Entropy and Variability: A Second Opinion by Deep Learning

BACKGROUND

Analysis of the distribution of amino acid types found at equivalent positions in multiple sequence alignments has found applications in human genetics, protein engineering, drug design, protein structure prediction, and many other fields. These analyses tend to revolve around measures of the distribution of the twenty amino acid types found at evolutionary equivalent positions: the columns in multiple sequence alignments. Commonly used measures are variability, average hydrophobicity, or Shannon entropy. One of these techniques, called entropy-variability analysis, as the name already suggests, reduces the distribution of observed residue types in one column to two numbers: the Shannon entropy and the variability as defined by the number of residue types observed.

RESULTS

We applied a deep learning, unsupervised feature extraction method to analyse the multiple sequence alignments of all human proteins. An auto-encoder neural architecture was trained on 27,835 multiple sequence alignments for human proteins to obtain the two features that best describe the seven million variability patterns. These two unsupervised learned features strongly resemble entropy and variability, indicating that these are the projections that retain most information when reducing the dimensionality of the information hidden in columns in multiple sequence alignments.

Structural anomalies in a published NMR-derived structure of IRAK-M

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.

Motions around conserved helical weak spots facilitate GPCR activation

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.

The Future of Protein Secondary Structure Prediction Was Invented by Oleg Ptitsyn

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.

Citius, Altius, Fortius

2020 is a leap year. That means that we have one day extra and, if the Olympic games had survived the corona crisis, we would all be watching television and ask the eternal question whether Olympic records will for ever be broken and broken again, or that there are limits to human biology1 . In this article we ask the same question, but rather than discussing aspects of Citius, Altius, and Fortius of athletes we will discuss them for macromolecules. It is remarkable how many parallels can be found between Olympic records in these two seemingly different worlds. People involved in structure validation and re-refinement try to make us believe that most aspects of macromolecular structures can be caught by a number that has some constant value with little variation around it. We will show here that the PDB2 databank proves this idea to be wrong. In the protein structure world, it holds for many that "participating is more important than winning", but some, fortunately, still go for the record books.

Facilities that make the PDB data collection more powerful

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.

Bio-knowledge-based filters improve residue-residue contact prediction accuracy

Motivation

Residue-residue contact prediction through direct coupling analysis has reached impressive accuracy, but yet higher accuracy will be needed to allow for routine modelling of protein structures. One way to improve the prediction accuracy is to filter predicted contacts using knowledge about the particular protein of interest or knowledge about protein structures in general.

Results

We focus on the latter and discuss a set of filters that can be used to remove false positive contact predictions. Each filter depends on one or a few cut-off parameters for which the filter performance was investigated. Combining all filters while using default parameters resulted for a test set of 851 protein domains in the removal of 29% of the predictions of which 92% were indeed false positives.

Availability and implementation

All data and scripts are available at http://comprec-lin.iiar.pwr.edu.pl/FPfilter/.

Supplementary information

Supplementary data are available at Bioinformatics online.

G protein-coupled receptors of class A harness the energy of membrane potential to increase their sensitivity and selectivity

The human genome contains about 700 genes of G protein-coupled receptors (GPCRs) of class A; these seven-helical membrane proteins are the targets of almost half of all known drugs. In the middle of the helix bundle, crystal structures reveal a highly conserved sodium-binding site, which is connected with the extracellular side by a water-filled tunnel. This binding site contains a sodium ion in those GPCRs that are crystallized in their inactive conformations but does not in those GPCRs that are trapped in agonist-bound active conformations. The escape route of the sodium ion upon the inactive-to-active transition and its very direction have until now remained obscure. Here, by modeling the available experimental data, we show that the sodium gradient over the cell membrane increases the sensitivity of GPCRs if their activation is thermodynamically coupled to the sodium ion translocation into the cytoplasm but decreases it if the sodium ion retreats into the extracellular space upon receptor activation. The model quantitatively describes the available data on both activation and suppression of distinct GPCRs by membrane voltage. The model also predicts selective amplification of the signal from (endogenous) agonists if only they, but not their (partial) analogs, induce sodium translocation. Comparative structure and sequence analyses of sodium-binding GPCRs indicate a key role for the conserved leucine residue in the second transmembrane helix (Leu2.46) in coupling sodium translocation to receptor activation. Hence, class A GPCRs appear to harness the energy of the transmembrane sodium potential to increase their sensitivity and selectivity.

