Publications from researchers at the Buck Institute for Research on Aging http://www.buckinstitute.org/mooneyLab © 2011 Buck Institute, All Rights Reserved ABSTRACT: BACKGROUND: Based on the distinguishing properties of proteinprotein interaction networks such as powerlaw degree distribution and modularity structure, several stochastic models for the evolution of these networks have been purposed, motivated by the idea that a validated model should reproduce similar topological properties of the empirical network. However, being able to capture topological properties does not necessarily mean it correctly reproduces how networks emerge and evolve. More importantly, there is already evidence suggesting functional organization and significance of these networks. The current stochastic models of evolution, however, grow the network without consideration for biological function and natural selection. RESULTS: To test whether protein interaction networks are functionally organized and affect the evolution of these networks, we analyzed their evolution at both the topological and functional level. We find that the human network is shown to be functionally organized, and its function evolves with the topological properties of the network. Our analysis suggests that function most likely affects local modularity of the network. Consistently, we further found that the topological unit is also the functional unit of the network. CONCLUSION: We have demonstrated functional organization of a protein interaction network. Given our observations, we suggest that its significance should not be overlooked when studying network evolution. http://www.ncbi.nlm.nih.gov/pubmed/22530615 Sat, 31 Dec 2011 00:00:00 -0800 Nextgeneration sequencing (NGS) technologies are yielding ever higher volumes of human genome sequence data. Given this large amount of data, it has become both a possibility and a priority to determine how diseasecausing single nucleotide polymorphisms (SNPs) detected within gene regulatory regions (rSNPs) exert their effects on gene expression. Recently, several studies have explored whether diseasecausing polymorphisms have attributes that can distinguish them from those that are neutral, attaining moderate success at discriminating between functional and putatively neutral regulatory SNPs. Here, we have extended this work by assessing the utility of both SNPbased features (those associated only with the polymorphism site and the surrounding DNA) and genebased features (those derived from the associated gene in whose regulatory region the SNP lies) in the identification of functional regulatory polymorphisms involved in either monogenic or complex disease. Genebased features were found to be capable of both augmenting and enhancing the utility of SNPbased features in the prediction of known regulatory mutations. Adopting this approach, we achieved an AUC of 0.903 for predicting regulatory SNPs. Finally, our tool predicted 225 new regulatory SNPs with a high degree of confidence, with 105 of the 225 falling into linkage disequilibrium blocks of reported diseaseassociated genomewide association studies SNPs. 2011 WileyLiss, Inc. http://www.ncbi.nlm.nih.gov/pubmed/21796725 Fri, 31 Dec 2010 00:00:00 -0800 Estrogen receptor is a transcription regulator and can bind structurally distinct ligands with full agonistic, SERMs, or full antagonistic properties. Crystal structures of the ER ligand binding domain (LBD)complexed with full agonists or SERMs show that these ligands induce two different orientations of Helix12 in LBD and generate two different conformations, agonist conformation (A conformation) and AF2 antagonist conformation (B conformation). To understand how ER ligands interact with LBD structurally and energetically, we docked 3 full agonists, 9 SERMs and 2 full antagonists in both the A and B conformation of ER LBD and performed a 4step molecular dynamics (MD) simulation on all 28 complexes followed by mmPBSA binding free energy calculation. We found that all full agonists prefer the A conformation while all SERMs prefer the B conformation. Analysis of the mmPBSA energies revealed that calculated total binding free energies (delta PBTOT) and the difference of VDW between complex and the sum of receptor of ligands and ligand (delta VDW) have the order of full agonistsSERMsfull antagonists. However, the PB surface term has the order of full antagonistsSERMsfull agonists. We also found that the sum of the RMSD of mainchain atoms of Helix12 and all atoms of ligands in the A conformation is significantly lower for full agonists than that of the other ligands. Together, we conclude that the three types of ER ligands interact with the A and B conformations of ER LBD differently and same type of ligands interact similarly. These findings will be useful in understanding the mechanism of ER antagonism and can be used in ligand type prediction. http://www.ncbi.nlm.nih.gov/pubmed/21969034 Fri, 31 Dec 2010 00:00:00 -0800 Carbamoyl Phosphate Synthetase 1 deficiency (CPS1D) is a rare autosomal recessive urea cycle disorder, potentially leading to lethal hyperammonemia. Based on the age of onset, there are two distinct phenotypes: neonatal and late form. The CPS1 enzyme, located in the mitochondrial matrix of hepatocytes and epithelial