An attention mechanism-based LSTM network for cancer kinase activity prediction

Despite the endeavours and achievements made in treating cancers during the past decades, resistance to available kinase drugs continues to be a major problem in cancer therapies. Thus, it is highly desirable to develop computational models that can predict the bioactivity of a compound against cancer kinases. Here, we present a Long Short-Term Memory (LSTM) framework for predicting the activities of lead molecules against seven different kinases. A total of 14,907 compounds from the ChEMBL database were selected for model building. Two different molecular representations, namely, 2D descriptors and MACCS fingerprints were subjected to the LSTM method for the training process. We also successfully integrated an attention mechanism into our model, which helped us to interpret the contribution of chemical features on kinase activity. The attention mechanism extracted the significant chemical moieties more effectively by taking them into consideration during the activity prediction. The recorded accuracies in the test sets for both 2D descriptors and MACCS fingerprints-based models were 0.81 and 0.78, respectively. The receiver operating characteristic curve (ROC)-area under the curve (AUC) score for both models was in the range of 0.8-0.99. The proposed framework can be a good starting point for the development of new cancer kinase drugs.

Targeting dementias through cancer kinases inhibition

The failures in Alzheimer's disease (AD) therapy strongly suggest the importance of reconsidering the research strategies analyzing other mechanisms that may take place in AD as well as, in general, in other neurodegenerative dementias. Taking into account that in AD a variety of defects result in neurotransmitter activity and signaling efficiency imbalance, neuronal cell degeneration and defects in damage/repair systems, aberrant and abortive cell cycle, glial dysfunction, and neuroinflammation, a target may be represented by the intracellular signaling machinery provided by the kinome. In particular, based on the observations of a relationship between cancer and AD, we focused on cancer kinases for targeting neurodegeneration, highlighting the importance of targeting the intracellular pathways at the intersection between cell metabolism control/duplication, the inhibition of which may stop a progression in neurodegeneration.