scholarly journals Systematic Finite-Temperature Reduction of Crystal Energy Landscapes.

2020 ◽  
Author(s):  
Nicholas Francia ◽  
Louise S. Price ◽  
Jonas Nyman ◽  
Sarah (Sally) Price ◽  
Matteo Salvalaglio
Keyword(s):  
Molecular Dynamics ◽  
Finite Temperature ◽  
Structure Prediction ◽  
Lattice Energy ◽  
Biased Sampling ◽  
Energy Landscapes ◽  
Polymorphic Transformations ◽  
Temperature And Pressure ◽  
Dynamics Simulations ◽  
The Impact

<p>Crystal structure prediction methods are prone to overestimate the number of potential polymorphs of organic molecules. In this work, we aim to reduce the overprediction by systematically applying molecular dynamics simulations and biased sampling methods to cluster subsets of structures that can easily interconvert at finite temperature and pressure. Following this approach, we rationally reduce the number of predicted putative polymorphs in CSP-generated crystal energy landscapes. This uses an unsupervised clustering approach to analyze independent finite-temperature molecular dynamics trajectories and hence identify a representative structure of each cluster of distinct lattice energy minima that are effectively equivalent at finite temperature and pressure. Biased simulations are used to reduce the impact of limited sampling time and to estimate the work associated with polymorphic transformations. We demonstrate the proposed systematic approach by studying the polymorphs of urea and succinic acid, reducing an initial set of over 100 energetically plausible CSP structures to 12 and 27 respectively, including the experimentally known polymorphs. The simulations also indicate the types of disorder and stacking errors that may occur in real structures.<br></p>

scholarly journals Systematic Finite-Temperature Reduction of Crystal Energy Landscapes.

2020 ◽  
Author(s):  
Nicholas Francia ◽  
Louise S. Price ◽  
Jonas Nyman ◽  
Sarah (Sally) Price ◽  
Matteo Salvalaglio
Keyword(s):  
Molecular Dynamics ◽  
Finite Temperature ◽  
Structure Prediction ◽  
Lattice Energy ◽  
Biased Sampling ◽  
Energy Landscapes ◽  
Polymorphic Transformations ◽  
Temperature And Pressure ◽  
Dynamics Simulations ◽  
The Impact

<p>Crystal structure prediction methods are prone to overestimate the number of potential polymorphs of organic molecules. In this work, we aim to reduce the overprediction by systematically applying molecular dynamics simulations and biased sampling methods to cluster subsets of structures that can easily interconvert at finite temperature and pressure. Following this approach, we rationally reduce the number of predicted putative polymorphs in CSP-generated crystal energy landscapes. This uses an unsupervised clustering approach to analyze independent finite-temperature molecular dynamics trajectories and hence identify a representative structure of each cluster of distinct lattice energy minima that are effectively equivalent at finite temperature and pressure. Biased simulations are used to reduce the impact of limited sampling time and to estimate the work associated with polymorphic transformations. We demonstrate the proposed systematic approach by studying the polymorphs of urea and succinic acid, reducing an initial set of over 100 energetically plausible CSP structures to 12 and 27 respectively, including the experimentally known polymorphs. The simulations also indicate the types of disorder and stacking errors that may occur in real structures.<br></p>

scholarly journals Systematic Finite-Temperature Reduction of Crystal Energy Landscapes.

2020 ◽  
Author(s):  
Nicholas Francia ◽  
Louise S. Price ◽  
Jonas Nyman ◽  
Sarah (Sally) Price ◽  
Matteo Salvalaglio
Keyword(s):  
Molecular Dynamics ◽  
Finite Temperature ◽  
Structure Prediction ◽  
Lattice Energy ◽  
Biased Sampling ◽  
Energy Landscapes ◽  
Polymorphic Transformations ◽  
Temperature And Pressure ◽  
Dynamics Simulations ◽  
The Impact

<p>Crystal structure prediction methods are prone to overestimate the number of potential polymorphs of organic molecules. In this work, we aim to reduce the overprediction by systematically applying molecular dynamics simulations and biased sampling methods to cluster subsets of structures that can easily interconvert at finite temperature and pressure. Following this approach, we rationally reduce the number of predicted putative polymorphs in CSP-generated crystal energy landscapes. This uses an unsupervised clustering approach to analyze independent finite-temperature molecular dynamics trajectories and hence identify a representative structure of each cluster of distinct lattice energy minima that are effectively equivalent at finite temperature and pressure. Biased simulations are used to reduce the impact of limited sampling time and to estimate the work associated with polymorphic transformations. We demonstrate the proposed systematic approach by studying the polymorphs of urea and succinic acid, reducing an initial set of over 100 energetically plausible CSP structures to 12 and 27 respectively, including the experimentally known polymorphs. The simulations also indicate the types of disorder and stacking errors that may occur in real structures.<br></p>

scholarly journals Reducing Crystal Structure Overprediction of Ibuprofen with Large Scale Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Nicholas Francia ◽  
Louise Price ◽  
Matteo Salvalaglio
Keyword(s):  
Crystal Structure ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Crystal Structures ◽  
Finite Temperature ◽  
Structure Prediction ◽  
Large Scale ◽  
Lattice Energy ◽  
Racemic Mixture ◽  
Dynamics Simulations

