MOTIVATION: The FoldX force field was originally validated with a database of 1000 mutants at a time when there were few high-resolution structures. Here, we have manually curated a database of 5556 mutants affecting protein stability, resulting in 2484 highly confident mutations denominated FoldX stability dataset (FSD), represented in non-redundant X-ray structures with <2.5 Å resolution, not involving duplicates, metals, or prosthetic groups. Using this database, we have created a new version of the FoldX force field by introducing pi stacking, pH dependency for all charged residues, improving aromatic-aromatic interactions, modifying the Ncap contribution and α-helix dipole, recalibrating the side-chain entropy of methionine, adjusting the H-bond parameters, and modifying the solvation contribution of tryptophan and others. RESULTS: These changes have led to significant improvements for the prediction of specific mutants involving the above residues/interactions and a statistically significant increase of FoldX predictions, as well as for the majority of the 20 aa. Removing all training sets data from FSD [Validation FoldX Stability Dataset (VFSD) dataset] resulted in improved predictions from R = 0.693 (RMSE = 1.277 kcal/mol) to R = 0.706 (RMSE = 1.252 kcal/mol) when compared with the previously released version. FoldX achieves 95% accuracy considering an error of ±0.85 kcal/mol in prediction and an area under the curve = 0.78 for the VFSD, predicting the sign of the energy change upon mutation. AVAILABILITY AND IMPLEMENTATION: FoldX versions 4.1 and 5.1 are freely available for academics at https://foldxsuite.crg.eu/.

MOTIVATION: Deep learning algorithms applied to structural biology often struggle to converge to meaningful solutions when limited data is available, since they are required to learn complex physical rules from examples. State-of-the-art force-fields, however, cannot interface with deep learning algorithms due to their implementation. RESULTS: We present MadraX, a forcefield implemented as a differentiable PyTorch module, able to interact with deep learning algorithms in an end-to-end fashion. AVAILABILITY AND IMPLEMENTATION: MadraX documentation, together with tutorials and installation guide, is available at madrax.readthedocs.io.

SUMMARY: Recent years have seen an increase in the number of structures available, not only for new proteins but also for the same protein crystallized with different molecules and proteins. While protein design software has proven to be successful in designing and modifying proteins, they can also be overly sensitive to small conformational differences between structures of the same protein. To cope with this, we introduce here pyFoldX, a python library that allows the integrative analysis of structures of the same protein using FoldX, an established forcefield and modelling software. The library offers new functionalities for handling different structures of the same protein, an improved molecular parametrization module and an easy integration with the data analysis ecosystem of the python programming language. AVAILABILITY AND IMPLEMENTATION: pyFoldX rely on the FoldX software for energy calculations and modelling, which can be downloaded upon registration in http://foldxsuite.crg.eu/ and its licence is free of charge for academics. The pyFoldX library is open-source. Full details on installation, tutorials covering the library functionality and the scripts used to generate the data and figures presented in this paper are available at https://github.com/leandroradusky/pyFoldX. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Independent Component Analysis (ICA) allows the dissection of omic datasets into modules that help to interpret global molecular signatures. The inherent randomness of this algorithm can be overcome by clustering many iterations of ICA together to obtain robust components. Existing algorithms for robust ICA are dependent on the choice of clustering method and on computing a potentially biased and large Pearson distance matrix. RESULTS: We present robustica, a Python-based package to compute robust independent components with a fully customizable clustering algorithm and distance metric. Here, we exploited its customizability to revisit and optimize robust ICA systematically. Of the 6 popular clustering algorithms considered, DBSCAN performed the best at clustering independent components across ICA iterations. To enable using Euclidean distances, we created a subroutine that infers and corrects the components' signs across ICA iterations. Our subroutine increased the resolution, robustness, and computational efficiency of the algorithm. Finally, we show the applicability of robustica by dissecting over 500 tumor samples from low-grade glioma (LGG) patients, where we define two new gene expression modules with key modulators of tumor progression upon IDH1 and TP53 mutagenesis. CONCLUSION: robustica brings precise, efficient, and customizable robust ICA into the Python toolbox. Through its customizability, we explored how different clustering algorithms and distance metrics can further optimize robust ICA. Then, we showcased how robustica can be used to discover gene modules associated with combinations of features of biological interest. Taken together, given the broad applicability of ICA for omic data analysis, we envision robustica will facilitate the seamless computation and integration of robust independent components in large pipelines.

