THEORETICAL INVESTIGATIONS ON ELUCIDATING FUNDAMENTAL MECHANISMS OF CATALYSIS AND DYNAMICS INVOLVED IN TRANSCRIPTION BY RNA POLYMERASE

2013 ◽  
Vol 12 (08) ◽  
pp. 1341005 ◽  
Author(s):  
FÁTIMA PARDO-AVILA ◽  
LIN-TAI DA ◽  
YING WANG ◽  
XUHUI HUANG
Keyword(s):  
Rna Polymerase ◽  
Conformational Changes ◽  
Normal Mode Analysis ◽  
Md Simulations ◽  
Mode Analysis ◽  
Transcription Process ◽  
Nucleotide Addition ◽  
Theoretical Investigations ◽  
State Models ◽  
Elongation Process

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.

scholarly journals Analysis of changes of cavity volumes in predefined directions of protein motions and cavity flexibility

2021 ◽  
Author(s):  
German P. Barletta ◽  
Matias Barletta ◽  
Tadeo E. Saldaño ◽  
Sebastian Alberti
Keyword(s):  
Conformational Changes ◽  
Normal Mode Analysis ◽  
Growth Factor Receptor ◽  
Principal Component ◽  
Md Simulations ◽  
Mode Analysis ◽  
It Use ◽  
Nmr Structures ◽  
Structural Distortions ◽  
Protein Fluctuations

Dynamics of protein cavities associated with protein fluctuations and conformational plasticity is essential for their biological function. NMR ensembles, Molecular Dynamics (MD) simulations combined with Principal Component Analysis (PCA), and Normal Mode Analysis (NMA) provide appropriate frameworks to explore functionally relevant protein dynamics and cavity changes relationships. Within this context, we have developed ANA (Analysis of Null Areas), an efficient method to calculate cavity volumes. ANA is based on a combination of algorithms that guarantees its robustness against numerical differentiations. This is a unique feature with respect to other methods. Herein, we test ANA as a biophysical and bioinformatic method to analyze different structural and dynamics properties of cavities. In order to address this task, we have developed an updated and improved version of ANA that expands it use to quantify changes in cavity features, like volume and flexibility, due to protein structural distortions performed on predefined biologically relevant directions, e.g, directions of largest contribution to protein fluctuations (PCA modes) obtained by MD simulations or ensembles of NMR structures, collective NMA modes or any other direction of motion associated with specific conformational changes. A web page has been developed and its facilities are explained in detail, making the software available to all users. Firstly, we show that ANA can be useful to explore gradual changes of cavity volume and flexibility associated with protein ligand binding. Secondly, we perform a comparison study of the extent of variability between protein backbone structural distortions, and changes in cavity volumes and flexibilities evaluated for an ensemble of NMR active and inactive conformers of the epidermal growth factor receptor (EGFR) structures. Finally, we compare changes in size and flexibility between sets of NMR structures for different homologous chains of dynein.

Mechanical Properties of α-Helices Estimated Using Molecular Dynamics and Finite Element Simulations

2008 ◽  
Author(s):  
Peyman Honarmandi ◽  
Philip Bransford ◽  
Roger D. Kamm
Keyword(s):  
Mechanical Properties ◽  
Molecular Dynamics ◽  
Finite Element ◽  
Solid Mechanics ◽  
Normal Mode Analysis ◽  
Computational Cost ◽  
Md Simulations ◽  
Elastic Stiffness ◽  
Mode Analysis ◽  
Molecular Volume

Mechanical properties of biomolecules and their response to mechanical forces may be studied using Molecular Dynamics (MD) simulations. However, high computational cost is a primary drawback of MD simulations. This paper presents a computational framework based on the integration of the Finite Element Method (FEM) with MD simulations to calculate the mechanical properties of polyalanine α-helix proteins. In this method, proteins are treated as continuum elastic solids with molecular volume defined exclusively by their atomic surface. Therefore, all solid mechanics theories would be applicable for the presumed elastic media. All-atom normal mode analysis is used to calculate protein’s elastic stiffness as input to the FEM. In addition, constant force molecular dynamics (CFMD) simulations can be used to predict other effective mechanical properties, such as the Poisson’s Ratio. Force versus strain data help elucidate the mechanical behavior of α-helices upon application of constant load. The proposed method may be useful in identifying the mechanical properties of any protein or protein assembly with known atomic structure.

scholarly journals STRUCTURE FLUCTUATIONS AND CONFORMATIONAL CHANGES IN PROTEIN BINDING

