scholarly journals Semi-Automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion

2020 ◽  
Author(s):  
Yalun Yu ◽  
Andreas Kramer ◽  
Andrew Simmonett ◽  
Rick Venable ◽  
Alex MacKerell ◽  
...  
Keyword(s):  
Force Field ◽  
Lipid Bilayers ◽  
Long Range ◽  
Liquid Crystalline ◽  
Pair Correlation ◽  
Optimization Method ◽  
Free Energy Calculations ◽  
Fine Tuning ◽  
Compression Isotherm ◽  
High Level

The development of the CHARMM lipid force field (FF) can be traced back to the early 1990s with its current version denoted CHARMM36 (C36). The parametrization of C36 utilized high-level quantum mechanical data and free energy calculations of model compounds before parameters were manually adjusted to yield agreement with experimental properties of lipid bilayers. While such manual fine-tuning of FF parameters is based on intuition and trial-and-error, automated methods can identify beneficial modifications of the parameters via their sensitivities and thereby guide the optimization process. This paper introduces a semi-automated approach to reparametrize the CHARMM lipid FF with consistent inclusion of long-range dispersion through the LennardJones particle-mesh Ewald (LJ-PME) approach. The optimization method is based on thermodynamic reweighting with regularization with respect to the C36 set. Two independent optimizations with different topology restrictions are presented. Targets of the optimizations are primarily liquid crystalline phase properties of lipid bilayers and the compression isotherm of monolayers. Pair correlation functions between water and lipid functional groups in aqueous solution are also included to address headgroup hydration. While the physics of the reweighting strategy itself is well understood, applying it to heterogeneous, complex anisotropic systems poses additional challenges. These were overcome through careful selection of target properties and reweighting settings allowing for the successful incorporation of the explicit treatment of long-range dispersion, and we denote the newly optimized lipid force field as C36/LJ-PME. The current implementation of the optimization protocol will facilitate the future development of the CHARMM and related lipid force fields.<br>

scholarly journals Semi-Automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion

2020 ◽  
Author(s):  
Yalun Yu ◽  
Andreas Kramer ◽  
Andrew Simmonett ◽  
Rick Venable ◽  
Alex MacKerell ◽  
...  
Keyword(s):  
Force Field ◽  
Lipid Bilayers ◽  
Long Range ◽  
Liquid Crystalline ◽  
Pair Correlation ◽  
Optimization Method ◽  
Free Energy Calculations ◽  
Fine Tuning ◽  
Compression Isotherm ◽  
High Level

The development of the CHARMM lipid force field (FF) can be traced back to the early 1990s with its current version denoted CHARMM36 (C36). The parametrization of C36 utilized high-level quantum mechanical data and free energy calculations of model compounds before parameters were manually adjusted to yield agreement with experimental properties of lipid bilayers. While such manual fine-tuning of FF parameters is based on intuition and trial-and-error, automated methods can identify beneficial modifications of the parameters via their sensitivities and thereby guide the optimization process. This paper introduces a semi-automated approach to reparametrize the CHARMM lipid FF with consistent inclusion of long-range dispersion through the LennardJones particle-mesh Ewald (LJ-PME) approach. The optimization method is based on thermodynamic reweighting with regularization with respect to the C36 set. Two independent optimizations with different topology restrictions are presented. Targets of the optimizations are primarily liquid crystalline phase properties of lipid bilayers and the compression isotherm of monolayers. Pair correlation functions between water and lipid functional groups in aqueous solution are also included to address headgroup hydration. While the physics of the reweighting strategy itself is well understood, applying it to heterogeneous, complex anisotropic systems poses additional challenges. These were overcome through careful selection of target properties and reweighting settings allowing for the successful incorporation of the explicit treatment of long-range dispersion, and we denote the newly optimized lipid force field as C36/LJ-PME. The current implementation of the optimization protocol will facilitate the future development of the CHARMM and related lipid force fields.<br>

scholarly journals A new lipid force field (FUJI)

2018 ◽  
Author(s):  
Nozomu Kamiya ◽  
Keiko Shinoda ◽  
Hideaki Fujitani
Keyword(s):  
Force Field ◽  
Lipid Bilayers ◽  
Lateral Diffusion ◽  
Multidrug Efflux ◽  
Amber Force Field ◽  
Torsion Energy ◽  
Area Per Lipid ◽  
The Stability ◽  
Dynamics Simulations ◽  
High Level

AbstractTo explore inhomogeneous and anisotropic systems such as lipid bilayers, the Lennard-Jones particle mesh Ewald (LJ-PME) method was applied without a traditional isotropic dispersion correction. As the popular AMBER and CHARMM lipid force fields were developed using a cutoff scheme, their lipid bilayers unacceptably shrank when using LJ-PME method. A new lipid force field (FUJI) was developed on the basis of the AMBER force field scheme including the Lipid14 van der Waals parameters. Point charges were calculated by the restrained electrostatic potentials of many lipid conformers. The torsion energy profiles were calculated by high level ab initio molecular orbitals (LCCSD(T)/Aug-cc-pVTZ//LMP2/Aug-cc-pVTZ); then, the molecular mechanical dihedral parameters were derived by means of a fast Fourier transform. Incorporating these parameters into a new lipid force field without any fittings to experimental data, desirable lipid characteristics such as the area per lipid and lateral diffusion coefficients were obtained by GROMACS molecular dynamics simulations using the LJ-PME method and hydrogen virtual sites. The stability and structures of large membranes with undulatory fluctuations were studied by a multidrug efflux transporter (AcrABZ-TolC) with inner and outer membranes.

