scholarly journals Interpretation of Single-Molecule Force Experiments on Proteins Using Normal Mode Analysis

Nanomaterials ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2795
Author(s):  
Jacob Bauer ◽  
Gabriel Žoldák

Single-molecule force spectroscopy experiments allow protein folding and unfolding to be explored using mechanical force. Probably the most informative technique for interpreting the results of these experiments at the structural level makes use of steered molecular dynamics (MD) simulations, which can explicitly model the protein under load. Unfortunately, this technique is computationally expensive for many of the most interesting biological molecules. Here, we find that normal mode analysis (NMA), a significantly cheaper technique from a computational perspective, allows at least some of the insights provided by MD simulation to be gathered. We apply this technique to three non-homologous proteins that were previously studied by force spectroscopy: T4 lysozyme (T4L), Hsp70 and the glucocorticoid receptor domain (GCR). The NMA results for T4L and Hsp70 are compared with steered MD simulations conducted previously, and we find that we can recover the main results. For the GCR, which did not undergo MD simulation, our approach identifies substructures that correlate with experimentally identified unfolding intermediates. Overall, we find that NMA can make a valuable addition to the analysis toolkit for the structural analysis of single-molecule force experiments on proteins.

2005 ◽  
Vol 45 (supplement) ◽  
pp. S220
Author(s):  
H. Wako ◽  
M. Otsuka ◽  
Y. Tomizawa ◽  
M. Kato ◽  
S. Endo

Author(s):  
Anish Kumar

Objective: Drug resistance is an imperative issue in the treatment of patients with lung cancer. In this work, investigation of the drug resistance mechanism of G2032R mutation in ROS1 is carried out using computational simulation techniques.Methods: Molecular docking and molecular dynamics (MD) simulation approach have been utilized to uncover the mechanism behind crizotinib resistance in ROS1 at a molecular level. Normal mode analysis was carried out using ElNemo server which examines the movements and conformational changes in the protein structure. ArgusLab, PEARLS, and Autodock were employed for the docking analysis, whereas GROMACS package 4.5.3 was used for MD simulation approach.Results: The results from our analysis indicates that wild-type ROS1 (Protein Data Bank Code 3ZBF) could be more crucial for the crizotinib binding as it indicates largest binding affinity, minimum number of H-bonds, and higher flexibility than mutant-type ROS1. Moreover, the theoretical basis for the cause of drug insensitivity is the differences in the electrostatic properties of binding site residues between the wild and mutant ROS1 structures. Our analysis theoretically suggests that E-2027 is a key residue responsible for the ROS1 drug selectivity.Conclusion: Molecular docking and MD simulation results provide an explanation of the resistance caused by G2032R and may give a key clue for the drug design to encounter drug resistance.Keywords: ROS1, Crizotinib resistance, Molecular docking, Normal mode analysis, Molecular dynamic simulation.


2001 ◽  
Vol 15 (28n30) ◽  
pp. 3865-3868 ◽  
Author(s):  
H. MIYAOKA ◽  
T. KUZE ◽  
H. SANO ◽  
H. MORI ◽  
G. MIZUTANI ◽  
...  

We have obtained the Raman spectra of TiCl n (n= 2, 3, and 4). Assignments of the observed Raman bands were made by a normal mode analysis. The force constants were determined from the observed Raman band frequencies. We have found that the Ti-Cl stretching force constant increases as the oxidation number of the Ti species increases.


2020 ◽  
Vol 153 (21) ◽  
pp. 215103
Author(s):  
Alexander Klinger ◽  
Dominik Lindorfer ◽  
Frank Müh ◽  
Thomas Renger

2009 ◽  
Vol 60 (2) ◽  
pp. 169-173 ◽  
Author(s):  
Sayan K. Chakrabarti ◽  
Pulak Ranjan Giri ◽  
Kumar S. Gupta

2016 ◽  
Vol 120 (33) ◽  
pp. 8276-8288 ◽  
Author(s):  
Xin-Qiu Yao ◽  
Lars Skjærven ◽  
Barry J. Grant

2013 ◽  
Vol 12 (08) ◽  
pp. 1341005 ◽  
Author(s):  
FÁTIMA PARDO-AVILA ◽  
LIN-TAI DA ◽  
YING WANG ◽  
XUHUI HUANG

RNA polymerase is the enzyme that synthesizes RNA during the transcription process. To understand its mechanism, structural studies have provided us pictures of the series of steps necessary to add a new nucleotide to the nascent RNA chain, the steps altogether known as the nucleotide addition cycle (NAC). However, these static snapshots do not provide dynamic information of these processes involved in NAC, such as the conformational changes of the protein and the atomistic details of the catalysis. Computational studies have made efforts to fill these knowledge gaps. In this review, we provide examples of different computational approaches that have improved our understanding of the transcription elongation process for RNA polymerase, such as normal mode analysis, molecular dynamic (MD) simulations, Markov state models (MSMs). We also point out some unsolved questions that could be addressed using computational tools in the future.


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