Biomedical subjects

Michael Schroeder

Publications and source records attributed to Michael Schroeder.

16 recordsLinked to original sources

PubMed2006

LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation.

BACKGROUND: Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed. RESULTS: We present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcsc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively. CONCLUSION: The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket

Algorithms↗

PubMed2006

The many faces of protein-protein interactions: A compendium of interface geometry.

A systematic classification of protein-protein interfaces is a valuable resource for understanding the principles of molecular recognition and for modelling protein complexes. Here, we present a classification of domain interfaces according to their geometry. Our new algorithm uses a hybrid approach of both sequential and structural features. The accuracy is evaluated on a hand-curated dataset of 416 interfaces. Our hybrid procedure achieves 83% precision and 95% recall, which improves the earlier sequence-based method by 5% on both terms. We classify virtually all domain interfaces of known structure, which results in nearly 6,000 distinct types of interfaces. In 40% of the cases, the interacting domain families associate in multiple orientations, suggesting that all the possible binding orientations need to be explored for modelling multidomain proteins and protein complexes. In general, hub proteins are shown to use distinct surface regions (multiple faces) for interactions with different partners. Our classification provides a convenient framework to query genuine gene fusion, which conserves binding orientation in both fused and separate forms. The result suggests that the binding orientations are not conserved in at least one-third of the gene fusion cases detected by a conventional sequence similarity search. We show that any evolutionary analysis on interfaces can be skewed by multiple binding orientations and multiple interaction partners. The taxonomic distribution of interface types suggests that ancient interfaces common to the three major kingdoms of life are enriched by symmetric homodimers. The classification results are online at http://www.scoppi.org.

Amino Acid Sequence↗

PubMed2006

Agents in bioinformatics, computational and systems biology.

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

Artificial Intelligence↗

PubMed2006

SCOWLP: a web-based database for detailed characterization and visualization of protein interfaces.

BACKGROUND: Currently there is a strong need for methods that help to obtain an accurate description of protein interfaces in order to be able to understand the principles that govern molecular recognition and protein function. Many of the recent efforts to computationally identify and characterize protein networks extract protein interaction information at atomic resolution from the PDB. However, they pay none or little attention to small protein ligands and solvent. They are key components and mediators of protein interactions and fundamental for a complete description of protein interfaces. Interactome profiling requires the development of computational tools to extract and analyze protein-protein, protein-ligand and detailed solvent interaction information from the PDB in an automatic and comparative fashion. Adding this information to the existing one on protein-protein interactions will allow us to better understand protein interaction networks and protein function. DESCRIPTION: SCOWLP (Structural Characterization Of Water, Ligands and Proteins) is a user-friendly and publicly accessible web-based relational database for detailed characterization and visualization of the PDB protein interfaces. The SCOWLP database includes proteins, peptidic-ligands and interface water molecules as descriptors of protein interfaces. It contains currently 74,907 protein interfaces and 2,093,976 residue-residue interactions formed by 60,664 structural units (protein domains and peptidic-ligands) and their interacting solvent. The SCOWLP web-server allows detailed structural analysis and comparisons of protein interfaces at atomic level by text query of PDB codes and/or by navigating a SCOP-based tree. It includes a visualization tool to interactively display the interfaces and label interacting residues and interface solvent by atomic physicochemical properties. SCOWLP is automatically updated with every SCOP release. CONCLUSION: SCOWLP enriches substantially the description of protein interfaces by adding detailed interface information of peptidic-ligands and solvent to the existing protein-protein interaction databases. SCOWLP may be of interest to many structural bioinformaticians. It provides a platform for automatic global mapping of protein interfaces at atomic level, representing a useful tool for classification of protein interfaces, protein binding comparative studies, reconstruction of protein complexes and understanding protein networks. The web-server with the database and its additional summary tables used for our analysis are available at http://www.scowlp.org.

Algorithms↗

PubMed2006

Efficacy of intensified hyperfractionated and accelerated radiotherapy and concurrent chemotherapy with carboplatin and 5-fluorouracil: updated results of a randomized multicentric trial in advanced head-and-neck cancer.

