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1.
Health Data Sci ; 4: 0113, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38486623

RESUMO

Background: In real-world drug discovery, human experts typically grasp molecular knowledge of drugs and proteins from multimodal sources including molecular structures, structured knowledge from knowledge bases, and unstructured knowledge from biomedical literature. Existing multimodal approaches in AI drug discovery integrate either structured or unstructured knowledge independently, which compromises the holistic understanding of biomolecules. Besides, they fail to address the missing modality problem, where multimodal information is missing for novel drugs and proteins. Methods: In this work, we present KEDD, a unified, end-to-end deep learning framework that jointly incorporates both structured and unstructured knowledge for vast AI drug discovery tasks. The framework first incorporates independent representation learning models to extract the underlying characteristics from each modality. Then, it applies a feature fusion technique to calculate the prediction results. To mitigate the missing modality problem, we leverage sparse attention and a modality masking technique to reconstruct the missing features based on top relevant molecules. Results: Benefiting from structured and unstructured knowledge, our framework achieves a deeper understanding of biomolecules. KEDD outperforms state-of-the-art models by an average of 5.2% on drug-target interaction prediction, 2.6% on drug property prediction, 1.2% on drug-drug interaction prediction, and 4.1% on protein-protein interaction prediction. Through qualitative analysis, we reveal KEDD's promising potential in assisting real-world applications. Conclusions: By incorporating biomolecular expertise from multimodal knowledge, KEDD bears promise in accelerating drug discovery.

2.
Angew Chem Int Ed Engl ; 62(51): e202315093, 2023 Dec 18.
Artigo em Inglês | MEDLINE | ID: mdl-37906116

RESUMO

DNA nanostructures have played an important role in the development of novel drug delivery systems. Herein, we report a DNA origami-based CRISPR/Cas9 gene editing system for efficient gene therapy in vivo. In our design, a PAM-rich region precisely organized on the surface of DNA origami can easily recruit and load sgRNA/Cas9 complex by PAM-guided assembly and pre-designed DNA/RNA hybridization. After loading the sgRNA/Cas9 complex, the DNA origami can be further rolled up by the locking strands with a disulfide bond. With the incorporation of DNA aptamer and influenza hemagglutinin (HA) peptide, the cargo-loaded DNA origami can realize the targeted delivery and effective endosomal escape. After reduction by GSH, the opened DNA origami can release the sgRNA/Cas9 complex by RNase H cleavage to achieve a pronounced gene editing of a tumor-associated gene for gene therapy in vivo. This rationally developed DNA origami-based gene editing system presents a new avenue for the development of gene therapy.


Assuntos
Sistemas CRISPR-Cas , Edição de Genes , Sistemas CRISPR-Cas/genética , RNA Guia de Sistemas CRISPR-Cas , Terapia Genética , DNA/genética
3.
Nucleic Acids Res ; 50(5): e28, 2022 03 21.
Artigo em Inglês | MEDLINE | ID: mdl-34893868

RESUMO

Patient-derived tumor organoids (PDOs) have emerged as a reliable in vitro model for drug discovery. However, RNA sequencing-based analysis of PDOs treated with drugs has not been realized in a high-throughput format due to the limited quantity of organoids. Here, we translated a newly developed pooled RNA-seq methodology onto a superhydrophobic microwell array chip to realize an assay of genome-wide RNA output unified with phenotypic data (Grouped-seq). Over 10-fold reduction of sample and reagent consumption together with a new ligation-based barcode synthesis method lowers the cost to ∼$2 per RNA-seq sample. Patient-derived colorectal cancer (CRC) organoids with a number of 10 organoids per microwell were treated with four anti-CRC drugs across eight doses and analyzed by the Grouped-seq. Using a phenotype-assisted pathway enrichment analysis (PAPEA) method, the mechanism of actions of the drugs were correctly derived, illustrating the great potential of Grouped-seq for pharmacological screening with tumor organoids.


Assuntos
Neoplasias , Organoides , Neoplasias Colorretais/tratamento farmacológico , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Descoberta de Drogas , Ensaios de Seleção de Medicamentos Antitumorais , Humanos , Neoplasias/metabolismo , Fenótipo , Transcriptoma
4.
Micromachines (Basel) ; 9(6)2018 Jun 06.
Artigo em Inglês | MEDLINE | ID: mdl-30424219

RESUMO

Microfluidic systems have been regarded as a potential platform for high-throughput screening technology in drug discovery due to their low sample consumption, high integration, and easy operation. The handling of small-volume liquid is an essential operation in microfluidic systems, especially in investigating large-scale combination conditions. Here, we develop a nanoliter centrifugal liquid dispenser (NanoCLD) coupled with superhydrophobic microwell array chips for high-throughput cell-based assays in the nanoliter scale. The NanoCLD consists of a plastic stock block with an array of drilled through holes, a reagent microwell array chip (reagent chip), and an alignment bottom assembled together in a fixture. A simple centrifugation at 800 rpm can dispense ~160 nL reagents into microwells in 5 min. The dispensed reagents are then delivered to cells by sandwiching the reagent chip upside down with another microwell array chip (cell chip) on which cells are cultured. A gradient of doxorubicin is then dispensed to the cell chip using the NanoCLD for validating the feasibility of performing drug tests on our microchip platform. This novel nanoliter-volume liquid dispensing method is simple, easy to operate, and especially suitable for repeatedly dispensing many different reagents simultaneously to microwells.

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