AIMC Topic: Drug Design

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Bayesian molecular design with a chemical language model.

Journal of computer-aided molecular design Mar 9, 2017
The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techni...
Computer Simulation Computer-Aided Design Drug Design Machine Learning Software Pharmaceutical Preparations Monte Carlo Method Small Molecule Libraries Bayes Theorem Models, Chemical Molecular Structure
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Creating the New from the Old: Combinatorial Libraries Generation with Machine-Learning-Based Compound Structure Optimization.

Journal of chemical information and modeling Feb 15, 2017
The growing computational abilities of various tools that are applied in the broadly understood field of computer-aided drug design have led to the extreme popularity of virtual screening in the search for new biologically active compounds. Most ofte...
Machine Learning Small Molecule Libraries Databases, Pharmaceutical Combinatorial Chemistry Techniques Computer-Aided Design Drug Design
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Predicting DPP-IV inhibitors with machine learning approaches.

Journal of computer-aided molecular design Feb 2, 2017
Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain...
Diabetes Mellitus, Type 2 Molecular Docking Simulation Humans Bayes Theorem Machine Learning Dipeptidyl Peptidase 4 Small Molecule Libraries Computer-Aided Design Dipeptidyl-Peptidase IV Inhibitors Drug Design
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Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

Tuberculosis (Edinburgh, Scotland) Jan 20, 2017
There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target...
DNA Topoisomerases, Type I Topoisomerase I Inhibitors Protein Conformation Mycobacterium smegmatis Bayes Theorem Humans Antitubercular Agents Drug Design Machine Learning Mycobacterium tuberculosis Dose-Response Relationship, Drug Molecular Targeted Therapy Structure-Activity Relationship Molecular Docking Simulation Computer-Aided Design Tuberculosis
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Design, synthesis, and bioactivities of novel oxadiazole-substituted pyrazole oximes.

Bioorganic & medicinal chemistry letters Dec 31, 2016
A series of novel pyrazole oxime derivatives containing a substituted oxadiazole group were designed and synthesized. The bioassay results indicated that some title compounds displayed good acaricidal and insecticidal activities against Tetranychus c...
Oxadiazoles Insecticides Oximes Animals Drug Design Pyrazoles
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Recent Progress in Machine Learning-Based Methods for Protein Fold Recognition.

International journal of molecular sciences Dec 16, 2016
Knowledge on protein folding has a profound impact on understanding the heterogeneity and molecular function of proteins, further facilitating drug design. Predicting the 3D structure (fold) of a protein is a key problem in molecular biology. Determi...
Computational Biology Protein Folding Drug Design Protein Structure, Tertiary Humans Machine Learning
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Beyond Rotatable Bond Counts: Capturing 3D Conformational Flexibility in a Single Descriptor.

Journal of chemical information and modeling Dec 6, 2016
A new molecular descriptor, nConf, based on chemical connectivity, is presented which captures the accessible conformational space of a molecule. Currently the best available two-dimensional descriptors for quantifying the flexibility of a particular...
Algorithms Drug Design Machine Learning Molecular Conformation Models, Molecular Crystallization
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Boosting Docking-Based Virtual Screening with Deep Learning.

Journal of chemical information and modeling Nov 29, 2016
In this work, we propose a deep learning approach to improve docking-based virtual screening. The deep neural network that is introduced, DeepVS, uses the output of a docking program and learns how to extract relevant features from basic data such as...
Ligands Neural Networks, Computer Software Algorithms Drug Design Humans Molecular Docking Simulation ROC Curve Computer-Aided Design Proteins
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The role of different sampling methods in improving biological activity prediction using deep belief network.

Journal of computational chemistry Nov 14, 2016
Thousands of molecules and descriptors are available for a medicinal chemist thanks to the technological advancements in different branches of chemistry. This fact as well as the correlation between them has raised new problems in quantitative struct...
Models, Theoretical Quantitative Structure-Activity Relationship Algorithms Computer Simulation Drug Design Neural Networks, Computer
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Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

Molecular informatics Oct 26, 2016
Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems hav...
Small Molecule Libraries Machine Learning Drug Design Molecular Docking Simulation Quantitative Structure-Activity Relationship
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