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A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain

Overview of attention for article published in Frontiers in Molecular Biosciences, September 2017
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Article details
Title
A Simple PB/LIE Free Energy Function Accurately Predicts the Peptide Binding Specificity of the Tiam1 PDZ Domain
Published in
Frontiers in Molecular Biosciences, September 2017
DOI 10.3389/fmolb.2017.00065
Pubmed ID
Authors
Abstract

PDZ domains generally bind short amino acid sequences at the C-terminus of target proteins, and short peptides can be used as inhibitors or model ligands. Here, we used experimental binding assays and molecular dynamics simulations to characterize 51 complexes involving the Tiam1 PDZ domain and to test the performance of a semi-empirical free energy function. The free energy function combined a Poisson-Boltzmann (PB) continuum electrostatic term, a van der Waals interaction energy, and a surface area term. Each term was empirically weighted, giving a Linear Interaction Energy or "PB/LIE" free energy. The model yielded a mean unsigned deviation of 0.43 kcal/mol and a Pearson correlation of 0.64 between experimental and computed free energies, which was superior to a Null model that assumes all complexes have the same affinity. Analyses of the models support several experimental observations that indicate the orientation of the α2 helix is a critical determinant for peptide specificity. The models were also used to predict binding free energies for nine new variants, corresponding to point mutants of the Syndecan1 and Caspr4 peptides. The predictions did not reveal improved binding; however, they suggest that an unnatural amino acid could be used to increase protease resistance and peptide lifetimes in vivo. The overall performance of the model should allow its use in the design of new PDZ ligands in the future.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 3 21%
Student > Master 3 21%
Student > Ph. D. Student 2 14%
Student > Doctoral Student 1 7%
Student > Postgraduate 1 7%
Other 0 0%
Unknown 4 29%
Readers by discipline
Readers by discipline Count As %
Chemistry 3 21%
Biochemistry, Genetics and Molecular Biology 2 14%
Agricultural and Biological Sciences 2 14%
Computer Science 2 14%
Arts and Humanities 1 7%
Other 1 7%
Unknown 3 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 September 2017.
All research outputs
#18,572,844
of 23,003,906 outputs
Outputs from Frontiers in Molecular Biosciences
#1,982
of 3,859 outputs
Outputs of similar age
#245,537
of 320,414 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#11
of 15 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,859 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 33rd percentile – i.e., 33% of its peers scored the same or lower than it.
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We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.