Consistent Principal Component Modes from Molecular Dynamics Simulations of Proteins

Cossio-Pérez, Rodrigo; Palma, Juliana; Pierdominici‐Sottile, Gustavo

doi:10.1021/acs.jcim.6b00646

Cited by 27 publications

(33 citation statements)

References 56 publications

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“…Hence, dynamics-based network analysis is presently one of the most comprehensive tools used to explore allosteric modulation of kinases. MD simulations provide a robust dataset for all-atomic fluctuations that can be analyzed for allosteric dynamics (33)(34)(35). Two key issues were kept in mind while searching for functionally relevant networks of correlated motions in our unbiased simulations: (i) that network analysis is dependent on the length of the simulation trajectory (36), wherein the description of conformational ensembles must adequately sample the free-energy landscape of the desired allosteric process; (ii) that it is more relevant to understand these inner amino acid motions in the context of experimentally verifiable observables that can corroborate the role of said dynamics in the kinase structure-function relationship.…”

Section: Resultsmentioning

confidence: 99%

Dynamic allostery-based molecular workings of kinase:peptide complexes

Ahuja

Aoto

Kornev

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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A dense interplay between structure and dynamics underlies the working of proteins, especially enzymes. Protein kinases are molecular switches that are optimized for their regulation rather than catalytic turnover rates. Using long-simulations dynamic allostery analysis, this study describes an exploration of the dynamic kinase:peptide complex. We have used protein kinase A (PKA) as a model system as a generic prototype of the protein kinase superfamily of signaling enzymes. Our results explain the role of dynamic coupling of active-site residues that must work in coherence to provide for a successful activation or inhibition response from the kinase. Amino acid networks-based community analysis allows us to ponder the conformational entropy of the kinase:nucleotide:peptide ternary complex. We use a combination of 7 peptides that include 3 types of PKA-binding partners: Substrates, products, and inhibitors. The substrate peptides provide for dynamic insights into the enzyme:substrate complex, while the product phospho-peptide allows for accessing modes of enzyme:product release. Mapping of allosteric communities onto the PKA structure allows us to locate the more unvarying and flexible dynamic regions of the kinase. These distributions, when correlated with the structural elements of the kinase core, allow for a detailed exploration of key dynamics-based signatures that could affect peptide recognition and binding at the kinase active site. These studies provide a unique dynamic allostery-based perspective to kinase:peptide complexes that have previously been explored only in a structural or thermodynamic context.

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Section: Resultsmentioning

confidence: 99%

Dynamic allostery-based molecular workings of kinase:peptide complexes

Ahuja

Aoto

Kornev

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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“…Variance-covariance matrices were calculated for the Cα atoms of the TM domain, including D358 to C646, after a RMSD fitting of the receptor conformation at time t on top of the conformation at time 0, for time frames taken every 4 ps for trajectories R0-2 [55]. Principal component analysis (PCA) was performed in order to summarize the main fluctuations using the first principal component axis [56].…”

Section: Methodsmentioning

confidence: 99%

Molecular dynamics simulation of the follicle-stimulating hormone receptor. Understanding the conformational dynamics of receptor variants at positions N680 and D408 from in silico analysis

et al. 2018

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Follicle-stimulating hormone receptor (FSHR) is a G-protein coupled receptor (GPCR) and a prototype of the glycoprotein hormone receptors subfamily of GPCRs. Structural data of the FSHR ectodomain in complex with follicle-stimulating hormone suggests a “pull and lift” activation mechanism that triggers a conformational change on the seven α-helix transmembrane domain (TMD). To analyze the conformational changes of the FSHR TMD resulting from sequence variants associated with reproductive impairment in humans, we set up a computational approach combining helix modeling and molecular simulation methods to generate conformational ensembles of the receptor at room (300 K) and physiological (310 K) temperatures. We examined the receptor dynamics in an explicit membrane environment of polyunsaturated phospholipids and solvent water molecules. The analysis of the conformational dynamics of the functional (N680 and S680) and dysfunctional (mutations at D408) variants of the FSHR allowed us to validate the FSHR-TMD model. Functional variants display a concerted motion of flexible intracellular regions at TMD helices 5 and 6. Disruption of side chain interactions and conformational dynamics were detected upon mutation at D408 when replaced with alanine, arginine, or tyrosine. Dynamical network analysis confirmed that TMD helices 2 and 5 may share communication pathways in the functional FSHR variants, whereas no connectivity was detected in the dysfunctional mutants, indicating that the global dynamics of the FSHR was sensitive to mutations at amino acid residue 408, a key position apparently linked to misfolding and variable cell surface plasma membrane expression of FSHRs with distinct mutations at this position.

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“…Ref. [36] introduced and examined a parameter that evaluates the overlap between such subspaces, called the root mean squared inner product (RMSIP), and suggested that PCA for the concatenated equivalent trajectories achieves better reproducibility.…”

Section: Error In Pcamentioning

confidence: 99%

Principal Component Analysis and Related Methods for Investigating the Dynamics of Biological Macromolecules

Kitao

2022

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Principal component analysis (PCA) is used to reduce the dimensionalities of high-dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high-dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods and their applications for investigating protein dynamics.

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Consistent Principal Component Modes from Molecular Dynamics Simulations of Proteins

Cited by 27 publications

References 56 publications

Dynamic allostery-based molecular workings of kinase:peptide complexes

Dynamic allostery-based molecular workings of kinase:peptide complexes

Molecular dynamics simulation of the follicle-stimulating hormone receptor. Understanding the conformational dynamics of receptor variants at positions N680 and D408 from in silico analysis

Principal Component Analysis and Related Methods for Investigating the Dynamics of Biological Macromolecules

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