The bio.tools registry of software tools and data resources for the life sciences

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.

Targeting CD40-Induced TRAF6 Signaling in Macrophages Reduces Atherosclerosis

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 β2-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-κB 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 atherosclerosis.

Loop modelling 1.0

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 4 amino 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/.

3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery

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.

Forecasting residue-residue contact prediction accuracy

Motivation

Apart from meta-predictors, most of today's methods for residue-residue contact prediction are based entirely on Direct Coupling Analysis (DCA) of correlated mutations in multiple sequence alignments (MSAs). These methods are on average ∼40% correct for the 100 strongest predicted contacts in each protein. The end-user who works on a single protein of interest will not know if predictions are either much more or much less correct than 40%, which is especially a problem if contacts are predicted to steer experimental research on that protein.

Results

We designed a regression model that forecasts the accuracy of residue-residue contact prediction for individual proteins with an average error of 7 percentage points. Contacts were predicted with two DCA methods (gplmDCA and PSICOV). The models were built on parameters that describe the MSA, the predicted secondary structure, the predicted solvent accessibility and the contact prediction scores for the target protein. Results show that our models can be also applied to the meta-methods, which was tested on RaptorX.

Availability and implementation

All data and scripts are available from http://comprec-lin.iiar.pwr.edu.pl/dcaQ/.

Contact

malgorzata.kotulska@pwr.edu.pl.

Supplementary information

Supplementary data are available at Bioinformatics online.

Molden 2.0: quantum chemistry meets proteins

Since the first distribution of Molden in 1995 and the publication of the first article about this software in 2000 work on Molden has continued relentlessly. A few of the many improved or fully novel features such as improved and broadened support for quantum chemistry calculations, preparation of ligands for use in drug design related softwares, and working with proteins for the purpose of ligand docking.

Aggregation of population-based genetic variation over protein domain homologues and its potential use in genetic diagnostics

Whole exomes of patients with a genetic disorder are nowadays routinely sequenced but interpretation of the identified genetic variants remains a major challenge. The increased availability of population‐based human genetic variation has given rise to measures of genetic tolerance that have been used, for example, to predict disease‐causing genes in neurodevelopmental disorders. Here, we investigated whether combining variant information from homologous protein domains can improve variant interpretation. For this purpose, we developed a framework that maps population variation and known pathogenic mutations onto 2,750 “meta‐domains.” These meta‐domains consist of 30,853 homologous Pfam protein domain instances that cover 36% of all human protein coding sequences. We find that genetic tolerance is consistent across protein domain homologues, and that patterns of genetic tolerance faithfully mimic patterns of evolutionary conservation. Furthermore, for a significant fraction (68%) of the meta‐domains high‐frequency population variation re‐occurs at the same positions across domain homologues more often than expected. In addition, we observe that the presence of pathogenic missense variants at an aligned homologous domain position is often paired with the absence of population variation and vice versa. The use of these meta‐domains can improve the interpretation of genetic variation.

Outer membrane phospholipase A's roles in Helicobacter pylori acid adaptation

Background

The pH of the human gastric mucosa varies around 2.5 so that only bacteria with strong acidic stress tolerance can colonize it. The ulcer causing Helicobacter pylori thrives in the gastric mucosa. We analyse the roles of the key outer membrane protein OMPLA in its roles in acid tolerance.

Results

The homology model of Helicobacter pylori outer membrane phospholipase A (OMPLA) reveals a twelve stranded β-barrel with a pore that allows molecules to pass with a diameter up to 4 Å. Structure based multiple sequence alignments revealed the functional roles of many amino acids, and led to the suggestion that OMPLA has multiple functions. Besides its role as phospholipase it lets urea enter and ammonium exit the periplasm. Combined with an extensive literature study, our work leads to a comprehensive model for H. pylori’s acid tolerance. This model is based on the conversion of urea into ammonium, and it includes multiple roles for OMPLA and involves two hitherto little studied membrane channels in the OMPLA operon.

Conclusion

The three-dimensional model of OMPLA predicts a transmembrane pore that can aid H. pylori’s acid tolerance through urea influx and ammonium efflux. After urea passes through OMPLA into the periplasm, it passes through the pH-gated inner membrane channel UreI into the cytoplasm where urease hydrolyses it into NH₃ and CO₂. Most of the NH₃ becomes NH₄⁺ that is likely to need an inner membrane channel to reach the periplasm. Two genes that are co-regulated with OMPLA in gastric Helicobacter operons could aid this transport. The NH₄⁺ that might leave the cell through the OMPLA pore has been implicated in H. pylor’s pathogenesis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13099-017-0184-y) contains supplementary material, which is available to authorized users.

