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Results for “structure-guided design”

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PubMed2026

Targeting SIRT6: the design and therapeutic implications of activators and inhibitors.

Sirtuin 6 (SIRT6) is an NAD+-dependent deacylase that maintains genomic stability, regulates metabolism, and influences aging, making it an attractive but challenging therapeutic target. Pharmacological modulation of SIRT6 holds promise for cancer and metabolic disorders, yet its context-dependent functions demand precise intervention strategies. Potent, selective, and drug-like chemical probes are therefore essential to dissect SIRT6 biology and to validate its therapeutic potential. This review critically evaluates recent medicinal chemistry advances in SIRT6 modulation. We focus on structure-guided design strategies and structure-activity relationships (SAR) that have transformed initial hits into optimized leads for both activators and inhibitors, highlighting the remaining challenges in achieving isoform selectivity and drug-like properties.

Sirtuins↗

PubMed2026

RNA structures regulate norovirus life cycle and enable rational attenuation in vivo.

Viral genomes encode regulatory RNA structures that orchestrate key steps of viral replication and gene expression. Although these structures are increasingly recognized as critical regulators of viral function, their systematic characterization in an infection context and roles in regulating viral fitness and immune recognition in vivo remain limited. Here, we systematically map and functionally interrogate structured RNA elements across the murine norovirus genome using orthogonal in-cell chemical probing, revealing conserved motifs that regulate viral function. Targeted disruption of specific structural elements reduces viral replication in cell culture, modulates translation in cis, and decreases viral RNA levels in animal infection models. These findings enabled the rational design of a genetically stable, attenuated virus that elicits protective immunity and limits viral replication upon secondary challenge. Together, this work uncovers essential roles for RNA structure in norovirus biology and establishes a generalizable framework for RNA structure-guided design of antiviral vaccines and therapeutics.

RNA structure↗

PubMed2026

PMGen: from peptide-MHC structure prediction to peptide generation.

MOTIVATION: Accurate structural modeling of peptide-major histocompatibility complex (pMHC) complexes is essential for structure-driven immunotherapy design, yet current prediction tools suffer from narrow class coverage, restricted peptide lengths, insufficient accuracy, and a lack of built-in structure-aware peptide sampling. Consequently, most mimotope and altered peptide ligand designs rely solely on sequence substitution, leaving spatial and biophysical insights from pMHC structures largely unexploited. RESULTS: We introduce peptide-MHC generator (PMGen), an integrated framework for structure prediction and structure-guided design of variable-length peptides across MHC Class I and II. PMGen enforces anchor constraints within AlphaFold2 through two complementary strategies, initial guess and template engineering, achieving state-of-the-art structural fidelity without model fine-tuning. On a comprehensive benchmark, PMGen outperforms all existing methods, yielding median peptide-core Cα RMSDs of 0.62 Å for MHC-I and 0.33 Å for MHC-II. We show that PMGen can recover incorrectly predicted anchor positions and that AlphaFold pLDDT scores enable sequence-independent binding-core identification. Applied to a published neoantigen/wild-type pair, PMGen accurately captures mutation-induced conformational changes. Beyond structure prediction, we show that ProteinMPNN sampling on PMGen-predicted backbones yields higher affinity peptides while preserving the parental 3D conformation. Using PMGen to generate 63 817 high-confidence pMHC structures as training data, we further improve ProteinMPNN's peptide sequence recovery from 0.14 to 0.64 on a test set of 85 unseen MHC-I alleles, highlighting the value of accurate predicted structures for downstream machine learning tasks. AVAILABILITY AND IMPLEMENTATION: PMGen is freely available at https://github.com/soedinglab/PMGen, with an interactive Colab notebook at https://colab.research.google.com/github/soedinglab/PMGen/blob/master/colab.ipynb.

Peptides↗

PubMed2026

Rational and computation-assisted engineering of a compact and efficient CRISPR-Cas12f genome editor.