cells of intestinal mucosa, is encoded by the CPS1 gene. At present more than 220 clearcut genetic lesions leading to CPS1D have been reported. As most of them are private mutations diagnosis is complicated. Here we report an overview of the main clinical findings and biochemical and molecular data of 13 CPS1D Italian patients. In two of them, one with the neonatal form and one with the late form, cadaveric auxiliary liver transplant was performed. Mutation analysis in these patients identified 17 genetic lesions, 9 of which were new confirming their "private" nature. Seven of the newly identified mutations were missense/nonsense changes. In order to study their protein level effects, we performed an in silico analysis whose results indicate that the amino acid substitutions occur at evolutionary conserved positions and affect residues necessary for enzyme stability or function. http://www.ncbi.nlm.nih.gov/pubmed/22173106 Fri, 31 Dec 2010 00:00:00 -0800 MOTIVATION: Enzyme catalysis is involved in numerous biological processes and the disruption of enzymatic activity has been implicated in human disease. Despite this, various aspects of catalytic reactions are not completely understood, such as the mechanics of reaction chemistry and the geometry of catalytic residues within active sites. As a result, the computational prediction of catalytic residues has the potential to identify novel catalytic pockets, aid in the design of more efficient enzymes and also predict the molecular basis of disease. RESULTS: We propose a new kernelbased algorithm for the prediction of catalytic residues based on protein sequence, structure and evolutionary information. The method relies upon explicit modeling of similarity between residuecentered neighborhoods in protein structures. We present evidence that this algorithm evaluates favorably against established approaches, and also provides insights into the relative importance of the geometry, physicochemical properties and evolutionary conservation of catalytic residue activity. The new algorithm was used to identify known mutations associated with inherited disease whose molecular mechanism might be predicted to operate specifically though the loss or gain of catalytic residues. It should, therefore, provide a viable approach to identifying the molecular basis of disease in which the loss or gain of function is not caused solely by the disruption of protein stability. Our analysis suggests that both mechanisms are actively involved in human inherited disease. AVAILABILITY AND IMPLEMENTATION: Source code for the structural kernel is available at www.informatics.indiana.edu/predrag/. http://www.ncbi.nlm.nih.gov/pubmed/20551136 Sat, 31 Jul 2010 00:00:00 -0700 As databases of genome data continue to grow, our understanding of the functional elements of the genome grows as well. Many genetic changes in the genome have now been discovered and characterized, including both diseasecausing mutations and neutral polymorphisms. In addition to experimental approaches to characterize specific variants, over the past decade, there has been intense bioinformatic research to understand the molecular effects of these genetic changes. In addition to genomic experimental assays, the bioinformatic efforts have focused on two general areas. First, researchers have annotated genetic variation data with molecular features that are likely to affect function. Second, statistical methods have been developed to predict mutations that are likely to have a molecular effect. In this protocol manuscript, methods for understanding the molecular functions of single nucleotide polymorphisms (SNPs) and mutations are reviewed and described. The intent of this chapter is to provide an introduction to the online tools that are both easy to use and useful. http://www.ncbi.nlm.nih.gov/pubmed/20238089 Sun, 28 Feb 2010 00:00:00 -0800 An important challenge in translational bioinformatics is to understand how genetic variation gives rise to molecular changes at the protein level that can precipitate both monogenic and complex disease. To this end, we compiled datasets of human diseaseassociated amino acid substitutions (AAS) in the contexts of inherited monogenic disease, complex disease, functional polymorphisms with no known disease association, and somatic mutations in cancer, and compared them with respect to predicted functional sites in proteins. Using the sequence homologybased tool SIFT to estimate the proportion of deleterious AAS in each dataset, only complex disease AAS were found to be indistinguishable from neutral polymorphic AAS. Investigation of monogenic disease AAS predicted to be nondeleterious by SIFT were characterized by a significant enrichment for inherited AAS within solvent accessible residues, regions of intrinsic protein disorder, and an association with the loss or gain of various posttranslational modifications. Sites of structural and/or functional interest were therefore surmised to constitute useful additional features with which to identify the molecular disruptions caused by deleterious AAS. A range of bioinformatic tools, designed to predict structural and functional sites in protein sequences, were then employed to demonstrate that intrinsic biases exist in terms of the distribution of