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Molecular machine

A molecular machine is a nanoscale assembly of molecular components designed or evolved to perform specific mechanical movements or functions, such as rotation, translocation, or force generation, typically powered by external stimuli like chemical energy, light, or redox reactions.^[1] These devices operate at dimensions around 1-100 nanometers, enabling tasks that mimic macroscopic machinery but at the molecular level, and they encompass both naturally occurring biological systems and human-made synthetic constructs.^[2] In biology, molecular machines are ubiquitous and essential for life processes, converting chemical energy—often from ATP hydrolysis—into directed mechanical work while navigating the challenges of thermal fluctuations and high viscosity in cellular environments.^[3] Prominent examples include the ribosome, a massive complex of RNA and proteins that synthesizes polypeptides by translating genetic code; DNA polymerase III, which accurately replicates DNA strands through polymerization and proofreading mechanisms; and helicases, enzymes that unwind double-stranded nucleic acids using nucleotide hydrolysis to facilitate replication and transcription.^[3] Motor proteins such as kinesin and myosin exemplify transport and contractile functions, with kinesin walking along microtubules to shuttle cellular cargo and myosin enabling muscle contraction via actin filament interactions.^[2] The bacterial flagellar motor further illustrates motility, rotating a helical propeller to propel cells through adaptive torque generation.^[3] Synthetic molecular machines, inspired by their biological counterparts, have advanced rapidly since the late 20th century, focusing on mechanically interlocked architectures like catenanes (interlocked rings) and rotaxanes (ring-on-axle systems) to achieve controlled motion.^[1] Breakthroughs include Jean-Pierre Sauvage's 1983 synthesis of catenanes using copper templates for interlocking, J. Fraser Stoddart's 1991 rotaxane shuttles that move directionally under pH or redox control, and Bernard L. Feringa's light-driven rotary motor, first reported in 1999, which was later optimized to achieve unidirectional 360° rotations at speeds up to 12 million revolutions per second in 2014.^[1] These innovations, recognized by the 2016 Nobel Prize in Chemistry, have led to applications such as molecular muscles that contract like human filaments, nanocar transporters on surfaces, and switchable systems for information processing in nanoscale devices.^[1]^[2] Ongoing research explores autonomous operation, collective behaviors, and biointegration, promising impacts in targeted drug delivery, catalysis, and molecular computing. As of 2025, these include molecular motors enabling non-invasive cancer therapies and autonomous self-driving molecular machines for precise spatiotemporal control.^[2]^[4]^[5]

Fundamentals

Definition and Principles

Molecular machines are assemblies of discrete molecular components, operating at the nanoscale with dimensions typically between 1 and 100 nm, designed to execute mechanical tasks through controlled, directed motion. These devices harness energy inputs from chemical reactions, light, or electricity to drive relative movements among their parts, thereby converting external stimuli into useful mechanical work. Unlike static molecular structures, molecular machines exhibit dynamic functionality, where the input energy powers cyclic or unidirectional processes that produce net displacement or force.^[6]^[7] At their core, molecular machines operate amidst pervasive thermal fluctuations characterized by Brownian motion, which causes random, undirected jostling of components at the molecular scale. Directed motion arises through mechanisms such as ratchets that asymmetrically rectify these fluctuations or energy gradients that impose directional bias, enabling the system to perform work against opposing forces. These processes are inherently nonequilibrium, requiring continuous energy dissipation to maintain directionality and overcome entropy increase as dictated by the second law of thermodynamics, which prohibits perpetual motion machines and imposes fundamental limits on efficiency. Energy conversion in these systems is thus constrained, with efficiencies often below 100% due to dissipative losses, though optimized designs can approach high thermodynamic bounds under specific conditions.^[8] The mechanical output of molecular machines is described by the basic relation for work, W = F \times d, where F is the force exerted and d the distance over which it acts. Energy inputs, such as from chemical fuels like ATP hydrolysis, provide the necessary free energy change \Delta G = -RT \ln K, with R the gas constant, T the temperature, and K the equilibrium constant reflecting reactant and product concentrations. In cellular contexts, this \Delta G for ATP hydrolysis typically ranges from -50 to -60 kJ/mol under physiological conditions, fueling the directed motions. Compared to macroscopic machines, molecular machines achieve work at vastly smaller scales and slower individual speeds (often nanometers per second), but their nanoscale size permits billions to operate simultaneously in parallel, facilitating high collective throughput in confined environments like cells.^[9]^[10]