CorNet: Assigning function to networks of co-evolving residues by automated literature mining

CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity.

Novel IRF6 Mutations Detected in Orofacial Cleft Patients by Targeted Massively Parallel Sequencing

Common variants in interferon regulatory factor 6 ( IRF6) have been associated with nonsyndromic cleft lip with or without cleft palate (NSCL/P) as well as with tooth agenesis (TA). These variants contribute a small risk towards the 2 congenital conditions and explain only a small percentage of heritability. On the other hand, many IRF6 mutations are known to be a monogenic cause of disease for syndromic orofacial clefting (OFC). We hypothesize that IRF6 mutations in some rare instances could also cause nonsyndromic OFC. To find novel rare variants in IRF6 responsible for nonsyndromic OFC and TA, we performed targeted multiplex sequencing using molecular inversion probes (MIPs) in 1,072 OFC patients, 67 TA patients, and 706 controls. We identified 3 potentially pathogenic de novo mutations in OFC patients. In addition, 3 rare missense variants were identified, for which pathogenicity could not unequivocally be shown, as all variants were either inherited from an unaffected parent or the parental DNA was not available. Retrospective investigation of the patients with these variants revealed the presence of lip pits in one of the patients with a de novo mutation suggesting a Van der Woude syndrome (VWS) phenotype, whereas, in other patients, no lip pits were identified.

Validation and correction of Zn-CysxHisy complexes

Many crystal structures in the Protein Data Bank contain zinc ions in a geometrically distorted tetrahedral complex with four Cys and/or His ligands. A method is presented to automatically validate and correct these zinc complexes. Analysis of the corrected zinc complexes shows that the average Zn-Cys distances and Cys-Zn-Cys angles are a function of the number of cysteines and histidines involved. The observed trends can be used to develop more context-sensitive targets for model validation and refinement.

GPCRdb: the G protein-coupled receptor database - an introduction

GPCRs make up the largest family of human membrane proteins and of drug targets. Recent advances in GPCR pharmacology and crystallography have shed new light on signal transduction, allosteric modulation and biased signalling, translating into new mechanisms and principles for drug design. The GPCR database, GPCRdb, has served the community for over 20 years and has recently been extended to include a more multidisciplinary audience. This review is intended to introduce new users to the services in GPCRdb, which meets three overall purposes: firstly, to provide reference data in an integrated, annotated and structured fashion, with a focus on sequences, structures, single‐point mutations and ligand interactions. Secondly, to equip the community with a suite of web tools for swift analysis of structures, sequence similarities, receptor relationships, and ligand target profiles. Thirdly, to facilitate dissemination through interactive diagrams of, for example, receptor residue topologies, phylogenetic relationships and crystal structure statistics. Herein, these services are described for the first time; visitors and guides are provided with good practices for their utilization. Finally, we describe complementary databases cross‐referenced by GPCRdb and web servers with corresponding functionality.

The role of the dopamine D1 receptor in social cognition: studies using a novel genetic rat model

Social cognition is an endophenotype that is impaired in schizophrenia and several other (comorbid) psychiatric disorders. One of the modulators of social cognition is dopamine, but its role is not clear. The effects of dopamine are mediated through dopamine receptors, including the dopamine D1 receptor (Drd1). Because current Drd1 receptor agonists are not Drd1 selective, pharmacological tools are not sufficient to delineate the role of the Drd1. Here, we describe a novel rat model with a genetic mutation in Drd1 in which we measured basic behavioural phenotypes and social cognition. The I116S mutation was predicted to render the receptor less stable. In line with this computational prediction, this Drd1 mutation led to a decreased transmembrane insertion of Drd1, whereas Drd1 expression, as measured by Drd1 mRNA levels, remained unaffected. Owing to decreased transmembrane Drd1 insertion, the mutant rats displayed normal basic motoric and neurological parameters, as well as locomotor activity and anxiety-like behaviour. However, measures of social cognition like social interaction, scent marking, pup ultrasonic vocalizations and sociability, were strongly reduced in the mutant rats. This profile of the Drd1 mutant rat offers the field of neuroscience a novel genetic rat model to study a series of psychiatric disorders including schizophrenia, autism, depression, bipolar disorder and drug addiction.

