AIMC Topic: Drug Design

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Generative Deep Learning for Targeted Compound Design.

Journal of chemical information and modeling Oct 26, 2021
In the past few years, molecular design has increasingly been using generative models from the emergent field of Deep Learning, proposing novel compounds that are likely to possess desired properties or activities. molecular design finds applicatio...
Drug Discovery Deep Learning Bayes Theorem Neural Networks, Computer Drug Design
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Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors.

International journal of molecular sciences Oct 26, 2021
Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulat...
Ligands HEK293 Cells Receptors, Odorant Support Vector Machine Bayes Theorem Drug Evaluation, Preclinical In Vitro Techniques User-Computer Interface Humans Machine Learning Molecular Docking Simulation Drug Design Drug Discovery Female Male
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Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning.

International journal of molecular sciences Oct 26, 2021
The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built to predict the probability of different ...
Humans Machine Learning Drug Carriers Drug Screening Assays, Antitumor Nanoparticles Databases, Chemical Databases, Pharmaceutical Glioblastoma Drug Design Antineoplastic Agents User-Computer Interface Drug Delivery Systems Brain Neoplasms
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MolGPT: Molecular Generation Using a Transformer-Decoder Model.

Journal of chemical information and modeling Oct 25, 2021
Application of deep learning techniques for generation of molecules, termed as inverse molecular design, has been gaining enormous traction in drug design. The representation of molecules in SMILES notation as a string of characters enables the usag...
Machine Learning Drug Design
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Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries.

Molecular diversity Oct 23, 2021
The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecules to overcome any disease is a costly and lengthy process, but the process continues uninterrupted...
Humans Artificial Intelligence Machine Learning COVID-19 Drug Treatment Drug Industry Drug Design
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Using computers to ESKAPE the antibiotic resistance crisis.

Drug discovery today Oct 21, 2021
Since the discovery of penicillin, the development and use of antibiotics have promoted safe and effective control of bacterial infections. However, the number of antibiotic-resistance cases has been ever increasing over time. Thus, the drug discover...
Quantum Theory Computing Methodologies Artificial Intelligence Computers Drug Design Drug Resistance, Microbial Anti-Bacterial Agents
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3D-Scaffold: A Deep Learning Framework to Generate 3D Coordinates of Drug-like Molecules with Desired Scaffolds.

The journal of physical chemistry. B Oct 18, 2021
The prerequisite of therapeutic drug design and discovery is to identify novel molecules and developing lead candidates with desired biophysical and biochemical properties. Deep generative models have demonstrated their ability to find such molecules...
Humans COVID-19 SARS-CoV-2 Deep Learning Antiviral Agents Pharmaceutical Preparations Molecular Docking Simulation Drug Design
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MANORAA: A machine learning platform to guide protein-ligand design by anchors and influential distances.

Structure (London, England : 1993) Oct 5, 2021
The MANORAA platform uses structure-based approaches to provide information on drug design originally derived from mapping tens of thousands of amino acids on a grid. In-depth analyses of the pockets, frequently occurring atoms, influential distances...
Computational Biology Proteins Databases, Protein Drug Design Protein Binding Crystallography, X-Ray Trimethoprim Tetrahydrofolate Dehydrogenase Protein Domains Ligands Models, Molecular Humans Machine Learning COVID-19 SARS-CoV-2 Pandemics
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Kinase Inhibitor Scaffold Hopping with Deep Learning Approaches.

Journal of chemical information and modeling Sep 29, 2021
The protein kinase family contains many promising drug targets. Many kinase inhibitors target the ATP-binding pocket, leading to approved drugs in past decades. Scaffold hopping is an effective approach for drug design. The kinase ATP-binding pocket ...
Protein Kinases Protein Kinase Inhibitors Drug Design Deep Learning Protein Binding
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Guided structure-based ligand identification and design via artificial intelligence modeling.

Expert opinion on drug discovery Sep 23, 2021
INTRODUCTION: The implementation of Artificial Intelligence (AI) methodologies to drug discovery (DD) are on the rise. Several applications have been developed for structure-based DD, where AI methods provide an alternative framework for the identifi...
Ligands Molecular Docking Simulation Drug Design Artificial Intelligence Machine Learning Humans
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