Biology subjects

Vafeados, D. K.

Publications and source records attributed to Vafeados, D. K..

8 recordsLinked to original sources

bioRxiv2026

Generative design of sequence specific DNA binding proteins

De novo protein design has advanced rapidly in recent years, yet the programmable recognition of specific DNA sequences remains a longstanding challenge. Here we describe a deep learning based approach for designing sequence selective DNA binding proteins. Our method combines structure generation using RFdiffusion3 with explicit screening against off-target interactions using AlphaFold3. We test this approach by generating 96 designs for each of 15 diverse DNA targets and identify specific binders for 7 targets, representing a ~100-fold improvement in success rates over previous approaches. We further characterize the binding landscape using variant competition assays and randomized library screening, revealing robust sequence discrimination across diverse targets. Together, these results represent a significant step forward in de novo sequence specific DNA binder design.

synthetic biology↗

bioRxiv2025

De novo design of phospho-tyrosine peptide binders

Phosphorylation on tyrosine is a key step in many signaling pathways. Despite recent progress in de novo design of protein binders, there are no current methods for designing binders that recognize phosphorylated proteins and peptides; this is a challenging problem as phosphate groups are highly charged, and phosphorylation often occurs within unstructured regions. Here we introduce RoseTTAFold Diffusion 2 for Molecular Interfaces (RFD2-MI), a deep generative framework for the design of binders for protein, ligand, and covalently modified protein targets. We demonstrate the power and versatility of this method by designing binders for four critical phosphotyrosine sites on three clinically relevant targets: Cluster of Differentiation 3 (CD3{varepsilon}), Epidermal Growth Factor Receptor (EGFR), Insulin Receptor (INSR) and Signal Transducer and Activator of Transcription 5 (STAT5). Experimental characterization shows that the designs bind their phosphotyrosine containing targets with affinities comparable to native binding sites and have negligible binding to non-phosphorylated targets or phosphopeptides with different sequences. X-ray crystal structures of generated binders to CD3{varepsilon} and EGFR are very close to the design models, demonstrating the accuracy of the design approach. A designed binder to an EGFR intracellular region phosphorylated upon EGF activation co-localizes with the receptor following EGF stimulation in single-particle tracking (SPT) experiments, demonstrating pY specific recognition in living cells. RFD2-MI provides a generalizable all-atom diffusion framework for probing and modulating phosphorylation-dependent signaling, and more generally, for developing research tools and targeted therapeutics against post-translationally modified proteins.

bioengineering↗

bioRxiv2025

Design of Orthogonal Far-Red, Orange and Green Fluorophore-binding Proteins for Multiplex Imaging

Fluorescent proteins and small molecule dyes have complementary strengths for biological imaging: the former are genetically manipulatable enabling tagging of specific proteins and detection of protein interactions, while the latter have greater photostability and brightness but are difficult to target. To combine these strengths, we used de novo protein design to generate binders to three bright, stable, cell-permeable dyes spanning the visible spectrum: JF657 (far red), JF596 (orange-red) and JF494 (green). For each dye, we obtain nanomolar binders with weak or no binding to the other two dyes; the accuracy of the design approach is confirmed by a crystal structure of one binder which is very close to the design model. Fusion of the JF567, JF596 and JF494 binders to three different targets followed by staining with the three dyes simultaneously enables multiplex imaging. We further expand functionality by incorporating an active site carrying out nucleophilic aromatic substitution to form a covalent linkage with the dye, and developing split versions which reconstitute fluorescence at subcellular locations where both halves are present, enabling both protein-protein interaction detection and chemically induced dimerization with fluorescence reporting. Our designs combine the advantages of fluorescent proteins and small molecule dyes and should be broadly useful for cellular imaging.

biochemistry↗

bioRxiv2025

De novo design of high-affinity miniprotein binders targeting Francisella tularensis virulence factor

Francisella tularensis poses considerable public health risk due to its high infectivity and potential for bioterrorism. Francisella-like lipoprotein (Flpp3), a key virulence factor unique to Francisella, plays critical roles in infection and immune evasion, making it a promising target for therapeutic development. However, the lack of well-defined binding pockets and structural information on native interactions has hindered structure-guided ligand discovery against Flpp3. Here, we used a combination of physics-based and deep-learning methods to design high-affinity miniprotein binders targeting two distinct sites on Flpp3. We identified four binders for site I with binding affinities ranging between 24-110 nM. For the second site, an initial binder showed a dissociation constant (KD) of 81 nM, and subsequent site saturation mutagenesis yielded variants with sub-nanomolar affinities. Circular dichroism confirmed the topology of designed miniproteins. The X-ray crystal structure of Flpp3 in complex with a site I binder is nearly identical to the design model (C root-mean-square deviation: 0.9 [A]). These designed miniproteins provide research tools to explore the roles of Flpp3 in tularemia and should enable the development of new therapeutic candidates.

