AIMC Topic: High-Throughput Screening Assays

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An open-source screening platform accelerates discovery of drug combinations.

Nature communications
Drug combinations are essential to modern medicine, but their discovery remains slow and inefficient as experimental complexity expands rapidly with each additional drug tested. Although modern liquid handling systems enable complex and highly custom...

From Bits to Bonds: High-Throughput Virtual Screening of Ribonucleic Acid Nanocarriers Using a Combinatorial Approach of Machine Learning and Molecular Dynamics.

Journal of the American Chemical Society
The implementation of high-throughput methods for fuelling the design of effective nanocarriers for RNA delivery remains challenging. Traditional experimental screening is resource-intensive, while purely computational approaches face limitations, su...

Condensation of Force Field Parameters from Machine Learning Predicted Distributions for High-Throughput Virtual Screening Applications.

Journal of chemical information and modeling
Transferable biomolecular force fields are developed by fitting either ab initio or experimental data related to representative molecules and can then be used to model chemical entities that are similar to the ones they were developed for. However, o...

DART Predictor: A Multi-Label Attention Model for High-Throughput Screening of Chemicals with Developmental and Reproductive Toxicity (DART).

Environmental science & technology
Chemicals with developmental and reproductive toxicity (DART) pose significant risks to human health, particularly exposure during critical windows of embryonic and fetal development. Therefore, rapid and accurate identification of DART chemicals is ...

Engineering enhanced signal peptides: A high-throughput computational pipeline for optimizing therapeutic protein production in CHO cells.

New biotechnology
Rational design of signal peptides (SPs), crucial for efficient therapeutic protein secretion in Chinese hamster ovary (CHO) cells, remains challenging due to their context-dependency activity. To overcome this limitation and enable the discovery of ...

HCS-3DX, a next-generation AI-driven automated 3D-oid high-content screening system.

Nature communications
Self-organised three-dimensional (3D) cell cultures, collectively called 3D-oids, include spheroids, organoids and other co-culture models. Systematic evaluation of these models forms a critical new generation of high-content screening (HCS) systems ...

BIOPTIC B1 Ultra-High-Throughput Virtual Screening System Discovers LRRK2 Ligands in Vast Chemical Space.

Journal of chemical information and modeling
The rapid expansion of chemical space presents significant challenges in identifying novel ligands for drug targets. Here, we introduce BIOPTIC B1, an ultra-high-throughput ligand-based virtual screening system capable of rapidly evaluating multi-bil...

High-throughput screening accelerated by machine learning for the morphology of silica nanoparticles with high cell permeability.

Nanoscale
In recent years, silica nanoparticles have garnered tremendous attention as drug-delivery carriers. However, the cell permeability of nanoparticles remains a major obstacle that limits the drug-delivery efficiency of drug carriers. It is a common pra...

Integrated transcriptomic and functional modeling reveals AKT and mTOR synergy in colorectal cancer.

Scientific reports
Colorectal cancer (CRC) treatment remains challenging due to genetic heterogeneity and resistance mechanisms. To address this, we developed a drug discovery pipeline using patient-derived primary CRC cultures with diverse genomic profiles. These cult...