AIMC Topic: Molecular Targeted Therapy

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Multi-target drug repositioning by bipartite block-wise sparse multi-task learning.

BMC systems biology
BACKGROUND: Finding potential drug targets is a crucial step in drug discovery and development. Recently, resources such as the Library of Integrated Network-Based Cellular Signatures (LINCS) L1000 database provide gene expression profiles induced by...

Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets.

Scientific reports
Identifying drug target genes in gene expression profiles is not straightforward. Because a drug targets proteins and not mRNAs, the mRNA expression of drug target genes is not always altered. In addition, the interaction between a drug and protein c...

Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening.

Journal of chemical information and modeling
In structure-based virtual screening, compound ranking through a consensus of scores from a variety of docking programs or scoring functions, rather than ranking by scores from a single program, provides better predictive performance and reduces targ...

Machine-Learning-Assisted Approach for Discovering Novel Inhibitors Targeting Bromodomain-Containing Protein 4.

Journal of chemical information and modeling
Bromodomain-containing protein 4 (BRD4) is implicated in the pathogenesis of a number of different cancers, inflammatory diseases and heart failure. Much effort has been dedicated toward discovering novel scaffold BRD4 inhibitors (BRD4is) with differ...

Literature evidence in open targets - a target validation platform.

Journal of biomedical semantics
BACKGROUND: We present the Europe PMC literature component of Open Targets - a target validation platform that integrates various evidence to aid drug target identification and validation. The component identifies target-disease associations in docum...

A novel framework for the identification of drug target proteins: Combining stacked auto-encoders with a biased support vector machine.

PloS one
The identification of drug target proteins (IDTP) plays a critical role in biometrics. The aim of this study was to retrieve potential drug target proteins (DTPs) from a collected protein dataset, which represents an overwhelming task of great signif...

Drug repositioning based on triangularly balanced structure for tissue-specific diseases in incomplete interactome.

Artificial intelligence in medicine
Finding new uses for existing drugs has become a new strategy for decades to treat more patients. Few traditional approaches consider the tissue specificities of diseases. Moreover, disease genes, drug targets and protein interaction (PPI) networks r...

SELF-BLM: Prediction of drug-target interactions via self-training SVM.

PloS one
Predicting drug-target interactions is important for the development of novel drugs and the repositioning of drugs. To predict such interactions, there are a number of methods based on drug and target protein similarity. Although these methods, such ...

Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

Tuberculosis (Edinburgh, Scotland)
There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target...