New Biological Insights from Better Structure Models

Structure validation is a key component of all steps in the structure determination process, from structure building, refinement, deposition, and evaluation all the way to post-deposition optimisation of structures in the Protein Data Bank (PDB) by re-refinement and re-building. Today, many aspects of protein structures are understood better than 10years ago, and combined with improved software and more computing power, the automated PDB_REDO procedure can significantly improve about 85% of all X-ray structures ever deposited in the PDB. We review structure validation, structure improvement, and a series of validation resources and facilities that give access to improved PDB files and to reports on the quality of the original and the improved structures. Post-deposition optimisation generally leads to improved protein structures and a series of examples will illustrate how that, in turn, leads to improved or even novel biological insights.

GPCRdb: an information system for G protein-coupled receptors

Recent developments in G protein-coupled receptor (GPCR) structural biology and pharmacology have greatly enhanced our knowledge of receptor structure-function relations, and have helped improve the scientific foundation for drug design studies. The GPCR database, GPCRdb, serves a dual role in disseminating and enabling new scientific developments by providing reference data, analysis tools and interactive diagrams. This paper highlights new features in the fifth major GPCRdb release: (i) GPCR crystal structure browsing, superposition and display of ligand interactions; (ii) direct deposition by users of point mutations and their effects on ligand binding; (iii) refined snake and helix box residue diagram looks; and (iii) phylogenetic trees with receptor classification colour schemes. Under the hood, the entire GPCRdb front- and back-ends have been re-coded within one infrastructure, ensuring a smooth browsing experience and development. GPCRdb is available at http://www.gpcrdb.org/ and it's open source code at https://bitbucket.org/gpcr/protwis.

KMAD: knowledge-based multiple sequence alignment for intrinsically disordered proteins

Summary: Intrinsically disordered proteins (IDPs) lack tertiary structure and thus differ from globular proteins in terms of their sequence–structure–function relations. IDPs have lower sequence conservation, different types of active sites and a different distribution of functionally important regions, which altogether make their multiple sequence alignment (MSA) difficult. The KMAD MSA software has been written specifically for the alignment and annotation of IDPs. It augments the substitution matrix with knowledge about post-translational modifications, functional domains and short linear motifs.

Results: MSAs produced with KMAD describe well-conserved features among IDPs, tend to agree well with biological intuition, and are a good basis for designing new experiments to shed light on this large, understudied class of proteins.

Availability and implementation: KMAD web server is accessible at http://www.cmbi.ru.nl/kmad/. A standalone version is freely available.

Contact: vriend@cmbi.ru.nl

Tools and data services registry: a community effort to document bioinformatics resources

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.

Here we present a community-driven curation effort, supported by ELIXIR—the European infrastructure for biological information—that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.

As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.

Stabilization of protein-protein interaction complexes through small molecules

Most of the small molecules that have been identified thus far to modulate protein-protein interactions (PPIs) are inhibitors. Another promising way to interfere with PPI-associated biological processes is to promote PPI stabilization. Even though PPI stabilizers are still scarce, stabilization of PPIs by small molecules is gaining momentum and offers new pharmacological options. Therefore, we have performed a literature survey of PPI stabilization using small molecules. From this, we propose a classification of PPI stabilizers based on their binding mode and the architecture of the complex to facilitate the structure-based design of stabilizers.

iPPI-DB: an online database of modulators of protein-protein interactions

In order to boost the identification of low-molecular-weight drugs on protein–protein interactions (PPI), it is essential to properly collect and annotate experimental data about successful examples. This provides the scientific community with the necessary information to derive trends about privileged physicochemical properties and chemotypes that maximize the likelihood of promoting a given chemical probe to the most advanced stages of development. To this end we have developed iPPI-DB (freely accessible at http://www.ippidb.cdithem.fr), a database that contains the structure, some physicochemical characteristics, the pharmacological data and the profile of the PPI targets of several hundreds modulators of protein–protein interactions. iPPI-DB is accessible through a web application and can be queried according to two general approaches: using physicochemical/pharmacological criteria; or by chemical similarity to a user-defined structure input. In both cases the results are displayed as a sortable and exportable datasheet with links to external databases such as Uniprot, PubMed. Furthermore each compound in the table has a link to an individual ID card that contains its physicochemical and pharmacological profile derived from iPPI-DB data. This includes information about its binding data, ligand and lipophilic efficiencies, location in the PPI chemical space, and importantly similarity with known drugs, and links to external databases like PubChem, and ChEMBL.

