Dissipative electro-elastic network model of protein electrostatics

Martin, Daniel R.; Ozkan, S. Banu; Matyushov, Dmitry V.

doi:10.1088/1478-3975/9/3/036004

Cited by 10 publications

(12 citation statements)

References 87 publications

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“…A protein folded in its native state in vivo has internal dynamics where some parts are more flexible than others due to the interresidue network of interactions. Protein dynamics is critical to biological function-allosteric signaling, protein transport (8)(9)(10)(11)(12), ligand recognition (13), electron transfer (14), enzymatic reaction efficiency (15,16), and evolution of novel functions (17). Furthermore, evolutionary sequence variability has been analyzed in the context of protein structure dynamics (18)(19)(20)(21)(22)(23) and shows a high correlation between evolutionary rates and the flexibility of individual positions (10,24).…”

Section: Introductionmentioning

confidence: 99%

The Role of Conformational Dynamics and Allostery in the Disease Development of Human Ferritin

Kumar

Glembo

Ozkan

2015

Biophysical Journal

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Determining the three-dimensional structure of myoglobin, the first solved structure of a protein, fundamentally changed the way protein function was understood. Even more revolutionary was the information that came afterward: protein dynamics play a critical role in biological functions. Therefore, understanding conformational dynamics is crucial to obtaining a more complete picture of protein evolution. We recently analyzed the evolution of different protein families including green fluorescent proteins (GFPs), β-lactamase inhibitors, and nuclear receptors, and we observed that the alteration of conformational dynamics through allosteric regulation leads to functional changes. Moreover, proteome-wide conformational dynamics analysis of more than 100 human proteins showed that mutations occurring at rigid residue positions are more susceptible to disease than flexible residue positions. These studies suggest that disease-associated mutations may impair dynamic allosteric regulations, leading to loss of function. Thus, in this study, we analyzed the conformational dynamics of the wild-type light chain subunit of human ferritin protein along with the neutral and disease forms. We first performed replica exchange molecular dynamics simulations of wild-type and mutants to obtain equilibrated dynamics and then used perturbation response scanning (PRS), where we introduced a random Brownian kick to a position and computed the fluctuation response of the chain using linear response theory. Using this approach, we computed the dynamic flexibility index (DFI) for each position in the chain for the wild-type and the mutants. DFI quantifies the resilience of a position to a perturbation and provides a flexibility/rigidity measurement for a given position in the chain. The DFI analysis reveals that neutral variants and the wild-type exhibit similar flexibility profiles in which experimentally determined functionally critical sites act as hinges in controlling the overall motion. However, disease mutations alter the conformational dynamic profile, making hinges more loose (i.e., softening the hinges), thus impairing the allosterically regulated dynamics.

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Section: Introductionmentioning

confidence: 99%

The Role of Conformational Dynamics and Allostery in the Disease Development of Human Ferritin

Kumar

Glembo

Ozkan

2015

Biophysical Journal

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“…A common feature among these methods is that they are based on the static 3D structure of the protein, which fails to capture the dynamic motion of the protein structure. From the conformational transitions of allosteric proteins to the required flexibility of a ligand‐binding site, proteins must fluctuate to achieve their function …”

Section: Introductionmentioning

confidence: 99%

“…From the conformational transitions of allosteric proteins to the required flexibility of a ligand-binding site, proteins must fluctuate to achieve their function. [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] A reason for the lack of methods incorporating protein dynamics into nsSNV diagnoses could be the absence of amino acid site-specific measures that can statistically quantify the contribution and impact of each position on the conformational dynamics of the protein in a fast and efficient way. We recently developed a dynamic flexibility index (dfi), which measures the contribution of each position to functionally important dynamics.…”

Section: Introductionmentioning

confidence: 99%

Conformational dynamics of nonsynonymous variants at protein interfaces reveals disease association

et al. 2015

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Recent studies have shown that the protein interface sites between individual monomeric units in biological assemblies are enriched in disease-associated non-synonymous single nucleotide variants (nsSNVs). In order to elucidate the mechanistic underpinning of this observation, we investigated the conformational dynamic properties of protein interface sites through a site-specific structural dynamic flexibility metric (dfi) for 333 multimeric protein assemblies. dfi measures the dynamic resilience of a single residue to perturbations that occurred in the rest of the protein structure and identifies sites contributing the most to functionally critical dynamics. Analysis of dfi profiles of over a thousand positions harboring variation revealed that amino acid residues at interfaces have lower average dfi (31%) than those present at non-interfaces (50%), which means that protein interfaces have less dynamic flexibility. Interestingly, interface sites with disease-associated nsSNVs have significantly lower average dfi (23%) as compared to those of neutral nsSNVs (42%), which directly relates structural dynamics to functional importance. We found that less conserved interface positions show much lower dfi for disease nsSNVs as compared to neutral nsSNVs. In this case, dfi is better as compared to the accessible surface area metric, which is based on the static protein structure. Overall, our proteome-wide conformational dynamics analysis indicates that certain interface sites play a critical role in functionally related dynamics (i.e., those with low dfi values), therefore mutations at those sites are more likely to be associated with disease.

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“…We call such a perturbation a move . Many different types of moves have been proposed, including dihedral perturbations [86] and Normal Modes [8]–[11], as well as moves based on Dynamic Elastic Networks [12]–[14], [87], to name a few. In our method, moves can be applied to both small protein fragments (such as loop regions) and the whole structure.…”

Section: Methodsmentioning

confidence: 99%

SIMS: A Hybrid Method for Rapid Conformational Analysis

2013

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Proteins are at the root of many biological functions, often performing complex tasks as the result of large changes in their structure. Describing the exact details of these conformational changes, however, remains a central challenge for computational biology due the enormous computational requirements of the problem. This has engendered the development of a rich variety of useful methods designed to answer specific questions at different levels of spatial, temporal, and energetic resolution. These methods fall largely into two classes: physically accurate, but computationally demanding methods and fast, approximate methods. We introduce here a new hybrid modeling tool, the Structured Intuitive Move Selector (sims), designed to bridge the divide between these two classes, while allowing the benefits of both to be seamlessly integrated into a single framework. This is achieved by applying a modern motion planning algorithm, borrowed from the field of robotics, in tandem with a well-established protein modeling library. sims can combine precise energy calculations with approximate or specialized conformational sampling routines to produce rapid, yet accurate, analysis of the large-scale conformational variability of protein systems. Several key advancements are shown, including the abstract use of generically defined moves (conformational sampling methods) and an expansive probabilistic conformational exploration. We present three example problems that sims is applied to and demonstrate a rapid solution for each. These include the automatic determination of “active” residues for the hinge-based system Cyanovirin-N, exploring conformational changes involving long-range coordinated motion between non-sequential residues in Ribose-Binding Protein, and the rapid discovery of a transient conformational state of Maltose-Binding Protein, previously only determined by Molecular Dynamics. For all cases we provide energetic validations using well-established energy fields, demonstrating this framework as a fast and accurate tool for the analysis of a wide range of protein flexibility problems.

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Dissipative electro-elastic network model of protein electrostatics

Cited by 10 publications

References 87 publications

The Role of Conformational Dynamics and Allostery in the Disease Development of Human Ferritin

The Role of Conformational Dynamics and Allostery in the Disease Development of Human Ferritin

Conformational dynamics of nonsynonymous variants at protein interfaces reveals disease association

SIMS: A Hybrid Method for Rapid Conformational Analysis

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