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Biomedical subjects

Patrick Aloy

Publications and source records attributed to Patrick Aloy.

At least 19 recordsLinked to original sources
PubMed2006

Target selection for complex structural genomics.

Most cellular processes are carried out by macromolecular assemblies and regulated through a complex network of transient protein-protein interactions. Genome-wide interaction discovery experiments are already delivering the first drafts of whole organism interactomes and, thus, depicting the limits of the interaction space. However, a complete understanding of molecular interactions can only come from high-resolution three-dimensional structures, as they provide key atomic details about the binding interfaces. The launch of structural genomics initiatives focused on protein interactions and complexes could quickly fill up the interaction space with structural details, offering a new perspective on how cell networks operate at atomic level. Clear target selection strategies that rationally identify the key interactions and complexes that should be first tackled are fundamental to maximize the return, minimize the costs and prevent experimental difficulties.

Genomics↗
PubMed2006

Proteome survey reveals modularity of the yeast cell machinery.

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.

Genome, Fungal↗
PubMed2006

Structural systems biology: modelling protein interactions.

Much of systems biology aims to predict the behaviour of biological systems on the basis of the set of molecules involved. Understanding the interactions between these molecules is therefore crucial to such efforts. Although many thousands of interactions are known, precise molecular details are available for only a tiny fraction of them. The difficulties that are involved in experimentally determining atomic structures for interacting proteins make predictive methods essential for progress. Structural details can ultimately turn abstract system representations into models that more accurately reflect biological reality.

Cell Physiological Phenomena↗
PubMed2005

Structure-based systems biology: a zoom lens for the cell.

Systems biology seeks to explain complex biological systems, such as the cell, through the integration of many different types of information. Here, we discuss how the incorporation of high-resolution structural data can provide key molecular details often necessary to understand the complex connection between individual molecules and cell behavior. We suggest a process of zooming on the cell, from global networks through pathways to the precise atomic contacts at the interfaces of interacting proteins.

Animals↗
PubMed2005

3did: interacting protein domains of known three-dimensional structure.

The database of 3D Interacting Domains (3did) is a collection of domain-domain interactions in proteins for which high-resolution three-dimensional structures are known. 3did exploits structural information to provide critical molecular details necessary for understanding how interactions occur. It also offers an overview of how similar in structure are interactions between different members of the same protein family. The database also contains Gene Ontology-based functional annotations and interactions between yeast proteins from large-scale interaction discovery studies. A web-based tool to query 3did is available at http://3did.embl.de.

Databases, Protein↗
PubMed2005

Protein complexes: structure prediction challenges for the 21st century.

Only a tiny fraction of the many hundreds of known protein complexes are also of known three-dimensional structure. The experimental difficulties surrounding structure determination of complexes make methods that are able to predict structures paramount. The challenge of predicting complex structures is daunting and raises many issues that need to be addressed. To produce the best models, new prediction methods have to somehow combine partial structures with a mixed bag of experimental data, including interactions and low-resolution electron microscopy images.

Binding Sites↗
PubMed2005

Structural similarity to bridge sequence space: finding new families on the bridges.

Structures for protein domains have increased rapidly in recent years owing to advances in structural biology and structural genomics projects. New structures are often similar to those solved previously, and such similarities can give insights into function by linking poorly understood families to those that are better characterized. They also allow the possibility of combing information to find still more proteins adopting a similar structure and sometimes a similar function, and to reprioritize families in structural genomics pipelines. We explore this possibility here by preparing merged profiles for pairs of structurally similar, but not necessarily sequence-similar, domains within the SMART and Pfam database by way of the Structural Classification of Proteins (SCOP). We show that such profiles are often able to successfully identify further members of the same superfamily and thus can be used to increase the sensitivity of database searching methods like HMMer and PSI-BLAST. We perform detailed benchmarks using the SMART and Pfam databases with four complete genomes frequently used as annotation benchmarks. We quantify the associated increase in structural information in Swissprot and discuss examples illustrating the applicability of this approach to understand functional and evolutionary relationships between protein families.

Protein Conformation↗
PubMed2004

Structural insights into the target specificity of plant invertase and pectin methylesterase inhibitory proteins.

Pectin methylesterase (PME) and invertase are key enzymes in plant carbohydrate metabolism. Inhibitors of both enzymes constitute a sequence family of extracellular proteins. Members of this family are selectively targeted toward either PME or invertase. In a comparative structural approach we have studied how this target specificity is implemented on homologous sequences. By extending crystallographic work on the invertase inhibitor Nt-CIF to a pectin methylesterase inhibitor (PMEI) from Arabidopsis thaliana, we show an alpha-helical hairpin motif to be an independent and mobile structural entity in PMEI. Removal of this hairpin fully inactivates the inhibitor. A chimera composed of the alpha-hairpin of PMEI and the four-helix bundle of Nt-CIF is still active against PME. By contrast, combining the corresponding segment of Nt-CIF with the four-helix bundle of PMEI renders the protein inactive toward either PME or invertase. Our experiments provide insight in how these homologous inhibitors can make differential use of similar structural modules to achieve distinct functions. Integrating our results with previous findings, we present a model for the PME-PMEI complex with important implications.

Amino Acid Motifs↗
PubMed2004

Structure-based assembly of protein complexes in yeast.

