scholarly journals Potential of mean force and umbrella sampling simulation for the transport of 5‐oxazolidinone in heterotetrameric sarcosine oxidase

2021 ◽  
Author(s):  
Shigetaka Yoneda ◽  
Takami Saito ◽  
Daisuke Nakajima ◽  
Go Watanabe
Keyword(s):  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Sarcosine Oxidase

scholarly journals An Efficient GaMD Multi-Level Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems

2021 ◽  
Author(s):  
Fréderic Célerse ◽  
Theo Jaffrelot-Inizan ◽  
Louis Lagardère ◽  
Olivier Adjoua ◽  
Pierre Monmarché ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Adaptive Sampling ◽  
Sampling Strategy ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Enhanced Sampling ◽  
Polarizable Force Field ◽  
Accelerated Molecular Dynamics ◽  
Polarizable Force Fields ◽  
Multi Level

We detail a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We then introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups thanks to the use of fast multiple--timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual-water approach is tested on the 1D Potential of Mean Force (PMF) of the CD2-CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling--US--GaMD (ASUS--GaMD) scheme. The highly parallel ASUS--GaMD setup decreases time to convergence by respectively 10 and 20 compared to GaMD--US and US.

scholarly journals An Efficient GaMD Multi-Level Enhanced Sampling Strategy for Polarizable Force Fields Simulations of Large Biological Systems

2021 ◽  
Author(s):  
Fréderic Célerse ◽  
Theo Jaffrelot-Inizan ◽  
Louis Lagardère ◽  
Olivier Adjoua ◽  
Pierre Monmarché ◽  
...  
Keyword(s):  
Adaptive Sampling ◽  
Sampling Strategy ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Enhanced Sampling ◽  
Polarizable Force Field ◽  
Accelerated Molecular Dynamics ◽  
Polarizable Force Fields ◽  
Solute Interactions ◽  
Multi Level

We introduce a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs -accelerated implementation within Tinker-HP. For the specific use with the flexible AMOEBA polarizable force field (PFF), we introduce the new "dual–water" GaMD mode. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups with fast multiple–timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual–water approach is tested on the 1D Potential of Mean Force (PMF) of the CD2–CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS–GaMD capabilities but also the introduction of the new Adaptive Sampling–US–GaMD (ASUS–GaMD) scheme. The highly parallel ASUS–GaMD setup decreases time to convergence by respectively 10 and 20 compared to GaMD–US and US.

scholarly journals Thermodynamic and Kinetic Characterization of Protein Conformational Dynamics within a Riemannian Framework

2021 ◽  
Author(s):  
Curtis Goolsby ◽  
Ashkan Fakharzadeh ◽  
Mahmoud Moradi
Keyword(s):  
Free Energy ◽  
Transition Rate ◽  
Conformational Dynamics ◽  
Diffusion Constant ◽  
Minimum Free Energy ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Collective Variable ◽  
Bayesian Estimator ◽  
Riemannian Framework

AbstractWe have formulated a Riemannian framework for describing the geometry of collective variable spaces of biomolecules within the context of molecular dynamics (MD) simulations. The formalism provides a theoretical framework to develop enhanced sampling techniques, path-finding algorithms, and transition rate estimators consistent with a Riemannian treatment of the collective variable space, where the quantities of interest such as the potential of mean force (PMF) and minimum free energy path (MFEP) remain invariant under coordinate transformation. Specific algorithms within this framework are discussed such as the Riemannian umbrella sampling, the Riemannian string method, and a Riemannian-Bayesian estimator of free energy and diffusion constant, which can be used to estimate the transition rate along an MFEP.

MOLECULAR DYNAMICS SIMULATIONS OF DNA DIMERS BASED ON REPLICA-EXCHANGE UMBRELLA SAMPLING II: FREE ENERGY ANALYSIS

2005 ◽  
Vol 04 (02) ◽  
pp. 433-448 ◽  
Author(s):  
KATSUMI MURATA ◽  
YUJI SUGITA ◽  
YUKO OKAMOTO
Keyword(s):  
Free Energy ◽  
Energy Analysis ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Sequence Dependence ◽  
Reaction Coordinates ◽  
Energy Profiles ◽  
Dynamics Simulations ◽  
Free Energy Analysis ◽  
Good Agreement

The free energy change of the stacking process of DNA dimers has been investigated by potential of mean force (PMF) calculations. Two reaction coordinates were considered. One is the distance R between the glycosidic nitrogen atoms of the bases. The other is the pseudo dihedral angle X (N–Cl′–Cl′–N) . All 16 possible DNA dimers composed of the adenine, cytosine, guanine, or thymine bases in 5′ and 3′ positions were considered. From the free energy profiles, we observed good stacking for all DNA dimers and sequence-dependent stacking stability. This sequence dependence of the stacking free energy is in good agreement with the experimental results. We also observed that the PMF is the lowest at R = 4.0~4.4 Å and X = 20~40° for all the DNA dimers except for the dGpdA dimer. These values are close to those of the canonical B-DNA (4.4 Å and 29°).

