Early prediction and detection enable reduced transmission of human diseases and provide healthcare professionals ample time to make subsequent diagnoses and treatment strategies. This, in turn, aids in saving more lives and results in lower medical costs. Designing small chemical molecules to treat fatal disorders is also urgently needed to address the high death rate of these diseases worldwide. A recent analysis of published literature suggested that deep learning (DL) based models apply more potential algorithms to hybrid databases of chemical data. Considering the above, we first discussed the concept of DL architectures and their applications in drug development and diagnostics in this review. Although DL-based approaches have applications in several fields, in the following sections of the article, we focus on recent developments of DL-based techniques in biology, notably in structure prediction, cancer drug development, COVID infection diagnostics, and drug repurposing strategies. Each review section summarizes several cutting-edge, recently developed DL-based techniques. Additionally, we introduced the approaches presented in our group, whose prediction accuracy is relatively comparable with current computational models. We concluded the review by discussing the benefits and drawbacks of DL techniques and outlining the future paths for data collecting and developing efficient computational models.

Targeted protein degradation (TPD) aids in developing novel bifunctional small-molecule degraders and eliminates proteins of interest. The TPD approach shows promising results in oncological, neuro...

The fat mass and obesity-associated (FTO) protein catalyzes metal-dependent modifications of nucleic acids, namely the demethylation of methyl adenosine inside mRNA molecules. The FTO protein has been identified as a potential target for developing anticancer therapies. Identifying a suitable ligand-targeting FTO protein is crucial to developing chemotherapeutic medicines to combat obesity and cancer. Scientists worldwide have employed many methodologies to discover a potent inhibitor for the FTO protein. This study uses deep learning-based methods and molecular docking techniques to investigate the FTO protein as a target. Our strategy involves systematically screening a database of small chemical compounds. By utilizing the crystal structures of the FTO complexed with ligands, we successfully identified three small-molecule chemical compounds (ZINC000003643476, ZINC000000517415, and ZINC000001562130) as inhibitors of the FTO protein. The identification process was accomplished by employing a combination of screening techniques, specifically deep learning (DeepBindGCN) and Autodock vina, on the ZINC database. These compounds were subjected to comprehensive analysis using 100 nanoseconds of molecular dynamics and binding free energy calculations. The findings of our study indicate the identification of three candidate inhibitors that might effectively target the human fat mass and obesity protein. The results of this study have the potential to facilitate the exploration of other chemicals that can interact with FTO. Conducting biochemical studies to evaluate these compounds’ effectiveness may contribute to improving fat mass and obesity treatment strategies.

Probiotic bacteria are producers of secretory products such as bacteriocins and polysaccharides. Both homopolymeric and heteropolymeric exopolysaccharides (EPS) present on the surface of microorganisms have shown beneficial properties. While the fact that they play a role in bacterial homeostasis is well established, studies exploring their health promoting effects have also gained traction. Some exopolysaccharides function by inducing immune tolerance, others act by evading immune responses such as those by B and T cells. The interaction between the EPS and the immune system helps protect the bacteria against an attack by the host immune system. Several exopolysaccharides also show tolerogenic properties by reducing the amount of pro-inflammatory cytokines and increasing IL-10 production. They are also associated with anti-bacterial activity, anti-biofilm activity and anti-tumour properties. This review highlights the different types of exopolysaccharides and their health benefiting potentials. Better understanding of these mechanisms will pave the way for harnessing their potential to improve our health.