The CRISPR-Cas12f system is an ultracompact genome-editing platform, yet only a few orthologs exhibit robust activity in mammalian cells. Here, we systematically screened 23 Cas12f orthologs and identified two active nucleases, PspCas12f1 and TcCas12f1, capable of genome editing in human cells. Single guide RNA (sgRNA) scaffold optimization enhanced the basal activity of PspCas12f1. To further improve its performance, we combined structure-guided rational design with protein language model-assisted filtering. Candidate mutations predicted by SaProt were further screened based on structural proximity to the DNA-binding interface and electrostatic compatibility. This integrative strategy identified Q100R and E293R, whose combination yielded the optimized variant enPspCas12f1. enPspCas12f1 achieved genome-editing efficiencies comparable to SpCas9 across multiple endogenous loci while maintaining high specificity. Collectively, our results demonstrate that integrating protein language model-assisted filtering with structure-guided rational design provides an effective strategy for engineering PspCas12f1 and may facilitate the optimization of additional compact CRISPR nucleases.

CRISPR-Cas12f↗

PubMed2026

Genomic prospecting and biochemical characterization of a novel thermostable 3-quinuclidinone reductase from hot spring metagenomes for efficient biocatalysis.

This study presents the discovery and characterization of a novel thermophilic 3-quinuclidinone reductase (ScQR) identified through metagenomic mining of hot spring environments. ScQR, a member of the short-chain dehydrogenase/reductase (SDR) superfamily, was heterologously expressed in Escherichia coli, and its catalytic properties were systematically characterized. The enzyme demonstrates exceptional thermal stability, retaining 86% of its activity after 48 hours at 70°C. Furthermore, K+ and Mg²+ ions significantly enhanced ScQR's activity at specific concentrations. Structural analysis revealed that ScQR adopts a typical SDR fold with a conserved catalytic triad (S141-Y155-K159), and it is NAD(H) dependent. Enzyme assays indicated that ScQR is highly stereoselective for (R)-3-quinuclidinol, with no activity against its enantiomer, (S)-3-quinuclidinol. The enzyme exhibits optimal activity at pH 9 and 85°C, making it a promising candidate for industrial applications requiring high thermal stability. Molecular dynamics simulations further revealed that ScQR preserves global structural integrity up to 360 K, whereas higher temperatures induce destabilization, predominantly in the C-terminal region and residues 95-100. In addition, structure-guided computational design enabled by LigandMPNN and UniKP yielded three ScQR variants with improved substrate affinity and catalytic efficiency while maintaining the overall fold and function. This work underscores the power of metagenomics with structure-driven protein design in discovering novel enzymes with unique catalytic properties from extreme environments and establishes ScQR as a promising biocatalyst for biotechnological and pharmaceutical applications.IMPORTANCEThis study reports the discovery of ScQR, a novel thermophilic 3-quinuclidinone reductase identified via metagenomic mining. ScQR represents one of the most heat-resistant members of the SDR superfamily discovered to date, maintaining 86% activity after 48 hours at 70°C. These findings establish ScQR as a robust biocatalyst for high-temperature pharmaceutical applications and demonstrate a scalable workflow for optimizing enzymes from extreme environments, offering significant value to the fields of biocatalysis and protein engineering.

computational design↗

PubMed2026

Structure and evolution-guided design of minimal RNA-guided nucleases.

The design of RNA-guided nucleases with properties not limited by evolution can expand programmable genome-editing capabilities. However, generating diverse multidomain proteins with robust enzymatic properties remains challenging. Here, we use a protein design strategy that couples a structure-guided inverse-folding model with evolution-informed residue constraints to generate active, divergent variants of TnpB, a minimal CRISPR-Cas12-like nuclease, termed SynTnpBs. High-throughput screening of artificial intelligence-generated variants yielded editors that retained or exceeded wild-type activity in bacterial, plant, and human cells. Cryo-electron microscopy-based structure determination of the most divergent variant revealed stabilizing contacts in the RNA-DNA interfaces across conformations, demonstrating the design potential of this approach. Together, these results establish a strategy for creating non-natural RNA-guided nucleases and conformationally active nucleic acid binders, enlarging the designable protein space.

Humans↗

PubMed2026

Development and characterization of triazole-based WDR5 inhibitors for the treatment of glioblastoma.

