Leveraging computation in the development of peptide therapeutics has garnered increasing recognition as a valuable tool to generate novel therapeutics for disease-related targets. To this end, computation has transformed the field of peptide design through identifying novel therapeutics that exhibit enhanced pharmacokinetic properties and reduced toxicity. The process of in-silico peptide design involves the application of molecular docking, molecular dynamics simulations, and machine learning algorithms. Three primary approaches for peptide therapeutic design including structural-based, protein mimicry, and short motif design have been predominantly adopted. Despite the ongoing progress made in this field, there are still significant challenges pertaining to peptide design including: enhancing the accuracy of computational methods; improving the success rate of preclinical and clinical trials; and developing better strategies to predict pharmacokinetics and toxicity. In this review, we discuss past and present research pertaining to the design and development of in-silico peptide therapeutics in addition to highlighting the potential of computation and artificial intelligence in the future of disease therapeutics.

Lithium Chloride (LiCl) toxicity, mode of action and cellular responses have been the subject of active investigations over the past decades. In yeast, LiCl treatment is reported to reduce the activity and alters the expression of PGM2, a gene that encodes a phosphoglucomutase involved in sugar metabolism. Reduced activity of phosphoglucomutase in the presence of galactose causes an accumulation of intermediate metabolites of galactose metabolism leading to a number of phenotypes including growth defect. In the current study, we identify two understudied yeast genes, YTA6 and YPR096C that when deleted, cell sensitivity to LiCl is increased when galactose is used as a carbon source. The 5’-UTR of PGM2 mRNA is structured. Using this region, we show that YTA6 and YPR096C influence the translation of PGM2 mRNA.

Heavy metal and metalloid contaminations are among the most concerning types of pollutant in the environment. Consequently, it is important to investigate the molecular mechanisms of cellular responses and detoxification pathways for these compounds in living organisms. To date, a number of genes have been linked to the detoxification process. The expression of these genes can be controlled at both transcriptional and translational levels. In baker’s yeast, Saccharomyces cerevisiae, resistance to a wide range of toxic metals is regulated by glutathione S-transferases. Yeast URE2 encodes for a protein that has glutathione peroxidase activity and is homologous to mammalian glutathione S-transferases. The URE2 expression is critical to cell survival under heavy metal stress. Here, we report on the finding of two genes, ITT1, an inhibitor of translation termination, and RPS1A, a small ribosomal protein, that when deleted yeast cells exhibit similar metal sensitivity phenotypes to gene deletion strain for URE2. Neither of these genes were previously linked to metal toxicity. Our gene expression analysis illustrates that these two genes affect URE2 mRNA expression at the level of translation.

Reactive oxygen species (ROS) are among the most severe types of cellular stressors with the ability to damage essential cellular biomolecules. Excess levels of ROS are correlated with multiple pathophysiological conditions including neurodegeneration, diabetes, atherosclerosis, and cancer. Failure to regulate the severely imbalanced levels of ROS can ultimately lead to cell death, highlighting the importance of investigating the molecular mechanisms involved in the detoxification procedures that counteract the effects of these compounds in living organisms. One of the most abundant forms of ROS is H ₂ O ₂ , mainly produced by the electron transport chain in the mitochondria. Numerous genes have been identified as essential to the process of cellular detoxification. Yeast YAP1 , which is homologous to mammalian AP‐1 type transcriptional factors, has a key role in oxidative detoxification by upregulating the expression of antioxidant genes in yeast. The current study reveals novel functions for COX5A and NPR3 in H ₂ O ₂ ‐induced stress by demonstrating that their deletions result in a sensitive phenotype. Our follow‐up investigations indicate that COX5A and NPR3 regulate the expression of YAP1 through an alternative mode of translation initiation. These novel gene functions expand our understanding of the regulation of gene expression and defense mechanism of yeast against oxidative stress.

Lithium chloride (LiCl) has been widely researched and utilized as a therapeutic option for bipolar disorder (BD). Several pathways, including cell signaling and signal transduction pathways in mammalian cells, are shown to be regulated by LiCl. LiCl can negatively control the expression and activity of PGM2, a phosphoglucomutase that influences sugar metabolism in yeast. In the presence of galactose, when yeast cells are challenged by LiCl, the phosphoglucomutase activity of PGM2p is decreased, causing an increase in the concentration of toxic galactose metabolism intermediates that result in cell sensitivity. Here, we report that the null yeast mutant strains DBP7∆ and YRF1-6∆ exhibit increased LiCl sensitivity on galactose-containing media. Additionally, we demonstrate that DBP7 and YRF1-6 modulate the translational level of PGM2 mRNA, and the observed alteration in translation seems to be associated with the 5′-untranslated region (UTR) of PGM2 mRNA. Furthermore, we observe that DBP7 and YRF1-6 influence, to varying degrees, the translation of other mRNAs that carry different 5′-UTR secondary structures.

Platelet-type von Willebrand disease (PT-VWD) refers to a rare bleeding disorder caused by gain-of-function mutations in platelet glycoprotein Ibα (GPIbα). These mutations lead to a hyperactive protein-protein interaction (PPI) with von Willebrand factor (VWF) and pathological platelet aggregation. Counterintuitively, patients with PT-VWD present with a bleeding diathesis as opposed to thrombosis. Despite well-defined genetic etiology, no targeted therapy exists for PT-VWD. Here, we sought to develop a peptide inhibitor that selectively targets the aberrant interaction in PT-VWD. Using the In Silico Protein Synthesizer, we designed and screened 10 000 peptides for predicted affinity and specificity toward GPIbαMet239Val. Functional validation of top-ranked peptides included a combination of in vitro functional assays using GPIbαGly233Val, Met239Val and ex vivo platelet assays from patients with PT-VWD. One peptide, G14, emerged as a potent and selective inhibitor of the GPIbαGly233Val, Met239Val–VWF PPI. Functional assays demonstrated that G14 disrupts this interaction without binding GPIbαWT or VWF alone. The peptide also displays picomolar affinity (6.6 pM) for GPIbαGly233Val, Met239Val. Structural modeling predicted G14 binds the β-switch region of GPIbαGly233Val, Met239Val involving the disease-associated Val239 residue. In platelet-rich plasma from a patient with PT-VWD, G14 selectively inhibited platelet-VWF binding and ristocetin-induced agglutination, with no measurable effect on healthy samples. The G14 peptide appears to be a highly specific inhibitor of the GPIbαGly233Val, Met239Val–VWF interaction, providing proof-of-concept data for therapeutic development in PT-VWD. Furthermore, the protein and platelet specificity of these data suggest that G14 may be a potential diagnostic tool for PT-VWD. The approach highlights the utility of artificial intelligence in targeting disease-specific PPIs with high precision.