scholarly journals Amino acid sequence determination by g.l.c.-mass spectrometry of permethylated peptides. Optimization of the formation of chemical derivatives at the 2-10 nmol level

1983 ◽  
Vol 215 (2) ◽  
pp. 261-272 ◽  
Author(s):  
K Rose ◽  
M G Simona ◽  
R E Offord

A new technique is described that permits the permethylation of acylated peptides at the 2-10 nmol level. The presence of up to 400 micrograms of sodium dodecyl sulphate per sample does not affect the reaction yields. The technique, which is a miniaturization of the widely used methyl iodide/dimethylsulphinyl carbanion procedure, employs a layer of hexane to exclude moisture and oxygen from the reaction mixture. Analysis of the peptide derivatives by combined g.l.c.-mass spectrometry permits amino acid sequence information to be obtained. In addition to studies of digests of a model substrate (glucagon), the new permethylation technique has been used to identify a peptide of interest from a digest of a cytochrome and to define the N-termini of two proteins at the 5 nmol level.

2002 ◽  
Vol 68 (6) ◽  
pp. 2731-2736 ◽  
Author(s):  
Hirokazu Nankai ◽  
Wataru Hashimoto ◽  
Kousaku Murata

ABSTRACT When cells of Bacillus sp. strain GL1 were grown in a medium containing xanthan as a carbon source, α-mannosidase exhibiting activity toward p-nitrophenyl-α-d-mannopyranoside (pNP-α-d-Man) was produced intracellularly. The 350-kDa α-mannosidase purified from a cell extract of the bacterium was a trimer comprising three identical subunits, each with a molecular mass of 110 kDa. The enzyme hydrolyzed pNP-α-d-Man (Km = 0.49 mM) and d-mannosyl-(α-1,3)-d-glucose most efficiently at pH 7.5 to 9.0, indicating that the enzyme catalyzes the last step of the xanthan depolymerization pathway of Bacillus sp. strain GL1. The gene for α-mannosidase cloned most by using N-terminal amino acid sequence information contained an open reading frame (3,144 bp) capable of coding for a polypeptide with a molecular weight of 119,239. The deduced amino acid sequence showed homology with the amino acid sequences of α-mannosidases belonging to glycoside hydrolase family 38.


FEBS Letters ◽  
1970 ◽  
Vol 7 (1) ◽  
pp. 8-12 ◽  
Author(s):  
M.M. Shemyakin ◽  
Yu.A. Ovchinnikov ◽  
E.I. Vinogradova ◽  
A.A. Kiryushkin ◽  
M.Yu. Feigina ◽  
...  

2001 ◽  
Vol 183 (2) ◽  
pp. 490-499 ◽  
Author(s):  
Chung-Dar Lu ◽  
Ahmed T. Abdelal

ABSTRACT The NAD+-dependent glutamate dehydrogenase (NAD-GDH) from Pseudomonas aeruginosa PAO1 was purified, and its amino-terminal amino acid sequence was determined. This sequence information was used in identifying and cloning the encodinggdhB gene and its flanking regions. The molecular mass predicted from the derived sequence for the encoded NAD-GDH was 182.6 kDa, in close agreement with that determined from sodium dodecyl sulfate-polyacrylamide gel electrophoresis of the purified enzyme (180 kDa). Cross-linking studies established that the native NAD-GDH is a tetramer of equal subunits. Comparison of the derived amino acid sequence of NAD-GDH from P. aeruginosa with the GenBank database showed the highest homology with hypothetical polypeptides from Pseudomonas putida, Mycobacterium tuberculosis, Rickettsia prowazakii, Legionella pneumophila, Vibrio cholerae, Shewanella putrefaciens, Sinorhizobium meliloti, andCaulobacter crescentus. A moderate degree of homology, primarily in the central domain, was observed with the smaller tetrameric NAD-GDH (protomeric mass of 110 kDa) fromSaccharomyces cerevisiae or Neurospora crassa. Comparison with the yet smaller hexameric GDH (protomeric mass of 48 to 55 kDa) of other prokaryotes yielded a low degree of homology that was limited to residues important for binding of substrates and for catalytic function. NAD-GDH was induced 27-fold by exogenous arginine and only 3-fold by exogenous glutamate. Primer extension experiments established that transcription of gdhB is initiated from an arginine-inducible promoter and that this induction is dependent on the arginine regulatory protein, ArgR, a member of the AraC/XyIS family of regulatory proteins. NAD-GDH was purified to homogeneity from a recombinant strain of P. aeruginosa and characterized. The glutamate saturation curve was sigmoid, indicating positive cooperativity in the binding of glutamate. NAD-GDH activity was subject to allosteric control by arginine and citrate, which function as positive and negative effectors, respectively. Both effectors act by influencing the affinity of the enzyme for glutamate. NAD-GDH from this organism differs from previously characterized enzymes with respect to structure, protomer mass, and allosteric properties indicate that this enzyme represents a novel class of microbial glutamate dehydrogenases.


Biomolecules ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 938
Author(s):  
Kriti Chopra ◽  
Bhawna Burdak ◽  
Kaushal Sharma ◽  
Ajit Kembhavi ◽  
Shekhar C. Mande ◽  
...  

Decrypting the interface residues of the protein complexes provides insight into the functions of the proteins and, hence, the overall cellular machinery. Computational methods have been devised in the past to predict the interface residues using amino acid sequence information, but all these methods have been majorly applied to predict for prokaryotic protein complexes. Since the composition and rate of evolution of the primary sequence is different between prokaryotes and eukaryotes, it is important to develop a method specifically for eukaryotic complexes. Here, we report a new hybrid pipeline for predicting the protein-protein interaction interfaces in a pairwise manner from the amino acid sequence information of the interacting proteins. It is based on the framework of Co-evolution, machine learning (Random Forest), and Network Analysis named CoRNeA trained specifically on eukaryotic protein complexes. We use Co-evolution, physicochemical properties, and contact potential as major group of features to train the Random Forest classifier. We also incorporate the intra-contact information of the individual proteins to eliminate false positives from the predictions keeping in mind that the amino acid sequence of a protein also holds information for its own folding and not only the interface propensities. Our prediction on example datasets shows that CoRNeA not only enhances the prediction of true interface residues but also reduces false positive rates significantly.


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