Ligand-binding pockets in RNA, and where to find them

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Март 15, 2025

ABSTRACT RNAs are critical regulators of gene expression, and their functions often mediated by complex secondary tertiary structures. Structured regions in RNA can selectively interact with small molecules – via well-defined ligand binding pockets to modulate the regulatory repertoire an RNA. The broad potential biological function intentionally RNA-ligand interactions remains unrealized, however, due challenges identifying compact motifs ability bind ligands good physicochemical properties (often termed drug-like). Here, we devise fpocketR , a computational strategy that accurately detects capable drug-like Remarkably few, roughly 50, such have ever been visualized. We experimentally confirmed ligandability novel detected using fragment-based approach introduced here, Frag-MaP, ligand-binding sites cells. Analysis validated Frag-MaP reveals dozens newly identified able ligands, supports model for structural quality creates framework understanding ligand-ome.

Язык: Английский

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Promotion of TLR7-MyD88-dependent inflammation and autoimmunity in mice through stem-loop changes in Lnc-Atg16l1

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Ноя. 25, 2024

Uncontrolled TLR signaling can cause inflammatory immunopathology and trigger autoimmune diseases. For example, TLR7 promotes pathogenesis of systemic lupus erythematosus. However, whether RNA structural changes affect nucleic acids-sensing TLRs impact disease progression is unclear. Here by iCLIP-seq we identify a TLR7-binding long non-coding RNA, Lnc-Atg16l1, find that it other MyD88-dependent in various types immune cells. Depletion Lnc-Atg16l1 attenuates development TLR7-linked phenotypes the mouse SLE model. Mechanistically, binds to at bases near U84 MyD88 around A129. The analysis situ structures show strengthens interaction between TIR domain through specific stem-loop structure as molecular scaffold after activation promote downstream signaling. Therefore, discover mechanism for host regulation innate its changes. These findings provide insights into pro-inflammatory function self structure-dependent manner suggest potential target TLR-related disorders.

Язык: Английский

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Computational advances in discovering cryptic pockets for drug discovery

Current Opinion in Structural Biology, Год журнала: 2025, Номер 90, С. 102975 - 102975

Опубликована: Янв. 7, 2025

Язык: Английский

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The Physics-AI Dialogue in Drug Design

RSC Medicinal Chemistry, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

A long path has led from the determination of first protein structure in 1960 to recent breakthroughs science. Protein prediction and design methodologies based on machine learning (ML) have been recognized with 2024 Nobel prize Chemistry, but they would not possible without previous work input many domain scientists. Challenges remain application ML tools for structural ensembles their usage within software pipelines by crystallography or cryogenic electron microscopy. In drug discovery workflow, techniques are being used diverse areas such as scoring docked poses, generation molecular descriptors. As become more widespread, novel applications emerge which can profit large amounts data available. Nevertheless, it is essential balance potential advantages against environmental costs deployment decide if when best apply it. For hit lead optimization efficiently interpolate between compounds chemical series free energy calculations dynamics simulations seem be superior designing derivatives. Importantly, complementarity and/or synergism physics-based methods (e.g., force field-based simulation models) data-hungry growing strongly. Current evolved decades research. It now necessary biologists, physicists, computer scientists fully understand limitations ensure that exploited design.

Язык: Английский

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RNAmigos2: accelerated structure-based RNA virtual screening with deep graph learning

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Март 21, 2025

Abstract RNAs are a vast reservoir of untapped drug targets. Structure-based virtual screening (VS) identifies candidate molecules by leveraging binding site information, traditionally using molecular docking simulations. However, struggles to scale with large compound libraries and RNA Machine learning offers solution but remains underdeveloped for due limited data practical evaluations. We introduce data-driven VS pipeline tailored RNA, utilizing coarse-grained 3D modeling, synthetic augmentation, RNA-specific self-supervision. Our model achieves 10,000x speedup over while ranking active compounds in the top 2.8% on structurally distinct test sets. It is robust variations successfully screens unseen riboswitches 20,000-compound in-vitro microarray, mean enrichment factor 2.93 at 1%. This marks first experimentally validated success structure-based deep VS.

