Disjoint combinations profiling (DCP): a new method for the prediction of antibody CDR conformation from sequence
A peer-reviewed article of this Preprint also exists.
Author and article information
Abstract
The accurate prediction of the conformation of Complementarity-Determining Regions (CDRs) is important in modelling antibodies for protein engineering applications. Specifically, the Canonical paradigm has proved successful in predicting the CDR conformation in antibody variable regions. It relies on canonical templates which detail allowed residues at key positions in the variable region framework or in the CDR itself for 5 of the 6 CDRs. While no templates have as yet been defined for the hypervariable CDR-H3, instead, reliable sequence rules have been devised for predicting the base of the CDR-H3 loop. Here a new method termed Disjoint Combinations Profiling (DCP) is presented, which contributes a considerable advance in the prediction of CDR conformations. This novel method is explained and compared with canonical templates and sequence rules in a 3-way blind prediction. DCP achieved 93% accuracy over 951 blind predictions and showed an improvement in cumulative accuracy compared to predictions with canonical templates or sequence-rules. In addition to its overall improvement in prediction accuracy, it is suggested that DCP is open to better implementations in the future and that it can improve as more antibody structures are deposited in the databank. In contrast, it is argued that canonical templates and sequence rules may have reached their peak.
Cite this as
2014. Disjoint combinations profiling (DCP): a new method for the prediction of antibody CDR conformation from sequence. PeerJ PrePrints 2:e292v3 https://doi.org/10.7287/peerj.preprints.292v3Author comment
A paper presenting a new classification of antibody CDR conformations, upon which the present methods' training/updating was based, is conjointly submitted to PeerJ preprint server, titled:"A complete, multi-level conformational clustering of antibody complementarity-determining regions." Version 2: added DOI of conjoint paper. Version 3: minor amendments.
Sections
Supplemental Information
Appendix with collection of tables outlining the detected multi-conformation full-rogue clusters
Notable features include resolutions close to 3Å and R-free > 0.25.
Appendix: absolute probabilistic significance of IF fragment disjointness
Presentation of a probabilistic closed-form equation for selecting only statistically significant signature signals.
Detailed canonical templates by CDR/Length
Canonical templates were derived from the clustering set for every applicable conformational cluster, using the definitions of structurally-determining residues described in Martin & Thornton, (1996).
Individual predictions per CDR
Detailed tables with all predictions for every CDR in the test sets, along with a measure of RMSD distance of the Query conformation from the closest cluster medoid.
Additional Information
Competing Interests
The authors report no competing interests.
Author Contributions
Dimitris Nikoloudis conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Jim E. Pitts contributed reagents/materials/analysis tools, reviewed drafts of the paper, expert advice, general project supervision.
José W. Saldanha conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper, expert advice, general project supervision.
Funding
The authors declare no external funding sources.