Ivana Mihalek

An Accurate, Sensitive, and Scalable Method to Identify Functional Sites in Protein Structures

Functional sites determine the activity and interactions of proteins and as such constitute the targets of most drugs. However, the exponential growth of sequence and structure data far exceeds the ability of experimental techniques to identify their locations and key amino acids. To fill this gap we developed a computational Evolutionary Trace method that ranks the evolutionary importance of amino acids in protein sequences. Studies show that the best-ranked residues form fewer and larger structural clusters than expected by chance and overlap with functional sites, but until now the significance of this overlap has remained qualitative. Here, we use 86 diverse protein structures, including 20 determined by the structural genomics initiative, to show that this overlap is a recurrent and statistically significant feature. An automated ET correctly identifies seven of ten functional sites by the least favorable statistical measure, and nine of ten by the most favorable one. These results quantitatively demonstrate that a large fraction of functional sites in the proteome may be accurately identified from sequence and structure. This should help focus structure-function studies, rational drug design, protein engineering, and functional annotation to the relevant regions of a protein.

An evolution based classifier for prediction of protein interfaces without using protein structures

MOTIVATION The number of available protein structures still lags far behind the number of known protein sequences. This makes it important to predict which residues participate in protein-protein interactions using only sequence information. Few studies have tackled this problem until now. RESULTS We applied support vector machines to sequences in order to generate a classification of all protein residues into those that are part of a protein interface and those that are not. For the first time evolutionary information was used as one of the attributes and this inclusion of evolutionary importance rankings improves the classification. Leave-one-out cross-validation experiments show that prediction accuracy reaches 64%.

Evolutionary trace report_maker: a new type of service for comparative analysis of proteins

: Evolutionary trace report_maker offers a new type of service for researchers investigating the function of novel proteins. It pools, from different sources, information about protein sequence, structure and elementary annotation, and to that background superimposes inference about the evolutionary behavior of individual residues, using real-valued evolutionary trace method. As its only input it takes a Protein Data Bank identifier or UniProt accession number, and returns a human-readable document in PDF format, supplemented by the original data needed to reproduce the results quoted in the report.

Accurate and scalable identification of functional sites by evolutionary tracing.

A common difficulty in post genomics biology is that large-scale techniques of data collection often strip away information on the biological context of these data. The result is a massive number of disconnected observations on sequence, structure, and function from which underlying patterns and biological meaning are obscured. One solution is to build computational filters that pick out sufficiently few facts, relevant to a query, that their relationship is immediately apparent and experimentally testable. Typically, these filters rely on mathematics and statistics, and on first principles from physics and chemistry. We show here that evolution itself can be used to filter sequence and structure data in order to identify evolutionarily important amino acids. A general property of these residues is that they form clusters in native protein structures and point to regions where mutations have the greatest biological impact. The result is an accurate method of functional site annotation that is scalable for structural proteomics.

Combining inference from evolution and geometric probability in protein structure evaluation.

Starting from the hypothesis that evolutionarily important residues form a spatially limited cluster in a proteins native fold, we discuss the possibility of detecting a non-native structure based on the absence of such clustering. The relevant residues are determined using the Evolutionary Trace method. We propose a quantity to measure clustering of the selected residues on the structure and show that the exact values for its average and variance over several ensembles of interest can be found. This enables us to study the behavior of the associated z-scores. Since our approach rests on an analytic result, it proves to be general, customizable, and computationally fast. We find that clustering is indeed detectable in a large representative protein set. Furthermore, we show that non-native structures tend to achieve lower residue-clustering z-scores than those attained by the native folds. The most important conclusion that we draw from this work is that consistency between structural and evolutionary information, manifested in clustering of key residues, imposes powerful constraints on the conformational space of a protein.

Helix Straightening as an Activation Mechanism in the Gelsolin Superfamily of Actin Regulatory Proteins

Villin and gelsolin consist of six homologous domains of the gelsolin/cofilin fold (V1–V6 and G1–G6, respectively). Villin differs from gelsolin in possessing at its C terminus an unrelated seventh domain, the villin headpiece. Here, we present the crystal structure of villin domain V6 in an environment in which intact villin would be inactive, in the absence of bound Ca2+ or phosphorylation. The structure of V6 more closely resembles that of the activated form of G6, which contains one bound Ca2+, rather than that of the calcium ion-free form of G6 within intact inactive gelsolin. Strikingly apparent is that the long helix in V6 is straight, as found in the activated form of G6, as opposed to the kinked version in inactive gelsolin. Molecular dynamics calculations suggest that the preferable conformation for this helix in the isolated G6 domain is also straight in the absence of Ca2+ and other gelsolin domains. However, the G6 helix bends in intact calcium ion-free gelsolin to allow interaction with G2 and G4. We suggest that a similar situation exists in villin. Within the intact protein, a bent V6 helix, when triggered by Ca2+, straightens and helps push apart adjacent domains to expose actin-binding sites within the protein. The sixth domain in this superfamily of proteins serves as a keystone that locks together a compact ensemble of domains in an inactive state. Perturbing the keystone initiates reorganization of the structure to reveal previously buried actin-binding sites.