Detection of trans-cis flips and peptide-plane flips in protein structures

A method is presented to detect peptide bonds that need either a trans–cis flip or a peptide-plane flip.

A coordinate-based method is presented to detect peptide bonds that need correction either by a peptide-plane flip or by a trans–cis inversion of the peptide bond. When applied to the whole Protein Data Bank, the method predicts 4617 trans–cis flips and many thousands of hitherto unknown peptide-plane flips. A few examples are highlighted for which a correction of the peptide-plane geometry leads to a correction of the understanding of the structure–function relation. All data, including 1088 manually validated cases, are freely available and the method is available from a web server, a web-service interface and through WHAT_CHECK.

New ways to boost molecular dynamics simulations

We describe a set of algorithms that allow to simulate dihydrofolate reductase (DHFR, a common benchmark) with the AMBER all-atom force field at 160 nanoseconds/day on a single Intel Core i7 5960X CPU (no graphics processing unit (GPU), 23,786 atoms, particle mesh Ewald (PME), 8.0 Å cutoff, correct atom masses, reproducible trajectory, CPU with 3.6 GHz, no turbo boost, 8 AVX registers). The new features include a mixed multiple time-step algorithm (reaching 5 fs), a tuned version of LINCS to constrain bond angles, the fusion of pair list creation and force calculation, pressure coupling with a "densostat," and exploitation of new CPU instruction sets like AVX2. The impact of Intel's new transactional memory, atomic instructions, and sloppy pair lists is also analyzed. The algorithms map well to GPUs and can automatically handle most Protein Data Bank (PDB) files including ligands. An implementation is available as part of the YASARA molecular modeling and simulation program from www.YASARA.org.

Key challenges for the creation and maintenance of specialist protein resources

As the volume of data relating to proteins increases, researchers rely more and more on the analysis of published data, thus increasing the importance of good access to these data that vary from the supplemental material of individual articles, all the way to major reference databases with professional staff and long-term funding. Specialist protein resources fill an important middle ground, providing interactive web interfaces to their databases for a focused topic or family of proteins, using specialized approaches that are not feasible in the major reference databases. Many are labors of love, run by a single lab with little or no dedicated funding and there are many challenges to building and maintaining them. This perspective arose from a meeting of several specialist protein resources and major reference databases held at the Wellcome Trust Genome Campus (Cambridge, UK) on August 11 and 12, 2014. During this meeting some common key challenges involved in creating and maintaining such resources were discussed, along with various approaches to address them. In laying out these challenges, we aim to inform users about how these issues impact our resources and illustrate ways in which our working together could enhance their accuracy, currency, and overall value.

Quantum chemical study of the isomerization of 24-methylenecycloartanol, a potential marker of olive oil refining

Quantum chemical calculations on the isomerization of 24-methylenecycloartanol are described. An energetically viable mechanism, with a rate-determining protonation step, is proposed. This rearrangement may find applicability in tests for determining if an olive oil has been refined.

The effect of novel mutations on the structure and enzymatic activity of unconventional myosins associated with autosomal dominant non-syndromic hearing loss

Mutations in five unconventional myosin genes have been associated with genetic hearing loss (HL). These genes encode the motor proteins myosin IA, IIIA, VI, VIIA and XVA. To date, most mutations in myosin genes have been found in the Caucasian population. In addition, only a few functional studies have been performed on the previously reported myosin mutations. We performed screening and functional studies for mutations in the MYO1A and MYO6 genes in Korean cases of autosomal dominant non-syndromic HL. We identified four novel heterozygous mutations in MYO6. Three mutations (p.R825X, p.R991X and Q918fsX941) produce a premature truncation of the myosin VI protein. Another mutation, p.R205Q, was associated with diminished actin-activated ATPase activity and actin gliding velocity of myosin VI in an in vitro analysis. This finding is consistent with the results of protein modelling studies and corroborates the pathogenicity of this mutation in the MYO6 gene. One missense variant, p.R544W, was found in the MYO1A gene, and in silico analysis suggested that this variant has deleterious effects on protein function. This finding is consistent with the results of protein modelling studies and corroborates the pathogenic effect of this mutation in the MYO6 gene.

