Sequence analyses methods

Smith, 1992). All of these can identify an optimal alignment between the query and either a set of previously studied sequences or a pattern of sequence elements identified as common to a set of previously studied proteins. De novo sequence analysis methods have proved less useful. Although there has been some slow progress in predicting a protein s structure from its sequence, no direct functional predictions methods have been developed. 

Evaluation of protein sequence analysis methods based on the use of PSSMs in benchmarking experiments and in a number of test cases shows that these methods are capable of systematically detecting relationships between proteins that previously have been deemed tractable only at the structure-comparison level. Clearly, however, there is still a lot of room for improvement, as many automated procedures missed subtle connections that subsequendy have been revealed on a case-by-case basis, in part thanks to a careful choice of starting points for the PSSM construction. An exhaustive exploration of the sequence space by recursive iterative searching is likely to yield additional, on many occasions unexpected, links between proteins and, in particular, is expected to increase the rate of structure prediction. 

DNLM 1. Drug Design. 2. Genomics-methods. 3. Oligonucleotide Array Sequence Analysis-methods. 4. Proteomics-methods. QV 744 M434a 2004] I. Title. 

Hunkapiller, M. W, Lujan, E., Ostrander, F., and Hood, L. E. (1983) Isolation of microgram quantities of proteins from polyacrylamide gels for amino acid sequence analysis. Methods Enzymol. 91, 227-236. 

Doolittle, R. F. (1996). Computer Methods for Macro-molecular Sequence Analysis. Methods Enzymology, 266. 

The sequence analysis method is very good to identify the organisms at genus and species level but it does not differentiate at the subspecies level. 

Matsudaira, P. (1990) Limited N-terminal Sequence Analysis, Methods Enzymd. 182, 602-613. 

Scheme 1. Wiebers s combined MS-enzymatic sequence analysis method. At the dinucleotide level one can already make an identification of the remaining sequence (FD). N stands for nucleoside.

A comparison of the alignment score of the target sequence with (many) different template proteins can be the basis of rating the significance of the produced structure model. P-values are a version of this approach that also applies to sequence analysis methods (see Chapter 2 of this volume), for which is has been studied extensively [9, 11, 70, 71]. In addition, the resulting models can be subjected to a wide variety of plausibility tests in order to ascertain their protein-likeness. Many of these checks will be made on the full-atom model of the protein that results from the procedures described in Chapter 5 of this volume. 

Other successful structure prediction methods based on sequence alone are FASTA [15, 18], hidden Markov models (HMMs) [25, 26, 28, 179], intermediate sequence search [182], and iterative profile search [29]. Sequence analysis methods are discussed in detail in Chapter 2. The results of such methods in the CASP experiment are described in [157, 183, 184],... 

Koehler J, Rawlings C, Verrier P (2005). Linking experimental results, biological networks and sequence analysis methods using Ontologies and Generalised Data Structures. In Silica Biol. 5 33-44. 

Hunkapiller, M., et al. (1983). Isolation of Microgram Quantities of Proteins from Polyacrylamide Gels for Amino Acid Sequence Analysis, Methods Enzymol. 91 227-236. 

Sequence Alignment A linear comparison of amino (or nucleic) acid sequences, in which insertions are made in order to bring equivalent positions in adjacent sequences into the correct register. Alignments are the basis of sequence analysis methods, and are used to pinpoint the occurrence of conserved motifs. 

With the growing number of proteins sequenced, there is a necessity for novel techniques to analyze protein sequences in order to determine their structure and function. The most commonly used protein sequence descriptors are based on evolutionary information and physicochemical properties. Even though these methods have proven to be efficient in most cases, in cases of transmembrane proteins, they may fall short. As the vast field of transmembrane proteins largely remains unexplored with many transmembrane proteins yet to be sequenced, it is possible to obtain new protein sequences without any known homolog. In such cases, traditional sequence analysis methods based on alignment profiles would not be sufficient. The evolutionary information-based descriptors appear inadequate, and indices based on physicochemical property can cause ambiguities. Therefore, it is of considerable interest to develop novel methods based on sequence information alone to represent protein sequences. 

R. F. Doolittle, in Computer Methods for Macromolecular Sequence Analysis , Methods in Enzymology, eds. J. N. Abelson and M. 1. Simon, Academic Press, New York, 1996, Vol. 266. 

Lindberg, B. LOnngren, J. Methylation analysis of complex carbohydrates General procedure and application for sequence analysis. Methods Enzymol. 1978, 50, 3-33. 

Heilman, EJ., Wiksell, E., and Karlsson, B.-M. (1990). A new approach to micropreparative desalting exemplified by desalting a reduction/alkylation mixture, presenred ar Eighr International Conference on Methods in Protein Sequence Analysis, Kiruna, Sweden, July 1-6. 

Gray, R. "Sequence Analysis with Dansyl Chloride", In "Methods In Enzymology", p. 333, Vol. XXV, "Enzyme Structure, Part B", C. H. W. Hlrs and S. N. Tlmasheff, Editors, Academic Press, New York, 1972. 

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