Biology subjects

Kimmel, B. R.

Publications and source records attributed to Kimmel, B. R..

9 recordsLinked to original sources

bioRxiv2026

ProteinDock: A physics-informed layer to improve protein-protein docking reliability

Computational modeling provides geometric insight into protein-protein interactions without requiring the resources of experimentation. However, reliability can be hindered when modeling proteins with distinctive features, such as antibodies, that use flexible, polar-rich loops to bind antigens. We developed ProteinDock, a physics-based tool that can be used in combination with leading modeling programs to improve the reliability of protein-protein docking; this work provides a case study of antibody-antigen interfaces. ProteinDock was layered onto Rosetta for docking unbound experimentally determined structures, and when evaluated on Docking Benchmark Set 5.5, generated CAPRI acceptable-quality or better for 80.2% of targets, an improvement of 32.8 percentage points over vanilla Rosettas 47.4% on the same dataset. To improve protein-protein prediction reliability from sequence inputs, we demonstrate that a truncated version of ProteinDock can be used to choose the optimal prediction among outputs from multiple deep learning-based tools. We show that this strategy is a computationally efficient alternative to increasing the seed quantity for deep-learning predictions. A graphical user interface for layering ProteinDock has been created and is available at https://github.com/Kimmel-Lab/proteindock and https://proteindock.com/. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/739238v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1547128org.highwire.dtl.DTLVardef@d1364corg.highwire.dtl.DTLVardef@143dcedorg.highwire.dtl.DTLVardef@5d5ba4_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2026

Experimentally Tuned Protein-RNA Rosetta Score Function using Bayesian Optimization

Protein-RNA complexes drive fundamental cellular processes such as transcription and translation. Despite the prevalence and importance of protein-RNA interactions, the field lacks reliable and accessible methods to quantify the energetic favorability of these interactions. We propose an experimentally tuned protein-RNA score function that can be directly implemented into ROSETTA. Fine-tuning these score functions for predictive tasks requires repeated evaluations on a set of protein-RNA complexes, which can be computationally expensive given the number of parameters to tune. We used Bayesian Optimization to efficiently improve the energetic agreement between ROSETTA and experimentation. We observe significant interactions for specific RNA subclasses, serving as further confirmation of the physical validity of the score function. Beyond protein-RNA interaction prediction, we establish a framework to efficiently fine-tune ROSETTA score functions for any protein-class interaction using Bayesian Optimization. TOC FIGURE O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/739244v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@c7d3edorg.highwire.dtl.DTLVardef@12a8fe2org.highwire.dtl.DTLVardef@14c4c5dorg.highwire.dtl.DTLVardef@297169_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2026

CovSite: A High-Throughput Blind Covalent Screening Framework for Reactive Site Detection

Targeted covalent inhibitors are a powerful, yet underexplored, class of therapeutics, and current computational covalent screeners are constrained in early drug discovery due to the need for prior knowledge of the target site and limited throughput. We present CovSite, a blind covalent screening tool that identifies candidate reactive residues across the entire protein surface, utilizing only the protein structure and electrophile SMILES. CovSite applies a pipeline of four orthogonal physicochemical filters (nucleophile identification, solvent accessibility, environment-dependent deprotonation prediction, and semi-quantum-mechanical reactivity ranking) to identify potential small-molecule candidate inhibitors. Validated against 2,062 diverse covalent protein-ligand complexes spanning six nucleophilic residue types, CovSite achieves a 98.5% blind target site hit on a held-out benchmark set of 207 cysteine-targeted complexes while reducing the search space by 97.8%. The target-site hit detection exceeds the 53-62% accuracy of popular covalent screening tools operating under non-blind conditions on the same benchmark set. By extending nucleophilic coverage beyond cysteine to include serine, threonine, lysine, histidine, and tyrosine, and completing a screening of a 200-residue protein in two to three minutes on standard hardware, CovSite serves as a platform technology with the potential to address critical gaps in throughput, generalizability, and accuracy in this field of covalent screening. We demonstrate this capability by using CovSite as a blind, ligand-specific approach that enables iterative, machine-learning-driven covalent inhibitor generation that is impractical with existing tools, establishing a foundation for computationally guided covalent drug discovery for novel and understudied targets. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/739288v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@139335forg.highwire.dtl.DTLVardef@5bd9feorg.highwire.dtl.DTLVardef@44d6c8org.highwire.dtl.DTLVardef@1710154_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2026

