AIMC Topic: High-Throughput Screening Assays

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Antiviral Peptide-Generative Pre-Trained Transformer (AVP-GPT): A Deep Learning-Powered Model for Antiviral Peptide Design with High-Throughput Discovery and Exceptional Potency.

Viruses
Traditional antiviral peptide (AVP) discovery is a time-consuming and expensive process. This study introduces AVP-GPT, a novel deep learning method utilizing transformer-based language models and multimodal architectures specifically designed for AV...

Enhancing the Predictive Power of Machine Learning Models through a Chemical Space Complementary DEL Screening Strategy.

Journal of medicinal chemistry
DNA-encoded library (DEL) technology is an effective method for small molecule drug discovery, enabling high-throughput screening against target proteins. While DEL screening produces extensive data, it can reveal complex patterns not easily recogniz...

Machine Learning-Driven Data Valuation for Optimizing High-Throughput Screening Pipelines.

Journal of chemical information and modeling
In the rapidly evolving field of drug discovery, high-throughput screening (HTS) is essential for identifying bioactive compounds. This study introduces a novel application of data valuation, a concept for evaluating the importance of data points bas...

Automation of biochemical assays using an open-sourced, inexpensive robotic liquid handler.

SLAS technology
High Throughput Screening is crucial in pharmaceutical companies for efficient testing in drug discovery and development. Our Vaccines Analytical Research and Development (V-AR&D) department extensively uses robotic liquid handlers in their High Thro...

High-throughput and computational techniques for aptamer design.

Expert opinion on drug discovery
INTRODUCTION: Aptamers refer to short ssDNA/RNA sequences that target small molecules, proteins, or cells. Aptamers have significantly advanced diagnostic applications, including biosensors for detecting specific biomarkers, state-of-the-art imaging,...

The revolution in high-throughput proteomics and AI.

Science (New York, N.Y.)
The recent capability to measure thousands of plasma proteins from a tiny blood sample has provided a new dimension of expansive data that can advance our understanding of human health. For example, the company SomaLogic has developed the means to me...

High-throughput prediction of stalk cellulose and hemicellulose content in maize using machine learning and Fourier transform infrared spectroscopy.

Bioresource technology
Cellulose and hemicellulose are key cross-linked carbohydrates affecting bioethanol production in maize stalks. Traditional wet chemical methods for their detection are labor-intensive, highlighting the need for high-throughput techniques. This study...

Automated High-Throughput Atomic Force Microscopy Single-Cell Nanomechanical Assay Enabled by Deep Learning-Based Optical Image Recognition.

Nano letters
Mechanical forces are essential for life activities, and the mechanical phenotypes of single cells are increasingly gaining attention. Atomic force microscopy (AFM) has been a standard method for single-cell nanomechanical assays, but its efficiency ...

On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering.

Faraday discussions
Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former relies on computation from first principles, while the latter is a combinatorial approach based on chanc...

Antimicrobial activity of compounds identified by artificial intelligence discovery engine targeting enzymes involved in Neisseria gonorrhoeae peptidoglycan metabolism.

Biological research
BACKGROUND: Neisseria gonorrhoeae (Ng) causes the sexually transmitted disease gonorrhoea. There are no vaccines and infections are treated principally with antibiotics. However, gonococci rapidly develop resistance to every antibiotic class used and...