PURPOSE: To prove an expected benefit of concurrent radiochemotherapy (RCT), a two-arm randomized multicentric study was performed. In a subgroup analysis the influence of pretherapeutical hemoglobin level (p-Hb) on survival under locoregional control (SLC) was tested. PATIENTS AND METHODS: The study included primarily untreated Stage III/IV (International Union Against Cancer [UICC]) oropharyngeal and hypopharyngeal carcinomas. Patients were randomized to receive either hyperfractionated (hf) and accelerated (acc) RCT with two cycles 5-fluorouracil (600 mg/m(2)/day) and carboplatin (70 mg/m(2)/day) on Days 1-5 and 29-33 or hf-acc radiotherapy (RT) alone. Total RT dose in both arms was 69.9 Gy in 38 days in concomitant boost technique. RESULTS: After a median follow-up time of 57 months, SLC is significantly better in RCT than in RT (p = 0.01), with median SLC of 17 months and 11 months, respectively. Also overall survival (OS) shows a benefit for RCT (p = 0.016), with a median survival of 23 months for RCT and 16 months for RT. However, the benefit in SLC and OS is not seen in hypopharyngeal carcinomas. In a multivariate analysis of oropharyngeal cancer patients, p-Hb levels lower than 12.7 g/dL resulted in lower SLC compared with higher p-Hb levels up to 13.8 g/dL. P-Hb levels >13.8 g/dL did not further improve SLC. CONCLUSIONS: Hyperfractionated-accelerated RCT is superior to hf-acc RT in oropharyngeal carcinomas. P-Hb levels >13.8 g/dL do not further improve SLC.

Adult↗

PubMed2006

SCOPPI: a structural classification of protein-protein interfaces.

SCOPPI, the structural classification of protein-protein interfaces, is a comprehensive database that classifies and annotates domain interactions derived from all known protein structures. SCOPPI applies SCOP domain definitions and a distance criterion to determine inter-domain interfaces. Using a novel method based on multiple sequence and structural alignments of SCOP families, SCOPPI presents a comprehensive geometrical classification of domain interfaces. Various interface characteristics such as number, type and position of interacting amino acids, conservation, interface size, and permanent or transient nature of the interaction are further provided. Proteins in SCOPPI are annotated with Gene Ontology terms, and the ontology can be used to quickly browse SCOPPI. Screenshots are available for every interface and its participating domains. Here, we describe contents and features of the web-based user interface as well as the underlying methods used to generate SCOPPI's data. In addition, we present a number of examples where SCOPPI becomes a useful tool to analyze viral mimicry of human interface binding sites, gene fusion events, conservation of interface residues and diversity of interface localizations. SCOPPI is available at http://www.scoppi.org.

Binding Sites↗

PubMed2006

Multicenter randomized trial for stage IIIB/IV non-small-cell lung cancer using every-3-week versus weekly paclitaxel/carboplatin.

PURPOSE: The combination of paclitaxel with carboplatin is effective in advanced-stage non-small cell lung cancer (NSCLC). This phase III study was designed to compare the efficacy and tolerability of a weekly versus an every-3-week schedule in the first-line treatment of advanced-stage NSCLC. PATIENTS AND METHODS: Chemotherapy-naive patients were randomized to receive paclitaxel 100 mg/m2 and carboplatin at an area under the curve of 2 once weekly for 6-8 weeks (arm A) or paclitaxel 200 mg/m2 and carboplatin at an area under the curve of 6 on day 1 every 21 days (arm B). RESULTS: A total of 883 patients received >or= 1 chemotherapy cycle and were included in the results. The objective response rates observed (complete response plus partial response) were 38% for arm A and 33% for arm B. Median times to progression and median survival times were 6.1 months and 8.9 months in arm A and 7.2 months and 9.5 months in arm B, respectively. There were no significant differences between treatment arms. The chemotherapy was well tolerated in both schedules. However, grade 3/4 sensory neuropathy occurred more frequently with the every-3-week schedule (9.1% vs. 4.4%), whereas grade 3/4 diarrhea occurred more frequently with the weekly schedule (4.2% vs. 1.1%). CONCLUSION: In terms of response and survival, paclitaxel/carboplatin administered once weekly is comparable with the every-3-week schedule. Toxicity differences should be considered when choosing the appropriate schedule for the individual.

Adolescent↗

PubMed2006

Sealife: a semantic grid browser for the life sciences applied to the study of infectious diseases.

The objective of Sealife is the conception and realisation of a semantic Grid browser for the life sciences, which will link the existing Web to the currently emerging eScience infrastructure. The SeaLife Browser will allow users to automatically link a host of Web servers and Web/Grid services to the Web content he/she is visiting. This will be accomplished using eScience's growing number of Web/Grid Services and its XML-based standards and ontologies. The browser will identify terms in the pages being browsed through the background knowledge held in ontologies. Through the use of Semantic Hyperlinks, which link identified ontology terms to servers and services, the SeaLife Browser will offer a new dimension of context-based information integration. In this paper, we give an overview over the different components of the browser and their interplay. This SeaLife Browser will be demonstrated within three application scenarios in evidence-based medicine, literature & patent mining, and molecular biology, all relating to the study of infectious diseases. The three applications vertically integrate the molecule/cell, the tissue/organ and the patient/population level by covering the analysis of high-throughput screening data for endocytosis (the molecular entry pathway into the cell), the expression of proteins in the spatial context of tissue and organs, and a high-level library on infectious diseases designed for clinicians and their patients. For more information see http://www.biote.ctu-dresden.de/sealife.

