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DNA-stabilized silver nanoclusters (AgN-DNAs) have sequence-tuned compositions and fluorescence colors. High-throughput experiments together with supervised machine learning models have recently enabled design of DNA templates that select for AgN-DNA properties, including near-infrared (NIR) emission that holds promise for deep tissue bioimaging. However, these existing models do not enable simultaneous selection of multiple AgN-DNA properties, and require significant expert input for feature engineering and class definitions. This work presents a model for multiobjective, continuous-property design of AgN-DNAs with automatic feature extraction, based on variational autoencoders (VAEs). This model is generative, i.e., it learns both the forward mapping from DNA sequence to AgN-DNA properties and the inverse mapping from properties to sequence, and is trained on an experimental data set of DNA sequences paired with AgN-DNA fluorescence properties. Experimental testing shows that the model enables effective design of AgN-DNA emission, including bright NIR AgN-DNAs with 4-fold greater abundance compared to training data. In addition, Shapley analysis is employed to discern learned nucleobase patterns that correspond to fluorescence color and brightness. This generative model can be adapted for a range of biomolecular systems with sequence-dependent properties, enabling precise design of emerging biomolecular nanomaterials.

ConspectusDNA-stabilized silver nanoclusters (AgN-DNAs) are sequence-encoded fluorophores. Like other noble metal nanoclusters, the optical properties of AgN-DNAs are dictated by their atomically precise sizes and shapes. What makes AgN-DNAs unique is that nanocluster size and shape are controlled by nucleobase sequence of the templating DNA oligomer. By choice of DNA sequence, it is possible to synthesize a wide range of AgN-DNAs with diverse emission colors and other intriguing photophysical properties. AgN-DNAs hold significant potential as "programmable" emitters for biological imaging due to their combination of small molecular-like sizes, bright and sequence-tuned fluorescence, low toxicities, and cost-effective synthesis. In particular, the potential to extend AgN-DNAs into the second near-infrared region (NIR-II) is promising for deep tissue imaging, which is a major area of interest for advancing biomedical imaging. Achieving this goal requires a deep understanding of the structure-property relationships that govern AgN-DNAs in order to design AgN-DNA emitters with sizes and geometries that support NIR-II emission.In recent years, major advances have been made in understanding the structure and composition of AgN-DNAs, enabling new insights into the correlation of nanocluster structure and photophysical properties. These advances have hinged on combined innovations in mass characterization and crystallography of compositionally pure AgN-DNAs, together with combinatorial experiments and machine learning-guided design. A combined approach is essential due to the major challenge of growing suitable AgN-DNA crystals for diffraction and to the labor-intensive nature of preparing and solving the molecular formulas of atomically precise AgN-DNAs by mass spectrometry. These approaches alone are not feasibly scaled to explore the large sequence space of DNA oligomer templates for AgN-DNAs.This account describes recent fundamental advances in AgN-DNA science that have been enabled by high throughput synthesis and fluorimetry together with detailed analytical studies of purified AgN-DNAs. First, short introductions to nanocluster chemistry and AgN-DNA basics are presented. Then, we review recent large-scale studies that have screened thousands of DNA templates for AgN-DNAs, leading to discovery of distinct classes of these emitters with unique cluster core compositions and ligand chemistries. In particular, the discovery of a new class of chloride-stabilized AgN-DNAs enabled the first ab initio calculations of AgN-DNA electronic structure and present new approaches to stabilize these emitters in biologically relevant conditions. Near-infrared (NIR) emissive AgN-DNAs are also found to exhibit diverse structures and properties. Finally, we conclude by highlighting recent proof-of-principle demonstrations of NIR AgN-DNAs for targeted fluorescence imaging. Continued efforts may future push AgN-DNAs into the tissue transparency window for fluorescence imaging in the NIR-II tissue transparency window.

