Exploring treatment options in cancer: Tumor treatment strategies

Signal Transduction and Targeted Therapy, Journal Year: 2024, Volume and Issue: 9(1)

Published: July 17, 2024

Traditional therapeutic approaches such as chemotherapy and radiation therapy have burdened cancer patients with onerous physical psychological challenges. Encouragingly, the landscape of tumor treatment has undergone a comprehensive remarkable transformation. Emerging fervently pursued modalities are small molecule targeted agents, antibody-drug conjugates (ADCs), cell-based therapies, gene therapy. These cutting-edge not only afford personalized precise targeting, but also provide enhanced comfort potential to impede disease progression. Nonetheless, it is acknowledged that these strategies still harbour untapped for further advancement. Gaining understanding merits limitations holds promise offering novel perspectives clinical practice foundational research endeavours. In this review, we discussed different modalities, including drugs, peptide antibody cell therapy, It will detailed explanation each method, addressing their status development, challenges, solutions. The aim assist clinicians researchers in gaining deeper diverse options, enabling them carry out effective advance more efficiently.

Language: Английский

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Past, present, and future of CRISPR genome editing technologies

Cell, Journal Year: 2024, Volume and Issue: 187(5), P. 1076 - 1100

Published: Feb. 1, 2024

Genome editing has been a transformative force in the life sciences and human medicine, offering unprecedented opportunities to dissect complex biological processes treat underlying causes of many genetic diseases. CRISPR-based technologies, with their remarkable efficiency easy programmability, stand at forefront this revolution. In Review, we discuss current state CRISPR gene technologies both research therapy, highlighting limitations that constrain them technological innovations have developed recent years address them. Additionally, examine summarize landscape applications context health therapeutics. Finally, outline potential future developments could shape coming years.

Language: Английский

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Artificial Intelligence for Drug Discovery: Are We There Yet?

The Annual Review of Pharmacology and Toxicology, Journal Year: 2023, Volume and Issue: 64(1), P. 527 - 550

Published: Sept. 22, 2023

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) accelerate effective treatment development while reducing costs animal experiments. AI transforming drug discovery, indicated by increasing interest from investors, industrial academic scientists, legislators. Successful requires optimizing properties related pharmacodynamics, pharmacokinetics, clinical outcomes. This review discusses the use of in three pillars discovery: diseases, targets, therapeutic modalities, with a focus on small molecule drugs. technologies, generative chemistry, machine learning, multi-property optimization, have enabled several compounds enter trials. The scientific community must carefully vet known information address reproducibility crisis. full potential can only be realized sufficient ground truth appropriate human intervention at later pipeline stages.

Language: Английский

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Tribulations and future opportunities for artificial intelligence in precision medicine

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: April 30, 2024

Abstract Upon a diagnosis, the clinical team faces two main questions: what treatment, and at dose? Clinical trials' results provide basis for guidance support official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate reported response from relevant trials. The decision complexity increases with combination treatments where drugs administered together can interact each other, which is often case. Additionally, individual's treatment varies changes in condition. In practice, drug dose selection depend significantly on medical protocol team's experience. As such, are inherently varied suboptimal. Big data Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit application. AI rapidly evolving dynamic field potential revolutionize various aspects of human life. has become increasingly crucial discovery development. enhances across different disciplines, such medicinal chemistry, molecular cell biology, pharmacology, pathology, practice. addition these, contributes patient population stratification. need healthcare evident it aids enhancing accuracy ensuring quality care necessary effective treatment. pivotal improving success rates increasing significance discovery, development, trials underscored by many scientific publications. Despite numerous advantages AI, advancing Precision Medicine (PM) remote monitoring, unlocking its full requires addressing fundamental concerns. These concerns include quality, lack well-annotated large datasets, privacy safety issues, biases algorithms, legal ethical challenges, obstacles related cost implementation. Nevertheless, integrating medicine will improve diagnostic outcomes, contribute more efficient delivery, reduce costs, facilitate better experiences, making sustainable. This article reviews applications development sustainable, highlights limitations applying AI.

