02909nas a2200241   4500008004100000245013300041210006900174300001200243490000700255520182100262653009602083653009302179653007402272653002302346653008902369100001802458700001502476700001602491700001502507700001502522700002402537856010602561       2008                        eng d00aUse of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans0 aUse of estimated evolutionary strength at the codon level improv  a198-2040 v293 aPredicting the functional impact of protein variation is one of the most challenging problems in bioinformatics. A rapidly growing number of genome-scale studies provide large amounts of experimental data, allowing the application of rigorous statistical approaches for predicting whether a given single point mutation has an impact on human health. Up until now, existing methods have limited their source data to either protein or gene information. Novel in this work, we take advantage of both and focus on protein evolutionary information by using estimated selective pressures at the codon level. Here we introduce a new method (SeqProfCod) to predict the likelihood that a given protein variant is associated with human disease or not. Our method relies on a support vector machine (SVM) classifier trained using three sources of information: protein sequence, multiple protein sequence alignments, and the estimation of selective pressure at the codon level. SeqProfCod has been benchmarked with a large dataset of 8,987 single point mutations from 1,434 human proteins from SWISS-PROT. It achieves 82% overall accuracy and a correlation coefficient of 0.59, indicating that the estimation of the selective pressure helps in predicting the functional impact of single-point mutations. Moreover, this study demonstrates the synergic effect of combining two sources of information for predicting the functional effects of protein variants: protein sequence/profile-based information and the evolutionary estimation of the selective pressures at the codon level. The results of large-scale application of SeqProfCod over all annotated point mutations in SWISS-PROT (available for download at http://sgu.bioinfo.cipf.es/services/Omidios/; last accessed: 24 August 2007), could be used to support clinical studies.10aAlgorithms Codon/genetics Computational Biology/*methods *DNA Mutational Analysis Databases10aHuman Humans Iduronic Acid/analogs & derivatives/metabolism *Point Mutation Polymorphism10aMolecular *Genetic Predisposition to Disease Genetic Variation Genome10aProtein *Evolution10aSingle Nucleotide Proteins/chemistry/*genetics Tumor Suppressor Protein p53/genetics1 aCapriotti, E.1 aArbiza, L.1 aCasadio, R.1 aDopazo, J.1 aDopazo, H.1 aMarti-Renom, M., A.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1793514802774nas a2200313   4500008004100000245014600041210006900187300001300256490000800269520115600277653004801433653003001481653005001511653023501561653012201796653010201918653014402020100002002164700001502184700002102199700002202220700001702242700002402259700001302283700002002296700001902316700001902335856010602354       2002                        eng d00aUse of single point mutations in domain I of beta 2-glycoprotein I to determine fine antigenic specificity of antiphospholipid autoantibodies0 aUse of single point mutations in domain I of beta 2glycoprotein   a7097-1030 v1693 aAutoantibodies against beta(2)-glycoprotein I (beta(2)GPI) appear to be a critical feature of the antiphospholipid syndrome (APS). As determined using domain deletion mutants, human autoantibodies bind to the first of five domains present in beta(2)GPI. In this study the fine detail of the domain I epitope has been examined using 10 selected mutants of whole beta(2)GPI containing single point mutations in the first domain. The binding to beta(2)GPI was significantly affected by a number of single point mutations in domain I, particularly by mutations in the region of aa 40-43. Molecular modeling predicted these mutations to affect the surface shape and electrostatic charge of a facet of domain I. Mutation K19E also had an effect, albeit one less severe and involving fewer patients. Similar results were obtained in two different laboratories using affinity-purified anti-beta(2)GPI in a competitive inhibition ELISA and with whole serum in a direct binding ELISA. This study confirms that anti-beta(2)GPI autoantibodies bind to domain I, and that the charged surface patch defined by residues 40-43 contributes to a dominant target epitope.10aAmino Acid Substitution/genetics Antibodies10aAntibody/genetics Binding10aAntiphospholipid/blood/*metabolism Antibodies10aCompetitive/genetics/immunology Enzyme-Linked Immunosorbent Assay/methods Epitopes/analysis/*immunology/metabolism Glycine/genetics Glycoproteins/biosynthesis/*genetics/*immunology/isolation & purification/metabolism Humans Models10aMolecular Peptide Fragments/genetics/immunology/isolation & purification/metabolism *Point Mutation Protein Structure10aMonoclonal/blood/metabolism Antiphospholipid Syndrome/immunology Arginine/genetics *Binding Sites10aTertiary/genetics Recombinant Proteins/biosynthesis/immunology/isolation & purification/metabolism Static Electricity beta 2-Glycoprotein I1 aIverson, G., M.1 aReddel, S.1 aVictoria, E., J.1 aCockerill, K., A.1 aWang, Y., X.1 aMarti-Renom, M., A.1 aSali, A.1 aMarquis, D., M.1 aKrilis, S., A.1 aLinnik, M., D.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12471146