AIMC Topic: Molecular Targeted Therapy

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Artificial Intelligence Steering Molecular Therapy in the Absence of Information on Target Structure and Regulation.

Journal of chemical information and modeling Dec 4, 2019
Protein associations are at the core of biological activity, and the drug-based disruption of dysfunctional associations poses a major challenge to targeted therapy. The problem becomes daunting when the structure and regulated modulation of the comp...
Proteins Databases, Protein Phosphorylation Molecular Targeted Therapy Artificial Intelligence Water Computational Biology
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Machine learning for target discovery in drug development.

Current opinion in chemical biology Nov 14, 2019
The discovery of macromolecular targets for bioactive agents is currently a bottleneck for the informed design of chemical probes and drug leads. Typically, activity profiling against genetically manipulated cell lines or chemical proteomics is pursu...
Machine Learning Computer Simulation Antineoplastic Agents Pentacyclic Triterpenes Sesquiterpenes Molecular Targeted Therapy Receptors, Cannabinoid Humans Proteomics Sesquiterpenes, Guaiane Drug Evaluation, Preclinical Transient Receptor Potential Channels Lipoxygenase Naphthoquinones
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Artificial intelligence and big data facilitated targeted drug discovery.

Stroke and vascular neurology Nov 7, 2019
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...
Pharmacokinetics Toxicology Computer-Aided Design Pharmaceutical Preparations Big Data Humans Data Mining Drug Design Structure-Activity Relationship Artificial Intelligence Molecular Targeted Therapy Drug Discovery Molecular Structure Databases, Factual
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Predicting Drug-Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation.

Journal of chemical information and modeling Sep 6, 2019
We propose a novel deep learning approach for predicting drug-target interaction using a graph neural network. We introduce a distance-aware graph attention algorithm to differentiate various types of intermolecular interactions. Furthermore, we extr...
Neural Networks, Computer Algorithms Computational Biology Proteins Protein Conformation Models, Molecular Computer Graphics Ligands Molecular Targeted Therapy
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Accurate prediction of potential druggable proteins based on genetic algorithm and Bagging-SVM ensemble classifier.

Artificial intelligence in medicine Jul 19, 2019
Discovering and accurately locating drug targets is of great significance for the research and development of new drugs. As a different approach to traditional drug development, the machine learning algorithm is used to predict the drug target by min...
Support Vector Machine Proteins Molecular Targeted Therapy Humans Algorithms Drug Development
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Future of Radiotherapy in Nasopharyngeal Carcinoma.

The British journal of radiology Jul 9, 2019
Nasopharyngeal carcinoma (NPC) is a malignancy with unique clinical biological profiles such as associated Epstein-Barr virus infection and high radiosensitivity. Radiotherapy has long been recognized as the mainstay for the treatment of NPC. However...
Radiotherapy, Intensity-Modulated Radiotherapy Radiation Injuries Immunotherapy Organs at Risk Molecular Targeted Therapy Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Forecasting Proton Therapy Precision Medicine Humans Artificial Intelligence
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Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.

Molecules (Basel, Switzerland) Jun 4, 2019
Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficacy of machine learning in these arenas is reliant upon highly accurate and abundant data. These two l...
Workflow Models, Biological Molecular Targeted Therapy Algorithms Reproducibility of Results Biomarkers, Tumor ROC Curve Bayes Theorem Drug Discovery Antineoplastic Agents Humans Neural Networks, Computer Machine Learning
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Deep Learning to Therapeutically Target Unreported Complexes.

Trends in pharmacological sciences May 21, 2019
The disruption of large protein-protein (PP) interfaces remains a challenge in targeted therapy. Designing drugs that compete with binding partners is daunting, especially when the structure of the protein complex is unknown. To address the problem w...
Drug Discovery Deep Learning Humans Databases, Factual Protein Interaction Maps Proteins Molecular Targeted Therapy
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Prediction of drug-target interaction by integrating diverse heterogeneous information source with multiple kernel learning and clustering methods.

Computational biology and chemistry Dec 2, 2018
BACKGROUND: Identification of potential drug-target interaction pairs is very important for pharmaceutical innovation and drug discovery. Numerous machine learning-based and network-based algorithms have been developed for predicting drug-target inte...
Computational Biology Cluster Analysis Molecular Targeted Therapy Algorithms Neoplasms Protein Binding Humans Machine Learning
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Deep learning-based transcriptome data classification for drug-target interaction prediction.

BMC genomics Sep 24, 2018
BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded...
Machine Learning Algorithms Databases, Factual Humans Transcriptome Proteins Molecular Targeted Therapy Computer Simulation Models, Theoretical Drug Interactions Drug Discovery Gene Expression Profiling
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