Flexibility–rigidity index for protein–nucleic acid flexibility and fluctuation analysis

Opron, Kristopher; Xia, Kelin; Burton, Zachary F.; Wei, Guo-Wei

doi:10.1002/jcc.24320

Cited by 21 publications

(17 citation statements)

References 75 publications

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“…In DMD simulations, the coarse-grained conformational ensembles of the Hsp90 structures were subjected to all-atom reconstruction 64 , 65 and subsequent refinement 66 . We then applied flexibility-rigidity index (FRI) method 67 , 68 which is a matrix decomposition-free method that utilizes topological connectivity in protein structures to estimate rigidity and flexibility of Hsp90 residues. Using all-atom reconstructed conformations along DMD trajectories, we computed the ensemble-based average FRI profiles for the Hsp90 structures (Fig.…”

Section: Resultsmentioning

confidence: 99%

Dissecting Structure-Encoded Determinants of Allosteric Cross-Talk between Post-Translational Modification Sites in the Hsp90 Chaperones

Stetz

Tse

Verkhivker

2018

Sci Rep

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Post-translational modifications (PTMs) represent an important regulatory instrument that modulates structure, dynamics and function of proteins. The large number of PTM sites in the Hsp90 proteins that are scattered throughout different domains indicated that synchronization of multiple PTMs through a combinatorial code can be invoked as an important mechanism to orchestrate diverse chaperone functions and recognize multiple client proteins. In this study, we have combined structural and coevolutionary analysis with molecular simulations and perturbation response scanning analysis of the Hsp90 structures to characterize functional role of PTM sites in allosteric regulation. The results reveal a small group of conserved PTMs that act as global mediators of collective dynamics and allosteric communications in the Hsp90 structures, while the majority of flexible PTM sites serve as sensors and carriers of the allosteric structural changes. This study provides a comprehensive structural, dynamic and network analysis of PTM sites across Hsp90 proteins, identifying specific role of regulatory PTM hotspots in the allosteric mechanism of the Hsp90 cycle. We argue that plasticity of a combinatorial PTM code in the Hsp90 may be enacted through allosteric coupling between effector and sensor PTM residues, which would allow for timely response to structural requirements of multiple modified enzymes.

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Section: Resultsmentioning

confidence: 99%

Dissecting Structure-Encoded Determinants of Allosteric Cross-Talk between Post-Translational Modification Sites in the Hsp90 Chaperones

Stetz

Tse

Verkhivker

2018

Sci Rep

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“…Our quantitative understanding of protein flexibility and function is greatly impeded by their complexity and a large number of degrees of freedom. Many time-independent methods, such as NMA [4,20,5,3], ENM [6], GNM [8,9,21], and FRI [11][12][13]22], exist that dramatically simplify the protein structural complexity and are able to analyze protein Bfactors, which reflect protein flexibility among other things. Based on the hypothesis that intrinsic physics lies in a low-dimensional space embedded in a high-dimensional data space, we introduced multiscale weighted colored graphs (MWCGs) to effectively reduce protein structural complexity and efficiently describe protein flexibility.…”

Section: Resultsmentioning

confidence: 99%

Blind prediction of protein B-factor and flexibility

Bramer

Wei

2018

The Journal of Chemical Physics

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Debye-Waller factor, a measure of X-ray attenuation, can be experimentally observed in protein X-ray crystallography. Previous theoretical models have made strong inroads in the analysis of Bfactors by linearly fitting protein B-factors from experimental data. However, the blind prediction of B-factors for unknown proteins is an unsolved problem. This work integrates machine learning and advanced graph theory, namely, multiscale weighted colored graphs (MWCGs), to blindly predict B-factors of unknown proteins. MWCGs are local features that measure the intrinsic flexibility due to a protein structure. Global features that connect the B-factors of different proteins, e.g., the resolution of X-ray crystallography, are introduced to enable the cross-protein B-factor predictions. Several machine learning approaches, including ensemble methods and deep learning, are considered in the present work. The proposed method is validated with hundreds of thousands of experimental B-factors. Extensive numerical results indicate that the blind B-factor predictions obtained from the present method are more accurate than the least squares fittings using traditional methods.

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“…21 It has been shown to be about 20% more accurate and orders of magnitude more efficient than other classic approaches, such as Gaussian network model (GNM), 22 and anisotropic network model (ANM) 23 in the B-factor prediction of hundreds of proteins 21,24,25 and protein-nucleic acid complexes. 26 For example, it predicts the B-factors of the entire HIV capsid with 313,236 residues in less 30 second, which would require GNM more than 120 years to compute were the memory not a problem. 24 Our postulation is confirmed by the evaluation of rigidity index (RI) over 195 protein complexes.…”

mentioning

confidence: 99%

Rigidity Strengthening: A Mechanism for Protein–Ligand Binding

Nguyen

Xiao

Wang

et al. 2017

J. Chem. Inf. Model.

100

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Protein-ligand binding is essential to almost all life processes. The understanding of protein-ligand interactions is fundamentally important to rational drug and protein design. Based on large scale data sets, we show that protein rigidity strengthening or flexibility reduction is a mechanism in protein-ligand binding. Our approach based solely on rigidity is able to unveil a surprisingly apparently long-range contribution of apparently four residue layers to protein-ligand binding, which has ramifications for drug and protein design. Additionally, the present work reveals that among various pairwise interactions, the short-range ones within the distance of the van der Waals diameter are most important. It is found that the present approach outperforms all other state-of-the-art scoring functions for protein-ligand binding affinity predictions of two benchmark test sets.

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Flexibility–rigidity index for protein–nucleic acid flexibility and fluctuation analysis

Cited by 21 publications

References 75 publications

Dissecting Structure-Encoded Determinants of Allosteric Cross-Talk between Post-Translational Modification Sites in the Hsp90 Chaperones

Dissecting Structure-Encoded Determinants of Allosteric Cross-Talk between Post-Translational Modification Sites in the Hsp90 Chaperones

Blind prediction of protein B-factor and flexibility

Rigidity Strengthening: A Mechanism for Protein–Ligand Binding

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