different types of human AAS with respect to specific structural, functional and pathological features. Our Web tool, designed to potentiate the functional profiling of novel AAS, has been made available at http://profile.mutdb.org/. http://www.ncbi.nlm.nih.gov/pubmed/20052762 Sun, 31 Jan 2010 00:00:00 -0800 Advanced statistical methods used to analyze highthroughput data (e.g. geneexpression assays) result in long lists of "significant genes." One way to gain insight into the significance of altered expression levels is to determine whether Gene Ontology (GO) terms associated with a particular biological process, molecular function, or cellular component are over or underrepresented in the set of genes deemed significant. This process, referred to as enrichment analysis, profiles a geneset, and is relevant for and extensible to data analysis with other highthroughput measurement modalities such as proteomics, metabolomics, and tissuemicroarray assays. With the availability of tools for automatic ontologybased annotation of datasets with terms from biomedical ontologies besides the GO, we need not restrict enrichment analysis to the GO. We describe, RANSUM Rich Annotation Summarizer which performs enrichment analysis using any ontology in the National Center for Biomedical Ontology's (NCBO) BioPortal. We outline the methodology of enrichment analysis, the associated challenges, and discuss novel analyses enabled by RANSUM. http://www.ncbi.nlm.nih.gov/pubmed/21347088 Thu, 31 Dec 2009 00:00:00 -0800 Xlinked chronic granulomatous disease (XCGD) is an inherited immunodeficiency with absent phagocyte NADPHoxidase activity caused by defects in the geneencoding gp91(phox). Here, we evaluated strategies for less intensive conditioning for gene therapy of genetic blood disorders without selective advantage for gene correction, such as might be used in a human XCGD protocol. We compared submyeloablative with ablative irradiation as conditioning in murine XCGD, examining engraftment, oxidase activity and vector integration in mice transplanted with marrow transduced with a gammaretroviral vector for gp91(phox) expression. The frequency of oxidasepositive neutrophils in the donor population was unexpectedly higher in many 300 cGyconditioned mice compared with lethally irradiated recipients, as was the fraction of vectormarked donor secondary CFUS12. Vector integration sites in marrow, spleen and secondary CFUS12 DNA from primary recipients were enriched for cancerassociated genes, including Evi1, and integrations in or near cancerassociated genes were more frequent in marrow and secondary CFUS12 from 300 cGyconditioned mice compared with fully ablated mice. These findings support the concept that vector integration can confer a selection bias, and suggest that the intensity of the conditioning regimen may further influence the effects of vector integration on clonal selection in posttransplant engraftment and hematopoiesis. http://www.ncbi.nlm.nih.gov/pubmed/19657370 Mon, 30 Nov 2009 00:00:00 -0800 Understanding and predicting molecular cause of disease is one of the major challenges for biology and medicine. One particular area of interest continues to be computational analyses of diseaseassociated amino acid substitutions. To this end, various studies have been performed to identify molecular functions disrupted by diseasecausing mutations. Here, we investigate the influence of diseaseassociated mutations on posttranslational modifications. In particular, we study the loss of modification target sites as a consequence of disease mutation. We find that about 5 of diseaseassociated mutations may affect known modification sites, either partially (4) of fully (1), compared to about 2 of putatively neutral polymorphisms. Most of the fifteen posttranslational modification types analyzed were found to be disrupted at levels higher than expected by chance. Molecular functions and physiochemical properties at sites of disease mutation were also compared to those of neutral polymorphisms involved in the process of posttranslational modification site disruption. Diseaseassociated mutations in the neighborhood of posttranslationally modified sites were found to be enriched in mutations that change polarity, charge, and hydrophobicity of the wildtype amino acids. Overall, these results further suggest that disruption of modification sites is an important but not the major cause of human genetic disease. http://www.ncbi.nlm.nih.gov/pubmed/19908386 Sat, 31 Oct 2009 00:00:00 -0700 MOTIVATION: Advances in highthroughput genotyping and next generation sequencing have generated a vast amount of human genetic variation data. Single nucleotide substitutions within protein coding regions are of particular importance owing to their potential to give rise to amino acid substitutions that affect protein structure and function which may ultimately lead to a disease state. Over the last decade, a number of computational methods have been developed to predict whether such amino acid substitutions result in an altered phenotype. Although these methods are useful in practice, and accurate for their intended purpose, they are not well suited for providing probabilistic estimates of the underlying disease mechanism. RESULTS: We have developed a new computational