A Yeast Surface Display Platform for Screening Dimeric Mammalian Receptors

Discovering proteins that modulate receptor activity remains a key challenge in the field of protein design and engineering. Traditionally, identifying proteins that interact with receptors often relies on binding as a selection criterion, yielding limited information about the function of discovered binders in a library, including the ability to activate or block signaling cascades associated with the receptor of interest. As a result, extensive downstream characterization is required to assess the biological relevance of discovered binders. To address this issue, we have developed a high-throughput screening system to screen dimeric mammalian receptors using yeast surface display. We demonstrate the programmed dimerization of the extracellular domains of mammalian receptors in yeast via engineered induction pathways, thereby enabling receptor expression and the secretion of associated native cytokines. This surface expression of the involved subunits for the protein receptor and cytokine-induced dimerization activity indicates that the receptor has been activated and is expected to trigger a DNA-driven signaling cascade within a mammalian cell. This system provides a modular platform technology that advances existing yeast-display systems, demonstrating the effectiveness of these high-throughput platforms for screening the function of mammalian receptors. This work is expected to provide a rapid, cost-effective approach to the molecular discovery of novel biologics for targeting dimeric mammalian receptors.

synthetic biology↗

bioRxiv2026

Computational Analysis of Structure and Binding Energy for the Development of a Cisplatin-Loaded Protein Nanocarrier

Platinum-based drugs, such as cisplatin, are first-line chemotherapy treatments for patients with cancer. However, the success of these drugs is balanced with severe off-target toxicities and high dosing requirements, prompting the development of selective nanocarriers for targeted drug delivery. This study uses a computationally guided approach to examine the role of amino acids in cisplatin binding within proteins as nanocarriers. Using density functional theory, we quantify the binding of cisplatin to platinum-coordinating amino acids. We then rationally engineer a model MSH6 protein carrier, and evaluate the ability of MSH6 to bind cisplatin via molecular docking simulations. Structure predictions of the engineered MSH6 show that inserting the cisplatin-binding site has a limited impact on the nearby protein architecture of MSH6. Finally, we confirm and reveal cisplatins mechanism of action with DNA binding, and compare the energetic potentials of DNA binding from protein-delivered cisplatin to systemically administered cisplatin. Future studies will use these results to experimentally validate the binding of cisplatin in model protein carriers, and inform the strategic design and experimental development of a protein nanocarrier to achieve targeted drug delivery in cancer. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/699809v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@feee4org.highwire.dtl.DTLVardef@ccc34org.highwire.dtl.DTLVardef@328cd3org.highwire.dtl.DTLVardef@bb8335_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Modular Nanobody Conjugates with Controlled Topology Using Genetically Encoded Non-canonical Amino Acids

Bispecific antibody-based derivatives are traditionally generated by fusing short, flexible peptides to two variable heavy and light chain pairs that recognize distinct antigens. However, this method limits domain joining to the amino (N) or carboxyl (C) termini, thereby restricting our ability to study the role of domain orientation in key properties of bispecific molecules, such as affinity and specificity. Here, we present an adaptable, plug-and-play application of genetic code expansion technology for the rapid, modular creation of bispecific nanobody conjugates from non-canonical amino acid (ncAA)- integrated nanobody domains, offering precise control over domain topology. We implement this strategy using a single-plasmid genetic code expansion system and computation-guided ncAA site selection to preserve nanobody expression and target binding. We demonstrate the effective incorporation and crosslinking of azide- and tetrazine-modified lysine and phenylalanine, respectively, at four engineered positions within an anti-PD-L1 nanobody and two positions within an anti-CTLA-4 nanobody in a panel of immune cell- and cancer-cell-binding nanobodies. Using this approach, we demonstrate the modular synthesis of a library of bispecific nanobodies, comprising four PD-L1xCD16 immune synapse engagers and eight PD-L1xCTLA-4 immune checkpoint bispecifics. This work enables a new dimension of control over protein crosslinking for rapidly constructing immune cell engagers for dual immune checkpoint blockade therapy and to bridge the synapse between immune cells and cancer cells.

