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Pseudodihedrals: simplified protein backbone representation with knowledge-based energy.

ABSTRACT: Pairwise contact energies do not explicitly take protein secondary structure into account, and so provide an incomplete description of conformational energy. In order to construct a Hamiltonian that specifically relates to protein backbone conformations, a simplified backbone angle is used. The pseudodihedral angle (the torsion angle between planes defined by 4 consecutive alpha-carbon atoms) provides a simplified backbone representation and continues to manifest information about secondary-structure elements: the pseudo-Ramachandran plot contains helical and sheetlike regions. The distribution of pseudodihedral angles is highly sensitive to the identity of the central pair of amino acids. Therefore, a sequence-dependent, knowledge-based potential energy was found according to a quasichemical approximation. These functions form complementary additions to the contact potentials currently in use. This pseudodihedral potential greatly enhances the ability to design sequences that are specific to a given conformation and also improves the ability to discriminate a native conformation from many other conformations.

SUBMITTER: DeWitte RS

PROVIDER: S-EPMC2142948 | biostudies-other | 1994 Sep

REPOSITORIES: biostudies-other

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Pseudodihedrals: simplified protein backbone representation with knowledge-based energy.

DeWitte R S RS Shakhnovich E I EI

Protein science : a publication of the Protein Society 19940901 9

Pairwise contact energies do not explicitly take protein secondary structure into account, and so provide an incomplete description of conformational energy. In order to construct a Hamiltonian that specifically relates to protein backbone conformations, a simplified backbone angle is used. The pseudodihedral angle (the torsion angle between planes defined by 4 consecutive alpha-carbon atoms) provides a simplified backbone representation and continues to manifest information about secondary-stru ...[more]

PMID: 7833816

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Project description:Knowledge acquisition is a process in which one actively selects a piece of information from the environment and assimilates it with prior knowledge. However, little is known about the neural mechanism underlying selectivity in knowledge acquisition. Here we executed a 2-day human experiment to investigate the involvement of characteristic spontaneous activity resembling a so-called "preplay" in selectivity in sentence comprehension, an instance of knowledge acquisition. On day 1, we presented 10 sentences (prior sentences) that were difficult to understand on their own. On the following day, we first measured the resting-state functional magnetic resonance imaging (fMRI). Then, we administered a sentence comprehension task using 20 new sentences (posterior sentences). The posterior sentences were also difficult to understand on their own, but some could be associated with prior sentences to facilitate their understanding. Next, we measured the posterior sentence-induced fMRI to identify the neural representation. From the resting-state fMRI, we extracted the appearances of activity patterns similar to the neural representations for posterior sentences. Importantly, the resting-state fMRI was measured before giving the posterior sentences, and thus such appearances could be considered as preplay-like or prototypical neural representations. We compared the intensities of such appearances with the understanding of posterior sentences. This gave a positive correlation between these two variables, but only if posterior sentences were associated with prior sentences. Additional analysis showed the contribution of the entorhinal cortex, rather than the hippocampus, to the correlation. The present study suggests that prior knowledge-based arrangement of neural activity before an experience contributes to the active selection of information to be learned. Such arrangement prior to an experience resembles preplay activity observed in the rodent brain. In terms of knowledge acquisition, the present study leads to a new view of the brain (or more precisely of the brain's knowledge) as an autopoietic system in which the brain (or knowledge) selects what it should learn by itself, arranges preplay-like activity as a position for the new information in advance, and actively reorganizes itself.

Dataset Information

Pseudodihedrals: simplified protein backbone representation with knowledge-based energy.

Publications

Pseudodihedrals: simplified protein backbone representation with knowledge-based energy.

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