model, MutPred, that is based upon protein sequence, and which models changes of structural features and functional sites between wildtype and mutant sequences. These changes, expressed as probabilities of gain or loss of structure and function, can provide insight into the specific molecular mechanism responsible for the disease state. MutPred also builds on the established SIFT method but offers improved classification accuracy with respect to human disease mutations. Given conservative thresholds on the predicted disruption of molecular function, we propose that MutPred can generate accurate and reliable hypotheses on the molecular basis of disease for approximately 11 of known inherited diseasecausing mutations. We also note that the proportion of changes of functionally relevant residues in the sets of cancerassociated somatic mutations is higher than for the inherited lesions in the Human Gene Mutation Database which are instead predicted to be characterized by disruptions of protein structure. AVAILABILITY: http://mutdb.org/mutpred CONTACT: predragindiana.edu smooneybuckinstitute.org. http://www.ncbi.nlm.nih.gov/pubmed/19734154 Wed, 30 Sep 2009 00:00:00 -0700 Understanding how mutations lead to changes in protein function and/or protein interaction is critical to understanding the molecular causes of clinical phenotypes. In this method, we present a path toward integration of protein interaction data and mutation data and then demonstrate the identification of a subset of proteins and interactions that are important to a particular disease. We then build a statistical model of disease mutations in this diseaseassociated subset of proteins, and visualize these results. Using Alzheimer's disease (AD) as case implementation, we find that we are able to identify a subset of proteins involved in AD and discriminate diseaseassociated mutations from SNPs in these proteins with 83 accuracy. As the molecular causes of disease become more understood, models such as these will be useful for identifying candidate variants most likely to be causative. http://www.ncbi.nlm.nih.gov/pubmed/19381537 Tue, 31 Mar 2009 00:00:00 -0700 Metazoan genes are encrypted with at least two superimposed codes: the genetic code to specify the primary structure of proteins and the splicing code to expand their proteomic output via alternative splicing. Here, we define the specificity of a central regulator of premRNA splicing, the conserved, essential splicing factor SFRS1. Crosslinking immunoprecipitation and highthroughput sequencing (CLIPseq) identified 23,632 binding sites for SFRS1 in the transcriptome of cultured human embryonic kidney cells. SFRS1 was found to engage many different classes of functionally distinct transcripts including mRNA, miRNA, snoRNAs, ncRNAs, and conserved intergenic transcripts of unknown function. The majority of these diverse transcripts share a purinerich consensus motif corresponding to the canonical SFRS1 binding site. The consensus site was not only enriched in exons crosslinked to SFRS1 in vivo, but was also enriched in close proximity to splice sites. mRNAs encoding RNA processing factors were significantly overrepresented, suggesting that SFRS1 may broadly influence the posttranscriptional control of gene expression in vivo. Finally, a search for the SFRS1 consensus motif within the Human Gene Mutation Database identified 181 mutations in 82 different genes that disrupt predicted SFRS1 binding sites. This comprehensive analysis substantially expands the known roles of human SR proteins in the regulation of a diverse array of RNA transcripts. http://www.ncbi.nlm.nih.gov/pubmed/19116412 Sat, 28 Feb 2009 00:00:00 -0800 Research in gene therapy involving genomeintegrating vectors now often includes analysis of vector integration sites across the genome using methods such as ligationmediated PCR (LMPCR) or linear amplificationmediated PCR (LAMPCR). To help researchers analyze these sites and the functions of nearby genes, we have developed SeqMap (http://seqmap.compbio.iupui.edu/) a secure, webbased comprehensive vector integration site management tool that automatically analyzes and annotates large numbers of vector integration sites derived from LMPCR experiments in human and model organisms upon a common genome database. We believe the use of this resource will enable better reproducibility and understanding of this important data. http://www.ncbi.nlm.nih.gov/pubmed/18580967 Sun, 31 Aug 2008 00:00:00 -0700 MOTIVATION: Codingregion mutations in human genes are responsible for a diverse spectrum of diseases and phenotypes. Among lesions that have been studied extensively, there are insights into several of the biochemical functions disrupted by diseasecausing mutations. Currently, there are more than 60 000 codingregion mutations associated with inherited disease catalogued in the Human Gene Mutation Database (HGMD, August 2007) and more than 70 000 polymorphic amino acid substitutions recorded in dbSNP (dbSNP, build 127). Understanding the mechanism and contribution these variants make to a clinical phenotype is a formidable problem. RESULTS: In this study, we investigate the role of phosphorylation in somatic cancer mutations and inherited diseases. Somatic cancer mutation datasets were shown to have a