Язык: Английский

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Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

Advanced Engineering Materials, Год журнала: 2025, Номер unknown

Опубликована: Март 26, 2025

The fourth Industrial Revolution facilitates a symbiotic relationship between computational techniques and material development, with special emphasis in the domain of bioinspired materials. This initiative aims to propel interdisciplinary research by integrating technology biomaterials, expediting advancements fabrication design. Computational design simulations also offer an expansive landscape engineer next‐generation biomaterials utilizing nuclei‐acid based materials, spanning from molecular macroscopic levels, guided specific dynamics principles. review provide succinct overview prevailing multiscale utilized ribonucleic acid (RNA)‐based nanomaterials. By elucidating interplay structure function, approaches facilitate creation biomimetic structures tailored properties functionalities for diverse applications. It underscores collaborations, wherein insights natural inspire rational synthesis novel hierarchical using methodologies. Through systematic exploration current paradigms, this endeavors delineate pathways future innovation advancement field RNA‐based fostering transformative impacts across sectors such as healthcare, biotechnology, beyond.

Язык: Английский

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The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning

International Journal of Biological Macromolecules, Год журнала: 2025, Номер 310, С. 143308 - 143308

Опубликована: Апрель 21, 2025

Язык: Английский

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Ligand-binding pockets in RNA and where to find them

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(17)

Опубликована: Апрель 22, 2025

RNAs are critical regulators of gene expression, and their functions often mediated by complex secondary tertiary structures. Structured regions in RNA can selectively interact with small molecules—via well-defined ligand-binding pockets—to modulate the regulatory repertoire an RNA. The broad potential to biological function intentionally via RNA–ligand interactions remains unrealized, however, due challenges identifying compact motifs ability bind ligands good physicochemical properties (often termed drug-like). Here, we devise fpocketR , a computational strategy that accurately detects pockets capable binding drug-like Remarkably few, roughly 50, such have ever been visualized. We experimentally confirmed ligandability novel detected using fragment-based approach introduced here, Frag-MaP, sites cells. Analysis validated Frag-MaP reveals dozens able ligands, supports model for structural quality creates framework understanding ligand-ome.

Язык: Английский

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On the Power and Challenges of Atomistic Molecular Dynamics to Investigate RNA Molecules

Journal of Chemical Theory and Computation, Год журнала: 2024, Номер unknown

Опубликована: Авг. 16, 2024

RNA molecules play a vital role in biological processes within the cell, with significant implications for science and medicine. Notably, functions exerted by specific are often linked to conformational ensemble. However, experimental characterization of such three-dimensional structures is challenged structural heterogeneity its multiple dynamic interactions binding partners as small molecules, proteins, metal ions. Consequently, our current understanding structure–function relationship still limited. In this context, we highlight molecular dynamics (MD) simulations powerful tool complement efforts on RNAs. Despite recognized limitations force fields MD simulations, examining selected RNAs has provided valuable functional insights into their structures.

Язык: Английский

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Machine learning-augmented molecular dynamics simulations (MD) reveal insights into the disconnect between affinity and activation of ZTP riboswitch ligands

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 14, 2024

The challenge of targeting RNA with small molecules necessitates a better understanding RNA-ligand interaction mechanisms. However, the dynamic nature nucleic acids, their ligand-induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs combination computational methods to address these challenges. By integrating structure-informed design, crystallography, machine learning-augmented all-atom molecular dynamics simulations (MD) we synthesized, biophysically biochemically characterized, studied dissociation library molecule activators ZTP riboswitch, ligand-binding motif that regulates bacterial expression. We uncovered key mechanisms, revealing valuable insights into role ligand binding kinetics on riboswitch activation. Further, established on-rates determine activation potency as opposed affinity elucidated structural differences, which provide mechanistic interplay structure

Язык: Английский

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