Structural informatic study of determined and AlphaFold2 predicted molecular structures of 13 human solute carrier transporters and their water-soluble QTY variants.

Solute carrier transporters are integral membrane proteins, and are important for diverse cellular nutrient transports, metabolism, energy demand, and other vital biological activities. They have recently been implicated in pancreatic cancer and other cancer metastasis, angiogenesis, programmed cell death and proliferation, cell metabolism and chemo-sensitivity. Here we report the study of 13 human solute carrier membrane transporters using the highly accurate AlphaFold2 predictions of 3D protein structures. In the native structures, there are hydrophobic amino acids leucine (L), isoleucine (I), valine (V) and phenylalanine (F) in the transmembrane alpha-helices. These hydrophobic amino acids L, I, V, F are systematically replaced by hydrophilic amino acids glutamine (Q), threonine (T) and tyrosine (Y), thus the QTY code. Therefore, these QTY variant transporters become water-soluble without requiring detergents. We present the superposed structures of these native solute carrier transporters and their water-soluble QTY variants. The superposed structures show remarkable similarity with RMSD ~ 1 Å-< 3 Å despite > 46% protein sequence substitutions in transmembrane alpha-helices. We also show the differences of surface hydrophobicity between the native solute carrier transporters and their QTY variants. Our study may further stimulate designs of water-soluble transmembrane proteins and other aggregated proteins for drug discovery and biotechnological applications.

Probing the Suitability of Different Ca2+ Parameters for Long Simulations of Diisopropyl Fluorophosphatase.

Organophosphate hydrolases are promising as potential biotherapeutic agents to treat poisoning with pesticides or nerve gases. However, these enzymes often need to be further engineered in order to become useful in practice. One example of such enhancement is the alteration of enantioselectivity of diisopropyl fluorophosphatase (DFPase). Molecular modeling techniques offer a unique opportunity to address this task rationally by providing a physical description of the substrate-binding process. However, DFPase is a metalloenzyme, and correct modeling of metal cations is a challenging task generally coming with a tradeoff between simulation speed and accuracy. Here, we probe several molecular mechanical parameter combinations for their ability to empower long simulations needed to achieve a quantitative description of substrate binding. We demonstrate that a combination of the Amber19sb force field with the recently developed 12-6 Ca2+ models allows us to both correctly model DFPase and obtain new insights into the DFP binding process.