significant enrichment for mutations that cause gain or loss of phosphorylation when compared to our control datasets (putatively neutral nsSNPs and random amino acid substitutions). Of the somatic cancer mutations, those in kinase genes represent the most enriched set of mutations that disrupt phosphorylation sites, suggesting phosphorylation target site mutation is an active cause of phosphorylation deregulation. Overall, this evidence suggests both gain and loss of a phosphorylation site in a target protein may be important features for predicting cancercausing mutations and may represent a molecular cause of disease for a number of inherited and somatic mutations. http://www.ncbi.nlm.nih.gov/pubmed/18689832 Thu, 31 Jul 2008 00:00:00 -0700 One of the most important tasks of modern bioinformatics is the development of computational tools that can be used to understand and treat human disease. To date, a variety of methods have been explored and algorithms for candidate gene prioritization are gaining in their usefulness. Here, we propose an algorithm for detecting genedisease associations based on the human proteinprotein interaction network, known genedisease associations, protein sequence, and protein functional information at the molecular level. Our method, PhenoPred, is supervised: first, we mapped each gene/protein onto the spaces of disease and functional terms based on distance to all annotated proteins in the protein interaction network. We also encoded sequence, function, physicochemical, and predicted structural properties, such as secondary structure and flexibility. We then trained support vector machines to detect genedisease associations for a number of terms in Disease Ontology and provided evidence that, despite the noise/incompleteness of experimental data and unfinished ontology of diseases, identification of candidate genes can be successful even when a large number of candidate disease terms are predicted on simultaneously. Availability: www.phenopred.org. http://www.ncbi.nlm.nih.gov/pubmed/18300252 Mon, 30 Jun 2008 00:00:00 -0700 Massively parallel pyrosequencing is a highthroughput technology that can sequence hundreds of thousands of DNA/RNA fragments in a single experiment. Combining it with immunoprecipitationbased biochemical assays, such as crosslinking immunoprecipitation (CLIP), provides a genomewide method to detect the sites at which proteins bind DNA or RNA. In a CLIPpyrosequencing experiment, the resolutions of the detected protein binding regions are partially determined by the length of the detected RNA fragments (CLIP amplicons) after trimming by RNase digestion. The lengths of these fragments usually range from 5070 nucleotides. Many genomic regions are marked by multiple RNA fragments. In this paper, we report an empirical approach to refine the localization of protein binding regions by using the distribution pattern of the detected RNA fragments and the sequence specificity of RNase digestion. We present two regions to which multiple amplicons map as examples to demonstrate this approach. http://www.ncbi.nlm.nih.gov/pubmed/18366606 Fri, 29 Feb 2008 00:00:00 -0800 Understanding how genetic variation affects the molecular function of gene products is an emergent area of bioinformatic research. Here, we present updates to MutDB (http://www.mutdb.org), a tool aiming to aid bioinformatic studies by integrating publicly available databases of human genetic variation with molecular features and clinical phenotype data. MutDB, first developed in 2002, integrates annotated SNPs in dbSNP and amino acid substitutions in SwissProt with protein structural information, links to scores that predict functional disruption and other useful annotations. Though these functional annotations are mainly focused on nonsynonymous SNPs, some information on other SNP types included in dbSNP is also provided. Additionally, we have developed a new functionality that facilitates KEGG pathway visualization of genes containing SNPs and a SNP query tool for visualizing and exporting sets of SNPs that share selected features based on certain filters. http://www.ncbi.nlm.nih.gov/pubmed/17827212 Mon, 31 Dec 2007 00:00:00 -0800 A common challenge for bioinformaticians, in either academic or industry laboratory environments, is providing informatic solutions via the Internet or through a web browser. Recently, the open source community began developing tools for building and maintaining web applications for many disciplines. These content management systems (CMS) provide many of the basic needs of an informatics group, whether in a small company, a group within a larger organisation or an academic laboratory. These tools aid in managing software development, website development, document development, course development, datasets, collaborations and customers. Since many of these tools are extensible, they can be developed to support other researchspecific activities, such as handling large biomedical datasets or deploying bioanalytic tools. In this review of open source website management tools, the basic features of content management systems are discussed along with commonly used open source software. Additionally, some examples of their use in biomedical research are given. http://www.ncbi.nlm.nih.gov/pubmed/18057072 