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Biophys. J. BioFAST: First Published September 17, 2004. doi:10.1529/biophysj.104.042044
© 2004 by the Biophysical Society.


A more recent version of this article appeared on January 1, 2005.
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BIOPHYSICAL THEORY AND MODELING

Computational Protein Design Is a Challenge for Implicit Solvation Models

Alfonso Jaramillo 1 and Shoshana Wodak 2*

1 Ecole Polytechnique
2 Université Libre de Bruxelles

* To whom correspondence should be addressed. E-mail: shosh{at}scmbb.ulb.ac.be.

Submitted on March 2, 2004
Revised on April 19, 2004
Accepted on 7 September 2004


   Abstract
Increasingly complex schemes for representing solvent effects in an implicit fashion are being used in computational analyses of biological macromolecules. These schemes speed up the calculations by orders of magnitude and are assumed to compromise little on essential features of the solvation phenomenon. In this work we examine this assumption. Five implicit solvation models, a surface area-based empirical model, two models that approximate the generalised Born treatment and a Finite Difference Poisson Boltzmann method are challenged in situations differing from those where these models were calibrated. These situations are encountered in automatic protein design procedures, whose job is to select sequences that stabilise a given protein 3D structure from a large number of alternatives. To this end we evaluate the energetic cost of burying amino acids in thousands environments with different solvent exposures belonging respectively, to decoys built with random sequences and to native protein crystal structures. In addition we perform actual sequence design calculations. Except for the crudest surface-area based procedure, all the tested models tend to favour the burial of polar amino acid in the protein interior over non-polar ones, a behaviour that leads to poor performance in protein design calculations. We show on the other hand that 3 of the examined models are nonetheless capable of discriminating between the native fold and many non-native alternatives, a test commonly used to validate force fields. It is concluded that protein design is a particularly challenging test for implicit solvation models because it requires accurate estimates of the solvation contribution of individual residues. This contrasts with native recognition, which depends less on solvation and more on other non-bonded contributions.

Key Words: Continuum Electrostatics, Implicit Solvation, Protein Design, Transfer Free Energy




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Copyright © 2004 by the Biophysical Society.