 https://www.proquest.com/docview/2634521192
Volume	41
WOSCitedRecordID	wos000762815200001&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: PRVAWR databaseName: Taylor & Francis Online Journals customDbUrl: eissn: 1538-0254 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0021171 issn: 0739-1102 databaseCode: TFW dateStart: 19831001 isFulltext: true titleUrlDefault: https://www.tandfonline.com providerName: Taylor & Francis
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwELagAomF96M8KiOxBvzKw2OFqBhQxVCgWxQ7ttSBBDUpEv8en5NUdKgYYImiKE5sn893Z5-_D6EbFmpnFEMeZEqQQAhNAqVoFnAeMyNzZhsEvteneDxOplP53GYTVm1aJcTQtgGK8HM1KHemqi4j7g42l5zVgmNUDC7OI0gAdNuZflDNyehtGXJR6kMuKBFAke4Mz7qvrFinFezS9R6ot0SjvX9owz7abd1QPGzGzQHaMMUh2m6IKb-OkB7iLscauykHrl4jsPHwhdhVGGvPB9GuJWKP9zArcO4zQnBd4vcyB2ow425aBl4MRrR53_n-x-hl9DC5fwxaOoZA84jWQRYSAw5jyLQkOrFZFDGiiBC5a4MSAE2YE5pxy0VErXvsvB3tortYaxXJhPAT1CvKwpwhrHkehVYqE5JMhIlMrFWS5YYkJlexpH1024kh_WhQN1LagZm2PZdCz6Vtz_WR_CmstPbLHbbhJkn5L2WvO8mmTrdgwyQrTLmoUhZxEQIEHuuj00bky-qA40okI-d_-PMF2gH2ep8_yS9Rr54vzBXa0p_1rJoP0GY8TQZ-PH8D_bru_w
linkProvider	Taylor & Francis
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1NT9wwEB1RaAUXoEDLAi2uxDXg-COJjwixWtTtnrYtNyt2bIkDSQUBiX9fj5Osdg-IQ3uxoshObI_tmbHH7wGcMWmDUpQ8KY2giRCWJsakZcJ5zpyqmO8Q-H5N89msuL1Vy3dhMKwSfWjfAUXEtRonN25GDyFxF3i6FNQW3qNimASToMjewYYMuhbx8-fj3wunK02j04VFEiwz3OJ57TMr-mkFvfR1GzTqovHO_2jFLmz3lii57IbOR1hz9R586LgpX_bBXpIhzJqEVQfTOCmIiwiGJNSY2EgJ0W8nkgj5cFeTKgaFkLYh902F7GAuPPQkvAT1aJc_mP8H8HN8Pb-aJD0jQ2J5lrZJKalDm1Eyq6gtfJlljBoqRBXaYASiE1Y0LbnnIkt9eB0MHhscvNxak6mC8k-wXje1OwRieZVJr4yTtBSyUIX3RrHK0cJVJlfpCM4HOeg_HfCGTgc8077nNPac7ntuBGpZWrqNOx6-oyfR_I2y3wbR6jC98MykrF3z9KhZxoVEFDw2gs-dzBfVQduVKkaP_uHPp7A5mf-Y6unN7PsxbCGZfQyn5Cew3j48uS_w3j63d48PX-Ow_guG1PJB
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3Pb9MwFH4aHUy7bDBgdAxmJK4Zju248XECqk1U1Q4b9GbFv6QdSKs2m7T_Hj8nqdZDxQEuVhTZie1n-33Pfv4ewGdW2KgUC55VRtBMCEszY_Iq43zEvHIstAx8Pyej6bSczdR150246twq0YYOLVFEWqtxci9c6D3ivuDhUtRaeI2KYRIRQSmfwW6EzhIH-c3419rmyvNkc2GRDMv0l3i2fWZDPW2Ql26HoEkVjQ__QyNewkGHQ8lFO3BewY6vj-BFG5ny8TXYC9I7WZO45mCapgTxib-QxAoTmwJCdJuJJBE-3NXEJZcQ0szJ77nD2GA-PnQheAlq0TZ_BP9v4Hb8_ebrZdbFY8gsl3mTVQX1iBgLZhW1ZaikZNRQIVxsgxHITehoXvHAhcxDfB3hjo3m3chaI1VJ-VsY1PPavwNiuZNFUMYXtBJFqcoQjGLO09I7M1L5EM57MehFS7uh857NtOs5jT2nu54bgnoqLN2k_Y7QBifR_C9lP_WS1XFy4YlJVfv5_UozyUWBHHhsCMetyNfVQeRKFaMn__DnM9i7_jbWk6vpj_ewj5Hsky8lP4VBs7z3H-C5fWjuVsuPaVD_AbGa8PM
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=A+sequence+space+search+engine+for+computational+protein+design+to+modulate+molecular+functionality&rft.jtitle=Journal+of+biomolecular+structure+%26+dynamics&rft.au=Malik%2C+Ayush&rft.au=Banerjee%2C+Anupam&rft.au=Pal%2C+Abantika&rft.au=Mitra%2C+Pralay&rft.date=2023-05-03&rft.pub=Taylor+%26+Francis&rft.issn=0739-1102&rft.eissn=1538-0254&rft.volume=41&rft.issue=7&rft.spage=2937&rft.epage=2946&rft_id=info:doi/10.1080%2F07391102.2022.2042386&rft.externalDocID=2042386
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0739-1102&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0739-1102&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0739-1102&client=summon