A laryngectomee is a person whose larynx has been removed by surgery, usually due to laryngeal cancer. After surgery, most laryngectomees are able to speak again, using techniques that are learned with the help of a speech therapist. This is termed as alaryngeal speech, and esophageal speech (ES) is one of the several alaryngeal speech production modes. A considerable amount of research has been dedicated to the study of alaryngeal speech, with a wide range of aims such as helping speech therapists with evaluation and diagnosis, and improving its quality and intelligibility using digital signal processing techniques. We present to you a database of Spanish ES voices, named AhoSLABI, which is designed to allow the development of new support technologies for this speech impairment. The database primarily consists of recordings of 31 laryngectomees (27 males and 4 females) pronouncing phonetically balanced sentences. Additionally, it includes parallel recordings of the sentences by 9 healthy speakers (6 males and 3 females) to facilitate speech processing tasks that require small parallel corpora, such as voice conversion or synthetic speech adaptation. Apart from the sentences, the database includes sustained vowels and a small set of isolated words, which can be valuable for research on ES analysis, diagnosis and evaluation. The paper describes the main contents of the database, the recording protocols and procedure, as well as the labeling process. The main acoustic characteristics of the voices, such as speaking rate, durations of the recordings, phones and silences, and other such characteristics are compared with those of a reduced set of healthy voices. In addition, we describe an experiment using the database to improve the performance of an ASR system for ES speakers. This new resource will be made available to the scientific community with the hope that it will be used to improve the quality of life of the laryngectomees.

SUMMARY: Accurate 3D modelling of protein-protein interactions (PPI) is essential to compensate for the absence of experimentally determined complex structures. Here, we present a new set of commands within the ModelX toolsuite capable of generating atomic-level protein complexes suitable for interface design. Among these commands, the new tool ProteinFishing proposes known and/or putative alternative 3D PPI for a given protein complex. The algorithm exploits backbone compatibility of protein fragments to generate mutually exclusive protein interfaces that are quickly evaluated with a knowledge-based statistical force field. Using interleukin-10-R2 co-crystalized with interferon-lambda-3, and a database of X-ray structures containing interleukin-10, this algorithm was able to generate interleukin-10-R2/interleukin-10 structural models in agreement with experimental data. AVAILABILITY AND IMPLEMENTATION: ProteinFishing is a portable command-line tool included in the ModelX toolsuite, written in C++, that makes use of an SQL (tested for MySQL and MariaDB) relational database delivered with a template SQL dump called FishXDB. FishXDB contains the empty tables of ModelX fragments and the data used by the embedded statistical force field. ProteinFishing is compiled for Linux-64bit, MacOS-64bit and Windows-32bit operating systems. This software is a proprietary license and is distributed as an executable with its correspondent database dumps. It can be downloaded publicly at http://modelx.crg.es/. Licenses are freely available for academic users after registration on the website and are available under commercial license for for-profit organizations or companies. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The coronavirus disease COVID-19 constitutes the most severe pandemic of the last decades having caused more than 1 million deaths worldwide. The SARS-CoV-2 virus recognizes the angiotensin converting enzyme 2 (ACE2) on the surface of human cells through its spike protein. It has been reported that the coronavirus can mildly infect cats, and ferrets, and perhaps dogs while not pigs, mice, chicken and ducks. Differences in viral infectivity among different species or individuals could be due to amino acid differences at key positions of the host proteins that interact with the virus, the immune response, expression levels of host proteins and translation efficiency of the viral proteins among other factors. Here, first we have addressed the importance that sequence variants of different animal species, human individuals and virus isolates have on the interaction between the RBD domain of the SARS-CoV-2 spike S protein and human angiotensin converting enzyme 2 (ACE2). Second, we have looked at viral translation efficiency by using the tRNA adaptation index. We find that integration of both interaction energy with ACE2 and translational efficiency explains animal infectivity. Humans are the top species in which SARS-CoV-2 is both efficiently translated as well as optimally interacting with ACE2. We have found some viral mutations that increase affinity for hACE and some hACE2 variants affecting ACE2 stability and virus binding. These variants suggest that different sensitivities to coronavirus infection in humans could arise in some cases from allelic variability affecting ACE2 stability and virus binding.