Terminology

In the field of molecular machines, precise terminology is essential to distinguish between related concepts and avoid overlaps with broader nanotechnology jargon. A molecular machine is generally defined as a nanoscale assembly capable of performing specific tasks through controlled mechanical movements, often powered by chemical, light, or electrical energy inputs. This contrasts with a molecular motor, which is a subset focused primarily on generating unidirectional propulsion or directional motion, such as transporting cargo along filaments in biological systems, whereas molecular machines encompass a wider range of functions including pumping, switching, or information processing beyond mere locomotion.^[11]^[6] The term nanomachine is often used interchangeably but tends to be broader, encompassing any nanoscale device that produces quasi-mechanical outputs in response to stimuli, including non-mechanical systems like sensors or logic gates, without the strict requirement for discrete molecular components.^[12] Molecular machines are classified along several axes to reflect their operational modes and origins. Autonomous molecular machines operate continuously in a self-sustaining manner, fueled by chemical gradients or light without external intervention, enabling repetitive cycles of motion until fuel depletion, in contrast to non-autonomous ones that require repeated external stimuli, such as pulsed light or chemical additions, to reset and drive each cycle.^[13] Natural molecular machines, evolved in biological contexts like ATP synthase or ribosomes, differ from synthetic ones, which are human-designed using covalent or supramolecular chemistry to mimic or innovate upon natural functions.^[14] Additionally, they can be unimolecular, consisting of a single covalently linked entity such as a rotaxane with mechanically interlocked components, or supramolecular assemblies, involving multiple loosely bound molecules that collectively perform tasks.^[2] Recent efforts to standardize terminology address longstanding ambiguities, particularly in distinguishing molecular machines from related fields like supramolecular chemistry. In 2025, the International Union of Pure and Applied Chemistry (IUPAC) launched a project to rigorously define key terms, including "molecular motor" as a device producing net directional motion and "mechanical bond" as a non-covalent entanglement preventing separation without bond breakage, aiming to resolve overlaps with nanotechnology and ensure consistent usage across disciplines.^[15] This initiative builds on earlier proposals, such as those from 1997, and involves community polls to refine definitions that exclude simple responsive molecules.^[16]^[17] A critical distinction in terminology is that qualifying as a molecular machine requires the system to exhibit programmability—through sequential or gated responses—and produce measurable net mechanical work, such as displacing mass against a force or altering configuration irreversibly in a cycle. Mere catalysts accelerate reactions without mechanical output, and basic switches toggle states bidirectionally without directionality or work, thus falling outside the machine category unless integrated to yield net displacement or energy transduction.^[2]^[6] This emphasis on work output underscores the field's aspiration to emulate macroscopic machines at the nanoscale.^[18]

Historical Development

Early Concepts

The concept of molecular machines traces its intellectual origins to early 20th-century explorations of microscopic motion and self-replication, where physicists grappled with the implications of thermal fluctuations on mechanical systems at the atomic scale. In 1912, Marian Smoluchowski proposed a thought experiment involving a ratchet and pawl mechanism driven by Brownian motion, demonstrating that random thermal collisions could not produce net directed work without violating the second law of thermodynamics, thus highlighting the challenges of harnessing noise for mechanical function. This model laid foundational groundwork for understanding how molecular-scale devices might operate amid pervasive thermal agitation. Building on such ideas, John von Neumann in the 1940s developed theoretical models of self-replicating automata, initially conceived for macroscopic computing but later extended conceptually to the molecular domain, where cellular automata could mimic biological reproduction through universal constructors capable of building copies of themselves.^[19] These abstract frameworks emphasized the logical requirements for self-assembly and replication at small scales, influencing later visions of programmable molecular systems. By 1959, Richard Feynman delivered his seminal lecture "There's Plenty of Room at the Bottom," advocating for the manipulation of individual atoms as a new frontier in physics and engineering, explicitly envisioning tiny machines that could rearrange matter with atomic precision.^[20] The 1980s marked a pivotal shift from pure speculation toward more scientifically grounded proposals, exemplified by K. Eric Drexler's 1986 book Engines of Creation, which popularized the idea of molecular assemblers—self-replicating nanometer-scale devices capable of fabricating complex structures atom by atom, drawing on von Neumann's principles to argue for practical nanotechnology.^[21] This era also saw the rise of supramolecular chemistry, pioneered by Jean-Marie Lehn and colleagues, which provided chemical tools for non-covalent interactions enabling dynamic molecular assemblies, bridging theoretical machine concepts with experimental feasibility in the late 1980s.^[22] Throughout these developments, debates persisted on the practicality of molecular machines due to thermal noise, which causes constant random jostling at the nanoscale and complicates precise positional control. Critics, including Richard Smalley in his 2001 essay, argued that such "sticky fingers" and "dumb holes"—gaps in understanding how manipulators could grasp and position atoms without being overwhelmed by Brownian motion—rendered Drexler-style assemblers infeasible under ambient conditions.^[23] These challenges underscored the need to integrate noise management into designs, transforming early conceptual hurdles into drivers for rigorous theoretical refinement.^[24]

