AIMC Topic: High-Throughput Screening Assays
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Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning.
Nature chemistry
Nov 23, 2023
Late-stage functionalization is an economical approach to optimize the properties of drug candidates. However, the chemical complexity of drug molecules often makes late-stage diversification challenging. To address this problem, a late-stage functio...
Analysis of cortical cell polarity by imaging flow cytometry.
Journal of cellular biochemistry
Sep 18, 2023
Metastasis is the main cause of cancer-related death and therapies specifically targeting metastasis are highly needed. Cortical cell polarity (CCP) is a prometastatic property of circulating tumor cells affecting their ability to exit blood vessels ...
Artificial intelligence-accelerated high-throughput screening of antibiotic combinations on a microfluidic combinatorial droplet system.
Lab on a chip
Sep 13, 2023
Microfluidic platforms have been employed as an effective tool for drug screening and exhibit the advantages of lower reagent consumption, higher throughput and a higher degree of automation. Despite the great advancement, it remains challenging to s...
DFRscore: Deep Learning-Based Scoring of Synthetic Complexity with Drug-Focused Retrosynthetic Analysis for High-Throughput Virtual Screening.
Journal of chemical information and modeling
Aug 31, 2023
Recently emerging generative AI models enable us to produce a vast number of compounds for potential applications. While they can provide novel molecular structures, the synthetic feasibility of the generated molecules is often questioned. To address...
Harmonizing across datasets to improve the transferability of drug combination prediction.
Communications biology
Apr 11, 2023
Combination treatment has multiple advantages over traditional monotherapy in clinics, thus becoming a target of interest for many high-throughput screening (HTS) studies, which enables the development of machine learning models predicting the respon...
High-throughput cell spheroid production and assembly analysis by microfluidics and deep learning.
SLAS technology
Mar 28, 2023
3D cell culture models are important tools in translational research but have been out of reach for high-throughput screening due to complexity, requirement of large cell numbers and inadequate standardization. Microfluidics and culture model miniatu...
Super High-Throughput Screening of Enzyme Variants by Spectral Graph Convolutional Neural Networks.
Journal of chemical theory and computation
Mar 24, 2023
Finding new enzyme variants with the desired substrate scope requires screening through a large number of potential variants. In a typical enzyme engineering workflow, it is possible to scan a few thousands of variants, and gather several candidates...
The Synergy between Deep Learning and Organs-on-Chips for High-Throughput Drug Screening: A Review.
Biosensors
Mar 15, 2023
Organs-on-chips (OoCs) are miniature microfluidic systems that have arguably become a class of advanced in vitro models. Deep learning, as an emerging topic in machine learning, has the ability to extract a hidden statistical relationship from the in...
High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography.
Journal of visualized experiments : JoVE
Mar 10, 2023
X-ray crystallography is the most commonly employed technique to discern macromolecular structures, but the crucial step of crystallizing a protein into an ordered lattice amenable to diffraction remains challenging. The crystallization of biomolecul...
20 years of crystal hits: progress and promise in ultrahigh-throughput crystallization screening.
Acta crystallographica. Section D, Structural biology
Feb 27, 2023
Diffraction-based structural methods contribute a large fraction of the biomolecular structural models available, providing a critical understanding of macromolecular architecture. These methods require crystallization of the target molecule, which r...
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