Comparing 2 crystal structures and 12 AlphaFold2-predicted human membrane glucose transporters and their water-soluble glutamine, threonine and tyrosine variants

Abstract

Membrane transporters including glucose transporters (GLUTs) are involved in cellular energy supplies, cell metabolism and other vital biological activities. They have also been implicated in cancer proliferation and metastasis, thus they represent an important target in combatting cancer. However, membrane transporters are very difficult to study due to their multispan transmembrane properties. The new computational tool, AlphaFold2, offers highly accurate predictions of three-dimensional protein structures. The glutamine, threonine and tyrosine (QTY) code provides a systematic method of rendering hydrophobic sequences into hydrophilic ones. Here, we present computational studies of native integral membrane GLUTs with 12 transmembrane helical segments determined by X-ray crystallography and CryoEM, comparing the AlphaFold2-predicted native structure to their water-soluble QTY variants predicted by AlphaFold2. In the native structures of the transmembrane helices, there are hydrophobic amino acids leucine (L), isoleucine (I), valine (V) and phenylalanine (F). Applying the QTY code, these hydrophobic amino acids are systematically replaced by hydrophilic amino acids, glutamine (Q), threonine (T) and tyrosine (Y) rendering them water-soluble. We present the superposed structures of native GLUTs and their water-soluble QTY variants. The superposed structures show remarkable similar residue mean square distance values between 0.47 and 3.6 Å (most about 1–2 Å) despite >44% transmembrane amino acid differences. We also show the differences of hydrophobicity patches between the native membrane transporters and their QTY variants. We explain the rationale why the membrane protein QTY variants become water-soluble. Our study provides insight into the differences between the hydrophobic helices and hydrophilic helices, and offers confirmation of the QTY method for studying multispan transmembrane proteins and other aggregated proteins through their water-soluble variants.

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

“…We previously reported 36 , 37 use of the AlphaFold2 tool to predict structures of the water-soluble variants of G protein coupled receptor chemokine receptors and glucose transporters, and compared them to the known experimentally-determined crystal or CryoEM structures.…”

“…The expressed and purified water-soluble proteins exhibited predicted characteristics and retained ligand-binding activity 31 – 35 . In July 2021, we prepared QTY variant protein structure predictions using AlphaFold2, achieving better results in 1–2 hours 36 , 37 , rather than ~ 5 weeks for each molecular simulation using GOMoDo, AMBER and YASARA programs 31 – 33 . We also produced a program and website for generating the membrane protein water-soluble QTY variants 38 .…”

Hiding in plain sight: three chemically distinctα-helix types

“…Despite significant amino acid changes (overall >24% and TM >44%), the crystal structure of GLUT1 and the predicted structure of its QTY variant GLUT1 QTY superpose well (RMSD = 1.55 Å). Likewise, the crystal structure of GLUT3 closely resembles that of the predicted structure of its variant GLUT3 QTY (RMSD = 1.03 Å) (Smorodina et al ., 2022). We believe that this simple QTY code could be widely applicable to diverse membrane proteins that have TM α -helices.…”

Structural bioinformatics studies of glutamate transporters and their AlphaFold2 predicted water-soluble QTY variants and uncovering the natural mutations of L->Q, I->T, F->Y and Q->L, T->I and Y->F

“…The expressed and purified water-soluble variants exhibited the predicted characteristics and maintained their ligand-binding activity [9][10][11][12][13][14]. After the Alpha-Fold2 was released in July 2021, we immediately used AlphaFold2 to make QTY variant protein structure predictions and achieved improved results in less than an hour [15][16][17][18], compared to the previous method which took approximately 5 weeks per simulation [9][10][11]. Additionally, we developed a program and website for designing water-soluble QTY variants of membrane proteins [19].…”