State of the art systems for voice conversion have been shown to generate highly natural sounding converted speech. Voice conversion techniques have also been applied to alaryngeal speech, with the aim of improving its quality or its intelligibility. In this paper, we present an attempt to apply a voice conversion strategy based on phonetic posteriorgrams (PPGs), which produces very high quality converted speech, to improve the characteristics of esophageal speech. The main advantage of this PPG based architecture lies in the fact that it is able to convert speech from any source, without the need to previously train the system with a parallel corpus. However, our results show that the PPG approach degrades the intelligibility of the converted speech considerably, especially when the input speech is already poorly intelligible. In this paper two systems are compared, an LSTM based one-to-one conversion system, which is referred to as the baseline, and the new system using phonetic posteriorgrams. Both spectral parameters and f0 are converted using DNN (Deep Neural Network) based architectures. Results from both objective and subjective evaluations are presented, showing that although ASR (Automated Speech Recognition) errors are reduced, original esophageal speech is still preferred by subjects.

SUMMARY: A new version of FoldX, whose main new features allows running classic FoldX commands on structures containing RNA molecules and includes a module that allows parametrization of ligands or small molecules (ParamX) that were not previously recognized in old versions, has been released. An extended FoldX graphical user interface has also being developed (available as a python plugin for the YASARA molecular viewer) allowing user-friendly parametrization of new custom user molecules encoded using JSON format. AVAILABILITY AND IMPLEMENTATION: http://foldxsuite.crg.eu/.

The ISO/IEEE 11073 standard for Personal Health Devices (X73PHD) aims to ensure interoperability between Personal Health Devices and aggregators-e.g. health appliances, routers-in ambulatory setups. The Integrating the Healthcare Enterprise (IHE) initiative promotes the coordinated use of different standards in healthcare systems (e.g. Personal/Electronic Health Records, alert managers, Clinical Decision Support Systems) by defining profiles intended for medical use cases. X73PHD provides a robust syntactic model and a comprehensive terminology, but it places limited emphasis on security and on interoperability with IHE-compliant systems and frameworks. However, the implementation of eHealth/mHealth applications in environments such as health and fitness monitoring, independent living and disease management (i.e. the X73PHD domains) increasingly requires features such as secure connections to mobile aggregators-e.g. smartphones, tablets-, the sharing of devices among different users with privacy, and interoperability with certain IHE-compliant healthcare systems. This work proposes a comprehensive IHE-based X73PHD extension consisting of additive layers adapted to different eHealth/mHealth applications, after having analyzed the features of X73PHD (especially its built-in security), IHE profiles related with these applications and other research works. Both the new features proposed for each layer and the procedures to support them have been carefully chosen to minimize the impact on X73PHD, on its architecture (in terms of delays and overhead) and on its framework. Such implications are thoroughly analyzed in this paper. As a result, an extended model of X73PHD is proposed, preserving its essential features while extending them with added value.

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products ('di-chromatic'), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation.

MOTIVATION: In proteomes of higher eukaryotes, many alternative splice variants can only be detected by their shared peptides. This makes it highly challenging to use peptide-centric mass spectrometry to distinguish and to quantify protein isoforms resulting from alternative splicing events. RESULTS: We have developed two complementary algorithms based on linear mathematical models to efficiently compute a minimal set of shared and unique peptides needed to quantify a set of isoforms and splice variants. Further, we developed a statistical method to estimate the splice variant abundances based on stable isotope labeled peptide quantities. The algorithms and databases are integrated in a web-based tool, and we have experimentally tested the limits of our quantification method using spiked proteins and cell extracts. AVAILABILITY AND IMPLEMENTATION: The TAPAS server is available at URL http://davinci.crg.es/tapas/. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Many proteins and signaling pathways are present in most cell types and tissues and yet perform specialized functions. To elucidate mechanisms by which these ubiquitous pathways are modulated, we overlaid information about cross-cell line protein abundance and variability, and evolutionary conservation onto functional pathway components and topological layers in the pathway hierarchy. We found that the input (receptors) and the output (transcription factors) layers evolve more rapidly than proteins in the intermediary transmission layer. In contrast, protein expression variability decreases from the input to the output layer. We observed that the differences in protein variability between the input and transmission layer can be attributed to both the network position and the tendency of variable proteins to physically interact with constitutively expressed proteins. Differences in protein expression variability and conservation are also accompanied by the tendency of conserved and constitutively expressed proteins to acquire somatic mutations, while germline mutations tend to occur in cell type-specific proteins. Thus, conserved core proteins in the transmission layer could perform a fundamental role in most cell types and are therefore less tolerant to germline mutations. In summary, we propose that the core signal transmission machinery is largely modulated by a variable input layer through physical protein interactions. We hypothesize that the bow-tie organization of cellular signaling on the level of protein abundance variability contributes to the specificity of the signal response in different cell types.

