Curvatura da superfície de proteínas no Java Protein Dossier.

Definição de superfície. Cálculo dos valores de curvatura com SurfRace.bitstream/CNPTIA/9897/1/comuntec38.pdfAcesso em: 30 maio 2008

GlyProt: in silico glycosylation of proteins

GlyProt () is a web-based tool that enables meaningful N-glycan conformations to be attached to all the spatially accessible potential N-glycosylation sites of a known three-dimensional (3D) protein structure. The probabilities of physicochemical properties such as mass, accessible surface and radius of gyration are calculated. The purpose of this service is to provide rapid access to reliable 3D models of glycoproteins, which can subsequently be refined by using more elaborate simulations and validated by comparing the generated models with experimental data

STING Report: convenient web-based application for graphic and tabular presentations of protein sequence, structure and function descriptors from the STING database

The Sting Report is a versatile web-based application for extraction and presentation of detailed information about any individual amino acid of a protein structure stored in the STING Database. The extracted information is presented as a series of GIF images and tables, containing the values of up to 125 sequence/structure/function descriptors/parameters. The GIF images are generated by the Gold STING modules. The HTML page resulting from the STING Report query can be printed and, most importantly, it can be composed and visualized on a computer platform with an elementary configuration. Using the STING Report, a user can generate a collection of customized reports for amino acids of specific interest. Such a collection comes as an ideal match for a demand for the rapid and detailed consultation and documentation of data about structure/function. The inclusion of information generated with STING Report in a research report or even a textbook, allows for the increased density of its contents. STING Report is freely accessible within the Gold STING Suite at http://www.cbi.cnptia.embrapa.br, http://www.es.embnet.org/SMS/, http://gibk26.bse.kyutech.ac.jp/SMS/ and http://trantor.bioc.columbia.edu/SMS (option: STING Report)

A new protein-ligand binding sites prediction method based on the integration of protein sequence conservation information

<p>Abstract</p> <p>Background</p> <p>Prediction of protein-ligand binding sites is an important issue for protein function annotation and structure-based drug design. Nowadays, although many computational methods for ligand-binding prediction have been developed, there is still a demanding to improve the prediction accuracy and efficiency. In addition, most of these methods are purely geometry-based, if the prediction methods improvement could be succeeded by integrating physicochemical or sequence properties of protein-ligand binding, it may also be more helpful to address the biological question in such studies.</p> <p>Results</p> <p>In our study, in order to investigate the contribution of sequence conservation in binding sites prediction and to make up the insufficiencies in purely geometry based methods, a simple yet efficient protein-binding sites prediction algorithm is presented, based on the geometry-based cavity identification integrated with sequence conservation information. Our method was compared with the other three classical tools: PocketPicker, SURFNET, and PASS, and evaluated on an existing comprehensive dataset of 210 non-redundant protein-ligand complexes. The results demonstrate that our approach correctly predicted the binding sites in 59% and 75% of cases among the TOP1 candidates and TOP3 candidates in the ranking list, respectively, which performs better than those of SURFNET and PASS, and achieves generally a slight better performance with PocketPicker.</p> <p>Conclusions</p> <p>Our work has successfully indicated the importance of the sequence conservation information in binding sites prediction as well as provided a more accurate way for binding sites identification.</p

Apresentação gráfica de parâmetros protéicos utilizando o Java Protein Dossier.

Parâmetros apresentados pelo JPD. Sequência de resíduos. Contatos. Contatos internos. Contatos na interface. Estrutura secundária. Dupla ocupância. Fator de temperatura. Entropia relativa. Confiabilidade. Acessibilidade de resíduos. Ângulos de torsão. Potencial eletrostático. Curvatura na superfície. Hidrofobicidade. Analisando com maior detalhes os parâmetros apresentados.bitstream/CNPTIA/9899/1/comuntec40.pdfAcesso em: 30 maio 2008

Hexameric ring structure of the N-terminal domain of Mycobacterium tuberculosis DnaB helicase

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74669/1/j.1742-4658.2008.06460.x.pd

Evaluating the Difficulty involved in Designing Small Molecule Drugs to Inhibit Protein-Protein Interactions

The targeting of drugs to block protein-protein interactions (PPIs) has attracted great interest over recent years. Such targets, however, have been held to be difficult to inhibit using low molecular weight compounds, and as a consequence they are often branded as “undruggable”. This is partly because the interfaces involved are seen to be large, and the fact that they are generally regarded as being too smooth and too flat. In the work reported here, a series of quantitative systematic studies have been performed to determine the molecular area, roughness, curvature, and amino acid composition of the interfacial surfaces of PPIs, to determine the feasibility of designing small molecule drugs to inhibit these interactions. The X-ray crystal structures are analysed for a set of 48 PPIs involving G-protein, membrane receptor extracellular domain, and enzyme-inhibitor complexes. The protein partners involved in these PPIs are shown to have much larger interfacial areas than those for protein-small molecule complexes (≥ 900 Å2 vs ~250 Å2, respectively), and they have interfaces that are fairly smooth (with fractal dimensions close to 2) and quite flat (with mean surface curvatures in the order of ± 0.1 Å-1). The mean interfacial surface curvatures of the PPI protein partners, however, are seen to change upon complexation, some very significantly so. Despite the fact that the amino acid compositions of the PPI interface surfaces are found to be significantly different from that of the average protein surface (with variations according to the type of PPI), it is concluded that the prospects for designing low molecular weight PPI inhibitors that act in an orthosteric manner remain rather limited. HIGHLIGHTS•Mean interfacial surface curvatures have been determined for protein-protein interaction (PPI) partners in their complexed and uncomplexed states.•Mean interfacial surface roughnesses have been determined for protein-protein interaction (PPI) partners in their complexed and uncomplexed states.•Amino acid compositions have been determined for PPI interface surfaces and these compared with that for the average protein surface.•Quantification of the PPI interfacial surface properties is used to assess the druggability of these targets

Nucleosome Structure Incorporated Histone Acetylation Site Prediction in \u3ci\u3eArabidopsis thaliana\u3c/i\u3e

BackgroundAcetylation is a crucial post-translational modification for histones, and plays a key role in gene expression regulation. Due to limited data and lack of a clear acetylation consensus sequence, a few researches have focused on prediction of lysine acetylation sites. Several systematic prediction studies have been conducted for human and yeast, but less for Arabidopsis thaliana. ResultsConcerning the insufficient observation on acetylation site, we analyzed contributions of the peptide-alignment-based distance definition and 3D structure factors in acetylation prediction. We found that traditional structure contributes little to acetylation site prediction. Identified acetylation sites of histones in Arabidopsis thaliana are conserved and cross predictable with that of human by peptide based methods. However, the predicted specificity is overestimated, because of the existence of non-observed acetylable site. Here, by performing a complete exploration on the factors that affect the acetylability of lysines in histones, we focused on the relative position of lysine at nucleosome level, and defined a new structure feature to promote the performance in predicting the acetylability of all the histone lysines in A. thaliana. ConclusionWe found a new spacial correlated acetylation factor, and defined a ε-N spacial location based feature, which contains five core spacial ellipsoid wired areas. By incorporating the new feature, the performance of predicting the acetylability of all the histone lysines in A. Thaliana was promoted, in which the previous mispredicted acetylable lysines were corrected by comparing to the peptide-based prediction