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Inferring functional units in ion channel pores via relative entropy.

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.

SUBMITTER: Schmidt M

PROVIDER: S-EPMC7872957 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Inferring functional units in ion channel pores via relative entropy.

Schmidt Michael M Schroeder Indra I Bauer Daniel D Thiel Gerhard G Hamacher Kay K

European biophysics journal : EBJ 20210101 1

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) observati ...[more]

PMID: 33523249

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