Solution NMR structure of a D,L‐alternating oligonorleucine as a model of β‐helix

Navarro, Esperanza; Tejero, Roberto; Fenude, Emma; Celda, Bernardo

doi:10.1002/1097-0282(200108)59:2<110::aid-bip1010>3.3.co;2-j

Cited by 10 publications

(12 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In some cases detailed X-ray descriptions (crystal x, y and z coordinates) for protein amino acids are difficult to obtain but we do have some 3-D structural information. For instance, knowledge about close contact amino acid pairs can be gained more quickly from NMR data [195][196][197][198]. If this kind of information is obtained, it is also possible to represent spatial protein information as a graph of the NAANs type.…”

Section: Tpgis or Cis For Free And Ligand-bound Proteinstructure Netwmentioning

confidence: 99%

Proteomics, networks and connectivity indices

et al. 2008

View full text Add to dashboard Cite

Describing the connectivity of chemical and/or biological systems using networks is a straight gate for the introduction of mathematical tools in proteomics. Networks, in some cases even very large ones, are simple objects that are composed at least by nodes and edges. The nodes represent the parts of the system and the edges geometric and/or functional relationships between parts. In proteomics, amino acids, proteins, electrophoresis spots, polypeptidic fragments, or more complex objects can play the role of nodes. All of these networks can be numerically described using the so-called Connectivity Indices (CIs). The transformation of graphs (a picture) into CIs (numbers) facilitates the manipulation of information and the search for structure-function relationships in Proteomics. In this work, we review and comment on the challenges and new trends in the definition and applications of CIs in Proteomics. Emphasis is placed on 1-D-CIs for DNA and protein sequences, 2-D-CIs for RNA secondary structures, 3-D-topographic indices (TPGIs) for protein function annotation without alignment, 2-D-CIs and 3-D-TPGIs for the study of drug-protein or drug-RNA quantitative structure-binding relationships, and pseudo 3-D-CIs for protein surface molecular recognition. We also focus on CIs to describe Protein Interaction Networks or RNA co-expression networks. 2-D-CIs for patient blood proteome 2-DE maps or mass spectra are also covered.

show abstract

Section: Tpgis or Cis For Free And Ligand-bound Proteinstructure Netwmentioning

confidence: 99%

Proteomics, networks and connectivity indices

et al. 2008

View full text Add to dashboard Cite

show abstract

“…In some cases detailed X-ray descriptions (crystal x, y, and z coordinates) for protein amino acids are difficult to obtain but we do have some 3D structural information. For instance, knowledge about close contact amino acid pairs can be gained more quickly from NMR data [75][76][77][78]. If we obtain this kind of information, we can represent spatial protein information as a graph.…”

Section: Pseudo-3d-tis To Speed Up Protein Structure Characterizationmentioning

confidence: 99%

Medicinal Chemistry and Bioinformatics - Current Trends in Drugs Discovery with Networks Topological Indices

González-Dı́az

Vilar²,

Santana³

et al. 2007

CTMC

281

170

View full text Add to dashboard Cite

The numerical encoding of chemical structure with Topological Indices (TIs) is currently growing in importance in Medicinal Chemistry and Bioinformatics. This approach allows the rapid collection, annotation, retrieval, comparison and mining of chemical structures within large databases. TIs can subsequently be used to seek quantitative structure-activity relationships (QSAR), which are models connecting chemical structure with biological activity. In the early 1990's, there was an explosion in the introduction and definition of new TIs. The Handbook of Molecular Descriptors by Todeschini and Consonni lists more than 1500 of these indices. At the end of the last century, researchers produced a large number of TIs with essentially the same advantages and/or disadvantages. Consequently, many researchers abandoned the definition of TIs for a time. In our opinion, one of the problems associated with TIs is that researchers aimed their efforts only at the codification of chemical connectivity for small-sized drugs. As a consequence, recently it seems that we have arrived at "Fukuyama's End of History in TIs definition". In the work described here, we review and comment on the "quo vadis" and challenges in the definition of TIs as we enter the new century. Emphasis is placed on new chiral TIs (CTIs), flexible TIs for unifying QSAR models with multiple targets, topographic indices (TPGIs), TIs for DNA and protein sequences, TIs for 2D RNA structures, TPGIs and drug-protein or drug-RNA quantitative structure-binding relationship (QSBR) studies, TIs to encode protein surface information and TIs for protein interaction networks (PINs).

show abstract

“…1–4 The most prominent representative of a β‐helix in α‐peptides is the membrane channel‐forming peptide gramicidin A5–7 with alternating 20‐ and 22‐membered hydrogen‐bonded rings. Immediately after the discovery of gramicidin A, further types of β‐helices were suggested for α‐peptides on the basis of general structure ideas, but only recently such secondary structures with alternating 14‐ and 16‐membered hydrogen‐bonded cycles were experimentally found 3, 4. In this context, it should be mentioned that antiparallel double‐strand β‐helices are also possible 4, 8.…”

Section: Introductionmentioning

confidence: 99%

Side‐chain control of folding of the homologous α‐, β‐, and γ‐peptides into “mixed” helices (β‐helices)

2005

View full text Add to dashboard Cite

A systematic analysis of the substituent influence on the formation of the unique secondary structure type of "mixed" helices in the homologous alpha-, beta-, and gamma-peptides was performed on the basis of ab initio molecular orbital theory. Contrary to the common periodic peptide helices, mixed helices have an alternating periodicity and their hydrogen-bonding pattern is similar to those of beta-sheets. They belong, therefore, to the family of beta-helices. It is shown that folding of peptide sequences into mixed helices is energetically preferred over folding into their periodic counterparts in numerous cases. The influence of entropy and solvents on the formation of the various competitive mixed and periodic helix types is discussed. Among the oligomers of the various homologous amino acids, beta-peptides show the highest tendency to form beta-helices. The rules of substituent influence derived from the analysis of a wide variety of backbone substitution patterns might be helpful for a rational design of mixed helix structures, which could be important for mimicking membrane channels.

show abstract

Solution NMR structure of a D,L‐alternating oligonorleucine as a model of β‐helix

Cited by 10 publications

References 6 publications

Proteomics, networks and connectivity indices

Proteomics, networks and connectivity indices

Medicinal Chemistry and Bioinformatics - Current Trends in Drugs Discovery with Networks Topological Indices

Side‐chain control of folding of the homologous α‐, β‐, and γ‐peptides into “mixed” helices (β‐helices)

Contact Info

Product

Resources

About