OBJECTIVETo set up the dual-indexes sequence analytical method for far-infrared fingerprint in which the dual indexes are common peak ratio and variant ration.

METHODTwo new indexes, common peak ratio and variant peak ratio, were applied and their values were calculated by means of sequential analysis, in which each Pyritum sample's far-infrared fingerprint spectra were set up and the common peak ratio sequences were arranged in order of size in comparision with other samples.

RESULTThe analytical results suggested that samples S3 and S4, S5, S6 and S7, S8 and S9 from the same region showed higher common peak ratio and lower variant peak ratio. However, the sample S1 from Anhui showed little similarity with others.

CONCLUSIONThe method, applied to distinguish Pyritum of different areas and batches, is reasonable to characterize of traditional Chinese medicine.

Iron ; analysis ; chemistry ; Medicine, Chinese Traditional ; Peptide Mapping ; Quality Control ; Sequence Analysis, Protein ; Spectrophotometry, Infrared ; methods ; Sulfides ; analysis ; chemistry

Here we discuss whether N terminal sequencing is appropriate as one of the conventional control methods for monoclonal antibody products. We determined the N terminal sequences of two monoclonal antibody products targeting two antigens separately with both Edman degradation and mass peptide spectrometry. We also identified the characteristic peptide fragments with mass spectrometry. Furthermore, we analyzed their heterogeneity with ion exchange chromatography, capillary zone electrophoresis and Imaged Capillary Isoelectric Focusing. Edman degradation method showed that the N terminal 15 amino acids of heavy and light chains of the two monoclonal antibodies were identical. Peptide mass spectrometry demonstrated that T1 peptide fragments of heavy and light chains of the two antibodies were also the same. But in contrast, peptide mapping and the three analytical methods for heterogeneity analysis could effectively identify and differentiate the two antibodies. The N terminal sequences of two monoclonal antibodies are identical because the number of framework sequences of humanized or human monoclonal antibodies is relatively limited, so whether N terminal sequencing analysis could be regulated as one of the practical control methods should be carefully discussed. Our work also proves that the above analytical methods could combinatorially applied to the identification of monoclonal antibody products, and are more objective compared to N terminal sequencing.
Amino Acid Sequence ; Antibodies, Monoclonal ; isolation & purification ; Chromatography, Ion Exchange ; Humans ; Isoelectric Focusing ; Mass Spectrometry ; Peptide Mapping ; Peptides ; Sequence Analysis, Protein ; methods

AIMTo identify protein spots on two dimentional protein electrophoresis (2DE) by post-source decay (PSD) technique associated with library search.

METHODSThe PSD-MALDI-TOF-MS method was set up by a segment of ACTH and a peptide digested by trypsin for TPA.

RESULTSTwo unknown protein spots on 2DE were identified as 40S ribosomal protein S12 and dnaK suppressor protein separately by established PSD-MALDI-TOF-MS method.

CONCLUSIONPSD technique has greater application prospects in peoteomics.

Adrenocorticotropic Hormone ; chemistry ; Amino Acid Sequence ; Databases, Protein ; Electrophoresis, Gel, Two-Dimensional ; Molecular Sequence Data ; Peptide Fragments ; chemistry ; Peptide Mapping ; Ribosomal Proteins ; analysis ; chemistry ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ; Tissue Plasminogen Activator ; chemistry

Pattern finding is one of the important tasks in a protein or DNA sequence analysis. Alignment is the widely used technique for finding patterns in sequence analysis. BLAST (Basic Local Alignment Search Tool) is one of the most popularly used tools in bio-informatics to explore available DNA or protein sequence databases. BLAST may generate a huge output for a large sequence data that contains various sequence patterns. However, BLAST does not provide a tool to summarize and analyze the patterns or matched alignments in the BLAST output file. BLAST lacks of general and robust parsing tools to extract the essential information out from its output. This paper presents a pattern summary system which is a powerful and comprehensive tool for discovering pattern structures in huge amount of sequence data in the BLAST. The pattern summary system can identify clusters of patterns, extract the cluster pattern sequences from the subject database of BLAST, and display the clusters graphically to show the distribution of clusters in the subject database.
Computational Biology ; Databases, Protein ; DNA ; Sequence Analysis* ; Sequence Analysis, DNA

Multiple sequence alignment is one of the basic techniques in bioinformatics, and it plays a vital role in structure modeling, functional site prediction, and phylogenetic analysis. In this paper, we review the methodologies and recent advances in the multiple protein sequence alignment, e.g., speeding up the calculation of distances among sequences and employing the iterative refinement and consistency-based scoring function, with emphasis on the use of additional sequence and structural information for improving alignment quality.
Algorithms ; Proteins ; chemistry ; Sequence Alignment ; methods ; Sequence Analysis, Protein ; methods

