From sequence to function: Bridging single-molecule kinetics and molecular diversity.

Biological function is fundamentally determined by nucleic acid and protein sequence. Beyond encoding genetic information, nucleic acids also display complex physicochemical parameters that shape structure, dynamics, and interactions. Understanding how sequence variation sculpts the energetic landscapes underlying these properties requires methods that capture both molecular diversity and dynamic behavior. Single-molecule techniques are ideally suited to this task, but conventional formats remain time and cost intensive. Recent breakthroughs have enabled highly multiplexed approaches for observing molecular dynamics across millions of individual molecules representing thousands of sequences or barcoded entities. Though still in development, these methods have begun to bridge sequence, structure, dynamics, and function at scale, opening new opportunities in drug discovery, molecular diagnostics, and functional genomics. Editor's summary: How DNA and RNA molecules fold, move, and interact is controlled by their sequence in complex ways that remain obscure. Existing methods can either determine sequences or measure single-molecule dynamics, but they typically do not connect both types of information for large numbers of distinct sequences at once. Kapanidis et al. reviewed new approaches that track the real-time dynamics of hundreds of thousands of individual molecules and then read out the exact sequence of each one. By linking sequence to kinetic "behavior profiles," these methods open new routes to understanding mutations, drug action, and molecular mechanisms. —Di Jiang BACKGROUND: Biomolecules derive their function from sequence. Small changes in DNA, RNA, or protein sequence can shift structure, mechanics, and reaction pathways. These effects shape folding, binding equilibria, and the mechanochemical cycles of molecular machines. Ensemble assays have mapped many sequence-function relationships, but population averaging obscures transient intermediates, rare states, alternative pathways, and static heterogeneity. Single-molecule methods overcome this limitation. Techniques such as single-molecule fluorescence resonance energy transfer (smFRET), colocalization imaging, optical and magnetic tweezers, and nanopore-based force spectroscopy reveal real-time transitions between structural states that bulk measurements hide. Yet typical single-molecule experiments are slow and low throughput, typically probing one construct at a time. This bottleneck has limited our ability to explore large sequence spaces and to connect specific sequences to detailed kinetics. ADVANCES: New multiplexed single-molecule strategies now address this gap. Recent work links the functional "phenotype" of an individual molecule to its precise sequence across thousands of variants in one experiment. Two general approaches have emerged: MUSCLE (multiplexed single-molecule characterization at the library scale) and SPARXS (single-molecule parallel analysis for rapid exploration of sequence space) couple TIRF (total internal reflection fluorescence)–based fluorescence trajectories with in situ Illumina sequencing, generating millions of spatially registered traces tied directly to a known variant. SPIN-seq (single-molecule phenotyping and in situ sequencing) uses single-molecule sequencing-by-hybridization on surface-immobilized DNA to identify each sequence variant after kinetic imaging on the same TIRF microscope. These methods now enable sequence-resolved measurements of conformational dynamics, kinetic landscapes, reaction pathways, and static heterogeneity at scale. This capability has already revealed how sequence tunes Holliday junction isomerization, DNA hairpin breathing, and Cas9-induced target unwinding and rewinding. It complements earlier single-molecule work showing that the stepping behavior of polymerases, helicases, polymerases, and ribosomes is dictated by local, sequence-dependent energy barriers. Multiplexing now generalizes such analyses to full libraries measured under identical conditions. Technical challenges remain: Field-of-view limitations, photobleaching, and incomplete cluster formation reduce throughput relative to standard next-generation sequencing. Rare behaviors may be missed when sampling limits are reached, and nonequilibrium reactions are difficult to synchronize across large sample surfaces. Advances in imaging hardware, photostable labeling, and optically fmotions and rotational degrees of be key for further development. OUTLOOK: The scope of multiplexed single-molecule techniques is also expanding beyond nucleic acids. Display technologies or DNA-barcoded proteins could support high-throughput kinetic analysis of peptide and protein libraries, including protein-protein, protein-ligand, and aptamer-ligand interactions relevant to drug discovery. Integrations with super-resolution imaging, force spectroscopy, or DNA origami scaffolds may extend measurements to mesoscale (tens to hundreds of nanometers up to a few micrometers) structural motions and rotational degrees of freedom. The iterative interplay between large-scale single-molecule datasets and machine-learning models will enable deeper interpretation and accelerate the discovery of sequence-function relationships. Ultimately, these developments reunite high-throughput sequencing with single-molecule biophysics. Tying molecular identity to dynamic behavior for millions of molecules provides a powerful route to map sequence-structure-function relationships with unprecedented resolution. This convergence promises a next generation of tools for mechanistic biology and molecular engineering. Sequence-function relationships across complex kinetic landscapes.: Conventional single-molecule assays reveal functional phenotypes such as Cas9 R-loop formation, rewinding, and conformational equilibria yet seldom show how these dynamic processes depend on sequence. Multiplexed approaches integrate pooled library assembly, kinetic imaging, in situ sequencing, and per-molecule registration to assign trajectories to specific variants, enabling direct analysis of how sequence modulates energetic landscapes, intermediate states, and pathway heterogeneity. [ABSTRACT FROM AUTHOR]