AIMC Topic: Drug Design

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Discovery of small molecule binders of human FSHR(TMD) with novel structural scaffolds by integrating structural bioinformatics and machine learning algorithms.

Journal of molecular graphics & modelling Mar 5, 2019
BACKGROUND: The activation of follicle stimulating hormone receptor (FSHR) by FSH and the consequent downstream signaling activities are crucial for reproductive health. The role of FSHR in tumor progression as well as osteoporosis advancement has al...
Computers, Molecular Receptors, FSH Binding Sites Computational Biology Cell Line Models, Molecular Ligands Hydrophobic and Hydrophilic Interactions Quantitative Structure-Activity Relationship Machine Learning Drug Design Protein Binding Humans
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De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping.

Journal of chemical information and modeling Mar 5, 2019
Here we show that Generative Topographic Mapping (GTM) can be used to explore the latent space of the SMILES-based autoencoders and generate focused molecular libraries of interest. We have built a sequence-to-sequence neural network with Bidirection...
Molecular Docking Simulation Drug Design Catalytic Domain Small Molecule Libraries Receptor, Adenosine A2A Deep Learning Drug Evaluation, Preclinical Ligands
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Shape-Based Generative Modeling for de Novo Drug Design.

Journal of chemical information and modeling Feb 28, 2019
In this work, we propose a machine learning approach to generate novel molecules starting from a seed compound, its three-dimensional (3D) shape, and its pharmacophoric features. The pipeline draws inspiration from generative models used in image ana...
Machine Learning Drug Design Hydrophobic and Hydrophilic Interactions Molecular Conformation Quantitative Structure-Activity Relationship Models, Molecular Molecular Structure Pharmaceutical Preparations Hydrogen Bonding
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Deep learning for molecular generation.

Future medicinal chemistry Jan 30, 2019
De novo drug design aims to generate novel chemical compounds with desirable chemical and pharmacological properties from scratch using computer-based methods. Recently, deep generative neural networks have become a very active research frontier in d...
Neural Networks, Computer Software Animals Humans Drug Design Drug Discovery Deep Learning
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Predictive Multitask Deep Neural Network Models for ADME-Tox Properties: Learning from Large Data Sets.

Journal of chemical information and modeling Jan 24, 2019
Successful drug discovery projects require control and optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety. While volume and chemotype coverage of public and corporate ADME-Tox (absorption, distribution, excr...
Databases, Pharmaceutical Permeability Quantitative Structure-Activity Relationship Drug Design Models, Statistical Caco-2 Cells Models, Molecular Pharmaceutical Preparations Humans Models, Biological Neural Networks, Computer
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Deep Learning: Current and Emerging Applications in Medicine and Technology.

IEEE journal of biomedical and health informatics Jan 23, 2019
Machine learning is enabling researchers to analyze and understand increasingly complex physical and biological phenomena in traditional fields such as biology, medicine, and engineering and emerging fields like synthetic biology, automated chemical ...
Biotechnology Robotics Nanomedicine Image Interpretation, Computer-Assisted Deep Learning Humans Computational Biology Drug Design Drug Discovery
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Network-Based Assessment of Adverse Drug Reaction Risk in Polypharmacy Using High-Throughput Screening Data.

International journal of molecular sciences Jan 17, 2019
The risk of adverse drug reactions increases in a polypharmacology setting. High-throughput drug screening with transcriptomics applied to human cells has shown that drugs have effects on several molecular pathways, and these affected pathways may be...
Humans Neural Networks, Computer Algorithms Risk Assessment Drug Design High-Throughput Screening Assays Data Interpretation, Statistical Polypharmacy Drug-Related Side Effects and Adverse Reactions
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Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy.

Pharmaceutical research Jan 7, 2019
PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse side effect of cancer chemotherapy that can be life debilitating and cause extreme pain. The multifactorial and poorly understood mechanisms of toxicity have impeded the i...
Peripheral Nervous System Diseases Structure-Activity Relationship Molecular Structure Drug Design Neural Networks, Computer Humans Antineoplastic Agents Machine Learning Incidence Neoplasms
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De Novo Molecule Design by Translating from Reduced Graphs to SMILES.

Journal of chemical information and modeling Dec 21, 2018
A key component of automated molecular design is the generation of compound ideas for subsequent filtering and assessment. Recently deep learning approaches have been explored as alternatives to traditional de novo molecular design techniques. Deep l...
Cheminformatics Models, Molecular Databases, Pharmaceutical Drug Design Molecular Structure Deep Learning Pharmaceutical Preparations
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Converging a Knowledge-Based Scoring Function: DrugScore.

Journal of chemical information and modeling Dec 18, 2018
We present DrugScore, a new version of the knowledge-based scoring function DrugScore, which builds upon the same formalism used to derive DrugScore but exploits a training data set of nearly 40 000 X-ray complex structures, a highly diverse and the,...
Informatics Drug Design Models, Molecular Knowledge Bases Ligands
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