Strategies for Computational Protein Design with Application to the Development of a Biomolecular Tool-kit for Single Molecule Protein Sequencing

One of the key properties of proteins is that they exhibit remarkable affinities and specificities for small-molecule and peptide binding partners. To improve the success rate of rational, computational protein design and widen the scope of potential applications, it is useful to define generalized strategies and automated methodology to improve and/or alter the affinity and specificity of interactions. I have implemented several strategies for engineering protein-small molecule interactions including: improvement of substrate accessibility, stabilization of the bound state, truncation and surface engineering, and transplantation of residue level, native (or native-like) interactions. Each strategy was applied to one or more model protein, and the resulting changes in affinity, specificity, and activity were characterized experimentally. Finally, we designed a biomolecular tool-kit, consisting of 17 engineered proteins for amino acid side-chain recognition and a single enzyme to catalyze the Edman degradation. We profiled the affinity and specificity of each protein, and implemented a computational framework that demonstrates its utility for amino acid calling in a single molecule protein sequencing assay

Serverification of Molecular Modeling Applications: the Rosetta Online Server that Includes Everyone (ROSIE)

The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code's difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step 'serverification' protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org

Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.

From Europe PMC via Jisc Publications RouterHistory: epub 2022-08-15, ppub 2022-10-01Publication status: PublishedFunder: UK Research and Innovation; Grant(s): ST/V006126/1, EP/V054236/1, EP/V033670/1We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs-a series of ideas, approaches and methods taken from existing visualization research and practice-deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond. See https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'

Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations

From The Royal Society via Jisc Publications RouterHistory: received 2021-10-14, accepted 2022-03-18, pub-electronic 2022-08-15, pub-print 2022-10-03Article version: VoRPublication status: PublishedFunder: UK Research and Innovation; Id: http://dx.doi.org/10.13039/100014013; Grant(s): EP/V033670/1, EP/V054236/1, ST/V006126/1We report on an ongoing collaboration between epidemiological modellers and visualization researchers by documenting and reflecting upon knowledge constructs—a series of ideas, approaches and methods taken from existing visualization research and practice—deployed and developed to support modelling of the COVID-19 pandemic. Structured independent commentary on these efforts is synthesized through iterative reflection to develop: evidence of the effectiveness and value of visualization in this context; open problems upon which the research communities may focus; guidance for future activity of this type and recommendations to safeguard the achievements and promote, advance, secure and prepare for future collaborations of this kind. In describing and comparing a series of related projects that were undertaken in unprecedented conditions, our hope is that this unique report, and its rich interactive supplementary materials, will guide the scientific community in embracing visualization in its observation, analysis and modelling of data as well as in disseminating findings. Equally we hope to encourage the visualization community to engage with impactful science in addressing its emerging data challenges. If we are successful, this showcase of activity may stimulate mutually beneficial engagement between communities with complementary expertise to address problems of significance in epidemiology and beyond. See https://ramp-vis.github.io/RAMPVIS-PhilTransA-Supplement/. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’

Crowdsourcing for information visualization: promises and pitfalls

Crowdsourcing offers great potential to overcome the limitations of controlled lab studies. To guide future designs of crowdsourcing-based studies for visualization, we review visualization research that has attempted to leverage crowdsourcing for empirical evaluations of visualizations. We discuss six core aspects for successful employment of crowdsourcing in empirical studies for visualization - participants, study design, study procedure, data, tasks, and metrics & measures. We then present four case studies, discussing potential mechanisms to overcome common pitfalls. This chapter will help the visualization community understand how to effectively and efficiently take advantage of the exciting potential crowdsourcing has to offer to support empirical visualization research

A high-performance gradient insert for rapid and short-T2 imaging at full duty cycle

Purpose The goal of this study was to devise a gradient system for MRI in humans that reconciles cutting‐edge gradient strength with rapid switching and brings up the duty cycle to 100% at full continuous amplitude. Aiming to advance neuroimaging and short‐T2 techniques, the hardware design focused on the head and the extremities as target anatomies. Methods A boundary element method with minimization of power dissipation and stored magnetic energy was used to design anatomy‐targeted gradient coils with maximally relaxed geometry constraints. The design relies on hollow conductors for high‐performance cooling and split coils to enable dual‐mode gradient amplifier operation. With this approach, strength and slew rate specifications of either 100 mT/m with 1200 mT/m/ms or 200 mT/m with 600 mT/m/ms were reached at 100% duty cycle, assuming a standard gradient amplifier and cooling unit. Results After manufacturing, the specified values for maximum gradient strength, maximum switching rate, and field geometry were verified experimentally. In temperature measurements, maximum local values of 63°C were observed, confirming that the device can be operated continuously at full amplitude. Testing for peripheral nerve stimulation showed nearly unrestricted applicability in humans at full gradient performance. In measurements of acoustic noise, a maximum average sound pressure level of 132 dB(A) was determined. In vivo capability was demonstrated by head and knee imaging. Full gradient performance was employed with echo planar and zero echo time readouts. Conclusion Combining extreme gradient strength and switching speed without duty cycle limitations, the described system offers unprecedented options for rapid and short‐T2 imaging. Magn Reson Med 79:3256–3266, 2018. © 2017 International Society for Magnetic Resonance in Medicine

Files required for app implementation and their role.

<p>Files required for app implementation and their role.</p

Schematic of ROSIE (Rosetta Online Server that Includes Everyone), which permits a number of front-ends for job submission by users, a number of servers (stored in a unified database), and a number of backends to allow expansion of computational resources.

<p>Schematic of ROSIE (Rosetta Online Server that Includes Everyone), which permits a number of front-ends for job submission by users, a number of servers (stored in a unified database), and a number of backends to allow expansion of computational resources.</p