The combination of nanostructures with biomolecules leading to the generation of functional nanosystems holds great promise for biotechnological and biomedical applications. As a naturally occurring biomacromolecule, DNA exhibits excellent biocompatibility and programmability. Also, scalable synthesis can be readily realized through automated instruments. Such unique properties, together with Watson-Crick base-pairing interactions, make DNA a particularly promising candidate to be used as a building block material for a wide variety of nanostructures. In the past few decades, various DNA nanostructures have been developed, including one-, two- and three-dimensional nanomaterials. Aptamers are single-stranded DNA or RNA molecules selected by Systematic Evolution of Ligands by Exponential Enrichment (SELEX), with specific recognition abilities to their targets. Therefore, integrating aptamers into DNA nanostructures results in powerful tools for biosensing and bioimaging applications. Furthermore, owing to their high loading capability, aptamer-modified DNA nanostructures have also been altered to play the role of drug nanocarriers for in vivo applications and targeted cancer therapy. In this review, we summarize recent progress in the design of aptamers and related DNA molecule-integrated DNA nanostructures as well as their applications in biosensing, bioimaging and cancer therapy. To begin with, we first introduce the SELEX technology. Subsequently, the methodologies for the preparation of aptamer-integrated DNA nanostructures are presented. Then, we highlight their applications in biosensing and bioimaging for various targets, as well as targeted cancer therapy applications. Finally, we discuss several challenges and further opportunities in this emerging field.

Iron phthalocyanine (FePc) is a promising non-precious catalyst for the oxygen reduction reaction (ORR). Unfortunately, FePc with plane-symmetric FeN 4 site usually exhibits an unsatisfactory ORR activity due to its poor O 2 adsorption and activation. Here, we report an axial Fe-O coordination induced electronic localization strategy to improve its O 2 adsorption, activation and thus the ORR performance. Theoretical calculations indicate that the Fe-O coordination evokes the electronic localization among the axial direction of O-FeN 4 sites to enhance O 2 adsorption and activation. To realize this speculation, FePc is coordinated with an oxidized carbon. Synchrotron X-ray absorption and Mössbauer spectra validate Fe-O coordination between FePc and carbon. The obtained catalyst exhibits fast kinetics for O 2 adsorption and activation with an ultralow Tafel slope of 27.5 mV dec −1 and a remarkable half-wave potential of 0.90 V. This work offers a new strategy to regulate catalytic sites for better performance.

All data used in the manuscript are publicly available (see URLs). GTEx and GERA data can be accessed by application to dbGaP. CommonMind data are available through formal application to NIMH. ADGC phase 2 summary statistics used for validation are available through NIAGADS portal (see URLs) with accession number NG00076.

In this postgenomic era, the ability to identify protein-protein interactions on a genomic scale is very important to assist in the assignment of physiological function. Because of the increasing number of solved structures involving protein complexes, the time is ripe to extend threading to the prediction of quaternary structure. In this spirit, a multimeric threading approach has been developed. The approach is comprised of two phases. In the first phase, traditional threading on a single chain is applied to generate a set of potential structures for the query sequences. In particular, we use our recently developed threading algorithm, PROSPECTOR. Then, for those proteins whose template structures are part of a known complex, we rethread on both partners in the complex and now include a protein-protein interfacial energy. To perform this analysis, a database of multimeric protein structures has been constructed, the necessary interfacial pairwise potentials have been derived, and a set of empirical indicators to identify true multimers based on the threading Z-score and the magnitude of the interfacial energy have been established. The algorithm has been tested on a benchmark set comprised of 40 homodimers, 15 heterodimers, and 69 monomers that were scanned against a protein library of 2478 structures that comprise a representative set of structures in the Protein Data Bank. Of these, the method correctly recognized and assigned 36 homodimers, 15 heterodimers, and 65 monomers. This protocol was applied to identify partners and assign quaternary structures of proteins found in the yeast database of interacting proteins. Our multimeric threading algorithm correctly predicts 144 interacting proteins, compared to the 56 (26) cases assigned by PSI-BLAST using a (less) permissive E-value of 1 (0.01). Next, all possible pairs of yeast proteins have been examined. Predictions (n = 2865) of protein-protein interactions are made; 1138 of these 2865 interactions have counterparts in the Database of Interacting Proteins. In contrast, PSI-BLAST made 1781 predictions, and 1215 have counterparts in DIP. An estimation of the false-negative rate for yeast-predicted interactions has also been provided. Thus, a promising approach to help assist in the assignment of protein-protein interactions on a genomic scale has been developed.