Biology subjects

Kritzer, J.

Publications and source records attributed to Kritzer, J..

7 recordsLinked to original sources

bioRxiv2026

BoltzMol-1: Towards Reliable Virtual Screening for Fast and Cost-Effective Hit Discovery

We present BoltzMol-1, a small-molecule hit discovery pipeline, centered on an optimized version of Boltz-2, explicitly adapted for prospective discovery. Reliable hit discovery that generalizes across target classes (rather than only the well-characterized families that dominate existing ligand data) would broaden the range of biology accessible to small-molecule intervention and reduce reliance on resource-intensive high-throughput screening. Towards this goal, the system prioritizes compounds for rapid experimental validation by coupling model-driven ranking with streamlined procurement from commercial catalogs. To improve developability at the point of selection, we introduce a suite of ADMET models for kinetic solubility (logS), lipophilicity (logD), and Caco-2 permeability. These models act as an early triage layer, systematically filtering out compounds with unfavorable physicochemical and absorption properties prior to synthesis or purchase. Across a panel of ten targets (most with no representation in the underlying affinity training data) we observe strong prospective performance on challenging systems. Functional actives or binders were identified for 6 of 10 targets, despite modest experimental budgets of 28-96 compounds per target. These results include successes on receptors and enzymes traditionally considered difficult for structure- or ligand-based approaches. Collectively, this work establishes a practical framework for low-throughput, cost-constrained discovery campaigns capable of delivering chemically tractable binders with favorable property profiles. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/736485v1_fig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1d7ff06org.highwire.dtl.DTLVardef@1a7fc7aorg.highwire.dtl.DTLVardef@1b0dc98org.highwire.dtl.DTLVardef@62b978_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO Overview of the prospective virtual-screening campaigns across all targets. For each target, the panel shows the predicted protein-ligand complex together with the number of compounds tested, the number of confirmed actives/binders, and the assays used for screening and follow-up. C_FIG

biochemistry↗

bioRxiv2026

Design and Evolution of an Orthogonal HaloTag for Multiplexed Labeling in Cells

The self-labeling protein HaloTag is used to install a wide variety of functional small molecules in cells and living organisms with exquisite specificity with respect to cell type and subcellular localization. HaloTag is a core part of many biotechnology-based tools for sensing, tracking, and manipulating biological systems with a high degree of spatial and temporal control. Due to the limitations of fluorescent proteins and other self-labeling proteins, most of these tools have historically been restricted to a single channel. In this work, we used structure-guided rational design and directed evolution to produce an orthogonal HaloTag protein called OrthoTag which reacts selectively with a modified chloroalkane substrate. OrthoTag retains many of HaloTags superior properties, and reaction rate measurements show OrthoTag and its substrate have 60-fold mutual orthogonality to HaloTag. We demonstrate the application of OrthoTag for multiplexed labeling experiments in mammalian cells with minimal optimization. Going forward, OrthoTag can be directly incorporated into any HaloTag-based system to allow simultaneous measurement or manipulation of two biological targets or processes. The availability of multiple high-performance self-labeling proteins will enable the continued development of new multiplexed biotechnology methods.

biochemistry↗

bioRxiv2026

Minimal N-methylated and stapled peptide ligands for the autophagy protein GABARAP

The LC3/GABARAP protein family is a promising target for selective inhibition of autophagy. Further, LC3/GABARAP ligands have been used as targeted degraders of soluble proteins, protein aggregates, mitochondria, lipid droplets, and RNA. However, the small molecules used for such applications have poor binding affinity and known off-target effects. LC3/GABARAP proteins are challenging targets for small-molecule drug development due to their long, shallow binding grooves. In this work, we evaluate multiple approaches to stabilizing the extended structure of the native binding motif, producing N-methylated peptides and stapled peptides with low nanomolar affinity. A crystal structure and molecular dynamics simulations support a model where the N-methylation pre-organizes the motif into an extended, strand-like structure. N-methylation allowed minimization of the binding motif to a tetrapeptide that retained sub-micromolar affinity while minimizing charge and overall molecular weight. The truncated, N-methylated tetrapeptide showed passive permeability in artificial membrane and cell-based transwell assays. These results highlight new drug-like space for LC3/GABARAP ligands with high affinity and subfamily selectivity. Table of Contents GraphicDrawn and developed by Mollie McGibbon and Joshua Kritzer O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/710535v2_ufig1.gif" ALT="Figure 1"> View larger version (68K): org.highwire.dtl.DTLVardef@1b74a1org.highwire.dtl.DTLVardef@861c09org.highwire.dtl.DTLVardef@9abc2corg.highwire.dtl.DTLVardef@b7f745_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Accurate de novo design of high-affinity protein binding macrocycles using deep learning