Discovery of small molecule CD40-TRAF6 inhibitors

The CD154-CD40 receptor complex plays a pivotal role in several inflammatory pathways. Attempts to inhibit the formation of this complex have resulted in systemic side effects. Downstream inhibition of the CD40 signaling pathway therefore seems a better way to ameliorate inflammatory disease. To relay a signal, the CD40 receptor recruits adapter proteins called tumor necrosis factor receptor-associated factors (TRAFs). CD40-TRAF6 interactions are known to play an essential role in several inflammatory diseases. We used in silico, in vitro, and in vivo experiments to identify and characterize compounds that block CD40-TRAF6 interactions. We present in detail our drug docking and optimization pipeline and show how we used it to find lead compounds that reduce inflammation in models of peritonitis and sepsis. These compounds appear to be good leads for drug development, given the observed absence of side effects and their demonstrated efficacy for peritonitis and sepsis in mouse models.

A series of PDB-related databanks for everyday needs

We present a series of databanks (http://swift.cmbi.ru.nl/gv/facilities/) that hold information that is computationally derived from Protein Data Bank (PDB) entries and that might augment macromolecular structure studies. These derived databanks run parallel to the PDB, i.e. they have one entry per PDB entry. Several of the well-established databanks such as HSSP, PDBREPORT and PDB_REDO have been updated and/or improved. The software that creates the DSSP databank, for example, has been rewritten to better cope with π-helices. A large number of databanks have been added to aid computational structural biology; some examples are lists of residues that make crystal contacts, lists of contacting residues using a series of contact definitions or lists of residue accessibilities. PDB files are not the optimal presentation of the underlying data for many studies. We therefore made a series of databanks that hold PDB files in an easier to use or more consistent representation. The BDB databank holds X-ray PDB files with consistently represented B-factors. We also added several visualization tools to aid the users of our databanks.

Visually impaired researchers get their hands on quantum chemistry: application to a computational study on the isomerization of a sterol

In molecular sciences, articles tend to revolve around 2D representations of 3D molecules, and sighted scientists often resort to 3D virtual reality software to study these molecules in detail. Blind and visually impaired (BVI) molecular scientists have access to a series of audio devices that can help them read the text in articles and work with computers. Reading articles published in this journal, though, is nearly impossible for them because they need to generate mental 3D images of molecules, but the article-reading software cannot do that for them. We have previously designed AsteriX, a web server that fully automatically decomposes articles, detects 2D plots of low molecular weight molecules, removes meta data and annotations from these plots, and converts them into 3D atomic coordinates. AsteriX-BVI goes one step further and converts the 3D representation into a 3D printable, haptic-enhanced format that includes Braille annotations. These Braille-annotated physical 3D models allow BVI scientists to generate a complete mental model of the molecule. AsteriX-BVI uses Molden to convert the meta data of quantum chemistry experiments into BVI friendly formats so that the entire line of scientific information that sighted people take for granted-from published articles, via printed results of computational chemistry experiments, to 3D models-is now available to BVI scientists too. The possibilities offered by AsteriX-BVI are illustrated by a project on the isomerization of a sterol, executed by the blind co-author of this article (HBW).

YASARA View - molecular graphics for all devices - from smartphones to workstations

Summary: Today's graphics processing units (GPUs) compose the scene from individual triangles. As about 320 triangles are needed to approximate a single sphere—an atom—in a convincing way, visualizing larger proteins with atomic details requires tens of millions of triangles, far too many for smooth interactive frame rates. We describe a new approach to solve this ‘molecular graphics problem’, which shares the work between GPU and multiple CPU cores, generates high-quality results with perfectly round spheres, shadows and ambient lighting and requires only OpenGL 1.0 functionality, without any pixel shader Z-buffer access (a feature which is missing in most mobile devices).

Availability and implementation: YASARA View, a molecular modeling program built around the visualization algorithm described here, is freely available (including commercial use) for Linux, MacOS, Windows and Android (Intel) from www.YASARA.org.

Contact:elmar@yasara.org

Supplementary information:Supplementary data are available at Bioinformatics online.