Silver cations can mediate base pairing of guanine (G) DNA oligomers, yielding linear parallel G-Ag+-G duplexes with enhanced stabilities compared to those of canonical DNA duplexes. To enable their use in programmable DNA nanotechnologies, it is critical to understand solution-state formation and the nanomechanical stiffness of G-Ag+-G duplexes. Using temperature-controlled circular dichroism (CD) spectroscopy, we find that heating mixtures of G oligomers and silver salt above 50 °C fully destabilizes G-quadruplex structures and converts oligomers to G-Ag+-G duplexes. Electrospray ionization mass spectrometry supports that G-Ag+-G duplexes form at stoichiometries of 1 Ag+ per base pair, and CD spectroscopy suggests that as the Ag+/base stoichiometry increases further, G-Ag+-G duplexes undergo additional morphological changes. Using liquid-phase atomic force microscopy, we find that this excess Ag+ enables assembly of long fiberlike structures with ∼2.5 nm heights equivalent to a single DNA duplex but with lengths that far exceed a single duplex. Finally, using the conditions established to form single G-Ag+-G duplexes, we use a surface forces apparatus (SFA) to compare the solution-phase stiffness of single G-Ag+-G duplexes with dG-dC Watson-Crick-Franklin duplexes. SFA shows that G-Ag+-G duplexes are 1.3 times stiffer than dG-dC duplexes, confirming gas-phase ion mobility spectrometry measurements and computational predictions. These findings may guide the development of structural DNA nanotechnologies that rely on silver-mediated base pairing.

Sequence-encoded biomolecules such as DNA and peptides are powerful programmable building blocks for nanomaterials. This paradigm is enabled by decades of prior research into how nucleic acid and amino acid sequences dictate biomolecular interactions. The properties of biomolecular materials can be significantly expanded with non-natural interactions, including metal ion coordination of nucleic acids and amino acids. However, these approaches present design challenges because it is often not well-understood how biomolecular sequence dictates such non-natural interactions. This Feature Article presents a case study in overcoming challenges in biomolecular materials with emerging approaches in data mining and machine learning for chemical design. We review progress in this area for a specific class of DNA-templated metal nanomaterials with complex sequence-to-property relationships: DNA-stabilized silver nanoclusters (AgN-DNAs) with bright, sequence-tuned fluorescence colors and promise for biophotonics applications. A brief overview of machine learning concepts is presented, and high-throughput experimental synthesis and characterization of AgN-DNAs are discussed. Then, recent progress in machine learning-guided design of DNA sequences that select for specific AgN-DNA fluorescence properties is reviewed. We conclude with emerging opportunities in machine learning-guided design and discovery of AgN-DNAs and other sequence-encoded biomolecular nanomaterials.

DNA-stabilized silver nanoclusters (AgN-DNAs) are known to have one or two DNA oligomer ligands per nanocluster. Here, we present the first evidence that AgN-DNA species can possess additional chloride ligands that lead to increased stability in biologically relevant concentrations of chloride. Mass spectrometry of five chromatographically isolated near-infrared (NIR)-emissive AgN-DNA species with previously reported X-ray crystal structures determines their molecular formulas to be (DNA)2[Ag16Cl2]8+. Chloride ligands can be exchanged for bromides, which red-shift the optical spectra of these emitters. Density functional theory (DFT) calculations of the 6-electron nanocluster show that the two newly identified chloride ligands were previously assigned as low-occupancy silvers by X-ray crystallography. DFT also confirms the stability of chloride in the crystallographic structure, yields qualitative agreement between computed and measured UV-vis absorption spectra, and provides interpretation of the 35Cl-nuclear magnetic resonance spectrum of (DNA)2[Ag16Cl2]8+. A reanalysis of the X-ray crystal structure confirms that the two previously assigned low-occupancy silvers are, in fact, chlorides, yielding (DNA)2[Ag16Cl2]8+. Using the unusual stability of (DNA)2[Ag16Cl2]8+ in biologically relevant saline solutions as a possible indicator of other chloride-containing AgN-DNAs, we identified an additional AgN-DNA with a chloride ligand by high-throughput screening. Inclusion of chlorides on AgN-DNAs presents a promising new route to expand the diversity of AgN-DNA structure-property relationships and to imbue these emitters with favorable stability for biophotonics applications.

