This work quantitatively characterizes intrinsic disorder in proteins in terms of
sequence composition and backbone conformational entropy. Analysis of the normalized
relative composition of the amino acid triads highlights a distinct boundary between
globular and disordered proteins. The conformational entropy is calculated from the
dihedral angles of the middle amino acid in the amino acid triad for the
conformational ensemble of the globular, partially and completely disordered
proteins relative to the non-redundant database. Both Monte Carlo (MC) and Molecular
Dynamics (MD) simulations are used to characterize the conformational ensemble of
the representative proteins of each group. The results show that the globular
proteins span approximately half of the allowed conformational states in the
Ramachandran space, while the amino acid triads in disordered proteins sample the
entire range of the allowed dihedral angle space following Flory’s
isolated-pair hypothesis. Therefore, only the sequence information in terms of the
relative amino acid triad composition may be sufficient to predict protein disorder
and the backbone conformational entropy, even in the absence of well-defined
structure. The predicted entropies are found to agree with those calculated using
mutual information expansion and the histogram method.
A Monte Carlo simulation based sequence design method is proposed to study the role of the local and the nonlocal interactions with varying secondary structure content in protein folding, misfolding and unfolding. A statistical potential is developed from the compilation of a data set of proteins, which accounts for the respective contribution of local and the nonlocal interactions. Sequences are designed through a combination of positive and negative design by a Monte Carlo simulation in the sequence space. The weights of the local and the nonlocal interactions are tuned appropriately to study the role of the local and the nonlocal interactions in the folding, unfolding and misfolding of the designed sequences. Results suggest that the nonlocal interactions are the primary determinant of protein folding while the local interactions may be required but not always necessary. The nonlocal interactions mainly guide the polypeptide chain to form compact structures but do not differentiate between the native-like conformations, while the local interactions stabilize the target conformation against the native-like competing conformations. The study concludes that the local interactions govern the fold-misfold transition, while the nonlocal interactions regulate the fold-unfold transition of proteins. However, for proteins with predominantly β-sheet content, the nonlocal interactions control both fold-misfold and fold-unfold transitions.
A self-consistent mean-field based model is presented to explore the role of site-directed point mutations in designing folded and/or misfolded sequences with a reduced hydrophobic-polar (HP) patterning of amino acids. This site-directed point mutation procedure is developed and applied to both real and lattice proteins to generate a diverse set of sequences. The respective roles of core and surface residues are analyzed with respect to the optimum hydrophobicity required for the structural stability of the protein. The core sites are found to have a critical number of hydrophobic residues, below which a protein may misfold, while the surface sites show a clear preference for the polar residues with the ability to tolerate some hydrophobic residues. Although core sites play an important role in the structural stability of proteins, some specific surface sites are also found to be equally important. A clash and match calculation procedure is proposed, which may be used to predict the number of residue pairs in a sequence with unfavorable and favorable interactions, respectively, due to site-directed point mutations. The number of clashing and matching residue pairs may indicate whether the mutated sequence would be folded or misfolded. The results are independent of the secondary structure topology of the protein. This model may provide new insights into the effect of point mutations on protein stability and may introduce a new method to predict the outcome of a mutation in terms of its probability to fold or misfold.
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