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Register a new userVisualizing biomolecular electrostatics in virtual reality with UnityMol-APBS
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Virtual reality is a powerful tool with the ability to immerse a user within a completely external environment. This immersion is particularly useful when visualizing and analyzing interactions between small organic molecules, molecular inorganic complexes, and biomolecular systems such as redox proteins and enzymes. A common tool used in the biomedical community to analyze such interactions is the APBS software, which was developed to solve the equations of continuum electrostatics for large biomolecular assemblages. Numerous applications exist for using APBS in the biomedical community including analysis of protein ligand interactions and APBS has enjoyed widespread adoption throughout the biomedical community. Currently, typical use of the full APBS toolset is completed via the command line followed by visualization using a variety of two-dimensional external molecular visualization software. This process has inherent limitations: visualization of three-dimensional objects using a two-dimensional interface masks important information within the depth component. Herein, we have developed a single application, UnityMol-APBS, that provides a dual experience where users can utilize the full range of the APBS toolset, without the use of a command line interface, by use of a simple ac{GUI} for either a standard desktop or immersive virtual reality experience.
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The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining p$K_a$ values, and an improved web-based visualization tool for viewing electrostatics.
This document attempts to clarify potential confusion regarding electrostatics calculations, specifically in the context of biomolecular structure and specifically as regards the units typically used to contour/visualize isopotential surfaces, potentials mapped onto molecular solvent-accessible surfaces, etc.
Recent years have seen a resurgence of interest in using Virtual Reality (VR) technology to benefit instruction, especially in physics and related subjects. As VR devices improve and become more widely available, there remains a number of unanswered questions regarding the impact of VR on student learning and how best to use this technology in the classroom. On the topic of electrostatics, for example, a large, controlled, randomized study performed by Smith et al. 2017cite{smith17}, found that VR-based instruction had an overall negligible impact on student learning compared to videos or images. However, they did find a strong trend for students who reported frequent video game play to learn better from VR than other media. One possible interpretation of this result is that extended videogame play provides a kind of training that enables a student to learn more comfortably in the virtual environment. In the present work we consider if a VR training activity that is unrelated to electrostatics can help prepare students to learn electrostatics from subsequent VR instruction. We find that preliminary VR training leads to a small but statistically significant improvement in student performance on our electrostatics assessment. We also find that student reported game play is still correlated with higher scores on this metric.
Virtual reality (VR) has long promised to revolutionize education, but with little follow-through. Part of the reason for this is the prohibitive cost of immersive VR headsets or caves. This has changed with the advent of smartphone-based VR (along the lines of Google cardboard) which allows students to use smartphones and inexpensive plastic or cardboard viewers to enjoy stereoscopic VR simulations. We have completed the largest-ever such study on 627 students enrolled in calculus-based freshman physics at The Ohio State University. This initial study focused on student understanding of electric fields. Students were split into three treatments groups: VR, video, and static 2D images. Students were asked questions before, during, and after treatment. Here we present a preliminary analysis including overall post-pre improvement among the treatment groups, dependence of improvement on gender, and previous video game experience. Results on select questions are discussed. Several electric field visualizations similar to those used in this study are freely available on Google Play http://go.osu.edu/BuckeyeVR
Equilibrium sampling of biomolecules remains an unmet challenge after more than 30 years of atomistic simulation. Efforts to enhance sampling capability, which are reviewed here, range from the development of new algorithms to parallelization to novel uses of hardware. Special focus is placed on classifying algorithms -- most of which are underpinned by a few key ideas -- in order to understand their fundamental strengths and limitations. Although algorithms have proliferated, progress resulting from novel hardware use appears to be more clear-cut than from algorithms alone, partly due to the lack of widely used sampling measures.
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