Histidine-enhanced gene delivery systems: The state of the art.

Gene therapy has emerged as a promising tool for treating different intractable diseases, particularly cancer or even viral diseases such as COVID-19 (coronavirus disease 2019). In this context, various non-viral gene carriers are being explored to transfer DNA or RNA sequences into target cells. Here, we review the applications of the naturally occurring amino acid histidine in the delivery of nucleic acids into cells. The biocompatibility of histidine-enhanced gene delivery systems has encouraged their wider use in gene therapy. Histidine-based gene carriers can involve the modification of peptides, dendrimers, lipids or nanocomposites. Several linear polymers, such as polyethylenimine, poly-l-lysine (synthetic) or dextran and chitosan (natural), have been conjugated with histidine residues to form complexes with nucleic acids for intracellular delivery. The challenges, opportunities and future research trends of histidine-based gene deliveries are investigated.

A multimodal deep learning-based drug repurposing approach for treatment of COVID-19.

Recently, various computational methods have been proposed to find new therapeutic applications of the existing drugs. The Multimodal Restricted Boltzmann Machine approach (MM-RBM), which has the capability to connect the information about the multiple modalities, can be applied to the problem of drug repurposing. The present study utilized MM-RBM to combine two types of data, including the chemical structures data of small molecules and differentially expressed genes as well as small molecules perturbations. In the proposed method, two separate RBMs were applied to find out the features and the specific probability distribution of each datum (modality). Besides, RBM was used to integrate the discovered features, resulting in the identification of the probability distribution of the combined data. The results demonstrated the significance of the clusters acquired by our model. These clusters were used to discover the medicines which were remarkably similar to the proposed medications to treat COVID-19. Moreover, the chemical structures of some small molecules as well as dysregulated genes' effect led us to suggest using these molecules to treat COVID-19. The results also showed that the proposed method might prove useful in detecting the highly promising remedies for COVID-19 with minimum side effects. All the source codes are accessible using https://github.com/LBBSoft/Multimodal-Drug-Repurposing.git.