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Andreas Plückthun

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Open access Jul 2026

Docking of virtual libraries identifies small-molecule agonists of neurotensin receptors with analgesic activity

Peptide-activated G protein-coupled receptors (GPCRs) play crucial roles in numerous diseases, but remain difficult therapeutic targets due to the challenges in developing small-molecule drugs. Here, we explore structure-based strategies to identify small-molecule agonists of neurotensin (NTS) receptors, which hold promise for developing non-opioid analgesics. Chemical libraries of drug-like molecules are first designed based on a receptor-peptide complex, and then 14.5 million compounds are computationally docked to the orthosteric binding site of the NTS1 receptor. A set of 39 top-ranked compounds is synthesized, and seven of these are experimentally confirmed to activate the NTS1 receptor. Structure-guided optimization yields NTS1 ligands with signaling signatures distinct from the endogenous peptide, and these compounds also exhibit high affinity for the NTS2 receptor. High-resolution crystal structures of two agonists bound to the NTS1 receptor confirm predicted binding modes and reveal key determinants of activation. In vivo, the compounds produce robust antinociception in rodents without inducing hypotension, consistent with a contribution of NTS2 receptor activity. To facilitate broader application of our virtual screening approach to peptide-binding GPCRs, we provide access to tailored chemical libraries containing billions of readily synthesizable compounds. In this work, small-molecule ligands of neurotensin receptors were identified using structure-based virtual screening, leading to the discovery of potent agonists with in vivo antinociceptive effects and to insights into the molecular basis of receptor activation.

Nicolas Panel, D. D. Vo, H. Hübner et al. · 0 citations
Review Open access Jul 2026

Protein engineering: status report

Abstract With this status report, we aim to provide a timely snapshot of the protein engineering field as a broad and rapidly advancing discipline that integrates computational, molecular biology, structure-guided, evolutionary, and synthetic approaches to create new and improved proteins with tailored structures and useful functions. The report is organized into eight thematic areas spanning core methodologies and major application domains, including enzymes, therapeutics, detection, synthetic biology, and materials. Contributions from experts across these areas highlight both the historical foundations and recent advances in their respective fields, with particular emphasis on the growing influence of machine learning and artificial intelligence-based methods. Emerging from this broad overview is a central message: protein engineering appears to be entering a golden age, defined by a rapidly accelerating pace of progress, even as significant challenges in design, screening, and real-world application remain. Looking ahead, the continued integration of computational and experimental strategies is poised to further accelerate the impact of protein engineering across an expanding range of economically and societally important sectors, from therapeutics and molecular imaging to diagnostics, plastic recycling, and industrial chemistry.

Hui-wang Ai, Frances H. Arnold, Doug Barrick et al. · 0 citations