Images of entire cells are preceding atomic structures of the separate molecular machines that they contain. The resulting gap in knowledge can be partly bridged by protein-protein interactions, bioinformatics, and electron microscopy. Here we use interactions of known three-dimensional structure to model a large set of yeast complexes, which we also screen by electron microscopy. For 54 of 102 complexes, we obtain at least partial models of interacting subunits. For 29, including the exosome, the chaperonin containing TCP-1, a 3'-messenger RNA degradation complex, and RNA polymerase II, the process suggests atomic details not easily seen by homology, involving the combination of two or more known structures. We also consider interactions between complexes (cross-talk) and use these to construct a structure-based network of molecular machines in the cell.

Chaperonins↗
PubMed2004

A structural perspective on protein-protein interactions.

Structures of macromolecular complexes are necessary for a mechanistic description of biochemical and cellular processes. They can be solved by experimental methods, such as X-ray crystallography, NMR spectroscopy and electron microscopy, as well as by computational protein structure prediction, docking and bioinformatics. Recent advances and applications of these methods emphasize the need for hybrid approaches that combine a variety of data to achieve better efficiency, accuracy, resolution and completeness.

Animals↗
PubMed2004

Ten thousand interactions for the molecular biologist.

Previous studies have suggested that nature is restricted to about 1,000 protein folds to perform a great diversity of functions. Here, we use protein interaction data from different sources and three-dimensional structures to suggest that the total number of interaction types is also limited, and estimate that most interactions in nature will conform to one of about 10,000 types. We currently know fewer than 2,000, and at the present rate of structure determination, it will be more than 20 years before we know a full representative set.

Cell Physiological Phenomena↗
PubMed2003

The relationship between sequence and interaction divergence in proteins.

There is currently a gap in knowledge between complexes of known three-dimensional structure and those known from other experimental methods such as affinity purifications or the two-hybrid system. This gap can sometimes be bridged by methods that extrapolate interaction information from one complex structure to homologues of the interacting proteins. To do this, it is important to know if and when proteins of the same type (e.g. family, superfamily or fold) interact in the same way. Here, we study interactions of known structure to address this question. We found all instances within the structural classification of proteins database of the same domain pairs interacting in different complexes, and then compared them with a simple measure (interaction RMSD). When plotted against sequence similarity we find that close homologues (30-40% or higher sequence identity) almost invariably interact the same way. Conversely, similarity only in fold (i.e. without additional evidence for a common ancestor) is only rarely associated with a similarity in interaction. The results suggest that there is a twilight zone of sequence similarity where it is not possible to say whether or not domains will interact similarly. We also discuss the rare instances of fold similarities interacting the same way, and those where obviously homologous proteins interact differently.

Amino Acid Sequence↗
PubMed2003

Predictions without templates: new folds, secondary structure, and contacts in CASP5.

We present the assessment of CASP5 predictions in the new fold category. For coordinate predictions, we considered five targets with new folds and eight lying on the fold recognition borderline. We performed detailed visual and numerical comparisons between predicted and experimental structures to assess prediction accuracy. The two procedures largely agreed, but the visual inspection identified instances where metrics, such as GDT_TS, ranked what we considered incorrect predictions highly. We found the quality of the best predictions to be very good: for nearly every target at least one group predicted a structure close to the correct one. However, selection of the best of five models is still problematic. The group of David Baker once again proved to be best overall, with many individual highlights. However, high quality and consistency were also seen from others, suggesting that the community is moving toward general procedures to predict accurate structures for proteins showing no resemblance to anything seen before. Predictions for secondary structure showed at best limited progress since CASP4. The number of targets is probably too small to spot differences in performance between methods, suggesting that such predictions might be better evaluated with schemes involving more proteins. For contact predictions, accuracies are still low, although there were several instances of accurate and useful contacts predicted de novo, and new approaches hint at future progress.

Algorithms↗
PubMed2003

InterPreTS: protein interaction prediction through tertiary structure.

SUMMARY: InterPreTS (Interaction Prediction through Tertiary Structure) is a web-based version of our method for predicting protein-protein interactions (Aloy and Russell, 2002, PROC: Natl Acad. Sci. USA, 99, 5896-5901). Given a pair of query sequences, we first search for homologues in a database of interacting domains (DBID) of known three-dimensional complex structures. Pairs of sequences homologous to a known interacting pair are scored for how well they preserve the atomic contacts at the interaction interface. InterPreTS includes a useful interface for visualising molecular details of any predicted interaction. AVAILABILITY: http://www.russell.embl.de/interprets.

Databases, Protein↗
PubMed2002

Interrogating protein interaction networks through structural biology.

Protein-protein interactions are central to most biological processes. Although much recent effort has been put into methods to identify interacting partners, there has been a limited focus on how these interactions compare with those known from three-dimensional (3D) structures. Because comparison of protein interactions often involves considering homologous, but not identical, proteins, a key issue is whether proteins that are homologous to an interacting pair will interact in the same way, or interact at all. Accordingly, we describe a method to test putative interactions on complexes of known 3D structure. Given a 3D complex and alignments of homologues of the interacting proteins, we assess the fit of any possible interacting pair on the complex by using empirical potentials. For studies of interacting protein families that show different specificities, the method provides a ranking of interacting pairs useful for prioritizing experiments. We evaluate the method on interacting families of proteins with multiple complex structures. We then consider the fibroblast growth factor/receptor system and explore the intersection between complexes of known structure and interactions proposed between yeast proteins by methods such as two-hybrids. We provide confirmation for several interactions, in addition to suggesting molecular details of how they occur.

Amino Acid Sequence↗