cgd5_783 | Uncharacterized protein

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  • Fasta :-

    >cgd5_783 MVKKKNKKNKKEINKEVLKNAGFDEGEIWRLDFKGEVEFEENVIDQSRFEVPLFDLKGYR SQKKIGKPMGQDIEMEKKHDSDDEREDSEAFDAAAEDDFDEYDVEQQKVDESRFLQKRFE FEVDYMKKLRVWEASFFIHTSENLENTPQEFFYVIEFGHVNPERNYEGTLKRMMVYTAAT LLKPGEVKVLTFPIIVWPKKILYISYSELEMFQISIKLWTIGTFTFNQLLASVKLTLKDV LENDPETHLMFKKHLPAPLGKDGKPRKDLNQKSFEVHRSRVTLQLQEIFDFDISLENWSF IPNKKLPIEIKKAPKFLRLKVPLNNDITSGMSSRSKLKCNKFL
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  • MitoProt II - v1.101 File : /home/rajan/sadaf/4480_mitoprot/test/cgd5_783.fa Sequence name : cgd5_783 Sequence length : 343 VALUES OF COMPUTED PARAMETERS Coef20 : 3.208 CoefTot : -1.059 ChDiff : -2 ZoneTo : 11 KR : 7 DE : 0 CleavSite : 0 HYDROPHOBIC SCALE USED GES KD GVH1 ECS H17 : 0.941 1.300 -0.080 0.546 MesoH : -0.043 0.628 -0.321 0.321 MuHd_075 : 11.489 13.947 4.662 4.047 MuHd_095 : 33.405 20.981 9.999 7.541 MuHd_100 : 22.767 14.288 7.704 5.633 MuHd_105 : 10.051 5.417 4.360 2.986 Hmax_075 : -20.562 1.313 -7.345 -0.472 Hmax_095 : -10.587 2.013 -5.184 0.752 Hmax_100 : -18.300 -1.500 -7.001 -0.200 Hmax_105 : -22.400 -5.300 -8.363 -0.630 CLASS NOT-MITO MITO(/CHLORO) DFM : 0.7767 0.2233 DFMC : 0.7857 0.2143
  • ##### ProP v.1.0b ProPeptide Cleavage Site Prediction ##### ##### Furin-type cleavage site prediction (Arginine/Lysine residues) ##### 343 cgd5_783 MVKKKNKKNKKEINKEVLKNAGFDEGEIWRLDFKGEVEFEENVIDQSRFEVPLFDLKGYRSQKKIGKPMGQDIEMEKKHD 80 SDDEREDSEAFDAAAEDDFDEYDVEQQKVDESRFLQKRFEFEVDYMKKLRVWEASFFIHTSENLENTPQEFFYVIEFGHV 160 NPERNYEGTLKRMMVYTAATLLKPGEVKVLTFPIIVWPKKILYISYSELEMFQISIKLWTIGTFTFNQLLASVKLTLKDV 240 LENDPETHLMFKKHLPAPLGKDGKPRKDLNQKSFEVHRSRVTLQLQEIFDFDISLENWSFIPNKKLPIEIKKAPKFLRLK 320 VPLNNDITSGMSSRSKLKCNKFL 400 ................................................................................ 80 ................................................................................ 160 ................................................................................ 240 ................................................................................ 320 ....................... 400 Propeptide cleavage sites predicted: Arg(R)/Lys(K): 0 Name Pos Context Score Pred ____________________________v_________________ cgd5_783 3 ----MVK|KK 0.061 . cgd5_783 4 ---MVKK|KN 0.101 . cgd5_783 5 --MVKKK|NK 0.106 . cgd5_783 7 MVKKKNK|KN 0.071 . cgd5_783 8 VKKKNKK|NK 0.099 . cgd5_783 10 KKNKKNK|KE 0.093 . cgd5_783 11 KNKKNKK|EI 0.126 . cgd5_783 15 NKKEINK|EV 0.068 . cgd5_783 19 INKEVLK|NA 0.074 . cgd5_783 30 DEGEIWR|LD 0.093 . cgd5_783 34 IWRLDFK|GE 0.062 . cgd5_783 48 NVIDQSR|FE 0.081 . cgd5_783 57 VPLFDLK|GY 0.060 . cgd5_783 60 FDLKGYR|SQ 0.114 . cgd5_783 63 KGYRSQK|KI 0.190 . cgd5_783 64 GYRSQKK|IG 0.109 . cgd5_783 67 SQKKIGK|PM 0.084 . cgd5_783 77 QDIEMEK|KH 0.057 . cgd5_783 78 DIEMEKK|HD 0.107 . cgd5_783 85 HDSDDER|ED 0.127 . cgd5_783 108 YDVEQQK|VD 0.057 . cgd5_783 113 QKVDESR|FL 0.119 . cgd5_783 117 ESRFLQK|RF 0.074 . cgd5_783 118 SRFLQKR|FE 0.241 . cgd5_783 127 FEVDYMK|KL 0.062 . cgd5_783 128 EVDYMKK|LR 0.070 . cgd5_783 130 DYMKKLR|VW 0.127 . cgd5_783 164 GHVNPER|NY 0.124 . cgd5_783 171 NYEGTLK|RM 0.056 . cgd5_783 172 YEGTLKR|MM 0.142 . cgd5_783 183 TAATLLK|PG 0.074 . cgd5_783 188 LKPGEVK|VL 0.056 . cgd5_783 199 PIIVWPK|KI 0.060 . cgd5_783 200 IIVWPKK|IL 0.101 . cgd5_783 217 MFQISIK|LW 0.072 . cgd5_783 234 QLLASVK|LT 0.058 . cgd5_783 238 SVKLTLK|DV 0.070 . cgd5_783 252 ETHLMFK|KH 0.059 . cgd5_783 253 THLMFKK|HL 0.102 . cgd5_783 261 LPAPLGK|DG 0.069 . cgd5_783 264 PLGKDGK|PR 0.058 . cgd5_783 266 GKDGKPR|KD 0.098 . cgd5_783 267 KDGKPRK|DL 0.136 . cgd5_783 272 RKDLNQK|SF 0.083 . cgd5_783 278 KSFEVHR|SR 0.125 . cgd5_783 280 FEVHRSR|VT 0.089 . cgd5_783 304 WSFIPNK|KL 0.068 . cgd5_783 305 SFIPNKK|LP 0.086 . cgd5_783 311 KLPIEIK|KA 0.068 . cgd5_783 312 LPIEIKK|AP 0.079 . cgd5_783 315 EIKKAPK|FL 0.068 . cgd5_783 318 KAPKFLR|LK 0.083 . cgd5_783 320 PKFLRLK|VP 0.052 . cgd5_783 334 TSGMSSR|SK 0.148 . cgd5_783 336 GMSSRSK|LK 0.067 . cgd5_783 338 SSRSKLK|CN 0.064 . cgd5_783 341 SKLKCNK|FL 0.071 . ____________________________^_________________

