Nanoporous Crystalline Materials for the Recognition and Applications of Nucleic Acids

Advanced Materials, Journal Year: 2023, Volume and Issue: unknown

Published: Aug. 24, 2023

Nucleic acid plays a crucial role in countless biological processes. Hence, there is great interest its detection and analysis various fields from chemistry, biology, to medicine. Nanoporous crystalline materials exhibit enormous potential as an effective platform for nucleic recognition application. These have highly ordered uniform pore structures, well adjustable surface chemistry size, making them good carriers extraction, detection, delivery. In this review, the latest developments nanoporous materials, including metal organic frameworks (MOFs), covalent (COFs), supramolecular (SOFs) applications are discussed. Different strategies functionalizing these explored specifically identify targets. Their selective separation of acids highlighted. They can also be used DNA/RNA sensors, gene delivery agents, host DNAzymes, DNA-based computing. Other include catalysis, data storage, biomimetics. The development novel with enhanced biocompatibility has opened up new avenues therapy, paving way sensitive, selective, cost-effective diagnostic therapeutic tools widespread applications.

Language: Английский

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Advances in machine-learning approaches to RNA-targeted drug design

Artificial Intelligence Chemistry, Journal Year: 2024, Volume and Issue: 2(1), P. 100053 - 100053

Published: Feb. 6, 2024

RNA molecules play multifaceted functional and regulatory roles within cells have garnered significant attention in recent years as promising therapeutic targets. With remarkable successes achieved by artificial intelligence (AI) different fields such computer vision natural language processing, there is a growing imperative to harness AI's potential computer-aided drug design (CADD) discover novel compounds that target RNA. Although machine-learning (ML) approaches been widely adopted the discovery of small targeting proteins, application ML model interactions between molecule still its infancy. Compared protein-targeted discovery, major challenges ML-based RNA-targeted stem from scarcity available data resources. interest development curated databases focusing on molecule, field anticipates rapid growth opening new avenue for disease treatment. In this review, we aim provide an overview advancements computationally modeling RNA-small context with particular emphasis methodologies employing techniques.

Language: Английский

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Technologies for Targeted RNA Degradation and Induced RNA Decay

Chemical Reviews, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 5, 2024

The vast majority of the human genome codes for RNA, but RNA-targeting therapeutics account a small fraction approved drugs. As such, there is great incentive to improve old and develop new approaches RNA targeting. For many targeting modalities, just binding not sufficient exert therapeutic effect; thus, targeted degradation induced decay emerged as powerful with pronounced biological effect. This review covers origins advanced use cases degrader technologies grouped by nature modality well mode degradation. It both well-established methods clinically successful platforms such interference, emerging recruitment quality control machinery, CRISPR, direct We also share our thoughts on biggest hurdles in this field, possible ways overcome them.

Language: Английский

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Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA

RNA, Journal Year: 2023, Volume and Issue: 29(4), P. 473 - 488

Published: Jan. 24, 2023

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these functions are rare. Machine learning other computational methods well poised to fill gaps knowledge overcome the inherent challenges targeting, such as dynamic nature difficulty obtaining high-resolution structures. Successful tools date include principal component analysis, linear discriminate k-nearest neighbor, artificial neural networks, multiple regression, many others. Employment has revealed critical factors for selective recognition RNA:small complexes, predictable differences RNA- protein-binding ligands, quantitative structure activity relationships allow rational design molecules given target. Herein we present our perspective on value using machine computation advance including select examples their validation necessary promising future directions will be key accelerate discoveries this important field.

Language: Английский

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Functional microRNA-targeting drug discovery by graph-based deep learning

Patterns, Journal Year: 2024, Volume and Issue: 5(1), P. 100909 - 100909

Published: Jan. 1, 2024

MicroRNAs are recognized as key drivers in many cancers but targeting them with small molecules remains a challenge. We present RiboStrike, deep-learning framework that identifies against specific microRNAs. To demonstrate its capabilities, we applied it to microRNA-21 (miR-21), known driver of breast cancer. ensure selectivity toward miR-21, performed counter-screens miR-122 and DICER. Auxiliary models were used evaluate toxicity rank the candidates. Learning from various datasets, screened pool nine million identified eight, three which showed anti-miR-21 activity both reporter assays RNA sequencing experiments. Target these compounds was assessed using microRNA profiling analysis. The top candidate tested xenograft mouse model cancer metastasis, demonstrating significant reduction lung metastases. These results RiboStrike's ability nominate target miRNAs

Language: Английский

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Competitive Microarray Screening Reveals Functional Ligands for the DHX15 RNA G-Quadruplex

ACS Medicinal Chemistry Letters, Journal Year: 2024, Volume and Issue: 15(6), P. 814 - 821

Published: May 2, 2024

RNAs are increasingly considered valuable therapeutic targets, and the development of methods to identify validate both RNA targets ligands is more important than ever. Here, we utilized a bioinformatic approach hairpin-containing G-quadruplex (rG4) in 5' untranslated region (5' UTR) DHX15 mRNA. By using novel competitive small molecule microarray (SMM) approach, identified compound that specifically binds rG4 (K D = 12.6 ± 1.0 μM). This directly impacts translation reporter mRNA vitro, binding our (F1) structure inhibits up 57% (IC50 22.9 3.8 methodology allowed us target cancer-relevant helicase with no known inhibitors. Our identification method novelty screening make work informative for future cancer therapeutics targets.

Language: Английский

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Advances and Mechanisms of RNA–Ligand Interaction Predictions

Life, Journal Year: 2025, Volume and Issue: 15(1), P. 104 - 104

Published: Jan. 15, 2025

The diversity and complexity of RNA include sequence, secondary structure, tertiary structure characteristics. These elements are crucial for RNA's specific recognition other molecules. With advancements in biotechnology, RNA-ligand structures allow researchers to utilize experimental data uncover the mechanisms complex interactions. However, determining these complexes experimentally can be technically challenging often results low-resolution data. Many machine learning computational approaches have recently emerged learn multiscale-level features predict Predicting interactions remains an unexplored area. Therefore, studying is essential understanding biological processes. In this review, we analyze interaction characteristics by examining structure. Our goal clarify how specifically recognizes ligands. Additionally, systematically discuss methods predicting guide future research directions. We aim inspire creation more reliable prediction tools.

Language: Английский

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Ligand-binding pockets in RNA and where to find them

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(17)

Published: April 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.

Language: Английский

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Physicochemical Principles Driving Small Molecule Binding to RNA

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 2, 2024

Abstract The possibility of using RNA-targeting small molecules to treat diseases is gaining traction as the next frontier drug discovery and development. chemical characteristics that bind RNA are still relatively poorly understood, particularly in comparison protein-targeting molecules. To fill this gap, we have generated an unprecedented amount RNA-small molecule binding data, used it derive physicochemical rules thumb could be define areas space enriched for binders - Small Targeting (STaR) thumb. These been applied publicly available datasets found largely generalizable. Furthermore, a number patented compounds FDA-approved also pass these rules, well key approved case studies including Risdiplam. We anticipate work will significantly accelerate exploration RNA-targeted space, towards unlocking RNA’s potential target. Graphical

Language: Английский

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LncRNAs: the good, the bad, and the unknown

Biochemistry and Cell Biology, Journal Year: 2023, Volume and Issue: 102(1), P. 9 - 27

Published: Aug. 14, 2023

Long non-coding RNAs (lncRNAs) are significant contributors in maintaining genomic integrity through epigenetic regulation. LncRNAs can interact with chromatin-modifying complexes both

Language: Английский

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