Abstract
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.
Highlights
Conformational entropy of proteins is a proxy measure of its internal dynamics, which may be characterized by enumerating the different microscopic structural states involved in atomic motion[1,2,3]
Protein disorder may be predicted from the relative sequence composition only, while the backbone conformational entropy provides an appropriate measure of this structural disorder
Conformational entropy of intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) calculated using the conformational ensembles of proteins generated by Molecular Dynamics (MD) simulations is compared with that in the non-redundant database and globular protein (1A4V) in Supplementary Fig. S3(a) online, while the same is depicted in Supplementary Fig. S3(b) online for the conformational ensembles generated by Monte Carlo (MC) simulations
Summary
Conformational entropy of proteins is a proxy measure of its internal dynamics, which may be characterized by enumerating the different microscopic structural states involved in atomic motion[1,2,3]. The correlation between the dihedral angles may be extracted from molecular dynamics simulation trajectories coupled with the experimental NMR relaxation data for proteins through generalized order parameters, S2, derived from spin relaxation[13,14] This method is not useful for the disordered proteins since they lack a well-defined structure. A recent study by Genheden, Akke and Ryde[21] infer that even long MD simulations do not completely equilibrate protein conformations, while the configurational entropy depends on both sampling statistics and simulation time These methods have limited scope for the intrinsically disordered proteins (IDPs), where the disordered regions/ domains are characterized by a conspicuous absence of interpretable electron density due to the fast motions of the atoms, rendering them invisible. The advantage of this method is that it avoids the requirement of extra long simulations which is computationally expensive and time consuming
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