The development of macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource-intensive and provide little control over binding mode. Despite considerable progress in physics-based methods for peptide design and deep-learning methods for protein design, there are currently no robust approaches for de novo design of protein-binding macrocycles. Here, we introduce RFpeptides, a denoising diffusion-based pipeline for designing macrocyclic peptide binders against protein targets of interest. We test 20 or fewer designed macrocycles against each of four diverse proteins and obtain medium to high-affinity binders against all selected targets. Designs against MCL1 and MDM2 demonstrate KD between 1-10 M, and the best anti-GABARAP macrocycle binds with a KD of 6 nM and a sub-nanomolar IC50 in vitro. For one of the targets, RbtA, we obtain a high-affinity binder with KD < 10 nM despite starting from the target sequence alone due to the lack of an experimentally determined target structure. X-ray structures determined for macrocycle-bound MCL1, GABARAP, and RbtA complexes match very closely with the computational design models, with three out of the four structures demonstrating Ca RMSD of less than 1.5 [A] to the design models. In contrast to library screening approaches for which determining binding mode can be a major bottleneck, the binding modes of RFpeptides-generated macrocycles are known by design, which should greatly facilitate downstream optimization. RFpeptides thus provides a powerful framework for rapid and custom design of macrocyclic peptides for diagnostic and therapeutic applications.

biochemistry↗

bioRxiv2024

Comparing cell penetration of biotherapeutics across human cell lines

A major obstacle in biotherapeutics development is maximizing cell penetration. Ideally, assays would allow for optimization of cell penetration in the cell type of interest early in the drug development process. However, few assays exist to compare cell penetration across different cell types, independent of drug function. In this work, we applied the chloroalkane penetration assay (CAPA) in seven mammalian cell lines as well as primary cells. Careful controls were used to ensure data could be compared across cell lines. We compared the penetration of several peptides and drug-like oligonucleotides and saw significant differences among the cell lines. To help explain these differences, we quantified the relative activities of endocytosis pathways in these cell lines and correlated them with the penetration data. Based on these results, we knocked down clathrin in a cell line with an efficient permeability profile and observed reduced penetration of peptides, but not oligonucleotides. Finally, we used small-molecule endosomal escape enhancers and observed enhancement of cell penetration of some oligonucleotides, but only in some of the cell lines tested. CAPA data provide valuable points of comparison among different cell lines, including primary cells, for evaluating the cell penetration of various classes of peptides and oligonucleotides. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/587257v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@9e75e9org.highwire.dtl.DTLVardef@14f209forg.highwire.dtl.DTLVardef@1e6cd59org.highwire.dtl.DTLVardef@1b3aabb_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2024

Exploring Arylidene-Indolinone Ligands of Autophagy Proteins LC3B and GABARAP

We report the first structure-activity studies of arylidene-indolinone compound GW5074 which was reported as a ligand of autophagy-related protein LC3B. The literature has conflicting information on the binding affinity of this compound and there is some debate regarding its use as a component of autophagy-dependent degrader compounds. We developed an AlphaScreen assay to measure competitive inhibition of the binding of known peptide ligands to LC3B and its paralog GABARAP. 18 analogs were synthesized and tested against both proteins. Inhibitory potencies were found to be in the mid- to high micromolar range. 2D-NMR data revealed the binding site on GABARAP as hydrophobic pocket 1, where native peptide ligands bind with an aromatic side chain. Our results suggest that GW5074 binds LC3B and GABARAP with micromolar affinity. These affinities could support further exploration in targeted protein degradation, but only if off-target effects and poor solubility can be appropriately addressed.

biochemistry↗

bioRxiv2023

BenzoHTag, a fluorogenic self-labeling enzyme developed using molecular evolution

Self-labeling proteins are powerful tools in chemical biology as they enable the precise cellular localization of a synthetic molecule, often a fluorescent dye, with the genetic specificity of a protein fusion. HaloTag7 is the most popular self-labeling protein due to its fast labeling kinetics and the simplicity of its chloroalkane ligand. Reaction rates of HaloTag7 with different chloroalkane-containing substrates is highly variable and rates are only very fast for rhodamine-based dyes. This is a major limitation for the HaloTag system because fast labeling rates are critical for live-cell assays. Here, we report a molecular evolution system for HaloTag using yeast surface display that enables the screening of libraries up to 108 variants to improve reaction rates with any substrate of interest. We applied this method to produce a HaloTag variant, BenzoHTag, which has improved performance with a fluorogenic benzothiadiazole dye. The resulting system has improved brightness and conjugation kinetics, allowing for robust, no-wash fluorescent labeling in live cells. The new BenzoHTag-benzothiadiazole system has improved performance in live-cell assays compared to the existing HaloTag7-silicon rhodamine system, including saturation of intracellular enzyme in under 100 seconds and robust labeling at dye concentrations as low as 7 nM. It was also found to be orthogonal to the silicon HaloTag7-rhodamine system, enabling multiplexed no-wash labeling in live cells. The BenzoHTag system, and the ability to optimize HaloTag for a broader collection of substrates using molecular evolution, will be very useful for the development of cell-based assays for chemical biology and drug development.

biochemistry↗