Biological Science Disciplines↗

PubMed2005

Equivalent binding sites reveal convergently evolved interaction motifs.

MOTIVATION: Much research has been devoted to the characterization of interaction interfaces found in complexes with known structure. In this context, the interactions of non-homologous domains at equivalent binding sites are of particular interest, as they can reveal convergently evolved interface motifs. Such motifs are an important source of information to formulate rules for interaction specificity and to design ligands based on the common features shared among diverse partners. RESULTS: We develop a novel method to identify non-homologous structural domains which bind at equivalent sites when interacting with a common partner. We systematically apply this method to all pairs of interactions with known structure and derive a comprehensive database for these interactions. Of all non-homologous domains, which bind with a common interaction partner, 4.2% use the same interface of the common interaction partner (excluding immunoglobulins and proteases). This rises to 16% if immunoglobulin and proteases are included. We demonstrate two applications of our database: first, the systematic screening for viral protein interfaces, which can mimic native interfaces and thus interfere; and second, structural motifs in enzymes and its inhibitors. We highlight several cases of virus protein mimicry: viral M3 protein interferes with a chemokine dimer interface. The virus has evolved the motif SVSPLP, which mimics the native SSDTTP motif. A second example is the regulatory factor Nef in HIV which can mimic a kinase when interacting with SH3. Among others the virus has evolved the kinase's PxxP motif. Further, we elucidate motif resemblances in Baculovirus p35 and HIV capsid proteins. Finally, chymotrypsin is subject to scrutiny wrt. its structural similarity to subtilisin and wrt. its inhibitor's similar recognition sites. SUPPLEMENTARY INFORMATION: A database is online at scoppi.biotec.tu-dresden.de/abac/.

Algorithms↗

PubMed2005

GoPubMed: exploring PubMed with the Gene Ontology.

The biomedical literature grows at a tremendous rate and PubMed comprises already over 15 000 000 abstracts. Finding relevant literature is an important and difficult problem. We introduce GoPubMed, a web server which allows users to explore PubMed search results with the Gene Ontology (GO), a hierarchically structured vocabulary for molecular biology. GoPubMed provides the following benefits: first, it gives an overview of the literature abstracts by categorizing abstracts according to the GO and thus allowing users to quickly navigate through the abstracts by category. Second, it automatically shows general ontology terms related to the original query, which often do not even appear directly in the abstract. Third, it enables users to verify its classification because GO terms are highlighted in the abstracts and as each term is labelled with an accuracy percentage. Fourth, exploring PubMed abstracts with GoPubMed is useful as it shows definitions of GO terms without the need for further look up. GoPubMed is online at www.gopubmed.org. Querying is currently limited to 100 papers per query.

Abstracting and Indexing↗

PubMed2005

Comparative interactomics analysis of protein family interaction networks using PSIMAP (protein structural interactome map).

MOTIVATION: Many genomes have been completely sequenced. However, detecting and analyzing their protein-protein interactions by experimental methods such as co-immunoprecipitation, tandem affinity purification and Y2H is not as fast as genome sequencing. Therefore, a computational prediction method based on the known protein structural interactions will be useful to analyze large-scale protein-protein interaction rules within and among complete genomes. RESULTS: We confirmed that all the predicted protein family interactomes (the full set of protein family interactions within a proteome) of 146 species are scale-free networks, and they share a small core network comprising 36 protein families related to indispensable cellular functions. We found two fundamental differences among prokaryotic and eukaryotic interactomes: (1) eukarya had significantly more hub families than archaea and bacteria and (2) certain special hub families determined the topology of the eukaryotic interactomes. Our comparative analysis suggests that a very small number of expansive protein families led to the evolution of interactomes and seemed to have played a key role in species diversification. SUPPLEMENTARY INFORMATION: http://interactomics.org.

Algorithms↗

PubMed2005

PSIbase: a database of Protein Structural Interactome map (PSIMAP).

UNLABELLED: Protein Structural Interactome map (PSIMAP) is a global interaction map that describes domain-domain and protein-protein interaction information for known Protein Data Bank structures. It calculates the Euclidean distance to determine interactions between possible pairs of structural domains in proteins. PSIbase is a database and file server for protein structural interaction information calculated by the PSIMAP algorithm. PSIbase also provides an easy-to-use protein domain assignment module, interaction navigation and visual tools. Users can retrieve possible interaction partners of their proteins of interests if a significant homology assignment is made with their query sequences. AVAILABILITY: http://psimap.org and http://psibase.kaist.ac.kr/

Binding Sites↗

PubMed2005

Distinct gene expression pattern of malignant hematopoietic stem and progenitor cells in polycythemia vera.

