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Signaling by Toll-Like Receptors and the Interleukin-1 Receptor (IL1-R) involves intracellular binding of MyD88, followed by assembly of IL1-R Associated Kinases (IRAKs) into the so-called Myddosome. Using NMR, Nechama et al. determined the structure of the IRAK-M death domain monomer (PDBid: 5UKE). With this structure, they performed a docking study to model the location of IRAK-M in the Myddosome. Based on this, they present a molecular basis for selectivity of IRAK-M towards IRAK1 over IRAK2 binding. When we attempted to use 5UKE as a homology modeling template, we noticed that our 5UKE-based models had structural issues, such as disallowed torsion angles and solvent exposed tryptophans. We therefore analyzed the NMR ensemble of 5UKE using structure validation tools and we compared 5UKE with homologous high-resolution X-ray structures. We identified several structural anomalies in 5UKE, including packing issues, frayed helices and improbable side chain conformations. We used Yasara to build a homology model, based on two high resolution death domain crystal structures, as an alternative model for the IRAK-M death domain (atomic coordinates, modeling details and validation are available at https://swift.cmbi.umcn.nl/gv/service/5uke/). Our model agrees better with known death domain structure information than 5UKE and also with the chemical shift data that was deposited for 5UKE.

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Proteins are key to many different processes in and around living cells, they are the molecular mechanisms that facilitate life. Therefore, protein function and structure have been of great interest to researchers over the past decades. A better understanding of how proteins work is important, as it will help us understand the various diseases caused by their malfunction and help us apply proteins in various applications, such as industrial processes. The research on proteins has resulted in an ever-increasing amount of data related to proteins.Protein information systems were developed to make sense out of all the data available for specific protein classes. The work described in this thesis makes use of the 3DM platform to store and order the enormous amount of protein data that is nowadays available. The 3DM platform integrates heterogeneous datasets for complete protein superfamilies to generate molecular class specific information systems (3DM systems).The main objective of this thesis is to facilitate a better understanding of protein function through data integration- and analysis-tools to support both DNA diagnostics and protein engineering efforts. To that end, chapter 2 and chapter 3 focus on the collection and integration of mutational data from scientific literature, followed by protein superfamily analysis to reveal predictive patterns. In chapter 4, mutational data mined for whole families are combined with a superfamily alignment analysis to assign function to networks of residues that appear to have co-evolved. And in chapter 5, the data of a 3DM system is used to train a machine learning model for the prediction of pathogenicity of novel genetic variants.In chapter 2 a method for the automated collection and integration of mutation data from scientific literature is described. This text-mining tool, Mutator, was designed to automatically identify and retrieve relevant literature for a complete protein family.Mutator was tested on the alpha-amylase p

Contains fulltext : 244283.pdf (Publisher’s version ) (Open Access), Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein's infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold (apparently without lowering performance of prediction methods); user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and secondary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. PredictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings.

Radboud University, 25 augustus 2021, Promotores : Veltman, J.A., Vriend, G. Co-promotor : Gilissen, C.F.H.A., Contains fulltext : 235388.pdf (Publisher’s version ) (Open Access)

Item does not contain fulltext, G protein-coupled receptors (GPCRs) participate in most physiological processes and are important drug targets in many therapeutic areas. Recently, many GPCR X-ray structures became available, facilitating detailed studies of their sequence-structure-mobility-function relations. We show that the functional role of many conserved GPCR sequence motifs is to create weak spots in the transmembrane helices that provide the structural plasticity necessary for ligand binding and signaling. Different receptor families use different conserved sequence motifs to obtain similar helix irregularities that allow for the same motions upon GPCR activation. These conserved motions come together to facilitate the timely release of the conserved sodium ion to the cytosol. Most GPCR crystal structures could be determined only after stabilization of the transmembrane helices by mutations that remove weak spots. These mutations often lead to diminished binding of agonists, but not antagonists, which logically agrees with the fact that large helix rearrangements occur only upon agonist binding. Upon activation, six of the seven TM helices in GPCRs undergo helix motions and/or deformations facilitated by weak spots in these helices. The location of these weak spots is much more conserved than the sequence motifs that cause them. Knowledge about these weak spots helps understand the activation process of GPCRs and thus helps design medicines.

Contains fulltext : 220847.pdf (publisher's version ) (Open Access), When Oleg Ptitsyn and his group published the first secondary structure prediction for a protein sequence, they started a research field that is still active today. Oleg Ptitsyn combined fundamental rules of physics with human understanding of protein structures. Most followers in this field, however, use machine learning methods and aim at the highest (average) percentage correctly predicted residues in a set of proteins that were not used to train the prediction method. We show that one single method is unlikely to predict the secondary structure of all protein sequences, with the exception, perhaps, of future deep learning methods based on very large neural networks, and we suggest that some concepts pioneered by Oleg Ptitsyn and his group in the 70s of the previous century likely are today's best way forward in the protein secondary structure prediction field.

