AIMC Topic: Drug Design

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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...
Pyrazoles Oximes Oxadiazoles Insecticides Animals Drug Design
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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...
Humans Computational Biology Protein Folding Protein Structure, Tertiary Machine Learning Drug Design
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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...
Crystallization Molecular Conformation Drug Design Models, Molecular Machine Learning Algorithms
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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...
Software Algorithms Humans Neural Networks, Computer Drug Design ROC Curve Proteins Molecular Docking Simulation Computer-Aided Design Ligands
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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...
Drug Design Models, Theoretical Quantitative Structure-Activity Relationship Algorithms Computer Simulation 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...
Machine Learning Molecular Docking Simulation Quantitative Structure-Activity Relationship Small Molecule Libraries Drug Design
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ROCS-derived features for virtual screening.

Journal of computer-aided molecular design Sep 8, 2016
Rapid overlay of chemical structures (ROCS) is a standard tool for the calculation of 3D shape and chemical ("color") similarity. ROCS uses unweighted sums to combine many aspects of similarity, yielding parameter-free models for virtual screening. I...
Machine Learning Algorithms Models, Molecular Pharmaceutical Preparations Molecular Structure Computer-Aided Design Drug Design
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Molecular graph convolutions: moving beyond fingerprints.

Journal of computer-aided molecular design Aug 24, 2016
Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structur...
Ligands Computer Graphics Neural Networks, Computer Molecular Structure Computer-Aided Design Pharmaceutical Preparations Drug Design Machine Learning
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A renaissance of neural networks in drug discovery.

Expert opinion on drug discovery Jul 4, 2016
INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to choose the mo...
Structure-Activity Relationship Pharmaceutical Preparations Models, Biological Drug Design Drug Discovery Humans Drug Delivery Systems Neural Networks, Computer Computer-Aided Design
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Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?

Expert opinion on drug discovery May 30, 2016
INTRODUCTION: Artificial neural networks (ANNs) are highly adaptive nonlinear optimization algorithms that have been applied in many diverse scientific endeavors, ranging from economics, engineering, physics, and chemistry to medical science. Notably...
Drug Discovery Models, Theoretical Animals Drug Design Quantitative Structure-Activity Relationship Neural Networks, Computer Humans Pharmaceutical Preparations Algorithms Nonlinear Dynamics
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