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

By Robert J. Pantazes, Costas D. Maranas. 2010

106 citations recorded by the source corpus.

Subfields: Molecular Biology, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

RosettaAntibodyDesign (RAbD): A general framework for computational antibody design (2017, methodology): “RAbD is most similar to methods previously developed by two other research groups: OptCDR [41] and OptMAVEn [42], developed by Maranas et al., and AbDesign developed by Fleishman et al. [47] These authors also present computational benchmarking of their meth-ods, and our benchmarking procedures,…”
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures (2022, methodology): “2 Related Work Computational Antibody Design Conventional computational approaches are mostly based on sampling algorithms over hand-crafted and statistical energy functions and iteratively modify protein sequences and structures [1, 29, 49, 36, 38].”
AbDesign: an algorithm for combinatorial backbone design guided by natural conformations and sequences (2015, background): “50 An antibody design strategy was suggested by Pantazes et al.51–53 that capitalizes on observations that antibody CDRs exhibit canonical conformations.”
OptMAVEn – A New Framework for the de novo Design of Antibody Variable Region Models Targeting Specific Antigen Epitopes (2014, methodology): “To address the limitations of current platforms for antibody design, we have developed the OptCDR method that can de novo design an antibody paratope model against any targeted antigen epitope by modeling and optimizing the complementarity determining regions (CDRs) [21].”