Alpha-bulges in G protein-coupled receptors

Agonist binding is related to a series of motions in G protein-coupled receptors (GPCRs) that result in the separation of transmembrane helices III and VI at their cytosolic ends and subsequent G protein binding. A large number of smaller motions also seem to be associated with activation. Most helices in GPCRs are highly irregular and often contain kinks, with extensive literature already available about the role of prolines in kink formation and the precise function of these kinks. GPCR transmembrane helices also contain many α-bulges. In this article we aim to draw attention to the role of these α-bulges in ligand and G-protein binding, as well as their role in several aspects of the mobility associated with GPCR activation. This mobility includes regularization and translation of helix III in the extracellular direction, a rotation of the entire helix VI, an inward movement of the helices near the extracellular side, and a concerted motion of the cytosolic ends of the helices that makes their orientation appear more circular and that opens up space for the G protein to bind. In several cases, α-bulges either appear or disappear as part of the activation process.

Abstract 611: Blocking CD40-TRAF6 Signaling is a Novel Therapeutic Target in Obesity-Associated Insulin Resistance

The immune system plays an instrumental role in obesity and insulin resistance. Here we unravel the role of the co-stimulatory molecule, CD40, and its signaling intermediates, TNF-Receptor-Associated-Factors (TRAFs), in diet-induced obesity (DIO). Although not exhibiting increased weight gain, male CD40-/- mice in DIO displayed worsened insulin resistance, as compared to wild type mice. This was associated with excessive inflammation of adipose tissue (AT), characterized by increased accumulation of CD8+ T cells and M1 macrophages, and enhanced hepatosteatosis. Mice with deficient CD40-TRAF2/3/5 signaling in MHCII+ cells exhibited a similar phenotype in DIO as CD40-/- mice. In contrast, mice with deficient CD40-TRAF6 signaling in MHCII+ cells displayed no insulin resistance, and showed a reduction in both AT inflammation and hepatosteatosis in DIO. To prove the therapeutic potential of inhibition of CD40-TRAF6 in obesity, DIO mice were treated with a small-molecule inhibitor that we designed to specifically block CD40-TRAF6 interactions; this improved insulin sensitivity, reduced AT inflammation and decreased hepatosteatosis. Our study reveals that the CD40-TRAF2/3/5 signaling pathway in MHCII+ cells protects against AT inflammation and metabolic complications associated with obesity, whereas CD40-TRAF6 interactions in MHCII+ cells aggravate these complications. Inhibition of CD40-TRAF6 signaling by our newly developed compound may provide a novel therapeutic option in obesity-associated insulin resistance.

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Anomalies in the refinement of isoleucine

A study of isoleucines in protein structures solved using X-ray crystallography revealed a series of systematic trends for the two side-chain torsion angles χ1 and χ2 dependent on the resolution, secondary structure and refinement software used. The average torsion angles for the nine rotamers were similar in high-resolution structures solved using either the REFMAC, CNS or PHENIX software. However, at low resolution these programs often refine towards somewhat different χ1 and χ2 values. Small systematic differences can be observed between refinement software that uses molecular dynamics-type energy terms (for example CNS) and software that does not use these terms (for example REFMAC). Detailing the standard torsion angles used in refinement software can improve the refinement of protein structures. The target values in the molecular dynamics-type energy functions can also be improved.

GPCRDB: an information system for G protein-coupled receptors

For the past 20 years, the GPCRDB (G protein-coupled receptors database; http://www.gpcr.org/7tm/) has been a ‘one-stop shop’ for G protein-coupled receptor (GPCR)-related data. The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data, such as multiple sequence alignments and homology models. The GPCRDB also provides visualization and analysis tools, plus a number of query systems. In the latest GPCRDB release, all multiple sequence alignments, and >65 000 homology models, have been significantly improved, thanks to a recent flurry of GPCR X-ray structure data. Tools were introduced to browse X-ray structures, compare binding sites, profile similar receptors and generate amino acid conservation statistics. Snake plots and helix box diagrams can now be custom coloured (e.g. by chemical properties or mutation data) and saved as figures. A series of sequence alignment visualization tools has been added, and sequence alignments can now be created for subsets of sequences and sequence positions, and alignment statistics can be produced for any of these subsets.

