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Characterizing aqueous solution conformations of a peptide backbone using Raman optical activity computations.

ABSTRACT: Mounting spectroscopic evidence indicates that alanine predominantly adopts extended polyproline II (PPII) conformations in short polypeptides. Here we analyze Raman optical activity (ROA) spectra of N-acetylalanine-N'-methylamide (Ala dipeptide) in H2O and D2O using density functional theory on Monte Carlo (MC) sampled geometries to examine the propensity of Ala dipeptide to adopt compact right-handed (alpha(R)) and left-handed (alpha(L)) helical conformations. The computed ROA spectra based on MC-sampled alpha(R) and PPII peptide conformations contain all the key spectral features found in the measured spectra. However, there is no significant similarity between the measured and computed ROA spectra based on the alpha(L)- and beta-conformations sampled by the MC methods. This analysis suggests that Ala dipeptide populates the alpha(R) and PPII conformations but no substantial population of alpha(L)- or beta-structures, despite sampling alpha(L)- and beta-structures in our MC simulations. Thus, ROA spectra combined with the theoretical analysis allow us to determine the dominant populated structures. Including explicit solute-solvent interactions in the theoretical analysis is essential for the success of this approach.

SUBMITTER: Mukhopadhyay P

PROVIDER: S-EPMC2599840 | biostudies-other | 2008 Dec

REPOSITORIES: biostudies-other

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Characterizing aqueous solution conformations of a peptide backbone using Raman optical activity computations.

Mukhopadhyay Parag P Zuber Gérard G Beratan David N DN

Biophysical journal 20080919 12

Mounting spectroscopic evidence indicates that alanine predominantly adopts extended polyproline II (PPII) conformations in short polypeptides. Here we analyze Raman optical activity (ROA) spectra of N-acetylalanine-N'-methylamide (Ala dipeptide) in H2O and D2O using density functional theory on Monte Carlo (MC) sampled geometries to examine the propensity of Ala dipeptide to adopt compact right-handed (alpha(R)) and left-handed (alpha(L)) helical conformations. The computed ROA spectra based on ...[more]

PMID: 18805935

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Project description:In many brain areas, sensory responses are heavily modulated by factors including attentional state, context, reward history, motor preparation, learned associations, and other cognitive variables. Modelling the effect of these modulatory factors on sensory responses has proven challenging, mostly due to the time-varying and nonlinear nature of the underlying computations. Here we present a computational model capable of capturing and dissociating multiple time-varying modulatory effects on neuronal responses on the order of milliseconds. The model's performance is tested on extrastriate perisaccadic visual responses in nonhuman primates. Visual neurons respond to stimuli presented around the time of saccades differently than during fixation. These perisaccadic changes include sensitivity to the stimuli presented at locations outside the neuron's receptive field, which suggests a contribution of multiple sources to perisaccadic response generation. Current computational approaches cannot quantitatively characterize the contribution of each modulatory source in response generation, mainly due to the very short timescale on which the saccade takes place. In this study, we use a high spatiotemporal resolution experimental paradigm along with a novel extension of the generalized linear model framework (GLM), termed the sparse-variable GLM, to allow for time-varying model parameters representing the temporal evolution of the system with a resolution on the order of milliseconds. We used this model framework to precisely map the temporal evolution of the spatiotemporal receptive field of visual neurons in the middle temporal area during the execution of a saccade. Moreover, an extended model based on a factorization of the sparse-variable GLM allowed us to disassociate and quantify the contribution of individual sources to the perisaccadic response. Our results show that our novel framework can precisely capture the changes in sensitivity of neurons around the time of saccades, and provide a general framework to quantitatively track the role of multiple modulatory sources over time.

Dataset Information

Characterizing aqueous solution conformations of a peptide backbone using Raman optical activity computations.

Publications

Characterizing aqueous solution conformations of a peptide backbone using Raman optical activity computations.

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