Fri, 30 Nov 2007 00:00:00 -0800 Structural genomics projects are determining the threedimensional structure of proteins without full characterization of their function. A critical part of the annotation process involves appropriate knowledge representation and prediction of functionally important residue environments. We have developed a method to extract features from sequence, sequence alignments, threedimensional structure, and structural environment conservation, and used support vector machines to annotate homologous and nonhomologous residue positions based on a specific training set of residue functions. In order to evaluate this pipeline for automated protein annotation, we applied it to the challenging problem of prediction of catalytic residues in enzymes. We also ranked the features based on their ability to discriminate catalytic from noncatalytic residues. When applying our method to a wellannotated set of protein structures, we found that topranked features were a measure of sequence conservation, a measure of structural conservation, a degree of uniqueness of a residue's structural environment, solvent accessibility, and residue hydrophobicity. We also found that features based on structural conservation were complementary to those based on sequence conservation and that they were capable of increasing predictor performance. Using a family nonredundant version of the ASTRAL 40 v1.65 data set, we estimated that the true catalytic residues were correctly predicted in 57.0 of the cases, with a precision of 18.5. When testing on proteins containing novel folds not used in training, the best features were highly correlated with the training on families, thus validating the approach to nonhomologous catalytic residue prediction in general. We then applied the method to 2781 coordinate files from the structural genomics target pipeline and identified both highly ranked and highly clustered groups of predicted catalytic residues. http://www.ncbi.nlm.nih.gov/pubmed/17189479 Sun, 31 Dec 2006 00:00:00 -0800 http://www.ncbi.nlm.nih.gov/pubmed/16470795 Tue, 31 Jan 2006 00:00:00 -0800 A primary challenge for structural genomics is the automated functional characterization of protein structures. We have developed a sequenceindependent method called SBLEST (StructureBased Local Environment Search Tool) for the annotation of previously uncharacterized protein structures. SBLEST encodes the local environment of an amino acid as a vector of structural property values. It has been applied to all amino acids in a nonredundant database of protein structures to generate a searchable structural resource. Given a query amino acid from an experimentally determined or modeled structure, SBLEST quickly identifies similar amino acid environments using a Knearest neighbor search. In addition, the method gives an estimation of the statistical significance of each result. We validated SBLEST on Xray crystal structures from the ASTRAL 40 nonredundant dataset. We then applied it to 86 crystallographically determined proteins in the protein data bank (PDB) with unknown function and with no significant sequence neighbors in the PDB. SBLEST was able to associate 20 proteins with at least one local structural neighbor and identify the amino acid environments that are most similar between those neighbors. http://www.ncbi.nlm.nih.gov/pubmed/16245324 Mon, 31 Oct 2005 00:00:00 -0800 Familial tumoral calcinosis (TC, OMIM 211900) is a heritable disorder characterized by hyperphosphatemia, normal or elevated serum 1,25dihydroxyvitamin D, and often severe ectopic calcifications. Two recessive mutations in fibroblast growth factor23 (FGF23), serine 71/glycine (S71G) and serine 129/phenylalanine (S129F), were identified as causing TC. Herein, we undertook comprehensive biochemical analyses of an extended TC family carrying the S71G FGF23 mutation, which revealed that heterozygous (serine/glycine, S/G) individuals had elevated serum FGF23 Cterminal fragments compared with wildtype (serine/serine, S/S) family members (P 0.025). To understand the differential processing of FGF23 in TC patients, we transiently expressed S71G as well as S129F FGF23. FGF23 ELISA in tandem with Western analyses revealed increased proteolytic cleavage of mutant FGF23 and a limited secretion of intact protein. Furthermore, S71G and S129F FGF23 carrying mutations that disrupt the furinlike protease RXXR motif in FGF23 rescued the secretion of the intact protein, and both TC mutant proteins harboring the R176Q mutation revealed no altered sensitivity to trypsin compared with the native (R176Q)FGF23. Finally, S71G, but not S129F mutant FGF23, is rescued by temperature. In summary, FGF23 mutations causing TC lead to increased intracellular proteolysis of FGF23, most likely by furinlike proteases, due to conformational changes of the mutant protein. The destabilizing nature of these mutations provides new insight into the pathophysiology of TC and exemplifies the physiological importance of FGF23 in phosphate and vitamin D metabolism. http://www.ncbi.nlm.nih.gov/pubmed/15961556 Sun, 31 Jul 2005 00:00:00 -0700 Gainoffunction mutations in fibroblast growth factor23 (FGF23) are responsible for autosomal dominant hypophosphatemic rickets, a disorder of isolated renal phosphate