Key Milestones

In the 1980s and early 1990s, pioneering work laid the foundation for synthetic molecular machines through the creation of mechanically interlocked structures. Jean-Pierre Sauvage and colleagues reported the first template-directed synthesis of a copper-complexed ^[25]catenane in 1983, demonstrating the feasibility of interlocking molecular rings using metal coordination.^[26] Building on this, J. Fraser Stoddart developed the first switchable donor-acceptor ^[25]rotaxane in 1991, where a molecular ring could shuttle between recognition sites on a dumbbell-shaped axle, enabling controlled motion.^[27] These achievements, recognized as precursors to later Nobel recognition, marked the shift from static molecular architectures to those capable of mechanical movement. The late 1990s and early 2000s saw breakthroughs in dynamic functionality. In 1999, Bernard L. Feringa and coworkers introduced the first light-driven unidirectional rotary molecular motor, a chiral overcrowded alkene that undergoes repetitive 360° rotations around a central carbon-carbon double bond upon sequential photoisomerization and thermal helix inversion.^[28] Concurrently, advances in biological systems included the 2003 single-molecule imaging of F1-ATPase rotation by Kazuhiko Kinosita and colleagues, visualizing the ATP-driven stepwise turning of the gamma subunit within the enzyme complex, confirming its role as a rotary motor in ATP synthase.^[29] The field gained global acclaim with the 2016 Nobel Prize in Chemistry, awarded to Jean-Pierre Sauvage, Sir J. Fraser Stoddart, and Bernard L. Feringa "for the design and synthesis of molecular machines."^[30] This honor highlighted their collective contributions to controllable molecular motion, from interlocked structures to autonomous rotors, inspiring broader applications in nanotechnology. Entering the 2010s and 2020s, progress accelerated toward autonomous and programmable systems. In 2010, David A. Leigh and team demonstrated an autonomous DNA walker capable of multistep organic synthesis, where the bipedal device processes along a DNA track, performing sequential acylation reactions fueled by a chemical gradient without external intervention.^[31] By August 2025, Leroy Cronin and collaborators unveiled the Chemputer platform, a modular robotic system for programmable synthesis of functional molecular machines, integrating autonomous reaction optimization and liquid handling to produce complex interlocked structures on demand.^[32] In July 2025, Beatrice Collins and Jonathan Clayden reported the first autonomous single-molecule motor powered by redox chemistry, utilizing an enzyme to oxidize an alcohol group, enabling ring rotation, followed by chemical reduction to complete the cycle, achieving full 360° turns over approximately 20 hours.^[33] Later, in October 2025, Caltech researchers developed enzyme-free DNA logic circuits and neural networks that perform computations powered by heat, rechargeable through temperature cycles, providing a sustainable energy source for nanoscale molecular machines without chemical fuels.^[34] These milestones reflect a trajectory from static interlocked molecules in the 1990s to dynamic, fuel-driven systems by the 2000s, and increasingly complex assemblies like multi-component gears and walkers in the 2020s, enabling scalable fabrication and potential device integration.^[6]