bioengineering↗

bioRxiv2025

Macromolecular Diamidobenzimidazole Conjugates Activate STING

Pharmacologic activation of the stimulator of interferon genes (STING) pathway has broad potential applications, including the treatment of cancer and viral infections, which has motivated the synthesis and testing of a diversity of STING agonists as next generation immunotherapeutics. A promising class of STING agonists are the non-nucleotide, small molecule, dimeric-amidobenzimidazoles (diABZI), which have been recently used in the synthesis of polymer- and antibody-drug conjugates to improve pharmacokinetics, modulate biodistribution, and to confer other favorable properties for specific disease applications. These approaches have leveraged diABZI variants functionalized with reactive handles and enzyme-cleavable linkers at the 7-position of the benzimidazole for conjugation to and tunable drug release from carriers. However, since this position does not interact with STING and is exposed from the binding pocket when bound in an "open lid" configuration, we sought to evaluate the activity of macromolecular diABZI conjugates that lack enzymatic release and are instead conjugated to polymers via a stable linker. By covalently ligating diABZI to 5 or 20 kDa mPEG chains via an amide bond, we surprisingly found that these conjugates could activate STING in vitro. To further evaluate this phenomenon, we designed a diABZI-functionalized RAFT chain transfer agent that provided an enabling tool for synthesis of large, hydrophilic, dimethylacrylamide (DMA) polymers directly from a single agonist and we found that these conjugates also elicited STING activation in vitro with similar kinetics to highly potent small molecule analogs. We further demonstrated the in vivo activity of these macromolecular diABZI platforms, which inhibited tumor growth to a similar extent as small molecule variants. Using flow cytometry and fluorescence microscopy to evaluate intracellular uptake and distribution of Cy5-labeled analogs, our data indicate that although diABZI-DMA conjugates enter cells via endocytosis, they can still colocalize with the ER, suggesting that intracellular trafficking processes can promote delivery of endocytosed macromolecular diABZI compounds to STING. In conclusion, we have described new chemical strategies for the synthesis of stable macromolecular diABZI conjugates with unexpectedly high immunostimulatory potency, findings with potential implications for the design of polymer-drug conjugates for STING agonist delivery that also further motivate investigation of endosomal and intracellular trafficking as an alternative route for achieving STING activation.

bioengineering↗

bioRxiv2024

STING-Activating Polymer-Drug Conjugates for Cancer Immunotherapy

The stimulator of interferon genes (STING) pathway links innate and adaptive antitumor immunity and therefore plays an important role in cancer immune surveillance. This has prompted widespread development of STING agonists for cancer immunotherapy, but pharmacological barriers continue to limit the clinical impact of STING agonists and motivate the development of drug delivery systems to improve their efficacy and/or safety. To address these challenges, we developed SAPCon, a STING-activating polymer-drug conjugate platform based on strain-promoted azide-alkyne cycloaddition of dimeric-amidobenzimidazole (diABZI) STING agonists to hydrophilic polymer chains through an enzyme-responsive chemical linker. To synthesize a first-generation SAPCon, we designed a diABZI prodrug modified with a DBCO reactive handle with a cathepsin B-cleavable spacer for intracellular drug release and conjugated this to pendant azide groups on a 100kDa poly(dimethyla acrylamide-co-azide methacrylate) copolymer backbone to increase circulation time and enable passive tumor accumulation. We found that intravenously administered SAPCon accumulated at tumor sites, where it was endocytosed by tumor-associated myeloid cells, resulting in increased STING activation in tumor tissue. Consequently, SAPCon promoted an immunogenic tumor microenvironment, characterized by increased frequency of activated macrophages and dendritic cells and improved infiltration of CD8+ T cells, resulting in inhibition of tumor growth, prolonged survival, and enhanced response to anti-PD-1 immune checkpoint blockade in orthotopic breast cancer models. Collectively, these studies position SAPCon as a modular and programmable platform for improving the efficacy of systemically administered STING agonists for cancer immunotherapy.

bioengineering↗

bioRxiv2022

Cell-free prototyping enables implementation of optimized reverse beta-oxidation pathways in heterotrophic and autotrophic bacteria

Carbon-negative synthesis of biochemical products has the potential to mitigate global CO2 emissions. An attractive route to do this is the reverse {beta}-oxidation (r-BOX) pathway coupled to the Wood-Ljungdahl pathway. Here, we optimized and implemented r-BOX for the synthesis of C4-C6 acids and alcohols. With a high-throughput in vitro prototyping workflow, we screened 762 unique pathway combinations using cell-free extracts tailored for r-BOX to identify enzyme sets for enhanced product selectivity. Implementation of these pathways into Escherichia coli generated designer strains for the selective production of butanoic acid (4.9 {+/-}0.1 gL-1), hexanoic acid (3.06 {+/-} 0.03 gL-1) and 1-hexanol (1.0 {+/-} 0.1 gL-1) at the best performance reported to date in this bacterium. We also generated Clostridium autoethanogenum strains able to produce 1-hexanol from syngas, achieving a titer of 0.26 gL-1 in a 1.5-L continuous fermentation. Our strategy enables optimization of rBOX derived products for biomanufacturing and industrial biotechnology.

synthetic biology↗