A backbone‐dependent rotamer library with high (ϕ, ψ) coverage using metadynamics simulations

Backbone‐dependent rotamer libraries are commonly used to assign the side chain dihedral angles of amino acids when modeling protein structures. Most rotamer libraries are created by curating protein crystal structure data and using various methods to extrapolate the existing data to cover all possible backbone conformations. However, these rotamer libraries may not be suitable for modeling the structures of cyclic peptides and other constrained peptides because these molecules frequently sample backbone conformations rarely seen in the crystal structures of linear proteins. To provide backbone‐dependent side chain information beyond the α‐helix, β‐sheet, and PPII regions, we used explicit‐solvent metadynamics simulations of model dipeptides to create a new rotamer library that has high coverage in the (ϕ, ψ) space. Furthermore, this approach can be applied to build high‐coverage rotamer libraries for noncanonical amino acids. The resulting Metadynamics of Dipeptides for Rotamer Distribution (MEDFORD) rotamer library predicts the side chain conformations of high‐resolution protein crystal structures with similar accuracy (~80%) to a state‐of‐the‐art rotamer library. Our ability to test the accuracy of MEDFORD at predicting the side chain dihedral angles of amino acids in noncanonical backbone conformation is restricted by the limited structural data available for cyclic peptides. For the cyclic peptide data that are currently available, MEDFORD and the state‐of‐the‐art rotamer library perform comparably. However, the two rotamer libraries indeed make different rotamer predictions in noncanonical (ϕ, ψ) regions. For noncanonical amino acids, the MEDFORD rotamer library predicts the χ ₁ values with approximately 75% accuracy.     

Rapamycin/metformin co‐treatment normalizes insulin sensitivity and reduces complications of metabolic syndrome in type 2 diabetic mice

Rapamycin treatment has positive and negative effects on progression of type 2 diabetes (T2D) in a recombinant inbred polygenic mouse model, male NONcNZO10/LtJ (NcZ10). Here, we show that combination treatment with metformin ameliorates negative effects of rapamycin while maintaining its benefits. From 12 to 30 weeks of age, NcZ10 males were fed a control diet or diets supplemented with rapamycin, metformin, or a combination of both. Rapamycin alone reduced weight gain, adiposity, HOMA‐IR, and inflammation, and prevented hyperinsulinemia and pre‐steatotic hepatic lipidosis, but exacerbated hyperglycemia, hypertriglyceridemia, and pancreatic islet degranulation. Metformin alone reduced hyperinsulinemia and circulating c‐reactive protein, but exacerbated nephropathy. Combination treatment retained the benefits of both while preventing many of the deleterious effects. Importantly, the combination treatment reversed effects of rapamycin on markers of hepatic insulin resistance and normalized systemic insulin sensitivity in this inherently insulin‐resistant model. In adipose tissue, rapamycin attenuated the expression of genes associated with adipose tissue expansion (Mest, Gpam), inflammation (Itgam, Itgax, Hmox1, Lbp), and cell senescence (Serpine1). In liver, the addition of metformin counteracted rapamycin‐induced alterations of G6pc, Ppara, and Ldlr expressions that promote hyperglycemia and hypertriglyceridemia. Both rapamycin and metformin treatment reduced hepatic Fasn expression, potentially preventing lipidosis. These results delineate a state of “insulin signaling restriction” that withdraws endocrine support for further adipogenesis, progression of the metabolic syndrome, and the development of its comorbidities. Our results are relevant for the treatment of T2D, the optimization of current rapamycin‐based treatments for posttransplant rejection and various cancers, and for the development of treatments for healthy aging.     

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