Peppy: A virtual reality environment for exploring the principles of polypeptide structure

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Mateverse, the Future Materials Science Computation Platform Based on Metaverse

Currently, computational materials science involves human-computer interaction through coding in software or neural networks. There is still no direct way for human intelligence endorsement. The digitalization of human intelligence should be the ultimate goal for many disciplines. In materials science, human intelligence is still irreplaceable from machine learning techniques, where humans can deal with complex correlations in the real world. We design the framework of Mateverse, a materials science computation platform based on Metaverse, which unifies human intelligence, experiment data, and theoretical simulations. In Mateverse, we intensively study the properties of H₂O, including the liquid and solid phases. We show that we can optimize a new water force field (which we name TIP4P-Meta) directly from the interactions between human and visible properties of H₂O. This force field is validated to be better than the conventional water model, and new ice polymorphs can be generated. We believe our platform can provide valuable hints in the paradigm upgrade in future computational materials science development.

The emerging potential of interactive virtual reality in drug discovery

INTRODUCTION

The potential of virtual reality (VR) to contribute to drug design and development has been recognized for many years. A recent advance is to use VR not only to visualize and interact with molecules, but also to interact with molecular dynamics simulations 'on the fly' (interactive molecular dynamics in VR, IMD-VR), which is useful for flexible docking and examining binding processes and conformational changes.

AREAS COVERED

The authors use the term 'interactive VR' to refer to software where interactivity is an inherent part of the user VR experience e.g. in making structural modifications or interacting with a physically rigorous molecular dynamics (MD) simulation, as opposed to using VR controllers to rotate and translate the molecule for enhanced visualization. Here, they describe these methods and their application to problems relevant to drug discovery, highlighting the possibilities that they offer in this arena.

EXPERT OPINION

The ease of viewing and manipulating molecular structures and dynamics, using accessible VR hardware, and the ability to modify structures on the fly (e.g. adding or deleting atoms) - and for groups of researchers to work together in the same virtual environment - makes modern interactive VR a valuable tool to add to the armory of drug design and development methods.

A Brave New World: Virtual Reality and Augmented Reality in Systems Biology

How we interact with computer graphics has not changed significantly from viewing 2D text and images on a flatscreen since their invention. Yet, recent advances in computing technology, internetworked devices and gaming are driving the design and development of new ideas in other modes of human-computer interfaces (HCIs). Virtual Reality (VR) technology uses computers and HCIs to create the feeling of immersion in a three-dimensional (3D) environment that contains interactive objects with a sense of spatial presence, where objects have a spatial location relative to, and independent of the users. While this virtual environment does not necessarily match the real world, by creating the illusion of reality, it helps users leverage the full range of human sensory capabilities. Similarly, Augmented Reality (AR), superimposes virtual images to the real world. Because humans learn the physical world through a gradual sensory familiarization, these immersive visualizations enable gaining familiarity with biological systems not realizable in the physical world (e.g., allosteric regulatory networks within a protein or biomolecular pathways inside a cell). As VR/AR interfaces are anticipated to be explosive in consumer markets, systems biologists will be more immersed into their world. Here we introduce a brief history of VR/AR, their current roles in systems biology, and advantages and disadvantages in augmenting user abilities. We next argue that in systems biology, VR/AR technologies will be most useful in visually exploring and communicating data; performing virtual experiments; and education/teaching. Finally, we discuss our perspective on future directions for VR/AR in systems biology.

Analyzing Sequence Data with Markov Chain Models in Scientific Experiments

Virtual reality-based instruction is becoming an important resource to improve learning outcomes and communicate hands-on skills in science laboratory courses. Our study attempts first to investigate whether a Markov chain model can predict the students’ performance in conducting an experiment and whether simulations improve learner achievement in handling lab equipment and conducting science experiments in physical labs. In the present study, three cohorts of graduate students are trained on a microscopy experiment using different teaching methodologies. The effectiveness of the teaching strategies is evaluated by observing the sequences of students’ actions, while engaging in the microscopy experiment in real-lab situations. The students’ ability in performing the science experiment is estimated by sequential analysis using a Markov chain model. According to the Markov chain analysis, the students who are trained via a virtual reality software exhibit a higher probability to perform the steps of the experiment without difficulty and without assistance than their fellow students who attend more traditional training scenarios. Our study indicates that a Markov chain model is a powerful tool that can lead to a dynamic evaluation of the students’ performance in science experiments by tracing the students’ knowledge states and by predicting their innate abilities.

Combining Virtual Reality Visualization with Ensemble Molecular Dynamics to Study Complex Protein Conformational Changes

Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics, and their biological function. Currently, it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome "collective variable" enhanced sampling protocols. Here, we describe a framework that combines ensemble MD simulations and virtual reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables a priori. We further show that eMD-VR generated pathways can be combined with Markov state models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts.

An immersive journey to the molecular structure of SARS-CoV-2: Virtual reality in COVID-19

The era of the explosion of immersive technologies has bumped head-on with the coronavirus disease 2019 (COVID-19) global pandemic caused by the severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2). The proper understanding of the three-dimensional structures that compose the virus, as well as of those involved in the infection process and in treatments, is expected to contribute to the advance of fundamental and applied research against this pandemic, including basic molecular biology studies and drug design. Virtual reality (VR) is a powerful technology to visualize the biomolecular structures that are currently being identified for SARS-CoV-2 infection, opening possibilities to significant advances in the understanding of the disease-associate mechanisms and thus to boost new therapies and treatments. The present availability of VR for a large variety of practical applications together with the increasingly easiness, quality and economic access of this technology is transforming the way we interact with digital information. Here, we review the software implementations currently available for VR visualization of SARS-CoV-2 molecular structures, covering a range of virtual environments: CAVEs, desktop software, and cell phone applications, all of them combined with head-mounted devices like cardboards, Oculus Rift or the HTC Vive. We aim to impulse and facilitate the use of these emerging technologies in research against COVID-19 trying to increase the knowledge and thus minimizing risks before placing huge amounts of money for the development of potential treatments.

Peppy: A virtual reality environment for exploring the principles of polypeptide structure

A key learning outcome for undergraduate biochemistry classes is a thorough understanding of the principles of protein structure. Traditional approaches to teaching this material, which include two-dimensional (2D) images on paper, physical molecular modeling kits, and projections of 3D structures into 2D, are unable to fully capture the dynamic 3D nature of proteins. We have built a virtual reality application, Peppy, aimed at facilitating teaching of the principles of protein secondary structure. Rather than attempt to model molecules with the same fidelity to the underlying physical chemistry as existing, research-oriented molecular modelling approaches, we took the more straightforward approach of harnessing the Unity video game physics engine. Indeed, the simplicity and limitations of our model are strengths in a teaching context, provoking questions and thus deeper understanding. Peppy allows exploration of the relative effects of hydrogen bonding (and electrostatic interactions more generally), backbone φ/ψ angles, basic chemical structure, and steric effects on a polypeptide structure in an accessible format that is novel, dynamic, and fun to use. Apart from describing the implementation and use of Peppy, we discuss the outcomes of deploying Peppy in undergraduate biochemistry courses.