The Study Of Relation Between Character And Structure Of Alpha-amylase With Bioinformatics

The relation between character and structure of alpha-amylase was studied in thispaper.First, alpha-amylase general character. Built an alpha-amylase's bank and everykingdom bank. After analysis, found those results. (1) The alpha-amylases' averagelength was 525.35484. From bacteria, archaea, to eukaryota, the sequence lengthdecreased. The sequence average length of different kingdoms were:bacteria,609.79832;archaea, 508.68182;eukaryota, 477.17085. The sequence lengths maximumwere: bacteria, 1826;archaea, 732;eukaryota, 721. (2) Comparing to common protein:alanine, cysteine, glutamic acid, lysine, their content was greater than commonprotein, cysteine content was 2 times common protein. Aspartic acid, phenylalanine,glycine, asparagine, tryptophan, tyrosine, their content wass smaller than commonprotein,tryptophan content is half of common protein. Other amino acids contentin alpha-amylase was same as common protein roughly. (3) In 3 kingdoms, phenylalanine,histidine, methionine, proline, arginine, valine, tryptophan, their content was sameeach other roughly. From archaea, bacteria to eukaryota, glutamic acid, leucine,tyrosine, their content depressed;Lysine, asparagine, serine, their contentincreased. (4) With glutamic acid, leucine, glutamine and threonine twain, man woulddistinguish roughly that: the alpha-amylase belonged which kingdom.Second, alpha-amylase optimal pH. An alpha-amylase's pH-sequence bank was built.(1)Predicting optimal pH of alpha-amylase with percent of amino acid. Literatures'optimal pH value was from 3.5 to 9.0;predicting optimal pH value was from 4.94415to 7.86983. Its correlation coefficient was 0.68341. Predicting optimal pH of noexperimental alpha-amylase, the data was from 3.85781 to 10.95326. (2)Relationbetween amino acid percentage and optimal pH of alpha-amylase. Analyze amino acidcoefficient absolute value, there were 3 types amino acid influence to alpha-amylasepH: great influence coefficient, 13 amino acids;middling influence coefficient,4 amino acids;small influence coefficient, 3 amino acids. Electrical charge aminoacid content rose, optimal pH became big. Fat amino acid content rose, optimal pHbecame small. (3)Related dipeptide and characteristic dipeptide of optimal pH inalpha-amylase. There were 8 related dipeptides with alpha-amylase's optimal pH.There were 5 serine dipeptides in higher pH alpha-amylase characteristic raredipeptide;at one time there were 5 serine dipeptides in high pH alpha-amylasecharacteristic rich dipeptide. Common dipeptide were CC,CF,MH,CQ,CK,CH,HC,HN,WC,CY,AC,KC,GC,CP,LC,QT,FC,WH,QC and RR. In rich characteristic dipeptide,the high optimal pH alpha-amylase had the greatest significance. The middle optimalpH alpha-amylase had the smallest significance. In rare characteristic dipeptide,the higher optimal pH alpha-amylase had the greatest significance. The middle optimalpH alpha-amylase had the smallest significance.Third, alpha-Amylase optimal temperature. Built alpha-amylase'stemperature-sequence bank. (1) Predicting optimal temperature of alpha-amylase withpercent of amino acid. Literatures' optimal temperature value was from 37°C to100°C;predicting optimal temperature value was from 21.35196°C to 106.30676°C. Predicting temperature of no experimental alpha-amylase, the data was from17.93274°C to 117.8403°C. Its correlation coefficient was 0.95971. (2) Relationbetween amino acid percentage and optimal temperature of alpha-amylase. Amino acidof the greatest influence coefficient was cysteine. Polar amino acid had greatinfluence on alpha-amylase optimal temperature. Most amino acids decreasedalpha-amylase optimal temperature. (3) Related dipeptide and characteristicdipeptide of optimal temperature in alpha-amylase. There were 63 related dipeptideswith alpha-amylase's optimal temperature. There were 6 alanine dipeptides innegative related dipeptides;there were 6 serine dipeptides in negative relateddipeptides, too. There were 5 lysine dipeptides in higher temperature alpha-amylasecharacteristic rich dipeptide;meanwhile there were 5 lysine dipeptides in hightemperature alpha-amylase characteristic rare dipeptide. Common dipeptide were CQ,CF,CK,CY,CH,CC,WC,QP,AE,LC,PC,TP,AM,QL,ET,EQ,CV,AC,KC and QM. Inrich characteristic dipeptide,the low optimal temperature alpha-amylase had thegreatest significance;the high optimal temperature alpha-amylase had the smallestsignificance. In rare characteristic dipeptide,the higher optimal temperaturealpha-amylase had the greatest significance;The high optimal temperaturealpha-amylase had the smallest significance.Fourth, alpha-amylase simulation. (1) Q9BPS4 structure with molecular dynamicssimulation. The Q9BPS4 structure optimized with molecular mechanics was chain. TheQ9BPS4 structure at 1ns was agglomerate. The Q9BPS4 structure at the lowest potentialenergy was agglomerate, too. (2) Amylose structure with molecular dynamics simulation.The amylose structure optimized with molecular mechanics was helix chain. The amylosestructure at 1ns was dumbbell shape. The amylose structure at the lowest potentialenergy was dumbbell shape, too.To sum up , built an alpha-amylase's bank and every kingdom bank, analpha-amylase's pH-sequence bank and an alpha-amylase's temperature-sequence bank.Studied the alpha-amylase amino acid feature in different kingdoms. Predictingoptimal pH of alpha-amylase with percent of amino acid, relation between amino acidpercentage and optimal pH of alpha-amylase, related dipeptide and characteristicdipeptide of optimal pH in alpha-amylase. Predicting optimal temperature ofalpha-amylase with percent of amino acid, relation between amino acid percentage andoptimal temperature of alpha-amylase, related dipeptide and characteristic dipeptideof optimal temperature in alpha-amylase. Finally, simulated alpha-amylase(Q9BPS4)and amylose structure with molecular dynamics simulation.Studying the relation between structure and property in alpha-amylase based theamino acid sequence data. This was a new method. It was first trait. These resultswould help alpha-amylase 's optimizing engineering in optimal pH and optimaltemperature. It was second trait. Simulated alpha-amylase and amylose structure withmolecular dynamics simulation. It was third trait.