Language: Английский

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Brainwide silencing of prion protein by AAV-mediated delivery of an engineered compact epigenetic editor

Science, Journal Year: 2024, Volume and Issue: 384(6703)

Published: June 27, 2024

Prion disease is caused by misfolding of the prion protein (PrP) into pathogenic self-propagating conformations, leading to rapid-onset dementia and death. However, elimination endogenous PrP halts progression. In this study, we describe Coupled Histone tail for Autoinhibition Release Methyltransferase (CHARM), a compact, enzyme-free epigenetic editor capable silencing transcription through programmable DNA methylation. Using histone H3 tail-Dnmt3l fusion, CHARM recruits activates methyltransferases, thereby reducing transgene size cytotoxicity. When delivered mouse brain systemic injection adeno-associated virus (AAV), Prnp -targeted ablates expression across brain. Furthermore, have temporally limited implementing kinetically tuned self-silencing approach. potentially represents broadly applicable strategy suppress proteins, including those implicated in other neurodegenerative diseases.

Language: Английский

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Epigenome editing technologies for discovery and medicine

Nature Biotechnology, Journal Year: 2024, Volume and Issue: 42(8), P. 1199 - 1217

Published: July 29, 2024

Language: Английский

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Site-saturation mutagenesis of 500 human protein domains

Nature, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Abstract Missense variants that change the amino acid sequences of proteins cause one-third human genetic diseases 1 . Tens millions missense exist in current population, and vast majority these have unknown functional consequences. Here we present a large-scale experimental analysis across many different proteins. Using DNA synthesis cellular selection experiments quantify effect more than 500,000 on abundance 500 protein domains. This dataset reveals 60% pathogenic reduce stability. The contribution stability to fitness varies is particularly important recessive disorders. We combine measurements with language models annotate sites Mutational effects are largely conserved homologous domains, enabling accurate prediction entire families using energy models. Our data demonstrate feasibility assaying at scale provides large consistent reference for clinical variant interpretation training benchmarking computational methods.

Language: Английский

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Geometric deep learning of protein–DNA binding specificity

Nature Methods, Journal Year: 2024, Volume and Issue: 21(9), P. 1674 - 1683

Published: Aug. 5, 2024

Predicting protein-DNA binding specificity is a challenging yet essential task for understanding gene regulation. Protein-DNA complexes usually exhibit to selected DNA target site, whereas protein binds, with varying degrees of specificity, wide range sequences. This information not directly accessible in single structure. Here, access this information, we present Deep Predictor Binding Specificity (DeepPBS), geometric deep-learning model designed predict from DeepPBS can be applied experimental or predicted structures. Interpretable heavy atom importance scores interface residues extracted. When aggregated at the residue level, these are validated through mutagenesis experiments. Applied proteins targeting specific sequences, was demonstrated experimentally measured specificity. offers foundation machine-aided studies that advance our molecular interactions and guide designs synthetic biology.

Language: Английский

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Mutations to transcription factor MAX allosterically increase DNA selectivity by altering folding and binding pathways

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 14, 2025

Understanding how proteins discriminate between preferred and non-preferred ligands ('selectivity') is essential for predicting biological function a central goal of protein engineering efforts, yet the biophysical mechanisms underpinning selectivity remain poorly understood. Towards this end, we study variants promiscuous transcription factor (TF) MAX (H. sapiens) alter DNA specificity selectivity, yielding >1700 Kds >500 rate constants in complex with multiple sequences. Twenty-two 240 assayed point mutations enhance none these occur at residues that contact nucleotides published structures. By applying thermodynamic kinetic models to results previous observations highly similar far more selective TF Pho4 (S. cerevisiae), find by altering partitioning or affinity within conformations different intrinsic providing mechanistic basis allosteric modulation ligand selectivity. These highlight importance conformational heterogeneity determining sequence can guide future efforts engineer proteins. In work, high-throughput microfluidic assays reveal substitutions folding-and-binding pathways shape landscapes human MAX.

Language: Английский

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Manipulating the 3D organization of the largest synthetic yeast chromosome

Molecular Cell, Journal Year: 2023, Volume and Issue: 83(23), P. 4424 - 4437.e5

Published: Nov. 8, 2023

Whether synthetic genomes can power life has attracted broad interest in the biology field. Here, we report de novo synthesis of largest eukaryotic chromosome thus far, synIV, a 1,454,621-bp yeast resulting from extensive genome streamlining and modification. We developed megachunk assembly combined with hierarchical integration strategy, which significantly increased accuracy flexibility construction. Besides drastic sequence changes, further manipulated 3D structure synIV to explore spatial gene regulation. Surprisingly, found few expression suggesting that positioning inside nucleoplasm plays minor role Lastly, tethered inner nuclear membrane via its hundreds loxPsym sites observed transcriptional repression entire chromosome, demonstrating chromosome-wide transcription manipulation without changing DNA sequences. Our sheds light on higher-order architectural design genomes.

Language: Английский

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