Contains fulltext : 218173.pdf (Publisher’s version ) (Open Access), We describe a series of databases and tools that directly or indirectly support biomedical research on macromolecules, with focus on their applicability in protein structure bioinformatics research. DSSP, that determines secondary structures of proteins, has been updated to work well with extremely large structures in multiple formats. The PDBREPORT database that lists anomalies in protein structures has been remade to remove many small problems. These reports are now available as PDF-formatted files with a computer-readable summary. The VASE software has been added to analyze and visualize HSSP multiple sequence alignments for protein structures. The Lists collection of databases has been extended with a series of databases, most noticeably with a database that gives each protein structure a grade for usefulness in protein structure bioinformatics projects. The PDB-REDO collection of reanalyzed and re-refined protein structures that were solved by X-ray crystallography has been improved by dealing better with sugar residues and with hydrogen bonds, and adding many missing surface loops. All academic software underlying these protein structure bioinformatics applications and databases are now publicly accessible, either directly from the authors or from the GitHub software repository.

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Contains fulltext : 208582.pdf (publisher's version ) (Open Access), Bioinformaticians and biologists rely increasingly upon workflows for the flexible utilization of the many life science tools that are needed to optimally convert data into knowledge. We outline a pan-European enterprise to provide a catalogue ( https://bio.tools ) of tools and databases that can be used in these workflows. bio.tools not only lists where to find resources, but also provides a wide variety of practical information.

Contains fulltext : 207049.pdf (publisher's version ) (Open Access)

Item does not contain fulltext, Engineering surface loops is a sub-topic of protein engineering that is used routinely in many research fields in academia and industry alike. We provide some tools that search in the PDB for loops satisfying a wide variety of constraints. We illustrate the usefulness of these tools by applying them to a series of recently published studies that included loop engineering or loop modelling. LoopFinder finds loops that fit between two anchor stretches of typically 2, 3, or 4amino acids each. ProDA find loops of a given length with predefined secondary structure, residue types, hydrophobicity, etc. WHAT IF has gotten a series of new options to scan the whole PDB for loops combining the LoopFinder and ProDA techniques. The open nature of these tools will allow bioinformaticians in this field to easily design their own loop modelling software around our tools. AVAILABILITY AND IMPLEMENTATION: LoopFinder is a stand-alone Fortran program that is likely to compile and run on every computer. The LoopFinder source code, data files, and documentation are freely available from swift.cmbi.ru.nl/gv/loops/. ProDA is free to all users. There is no login requirement. It is available at: http://bioinf.modares.ac.ir/software/linda/. WHAT IF is shareware that is available from https://swift.cmbi.ru.nl/whatif/.

Contains fulltext : 190646.pdf (Publisher’s version ) (Open Access), BACKGROUND: Disrupting the costimulatory CD40-CD40L dyad reduces atherosclerosis, but can result in immune suppression. The authors recently identified small molecule inhibitors that block the interaction between CD40 and tumor necrosis factor receptor-associated factor (TRAF) 6 (TRAF-STOPs), while leaving CD40-TRAF2/3/5 interactions intact, thereby preserving CD40-mediated immunity. OBJECTIVES: This study evaluates the potential of TRAF-STOP treatment in atherosclerosis. METHODS: The effects of TRAF-STOPs on atherosclerosis were investigated in apolipoprotein E deficient (Apoe(-/-)) mice. Recombinant high-density lipoprotein (rHDL) nanoparticles were used to target TRAF-STOPs to macrophages. RESULTS: TRAF-STOP treatment of young Apoe(-/-) mice reduced atherosclerosis by reducing CD40 and integrin expression in classical monocytes, thereby hampering monocyte recruitment. When Apoe(-/-) mice with established atherosclerosis were treated with TRAF-STOPs, plaque progression was halted, and plaques contained an increase in collagen, developed small necrotic cores, and contained only a few immune cells. TRAF-STOP treatment did not impair "classical" immune pathways of CD40, including T-cell proliferation and costimulation, Ig isotype switching, or germinal center formation, but reduced CD40 and beta2-integrin expression in inflammatory monocytes. In vitro testing and transcriptional profiling showed that TRAF-STOPs are effective in reducing macrophage migration and activation, which could be attributed to reduced phosphorylation of signaling intermediates of the canonical NF-kappaB pathway. To target TRAF-STOPs specifically to macrophages, TRAF-STOP 6877002 was incorporated into rHDL nanoparticles. Six weeks of rHDL-6877002 treatment attenuated the initiation of atherosclerosis in Apoe(-/-) mice. CONCLUSIONS: TRAF-STOPs can overcome the current limitations of long-term CD40 inhibition in atherosclerosis and have the potential to become a future therapeutic for atheroscle

Contains fulltext : 190629.pdf (Publisher’s version ) (Open Access), eScience technologies are needed to process the information available in many heterogeneous types of protein-ligand interaction data and to capture these data into models that enable the design of efficacious and safe medicines. Here we present scientific KNIME tools and workflows that enable the integration of chemical, pharmacological, and structural information for: i) structure-based bioactivity data mapping, ii) structure-based identification of scaffold replacement strategies for ligand design, iii) ligand-based target prediction, iv) protein sequence-based binding site identification and ligand repurposing, and v) structure-based pharmacophore comparison for ligand repurposing across protein families. The modular setup of the workflows and the use of well-established standards allows the re-use of these protocols and facilitates the design of customized computer-aided drug discovery workflows.

