scholarly journals Namdinator - Automatic Molecular Dynamics flexible fitting of structural models into cryo-EM and crystallography experimental maps

2018 ◽  
Author(s):  
Rune Thomas Kidmose ◽  
Jonathan Juhl ◽  
Poul Nissen ◽  
Thomas Boesen ◽  
Jesper Lykkegaard Karlsen ◽  
...  

AbstractModel building into experimental maps is a key element of structural biology, but can be both time consuming and error-prone. Here we present Namdinator, an easy-to-use tool that enables the user to run a Molecular Dynamics Flexible Fitting (MDFF) simulation in an automated manner through a pipeline system. Namdinator will modify an atomic model to fit within cryo-EM or crystallography density maps, and can be used advantageously for both the initial fitting of models, and for a geometrical optimization step to correct outliers, clashes and other model problems. We have benchmarked Namdinator against 39 deposited models and maps from cryo-EM and observe model improvements in 34 of these cases (87%). Clashes between atoms were reduced, and model-to-map fit and overall model geometry were improved, in several cases substantially. We show that Namdinator is able to model large scale conformational changes compared to the starting model. Namdinator is a fast and easy way to create suitable initial models for both cryo-EM and crystallography. It can fix model errors in the final steps of model building, and is usable for structural model builders at all skill levels. Namdinator is available as a web service (https://namdinator.au.dk), or can be run locally as a command-line tool.SynopsisA pipeline tool called Namdinator is presented that enables the user to run a Molecular Dynamics Flexible Fitting (MDFF) simulation in a fully automated manner, both online and locally. This provides a fast and easy way to create suitable initial models for both cryo-EM and crystallography and help fix errors in the final steps of model building.

IUCrJ ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 526-531 ◽  
Author(s):  
Rune Thomas Kidmose ◽  
Jonathan Juhl ◽  
Poul Nissen ◽  
Thomas Boesen ◽  
Jesper Lykkegaard Karlsen ◽  
...  

Model building into experimental maps is a key element of structural biology, but can be both time consuming and error prone for low-resolution maps. Here we present Namdinator, an easy-to-use tool that enables the user to run a molecular dynamics flexible fitting simulation followed by real-space refinement in an automated manner through a pipeline system. Namdinator will modify an atomic model to fit within cryo-EM or crystallography density maps, and can be used advantageously for both the initial fitting of models, and for a geometrical optimization step to correct outliers, clashes and other model problems. We have benchmarked Namdinator against 39 deposited cryo-EM models and maps, and observe model improvements in 34 of these cases (87%). Clashes between atoms were reduced, and the model-to-map fit and overall model geometry were improved, in several cases substantially. We show that Namdinator is able to model large-scale conformational changes compared to the starting model. Namdinator is a fast and easy tool for structural model builders at all skill levels. Namdinator is available as a web service (https://namdinator.au.dk), or it can be run locally as a command-line tool.


2020 ◽  
Author(s):  
Jordi Juárez-Jiménez ◽  
Philip Tew ◽  
Michael o'connor ◽  
Salome Llabres ◽  
Rebecca Sage ◽  
...  

<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>


2020 ◽  
Author(s):  
Jordi Juárez-Jiménez ◽  
Philip Tew ◽  
Michael o'connor ◽  
Salome Llabres ◽  
Rebecca Sage ◽  
...  

<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>


2021 ◽  
Author(s):  
Sanat Aidarbayev ◽  
Mohamed Kamel Ouldamer ◽  
Guillaume Masson ◽  
Jean-Michel Codo

Abstract Objectives/Scope At brownfield development stage, dealing with diverse and large amount of data makes it challenging to integrate them all in a consistent manner to build a prime structural model. Like many others, the studied field consists of several-stacked reservoirs featuring many faults and close to a thousand drilled wells with vertical, slanted and horizontal trajectories. On top of that, many horizontal wells are targeting thin carbonate layers for which tightly spaced data points often result in conflicting observations. Consequently, horizontal and deviated wells are commonly discarded from structural modelling, leaving substantial and valuable information unused. Some of these wells may be indirectly accounted through the introduction of pseudo-wells, making the modelling workflow tedious, user-dependent and therefore difficult to repeat. Methods, Procedures, Process ’It's better to be approximately right than exactly wrong’ quoted by Carveth Read, 18th century. Accordingly, every physical measurement, even from the most modern and sophisticated tools, is subject to some uncertainty. Therefore, assessing the uncertainty related to each input data is paramount in this method. Integrated teamwork between geologists, geophysicists and drilling specialists lead to a thorough analysis of each data feeding the process of structural model building while providing best uncertainty estimates. The ranges were specified for ∼1000 well trajectories, ∼16000 geological markers, 3 seismic travel time maps, 3 interval velocities and 59 thickness maps. All available data are used in a consistent manner to minimize the depth uncertainty. The accuracy is further improved by linking together all surfaces in a multi-layered model. In addition, this methodology considers both large scale spatial continuity capturing structural trends and more local scale incorporating inter-well variations of thickness due to sedimentological controls. Results, Observations, Conclusions After following this approach, all subsurface data started to come in agreement and resulted in more geological architectures. As an example, Figure 1 shows a cross-section along a well that drilled in B4 target layer which average thickness of 6 ft. As illustrated in the left figure, classical workflow using vertical wells and some pseudo-wells resulted in an anomalous pull-up structure and overall wavy non-geological geometry. Moreover, the well shows that it is in non-reservoir dense layer even though the well in the reservoir based on the zone log interpretation. However, the right figure shows that considering horizontal wells and uncertainties help to integrate all subsurface data with improved consistency where the structure model is smoother & more geological, plus the well is correctly placed in the targeted reservoir. Novel/Additive Information This approach will make the studied field one of the first brownfields that incorporated all data in consistent manner without pseudo-wells to build 3D structural model. It will bring considerable value to reduce uncertainties during subsequent property and dynamic modelling stages.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2917-2917
Author(s):  
Tai-Sung Lee ◽  
Steven Potts ◽  
Hagop Kantarjian ◽  
Jorge Cortes ◽  
Francis Giles ◽  
...  

