Trends in global warming and evolution of polymerase basic protein 2 family from influenza a virus

Both global warming and influenza trouble humans in varying ways, therefore it is important to study the trends in both global warming and evolution of influenza A virus, in particular, proteins from influenza A virus. Recently, we have conducted two studies along this line to determine the trends between global warming and polymerase acidic protein as well as matrix protein 2. Although these two studies reveal some interesting findings, many studies are still in need because at least there are ten different proteins in influenza A virus. In this study, we analyze the trends in global warming and evolution of polymerase basic protein 2 (PB2) from influenza A virus. The PB2 evolution from 1956 to 2008 was defined using the unpredictable portion of aminoacid pair. Then the trend in this evolution was compared with the trend in the global temperature, the temperature in north and south hemispheres, and the temperature in influenza A virus sampling site and species carrying influenza A virus. The results show the similar trends in global warming and in PB2 evolution, which are in good agreement with our previous studies in polymerase acidic protein and matrix protein 2 from influenza A virus.

Prediction of mutation position, mutated amino acid and timing in hemagglutinins from North America H1 influenza A virus

This study was trying to predict the mutations in H1 hemagglutinins of influenza A virus from North America including the predictions of mu-tation position, the predictions of would-be-mutated amino acids and the predictions of time of occurrence of mutations. The results paved a possible way for accurate, precise and reliable prediction of mutation in proteins from influenza A virus.

Descriptively probabilistic relationship between mutated primary structure of von Hippel-Lindau protein and its clinical outcome

In this study, we use the cross-impact analysis to build a descriptively probabilistic relationship between mutant von Hippel-Lindau protein and its clinical outcome after quantifying mutant von Hippel-Lindau proteins with the amino-acid distribution probability, then we use the Bayes-ian equation to determine the probability that the von Hippel-Lindau disease occurs under a mutation, and finally we attempt to distinguish the classifications of clinical outcomes as well as the endocrine and nonendocrine neoplasia induced by mutations of von Hippel-Lindau protein. The results show that a patient has 9/10 chance of being von Hippel-Lindau disease when a new mutation occurs in von Hippel- Lindau protein, the possible distinguishing of classifications of clinical outcomes using mod-eling, and the explanation of the endocrine and nonendocrine neoplasia in modeling view.

Fitting evolutionary process of matrix protein 2 family from influenza A virus using analytical solution of differential equation

The evolution of protein family is a process along the time course, thus any mathematical methods that can describe a process over time could be possible to describe an evolutionary process. In our previously concept-initiated study, we attempted to use the differential equation to describe the evolution of hemagglutinins from influenza A viruses, and to discuss various issues related to the building of differential equation. In this study, we attempted not only to use the differential equation to describe the evolution of matrix protein 2 family from influenza A virus, but also to use the analytical solution to fit its evolutionary process. The results showed that the fitting was possible and workable. The fitted model parameters provided a way to further determine the evolutionary dynamics and kinetics, a way to more precisely predict the time of occurrence of mutation, and a way to figure out the interaction between protein family and its environment.

Mutation pattern in human adrenoleukodystrophy protein in terms of amino-acid pair predictability

The mutation pattern in protein is a very important feature and is studied through various approaches including the study on mutation pattern in domains where amino acids are converted into numbers from letters. In this study, we converted the amino acids in human adrenoleukodystrophy protein with its 128 missense mutations into random domain using the amino-acid pair predictability, and then we studied their mutation patterns. The results show 1) the mutations are more likely to target the amino-acid pairs whose actual frequency is larger than their predicted one, 2) the mutations are more likely to form the amino-acid pairs whose actual frequency is smaller than their predicted frequency, 3) mutations are more likely to occur at unpredictable amino-acid pairs, and 4) mutations have the trend to narrow the difference between predicted and actual frequencies of amino-acid pairs.