Maximizing Kinetic Information Gain of Markov State Models for Optimal Design of Spectroscopy Experiments.

Spectroscopic techniques such as Trp-Tyr quenching, luminescence resonance energy transfer, and triplet-triplet energy transfer are widely used for understanding the dynamic behavior of proteins. These experiments measure the relaxation of a particular labeled set of residue pairs, and the choice of residue pairs requires careful thought. As a result, experimentalists must pick residue pairs from a large pool of possibilities. In the current work, we show that molecular simulation datasets of protein dynamics can be used to systematically select an optimal set of residue positions to place probes for conducting spectroscopic experiments. The method described in this work, called Optimal Probes, can be used to rank trial sets of residue pairs in terms of their ability to capture the conformational dynamics of the protein. Optimal probes ensures two conditions: residue pairs capture the slow dynamics of the protein and their dynamics is not correlated for maximum information gain to score each trial set. Eventually, the highest scored set can be used for biophysical experiments to study the kinetics of the protein. The scoring methodology is based on kinetic network models of protein dynamics and a variational principle for molecular kinetics to optimize the hyperparameters used for the model. We also discuss that the scoring strategy used by Optimal Probes is the best possible way to ensure the ideal choice of residue pairs for experiments. We predict the best experimental probe positions for proteins λ-repressor, ß2-adrenergic receptor, and villin headpiece domain. These proteins have been well-studied and allow for a rigorous comparison of Optimal Probes predictions with already available experiments. Additionally, we also illustrate that our method can be used to predict the best choice for experiments by including any previous experiment choices available from other studies on the same protein. We consistently find that the best choice cannot be based on intuition or structural information such as distance difference between few known stable structures of the protein. Therefore, we show that incorporating protein dynamics could be used to maximize the information gain from experiments.

Phosphorylation-mediated conformational changes in the mouse neurofilament architecture: insight from a neurofilament brush model.

Neurofilaments (NFs) are important cytoskeletal filaments that consist of long flexible C-terminal tails that are abundant with charges. The tails attain additional negative charges through serine phosphorylation of Lys-Ser-Pro (KSP) repeat motifs that are particularly found in neurofilament heavy (NF-H) and neurofilament medium (NF-M) proteins. These side-arm protrusions mediate the interaction between neighboring filaments and maintain axonal diameter. However, the precise role of NF proteins and their phosphorylation in regulating interfilament distances and axonal diameter still remains unclear. In this regard, a recent gene replacement study revealed that the phosphorylation of mouse NF-M KSP repeats does not affect axonal cytoarchitecture, challenging the conventional viewpoint on the role of NF phosphorylation. To better understand the effect of phosphorylation, particularly NF-M phosphorylation, we applied a computational method to reveal phosphorylation-mediated conformational changes in mouse NF architecture. We employed a three-dimensional sequence-based coarse-grained NF brush model to perform Monte Carlo simulations of mouse NF by using the sequence and stoichiometry of mouse NF proteins. Our result shows that the phosphorylation of mouse NF-M does not change the radial extension of NF-M side arms under a salt-free condition and in ionic solution, highlighting a structural factor that supports the notion that NF-M KSP phosphorylation has no effect on the axonal diameter of mouse. On the other hand, significant phosphorylation-mediated conformational changes were found in NF-H side arms under the salt-free condition, while the changes in ionic solution are not significant. However, NF-H side arms are found at the periphery of mouse NF architecture, implying a role in linking neighboring filaments.

A critical assessment of putative gatekeeper interactions in the villin headpiece helical subdomain.

The helical subdomain of the villin headpiece (HP36) is one of the smallest naturally occurring proteins that folds cooperatively. Its small size, rapid folding, and simple three-helix topology have made it an extraordinary popular model system for computational, theoretical, and experimental studies of protein folding. Aromatic-proline interactions involving Trp64 and Pro62 have been proposed to play a critical role in specifying the subdomain fold by acting as gatekeeper residues. Note that the numbering corresponds to full-length headpiece. Mutation of Pro62 has been shown to lead to a protein that does not fold, but this may arise for two different reasons: The residue may make interactions that are critical for the specificity of the fold or the mutation may simply destabilize the domain. In the first case, the protein cannot fold, while in the second, the small fraction of molecules that do fold adopt the correct structure. The modest stability of the wild type prevents a critical analysis of these interactions because even moderately destabilizing mutations lead to a very small folded state population. Using a hyperstable variant of HP36, denoted DM HP36, as our new wild type, we characterized a set of mutants designed to assess the role of the putative gatekeeper interactions. Four single mutants, DM Pro62Ala, DM Trp64Leu, DM Trp64Lys, and DM Trp64Ala, and a double mutant, DM Pro62Ala Trp64Leu, were prepared. All mutants are less stable than DM HP36, but all are well folded as judged by CD and (1)H NMR. All of the mutants display sigmoidal thermal unfolding and urea-induced unfolding curves. Double-mutant cycle analysis shows that the interactions between Pro62 and Trp64 are weak but favorable. Interactions involving Pro62 and proline-aromatic interactions are, thus, not required for specifying the subdomain fold. The implications for the design and thermodynamics of miniature proteins are discussed.

A critical assessment of the RNAse protection assay as a means of determining exon sizes.

The RNAse protection assay is a highly sensitive assay which is commonly used to detect specific hybridization between complementary RNAs and to determine exon sizes in gene characterization studies. Unfortunately, each of the numerous steps involved in the assay could give artifacts depending on the probe used. In this study, common causes of artifacts have been identified using riboprobes which identify exons of known sizes. The RNAse concentration and duration of digestion used were found to be critical factors affecting exon size estimations. Five different riboprobes were tested to obtain a consensus optimum RNAse condition--10 micrograms/ml RNAse A, 0.5 microgram/ml RNAse T1--enabling the correct determination of exon sizes. This condition was further analyzed for its specificity when RNAse protection assays were performed between highly homologous RNA fragments from two different species. Results show that this concentration of RNAse would efficiently cleave a minimum of two nucleotide mismatches. Single nucleotide mismatches were frequently not cleaved by the same RNAse concentration making it possible to detect the correct exon size regardless of such sequence polymorphisms in gene sequences.