  • Fasta :-

    >cgd5_783 TTTTTGTTTAAGTTATTAAGCATCTAAAGATGGTTAAAAAGAAGAATAAGAAAAACAAAA AAGAAATAAATAAGGAAGTGCTTAAAAATGCAGGATTTGATGAAGGCGAGATTTGGAGGT TAGACTTCAAAGGTGAGGTGGAATTTGAAGAAAATGTGATTGACCAAAGTAGATTTGAAG TTCCTTTATTCGATTTGAAGGGTTACAGAAGTCAAAAAAAAATAGGTAAACCAATGGGAC AAGATATTGAAATGGAAAAAAAACATGACTCAGATGATGAACGCGAAGATTCAGAAGCTT TTGATGCTGCTGCGGAGGACGATTTTGATGAATATGATGTTGAGCAACAAAAAGTTGATG AATCCAGATTTCTGCAAAAACGATTTGAATTCGAGGTTGATTATATGAAGAAACTCAGAG TATGGGAAGCTTCTTTTTTTATTCATACTAGTGAAAATCTAGAAAATACACCACAAGAAT TCTTCTATGTTATTGAATTTGGGCATGTTAATCCAGAGAGAAACTACGAAGGAACTTTAA AGAGAATGATGGTTTATACAGCTGCGACTTTATTAAAACCAGGAGAAGTAAAAGTATTAA CTTTCCCGATTATCGTTTGGCCAAAAAAGATCTTATATATATCGTATTCTGAATTAGAGA TGTTTCAAATATCCATTAAGCTCTGGACAATTGGAACCTTTACTTTCAACCAACTGCTTG CTTCAGTCAAACTTACACTCAAAGATGTACTGGAAAACGATCCAGAAACTCATTTAATGT TTAAAAAGCATCTTCCTGCACCTTTGGGAAAGGATGGAAAACCTCGTAAAGATCTTAACC AAAAAAGTTTTGAAGTGCATAGAAGCAGAGTAACTTTACAGTTACAAGAAATTTTTGATT TTGATATTTCCTTGGAAAATTGGAGTTTTATTCCTAATAAGAAACTTCCTATTGAAATTA AAAAAGCACCCAAATTTTTGAGACTAAAGGTACCTTTAAATAATGATATAACTTCAGGAA TGTCTTCTAGGAGTAAGTTGAAATGTAATAAATTTCTTTAAACATTAATAT
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cgd5_783      



Dinesh Gupta lab Translational bioinformatics group, ICGEB, New Delhi, India