Biological Molecular Machines

Structure and Function

Biological molecular machines exhibit diverse structural motifs that enable their precise operations within cellular environments. Proteins often fold into complex architectures, such as helical domains, to form motor components that facilitate movement and force generation; for instance, alpha-helical bundles and coiled-coil structures provide mechanical stability and leverage in these assemblies.^[35] Nucleic acid scaffolds, particularly RNA, serve as foundational frameworks in machines like the ribosome, where structured motifs such as loops and helices organize catalytic sites and support protein synthesis.^[36] Many molecular machines integrate into lipid membranes via transmembrane domains, allowing them to harness gradients or transport substrates across bilayers while maintaining structural integrity through hydrophobic interactions with phospholipids.^[37] The operational mechanisms of these machines rely on cyclic processes that convert chemical energy into directed mechanical work. Functional cycles typically involve either a power stroke mechanism, where ATP hydrolysis triggers a conformational change to produce force, or a Brownian search-and-ratchet model, in which thermal fluctuations enable substrate binding and subsequent rectification for net displacement.^[38] Allosteric regulation modulates these cycles by transmitting signals across distant sites, altering affinity for substrates or effectors to ensure coordinated action.^[39] Feedback loops further impose directionality, such as through product inhibition or environmental sensing, preventing futile cycling and maintaining efficiency in dynamic cellular conditions.^[40] Energy for these cycles derives primarily from hydrolysis of high-energy phosphates like ATP to ADP or GTP to GDP, or from transmembrane proton gradients that drive rotary or pumping actions.^[41] In specialized cases, such as ATP synthase, thermodynamic efficiencies reach 60-90%, reflecting near-reversible coupling of proton flow to phosphate bond synthesis under physiological loads.^[42] The kinetics of these energy-dependent cycles often follow a Michaelis-Menten framework adapted for motor function, where the rate of ATP binding and hydrolysis determines turnover:

v = \frac{V_{\max} [S]}{K_m + [S]}

Here, v is the reaction velocity, V_{\max} the maximum rate, [S] the substrate concentration (e.g., ATP), and K_m the Michaelis constant reflecting binding affinity, which modulates motor stepping frequency under varying loads.^[43] Disruptions in structure or dynamics can lead to failures, such as protein misfolding that impairs assembly and function, resulting in diseases like cystic fibrosis where the CFTR transporter misfolds and fails to traffic to the membrane.^[44] Jamming occurs when motors collide or stall on tracks, reducing transport efficiency in crowded cytoskeletal environments and potentially contributing to cellular dysfunction.^[45]

Key Examples

One prominent example of a biological molecular machine is ATP synthase, which functions as a rotary motor to synthesize adenosine triphosphate (ATP), the primary energy currency of the cell.^[46] This enzyme consists of two main subunits: the membrane-embedded F0 portion, which acts as a proton-driven motor, and the soluble F1 portion, which catalyzes ATP production.^[46] Protons flowing through the F0 subunit drive the rotation of a central stalk at approximately 100 revolutions per second, inducing conformational changes in the F1 subunit that facilitate ATP synthesis from ADP and inorganic phosphate.^[47] This mechanism achieves near-perfect coupling efficiency, converting proton motive force into chemical energy with minimal slippage. Kinesin and dynein exemplify motor proteins that serve as microtubule-based walkers for intracellular transport, enabling the movement of vesicles, organelles, and other cargoes along cytoskeletal tracks.^[48] Kinesin typically moves toward the plus end of microtubules in an anterograde direction, taking hand-over-hand steps of about 8 nm per ATP hydrolyzed, corresponding to the spacing between tubulin dimers.^[48] It can bear loads up to 7 piconewtons before stalling, ensuring robust transport even under mechanical resistance.^[48] Dynein, in contrast, travels toward the minus end in a retrograde manner, exhibiting similar step sizes of around 8 nm under high load, though its stepping can vary to 24-32 nm at lower loads for efficient navigation.^[49] These motors coordinate bidirectional transport, with their ATPase cycles tightly coupled to mechanical stepping, preventing futile cycling and maintaining cellular logistics.^[48] The ribosome represents a quintessential molecular machine for protein synthesis, assembling amino acids into polypeptides through a processive cycle of translation.^[50] During elongation, transfer RNAs (tRNAs) carrying specific amino acids bind to messenger RNA codons in the ribosome's A site, followed by peptide bond formation and tRNA translocation to the P and E sites, advancing the mRNA by three nucleotides per cycle.^[51] This translocation is powered by elongation factor G and achieves remarkably low error rates of less than 1% (typically 10^{-4} per codon), ensuring the fidelity of the genetic code through kinetic proofreading and tRNA selection mechanisms.^[50] DNA polymerase functions as a replicative machine that copies genomic DNA with exceptional accuracy and efficiency during cell division.^[52] Its fidelity is enhanced by a proofreading exonuclease activity that excises mismatched nucleotides, reducing error rates from about 10^{-5} to 10^{-7} per base pair incorporated.^[52] High processivity, often exceeding 10^5 nucleotides per binding event in holoenzyme complexes like E. coli DNA polymerase III, allows continuous synthesis over long stretches without frequent dissociation, minimizing replication errors and gaps.^[53] These molecular machines exhibit profound evolutionary conservation, with core structures and mechanisms preserved across prokaryotes and eukaryotes, reflecting their essential roles in fundamental cellular processes.00111-9) Mutations in genes encoding these proteins, such as those affecting kinesin or dynein, are frequently linked to neurodegenerative disorders like amyotrophic lateral sclerosis and hereditary spastic paraplegia, underscoring their vulnerability to disruption in long-lived neurons.^[54]