An Update on Recent Advances in Cubosome: A Novel Drug Delivery System

2021 ◽  
Vol 21 ◽  
Author(s):  
Madhukar Garg ◽  
Anju Goyal ◽  
Sapna Kumari
Keyword(s):  
Drug Delivery ◽  
Drug Delivery System ◽  
Lipid Bilayers ◽  
Delivery System ◽  
Liquid Crystalline ◽  
Three Dimensional ◽  
Biologically Active ◽  
Potential Applications ◽  
Health Related ◽  
Novel Drug

: Cubosomes are highly stable nanostructured liquid crystalline dosage delivery form derived from amphiphilic lipids and polymer-based stabilizers converting it in a form of effective biocompatible carrier for the drug delivery. The delivery form comprised of bicontinuous lipid bilayers arranged in three dimensional honeycombs like structure provided with two internal aqueous channels for incorporation of number of biologically active ingredients. In contrast liposomes they provide large surface area for incorporation of different types of ingredients. Due to the distinct advantages of biocompatibility and thermodynamic stability, cubosomes have remained the first preference as method of choice in the sustained release, controlled release and targeted release dosage forms as new drug delivery system for the better release of the drugs. As lot of advancement in the new form of dosage form has bring the novel avenues in drug delivery mechanisms so it was matter of worth to compile the latest updates on the various aspects of mentioned therapeutic delivery system including its structure, routes of applications along with the potential applications to encapsulate variety drugs to serve health related benefits.

scholarly journals Genome-Wide Metabolic Reconstruction of the Synthesis of Polyhydroxyalkanoates from Sugars and Fatty Acids by Burkholderia Sensu Lato Species

2021 ◽  
Vol 9 (6) ◽  
pp. 1290
Author(s):  
Natalia Alvarez-Santullano ◽  
Pamela Villegas ◽  
Mario Sepúlveda Mardones ◽  
Roberto E. Durán ◽  
Raúl Donoso ◽  
...  
Keyword(s):  
Fatty Acids ◽  
De Novo ◽  
Reducing Power ◽  
Pentose Phosphate ◽  
Fine Tuning ◽  
Metabolic Reconstruction ◽  
Phylogenetic Groups ◽  
Outlier Group ◽  
Pha Genes ◽  
High Level

Burkholderia sensu lato (s.l.) species have a versatile metabolism. The aims of this review are the genomic reconstruction of the metabolic pathways involved in the synthesis of polyhydroxyalkanoates (PHAs) by Burkholderia s.l. genera, and the characterization of the PHA synthases and the pha genes organization. The reports of the PHA synthesis from different substrates by Burkholderia s.l. strains were reviewed. Genome-guided metabolic reconstruction involving the conversion of sugars and fatty acids into PHAs by 37 Burkholderia s.l. species was performed. Sugars are metabolized via the Entner–Doudoroff (ED), pentose-phosphate (PP), and lower Embden–Meyerhoff–Parnas (EMP) pathways, which produce reducing power through NAD(P)H synthesis and PHA precursors. Fatty acid substrates are metabolized via β-oxidation and de novo synthesis of fatty acids into PHAs. The analysis of 194 Burkholderia s.l. genomes revealed that all strains have the phaC, phaA, and phaB genes for PHA synthesis, wherein the phaC gene is generally present in ≥2 copies. PHA synthases were classified into four phylogenetic groups belonging to class I II and III PHA synthases and one outlier group. The reconstruction of PHAs synthesis revealed a high level of gene redundancy probably reflecting complex regulatory layers that provide fine tuning according to diverse substrates and physiological conditions.

Semi-automated Optimization of the CHARMM36 Lipid Force Field to Include Explicit Treatment of Long-Range Dispersion

2021 ◽  
Vol 17 (3) ◽  
pp. 1562-1580 ◽  
Author(s):  
Yalun Yu ◽  
Andreas Krämer ◽  
Richard M. Venable ◽  
Andrew C. Simmonett ◽  
Alexander D. MacKerell ◽  
...  
Keyword(s):  
Force Field ◽  
Long Range ◽  
Automated Optimization

scholarly journals Train Fast While Reducing False Positives: Improving Animal Classification Performance Using Convolutional Neural Networks

Geomatics ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 34-49
Author(s):  
Mael Moreni ◽  
Jerome Theau ◽  
Samuel Foucher
Keyword(s):  
False Positive ◽  
Classification Performance ◽  
Large Datasets ◽  
False Positives ◽  
Fine Tuning ◽  
Training Time ◽  
In The Wild ◽  
Test Sets ◽  
High Level ◽  
Time Decrease