Defining the Phenotype in Congenital Disorder of Glycosylation Due to ALG1 Mutations

Deficiency of β-1,4 mannosyltransferase (MT-1) congenital disorder of glycosylation (CDG), due to ALG1 gene mutations. Features in 9 patients reported previously consisted of prenatal growth retardation, pregnancy-induced maternal hypertension and fetal hydrops. Four patients died before 5 years of age, and survivors showed a severe psychomotor retardation. We report on 7 patients with psychomotor delay, microcephaly, strabismus and coagulation abnormalities, seizures and abnormal fat distribution. Four children had a stable clinical course, two had visual impairment, and 1 had hearing loss. Thrombotic and vascular events led to deterioration of the clinical outcome in 2 patients. Four novel ALG1 mutations were identified. Pathogenicity was determined in alg1 yeast mutants transformed with hALG1. Functional analyses showed all novel mutations representing hypomorphs associated with residual enzyme activity. We extend the phenotypic spectrum including the first description of deafness in MT1 deficiency, and report on mildly affected patients, surviving to adulthood. The dysmorphic features, including abnormal fat distribution and strabismus highly resemble CDG due to phosphomannomutase-2 deficiency (PMM2-CDG), the most common type of CDG. We suggest testing for ALG1 mutations in unsolved CDG patients with a type 1 transferrin isoelectric focusing pattern, especially with epilepsy, severe visual loss and hemorrhagic/thrombotic events.

Rank information: A structure‐independent measure of evolutionary trace quality that improves identification of protein functional sites

Protein functional sites are key targets for drug design and protein engineering, but their large‐scale experimental characterization remains difficult. The evolutionary trace (ET) is a computational approach to this problem that has been useful in a variety of case studies, but its proteomic scale application is partially hindered because automated retrieval of input sequences from databases often includes some with errors that degrade functional site identification. To recognize and purge these sequences, this study introduces a novel and structure‐free measure of ET quality called rank information (RI). It is shown that RI decreases in response to errors in sequences, alignments, or functional classifications. Conversely, an automated procedure to increase RI by selectively removing sequences improves functional site identification so as to nearly match manually curated traces in kinases and in a test set of 79 diverse proteins. Thus we conclude that RI partially reflects the evolutionary consistency of sequence, structure, and function. In practice, as the size of the proteome continues to grow exponentially, it provides a novel and structure‐free measure of ET quality that increases its accuracy for large‐scale automated annotation of protein functional sites. Proteins 2006.

A structure and evolution-guided Monte Carlo sequence selection strategy for multiple alignment-based analysis of proteins

MOTIVATION Various multiple sequence alignment-based methods have been proposed to detect functional surfaces in proteins, such as active sites or protein interfaces. The effect that the choice of sequences has on the conclusions of such analysis has seldom been discussed. In particular, no method has been discussed in terms of its ability to optimize the sequence selection for the reliable detection of functional surfaces. RESULTS Here we propose, for the case of proteins with known structure, a heuristic Metropolis Monte Carlo strategy to select sequences from a large set of homologues, in order to improve detection of functional surfaces. The quantity guiding the optimization is the clustering of residues which are under increased evolutionary pressure, according to the sample of sequences under consideration. We show that we can either improve the overlap of our prediction with known functional surfaces in comparison with the sequence similarity criteria of selection or match the quality of prediction obtained through more elaborate non-structure based-methods of sequence selection. For the purpose of demonstration we use a set of 50 homodimerizing enzymes which were co-crystallized with their substrates and cofactors.

deconSTRUCT: general purpose protein database search on the substructure level

deconSTRUCT webserver offers an interface to a protein database search engine, usable for a general purpose detection of similar protein (sub)structures. Initially, it deconstructs the query structure into its secondary structure elements (SSEs) and reassembles the match to the target by requiring a (tunable) degree of similarity in the direction and sequential order of SSEs. Hierarchical organization and judicious use of the information about protein structure enables deconSTRUCT to achieve the sensitivity and specificity of the established search engines at orders of magnitude increased speed, without tying up irretrievably the substructure information in the form of a hash. In a post-processing step, a match on the level of the backbone atoms is constructed. The results presented to the user consist of the list of the matched SSEs, the transformation matrix for rigid superposition of the structures and several ways of visualization, both downloadable and implemented as a web-browser plug-in. The server is available at http://epsf.bmad.bii.a-star.edu.sg/struct_server.html.