Automated antibody structure prediction using Accelrys tools: results and best practices.
Proteins
; 82(8): 1583-98, 2014 Aug.
Article
em En
| MEDLINE
| ID: mdl-24833271
ABSTRACT
We describe the methodology and results from our participation in the second Antibody Modeling Assessment experiment. During the experiment we predicted the structure of eleven unpublished antibody Fv fragments. Our prediction methods centered on template-based modeling; potential templates were selected from an antibody database based on their sequence similarity to the target in the framework regions. Depending on the quality of the templates, we constructed models of the antibody framework regions either using a single, chimeric or multiple template approach. The hypervariable loop regions in the initial models were rebuilt by grafting the corresponding regions from suitable templates onto the model. For the H3 loop region, we further refined models using ab initio methods. The final models were subjected to constrained energy minimization to resolve severe local structural problems. The analysis of the models submitted show that Accelrys tools allow for the construction of quite accurate models for the framework and the canonical CDR regions, with RMSDs to the X-ray structure on average below 1 Å for most of these regions. The results show that accurate prediction of the H3 hypervariable loops remains a challenge. Furthermore, model quality assessment of the submitted models show that the models are of quite high quality, with local geometry assessment scores similar to that of the target X-ray structures.
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Base de dados:
MEDLINE
Assunto principal:
Modelos Moleculares
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Regiões Determinantes de Complementaridade
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Anticorpos
Tipo de estudo:
Guideline
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Prognostic_studies
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Risk_factors_studies
Limite:
Animals
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Humans
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article