Adera2.0: A Drug Repurposing Workflow for Neuroimmunological Investigations Using Neural Networks.

Drug repurposing in the context of neuroimmunological (NI) investigations is still in its primary stages. Drug repurposing is an important method that bypasses lengthy drug discovery procedures and focuses on discovering new usages for known medications. Neuroimmunological diseases, such as Alzheimer's, Parkinson's, multiple sclerosis, and depression, include various pathologies that result from the interaction between the central nervous system and the immune system. However, the repurposing of NI medications is hindered by the vast amount of information that needs mining. We previously presented Adera1.0, which was capable of text mining PubMed for answering query-based questions. However, Adera1.0 was not able to automatically identify chemical compounds within relevant sentences. To challenge the need for repurposing known medications for neuroimmunological diseases, we built a deep neural network named Adera2.0 to perform drug repurposing. The workflow uses three deep learning networks. The first network is an encoder and its main task is to embed text into matrices. The second network uses a mean squared error (MSE) loss function to predict answers in the form of embedded matrices. The third network, which constitutes the main novelty in our updated workflow, also uses a MSE loss function. Its main usage is to extract compound names from relevant sentences resulting from the previous network. To optimize the network function, we compared eight different designs. We found that a deep neural network consisting of an RNN neural network and a leaky ReLU could achieve 0.0001 loss and 67% sensitivity. Additionally, we validated Adera2.0's ability to predict NI drug usage against the DRUG Repurposing Hub database. These results establish the ability of Adera2.0 to repurpose drug candidates that can shorten the development of the drug cycle. The workflow could be download online.

Additive effect of combined application of magnesium and MK-801 on analgesic action of morphine.

As previously reported, magnesium ions (Mg(2+)) administered in relatively low doses markedly potentiated opioid analgesia in neuropathic pain, in which the effectiveness of opioids is limited. Considering that Mg(2+) behaves like an N-methyl-D-aspartate receptor antagonist, the effect of this ion on the analgesic action of morphine was compared with that of MK-801. Acute pain was evoked by mechanical or thermal stimuli, whereas neuropathic hyperalgesia was induced by streptozotocin (STZ) administration. Magnesium sulphate (40 mg/kg i.p.) or MK-801 (0.05 mg/kg s.c.) administered alone did not modify the nociceptive threshold to acute stimuli or the streptozotocin hyperalgesia but significantly augmented the analgesic action of morphine (5 mg/kg i.p.). Furthermore, if these drugs (i.e. magnesium sulphate and MK-801) were applied concomitantly, a clear additive effect on the analgesic action of morphine occurred in both models of pain. Possible explanations of these observations are discussed.