wasting. Patients with the disorder display hypophosphatemia with normocalcemia as well as inappropriately normal 1,25dihydroxyvitamin D 1,25(OH)2D3 concentrations. Reciprocally tumoral calcinosis (TC) patients are often hyperphosphatemic with inappropriately normal or elevated serum 1,25(OH)2D3 levels and have ectopic and vascular calcifications, a phenotype similar to that of Fgf23 null mice. Therefore, the goal of the present studies was to test whether FGF23 was a candidate gene for TC. Two sisters in a consanguineous TC family had hyperphosphatemia and normal 1,25(OH)2D3 levels with characteristic ectopic and vascular calcifications. Interestingly, these patients had lownormal intact serum FGF23 levels but demonstrated FGF23 concentrations approximately 40 times normal when assessed with a Cterminal FGF23 serum assay. Mutational analyses identified a homozygous S71G mutation in FGF23 in the TC patients, which was not found in control alleles. Finally, modeling demonstrated that the S71G mutation most likely destabilizes fulllength FGF23. In summary, recessive FGF23 mutations can lead to TC. Additionally, our findings indicate that FGF23 may adopt an unstable conformation in some TC patients, possibly leading to nonfunctional FGF23 protein. http://www.ncbi.nlm.nih.gov/pubmed/15687325 Thu, 31 Mar 2005 00:00:00 -0800 Despite the advantages provided by the enormous recent increases in the availability of structural information, functional assignment for the large number of proteins represented in the sequence and structural genomics projects remains a pressing problem for genomic era biology. This section describes work relevant to this problem from several perspectives, including new approaches that take advantage of combined structure and sequencebased classification. Leveraging of genomic context and evolutionary information to improve classification and predictive power is a second prominent theme in the papers represented here. Finally, issues in building a database for linking sequence, structural, and functional information are explored. http://www.ncbi.nlm.nih.gov/pubmed/15759637 Mon, 28 Feb 2005 00:00:00 -0800 BACKGROUND: For many years, scientists believed that point mutations in genes are the genetic switches for somatic and inherited diseases such as cystic fibrosis, phenylketonuria and cancer. Some of these mutations likely alter a protein's function in a manner that is deleterious, and they should occur in functionally important regions of the protein products of genes. Here we show that diseaseassociated mutations occur in regions of genes that are conserved, and can identify likely diseasecausing mutations. RESULTS: To show this, we have determined conservation patterns for 6185 nonsynonymous and heritable diseaseassociated mutations in 231 genes. We define a parameter, the conservation ratio, as the ratio of average negative entropy of analyzable positions with reported mutations to that of every analyzable position in the gene sequence. We found that 84.0 of the 231 genes have conservation ratios less than one. 139 genes had eleven or more analyzable mutations and 88.0 of those had conservation ratios less than one. CONCLUSIONS: These results indicate that phylogenetic information is a powerful tool for the study of diseaseassociated mutations. Our alignments and analysis has been made available as part of the database at http://cancer.stanford.edu/mutpaper/. Within this dataset, each position is annotated with the analysis, so the most likely diseasecausing mutations can be identified. http://www.ncbi.nlm.nih.gov/pubmed/12220483 Tue, 30 Sep 2003 00:00:00 -0700 SUMMARY: We have developed a resource, MutDB (http://mutdb.org/), to aid in determining which single nucleotide polymorphisms (SNPs) are likely to alter the function of their associated protein product. MutDB contains protein structure annotations and comparative genomic annotations for 8000 diseaseassociated mutations and SNPs found in the UCSC Annotated Genome and the human RefSeq gene set. MutDB provides interactive mutation maps at the gene and protein levels, and allows for ranking of their predicted functional consequences based on conservation in multiple sequence alignments. AVAILABILITY: http://mutdb.org/ Supplementary information: http://mutdb.org/about/about.html http://www.ncbi.nlm.nih.gov/pubmed/14512363 Sun, 31 Aug 2003 00:00:00 -0700 Inducible (iNOS) and constitutive (eNOS, nNOS) nitricoxide synthases differ in their Ca2calmodulin (CaM) dependence. iNOS binds CaM irreversibly but eNOS and nNOS, which bind CaM reversibly, have inserts in their reductase domains that regulate electron transfer. These include the 4345amino acid autoinhibitory element (AI) that attenuates electron transfer in the absence of CaM, and the Cterminal 2040amino acid tail that attenuates electron transfer in a CaMindependent manner. We constructed models of the reductase domains of the three NOS isoforms to predict the structural basis for CaMdependent regulation. We have identified and characterized a loop (CD2A) within the NOS connecting domain that is highly conserved by isoform and that, like the AI element, is within direct interaction distance of the CaM binding region. The eNOS CD2A loop (eCD2A) has the sequence 834KGSPGGPPPG843, and is truncated to 