Glioblastoma (GBM) cancer stem cells (CSCs) contribute to tumor recurrence, treatment resistance, and dismal clinical outcomes. Genetic and pharmacological evidence suggests that the nuclear scaffolding protein WD-repeat containing protein 5 (WDR5) is a therapeutic vulnerability of the CSC population. However, previously reported WDR5 inhibitors display low permeability and are unable to penetrate the blood-brain barrier (BBB), limiting their utility in GBM. Herein, we report the structure-guided development of a series of triazole-based WDR5 WIN-site inhibitors designed to increase passive brain penetration. We identified triazole-based WDR5 inhibitors that are potent, passively permeable, and in some cases more brain penetrant than other scaffolds. We phenotypically assessed our WDR5 inhibitors in a panel of patient-derived CSC models and uncovered unique WDR5-regulated metabolic genes in GBM. We also evaluated their antiproliferative activity against CSCs both in vitro and in vivo. Finally, to identify potential combination opportunities, we screened a 2,100-compound chemical probe library and identified that the ATAD2 inhibitor BAY-850 synergizes with WDR5 inhibitors to enhance CSC killing. Our work diversifies the chemical matter targeting WDR5, clarifies the in vitro consequences of WIN-site inhibition in CSCs, and encourages the future development of next-generation WDR5 inhibitors with the potential to achieve in vivo efficacy in the brain.

Humans↗

PubMed2026

Comprehensive identification of carboxylic acids by using bromine isotope-based chemical isotope labelling and structure-guided molecular network.

Carboxylic acids (CAs) are important contributors to the flavor quality of sauce-flavor Chinese Baijiu, yet their comprehensive analysis remains challenging due to poor ionization efficiency, weak chromatographic retention, and limited annotation capability. Herein, we developed a workflow for the high-coverage discovery and annotation of CAs in Baijiu by coupling chemical isotope labeling-liquid chromatography-mass spectrometry with a structure-guided molecular network strategy (SGMNS). A bromine-containing derivatization reagent, 1-(3-aminopropyl)-3-bromoquinolin-1-ium bromide (APBQ), was designed and synthesized to exploit the natural isotope distribution of bromine and characteristic MS/MS fragmentation behavior. Following APBQ derivatization, the target CAs showed superior chromatographic retention and favorable analytical performance. Based on isotopic peak pairing in MS1 and diagnostic fragment validation in MS2, 372 potential CA derivatives were discovered from pooled Baijiu samples and 355 of them were validated by diagnostic fragments in MS2 spectra. To address the scarcity of derivatized spectral libraries, SGMNS was employed for annotation using a background network constructed from APBQ-labeled candidates derived from the Expanded Chinese Baijiu Compound Database. The developed method was further applied to profile Baijiu samples, revealing pronounced differences in CA composition across the seven fermentation rounds. Notably, rounds 3 to 5 exhibited the largest numbers of differential CAs. This study provided an effective analytical strategy for large-scale CA profiling, offering new insight into the chemical basis of flavor formation during multi-round fermentation of sauce-flavor Baijiu.

Isotope Labeling↗

PubMed2026

Structure-guided discovery of non-catechol dopamine D1 receptor ligands with biased agonism and antagonism.

The catechol L-DOPA, a cornerstone of Parkinson's disease (PD) treatment, has two major drawbacks: poor pharmacokinetics and, more significantly, debilitating dyskinesias from chronic dopamine D1 receptor (D1R) activation. Preclinical rodent studies suggest that D1R antagonism or β-arrestin-biased agonism can alleviate these motor complications, highlighting the need for next-generation non-catechol ligands. Through virtual screening, we identified eight novel chemotypes as D1R ligands, including two G protein-biased agonists, two β-arrestin-biased agonists and four antagonists. Structure-activity relationship (SAR) optimization led to the development of A82R, a non-catechol D1R antagonist (Ki 733 nM) with high D1 family over D2 family selectivity. Additionally, we present A69, a novel non-catechol β-arrestin-biased partial agonist for D1R (Ki 86.9 nM, stronger than representative D1R commercial drugs) with a sustained half-life of 1 h in the mouse brain. We show that the observed selectivity patterns are consistent with structural and information-theoretic limits on dopamine's ability to encode receptor subtype identity. Within these bounds, the non-catechol ligand chemotypes represent promising leads for developing therapies that modulate D1R signaling and reduce L-DOPA-induced dyskinesia in PD.

Receptors, Dopamine D1↗