We apply down operators in the affine nilCoxeter algebra to yield explicit combinatorial expansions for certain families of noncommutative $k$-Schur functions. This yields a combinatorial interpretation for a new family of $k$-Littlewood--Richardson coefficients.

Standardized exchange of clinical information is a key factor in the provision of high quality health care systems. In this context, the openEHR specification facilitates the management of health data in electronic health records (EHRs), while the ISO/IEEE11073 (also referred to as X73PHD) family of standards provides a reference framework for medical device interoperability. Hospitals and health care providers using openEHR require flawless integration of data coming from external sources, such as X73PHD. Hence, a harmonization process is crucial for achieving a seamless, coherent use of those specifications in real scenarios. Such harmonization is the aim of this paper. Thus, the classes and attributes of a representative number of X73PHD specializations for medical devices--weight, temperature, blood pressure, pulse and heart rate, oximetry, and electrocardiograph--along with the X73PHD core document--ISO/IEEE11073-20601--have been analyzed and mapped to openEHR archetypes. The proposed methodology reuses the existing archetypes when possible and suggests new ones--or appropriate modifications--otherwise. As a result, this paper analyzes the inconsistencies found and the implications thereof in the coordinated use of these two standards. The procedure has also shown how existing standards are able to influence the archetype development process, enhancing the existing archetype corpus.

SUMMARY: Protein interaction networks are widely used to depict the relationships between proteins. These networks often lack the information on physical binary interactions, and they do not inform whether there is incompatibility of structure between binding partners. Here, we introduce SAPIN, a framework dedicated to the structural analysis of protein interaction networks. SAPIN first identifies the protein parts that could be involved in the interaction and provides template structures. Next, SAPIN performs structural superimpositions to identify compatible and mutually exclusive interactions. Finally, the results are displayed using Cytoscape Web. AVAILABILITY: The SAPIN server is available at http://sapin.crg.es. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Online.

Abstract Summary: A graphical user interface for the FoldX protein design program has been developed as a plugin for the YASARA molecular graphics suite. The most prominent FoldX commands such as free energy difference upon mutagenesis and interaction energy calculations can now be run entirely via a windowed menu system and the results are immediately shown on screen. Availability and Implementation: The plugin is written in Python and is freely available for download at http://foldxyasara.switchlab.org/ and supported on Linux, MacOSX and MS Windows. Contact: [email protected]; [email protected]; [email protected]

Traditionally, e-Health solutions were located at the point of care (PoC), while the new ubiquitous user-centered paradigm draws on standard-based personal health devices (PHDs). Such devices place strict constraints on computation and battery efficiency that encouraged the International Organization for Standardization/IEEE11073 (X73) standard for medical devices to evolve from X73PoC to X73PHD. In this context, low-voltage low-power (LV-LP) technologies meet the restrictions of X73PHD-compliant devices. Since X73PHD does not approach the software architecture, the accomplishment of an efficient design falls directly on the software developer. Therefore, computational and battery performance of such LV-LP-constrained devices can even be outperformed through an efficient X73PHD implementation design. In this context, this paper proposes a new methodology to implement X73PHD into microcontroller-based platforms with LV-LP constraints. Such implementation methodology has been developed through a patterns-based approach and applied to a number of X73PHD-compliant agents (including weighing scale, blood pressure monitor, and thermometer specializations) and microprocessor architectures (8, 16, and 32 bits) as a proof of concept. As a reference, the results obtained in the weighing scale guarantee all features of X73PHD running over a microcontroller architecture based on ARM7TDMI requiring only 168 B of RAM and 2546 B of flash memory.

MOTIVATION: Molecular chaperones prevent the aggregation of their substrate proteins and thereby ensure that they reach their functional native state. The bacterial GroEL/ES chaperonin system is understood in great detail on a structural, mechanistic and functional level; its interactors in Escherichia coli have been identified and characterized. However, a long-standing question in the field is: What makes a protein a chaperone substrate? RESULTS: Here we identify, using a bioinformatics-based approach a simple set of quantities, which characterize the GroEL-substrate proteome. We define three novel parameters differentiating GroEL interactors from other cellular proteins: lower rate of evolution, hydrophobicity and aggregation propensity. Combining them with other known features to a simple Bayesian predictor allows us to identify known homologous and heterologous GroEL substrateproteins. We discuss our findings in relation to established mechanisms of protein folding and evolutionary buffering by chaperones.

An estimated 15-40% of all interactions in the cell are mediated through protein-peptide interactions [1,2] meaning that, at the most extreme, nearly every protein is affected either directly or indirectly by peptide-binding events.