2012 ◽  
Vol 10 (02) ◽  
pp. 1241002 ◽  
Author(s):  
ANATOLY M. RUVINSKY ◽  
TATSIANA KIRYS ◽  
ALEXANDER V. TUZIKOV ◽  
ILYA A. VAKSER
Keyword(s):  
Conformational Changes ◽  
Protein Complexes ◽  
Normal Mode Analysis ◽  
Distribution Functions ◽  
Mode Analysis ◽  
Amino Acid Type ◽  
Dihedral Angles ◽  
Elastic Network Model ◽  
Centers Of Mass ◽  
Interface Residues

Structure fluctuations and conformational changes accompany all biological processes involving macromolecules. The paper presents a classification of protein residues based on the normalized equilibrium fluctuations of the residue centers of mass in proteins and a statistical analysis of conformation changes in the side-chains upon binding. Normal mode analysis and an elastic network model were applied to a set of protein complexes to calculate the residue fluctuations and develop the residue classification. Comparison with a classification based on normalized B-factors suggests that the B-factors may underestimate protein flexibility in solvent. Our classification shows that protein loops and disordered fragments are enriched with highly fluctuating residues and depleted with weakly fluctuating residues. Strategies for engineering thermostable proteins are discussed. To calculate the dihedral angles distribution functions, the configuration space was divided into cells by a cubic grid. The effect of protein association on the distribution functions depends on the amino acid type and a grid step in the dihedral angles space. The changes in the dihedral angles increase from the near-backbone dihedral angle to the most distant one, for most residues. On average, one fifth of the interface residues change the rotamer state upon binding, whereas the rest of the interface residues undergo local readjustments within the same rotamer.

Structure network analysis to gain insights into GPCR function

2016 ◽  
Vol 44 (2) ◽  
pp. 613-618 ◽  
Author(s):  
Francesca Fanelli ◽  
Angelo Felline ◽  
Francesco Raimondi ◽  
Michele Seeber
Keyword(s):  
G Protein ◽  
Normal Mode Analysis ◽  
Network Models ◽  
Md Simulations ◽  
G Protein Coupled Receptors ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Biomolecular Systems ◽  
Retinal Chromophore ◽  
G Protein Coupled

G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM–NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM–NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor.

scholarly journals Conformational heterogeneity of the AAA ATPase p97 characterized by single particle cryo-EM

2014 ◽  
Vol 70 (a1) ◽  
pp. C853-C853
Author(s):  
Driss Mountassif ◽  
Lucien Fabre ◽  
Kaustuv Basu ◽  
Mihnea Bostina ◽  
Slavica Jonic ◽  
...  
Keyword(s):  
Atpase Activity ◽  
Conformational Changes ◽  
Single Particle ◽  
Molecular Mechanisms ◽  
Protein Complexes ◽  
Normal Mode Analysis ◽  
Single Amino Acid ◽  
Mode Analysis ◽  
Conformational Heterogeneity ◽  
Aaa Atpase

p97, a member of the AAA (ATPase Associated with various Activities) ATPase family, is essential and centrally involved in a wide variety of cellular processes. Single amino-acid substitutions in p97 have been associated with the severe degenerative disorder of Inclusion Body Myopathy associated with Paget disease of bone and Frontotemporal Dementia (IBMPFD) as well as amytropic leteral sclerosis (ALS). Current models propose that p97 acts as a motor transmitting the energy from the ATPase cycle to conformational changes of substrate protein complexes causing segregation, remodeling or translocation. Mutations at the interface between the N and the D1 domains impact the ATPase activity and the conformation of D2 on the opposite side of the protein complex, suggesting intermolecular communication. Because of limited structural information, the molecular mechanisms on how p97 drives its activities and the molecular basis for transmission of information within the molecule remain elusive. Structural heterogeneity is observed in vitro and is likely relevant for the in vivo biological function of p97. Single particle cryo-EM is the method of choice to study a flexible complex. The technique allows study in solution and also deals with sample heterogeneity by image classification. We have set-up the characterization of the conformational heterogeneity in WT and disease relevant p97 mutant using multi-likelihood classification and Hybrid Electron Microscopy Normal Mode Analysis HEMNMA. The multi-likelihood analysis shows a link between the conformations of the N and D2 domains. HEMNMA allows the analysis of the asymmetry of the conformational changes. Together these studies describe the structural flexibility of p97 and the coupling of the ATPase activity with conformational changes in health and in disease. Study of this model system also allows the development of new methods to understand the conformational heterogeneity of other protein complexes.

scholarly journals A force field for virtual atom molecular mechanics of proteins

2009 ◽  
Vol 106 (37) ◽  
pp. 15667-15672 ◽  
Author(s):  
Anil Korkut ◽  
Wayne A. Hendrickson
Keyword(s):  
Force Field ◽  
Molecular Mechanics ◽  
Normal Mode ◽  
Conformational Changes ◽  
Normal Mode Analysis ◽  
Coarse Grained ◽  
Mode Analysis ◽  
Biological Macromolecules ◽  
Molecular Mechanics Calculations ◽  
Low Degrees

