Information and redundancy in the burial folding code of globular proteins within a wide range of shapes and sizes

• Published in: Proteins, structure, function, and bioinformatics structure, function, and bioinformatics, 2016-04, Vol.84 (4), p.515-531
• Main Authors: Ferreira, Diogo C., van der Linden, Marx G., de Oliveira, Leandro C., Onuchic, José N., Pereira de Araújo, Antônio F.
• Format: Article
• Language: English
• Subjects: Algorithms; Amino Acid Sequence; atomic burial; Computer Simulation; hydrophobic potential; Models, Molecular; Monte Carlo Method; Protein Folding; protein folding; structure prediction; computer simulation; hydrophobic potential; atomic burial; Protein Structure, Tertiary; Proteins; Proteins - chemistry; structure prediction; Thermodynamics
• ISSN: 0887-3585; 1097-0134
• DOI: 10.1002/prot.24998

ABSTRACT Recent ab initio folding simulations for a limited number of small proteins have corroborated a previous suggestion that atomic burial information obtainable from sequence could be sufficient for tertiary structure determination when combined to sequence‐independent geometrical constraints. Here, we use simulations parameterized by native burials to investigate the required amount of information in a diverse set of globular proteins comprising different structural classes and a wide size range. Burial information is provided by a potential term pushing each atom towards one among a small number L of equiprobable concentric layers. An upper bound for the required information is provided by the minimal number of layers Lmin still compatible with correct folding behavior. We obtain Lmin between 3 and 5 for seven small to medium proteins with 50 ≤ Nr ≤ 110 residues while for a larger protein with Nr = 141 we find that L ≥ 6 is required to maintain native stability. We additionally estimate the usable redundancy for a given L ≥ Lmin from the burial entropy associated to the largest folding‐compatible fraction of “superfluous” atoms, for which the burial term can be turned off or target layers can be chosen randomly. The estimated redundancy for small proteins with L = 4 is close to 0.8. Our results are consistent with the above‐average quality of burial predictions used in previous simulations and indicate that the fraction of approachable proteins could increase significantly with even a mild, plausible, improvement on sequence‐dependent burial prediction or on sequence‐independent constraints that augment the detectable redundancy during simulations. Proteins 2016; 84:515–531. © 2016 Wiley Periodicals, Inc.