Fluctuation matching approach for elastic network model and structure-based model of biomacromolecules

Bope, Christian Domilongo; Tong, Dudu; Li, Xiuting; Lu, Lanyuan

doi:10.1016/j.pbiomolbio.2016.12.006

Cited by 8 publications

(7 citation statements)

References 67 publications

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“…The ability of ENMs to efficiently assess intrinsically favored global movements, as well as the relevance of these predictions to the dominant changes in structure observed for a given protein in the presence of different ligands suggest that intrinsic dynamics play a role in the mediation of ligand-protein complex interactions, and could be comparable to MD measurements [63] , [64] . However, there are few reports on the use of ENM for the study of conformational perturbations in SARS-CoV-2, in this direction, our results show that the complexed structures have a stable interaction movement with each other after the molecular union, in addition, the complexes presented a greater deformation than those reported [65] .…”

Section: Resultsmentioning

confidence: 94%

Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models

González

Hurtado-León

Lossada

et al. 2021

Journal of Molecular Liquids

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The COVID-19 pandemic has accelerated the study of the potential of multi-target drugs (MTDs). The mixture of homologues called ivermectin (avermectin-B1a + avermectin-B1b) has been shown to be a MTD with potential antiviral activity against SARS-CoV-2 in vitro . However, there are few reports on the effect of each homologue on the flexibility and stiffness of proteins associated with COVID-19, described as ivermectin targets. We observed that each homologue was stably bound to identified proteinsthe proteins studied and were able to induce detectable changes with Elastic Network Models (ENMs). The perturbations induced by each homologue were characteristic of each compound and, in turn, were represented by a disruption of native intramolecular networks (interactions between residues). The homologues were able to slightly modify the conformation and stability of the connection points between the Cα atoms of the residues that make up the structural network of proteins (nodes), compared to free proteins. Each homologue was able to modified differently the distribution of quasi-rigid regions of the proteins, which could theoretically alter their biological activities. These results could provide a biophysical-computational view of the potential MTD mechanism that has been reported for ivermectin.

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Section: Resultsmentioning

confidence: 94%

Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models

González

Hurtado-León

Lossada

et al. 2021

Journal of Molecular Liquids

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“…The first type of the simulation treats a protein system by a hybrid model of AAM and CGM 49–53 ; one example of an early study was performed by Neri et al 49 The second type of simulation constructs an improved CGM force field by fitting the AAM simulation results. Furthermore, examples of this type are part of the force‐matching method 54–62 and fluctuation‐matching method 63–67 . The third type of simulation first treat a protein by CGM, then the AAM simulation is performed using conformational information of CGM 68–73 …”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, examples of this type are part of the force-matching method [54][55][56][57][58][59][60][61][62] and fluctuation-matching method. [63][64][65][66][67] The third type of simulation first treat a protein by CGM, then the AAM simulation is performed using conformational information of CGM. [68][69][70][71][72][73] In the present study, we propose a novel multi-scale divide-andconquer (MSDC) method, which performs multi-scale simulation with umbrella-sampling on principal component (PC) spaces.…”

mentioning

confidence: 99%

Atomistic detailed free‐energy landscape of intrinsically disordered protein studied by multi‐scale divide‐and‐conquer molecular dynamics simulation

Shimoyama

Yonezawa

2020

J Comput Chem

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Calcineurin (CaN) is a eukaryotic serine/threonine protein phosphatase activated by both Ca 2+ and calmodulin (CaM), including intrinsically disordered region (IDR). The region undergoes folding into an α-helix form in the presence Ca 2+-loaded CaM. To sample the ordered structure of the IDR by conventional all atom model (AAM) molecular dynamics (MD) simulation, the IDR and Ca 2+-loaded CaM must be simultaneously treated. However, it is time-consuming task because the coupled folding and binding should include repeated binding and dissociation. Then, in this study, we propose novel multi-scale divide-and-conquer MD (MSDC-MD), which combines AAM-MD and coarse-grained model MD (CGM-MD). To speed up the conformation sampling, MSDC-MD simulation first treats the IDR by CGM to sample conformations from wide conformation space; then, multiple AAM-MD in a limited area is initiated using the resultant CGM conformation, which is reconstructed by homology modeling method. To investigate performance, we sampled the ordered conformation of the IDR using MSDC-MD; the root-mean-square distance (RMSD) with respect to the experimental structure was 2.23 Å.

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“…After the original formulation of the method developed by [7], [50] proposed an improved version of the original fluctuation matching algorithm. Other MD simulations studies using the fluctuationmatching algorithm to parameterized CG-ENM force fields can be found in literature [9,54,55]. The target fluctuations can be obtained from NMA instead of the conventional MD simulations [51].…”

Section: Binding Different Computational Methods Have Been Proposed mentioning

confidence: 99%

“…Raphson algorithm to parameterized a heterogeneous elastic network model known as the "Heterogeneous Elastic Network Model Parameterized by Using the Relative Entropy method with Non-negative Constraints" [55] is explained in detail.…”

Section: Relative-entropy-based Fluctuation Matching With Improved Comentioning

confidence: 99%

Molecular modeling and simulation for proteins and polymer membranes

Christian¹

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for their collaborative support and open-minded scientific discussions. My appreciation to Professor Benoit Morel for the proofreading of my thesis at the Carnegie Mellon University, United State of America. A special thanks goes to my family, particularly my father Crispin Bope Domilongo may his soul rest in peace and receive the fruits of his huge sacrifices; to my mother Josephine Bokashanga. To my lovely wife Florence Bope and my son Precious Bope Domilongo for their love and prayers.

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Fluctuation matching approach for elastic network model and structure-based model of biomacromolecules

Cited by 8 publications

References 67 publications

Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models

Structural deformability induced in proteins of potential interest associated with COVID-19 by binding of homologues present in ivermectin: Comparative study based in elastic networks models

Atomistic detailed free‐energy landscape of intrinsically disordered protein studied by multi‐scale divide‐and‐conquer molecular dynamics simulation

Molecular modeling and simulation for proteins and polymer membranes

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