Abstract Molecular dynamics (MD) simulations on the complex of imatinib with the wild-type, T315I, and other 10 P-loop mutants of the tyrosine kinase Bcr-Abl have been performed to study the imatinib resistance mechanism at the atomic level. MD simulations show that large scale computational simulations could offer insight information that a static structure or simple homology modeling methods cannot provide for studying the Bcr-Abl imatinib resistance problem, especially in the case of conformational changes due to remote mutations. By utilizing the Molecular Mechanics/Poisson-Boltzmann surface area (MM-PBSA) techniques and analyzing the interactions between imatinib and individual residues, imatinib resistance mechanisms not previously thought have been revealed. Non-directly contacted P-loop mutations either unfavorably change the direct electrostatic interactions with imatinib, or cause the conformational changes influencing the contact energies between imatinib and other non-P-loop residues. We demonstrate that imatinib resistance of T315I mainly comes from the breakdown of the interactions between imatinib and E286 and M290, contradictory to previously suggested that the missing hydrogen bonding is the main contribution. We also demonstrate that except for the mutations of the direct contact residues, such as L248 and Y253, the unfavorable electrostatic interaction between P-loop and imatinib is the main reason for resistance for the P-loop mutations. Furthermore, in Y255H, protonation of the histidin is essential for rendering this mutation resistant to Gleevec. Our results demonstrate that MD is a powerful way to verify and predict clinical response or resistance to imatinib and other potential drugs.


2020 ◽  
Author(s):  
Jordi Juárez-Jiménez ◽  
Philip Tew ◽  
Michael o'connor ◽  
Salome Llabres ◽  
Rebecca Sage ◽  
...  

<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>


2018 ◽  
Author(s):  
D. R. Kattnig ◽  
C. Nielsen ◽  
I. A. Solov’yov

AbstractBirds appear to be equipped with a light-dependent, radical-pair-based magnetic compass that relies on truly quantum processes. While the identity of the sensory protein has remained speculative, cryptochrome 4 has recently been identified as the most auspicious candidate. Here, we report on allatom molecular dynamics (MD) simulations addressing the structural reorganisations that accompany the photoreduction of the flavin cofactor in a model of the European robin cryptochrome 4 (ErCry4). Extensive MD simulations reveal that the photo-activation of ErCry4 induces large-scale conformational changes on short (hundreds of nanoseconds) timescales. Specifically, the photo-reduction is accompanied with the release of the C-terminal tail, structural rearrangements in the vicinity of the FAD-binding site, and the noteworthy formation of an α-helical segment at the N-terminal part. Some of these rearrangements appear to expose potential phosphorylation sites. We describe the conformational dynamics of the protein using a graph-based approach that is informed by the adjacency of residues and the correlation of their local motions. This approach reveals densely coupled reorganisation communities, which facilitate an efficient signal transduction due to a high density of hubs. These communities are interconnected by a small number of highly important residues characterized by high betweenness centrality. The network approach clearly identifies the sites restructuring upon photoactivation, which appear as protrusions or delicate bridges in the reorganisation network. We also find that, unlike in the homologous cryptochrome from D. melanogaster, the release of the C-terminal domain does not appear to be correlated with the transposition of a histidine residue close to the FAD cofactor.


2020 ◽  
Vol 117 (24) ◽  
pp. 13490-13498 ◽  
Author(s):  
Andrew D. Geragotelis ◽  
Mona L. Wood ◽  
Hendrik Göddeke ◽  
Liang Hong ◽  
Parker D. Webster ◽  
...  

The voltage-gated Hv1 proton channel is a ubiquitous membrane protein that has roles in a variety of cellular processes, including proton extrusion, pH regulation, production of reactive oxygen species, proliferation of cancer cells, and increased brain damage during ischemic stroke. A crystal structure of an Hv1 construct in a putative closed state has been reported, and structural models for the channel open state have been proposed, but a complete characterization of the Hv1 conformational dynamics under an applied membrane potential has been elusive. We report structural models of the Hv1 voltage-sensing domain (VSD), both in a hyperpolarized state and a depolarized state resulting from voltage-dependent conformational changes during a 10-μs-timescale atomistic molecular dynamics simulation in an explicit membrane environment. In response to a depolarizing membrane potential, the S4 helix undergoes an outward displacement, leading to changes in the VSD internal salt-bridge network, resulting in a reshaping of the permeation pathway and a significant increase in hydrogen bond connectivity throughout the channel. The total gating charge displacement associated with this transition is consistent with experimental estimates. Molecular docking calculations confirm the proposed mechanism for the inhibitory action of 2-guanidinobenzimidazole (2GBI) derived from electrophysiological measurements and mutagenesis. The depolarized structural model is also consistent with the formation of a metal bridge between residues located in the core of the VSD. Taken together, our results suggest that these structural models are representative of the closed and open states of the Hv1 channel.


Sign in / Sign up

Export Citation Format

Share Document