<p>The control of the crystal form is a central issue in the pharmaceutical industry. The identification of putative polymorphs through Crystal Structure Prediction (CSP) methods is based on lattice energy calculations, which are known to significantly over-predict the number of plausible crystal structures. A valuable tool to reduce overprediction is to employ physics-based, dynamic simulations to coalesce lattice energy minima separated by small barriers into a smaller number of more stable geometries once thermal effects are introduced. Molecular dynamics simulations and enhanced sampling methods can be employed in this context to simulate crystal structures at finite temperature and pressure. </p><p>Here we demonstrate the applicability of approaches based on molecular dynamics to systematically process realistic CSP datasets containing several hundreds of crystal structures. The system investigated is ibuprofen, a conformationally flexible active pharmaceutical ingredient that crystallises both in enantiopure forms and as a racemic mixture. By introducing a hierarchical approach in the analysis of finite-temperature supercell configurations, we can post-process a dataset of 555 crystal structures, identifying 65% of the initial structures as labile, while maintaining all the experimentally known crystal structures in the final, reduced set. Moreover, the extensive nature of the initial dataset allows one to gain quantitative insight into the persistence and the propensity to transform of crystal structures containing common hydrogen-bonded intermolecular interaction motifs.</p>

scholarly journals Reducing Crystal Structure Overprediction of Ibuprofen with Large Scale Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Nicholas Francia ◽  
Louise Price ◽  
Matteo Salvalaglio
Keyword(s):  
Crystal Structure ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Crystal Structures ◽  
Finite Temperature ◽  
Structure Prediction ◽  
Large Scale ◽  
Lattice Energy ◽  
Racemic Mixture ◽  
Dynamics Simulations

<p>The control of the crystal form is a central issue in the pharmaceutical industry. The identification of putative polymorphs through Crystal Structure Prediction (CSP) methods is based on lattice energy calculations, which are known to significantly over-predict the number of plausible crystal structures. A valuable tool to reduce overprediction is to employ physics-based, dynamic simulations to coalesce lattice energy minima separated by small barriers into a smaller number of more stable geometries once thermal effects are introduced. Molecular dynamics simulations and enhanced sampling methods can be employed in this context to simulate crystal structures at finite temperature and pressure. </p><p>Here we demonstrate the applicability of approaches based on molecular dynamics to systematically process realistic CSP datasets containing several hundreds of crystal structures. The system investigated is ibuprofen, a conformationally flexible active pharmaceutical ingredient that crystallises both in enantiopure forms and as a racemic mixture. By introducing a hierarchical approach in the analysis of finite-temperature supercell configurations, we can post-process a dataset of 555 crystal structures, identifying 65% of the initial structures as labile, while maintaining all the experimentally known crystal structures in the final, reduced set. Moreover, the extensive nature of the initial dataset allows one to gain quantitative insight into the persistence and the propensity to transform of crystal structures containing common hydrogen-bonded intermolecular interaction motifs.</p>

scholarly journals Reducing Crystal Structure Overprediction of Ibuprofen with Large Scale Molecular Dynamics Simulations

CrystEngComm ◽  
2021 ◽  
Author(s):  
Nicholas Francesco Francia ◽  
Louise Price ◽  
Matteo Salvalaglio
Keyword(s):  
Crystal Structure ◽  
Molecular Dynamics ◽  
Pharmaceutical Industry ◽  
Molecular Dynamics Simulations ◽  
Structure Prediction ◽  
Large Scale ◽  
Lattice Energy ◽  
Crystal Form ◽  
Crystal Structure Prediction ◽  
Dynamics Simulations

The control of the crystal form is a central issue in the pharmaceutical industry. The identification of putative polymorphs through Crystal Structure Prediction (CSP) methods is based on lattice energy...

