AIMC Topic: Drug Evaluation, Preclinical

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Deep learning-based classification model for GPR151 activator activity prediction.

BMC bioinformatics Jun 9, 2023
BACKGROUND: GPR151 is a kind of protein belonging to G protein-coupled receptor family that is closely associated with a variety of physiological and pathological processes.The potential use of GPR151 as a therapeutic target for the management of met...
Algorithms Drug Discovery Deep Learning Drug Evaluation, Preclinical Neural Networks, Computer
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Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Molecular diversity Apr 6, 2023
Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people worldwide characterized by cognitive decline and neurodegeneration. The accumulation of tau protein into paired helical filaments is one of the major ...
Molecular Dynamics Simulation Drug Evaluation, Preclinical Alzheimer Disease Ligands Molecular Docking Simulation Drug Discovery Protein Binding Artificial Intelligence Computer Simulation tau Proteins Humans Protein Aggregates
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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...
Microphysiological Systems Drug Evaluation, Preclinical Humans Microfluidics Deep Learning High-Throughput Screening Assays
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Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

Biochemical and biophysical research communications Oct 1, 2022
The number of patients with heart failure and related deaths is rapidly increasing worldwide, making it a major problem. Cardiac hypertrophy is a crucial preliminary step in heart failure, but its treatment has not yet been fully successful. In this ...
Cells, Cultured Animals Cholesterol Drug Evaluation, Preclinical Heart Failure Cardiomegaly Deep Learning Mice Rats Endothelin-1 Myocytes, Cardiac Ezetimibe Angiotensin II
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Deep-learning analysis of micropattern-based organoids enables high-throughput drug screening of Huntington's disease models.

Cell reports methods Sep 19, 2022
Organoids are carrying the promise of modeling complex disease phenotypes and serving as a powerful basis for unbiased drug screens, potentially offering a more efficient drug-discovery route. However, unsolved technical bottlenecks of reproducibilit...
Huntington Disease Organoids Deep Learning Drug Evaluation, Preclinical High-Throughput Screening Assays Humans Reproducibility of Results
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Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.

International journal of molecular sciences Mar 17, 2022
The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponent...
Drug Evaluation, Preclinical Ligands High-Throughput Nucleotide Sequencing COVID-19 Drug Treatment Small Molecule Libraries Drug Discovery Antiviral Agents Structure-Activity Relationship COVID-19 SARS-CoV-2 Drug Design Humans Artificial Intelligence
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Design of SARS-CoV-2 Mpro, PLpro dual-target inhibitors based on deep reinforcement learning and virtual screening.

Future medicinal chemistry Feb 27, 2022
Since December 2019, SARS-CoV-2 has continued to spread rapidly around the world. The effective drugs may provide a long-term strategy to combat this virus. The main protease (Mpro) and papain-like protease (PLpro) are two important targets for the ...
Deep Learning Antiviral Agents Molecular Dynamics Simulation Humans Drug Evaluation, Preclinical SARS-CoV-2 Protease Inhibitors Molecular Docking Simulation
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Combining explainable machine learning, demographic and multi-omic data to inform precision medicine strategies for inflammatory bowel disease.

PloS one Feb 23, 2022
Inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn's disease, affect several million individuals worldwide. These diseases are heterogeneous at the clinical, immunological and genetic levels and result from complex host and en...
Genomics Signal Transduction Colitis, Ulcerative Drug Evaluation, Preclinical Pyrazoles Anti-Inflammatory Agents, Non-Steroidal Crohn Disease Middle Aged Transcriptome Tumor Necrosis Factor-alpha Adolescent Precision Medicine Young Adult Female Adult Humans Aged Male Mesalamine Phenylurea Compounds Machine Learning Naphthalenes Prednisolone
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Machine-Learning-Enabled Virtual Screening for Inhibitors of Lysine-Specific Histone Demethylase 1.

Molecules (Basel, Switzerland) Dec 10, 2021
A machine learning approach has been applied to virtual screening for lysine specific demethylase 1 (LSD1) inhibitors. LSD1 is an important anti-cancer target. Machine learning models to predict activity were constructed using Morgan molecular finger...
Lysine Humans Molecular Structure Histone Demethylases Drug Evaluation, Preclinical Machine Learning Enzyme Inhibitors Databases, Factual
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IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds.

International journal of molecular sciences Dec 2, 2021
The parasite species of genus causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, computational prediction of new Antimalarial compounds...
Antimalarials Markov Chains Protozoan Proteins Machine Learning Plasmodium falciparum Databases, Pharmaceutical Drug Discovery Algorithms Models, Theoretical Genome, Protozoan Reproducibility of Results Drug Evaluation, Preclinical
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