De Novo Design of Ligand Binding and Sensing With a Physics-Based Generative Approach 1. The study introduces a physics-based generative framework that designs ligand-binding proteins directly around target molecules while simultaneously optimizing protein folding. Rather than searching existing scaffold libraries, it builds customized helical architectures with binding pockets tailored to small molecules or metal ions. 2. Its central innovation is the joint optimization of scaffold topology, internal protein stability, and protein–ligand interactions. This enables the authors to design not only static binders, but also proteins whose ligand recognition drives fragment reassociation or global protein folding—properties that are directly useful for biosensor construction. 3. The pipeline combines Rotamer Interaction Fields with Monte Carlo fragment assembly. Favorable ligand-contacting side chains are first enumerated as spatial anchors, after which protein backbones are generated around those anchors using ligand-interaction scores and residue-pair packing scores to guide folding. 4. For metal ions, the framework explicitly encodes coordination chemistry. It generated tetrahedral zinc-binding sites and octahedral nickel-binding sites by controlling coordinating residue identities, positions, and geometries during backbone construction. 5. The method produced experimentally validated binders for five chemically diverse small molecules: dolutegravir, cianidanol, DFHBI, serotonin, and dopamine. It successfully targeted serotonin and dopamine despite their unusually small size and polarity, which provide relatively few opportunities for favorable protein contacts. 6. Initial screening identified 14 binders among 96 dolutegravir designs, 20 among 94 cianidanol designs, six among 38 serotonin designs, and one among 33 dopamine designs. Subsequent structural or sequence optimization improved the best dolutegravir affinity to 971 nM and the optimized serotonin binder affinity to 29.9 μM. 7. High-resolution crystal structures strongly validated the computational models. The serotonin binder SRO_30, dopamine binder DPA_9, and zinc binder ZK2 matched their designed backbones with Cα RMSDs of approximately 0.97 Å, 0.79 Å, and 0.45 Å, respectively, while the designed ligand poses and metal-coordination geometries were largely reproduced. 8. The zinc binder ZK2 coupled metal recognition to protein folding, binding zinc with a reported Kd of 150 nM while showing no detectable binding to copper, cobalt, or nickel. This selectivity is notable because copper would ordinarily be thermodynamically favored over zinc according to the Irving–Williams series. 9. The authors converted the serotonin and dopamine binders into fluorescent sensors by splitting their helical bundles and fusing the fragments to circularly permuted GFP. Repeat helices, interface-weakening mutations, fragment truncation, and linker optimization reduced ligand-independent fragment association and improved signal responsiveness. 10. The optimized serotonin sensor wcSRO30_1.0 reached a ΔF/F₀ of approximately 340% during development and displayed a reported maximal response of 411%, an EC₅₀ of 539.9 μM, strong selectivity over related neurotransmitters, reversibility in E. coli, and measurable responses in HEK293T cells. A dopamine construct produced a 37.5% fluorescence response and was described as the first reported soluble dopamine biosensor. 11. The zinc-induced folding mechanism was also connected to split NanoLuc complementation. Two resulting zinc sensors achieved EC₅₀ values of 72.8 and 78.7 nM, illustrating how designed folding transitions can directly generate sensitive luminescent outputs without requiring a naturally evolved sensing domain. 12. Overall, the work presents ligand-binding protein design as an integrated problem of molecular recognition, scaffold generation, conformational energetics, and signal transduction. The current neurotransmitter sensors still require improvements in affinity and physiological sensitivity, but the framework provides a modular route from a specified ligand to an experimentally validated binder and then to a functional biosensor. 📜Paper: doi.org/10.64898/2026.07.13.… #ProteinDesign #ComputationalBiology #Biosensors #DeNovoDesign #GenerativeBiology #SmallMolecules #MetalBinding #Serotonin #Dopamine #SyntheticBiology