Computational characterization of the sequence landscape in simple protein alphabets
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Updated: Aug 6, 2026

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
M Scott Shell1, Pablo G Debenedetti, Athanassios Z Panagiotopoulos
1Department of Chemical Engineering, Princeton University, Princeton, NJ 08544, USA. shell@princeton.edu
Abstract:
We characterize the "sequence landscapes" in several simple, heteropolymer models of proteins by examining their mutation properties. Using an efficient flat-histogram Monte Carlo search method, our approach involves determining the distribution in energy of all sequences of a given length when threaded through a common backbone. These calculations are performed for a number of Protein Data Bank structures using two variants of the 20-letter contact potential developed by Miyazawa and Jernigan [Miyazawa S, Jernigan WL. Macromolecules 1985;18:534], and the 2-monomer HP model of Lau and Dill [Lau KF, Dill KA. Macromolecules 1989;22:3986]. Our results indicate significant differences among the energy functions in terms of the "smoothness" of their landscapes. In particular, one of the Miyazawa-Jernigan contact potentials reveals unusual cooperative behavior among its species' interactions, resulting in what is essentially a set of phase transitions in sequence space. Our calculations suggest that model-specific features can have a profound effect on protein design algorithms, and our methods offer a number of ways by which sequence landscapes can be quantified.
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