PySAGES: flexible, advanced sampling methods accelerated with GPUs

Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system's configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this new tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes

SSAGES : Software Suite for Advanced General Ensemble Simulations

Molecular simulation has emerged as an essential tool for modern-day research, but obtaining proper results and making reliable conclusions from simulations requires adequate sampling of the system under consideration. To this end, a variety of methods exist in the literature that can enhance sampling considerably, and increasingly sophisticated, effective algorithms continue to be developed at a rapid pace. Implementation of these techniques, however, can be challenging for experts and non-experts alike. There is a clear need for software that provides rapid, reliable, and easy access to a wide range of advanced sampling methods and that facilitates implementation of new techniques as they emerge. Here we present SSAGES, a publicly available Software Suite for Advanced General Ensemble Simulations designed to interface with multiple widely used molecular dynamics simulations packages. SSAGES allows facile application of a variety of enhanced sampling techniques—including adaptive biasing force, string methods, and forward flux sampling—that extract meaningful free energy and transition path data from all-atom and coarse-grained simulations. A noteworthy feature of SSAGES is a user-friendly framework that facilitates further development and implementation of new methods and collective variables. In this work, the use of SSAGES is illustrated in the context of simple representative applications involving distinct methods and different collective variables that are available in the current release of the suite. The code may be found at: https://github.com/MICCoM/SSAGES-public

Ebola virus epidemiology, transmission, and evolution during seven months in Sierra Leone

The 2013-2015 Ebola virus disease (EVD) epidemic is caused by the Makona variant of Ebola virus (EBOV). Early in the epidemic, genome sequencing provided insights into virus evolution and transmission and offered important information for outbreak response. Here, we analyze sequences from 232 patients sampled over 7 months in Sierra Leone, along with 86 previously released genomes from earlier in the epidemic. We confirm sustained human-to-human transmission within Sierra Leone and find no evidence for import or export of EBOV across national borders after its initial introduction. Using high-depth replicate sequencing, we observe both host-to-host transmission and recurrent emergence of intrahost genetic variants. We trace the increasing impact of purifying selection in suppressing the accumulation of nonsynonymous mutations over time. Finally, we note changes in the mucin-like domain of EBOV glycoprotein that merit further investigation. These findings clarify the movement of EBOV within the region and describe viral evolution during prolonged human-to-human transmission

Virus genomes reveal factors that spread and sustained the Ebola epidemic.

The 2013-2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic 'gravity' model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics

Dynamics and assembly of colloidal particles

In this dissertation, I present research into the dynamics and assembly of colloidal particles. This involves investigations into single particle dynamics, collective dynamics of assembled clusters, and thermodynamic studies of colloidal superstructure formation. To do this, I have utilized a combination of many simulation and theoretical techniques. Chapter 2 presents a study I have done of the methods in which to implement hydrodynamics into a mesoscopic coarse-grained solvent model (Multiparticle Collision Dynamics). This is done in order that colloidal particles may be studied with hydrodynamics (as is presented in Chapters 4 and 8) in the proper limits. Chapter 3 presents some general considerations for the study of kinetically arrested colloidal gels, which are studied in more detail in Chapters 4 and 5 through molecular dynamics simulations. Chapter 4 considers the structures formed by colloidal particles interacting attractively interact in solvent, while Chapter 5 examines sediment structures formed by attractive particles and their clusters. In Chapter 6, I examine how the presence of patches on the surface of colloidal particles can influence their assembly into superstructures, and the interesting dynamics that can develop in dense systems of such particles, as well as the thermodynamics of specific structure assembly. Further, in Chapter 7, I explain how prototypical two-faced Janus colloids form into elongated helical structures (which are not global free-energy minima) through kinetic pathway selection. Finally, in Chapter 8, I examine how hydrodynamics influences the dynamics of a Janus particle having stick–slip boundary conditions, and examine how this might influence the conformations of clusters, presenting a way to utilize hydrodynamic flows in order to control particle orientations in suspension processing and the manufacture of composite materials

Correction: Quevillon, M.J., et al. Charge Transport and Phase Behavior of Imidazolium-Based Ionic Liquid Crystals from Fully Atomistic Simulations. Materials 2018, 11, 64

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