Comparing position and force control for interactive molecular simulators with haptic feedback

Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers

For years, immersive interfaces using virtual and augmented reality (AR) for molecular visualization and modeling have promised a revolution in the way how we teach, learn, communicate and work in chemistry, structural biology and related areas. However, most tools available today for immersive modeling require specialized hardware and software, and are costly and cumbersome to set up. These limitations prevent wide use of immersive technologies in education and research centers in a standardized form, which in turn prevents large-scale testing of the actual effects of such technologies on learning and thinking processes. Here, I discuss building blocks for creating marker-based AR applications that run as web pages on regular computers, and explore how they can be exploited to develop web content for handling virtual molecular systems in commodity AR with no more than a webcam- and internet-enabled computer. Examples span from displaying molecules, electron microscopy maps and molecular orbitals with minimal amounts of HTML code, to incorporation of molecular mechanics, real-time estimation of experimental observables and other interactive resources using JavaScript. These web apps provide virtual alternatives to physical, plastic-made molecular modeling kits, where the computer augments the experience with information about spatial interactions, reactivity, energetics, etc. The ideas and prototypes introduced here should serve as starting points for building active content that everybody can utilize online at minimal cost, providing novel interactive pedagogic material in such an open way that it could enable mass-testing of the effect of immersive technologies on chemistry education.

Studying chemical reactivity in a virtual environment

Chemical reactivity of a set of reactants is determined by its potential (electronic) energy (hyper)surface. The high dimensionality of this surface renders it difficult to efficiently explore reactivity in a large reactive system. Exhaustive sampling techniques and search algorithms are not straightforward to employ as it is not clear which explored path will eventually produce the minimum energy path of a reaction passing through a transition structure. Here, the chemist's intuition would be of invaluable help, but it cannot be easily exploited because (1) no intuitive and direct tool for the scientist to manipulate molecular structures is currently available and because (2) quantum chemical calculations are inherently expensive in terms of computational effort. In this work, we elaborate on how the chemist can be reintroduced into the exploratory process within a virtual environment that provides immediate feedback and intuitive tools to manipulate a reactive system. We work out in detail how this immersion should take place. We provide an analysis of modern semi-empirical methods which already today are candidates for the interactive study of chemical reactivity. Implications of manual structure manipulations for their physical meaning and chemical relevance are carefully analysed in order to provide sound theoretical foundations for the interpretation of the interactive reactivity exploration.

Haptic-driven applications to molecular modeling: state-of-the-art and perspectives

Drug design is a creative process that combines different scientific expertise. With the development of increasingly powerful computers, disciplines such as molecular modeling and, in particular, drug design, are becoming an important component of drug discovery. However, modern software often limits the user interaction with the computer calculation, reducing the potential for researchers to use their knowledge in the design process. For this reason, interactive methodologies have been investigated in recent years. In particular, haptic-driven simulators offer the possibility for users to drive and control the modeling simulations, efficiently combining human knowledge and computational power. In this article, we will discuss the state-of-the-art and future perspectives of such methodologies.