Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: The myoglobin case

Papaleo, Elena; Mereghetti, Paolo; Fantucci, Piercarlo; Grandori, Rita; Gioia, Luca De

doi:10.1016/j.jmgm.2009.01.006

Cited by 347 publications

(237 citation statements)

References 70 publications

Supporting

Mentioning

224

Contrasting

Order By: Relevance

“…On the basis of the above PCA data, the first 2 PCs are chosen as the reaction coordinates X 1 and X 2 . 34,40 Then, the 2-dimensional free energy landscapes are constructed from the joint probability distributions P.X 1 ; X 2 /. In the FEL, the local basins usually represent the conformational ensemble in the relatively stable states, and the barriers indicate the transient states.…”

Section: Free Energy Landscapementioning

confidence: 99%

Exploring the molecular basis of RNA recognition by the dimeric RNA-binding protein via molecular simulation methods

Chang

Zhang

et al. 2016

RNA Biology

View full text Add to dashboard Cite

RNA-binding protein with multiple splicing (RBPMS) is critical for axon guidance, smooth muscle plasticity, and regulation of cancer cell proliferation and migration. Recently, different states of the RNA-recognition motif (RRM) of RBPMS, one in its free form and another in complex with CAC-containing RNA, were determined by Xray crystallography. In this article, the free RRM domain, its wild type complex and 2 mutant complex systems are studied by molecular dynamics (MD) simulations. Through comparison of free RRM domain and complex systems, it's found that the RNA binding facilitates stabilizing the RNA-binding interface of RRM domain, especially the C-terminal loop. Although both R38Q and T103A/K104A mutations reduce the binding affinity of RRM domain and RNA, the underlining mechanisms are different. Principal component analysis (PCA) and Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) methods were used to explore the dynamical and recognition mechanisms of RRM domain and RNA. R38Q mutation is positioned on the homodimerization interface and mainly induces the large fluctuations of RRM domains. This mutation does not directly act on the RNA-binding interface, but some interfacial hydrogen bonds are weakened. In contrast, T103A/K104A mutations are located on the RNA-binding interface of RRM domain. These mutations obviously break most of high occupancy hydrogen bonds in the RNA-binding interface. Meanwhile, the key interfacial residues lose their favorable energy contributions upon RNA binding. The ranking of calculated binding energies in 3 complex systems is well consistent with that of experimental binding affinities. These results will be helpful in understanding the RNA recognition mechanisms of RRM domain.

show abstract

Section: Free Energy Landscapementioning

confidence: 99%

Exploring the molecular basis of RNA recognition by the dimeric RNA-binding protein via molecular simulation methods

Chang

Zhang

et al. 2016

RNA Biology

View full text Add to dashboard Cite

show abstract

“…Hence, we retained all the three models for MD simulations. In this way, we both exploit different starting structures and random seeds to initialize the simulations with a multi-replicate approach, which is commonly used to achieve a larger sampling of the conformational space [75][76][77]. Indeed, it is always crucial to verify the reproducibility of the results when classical constant temperature MD is used since independent replicates do not generally converge to identical results [78,79].…”

Section: Starting Structures For the Simulationsmentioning

confidence: 99%

Structural investigation of the cold-adapted acylaminoacyl peptidase from Sporosarcina psychrophila by atomistic simulations and biophysical methods

Papaleo

Parravicini

Grandori

et al. 2014

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics

Self Cite

View full text Add to dashboard Cite

“…The first principal component dominates the motion of the protein ( Figure 6A). A Gibbs free energy landscape is constructed over the first and second largest principal components which gives a clear description of the folding dynamics of the protein ( Figure 6B) (Papaleo et al, 2009;Maisuradze et al, 2012).…”

Section: Resultsmentioning

confidence: 99%

Evolutionary analysis of galectins and identification of potential galectin-1 inhibitors: A computational approach

Vipperla¹,

Kannan²,

Jayanthi³

2014

Bangladesh J Pharmacol

View full text Add to dashboard Cite

Free-energy landscape, principal component analysis, and structural clustering to identify representative conformations from molecular dynamics simulations: The myoglobin case

Cited by 347 publications

References 70 publications

Exploring the molecular basis of RNA recognition by the dimeric RNA-binding protein via molecular simulation methods

Exploring the molecular basis of RNA recognition by the dimeric RNA-binding protein via molecular simulation methods

Structural investigation of the cold-adapted acylaminoacyl peptidase from Sporosarcina psychrophila by atomistic simulations and biophysical methods

Evolutionary analysis of galectins and identification of potential galectin-1 inhibitors: A computational approach

Contact Info

Product

Resources

About