Assessment of flexible backbone protein design methods for sequence library prediction in the therapeutic antibody Herceptin-HER2 interface

Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low-energy sequences compatible with a desired structure and function. Incorporating backbone flexibility in computational design allows conformational adjustments that shou...

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Published inProtein science Vol. 20; no. 6; pp. 1082 - 1089
Main Authors Babor, Mariana, Mandell, Daniel J, Kortemme, Tanja
Format Journal Article
LanguageEnglish
Published United States Wiley Subscription Services, Inc 01.06.2011
Wiley Subscription Services, Inc., A Wiley Company
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Abstract Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low-energy sequences compatible with a desired structure and function. Incorporating backbone flexibility in computational design allows conformational adjustments that should broaden the range of predicted low-energy sequences. Here, we evaluate computational predictions of sequence libraries from different protocols for modeling backbone flexibility using the complex between the therapeutic antibody Herceptin and its target human epidermal growth factor receptor 2 (HER2) as a model system. Within the program RosettaDesign, three methods are compared: The first two use ensembles of structures generated by Monte Carlo protocols for near-native conformational sampling: kinematic closure (KIC) and backrub, and the third method uses snapshots from molecular dynamics (MD) simulations. KIC or backrub methods were better able to identify the amino acid residues experimentally observed by phage display in the Herceptin-HER2 interface than MD snapshots, which generated much larger conformational and sequence diversity. KIC and backrub, as well as fixed backbone simulations, captured the key mutation Asp98Trp in Herceptin, which leads to a further threefold affinity improvement of the already subnanomolar parental Herceptin-HER2 interface. Modeling subtle backbone conformational changes may assist in the design of sequence libraries for improving the affinity of antibody-antigen interfaces and could be suitable for other protein complexes for which structural information is available.
AbstractList Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low-energy sequences compatible with a desired structure and function. Incorporating backbone flexibility in computational design allows conformational adjustments that should broaden the range of predicted low-energy sequences. Here, we evaluate computational predictions of sequence libraries from different protocols for modeling backbone flexibility using the complex between the therapeutic antibody Herceptin and its target human epidermal growth factor receptor 2 (HER2) as a model system. Within the program RosettaDesign, three methods are compared: The first two use ensembles of structures generated by Monte Carlo protocols for near-native conformational sampling: kinematic closure (KIC) and backrub, and the third method uses snapshots from molecular dynamics (MD) simulations. KIC or backrub methods were better able to identify the amino acid residues experimentally observed by phage display in the Herceptin-HER2 interface than MD snapshots, which generated much larger conformational and sequence diversity. KIC and backrub, as well as fixed backbone simulations, captured the key mutation Asp98Trp in Herceptin, which leads to a further threefold affinity improvement of the already subnanomolar parental Herceptin-HER2 interface. Modeling subtle backbone conformational changes may assist in the design of sequence libraries for improving the affinity of antibody-antigen interfaces and could be suitable for other protein complexes for which structural information is available. [PUBLICATION ABSTRACT]
Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low-energy sequences compatible with a desired structure and function. Incorporating backbone flexibility in computational design allows conformational adjustments that should broaden the range of predicted low-energy sequences. Here, we evaluate computational predictions of sequence libraries from different protocols for modeling backbone flexibility using the complex between the therapeutic antibody Herceptin and its target human epidermal growth factor receptor 2 (HER2) as a model system. Within the program RosettaDesign, three methods are compared: The first two use ensembles of structures generated by Monte Carlo protocols for near-native conformational sampling: kinematic closure (KIC) and backrub, and the third method uses snapshots from molecular dynamics (MD) simulations. KIC or backrub methods were better able to identify the amino acid residues experimentally observed by phage display in the Herceptin-HER2 interface than MD snapshots, which generated much larger conformational and sequence diversity. KIC and backrub, as well as fixed backbone simulations, captured the key mutation Asp98Trp in Herceptin, which leads to a further threefold affinity improvement of the already subnanomolar parental Herceptin-HER2 interface. Modeling subtle backbone conformational changes may assist in the design of sequence libraries for improving the affinity of antibody-antigen interfaces and could be suitable for other protein complexes for which structural information is available.
Abstract Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low‐energy sequences compatible with a desired structure and function. Incorporating backbone flexibility in computational design allows conformational adjustments that should broaden the range of predicted low‐energy sequences. Here, we evaluate computational predictions of sequence libraries from different protocols for modeling backbone flexibility using the complex between the therapeutic antibody Herceptin and its target human epidermal growth factor receptor 2 (HER2) as a model system. Within the program RosettaDesign, three methods are compared: The first two use ensembles of structures generated by Monte Carlo protocols for near‐native conformational sampling: kinematic closure (KIC) and backrub, and the third method uses snapshots from molecular dynamics (MD) simulations. KIC or backrub methods were better able to identify the amino acid residues experimentally observed by phage display in the Herceptin–HER2 interface than MD snapshots, which generated much larger conformational and sequence diversity. KIC and backrub, as well as fixed backbone simulations, captured the key mutation Asp98Trp in Herceptin, which leads to a further threefold affinity improvement of the already subnanomolar parental Herceptin‐HER2 interface. Modeling subtle backbone conformational changes may assist in the design of sequence libraries for improving the affinity of antibody–antigen interfaces and could be suitable for other protein complexes for which structural information is available.
