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BioMed Central, BMC Structural Biology, 1(7), 2007

DOI: 10.1186/1472-6807-7-9

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Evaluation of the structural quality of modeled proteins by using globularity criteria

Journal article published in 2007 by Susan Costantini, Angelo M. Facchiano ORCID, Giovanni Colonna
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Background The knowledge of the three-dimensional structure of globular proteins is fundamental for a detailed investigation of their functional properties. Experimental methods are too slow for structure investigation on a large scale, while computational prediction methods offer alternatives that are continuously being improved. The international Comparative Assessment of Structure Prediction (CASP), an "a posteriori" evaluation of the quality of theoretical models when the experimental structure becomes available, demonstrates that predictions can be successful as well as unsuccessful, and this suggests the necessity for evaluations able to discard "a priori" the wrong models. Results We analyzed different structural properties of globular proteins for experimentally solved proteins belonging to the four different structural classes: "mainly alpha", "mainly beta", "alpha/beta" and "alpha+beta". The properties were found to be linearly correlated to protein molecular weight, but with some differences among the four classes. These results were applied to develop an evaluation test of theoretical models based on the expected globular properties of proteins. To verify the success of our test, we applied it to several protein models submitted to the sixth edition of CASP. The best theoretical models, as judged by CASP assessors, were in agreement with the expected properties, while most of the low-quality models had not passed our evaluations. Conclusion This study supports the need for careful checks to avoid the diffusion of incorrect structural models. Our test allows the evaluation of models in the absence of experimental reference structures, thereby preventing the diffusion of incorrect structural models and the formulation of incorrect functional hypotheses. It can be used to check the globularity of predicted models, and to supplement other methods already used to evaluate their quality.