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The COVID-19 pandemic has accelerated the shift from traditional in-person teaching to remote and online learning, necessitating a more adaptable educational platform to serve the diverse needs of students. Transforming hands-on “wet lab” activities into virtual “dry lab” exercises can promote a more accessible and flexible learning environment, offering innovative methods to improve online teaching outcomes, incorporate interactive components, and provide student support. Here we describe our effort of utilizing NUPACK, a free cloud-based web application, to develop new educational modules on nucleic acids for teaching biochemistry lectures and laboratories. These modules include fundamental topics such as melting temperature, hybridization equilibrium, free energy, secondary folding structures of nucleic acids, and the thermal stability of single-nucleotide polymorphisms. The NUPACK-based DNA computational lab not only provides a hands-on learning experience to enhance students’ understanding of nucleic acid structures, hybridizations, and characteristics but also facilitated the transition to remote learning during the pandemic. Furthermore, these computation-assisted DNA experiments have been extended to engage local high school students at Rutgers UniversityCamden. This article summarizes the curriculum development and guidelines for the DNA computational lab, aiming to benefit the education of nucleic acids in biochemistry for a wider audience of educators and learners. 

Abstract The field of nucleic acid self‐assembly has advanced significantly, enabling the creation of multi‐dimensional nanostructures with precise sizes and shapes. These nanostructures hold great potential for various applications, including biocatalysis, smart materials, molecular diagnosis, and therapeutics. Here, dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) are employed to investigate DNA origami nanostructures, focusing on size distribution and particle concentration. Compared to DLS, NTA provided higher resolution in size measurement with a smaller full‐width at half‐maximum (FWHM), making it particularly suitable for characterizing DNA nanostructure. To enhance sensitivity, a fluorescent NTA method is developed by incorporating an intercalation dye to amplify the fluorescence signals of DNA origami. This method is validated by analyzing various DNA origami structures, ranging from 1 and 2D flexible structures to 3D compact shapes, and evaluating structural assembly yields. Additionally, NTA is used to analyze dynamic DNA nanocages that undergo conformational switches among linear, square, and pyramid shapes in response to the addition of trigger strands. Quantitative size distribution data is crucial not only for production quality control but also for providing mechanistic insights into the various applications of DNA nanomaterials. 

Enzymes play key roles in the biological functions of living organisms, which serve as catalysts to and regulate biochemical reaction pathways. Recent studies suggest that peptides are promising molecules for modulating enzyme function due to their advantages in large chemical diversity and well-established methods for library synthesis. Experimental approaches to identify protein-binding peptides are time-consuming and costly. Hence, there is a demand to develop a fast and accurate computational approach to tackle this problem. Another challenge in developing a computational approach is the lack of a large and reliable dataset. In this study, we develop a new machine learning approach called PepBind-SVM to predict protein-binding peptides. To build this model, we extract different sequential and physicochemical features from peptides and use a Support Vector Machine (SVM) as the classification technique. We train this model on the dataset that we also introduce in this study. PepBind-SVM achieves 92.1% prediction accuracy, outperforming other classifiers at predicting protein-binding peptides. 

Nucleic acids self-assembly has rapidly advanced to produce multi-dimensional nanostructures with precise sizes and shapes. DNA nanostructures hold great potential for a wide range of applications, including biocatalysis, smart materials, molecular diagnosis, and therapeutics. Here, we present a study of using dynamic light scattering (DLS) and nanoparticles tracking analysis (NTA) to analyze DNA origami nanostructures for their size distribution and particles concentrations. Compared to DLS, NTA demonstrated higher resolution of size measurement with a smaller FWHM and was well suited for characterizing multimerization of DNA nanostructures. We future used intercalation dye to enhance the fluorescence signals of DNA origami to increase the detection sensitivity. By optimizing intercalation dyes and the dye-to-DNA origami ratio, fluorescent NTA was able to accurately quantify the concentration of dye-intercalated DNA nanostructures, closely matching with values obtained by UV absorbance at 260 nm. This optimized fluorescent NTA method offers an alternative approach for determining the concentration of DNA nanostructures based on their size distribution, in addition to commonly used UV absorbance quantification. This detailed information of size and concentration is not only crucial for production and quality control but could also provide mechanistic insights in various applications of DNA nanomaterials. 

In recent decades, nucleic acid self-assemblies have emerged as popular nanomaterials due to their programmable and robust assembly, prescribed geometry, and versatile functionality. However, it remains a challenge to purify large quantities of DNA nanostructures or DNA-templated nanocomplexes for various applications. Commonly used purification methods are either limited by a small scale or incompatible with functionalized structures. To address this unmet need, we present a robust and scalable method of purifying DNA nanostructures by Sepharose resin-based size exclusion. The resin column can be manually packed in-house with reusability. The separation is driven by a low-pressure gravity flow in which large DNA nanostructures are eluted first followed by smaller impurities of ssDNA and proteins. We demonstrated the efficiency of the method for purifying DNA origami assemblies and protein-immobilized DNA nanostructures. Compared to routine agarose gel electrophoresis that yields 1 μg or less of purified products, this method can purify ∼100–1000 μg of DNA nanostructures in less than 30 min, with the overall collection yield of 50–70% of crude preparation mixture. The purified nanocomplexes showed more precise activity in evaluating enzyme functions and antibody-triggered activation of complement protein reactions. 

Abstract Nucleic acid detection plays a crucial role in various applications, including disease diagnostics, research development, food safety, and environmental health monitoring. A rapid, point‐of‐care (POC) nucleic acid test can greatly benefit healthcare system by providing timely diagnosis for effective treatment and patient management, as well as supporting diseases surveillance for emerging pandemic diseases. Recent advancements in nucleic acids technology have led to rapid assays for single‐stranded nucleic acids that can be integrated into simple and miniaturized platforms for ease of use. In this review, the study focuses on the developments in isothermal amplification, nucleic acid hybridization circuits, various enzyme‐based signal reporting mechanisms, and detection platforms that show promise for POC testing. The study also evaluates critical technical breakthroughs to identify the advantages and disadvantages of these methods in various applications.