Abstract
Coarse-grained protein models approximate the first-principle physical potentials. Among those modeling approaches, the relative entropy framework yields promising and physically sound results, in which a mapping from the target protein structure and dynamics to a model is defined and subsequently adjusted by an entropy minimization of the model parameters. Minimization of the relative entropy is equivalent to maximization of the likelihood of reproduction of (configurational ensemble) observations by the model. In this study, we extend the relative entropy minimization procedure beyond parameter fitting by a second optimization level, which identifies the optimal mapping to a (dimension-reduced) topology. We consider anisotropic network models of a diverse set of ion channels and assess our findings by comparison to experimental results.
Highlights
Coarse-grained models are established tools in a variety of applications in structural biophysics (Tozzini 2005; Bahar and Rader 2005; Shell 2008; Schlick 2010; Saunders and Voth 2013; Noid 2013; Kmiecik et al 2016; Shell 2016)
The anisotropic network of KcsA can be reduced to four amino acid positions As a test case, we started the analysis with the pore module of KcsA, the best studied K+ channel pore
The results of the analyses show that the critical amino acids, which correspond to 71 and 76 in KcsA are detected with a high scoring value in all the pore modules of K+ channels with a 6 TMD type architecture (Fig. 1bii)
Summary
Coarse-grained models are established tools in a variety of applications in structural biophysics (Tozzini 2005; Bahar and Rader 2005; Shell 2008; Schlick 2010; Saunders and Voth 2013; Noid 2013; Kmiecik et al 2016; Shell 2016). Their simplified structure allows investigation of important functional, dynamical, and structural properties of biomolecules including proteins, which are too large for finer grained approaches like molecular dynamics (MD) simulations. Normal-mode analysis of a Gaussian network model of the channel pores revealed a common pattern of intrinsic low-frequency motions
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