DNA can stabilize silver nanoclusters (AgN-DNAs) whose atomic sizes and diverse fluorescence colors are selected by nucleobase sequence. These programmable nanoclusters hold promise for sensing, bioimaging, and nanophononics. However, DNA's vast sequence space challenges the design and discovery of AgN-DNAs with tailored properties. In particular, AgN-DNAs with bright near-infrared luminescence above 800 nm remain rare, placing limits on their applications for bioimaging in the tissue transparency windows. Here, we present a design method for near-infrared emissive AgN-DNAs. By combining high-throughput experimentation and machine learning with fundamental information from AgN-DNA crystal structures, we distill the salient DNA sequence features that determine AgN-DNA color, for the entire known spectral range of these nanoclusters. A succinct set of nucleobase staple features are predictive of AgN-DNA color. By representing DNA sequences in terms of these motifs, our machine learning models increase the design success for near-infrared emissive AgN-DNAs by 12.3 times as compared to training data, nearly doubling the number of known AgN-DNAs with bright near-infrared luminescence above 800 nm. These results demonstrate how incorporating known structure-property relationships into machine learning models can enhance materials study and design, even for sparse and imbalanced training data.

DNA oligomers are known to serve as stabilizing ligands for silver nanoclusters (AgN-DNAs) with rod-like nanocluster geometries and nanosecond-lived fluorescence. Here, we report two AgN-DNAs that possess distinctly different structural properties and are the first to exhibit only microsecond-lived luminescence. These emitters are characterized by significant broadband downconversion from the ultraviolet/visible to the near-infrared region. Circular dichroism spectroscopy shows that the structures of these two AgN-DNAs differ significantly from previously reported AgN-DNAs. We find that these nanoclusters contain eight valence electrons, making them the first reported DNA-stabilized luminescent quasi-spherical superatoms. This work demonstrates the important role that nanocluster composition and geometry play in dictating luminescence properties of AgN-DNAs and significantly expands the space of structure-property relations that can be achieved for AgN-DNAs.

DNA serves as a versatile template for few-atom silver clusters and their organized self-assembly. These clusters possess unique structural and photophysical properties that are programmed into the DNA template sequence, resulting in a rich palette of fluorophores which hold promise as chemical and biomolecular sensors, biolabels, and nanophotonic elements. Here, we review recent advances in the fundamental understanding of DNA-templated silver clusters (Ag N -DNAs), including the role played by the silver-mediated DNA complexes which are synthetic precursors to Ag N -DNAs, structure-property relations of Ag N -DNAs, and the excited state dynamics leading to fluorescence in these clusters. We also summarize the current understanding of how DNA sequence selects the properties of Ag N -DNAs and how sequence can be harnessed for informed design and for ordered multi-cluster assembly. To catalyze future research, we end with a discussion of several opportunities and challenges, both fundamental and applied, for the Ag N -DNA research community. A comprehensive fundamental understanding of this class of metal cluster fluorophores can provide the basis for rational design and for advancement of their applications in fluorescence-based sensing, biosciences, nanophotonics, and catalysis.

DNA-stabilized silver clusters (AgN-DNAs) exhibit diverse sequence-programmed fluorescence, making these tunable nanoclusters promising sensors and bioimaging probes. Recent advances in the understanding of AgN-DNA structures and optical properties have largely relied on detailed characterization of single species isolated by chromatography. Because most AgN-DNAs are unstable under chromatography, such studies do not fully capture the diversity of these clusters. As an alternative method, we use high-throughput synthesis and spectroscopy to measure steady state Stokes shifts of hundreds of AgN-DNAs. Steady state Stokes shift is of interest because its magnitude is determined by energy relaxation processes which may be sensitive to specific cluster geometry, attachment to the DNA template, and structural engagement of solvent molecules. We identify 305 AgN-DNA samples with single-peaked emission and excitation spectra, a characteristic of pure solutions and single emitters, which thus likely contain a dominant emissive AgN-DNA species. Steady state Stokes shifts of these samples vary widely, are in agreement with values reported for purified clusters, and are several times larger than for typical organic dyes. We then examine how DNA sequence selects AgN-DNA excitation energies and Stokes shifts, comment on possible mechanisms for energy relaxation processes in AgN-DNAs, and discuss how differences in AgN-DNA structure and DNA conformation may result in the wide distribution of optical properties observed here. These results may aid computational studies seeking to understand the fluorescence process in AgN-DNAs and the relations of this process to AgN-DNA structure.