Polycythemia vera (PV) is a chronic myeloproliferative disorder with an expansion of multipotent hematopoietic progenitor cells. Although it is known that hematopoietic progenitors in PV are erythropoietin independent and hypersensitive to several cytokines, the molecular oncogenic mechanisms in PV are largely unknown. In this study, we examined gene expression profiles of CD34(+) cells from bone marrow of patients with de novo PV and from healthy volunteers to identify molecular changes associated with the malignant growth of hematopoietic stem and progenitor cells in this myeloproliferative disorder. Using cDNA arrays, we found significant differences (P < .01) in the expression of 107 genes. Proapoptotic genes (CASP2, CASP3, DAPK1, ALG2) were expressed at lower levels in PV-CD34(+) cells, reflecting a lower apoptotic activity. Fibrosis-stimulating growth factors (transforming growth factor beta1, transforming growth factor beta2, bone morphogenetic protein 2, and endothelial growth factor) were expressed at significantly higher levels in PV-CD34(+) cells. Furthermore, PV-CD34(+) cells overexpressed several receptors, protein kinases, and proteasome subunits, which might be targets for directed therapeutic approaches. It is interesting that three retinoid receptors were overexpressed in PV-CD34(+) cells--retinoic acid receptor beta (RARbeta), retinoid X receptor beta (RXRbeta), and cellular retinoic acid binding protein 2 (CRABP2). Using methylcellulose colony-forming assays, we found that the formation of erythroid colonies derived from PV hematopoietic progenitors was inhibited by all-trans-retinoic acid (ATRA), a natural ligand of those receptors, in a dose-dependent manner, showing a maximum inhibition of 89% at 10 microM; the growth of myelomonocytic colonies was not significantly affected. These data suggest that the use of ATRA could be of therapeutic benefit for patients with PV.

Gene Expression↗

PubMed2004

Clinical response to induction chemotherapy predicts local control and long-term survival in multimodal treatment of patients with locally advanced esophageal cancer.

PURPOSE: From 1991 to 1994 we performed a phase II study with intensive preoperative chemoradiation in locally advanced squamous cell carcinoma and adenocarcinoma of the esophagus. We now report on a multivariate analysis of prognostic factors based on the long-term results at a median follow-up of 6.5 years. PATIENTS AND METHODS: Eighty-eight patients were treated. Prognostic factors for overall survival and local tumor control were identified by univariate and multivariate analysis. RESULTS: Median overall survival reached 17 months, and the survival rate at 5 years was 22% (95%-confidence interval: 18-26%). Response to induction chemotherapy was the only independent factor predicting local tumor control and--beside weight loss prior to treatment--it also proved to be an independent prognostic factor for long-term survival. CONCLUSIONS: Intensive chemoradiation followed by surgery seems to be appropriate to improve long-term survival of high-risk patients with locally advanced esophageal cancer. In our trial, local tumor control and prognosis were best correlated with response to induction chemotherapy. These results may help to guide decisions regarding surgery in multimodal treatment of EC. Further efforts are needed to increase the number of treatment responders and to predict tumors not responding to chemo(radio)therapy earlier.

Adenocarcinoma↗

PubMed2004

Using convex hulls to extract interaction interfaces from known structures.

MOTIVATION: Protein interactions provide an important context for the understanding of function. Experimental approaches have been complemented with computational ones, such as PSIMAP, which computes domain-domain interactions for all multi-domain and multi-chain proteins in the Protein Data Bank (PDB). PSIMAP has been used to determine that superfamilies occurring in many species have many interaction partners, to show examples of convergent evolution through shared interaction partners and to uncover complexes in the interaction map. To determine an interaction, the original PSIMAP algorithm checks all residue pairs of any domain pair defined by classification systems such as SCOP. The computation takes several days for the PDB. The computation of PSIMAP has two shortcomings: first, the original PSIMAP algorithm considers only interactions of residue pairs rather than atom pairs losing information for detailed analysis of contact patterns. At the atomic level the original algorithm would take months. Second, with the superlinear growth of PDB, PSIMAP is not sustainable. RESULTS: We address these two shortcomings by developing a family of new algorithms for the computation of domain-domain interactions based on the idea of bounding shapes, which are used to prune the search space. The best of the algorithms improves on the old PSIMAP algorithm by a factor of 60 on the PDB. Additionally, the algorithms allow a distributed computation, which we carry out on a farm of 80 Linux PCs. Overall, the new algorithms reduce the computation at atomic level from months to 20 min. The combination of pruning and distribution makes the new algorithm scalable and sustainable even with the superlinear growth in PDB.

Algorithms↗

PubMed2003

Visualisation and graph-theoretic analysis of a large-scale protein structural interactome.

BACKGROUND: Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. RESULTS: We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. CONCLUSIONS: Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.

Archaeal Proteins↗