Artificial Molecular Machines

Design Principles

The design of synthetic molecular machines relies on bottom-up assembly strategies, where individual molecular components are precisely organized to mimic the functionality of their biological counterparts, drawing inspiration from natural systems like ATP synthase.^[55] These approaches emphasize the use of supramolecular interactions to construct mechanically interlocked or responsive architectures at the nanoscale. Assembly methods for synthetic molecular machines primarily involve covalent synthesis for rigid frameworks and non-covalent self-assembly for dynamic structures. Covalent synthesis employs traditional organic reactions to form stable bonds, enabling the creation of precisely defined scaffolds that serve as the core of the machine.^[2] In contrast, self-assembly leverages weaker interactions such as hydrogen bonding or π-π stacking to spontaneously organize components into higher-order structures, allowing for reversibility and adaptability.^[56] For mechanically interlocked systems like rotaxanes and catenanes, templated threading directs the encirclement of one molecular component by another, often using metal ions or hydrogen-bonding templates to guide the process before locking the structure in place.^[57] The stability of these self-assembled complexes is governed by the binding affinity, expressed as the association constant K_a = \frac{[\text{complex}]}{[\text{host}][\text{guest}]}, which quantifies the equilibrium between free and bound species and ensures reliable formation under controlled conditions.^[56] Control mechanisms are essential to direct motion and function in these machines, often triggered by external stimuli to achieve directed operations. Gating strategies utilize changes in pH, light, or redox potentials to modulate interactions, such as protonation/deprotonation altering hydrogen bonds or photoisomerization inducing conformational shifts.^[58] For rotational dynamics, unidirectional motion is imposed through chiral barriers, where steric or energetic asymmetries prevent back-rotation, enabling ratchet-like behavior powered by thermal fluctuations or chemical fuels.^[59] Scalability in molecular machine design is achieved via modular architectures, incorporating versatile building blocks such as porphyrins for light-harvesting components or fullerenes for electron-accepting units, which can be systematically varied to tune properties.^[60] These modules facilitate integration into larger ensembles, such as immobilization on surfaces for device applications or incorporation into polymers to form responsive materials that amplify machine-like behavior at macroscopic scales.^[61] Despite these advances, challenges persist in optimizing yields and purifying products from synthetic byproducts, as low-affinity interactions can lead to incomplete assemblies or side reactions during templating.^[2] Strategies like dynamic covalent chemistry help mitigate these issues by allowing error correction during assembly, though achieving high-fidelity production remains a key hurdle for practical implementation.^[62]

