M2 pyruvate kinase provides a mechanism for nutrient sensing and regulation of cell proliferation

We show that the M2 isoform of pyruvate kinase (M2PYK) exists in equilibrium between monomers and tetramers regulated by allosteric binding of naturally occurring small-molecule metabolites. Phenylalanine stabilizes an inactive T-state tetrameric conformer and inhibits M2PYK with an IC(50) value of 0.24 mM, whereas thyroid hormone (triiodo-l-thyronine, T3) stabilizes an inactive monomeric form of M2PYK with an IC(50) of 78 nM. The allosteric activator fructose-1,6-bisphosphate [F16BP, AC(50) (concentration that gives 50% activation) of 7 μM] shifts the equilibrium to the tetrameric active R-state, which has a similar activity to that of the constitutively fully active isoform M1PYK. Proliferation assays using HCT-116 cells showed that addition of inhibitors phenylalanine and T3 both increased cell proliferation, whereas addition of the activator F16BP reduced proliferation. F16BP abrogates the inhibitory effect of both phenylalanine and T3, highlighting a dominant role of M2PYK allosteric activation in the regulation of cancer proliferation. X-ray structures show constitutively fully active M1PYK and F16BP-bound M2PYK in an R-state conformation with a lysine at the dimer-interface acting as a peg in a hole, locking the active tetramer conformation. Binding of phenylalanine in an allosteric pocket induces a 13° rotation of the protomers, destroying the peg-in-hole R-state interface. This distinct T-state tetramer is stabilized by flipped out Trp/Arg side chains that stack across the dimer interface. X-ray structures and biophysical binding data of M2PYK complexes explain how, at a molecular level, fluctuations in concentrations of amino acids, thyroid hormone, and glucose metabolites switch M2PYK on and off to provide the cell with a nutrient sensing and growth signaling mechanism

Path to Facilitate the Prediction of Functional Amino Acid Substitutions in Red Blood Cell Disorders – A Computational Approach

A major area of effort in current genomics is to distinguish mutations that are functionally neutral from those that contribute to disease. Single Nucleotide Polymorphisms (SNPs) are amino acid substitutions that currently account for approximately half of the known gene lesions responsible for human inherited diseases. As a result, the prediction of non-synonymous SNPs (nsSNPs) that affect protein functions and relate to disease is an important task.In this study, we performed a comprehensive analysis of deleterious SNPs at both functional and structural level in the respective genes associated with red blood cell metabolism disorders using bioinformatics tools. We analyzed the variants in Glucose-6-phosphate dehydrogenase (G6PD) and isoforms of Pyruvate Kinase (PKLR & PKM2) genes responsible for major red blood cell disorders. Deleterious nsSNPs were categorized based on empirical rule and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for evaluation of protein structure stability.We argue here that bioinformatics tools can play an important role in addressing the complexity of the underlying genetic basis of Red Blood Cell disorders. Based on our investigation, we report here the potential candidate SNPs, for future studies in human Red Blood Cell disorders. Current study also demonstrates the presence of other deleterious mutations and also endorses with in vivo experimental studies. Our approach will present the application of computational tools in understanding functional variation from the perspective of structure, expression, evolution and phenotype