SNP linkage analysis and whole exome sequencing identify a novel POU4F3 mutation in autosomal dominant late-onset nonsyndromic hearing loss (DFNA15)

Autosomal dominant non-syndromic hearing loss (AD-NSHL) is one of the most common genetic diseases in human and is well-known for the considerable genetic heterogeneity. In this study, we utilized whole exome sequencing (WES) and linkage analysis for direct genetic diagnosis in AD-NSHL. The Korean family had typical AD-NSHL running over 6 generations. Linkage analysis was performed by using genome-wide single nucleotide polymorphism (SNP) chip and pinpointed a genomic region on 5q31 with a significant linkage signal. Sequential filtering of variants obtained from WES, application of the linkage region, bioinformatic analyses, and Sanger sequencing validation identified a novel missense mutation Arg326Lys (c.977G>A) in the POU homeodomain of the POU4F3 gene as the candidate disease-causing mutation in the family. POU4F3 is a known disease gene causing AD-HSLH (DFNA15) described in 5 unrelated families until now each with a unique mutation. Arg326Lys was the first missense mutation affecting the 3(rd) alpha helix of the POU homeodomain harboring a bipartite nuclear localization signal sequence. The phenotype findings in our family further supported previously noted intrafamilial and interfamilial variability of DFNA15. This study demonstrated that WES in combination with linkage analysis utilizing bi-allelic SNP markers successfully identified the disease locus and causative mutation in AD-NSHL.

Abstract 14: Small Molecule Inhibitors of the CD40-TRAF6 Interaction Reduce Atherosclerosis by Inducing Hypo-inflammatory Myeloid Cells

The co-stimulatory CD40-CD40L dyad is well known for its pro-inflammatory role in atherosclerosis. Inhibition of CD40(L) in hyperlipidemic mice drastically reduces atherosclerosis. However, long term inhibition of CD40(L) results in immunosuppression and/or thromboembolic events. Therefore more targeted inhibition of the CD40L-CD40 dyad is required. To elicit intracellular signalling upon activation, CD40 needs to recruit adaptor proteins: the tumour necrosis factor receptor-associated factors (TRAFs). Using mice with a mutation in the CD40-TRAF binding site, we previously showed that CD40-TRAF6, and not CD40-TRAF2/3/5, are pivotal in atherosclerosis.

To discover small drug-like molecules that inhibit the CD40-TRAF6 interaction an in silico approach of virtual ligand screening was used; this resulted in the identification of 40.000 compounds. Analysis of the top 800 compounds identified 7 compounds that dose-dependently reduced NFκB activation and IL1β and IL6 expression in RAW cells and CD40-stimulated bone marrow-derived macrophages, respectively. Surface plasmon resonance experiments confirmed direct binding of the compounds to the TRAF6 C-domain.

To analyze the effects of the top two compounds on atherosclerosis, Apoe -/- mice were daily treated with compounds 6877002 or 6860766 for 6 weeks. Compound treatment reduced atherosclerosis in the aortic arch by 47.1% (6877002) and 66.8% (6860766). The number of plaque monocytes/macrophages was decreased by 41.4% (6877002) and 53.0% (6860766), and granulocytes by 62.5% (6877002) and 41.5% (6860766). Intravital microscopy showed that the compounds reduced monocyte recruitment to the endothelium by 40.1% (6877002) and 51.2% (6860766), neutrophil adhesion was reduced by 40.2% (6877002) and 51.2% (6860766). In accordance, expression of CCL2-CCR2 and CCL5-CCR5 was remarkably reduced in compound treated macrophages. Moreover, compound treatment abolished CD40-induced expression of TNFα, IL1β, IL6, IL10, and IL12.

These results establish the importance and possibilities of long-term therapeutic inhibition of CD40-TRAF6 interactions in atherosclerosis and other inflammatory diseases and harbor the potential to overcome the current limitations of CD40(L) blocking therapies.

CING: an integrated residue-based structure validation program suite

We present a suite of programs, named CING for Common Interface for NMR Structure Generation that provides for a residue-based, integrated validation of the structural NMR ensemble in conjunction with the experimental restraints and other input data. External validation programs and new internal validation routines compare the NMR-derived models with empirical data, measured chemical shifts, distance- and dihedral restraints and the results are visualized in a dynamic Web 2.0 report. A red-orange-green score is used for residues and restraints to direct the user to those critiques that warrant further investigation. Overall green scores below ~20 % accompanied by red scores over ~50 % are strongly indicative of poorly modelled structures. The publically accessible, secure iCing webserver ( https://nmr.le.ac.uk ) allows individual users to upload the NMR data and run a CING validation analysis.