809ESGSY813 (iCD2A) in iNOS. The eCD2A contributes to the Ca2 dependence of CaMbound activity to a level similar to that of the AI element. The eCD2A plays an autoinhibitory role in the control of NO, and CaMdependent and independent reductase activity, but this autoinhibitory function is masked by the dominant AI element. Finally, the iCD2A is involved in determining the salt dependence of NO activity at a postflavin reduction level. Electrostatic interactions between the CD2A loop and the CaMbinding region, and CaM itself, provide a structural means for the CD2A to mediate CaM regulation of intrasubunit electron transfer within the active NOS complex. http://www.ncbi.nlm.nih.gov/pubmed/12805387 Thu, 31 Jul 2003 00:00:00 -0700 Mutations in the androgen receptor (AR) are associated with a variety of diseases including androgen insensitivity syndrome and prostate cancer, but the way in which these mutations cause disease is poorly understood. We present a method for distinguishing likely diseasecausing mutations from mutations that are merely associated with disease but have no causal role. Our method uses a measure of nucleotide conservation, and we find that conservation often correlates with severity of the clinical phenotype. Further, by only including mutations whose pathogenicity has been proven experimentally, this correlation is enhanced in the case of prostate cancerassociated mutations. Our method provides a means for assessing the significance of single nucleotide polymorphisms (SNPs) and cancerassociated mutations. http://www.ncbi.nlm.nih.gov/pubmed/12682377 Mon, 31 Mar 2003 00:00:00 -0800 Osteogenesis imperfecta (OI) is a genetic disease in which the most common mutations result in substitutions for glycine residues in the triple helical domain of the chains of type I collagen. Currently there is no way to use sequence information to predict the clinical OI phenotype. However, structural models coupled with biophysical and machine learning methods may be able to predict sequences that, when mutated, would be associated with more severe forms of OI. To build appropriate structural models, we have applied a high throughput molecular dynamic approach. Homotrimeric peptides covering 57 positions in which mutations are associated with OI were simulated both with and without mutations. Our models revealed structural differences that occur with different substituting amino acids. When mutations were introduced, we observed a decrease in helix stability, as caused by fewer main chain backbone hydrogen bonds, and an increase in main chain root mean square deviation and specifically bound water molecules. http://www.ncbi.nlm.nih.gov/pubmed/12488462 Sat, 30 Nov 2002 00:00:00 -0800 Researchers have recently questioned the role hydroxylated prolines play in stabilizing the collagen triple helix. To address these issues, we have developed new molecular mechanics parameters for the simulation of peptides containing 4(R)fluoroproline (Flp), 4(R)hydroxyproline (Hyp), and 4(R)aminoproline (Amp). Simulations of peptides based on these parameters can be used to determine the components that stabilize hydroxyproline over proline in the triple helix. The dihedrals FCCN, OCCN, and NCCN were built using a Nbetaethyl amide model. One nanosecond simulations were performed on the trimers (ProProGly)(10)(3), (ProHypGly)(10)(3), (ProAmpGly)(10)(3), (ProAmp(1)Gly)(10)(3), and (ProFlpGly)(10)(3) in explicit solvent. The results of our simulations suggest that pyrrolidine ring conformation is mediated by the strength of the gauche effect and classical electrostatic interactions. http://www.ncbi.nlm.nih.gov/pubmed/11979516 Tue, 30 Apr 2002 00:00:00 -0700 We studied the results of mutating alanine glycine at three positions of a collagenlike peptide in an effort to develop a computational method for predicting the energetic and structural effects of a single point genetic mutation in collagen, which is associated with the clinical diagnosis of Osteogenesis Imperfecta (OI). The differences in free energy of denaturation were calculated between the collagenlike peptides (POG)(4)(POA)(POG)(4)(3) and (POG)(10)(3) (POG: prolinehydroxyprolineglycine). Our computational results, which suggest significant destabilization of the collagenlike triplehelix upon the glycine alanine mutations, correlate very well with the experimental free energies of denaturation. The robustness of our collagenlike peptide model is shown by its reproduction of experimental results with both different simulation paths and different lengths of the model peptide. The individual free energy for each alanine glycine mutation (and the reverse free energy, glycine alanine mutation) in the collagenlike peptide has been calculated. We find that the first alanine introduced into the triple helix causes a very large destabilization of the helix, but the last alanine introduced into the same position of an adjacent chain causes a very small change in the peptide stability. Thus, our results demonstrate that each mutation does not contribute equally to the free energy. We find that the sum of the calculated individual residues' free energy can accurately model the experimental free energy for the whole peptide. http://www.ncbi.nlm.nih.gov/pubmed/11169394 Wed, 31 Jan 2001 00:00:00 -0800