Types and Examples

Artificial molecular machines are broadly classified into rotary motors, linear motors, switches and elevators, as well as gears and pumps, each designed to perform specific mechanical tasks at the nanoscale through controlled molecular motions. These categories draw inspiration from biological counterparts but employ synthetic strategies such as photochemical isomerization, DNA hybridization, or supramolecular interactions to achieve directed movement. Representative examples illustrate their operational principles and performance metrics, emphasizing unidirectional rotation, processive transport, or responsive shuttling. Rotary motors, capable of completing full 360° rotations around a central axis, represent a cornerstone of artificial molecular machines, often powered by light to overcome thermal barriers and achieve directional motion. A seminal example is Ben Feringa's light-driven rotary motor based on overcrowded alkenes, first demonstrated in 1999, where a chiral helical structure undergoes unidirectional rotation upon irradiation with visible light, completing a full cycle through sequential photoisomerization and thermal helix inversion steps.^[28] These motors have since been optimized for higher speeds, with second-generation designs reaching rotation rates up to the MHz regime under continuous illumination, enabling potential applications in nanoscale actuation.^[63] Recent advancements in 2025 have introduced tunable cores that adjust rotary speeds via structural modifications while maintaining high photostationary states for efficient operation.^[64] Linear motors facilitate directional transport along predefined tracks, mimicking the processive walking of biological proteins like kinesin. DNA-based walkers exemplify this class, where bipedal nanostructures advance step-by-step via strand displacement or enzymatic reactions, enabling cargo delivery over extended distances. A foundational design from 2004 features a processive bipedal DNA motor that transports payloads by alternating foot attachments on a DNA track, achieving controlled steps on the order of nanometers per cycle.^[65] Advanced DNA origami-integrated walkers have demonstrated highly processive motion, covering micron-scale distances autonomously without external intervention, thus highlighting their potential for long-range molecular transport.^[66] Switches and elevators operate through reversible positional changes in interlocked components, often triggered by chemical stimuli like pH variations. Rotaxane-based systems, featuring a macrocycle threaded onto an axle with recognition sites, serve as pH-responsive shuttles where protonation/deprotonation alters binding affinities to drive directed motion. A prominent example is Fraser Stoddart's molecular elevator, reported in 2004, which employs a tetracationic cyclophane ring that "elevates" between two carboxylate floors on a thread-like axle upon pH adjustment, mimicking multistage mechanical lifting at the single-molecule level. This design achieves precise control over ring positioning, with the shuttle responding reversibly to acid-base inputs for up to four distinct states.^[67] Gears and pumps enable mechanical coupling or active transport across barriers, transmitting forces or gradients in a directed manner. Supramolecular gears, assembled from surface-bound molecules like pentafluorophenyl or triptycene rotors, facilitate torque transmission through interlocking teeth-like interactions, allowing rotational motion to propagate across multiple units. Simulations and experimental studies in 2020 revealed regimes of synchronized rotation in gear trains, where external torque on a driver gear induces collective motion in slave gears, with efficiency depending on intergear spacing and friction.^[68] For pumps, artificial ion pumps mimic the selective transport of gramicidin A channels by forming transmembrane pores that conduct ions unidirectionally. A 2014 synthetic triazole-based channel replicates gramicidin's beta-helical structure, enabling potassium ion permeation across lipid bilayers with conductance rates comparable to the natural peptide, driven by hydrophobic matching and dipole alignment.^[69] A 2024 example of self-driving molecular machines with spatiotemporal control includes DNA-based gliding robots that autonomously assemble and disassemble via cascade reactions, enabling precise positioning and motion in response to temporal cues like fuel gradients.^[70] Additionally, modular robotic platforms for machine synthesis, such as the Chemputer system, automate the assembly of functional molecular machines through integrated feedback loops, producing complex rotaxanes and motors with high yield and reproducibility.^[32]