Activities of many biological macromolecules involve large conformational transitions for which crystallography can specify atomic details of alternative end states, but the course of transitions is often beyond the reach of computations based on full-atomic potential functions. We have developed a coarse-grained force field for molecular mechanics calculations based on the virtual interactions of Cα atoms in protein molecules. This force field is parameterized based on the statistical distribution of the energy terms extracted from crystallographic data, and it is formulated to capture features dependent on secondary structure and on residue-specific contact information. The resulting force field is applied to energy minimization and normal mode analysis of several proteins. We find robust convergence in minimizations to low energies and energy gradients with low degrees of structural distortion, and atomic fluctuations calculated from the normal mode analyses correlate well with the experimental B-factors obtained from high-resolution crystal structures. These findings suggest that the virtual atom force field is a suitable tool for various molecular mechanics applications on large macromolecular systems undergoing large conformational changes.

scholarly journals A Virtual Reality Ensemble Molecular Dynamics Workflow to Study Complex Conformational Changes in Proteins

2020 ◽  
Author(s):  
Jordi Juárez-Jiménez ◽  
Philip Tew ◽  
Michael o'connor ◽  
Salome Llabres ◽  
Rebecca Sage ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Virtual Reality ◽  
Conformational Changes ◽  
Large Scale ◽  
A Priori ◽  
Computational Cost ◽  
Md Simulations ◽  
Collective Variables ◽  
Sampling Protocols ◽  
State Models

<p>Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics and their biological function. Currently it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome ‘collective variable’ enhanced sampling protocols. Here we describe a framework that combines ensemble MD simulations and virtual-reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables <i>a priori</i>. We further show that eMD-VR generated pathways can be combined with Markov State Models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts. </p>

scholarly journals Protein conformational transitions explored by a morphing approach based on normal mode analysis in internal coordinates

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0258818
Author(s):  
Byung Ho Lee ◽  
Soon Woo Park ◽  
Soojin Jo ◽  
Moon Ki Kim
Keyword(s):  
Normal Mode ◽  
Conformational Changes ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Conformational Transition ◽  
Normal Mode Analysis ◽  
Mode Analysis ◽  
Theoretical Approaches ◽  
Internal Coordinates ◽  
Transition Pathways

Large-scale conformational changes are essential for proteins to function properly. Given that these transition events rarely occur, however, it is challenging to comprehend their underlying mechanisms through experimental and theoretical approaches. In this study, we propose a new computational methodology called internal coordinate normal mode-guided elastic network interpolation (ICONGENI) to predict conformational transition pathways in proteins. Its basic approach is to sample intermediate conformations by interpolating the interatomic distance between two end-point conformations with the degrees of freedom constrained by the low-frequency dynamics afforded by normal mode analysis in internal coordinates. For validation of ICONGENI, it is applied to proteins that undergo open-closed transitions, and the simulation results (i.e., simulated transition pathways) are compared with those of another technique, to demonstrate that ICONGENI can explore highly reliable pathways in terms of thermal and chemical stability. Furthermore, we generate an ensemble of transition pathways through ICONGENI and investigate the possibility of using this method to reveal the transition mechanisms even when there are unknown metastable states on rough energy landscapes.

scholarly journals MODE-TASK: Large-scale protein motion tools

2017 ◽  
Author(s):  
Caroline Ross ◽  
Bilal Nizami ◽  
Michael Glenister ◽  
Olivier Sheik Amamuddy ◽  
Ali Rana Atilgan ◽  
...  
Keyword(s):  
Large Scale ◽  
Protein Complexes ◽  
Normal Mode Analysis ◽  
Md Simulations ◽  
Supplementary Information ◽  
Mode Analysis ◽  
Analysis Tool ◽  
Link Type ◽  
Supplementary Material ◽  
Anisotropic Network

AbstractSummaryMODE-TASK, a novel software suite, comprises Principle Component Analysis, Multidimensional Scaling, and t-Distributed Stochastic Neighbor Embedding techniques using molecular dynamics trajectories. MODE-TASK also includes a Normal Mode Analysis tool based on Anisotropic Network Model so as to provide a variety of ways to analyse and compare large-scale motions of protein complexes for which long MD simulations are prohibitive.Availability and ImplementationMODE-TASK has been open-sourced, and is available for download from https://github.com/RUBi-ZA/MODE-TASK, implemented in Python and C++.Supplementary informationDocumentation available at http://mode-task.readthedocs.io.

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