scholarly journals Detailed Characterization of the Cooperative Binding of Piperine with Heat Shock Protein 70 by Molecular Biophysical Approaches

Biomedicines ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 629
Author(s):  
Gabriel Zazeri ◽  
Ana Paula Ribeiro Povinelli ◽  
Marcelo de Freitas Lima ◽  
Marinônio Lopes Cornélio
Keyword(s):  
Heat Shock ◽  
Heat Shock Protein ◽  
Conformational Changes ◽  
Binding Sites ◽  
Heat Shock Protein 70 ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Positive Cooperativity ◽  
Force Profile ◽  
Different Temperatures

In this work, for the first time, details of the complex formed by heat shock protein 70 (HSP70) independent nucleotide binding domain (NBD) and piperine were characterized through experimental and computational molecular biophysical methods. Fluorescence spectroscopy results revealed positive cooperativity between the two binding sites. Circular dichroism identified secondary conformational changes. Molecular dynamics along with molecular mechanics Poisson Boltzmann surface area (MM/PBSA) reinforced the positive cooperativity, showing that the affinity of piperine for NBD increased when piperine occupied both binding sites instead of one. The spontaneity of the complexation was demonstrated through the Gibbs free energy (∆G < 0 kJ/mol) for different temperatures obtained experimentally by van’t Hoff analysis and computationally by umbrella sampling with the potential of mean force profile. Furthermore, the mean forces which drove the complexation were disclosed by van’t Hoff and MM/PBSA as being the non-specific interactions. In conclusion, the work revealed characteristics of NBD and piperine interaction, which may support further drug discover studies.

scholarly journals Inserting small molecules across membrane mixtures: Insight from the potential of mean force

2019 ◽  
Author(s):  
Alessia Centi ◽  
Arghya Dutta ◽  
Sapun H. Parekh ◽  
Tristan Bereau
Keyword(s):  
Phase Separation ◽  
Small Molecules ◽  
Lipid Membrane ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Conformational Space ◽  
Coarse Grained ◽  
Computationally Efficient ◽  
Computational Screening ◽  
Wide Range

ABSTRACTSmall solutes have been shown to alter the lateral organization of cell membranes and reconstituted phospholipid bilayers; however, the mechanisms by which these changes happen are still largely unknown. Traditionally, both experiment and simulation studies have been restricted to testing only a few compounds at a time, failing to identify general molecular descriptors or chemical properties that would allow extrapolating beyond the subset of considered solutes. In this work, we probe the competing energetics of inserting a solute in different membrane environments by means of the potential of mean force. We show that these calculations can be used as a computationally-efficient proxy to establish whether a solute will stabilize or destabilize domain phase separation. Combined with umbrella sampling simulations and coarse-grained molecular dynamics simulations, we are able to screen solutes across a wide range of chemistries and polarities. Our results indicate that, for the system under consideration, preferential partitioning and therefore effectiveness in altering membrane phase separation are strictly linked to the location of insertion in the bilayer (i.e., midplane or interface). Our approach represents a fast and simple tool for obtaining structural and thermodynamic insight into the partitioning of small molecules between lipid domains and its relation to phase separation, ultimately providing a platform for identifying the key determinants of this process.SIGNIFICANCEIn this work we explore the relationship between solute chemistry and the thermodynamics of insertion in a mixed lipid membrane. By combining a coarse-grained resolution and umbrella-sampling simulations we efficiently sample conformational space to study the thermodynamics of phase separation. We demonstrate that measures of the potential of mean force—a computationally-efficient quantity—between different lipid environments can serve as a proxy to predict a compound’s ability to alter the thermodynamics of the lipid membrane. This efficiency allows us to set up a computational screening across many compound chemistries, thereby gaining insight beyond the study of a single or a handful of compounds.

scholarly journals An Efficient GaMD Multi-Level Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems

2021 ◽  
Author(s):  
Fréderic Célerse ◽  
Theo Jaffrelot-Inizan ◽  
Louis Lagardère ◽  
Olivier Adjoua ◽  
Pierre Monmarché ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Adaptive Sampling ◽  
Force Fields ◽  
Biological Systems ◽  
Sampling Strategy ◽  
Umbrella Sampling ◽  
Potential Of Mean Force ◽  
Enhanced Sampling ◽  
Polarizable Force Fields ◽  
Multi Level

We introduce a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field.By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups thanks to the use of fast multiple--timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual--water approach is tested on the 1D Potential of Mean Force (PMF) of the solvated CD2--CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling--US--GaMD (ASUS-GaMD) scheme. The highly parallel ASUS--GaMD setup decreases time to convergence by respectively 10 and 20 times compared to GaMD-US and US. Overall, beside the acceleration of PMF computations, Tinker-HP now allows for the simultaneous use of Adaptive Sampling and GaMD-"dual water" enhanced sampling approaches increasing the applicability of polarizable force fields to large scale simulations of biological systems.

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