Literature DB >> 20847101

OptCDR: a general computational method for the design of antibody complementarity determining regions for targeted epitope binding.

R J Pantazes1, C D Maranas.   

Abstract

Antibodies are an important class of proteins with many biomedical and biotechnical applications. Although there are a plethora of experimental techniques geared toward their efficient production, there is a paucity of computational methods for their de novo design. OptCDR is a general computational method to design the binding portions of antibodies to have high specificity and affinity against any targeted epitope of an antigen. First, combinations of canonical structures for the antibody complementarity determining regions (CDRs) that are most likely to be able to favorably bind the antigen are selected. This is followed by the simultaneous refinement of the CDR structures' backbones and optimal amino acid selection for each position. OptCDR is applied to three computational test cases: a peptide from the capsid of hepatitis C, the hapten fluorescein and the protein vascular endothelial growth factor. The results demonstrate that OptCDR can efficiently generate diverse antibody libraries of a pre-specified size with promising antigen affinity potential as exemplified by computationally derived binding metrics.

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Year:  2010        PMID: 20847101     DOI: 10.1093/protein/gzq061

Source DB:  PubMed          Journal:  Protein Eng Des Sel        ISSN: 1741-0126            Impact factor:   1.650


  24 in total

1.  Rational design of antibodies targeting specific epitopes within intrinsically disordered proteins.

Authors:  Pietro Sormanni; Francesco A Aprile; Michele Vendruscolo
Journal:  Proc Natl Acad Sci U S A       Date:  2015-07-27       Impact factor: 11.205

Review 2.  Advances in Antibody Design.

Authors:  Kathryn E Tiller; Peter M Tessier
Journal:  Annu Rev Biomed Eng       Date:  2015-08-14       Impact factor: 9.590

3.  Forcefield_PTM: Ab Initio Charge and AMBER Forcefield Parameters for Frequently Occurring Post-Translational Modifications.

Authors:  George A Khoury; Jeff P Thompson; James Smadbeck; Chris A Kieslich; Christodoulos A Floudas
Journal:  J Chem Theory Comput       Date:  2013-12-10       Impact factor: 6.006

4.  mmCSM-AB: guiding rational antibody engineering through multiple point mutations.

Authors:  Yoochan Myung; Douglas E V Pires; David B Ascher
Journal:  Nucleic Acids Res       Date:  2020-07-02       Impact factor: 16.971

5.  Computational de novo design of antibodies binding to a peptide with high affinity.

Authors:  Venkata Giridhar Poosarla; Tong Li; Boon Chong Goh; Klaus Schulten; Thomas K Wood; Costas D Maranas
Journal:  Biotechnol Bioeng       Date:  2017-02-02       Impact factor: 4.530

6.  Analysis and modeling of the variable region of camelid single-domain antibodies.

Authors:  Aroop Sircar; Kayode A Sanni; Jiye Shi; Jeffrey J Gray
Journal:  J Immunol       Date:  2011-04-27       Impact factor: 5.422

7.  Structure-based non-canonical amino acid design to covalently crosslink an antibody-antigen complex.

Authors:  Jianqing Xu; Drew Tack; Randall A Hughes; Andrew D Ellington; Jeffrey J Gray
Journal:  J Struct Biol       Date:  2013-05-13       Impact factor: 2.867

Review 8.  Protein folding and de novo protein design for biotechnological applications.

Authors:  George A Khoury; James Smadbeck; Chris A Kieslich; Christodoulos A Floudas
Journal:  Trends Biotechnol       Date:  2013-11-19       Impact factor: 19.536

9.  AbDesign: An algorithm for combinatorial backbone design guided by natural conformations and sequences.

Authors:  Gideon D Lapidoth; Dror Baran; Gabriele M Pszolla; Christoffer Norn; Assaf Alon; Michael D Tyka; Sarel J Fleishman
Journal:  Proteins       Date:  2015-06-06

10.  MAPs: a database of modular antibody parts for predicting tertiary structures and designing affinity matured antibodies.

Authors:  Robert J Pantazes; Costas D Maranas
Journal:  BMC Bioinformatics       Date:  2013-05-30       Impact factor: 3.169

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