biochemistry↗

bioRxiv2025

De novo design of miniprotein agonists and antagonists targeting G protein-coupled receptors

G protein-coupled receptors (GPCRs) play key roles in physiology and are central targets for drug discovery and development, but the design of protein agonists and antagonists has been challenging as GPCRs are integral membrane proteins and conformationally dynamic. Here we describe computational de novo design methods and a high throughput "receptor diversion" microscopy-based screen for generating GPCR binding miniproteins with high affinity, potency and selectivity, and the use of these methods to generate agonists for MRGPRX1, NK1R and CCR5, as well as antagonists for CXCR4, CCR5, OXTR, GLP1R, GIPR, GCGR, PTH1R and CGRPR.. Cryo-electron microscopy data reveals atomic-level agreement between designed and experimentally determined structures for CGRPR- and CXCR4-bound antagonists and MRGPRX1-bound agonists. Our de novo design and screening approach opens new frontiers in GPCR drug discovery and development.

bioengineering↗

bioRxiv2024

Design of high specificity binders for peptide-MHC-I complexes

Class I MHC molecules present peptides derived from intracellular antigens on the cell surface for immune surveillance, and specific targeting of these peptide-MHC (pMHC) complexes could have considerable utility for treating diseases. Such targeting is challenging as it requires readout of the few outward facing peptide antigen residues and the avoidance of extensive contacts with the MHC carrier which is present on almost all cells. Here we describe the use of deep learning-based protein design tools to de novo design small proteins that arc above the peptide binding groove of pMHC complexes and make extensive contacts with the peptide. We identify specific binders for ten target pMHCs which when displayed on yeast bind the on-target pMHC tetramer but not closely related peptides. For five targets, incorporation of designs into chimeric antigen receptors leads to T-cell activation by the cognate pMHC complexes well above the background from complexes with peptides derived from proteome. Our approach can generate high specificity binders starting from either experimental or predicted structures of the target pMHC complexes, and should be widely useful for both protein and cell based pMHC targeting.

immunology↗

bioRxiv2024

Controlling semiconductor growth with structured de novo protein interfaces

Protein design now enables the precise arrangement of atoms on the nanometer length scales of inorganic crystal nuclei, opening up the possibility of templating the growth of metal oxides including semiconductors. We designed proteins presenting regularly repeating interfaces containing functional groups that organize ions and water molecules, and characterized their ability to bind to and template metal oxides. Two interfaces promoted the growth of hematite under conditions that otherwise resulted in the formation of magnetite. Three interfaces promoted ZnO nucleation under conditions where traditional ZnO-binding peptides and control proteins were ineffective. Designed cyclic assemblies with these ZnO nucleating interfaces lining interior cavities promoted ZnO growth within the cavity. CryoEM analysis of a designed octahedral nanocage revealed atomic density likely corresponding to the growing ZnO directly adjacent to the designed nucleation promoting interfaces. These findings demonstrate that designed proteins can direct the formation of metal oxides not observed in biological systems, opening the door to protein-semiconductor hybrid materials. One Sentence SummaryWe describe the design of structured protein interfaces that bind to, promote, and localize the growth of zinc oxide and hematite, inorganic materials which are not found in biological systems.

bioengineering↗

bioRxiv2023

De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles

A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, and transducing binding events into signals is challenging. Here we describe an integrated deep learning and energy based approach for designing high shape complementarity binders to small molecules that are poised for downstream sensing applications. We employ deep learning generated psuedocycles with repeating structural units surrounding central pockets; depending on the geometry of the structural unit and repeat number, these pockets span wide ranges of sizes and shapes. For a small molecule target of interest, we extensively sample high shape complementarity pseudocycles to generate large numbers of customized potential binding pockets; the ligand binding poses and the interacting interfaces are then optimized for high affinity binding. We computationally design binders to four diverse molecules, including for the first time polar flexible molecules such as methotrexate and thyroxine, which are expressed at high levels and have nanomolar affinities straight out of the computer. Co-crystal structures are nearly identical to the design models. Taking advantage of the modular repeating structure of pseudocycles and central location of the binding pockets, we constructed low noise nanopore sensors and chemically induced dimerization systems by splitting the binders into domains which assemble into the original pseudocycle pocket upon target molecule addition. One Sentence SummaryWe use a pseuodocycle-based shape complementarity optimizing approach to design nanomolar binders to diverse ligands, including the flexible and polar methotrexate and thyroxine, that can be directly converted into ligand-gated nanopores and chemically induced dimerization systems.

biochemistry↗