Hidden Markov model (HMM) used in the research of protein is a new field of bioinformatics. Nowadays large amount of data about protein sequences and structures have been obtained. Traditional methods of protein analysis are no longer used. Biologists have updated their research methods with computer technology and statistics, which can deal with large amount of data. HMM can be used to distinguish protein sequence with the same characteristics. A family of protein from SCOP database was selected, through which a HMM model representing the family was obtained, and then the model was utilized to analyze protein sequences. Results indicate that HMM can express particular family of protein, and recognize the given protein sequences of the family from many sequences.
Algorithms ; Linear Models ; Proteins ; classification ; Sequence Analysis, Protein ; methods

May the structure information of protein be obtained from the corresponding nucleotide sequence? For this question, a computer program was used to conduct a statistical analysis about the clustering phenomena of amino acids. In this method, 20 kinds of amino acid were classified into 2 types according to the number of hydrogen bonds formed by middle base of their correlation codons. It can be seen that amino acid has a rather great possibility of neighboring on another of its class and this assembly has a tendency to forming specific secondary structure. A sequence was designed and its secondary structure was predicted by this prediction software.
Amino Acid Sequence ; Amino Acids ; chemistry ; classification ; Cluster Analysis ; Nucleotides ; chemistry ; genetics ; Protein Structure, Secondary ; genetics ; Sequence Analysis, Protein ; methods

A novel method of feature extraction from protein primary structure has been proposed and applied to classify the protein homodimer, homotrimer, homotetramer and homohexamer, i. e. one protein sequence can be represented by a feature vector composed of amino acid compositions and a set of weighted auto-correlation function factors of amino acid residue index. As a result, high classification accuracies are obtained. For example, with the same support vector machine (SVM), the total accuracies of QIANA, AIANB, MEEJ, ROBB and SNEP sets based on this novel feature extraction method are 77.63, 77.16, 76.46, 76.70 and 75.06% respectively in Jackknife test, which are 6.39, 5.92, 5.22, 5.46 and 3.82 percent points respectively higher than that of COMP set based on the conventional method composed of amino acid compositions. With the same QIANA set, the total accuracy of SVM is 77.63%, which is 16.29 percent points higher than that of covariant discriminant algorithm. These results show: (1) The novel feature extraction method is effective and feasible, and the feature vectors based on this method may contain more protein quaternary structure information and appear to capture essential information about the composition and hydrophobicity of residues in the surface patches buried in the interfaces of associated subunits; (2) SVM can be referred as a powerful computational tool for classifying the homo-oligomers of proteins.
Algorithms ; Amino Acid Sequence ; Artificial Intelligence ; Cluster Analysis ; Humans ; Models, Molecular ; Molecular Sequence Data ; Protein Conformation ; Proteins ; chemistry ; classification ; Sequence Analysis, Protein ; methods

Enlightened by the law of interactions among objects in the physical world, we propose a heuristic algorithm for solving the three-dimensional (3D) off-lattice protein folding problem. Based on a physical model, the problem is converted from a nonlinear constraint-satisfied problem to an unconstrained optimization problem which can be solved by the well-known gradient method. To improve the efficiency of our algorithm, a strategy was introduced to generate initial configuration. Computational results showed that this algorithm could find states with lower energy than previously proposed ground states obtained by nPERM algorithm for all chains with length ranging from 13 to 55.
Algorithms ; Amino Acid Sequence ; Computer Simulation ; Models, Chemical ; Models, Molecular ; Molecular Sequence Data ; Protein Conformation ; Protein Folding ; Proteins ; chemistry ; Sequence Analysis, Protein ; methods

OBJECTIVETo develop an optimal sequencing system which can improve the resolution of sequencing G-C rich DNA with abundant trinucleotide repeats by applying concentration gradients of betaine to the Sanger sequencing system.

METHODSConcentration gradients of betaine were introduced into the sequencing system by taking the 5' terminal of Nogo-B cDNA (Am-Nogo-B) (G-C%=72%, without trinucleotide repeats) and 5' terminal of Huntingtin cDNA (Am-HTT) (G-C%=74%, with abundant CAG and CCG repeats) the results of sequencing were compared.

RESULTSThe optimum concentration of betaine for sequencing Am-Nogo-B has differed from that for Am-HTT. Result of sequencing Am-Nogo-B has achieved the best quality when the concentration of betaine was at 0.8-1.2 mol/L, whereas the result of sequencing Am-HTT obtained the best quality when the concentration of betaine was at 1.6 -2.4 mol/L. The results were reproducible.

CONCLUSIONG-C rich DNA with similar G-C% required different concentrations of betaine in the sequencing system due to base pair compositions. The sequencing system developed for improving the resolution of sequencing of G-C rich DNA with abundant trinucleotide repeats can be used as a reference for similar studies.

Base Sequence ; Betaine ; pharmacology ; Huntingtin Protein ; Molecular Sequence Data ; Nerve Tissue Proteins ; genetics ; Sequence Analysis, DNA ; methods ; Trinucleotide Repeats