Polystyrene-b-polyethylene glycol (PS-b-PEG) amphiphilic block copolymers featuring a terminal tridentate N,N,N-ligand (terpyridine) were synthesized for the first time through an efficient route. In this approach, telechelic chain-end modified polystyrenes were produced via reversible addition-fragmentation chain-transfer (RAFT) polymerization by using terpyridine trithiocarbonate as the chain-transfer agent, after which the hydrophilic polyethylene glycol (PEG) block was incorporated into the hydrophobic polystyrene (PS) block in high yields via a thiol-ene process. Following metal-coordination with Mn2+, Fe2+, Ni2+, and Zn2+, the resulting metallo-polymers were self-assembled into spherical, vesicular nanostructures, as characterized by dynamic light scattering and transmission electron microscopy (TEM) imaging.

DNA-protected silver clusters (AgN-DNA) possess unique fluorescence properties that depend on the specific DNA template that stabilizes the cluster. They exhibit peak emission wavelengths that range across the visible and near-IR spectrum. This wide color palette, combined with low toxicity, high fluorescence quantum yields of some clusters, low synthesis costs, small cluster sizes and compatibility with DNA are enabling many applications that employ AgN-DNA. Here we review what is known about the underlying composition and structure of AgN-DNA, and how these relate to the optical properties of these fascinating, hybrid biomolecule-metal cluster nanomaterials. We place AgN-DNA in the general context of ligand-stabilized metal clusters and compare their properties to those of other noble metal clusters stabilized by small molecule ligands. The methods used to isolate pure AgN-DNA for analysis of composition and for studies of solution and single-emitter optical properties are discussed. We give a brief overview of structurally sensitive chiroptical studies, both theoretical and experimental, and review experiments on bringing silver clusters of distinct size and color into nanoscale DNA assemblies. Progress towards using DNA scaffolds to assemble multi-cluster arrays is also reviewed.

DNA-stabilized silver clusters are remarkable for the selection of fluorescence color by the sequence of the stabilizing DNA oligomer. Yet despite a growing number of applications that exploit this property, no large-scale studies have probed origins of cluster color or whether certain colors occur more frequently than others. Here we employ a set of 684 randomly chosen 10-base oligomers to address these questions. Rather than a flat distribution, we find that specific color bands dominate. Cluster size data indicate that these "magic colors" originate from the existence of magic numbers for DNA-stabilized silver clusters, which differ from those of spheroidal gold clusters stabilized by small-molecule ligands. Elongated cluster structures, enforced by multiple base ligands along the DNA, can account for both magic number sizes and color variation around peak wavelength populations.

We present chemical synthesis strategies for DNA-stabilized silver nanoclusters (AgN-DNAs) with near-infrared (NIR) emission in the biological tissue transparency windows. Elevated temperatures can significantly increase chemical yield of near-infrared nanoclusters. In most cases, basic pH favors near-infrared nanoclusters while micromolar amounts of NaCl inhibit their formation. [ABSTRACT FROM AUTHOR]

DNA-stabilized silver nanoclusters (Ag N -DNAs) are emitters with tuneable structures and photophysical properties. While understanding of the sequence-structure-property relationships of Ag N -DNAs has advanced significantly, their chemical transformations and degradation pathways are far less understood. To advance understanding of these pathways, we analysed the fragmentation products of 21 different red and NIR Ag N -DNAs using negative ion mode electrospray ionization mass spectrometry (ESI-MS). Ag N -DNAs were found to lose Ag + under ESI-MS conditions, and sufficient loss of silver atoms can lead to a transition to a lesser number of effective valence electrons, N 0 . Of more than 400 mass spectral peaks analysed, only even values of N 0 were identified, suggesting that solution-phase Ag N -DNAs with odd values of N 0 are unlikely to be stable. Ag N -DNAs stabilized by three DNA strands were found to fragment significantly more than Ag N -DNAs stabilized by two DNA strands. Moreover, the fragmentation behaviour depends strongly on the DNA template sequence, with diverse fragmentation patterns even for Ag N -DNAs with similar molecular formulae. Molecular dynamics simulations, with forces calculated from density functional theory, of the fragmentation of (DNA) 2 (Ag 16 Cl 2 ) 8+ with a known crystal structure show that the 6-electron Ag 16 Cl 2 core fragments into a 4-electron Ag 10 and a 2-electron Ag 6 , preserving electron-pairing rules even at early stages of the fragmentation process, in agreement with experimental observation. These findings provide new insights into the mechanisms by which Ag N -DNAs degrade and transform, with relevance for their applications in sensing and biomedical applications.

