AIMC Topic: Drug Design

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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 Design Drug Discovery Artificial Intelligence
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A Turing Test for Molecular Generators.

Journal of medicinal chemistry Oct 12, 2020
Machine learning approaches promise to accelerate and improve success rates in medicinal chemistry programs by more effectively leveraging available data to guide a molecular design. A key step of an automated computational design algorithm is molecu...
Humans Drug Design Molecular Structure Chemistry, Pharmaceutical 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...
Machine Learning Quantum Theory Ligands Models, Molecular Drug Design Pharmaceutical Preparations Drug Discovery
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Machine learning-guided discovery and design of non-hemolytic peptides.

Scientific reports Oct 6, 2020
Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are cost-effective and time-saving strategies used to predict biol...
Pore Forming Cytotoxic Proteins Drug Design Cost-Benefit Analysis Hemolysis Machine Learning Amino Acid Sequence
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Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design.

Journal of chemical information and modeling Sep 10, 2020
One of the main challenges in drug discovery is predicting protein-ligand binding affinity. Recently, machine learning approaches have made substantial progress on this task. However, current methods of model evaluation are overly optimistic in measu...
Neural Networks, Computer Protein Binding Ligands Databases, Protein Drug Design
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Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization.

Journal of chemical information and modeling Sep 9, 2020
Artificial intelligence and multiobjective optimization represent promising solutions to bridge chemical and biological landscapes by addressing the automated design of compounds as a result of a humanlike creative process. In the present study, we ...
Betacoronavirus Pneumonia, Viral Small Molecule Libraries Cysteine Endopeptidases Coronavirus 3C Proteases Acetylcholinesterase Cholinesterase Inhibitors Enzyme Inhibitors Viral Nonstructural Proteins Coronavirus Infections Pandemics Neuraminidase Influenza A virus COVID-19 Antiviral Agents Molecular Docking Simulation Neural Networks, Computer Drug Design SARS-CoV-2 Artificial Intelligence Humans
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Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics.

Scientific reports Sep 2, 2020
One of the major drawbacks of cheminformatics is a large amount of information present in the datasets. In the majority of cases, this information contains redundant instances that affect the analysis of similarity measurements with respect to drug d...
Cheminformatics Humans Machine Learning Support Vector Machine Algorithms Heuristics Drug Design
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Computational Method for Quantitative Comparison of Activity Landscapes on the Basis of Image Data.

Molecules (Basel, Switzerland) Aug 29, 2020
Activity landscape (AL) models are used for visualizing and interpreting structure-activity relationships (SARs) in compound datasets. Therefore, ALs are designed to present chemical similarity and compound potency information in context. Different t...
Machine Learning Models, Molecular Drug Design Drug Discovery Structure-Activity Relationship
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Current methods and challenges for deep learning in drug discovery.

Drug discovery today. Technologies Aug 17, 2020
Driven by rapid advances in computer hardware and publicly available datasets over the past decade, deep learning has achieved tremendous success in the transformation of many computational disciplines. These novel technologies have had considerable ...
Drug Discovery Humans Deep Learning Drug Design
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Digital Pharmaceutical Sciences.

AAPS PharmSciTech Jul 26, 2020
Artificial intelligence (AI) and machine learning, in particular, have gained significant interest in many fields, including pharmaceutical sciences. The enormous growth of data from several sources, the recent advances in various analytical tools, a...
Drug Design Chemistry, Pharmaceutical Neural Networks, Computer Artificial Intelligence Machine Learning Algorithms
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