Contains fulltext : 193176.pdf (publisher's version ) (Open Access)

Contains fulltext : 198234.pdf (Publisher’s version ) (Closed access)

Contains fulltext : 176900.pdf (publisher's version ) (Closed access), The NewProt protein engineering portal is a one-stop-shop for in silico protein engineering. It gives access to a large number of servers that compute a wide variety of protein structure characteristics supporting work on the modification of proteins through the introduction of (multiple) point mutations. The results can be inspected through multiple visualizers. The HOPE software is included to indicate mutations with possible undesired side effects. The Hotspot Wizard software is embedded for the design of mutations that modify a proteins' activity, specificity, or stability. The NewProt portal is freely accessible at http://newprot.cmbi.umcn.nl/ and http://newprot.fluidops.net/.

Item does not contain fulltext, Motivation: The recently developed direct coupling analysis (DCA) method has greatly improved the accuracy with which residue-residue contacts can be predicted from multiple sequence alignments. Contact prediction accuracy, though, is still often not sufficient for complete ab initio protein structure prediction. DCA can, however, support protein structure studies in several ways. Results: We show that DCA can select the better structure from among properly folded and misfolded variants. This idea was tested by comparing obsolete PDB files with their more correctly folded successors and by the comparison of structures with deliberately misfolded decoy models from the Decoys 'R' Us database. The DCA method systematically predicts more contacts for properly folded structures than for misfolded ones. The method works much better for X-ray structures than for NMR structures. Availability and Implementation: All data are available from http://comprec-lin.iiar.pwr.edu.pl/dcaVSmisfolds/ and http://swift.cmbi.ru.nl/dcaVSmisfolds/ . Contact: malgorzata.kotulska@pwr.edu.pl . Supplementary information: Supplementary data are available at Bioinformatics online.

Contains fulltext : 180449.pdf (publisher's version ) (Open Access)

Contains fulltext : 176925.pdf (publisher's version ) (Closed access), Haploinsufficiency (HI) is the best characterized mechanism through which dominant mutations exert their effect and cause disease. Non-haploinsufficiency (NHI) mechanisms, such as gain-of-function and dominant-negative mechanisms, are often characterized by the spatial clustering of mutations, thereby affecting only particular regions or base pairs of a gene. Variants leading to haploinsufficency might occasionally cluster as well, for example in critical domains, but such clustering is on the whole less pronounced with mutations often spread throughout the gene. Here we exploit this property and develop a method to specifically identify genes with significant spatial clustering patterns of de novo mutations in large cohorts. We apply our method to a dataset of 4,061 de novo missense mutations from published exome studies of trios with intellectual disability and developmental disorders (ID/DD) and successfully identify 15 genes with clustering mutations, including 12 genes for which mutations are known to cause neurodevelopmental disorders. For 11 out of these 12, NHI mutation mechanisms have been reported. Additionally, we identify three candidate ID/DD-associated genes of which two have an established role in neuronal processes. We further observe a higher intolerance to normal genetic variation of the identified genes compared to known genes for which mutations lead to HI. Finally, 3D modeling of these mutations on their protein structures shows that 81% of the observed mutations are unlikely to affect the overall structural integrity and that they therefore most likely act through a mechanism other than HI.

Contains fulltext : 169642.pdf (Publisher’s version ) (Open Access), 3D-e-Chem-VM is an open source, freely available Virtual Machine ( http://3d-e-chem.github.io/3D-e-Chem-VM/ ) that integrates cheminformatics and bioinformatics tools for the analysis of protein-ligand interaction data. 3D-e-Chem-VM consists of software libraries, and database and workflow tools that can analyze and combine small molecule and protein structural information in a graphical programming environment. New chemical and biological data analytics tools and workflows have been developed for the efficient exploitation of structural and pharmacological protein-ligand interaction data from proteomewide databases (e.g., ChEMBLdb and PDB), as well as customized information systems focused on, e.g., G protein-coupled receptors (GPCRdb) and protein kinases (KLIFS). The integrated structural cheminformatics research infrastructure compiled in the 3D-e-Chem-VM enables the design of new approaches in virtual ligand screening (Chemdb4VS), ligand-based metabolism prediction (SyGMa), and structure-based protein binding site comparison and bioisosteric replacement for ligand design (KRIPOdb).