Research and Applications

Current Advances

Since 2020, significant breakthroughs in molecular machine research have centered on enhancing control and functionality through external stimuli and computational tools. A notable advancement is the development of electric field-controlled rotary motors, exemplified by the E-motor, a light-driven unidirectional molecular rotary motor capable of remotely switching rotation direction via short electric field pulses up to 4 V/nm. This system employs a polar switching unit to modulate axial chirality, enabling reversible transitions between clockwise and counterclockwise rotations without chemical fuels, as demonstrated by non-adiabatic molecular dynamics simulations showing excited-state decay in 3.6 ps. Such motors represent a step toward non-invasive, real-time manipulation of nanoscale devices for applications in smart materials.^[71] Artificial intelligence has accelerated the design of dynamic molecular machines, particularly through machine learning models that predict and optimize multistate protein switches. In 2025, researchers introduced a pipeline integrating AlphaFold2 for structure prediction, ProteinMPNN for sequence design, and molecular dynamics simulations to create calcium-binding proteins with switchable conformations controlled by single-residue mutations, achieving 10-fold differences in binding affinity between states on microsecond timescales. This AI-driven approach enables the rapid generation of autonomous, ligand-responsive machines that mimic natural protein dynamics, reducing design iterations from years to months. Complementing this, the 2025 Chemputer platform—a modular robotic system for automated chemical synthesis—has streamlined the production of functional molecular machines by executing complex, multi-step reactions with high yield, including the assembly of rotaxanes and catenanes previously limited by manual labor.^[72]^[32] Progress in ion transport machines has yielded synthetic channels that approach the efficiency of biological proteins, facilitating transmembrane pumping with selective ion fluxes. A 2025 review highlights artificial light-driven ion pumps that mimic biological ion transport through photoresponsive mechanisms, enabling selective ion fluxes across membranes.^[73] Hybrid integrations have further expanded capabilities, such as DNA origami-based molecular machines coupled with CRISPR-Cas9 for targeted nucleic acid delivery, where programmable nanostructures guide ribonucleoproteins to specific genomic loci.^[74] Nanomachine swarms have emerged for collective sensing tasks, leveraging coordinated behaviors at the nanoscale for enhanced sensitivity. Advanced imaging techniques support these developments: single-molecule spectroscopy, including atomic force microscopy and optical tweezers, has resolved shuttling dynamics in rotaxanes with forces up to 50 pN and rupture events at 8-9 pN, revealing energy barriers as low as 10 kT. Similarly, time-resolved cryo-electron microscopy has captured conformational dynamics of ATP synthase-like machines, resolving intermediate states at 3 Å resolution during 100-ms mixing experiments to elucidate rotation mechanisms. These tools, combined with improved autonomy—evidenced by supramolecular polymers integrating thousands of motors for contraction—underscore the field's shift toward scalable, durable systems.^[75]^[76]^[77]^[78]

Potential Impacts and Challenges

Molecular machines hold significant promise for transformative applications in drug delivery, where synthetic constructs like rotaxanes and catenanes enable targeted and controlled release of therapeutics, minimizing side effects and improving efficacy in treating diseases such as cancer.^[2] In materials science, these machines can drive the development of smart polymers that respond to external stimuli, such as light or pH changes, for adaptive structures in sensors or actuators.^[79] For computing, artificial molecular machines function as logic gates, performing binary operations at the nanoscale to potentially enable ultra-dense information processing beyond conventional silicon-based systems.^[80] Environmentally, they offer potential in pollutant degradation, with propelled nanomachines capable of breaking down contaminants in water or soil through catalytic actions.^[81] The broader impacts of molecular machines span medicine, where nanobot-like devices could perform precise intracellular surgery or tissue repair, revolutionizing treatments for intractable conditions.^[82] In energy sectors, photochemical molecular machines may enhance solar energy conversion by efficiently harvesting and storing light as mechanical or chemical energy, contributing to sustainable power systems.^[83] For manufacturing, they facilitate bottom-up assembly processes, allowing atom-precise construction of complex materials and reducing waste in nanoscale fabrication.^[84] Despite these prospects, several challenges impede realization. Scalability remains a primary hurdle, as harnessing collective motions of individual molecular machines to produce observable macroscopic effects requires overcoming disorder in solution and inefficiencies in energy transduction.^[2] In vivo toxicity poses risks, particularly for biomedical uses, where unintended interactions with biological systems could lead to immune responses or cellular damage.^[85] Energy supply limitations further complicate autonomous operation, as current chemical fuels often degrade quickly or require constant external input, hindering long-term functionality.^[86] Ethical concerns, including the risks of self-replicating machines leading to uncontrolled proliferation or biosafety issues, necessitate careful governance in synthetic designs inspired by biological systems.^[87] Looking ahead, the field anticipates integration with emerging technologies, though robust regulatory frameworks will be essential to address safety and ethical deployment by the 2030s. Economically, the nanomedicine sector incorporating molecular machine technologies is projected to grow substantially, with the broader nanorobotics market—encompassing such innovations—reaching approximately $27 billion by 2035.^[88]

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By 2035, Nanorobotics Market worth $27.21 Bn at a CAGR of 10.91%
The nanorobotics market was valued at USD 8.51 billion in 2024 and is estimated to reach USD 27.21 billion by 2035, at a CAGR of 10.91% between 2025 and ...