Although nonflexible, scaled molecular models like Pauling-Corey's and its descendants have made significant contributions in structural biology research and pedagogy, recent technical advances in 3D printing and electronics make it possible to go one step further in designing physical models of biomacromolecules: to make them conformationally dynamic. We report here the design, construction, and validation of a flexible, scaled, physical model of the polypeptide chain, which accurately reproduces the bond rotational degrees of freedom in the peptide backbone. The coarsegrained backbone model consists of repeating amide and α-carbon units, connected by mechanical bonds (corresponding to φ and ψ) that include realistic barriers to rotation that closely approximate those found at the molecular scale. Longer-range hydrogen-bonding interactions are also incorporated, allowing the chain to readily fold into stable secondary structures. The model is easily constructed with readily obtainable parts and promises to be a tremendous educational aid to the intuitive understanding of chain folding as the basis for macromolecular structure. Furthermore, this physical model can serve as the basis for linking tangible biomacromolecular models directly to the vast array of existing computational tools to provide an enhanced and interactive humancomputer interface.protein folding | self-assembly | biomimetic modular robotics | rotational energy barrier | conformational isomerism U nderstanding protein folding pathways, predicting protein structure and the de novo designing of functional proteins have been a long-standing grand challenge in computational and structural biology. Although tremendous advances are being made (1), folded protein structures are very difficult to visualize in our mind due to their complexity and shear size. State-of-the-art computer visualization techniques are well developed and provide an array of powerful interactive tools for exploring the 3D structures of biomacromolecules (2-4). While increasingly complex molecules can be visualized with computers, the mode of user interaction has been mostly limited to the mouse and keyboard. Although the use of haptic devices is on the rise, there are only a few low-cost, specialized input devices particularly designed for interaction with biomacromolecules. Augmented-reality (AR) and immersive environments enhance user interaction experiences during the handling of existing visualization tools (2, 5, 6), but the physical models used in these environments are not flexible or precise enough to represent the conformational dynamism of polypeptides by themselves. There is a strong need for scaled, realistically foldable, but inexpensive, physical models to go hand-in-hand with the AR and other computer interfaces, while concomitantly taking better advantage of current computational capabilities.Physical molecular models of organic small molecules and biomacromolecules with atomic representations have been around for many decades (7-17). Although early pioneers like...

Many scientific journals have committed to advancing diversity, equity, and inclusion, but publish articles counter to this goal. We propose actions the scientific community should take to move research and the publication process toward more rigorous and socially-just standards.

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The problems of scheduling a single parallel job across a large-scale distributed system are well known and surprisingly difficult to solve. In addition, because of the issues involved in distributed submission, such as co-reserving resources, and managing accounts and certificates simultaneously on multiple machines, etc., the vast number of highperformance computing (HPC) application users have been happy to remain restricted to submitting jobs to single machines. Meanwhile, the need to simulate larger and more complex physical systems continues to grow, with a concomitant increase in the number of cores required to solve the resulting scientific problems. One might reduce the demand on load per machine, and eventually the wait-time in queue, by decomposing the problem to use two resources in such circumstances, even though there might be a reduction in the peak performance. This motivates a question. Can otherwise monolithic jobs running on single resources be distributed over more than one machine such that there is an overall reduction in the time-to-solution? In this paper, we briefly discuss the development and performance of a parallel molecular dynamics code and its generalization to work on multiple distributed machines (using MPICH-G2). We benchmark and validate the performance of our simulations over multiple input datasets of varying sizes. The primary aim of this work, however, is to show that the time-to-solution can be reduced by sacrificing some peak performance and distributing over multiple machines.

The discovery and management of energy resources, especially at locations in the Gulf