Author Kortemme, Tanja
Mandell, Daniel J
Babor, Mariana
AuthorAffiliation 2 Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, California 94158-2330
1 California Institute for Quantitative Biomedical Research, University of California San Francisco, San Francisco, California 94158-2330
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Cites_doi 10.1126/science.278.5335.82
10.1093/protein/gzp042
10.1002/prot.10613
10.1016/S0022-2836(02)00677-0
10.1016/j.str.2005.10.007
10.1038/nbt0905-1073
10.1016/j.jmb.2008.05.006
10.1016/j.sbi.2004.03.001
10.1006/jmbi.2001.4949
10.1371/journal.pcbi.0020085
10.1073/pnas.212627499
10.1016/j.str.2008.09.012
10.1073/pnas.0707977104
10.1002/prot.20185
10.1016/j.jmb.2008.05.023
10.1016/0022-2836(87)90358-5
10.1016/j.jmb.2010.07.032
10.1016/j.jmb.2007.04.069
10.1016/0021-9991(77)90098-5
10.1126/science.282.5393.1462
10.1126/science.1089427
10.1002/pro.5560060810
10.1016/j.str.2007.09.024
10.1529/biophysj.107.110627
10.1006/jmbi.1999.2866
10.1007/978-94-015-7658-1_21
10.1073/pnas.0609647103
10.1038/nmeth0809-551
10.1093/bioinformatics/btm197
10.1016/j.copbio.2009.07.006
10.1007/s008940100045
10.1110/ps.0203902
10.1016/j.sbi.2010.02.004
10.1371/journal.pcbi.1000393
10.1063/1.448118
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Additional Supporting Information may be found in the online version of this article.
Grant sponsor: NSF; Grant numbers: MCB-0744541 and EF-0849400 (to T.K.); Grant sponsors: University of California Lab Research Program (to T.K.) and PhRMA Foundation Predoctoral Fellowship (to D.J.M.).
Author contributions: M.B.: conceived and designed the experiments, performed the experiments and analyzed the data, discussed the data and wrote the manuscript; T.K.: conceived and designed the experiments, discussed the data and wrote the manuscript; D.J.M.: developed the KIC refinement design protocol, discussed the data and wrote the manuscript.
Mariana Babor's current address is Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, California 92037.
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References 17971437 - Proc Natl Acad Sci U S A. 2007 Nov 6;104(45):17668-73
16472746 - Structure. 2006 Feb;14(2):265-74
19081054 - Structure. 2008 Dec 10;16(12):1777-88
17827237 - Biophys J. 2008 Jan 15;94(2):584-99
18547585 - J Mol Biol. 2008 Jul 18;380(4):742-56
11545603 - J Mol Biol. 2001 Sep 7;312(1):289-307
9822371 - Science. 1998 Nov 20;282(5393):1462-7
18073107 - Structure. 2007 Dec;15(12):1567-76
17646295 - Bioinformatics. 2007 Jul 1;23(13):i185-94
12441379 - Protein Sci. 2002 Dec;11(12):2804-13
2441069 - J Mol Biol. 1987 Feb 20;193(4):775-91
19709874 - Curr Opin Biotechnol. 2009 Aug;20(4):420-8
14631033 - Science. 2003 Nov 21;302(5649):1364-8
9311930 - Science. 1997 Oct 3;278(5335):82-7
20654621 - J Mol Biol. 2010 Sep 17;402(2):460-74
15048827 - Proteins. 2004 May 1;55(2):351-67
19644455 - Nat Methods. 2009 Aug;6(8):551-2
16151394 - Nat Biotechnol. 2005 Sep;23(9):1073-8
15093835 - Curr Opin Struct Biol. 2004 Apr;14(2):202-7
19643976 - Protein Eng Des Sel. 2009 Sep;22(9):575-86
16839198 - PLoS Comput Biol. 2006 Jul 7;2(7):e85
18547586 - J Mol Biol. 2008 Jul 18;380(4):757-74
12206766 - J Mol Biol. 2002 Aug 30;321(5):851-62
10388574 - J Mol Biol. 1999 Jul 2;290(1):305-18
17179210 - Proc Natl Acad Sci U S A. 2007 Jan 2;104(1):48-53
9260282 - Protein Sci. 1997 Aug;6(8):1701-7
17597151 - J Mol Biol. 2007 Aug 24;371(4):1099-117
15340927 - Proteins. 2004 Nov 1;57(2):400-13
20303740 - Curr Opin Struct Biol. 2010 Jun;20(3):377-84
19478996 - PLoS Comput Biol. 2009 May;5(5):e1000393
12446841 - Proc Natl Acad Sci U S A. 2002 Dec 10;99(25):15926-31
e_1_2_7_5_2
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e_1_2_7_2_2
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e_1_2_7_8_2
