AIMC Topic: Drug Discovery

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AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks.

International journal of molecular sciences Nov 10, 2020
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient and successful rational drug design. Therefore, many binding affinity prediction methods have been developed. In recent years, since deep learning tech...
Humans Neural Networks, Computer Ligands Databases, Protein Molecular Dynamics Simulation Deep Learning User-Computer Interface Protein Binding Proteins Drug Design Drug Discovery Molecular Docking Simulation Computer-Aided Design
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Systematic Data Analysis and Diagnostic Machine Learning Reveal Differences between Compounds with Single- and Multitarget Activity.

Molecular pharmaceutics Nov 5, 2020
Small molecules with multitarget activity are capable of triggering polypharmacological effects and are of high interest in drug discovery. Compared to single-target compounds, promiscuity also affects drug distribution and pharmacodynamics and alter...
Machine Learning Structure-Activity Relationship Molecular Structure Polypharmacology Data Analysis Drug Discovery
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REINVENT 2.0: An AI Tool for De Novo Drug Design.

Journal of chemical information and modeling Oct 29, 2020
In the past few years, we have witnessed a renaissance of the field of molecular de novo drug design. The advancements in deep learning and artificial intelligence (AI) have triggered an avalanche of ideas on how to translate such techniques to a var...
Drug Discovery Artificial Intelligence Drug Design
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Deep Learning Total Energies and Orbital Energies of Large Organic Molecules Using Hybridization of Molecular Fingerprints.

Journal of chemical information and modeling Oct 29, 2020
The ability to predict material properties without the need for resource-consuming experimental efforts can immensely accelerate material and drug discovery. Although ab initio methods can be reliable and accurate in making such predictions, they are...
Drug Discovery Deep Learning Artificial Intelligence Machine Learning Neural Networks, Computer
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Profiling SARS-CoV-2 Main Protease (M) Binding to Repurposed Drugs Using Molecular Dynamics Simulations in Classical and Neural Network-Trained Force Fields.

ACS combinatorial science Oct 29, 2020
The current COVID-19 pandemic caused by a novel coronavirus SARS-CoV-2 urgently calls for a working therapeutic. Here, we report a computation-based workflow for efficiently selecting a subset of FDA-approved drugs that can potentially bind to the SA...
Molecular Dynamics Simulation Catalytic Domain Neural Networks, Computer Drug Repositioning Drug Discovery Workflow Antiviral Agents Coronavirus 3C Proteases Protein Binding Coronavirus Protease Inhibitors
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Artificial intelligence in drug discovery and development.

Drug discovery today Oct 21, 2020
Artificial intelligence-integrated drug discovery and development has accelerated the growth of the pharmaceutical sector, leading to a revolutionary change in the pharma industry. Here, we discuss areas of integration, tools, and techniques utilized...
Humans Artificial Intelligence Drug Discovery Pharmaceutical Research
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Predicting With Confidence: Using Conformal Prediction in Drug Discovery.

Journal of pharmaceutical sciences Oct 17, 2020
One of the challenges with predictive modeling is how to quantify the reliability of the models' predictions on new objects. In this work we give an introduction to conformal prediction, a framework that sits on top of traditional machine learning al...
Reproducibility of Results Drug Discovery Quantitative Structure-Activity Relationship Molecular Conformation Machine Learning Algorithms
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Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications.

Journal of computer-aided molecular design Oct 9, 2020
Atomistic simulations have become an invaluable tool for industrial applications ranging from the optimization of protein-ligand interactions for drug discovery to the design of new materials for energy applications. Here we review recent advances in...
Quantum Theory Ligands Models, Molecular Pharmaceutical Preparations Drug Design Drug Discovery Machine Learning
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Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Scientific reports Oct 8, 2020
Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine learning algorithm in artificial neural networks, has been applied to the advancement of precision medicine and drug discovery. In this study, we perf...
Antineoplastic Agents Deep Learning Algorithms Drug Discovery Triple Negative Breast Neoplasms Receptors, G-Protein-Coupled Humans Neural Networks, Computer
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Efficient molecular encoders for virtual screening.

Drug discovery today. Technologies Oct 4, 2020
Molecular representations encoding molecular structure information play critical roles in molecular virtual screening (VS). In order to improve VS performance, an abundance of molecular encoders have been developed and tested by various VS challenges...
Deep Learning Humans Molecular Structure Drug Discovery
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