DNA-stabilized silver nanoclusters (Ag N -DNAs) have sequence-tuned compositions and fluorescence colors. High-throughput experiments together with supervised machine learning models have recently enabled design of DNA templates that select for Ag N -DNA properties, including near-infrared (NIR) emission that holds promise for deep tissue bioimaging. However, these existing models do not enable simultaneous selection of multiple Ag N -DNA properties, and require significant expert input for feature engineering and class definitions. This work presents a model for multiobjective, continuous-property design of Ag N -DNAs with automatic feature extraction, based on variational autoencoders (VAEs). This model is generative, i.e., it learns both the forward mapping from DNA sequence to Ag N -DNA properties and the inverse mapping from properties to sequence, and is trained on an experimental data set of DNA sequences paired with Ag N -DNA fluorescence properties. Experimental testing shows that the model enables effective design of Ag N -DNA emission, including bright NIR Ag N -DNAs with 4-fold greater abundance compared to training data. In addition, Shapley analysis is employed to discern learned nucleobase patterns that correspond to fluorescence color and brightness. This generative model can be adapted for a range of biomolecular systems with sequence-dependent properties, enabling precise design of emerging biomolecular nanomaterials.

ConspectusDNA-stabilized silver nanoclusters (Ag N -DNAs) are sequence-encoded fluorophores. Like other noble metal nanoclusters, the optical properties of Ag N -DNAs are dictated by their atomically precise sizes and shapes. What makes Ag N -DNAs unique is that nanocluster size and shape are controlled by nucleobase sequence of the templating DNA oligomer. By choice of DNA sequence, it is possible to synthesize a wide range of Ag N -DNAs with diverse emission colors and other intriguing photophysical properties. Ag N -DNAs hold significant potential as "programmable" emitters for biological imaging due to their combination of small molecular-like sizes, bright and sequence-tuned fluorescence, low toxicities, and cost-effective synthesis. In particular, the potential to extend Ag N -DNAs into the second near-infrared region (NIR-II) is promising for deep tissue imaging, which is a major area of interest for advancing biomedical imaging. Achieving this goal requires a deep understanding of the structure-property relationships that govern Ag N -DNAs in order to design Ag N -DNA emitters with sizes and geometries that support NIR-II emission.In recent years, major advances have been made in understanding the structure and composition of Ag N -DNAs, enabling new insights into the correlation of nanocluster structure and photophysical properties. These advances have hinged on combined innovations in mass characterization and crystallography of compositionally pure Ag N -DNAs, together with combinatorial experiments and machine learning-guided design. A combined approach is essential due to the major challenge of growing suitable Ag N -DNA crystals for diffraction and to the labor-intensive nature of preparing and solving the molecular formulas of atomically precise Ag N -DNAs by mass spectrometry. These approaches alone are not feasibly scaled to explore the large sequence space of DNA oligomer templates for Ag N -DNAs.This account describes recent fundamental advances in Ag N -DNA science that have been enabled by high throughput synthesis and fluorimetry together with detailed analytical studies of purified Ag N -DNAs. First, short introductions to nanocluster chemistry and Ag N -DNA basics are presented. Then, we review recent large-scale studies that have screened thousands of DNA templates for Ag N -DNAs, leading to discovery of distinct classes of these emitters with unique cluster core compositions and ligand chemistries. In particular, the discovery of a new class of chloride-stabilized Ag N -DNAs enabled the first ab initio calculations of Ag N -DNA electronic structure and present new approaches to stabilize these emitters in biologically relevant conditions. Near-infrared (NIR) emissive Ag N -DNAs are also found to exhibit diverse structures and properties. Finally, we conclude by highlighting recent proof-of-principle demonstrations of NIR Ag N -DNAs for targeted fluorescence imaging. Continued efforts may future push Ag N -DNAs into the tissue transparency window for fluorescence imaging in the NIR-II tissue transparency window.