Finite Temperature Infrared Spectra from Polarizable Molecular Dynamics Simulations

2014 ◽  
Vol 10 (8) ◽  
pp. 3190-3199 ◽  
Author(s):  
David Semrouni ◽  
Ashwani Sharma ◽  
Jean-Pierre Dognon ◽  
Gilles Ohanessian ◽  
Carine Clavaguéra
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Infrared Spectra ◽  
Finite Temperature ◽  
Dynamics Simulations

Molecular Dynamics Study of Ion Impact Phenomena and Compressive Stress in Thin Films

1993 ◽  
Vol 317 ◽  
Author(s):  
N.A. Marks ◽  
P. Guan ◽  
D.R. Mckenzie ◽  
B.A. PailThorpe
Keyword(s):  
Molecular Dynamics ◽  
Three Dimensional ◽  
Carbon Films ◽  
Loss Mechanism ◽  
Ion Energy ◽  
Lennard Jones ◽  
Impact Phenomena ◽  
Ion Impact ◽  
Dynamics Simulations ◽  
The Impact

ABSTRACTMolecular dynamics simulations of nickel and carbon have been used to study the phenomena due to ion impact. The nickel and carbon interactions were described using the Lennard-Jones and Stillinger-Weber potentials respectively. The phenomena occurring after the impact of 100 e V to 1 keV ions were studied in the nickel simulations, which were both two and three-dimensional. Supersonic focussed collision sequences (or focusons) were observed, and associated with these focusons were unexpected sonic bow waves, which were a major energy loss mechanism for the focuson. A number of 2D carbon films were grown and the stress in the films as a function of incident ion energy was Measured. With increasing energy the stress changed from tensile to compressive and reached a maximum around 50 eV, in agreement with experiment.

scholarly journals Exploiting correlated molecular-dynamics networks to counteract enzyme activity–stability trade-off

2018 ◽  
Vol 115 (52) ◽  
pp. E12192-E12200 ◽  
Author(s):  
Haoran Yu ◽  
Paul A. Dalby
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Active Site ◽  
Dynamic Networks ◽  
Aromatic Aldehydes ◽  
Active Site Residues ◽  
Trade Off ◽  
Highly Correlated ◽  
Dynamics Simulations ◽  
The Impact

The directed evolution of enzymes for improved activity or substrate specificity commonly leads to a trade-off in stability. We have identified an activity–stability trade-off and a loss in unfolding cooperativity for a variant (3M) of Escherichia coli transketolase (TK) engineered to accept aromatic substrates. Molecular dynamics simulations of 3M revealed increased flexibility in several interconnected active-site regions that also form part of the dimer interface. Mutating the newly flexible active-site residues to regain stability risked losing the new activity. We hypothesized that stabilizing mutations could be targeted to residues outside of the active site, whose dynamics were correlated with the newly flexible active-site residues. We previously stabilized WT TK by targeting mutations to highly flexible regions. These regions were much less flexible in 3M and would not have been selected a priori as targets using the same strategy based on flexibility alone. However, their dynamics were highly correlated with the newly flexible active-site regions of 3M. Introducing the previous mutations into 3M reestablished the WT level of stability and unfolding cooperativity, giving a 10.8-fold improved half-life at 55 °C, and increased midpoint and aggregation onset temperatures by 3 °C and 4.3 °C, respectively. Even the activity toward aromatic aldehydes increased up to threefold. Molecular dynamics simulations confirmed that the mutations rigidified the active-site via the correlated network. This work provides insights into the impact of rigidifying mutations within highly correlated dynamic networks that could also be useful for developing improved computational protein engineering strategies.

scholarly journals A NOVEL DESIGN OF PERISTALTIC CARBON NANO PUMP AND AN ANALYSIS OF HELIUM FLOW

2021 ◽  
Vol 55 (6) ◽  
Author(s):  
M. Gokhan Günay ◽  
Ubade Kemerli
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Pump Design ◽  
Helium Atoms ◽  
Multi Walled Carbon Nanotubes ◽  
Temperature And Pressure ◽  
Dynamics Simulations ◽  
Walled Carbon Nanotubes ◽  
Novel Design ◽  
Main Carbon

A novel nano-scale pump that can transport atoms or small molecules with a peristaltic motion is designed. It is proven by molecular-dynamics simulations that the introduced nano-pump design works properly. The designed nano-pump consists of one main carbon nanotube named the flow tube and two rotors where multi-walled carbon nanotubes are attached. The pumping of helium atoms by the designed peristaltic carbon nano-pump is investigated by molecular-dynamics simulations. For varying rotor speeds and blade counts, time-averaged velocity, temperature, and pressure results of pumped helium atoms are calculated, and relationships between them are modeled as polynomial surfaces. The results showed that rotor frequency increases the velocity of helium linearly and the temperature and pressure of helium non-linearly. Furthermore, the blade count of the proposed mechanism does not substantially affect the velocity as per the previous studies in the literature.

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