The combination of unmanned aerial vehicles (UAV) with deep learning models has the capacity to replace manned aircrafts for wildlife surveys. However, the scarcity of animals in the wild often leads to highly unbalanced, large datasets for which even a good detection method can return a large amount of false detections. Our objectives in this paper were to design a training method that would reduce training time, decrease the number of false positives and alleviate the fine-tuning effort of an image classifier in a context of animal surveys. We acquired two highly unbalanced datasets of deer images with a UAV and trained a Resnet-18 classifier using hard-negative mining and a series of recent techniques. Our method achieved sub-decimal false positive rates on two test sets (1 false positive per 19,162 and 213,312 negatives respectively), while training on small but relevant fractions of the data. The resulting training times were therefore significantly shorter than they would have been using the whole datasets. This high level of efficiency was achieved with little tuning effort and using simple techniques. We believe this parsimonious approach to dealing with highly unbalanced, large datasets could be particularly useful to projects with either limited resources or extremely large datasets.

scholarly journals Binary Superlattices from {Mo132} Polyoxometalates and Maghemite Nanocrystals: Long-Range Ordering and Fine-Tuning of Dipole Interactions

Small ◽  
2015 ◽  
Vol 12 (2) ◽  
pp. 220-228 ◽  
Author(s):  
Romain Breitwieser ◽  
Thomas Auvray ◽  
Florence Volatron ◽  
Caroline Salzemann ◽  
Anh-Tu Ngo ◽  
...  
Keyword(s):  
Long Range ◽  
Fine Tuning ◽  
Dipole Interactions ◽  
Long Range Ordering

scholarly journals Dynamic Interaction of Norfloxacin to Magnesium Monitored by Bacterial Outer Membrane Nanopores

2020 ◽  
Author(s):  
Jiajun Wang ◽  
Jigneshkumar Dahyabhai Prajapati ◽  
Ulrich Kleinekathöfer ◽  
Mathias Winterhalter
Keyword(s):  
Outer Membrane ◽  
Lipid Bilayers ◽  
Brownian Dynamics ◽  
Single Channel ◽  
Ion Selectivity ◽  
Computational Modelling ◽  
Free Energy Calculations ◽  
Divalent Ions ◽  
Dynamics Simulations ◽  
Brownian Dynamics Simulations

The effect of divalent ions on the permeability of norfloxacin across the major outer membrane channels from <i>E. coli</i> (OmpF, OmpC) and <i>E. aerogenes</i> (Omp35, Omp36) has been investigated at the single channel level. To understand the rate limiting steps in permeation, we reconstituted single porin into planar lipid bilayers and analyzed the ion current fluctuations caused in the presence of norfloxacin. To obtain an atomistic view, we complemented the experiments with millisecond-long free energy calculations based on temperature-accelerated Brownian dynamics simulations to identify the most probable permeation pathways of the antibiotics through the respective pore. Both, experimental analysis and computational modelling, suggest that norfloxacin is able to permeate through the larger porins, i.e., OmpF, OmpC, and Omp35, whereas it only binds to the slightly narrower porin Omp36. Moreover, divalent ions can bind to negatively charged residues inside the porin, reversing the ion selectivity of the pore. In addition, the divalent ions can chelate with the fluoroquinolones and alter their physicochemical properties. The results suggest that the conjugation must break with either one of them when the antibiotics molecules bypass the lumen of the porin, with the conjugation to the antibiotic being more stable than that to the pore. In general, the permeation or binding process of fluoroquinolone in porins occurs irrespective of the presence of divalent ions, but the presences of divalent ions can vary the kinetics significantly.

scholarly journals Contribution to image restoration using a neural network model

2002 ◽  
Vol Volume 1, 2002 ◽  
Author(s):  
Karim Achour ◽  
Nadia Zenati ◽  
Oualid Djekoune
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
Network Model ◽  
Neural Network Model ◽  
Hopfield Neural Network ◽  
Optimization Method ◽  
Nous Proposons ◽  
International Audience ◽  
High Level

International audience The reduction of the blur and the noise is an important task in image processing. Indeed, these two types of degradation are some undesirable components during some high level treatments. In this paper, we propose an optimization method based on neural network model for the regularized image restoration. We used in this application a modified Hopfield neural network. We propose two algorithms using the modified Hopfield neural network with two updating modes : the algorithm with a sequential updates and the algorithm with the n-simultaneous updates. The quality of the obtained result attests the efficiency of the proposed method when applied on several images degraded with blur and noise. La réduction du bruit et du flou est une tâche très importante en traitement d'images. En effet, ces deux types de dégradations sont des composantes indésirables lors des traitements de haut niveau. Dans cet article, nous proposons une méthode d'optimisation basée sur les réseaux de neurones pour résoudre le problème de restauration d'images floues-bruitées. Le réseau de neurones utilisé est le réseau de « Hopfield ». Nous proposons deux algorithmes utilisant deux modes de mise à jour: Un algorithme avec un mode de mise à jour séquentiel et un algorithme avec un mode de mise à jour n-simultanée. L'efficacité de la méthode mise en œuvre a été testée sur divers types d'images dégradées.

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