AIMC Topic: Drug Discovery

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Use of machine learning approaches for novel drug discovery.

Expert opinion on drug discovery Jan 1, 2016
INTRODUCTION: The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery met...
Neural Networks, Computer Machine Learning Molecular Docking Simulation Humans Decision Trees Models, Biological Ligands Binding Sites Drug Design Drug Discovery Support Vector Machine
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A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

Molecular bioSystems Dec 1, 2015
Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize ...
Humans Machine Learning Drug Discovery Binding Sites Protein Binding Protein Interaction Mapping Antineoplastic Agents, Phytogenic Computational Biology Cell Line, Tumor Mouth Neoplasms Receptors, CXCR4 Gene Expression Regulation, Neoplastic High-Throughput Screening Assays ROC Curve Models, Molecular Molecular Conformation Gene Regulatory Networks
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Predicting selective liver X receptor β agonists using multiple machine learning methods.

Molecular bioSystems May 1, 2015
Liver X receptor (LXR) α and β are cholesterol sensors; they respond to excess cholesterol and stimulate reverse cholesterol transport. Activating LXRs represents a promising therapeutic option for dyslipidemia. However, activating LXRα may cause unw...
Drug Discovery Protein Binding Models, Theoretical Liver X Receptors Orphan Nuclear Receptors Machine Learning Algorithms Reproducibility of Results Humans
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Unsupervised Structure Detection in Biomedical Data.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2015
A major challenge in computational biology is to find simple representations of high-dimensional data that best reveal the underlying structure. In this work, we present an intuitive and easy-to-implement method based on ranked neighborhood compariso...
Neoplasms Drug Discovery HIV Infections Artificial Intelligence Algorithms Databases, Factual Pattern Recognition, Automated Anti-HIV Agents Computational Biology Data Mining Humans
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Artificial Neural Network Methods Applied to Drug Discovery for Neglected Diseases.

Combinatorial chemistry & high throughput screening Jan 1, 2015
Among the chemometric tools used in rational drug design, we find artificial neural network methods (ANNs), a statistical learning algorithm similar to the human brain, to be quite powerful. Some ANN applications use biological and molecular data of ...
Neglected Diseases Humans Neural Networks, Computer Drug Discovery
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A lazy learning-based QSAR classification study for screening potential histone deacetylase 8 (HDAC8) inhibitors.

SAR and QSAR in environmental research Jan 1, 2015
Histone deacetylases 8 (HDAC8) is an enzyme repressing the transcription of various genes including tumour suppressor gene and has already become a target of human cancer treatment. In an effort to facilitate the discovery of HDAC8 inhibitors, two qu...
Histone Deacetylases Principal Component Analysis Machine Learning Models, Chemical Databases, Chemical Molecular Dynamics Simulation Drug Discovery Quantitative Structure-Activity Relationship Histone Deacetylase Inhibitors
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In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

Mini reviews in medicinal chemistry Jan 1, 2015
The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of to...
Fullerenes Computer Simulation Animals Toxicological Phenomena Vitamin B Complex Drug Discovery Models, Biological Databases, Pharmaceutical Quantitative Structure-Activity Relationship Humans Thiamine Cyclams Anti-HIV Agents Benzylamines Neural Networks, Computer Antiprotozoal Agents Models, Molecular Heterocyclic Compounds Tinidazole Pharmaceutical Preparations
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Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion tha...
Humans Neural Networks, Computer Algorithms Drug Discovery Nerve Net Models, Biological Image Processing, Computer-Assisted Tuberculosis Computational Biology Protein Conformation Proteins
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AutoWeka: toward an automated data mining software for QSAR and QSPR studies.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
UNLABELLED: In biology and chemistry, a key goal is to discover novel compounds affording potent biological activity or chemical properties. This could be achieved through a chemical intuition-driven trial-and-error process or via data-driven predict...
Data Mining Quantitative Structure-Activity Relationship Humans Neural Networks, Computer Models, Molecular Software Pharmaceutical Preparations Drug Discovery
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