e_1_2_7_7_2
e_1_2_7_6_2
e_1_2_7_19_2
e_1_2_7_18_2
e_1_2_7_17_2
e_1_2_7_16_2
e_1_2_7_15_2
e_1_2_7_14_2
e_1_2_7_13_2
e_1_2_7_12_2
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e_1_2_7_10_2
e_1_2_7_26_2
e_1_2_7_27_2
e_1_2_7_28_2
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Press W (e_1_2_7_32_2) 2007
van Gunsteren WF (e_1_2_7_34_2) 1996
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e_1_2_7_38_2
References_xml – ident: e_1_2_7_3_2
  doi: 10.1126/science.278.5335.82
– ident: e_1_2_7_24_2
  doi: 10.1093/protein/gzp042
– ident: e_1_2_7_35_2
  doi: 10.1002/prot.10613
– ident: e_1_2_7_28_2
  doi: 10.1016/S0022-2836(02)00677-0
– ident: e_1_2_7_26_2
  doi: 10.1016/j.str.2005.10.007
– ident: e_1_2_7_25_2
  doi: 10.1038/nbt0905-1073
– ident: e_1_2_7_31_2
  doi: 10.1016/j.jmb.2008.05.006
– ident: e_1_2_7_5_2
  doi: 10.1016/j.sbi.2004.03.001
– ident: e_1_2_7_4_2
  doi: 10.1006/jmbi.2001.4949
– ident: e_1_2_7_11_2
  doi: 10.1371/journal.pcbi.0020085
– ident: e_1_2_7_29_2
  doi: 10.1073/pnas.212627499
– ident: e_1_2_7_17_2
  doi: 10.1016/j.str.2008.09.012
– ident: e_1_2_7_22_2
  doi: 10.1073/pnas.0707977104
– ident: e_1_2_7_14_2
  doi: 10.1002/prot.20185
– ident: e_1_2_7_16_2
  doi: 10.1016/j.jmb.2008.05.023
– ident: e_1_2_7_2_2
  doi: 10.1016/0022-2836(87)90358-5
– ident: e_1_2_7_23_2
  doi: 10.1016/j.jmb.2010.07.032
– ident: e_1_2_7_13_2
  doi: 10.1016/j.jmb.2007.04.069
– ident: e_1_2_7_37_2
  doi: 10.1016/0021-9991(77)90098-5
– ident: e_1_2_7_19_2
  doi: 10.1126/science.282.5393.1462
– ident: e_1_2_7_20_2
  doi: 10.1126/science.1089427
– ident: e_1_2_7_8_2
  doi: 10.1002/pro.5560060810
– ident: e_1_2_7_15_2
  doi: 10.1016/j.str.2007.09.024
– ident: e_1_2_7_21_2
  doi: 10.1529/biophysj.107.110627
– ident: e_1_2_7_9_2
  doi: 10.1006/jmbi.1999.2866
– ident: e_1_2_7_36_2
  doi: 10.1007/978-94-015-7658-1_21
– ident: e_1_2_7_30_2
  doi: 10.1073/pnas.0609647103
– ident: e_1_2_7_27_2
  doi: 10.1038/nmeth0809-551
– ident: e_1_2_7_12_2
  doi: 10.1093/bioinformatics/btm197
– ident: e_1_2_7_7_2
  doi: 10.1016/j.copbio.2009.07.006
– ident: e_1_2_7_33_2
  doi: 10.1007/s008940100045
– ident: e_1_2_7_10_2
  doi: 10.1110/ps.0203902
– volume-title: Biomolecular simulation: the GROMOS96 manual and user guide
  year: 1996
  ident: e_1_2_7_34_2
  contributor:
    fullname: van Gunsteren WF
– ident: e_1_2_7_6_2
  doi: 10.1016/j.sbi.2010.02.004
– ident: e_1_2_7_18_2
  doi: 10.1371/journal.pcbi.1000393
– volume-title: Numerical Recipes: The Art of Scientific Computing
  year: 2007
  ident: e_1_2_7_32_2
  contributor:
    fullname: Press W
– ident: e_1_2_7_38_2
  doi: 10.1063/1.448118
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Snippet Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low-energy sequences compatible...
Abstract Computational protein design methods can complement experimental screening and selection techniques by predicting libraries of low‐energy sequences...
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SubjectTerms Amino Acid Sequence
Antibodies, Monoclonal - chemistry
Antibodies, Monoclonal - immunology
Antibodies, Monoclonal, Humanized
Antigen-Antibody Complex - chemistry
Antigen-Antibody Complex - immunology
Computer Simulation
Drug Design
For the Record
Humans
Libraries
Methods
Models, Molecular
Molecular Sequence Data
Protein Conformation
Proteins
Receptor, ErbB-2 - chemistry
Receptor, ErbB-2 - immunology
Trastuzumab
Title Assessment of flexible backbone protein design methods for sequence library prediction in the therapeutic antibody Herceptin-HER2 interface
URI https://www.ncbi.nlm.nih.gov/pubmed/21465611
https://www.proquest.com/docview/1519495448
https://search.proquest.com/docview/867720737
https://pubmed.ncbi.nlm.nih.gov/PMC3104238
Volume 20
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