AIMC Topic: Drug Discovery

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Network-Based Drug Discovery: Coupling Network Pharmacology with Phenotypic Screening for Neuronal Excitability.

Journal of molecular biology Jul 18, 2018
Diseases such as chronic pain with complex etiologies are unlikely to respond to single, target-specific therapeutics but rather require intervention at multiple points within a perturbed disease system. Such approaches are being enabled by the rise ...
Humans Neural Networks, Computer ROC Curve Computational Biology Drug Discovery Cell Culture Techniques Neurons High-Throughput Screening Assays
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A Machine Learning Approach for Predicting HIV Reverse Transcriptase Mutation Susceptibility of Biologically Active Compounds.

Journal of chemical information and modeling Jul 17, 2018
HIV resistance emerging against antiretroviral drugs represents a great threat to the continued prolongation of the lifespans of HIV-infected patients. Therefore, methods capable of predicting resistance susceptibility in the development of compounds...
HIV Reverse Transcriptase Point Mutation Reverse Transcriptase Inhibitors Drug Resistance, Viral Drug Discovery HIV Infections Models, Biological HIV-1 Bayes Theorem Humans Machine Learning
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Classification of thyroid hormone receptor agonists and antagonists using statistical learning approaches.

Molecular diversity Jul 16, 2018
In silico models are presented for modeling and predicting thyroid hormone receptor (TR) agonists and antagonists. A data set consisting of 258 compounds is used in the present work. The C4.5, random forest (RF) and support vector machine (SVM) stati...
Support Vector Machine Ligands Receptors, Thyroid Hormone Quantitative Structure-Activity Relationship Algorithms Drug Discovery
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Convolutional neural network scoring and minimization in the D3R 2017 community challenge.

Journal of computer-aided molecular design Jul 10, 2018
We assess the ability of our convolutional neural network (CNN)-based scoring functions to perform several common tasks in the domain of drug discovery. These include correctly identifying ligand poses near and far from the true binding mode when giv...
Cathepsins Databases, Protein Structure-Activity Relationship Protein Conformation Binding Sites Ligands Neural Networks, Computer Drug Discovery Protein Binding Algorithms Molecular Docking Simulation
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Geometric Deep Learning Autonomously Learns Chemical Features That Outperform Those Engineered by Domain Experts.

Molecular pharmaceutics Jul 7, 2018
Artificial Intelligence has advanced at an unprecedented pace, backing recent breakthroughs in natural language processing, speech recognition, and computer vision: domains where the data is euclidean in nature. More recently, considerable progress h...
Neural Networks, Computer Algorithms Artificial Intelligence Drug Discovery Machine Learning Deep Learning
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Data analytics and deep learning in medicinal chemistry.

Future medicinal chemistry Jul 3, 2018
Drug Discovery Deep Learning Data Mining Humans Chemistry, Pharmaceutical
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Artificial intelligence in pharmaceutical research and development.

Future medicinal chemistry Jul 3, 2018
Artificial Intelligence Drug Discovery Drug Development Humans Quantitative Structure-Activity Relationship Pharmaceutical Research
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PAIN(S) relievers for medicinal chemists: how computational methods can assist in hit evaluation.

Future medicinal chemistry Jun 29, 2018
Drug Discovery Drug Evaluation, Preclinical Small Molecule Libraries Humans Machine Learning High-Throughput Screening Assays Models, Statistical
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Neural network and deep-learning algorithms used in QSAR studies: merits and drawbacks.

Drug discovery today Jun 21, 2018
Deep Learning Pharmaceutical Preparations Ligands Algorithms Drug Discovery Quantitative Structure-Activity Relationship Humans Neural Networks, Computer
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Reinforced Adversarial Neural Computer for de Novo Molecular Design.

Journal of chemical information and modeling Jun 12, 2018
In silico modeling is a crucial milestone in modern drug design and development. Although computer-aided approaches in this field are well-studied, the application of deep learning methods in this research area is at the beginning. In this work, we p...
Deep Learning Equipment Design Drug Design Drug Discovery Machine Learning Algorithms Neural Networks, Computer Computer-Aided Design
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