MutDB services: interactive structural analysis of mutation data.

Non-synonymous single nucleotide polymorphisms (SNPs) and mutations have been associated with human phenotypes and disease. As more and more SNPs are mapped to phenotypes, understanding how these variations affect the function and expression of genes and gene products becomes an important endeavor. We have developed a set of tools to aid in the understanding of how amino acid substitutions affect protein structures. To do this, we have annotated SNPs in dbSNP and amino acid substitutions in Swiss-Prot with protein structural information, if available. We then developed a novel web interface to this data that allows for visualization of the location of these substitutions. We have also developed a web service interface to the dataset and developed interactive plugins for UCSF's Chimera structural modeling tool and PyMOL that integrate our annotations with these sophisticated structural visualization and modeling tools. The web services portal and plugins can be downloaded from http://www.lifescienceweb.org/ and the web interface is at http://www.mutdb.org/.

Identification of similar regions of protein structures using integrated sequence and structure analysis tools.

BACKGROUND: Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site http://www.sblest.org/ and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest. RESULTS: Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO) ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein. CONCLUSION: With structural genomics initiatives determining structures with little, if any, functional characterization, development of protein structure and function analysis tools are a necessary endeavor. We have developed a useful application towards a solution to this problem using common structural and sequence based analysis tools. These approaches are able to find statistically significant environments in a database of protein structure, and the method is able to quantify how closely associated each environment is to a predicted functional annotation.

Visual methods for interpreting optical nonlinearity at the molecular level.

The emergence of nonlinear optical (NLO) measurement approaches has provided new windows into molecular and macromolecular structure within thin films and materials. The greatest barriers in mining this structural information increasingly appear in meaningfully relating these macroscopic results back to molecular-level descriptions, driven largely by the increasing complexity of the molecular systems and interfacial architectures under interrogation. As NLO methods continue their expansion into increasingly diverse disciplines, so grows the need for tools to guide this evolution without sacrificing the mathematical rigor of more traditional tensor representations. Recent developments reviewed in this Account are designed to facilitate interpretation of complex assemblies using relatively simple but still quantitatively accurate visual representations of the polarization-dependent optical nonlinearity, both for individual chromophores and for polymeric assemblies of coupled chromophores. Although the primary focus of this Account is on second-order nonlinear optical effects, including second harmonic generation and sum frequency generation, many of these same concepts also directly apply to higher-order phenomena.

NLOPredict: visualization and data analysis software for nonlinear optics.

A data analysis and visualization program was developed to assist in the interpretation of second-order nonlinear optical (NLO) processes, including vibrational sum-frequency generation and electronically resonant second harmonic generation. A novel diagrammatic approach allows concise visual representations of the resonant NLO molecular response. By mapping the predicted NLO response as a function of molecular orientation, molecular modeling results can be combined with experimental measurements for orientational analysis. A method is developed and implemented to predict the nonlinear optical properties of the amide backbones in complete proteins with known structures. NLOPredict is available for most computer operating systems from http://sda.iu.edu/nlopredict/.