The ISO/IEEE 11073 (x73) family of standards is a reference frame for medical device interoperability. A draft for an ECG device specialization (ISO/IEEE 11073-10406-d02) has already been presented to the Personal Health Device (PHD) Working Group, and the Standard Communications Protocol for Computer-Assisted ElectroCardioGraphy (SCP-ECG) Standard for short-term diagnostic ECGs (EN1064:2005+A1:2007) has recently been approved as part of the x73 family (ISO 11073-91064:2009). These factors suggest the coordinated use of these two standards in foreseeable telecardiology environments, and hence the need to harmonize them. Such harmonization is the subject of this paper. Thus, a mapping of the mandatory attributes defined in the second draft of the ISO/IEEE 11073-10406-d02 and the minimum SCP-ECG fields is presented, and various other capabilities of the SCP-ECG Standard (such as the messaging part) are also analyzed from an x73-PHD point of view. As a result, this paper addresses and analyzes the implications of some inconsistencies in the coordinated use of these two standards. Finally, a proof-of-concept implementation of the draft x73-PHD ECG device specialization is presented, along with the conversion from x73-PHD to SCP-ECG. This paper, therefore, provides recommendations for future implementations of telecardiology systems that are compliant with both x73-PHD and SCP-ECG.

MOTIVATION: Most of the structures and functions of proteome globular domains are yet unknown. We can use high-resolution structures from different modular domains in combination with automatic protein design algorithms to predict genome-wide potential interactions of a protein. ADAN database and related web tools are online resources for the predictive analysis of ligand-domain complexes. ADAN database is a collection of different modular protein domains (SH2, SH3, PDZ, WW, etc.). It contains 3505 entries with extensive structural and functional information available, manually integrated, curated and annotated with cross-references to other databases, biochemical and thermodynamical data, simplified coordinate files, sequence files and alignments. Prediadan, a subset of ADAN database, offers position-specific scoring matrices for protein-protein interactions, calculated by FoldX, and predictions of optimum ligands and putative binding partners. Users can also scan a query sequence against selected matrices, or improve a ligand-domain interaction. AVAILABILITY: ADAN is accessible at http://adan-embl.ibmc.umh.es/ or http://adan.crg.es/.

Advances in information and communication technologies, ICT, are bringing new opportunities in the field of middleware systems oriented to ubiquitous environments and wearable devices used for patient telemonitoring. At a time of such challenges, this paper arises from the need to identify robust technical telemonitoring solutions that are both open and interoperable in home or mobile scenarios. These middleware systems demand standardized solutions to be cost effective and to take advantage of standardized operation and interoperability. Thus, a fundamental challenge is to design a plug-&-play platform that, either as individual elements or as components, can be incorporated in a simple way into different telecare systems, perhaps configuring a personal user network. Moreover, there is an increasing market pressure from companies not traditionally involved in medical markets, asking for a standard for personal health devices (PHD), which foresee a vast demand for telemonitoring, wellness, ambient assisted living (AAL) and applications for ubiquitous-health (u-health). However, the newly emerging situations imply very strict requirements for the protocols involved in the communication. The ISO/IEEE 11073 (X73) family of standards is adapting to new personal devices, implementing high quality sensors, and supporting wireless transport (e.g. Bluetooth) and the access to faster and reliable communication network resources. Its optimized version (X73-PHD) is adequate for this new technology snapshot and might appear the best-positioned international standards to reach this goal. This work presents an updated survey of this standard and its implementation in a middleware telemonitoring platform.

This paper presents a novel topology that implements an accurate approximation to the tanh (x) function. This approximation works in current mode and uses transistors in the subthreshold region of operation minimising power consumption and occupied area. Moreover, it has been designed with fully differential and balanced topologies so that the external influences, offset and distortion of even order are reduced. The proposed topology is thoroughly explained and it is analysed taking the body effect into account. Some modifications are applied in order to immunise it from the body effect, and simulated results for an implementation on a 0.35μm AMI CMOS technology are presented.

A proof-of-concept design of a patient monitoring solution for intensive care unit environments has been presented. It is end-to-end standard-based, using ISO/IEEE 11073 (X73) in the bedside environment and EN13606 to communicate the information to an electronic healthcare record (EHR) server. At the bedside end, the system is a plug-and-play sensor network communicating with a gateway that collects medical information and sends the data to a monitoring server. The monitoring server transforms this information into an EN13606 extract to be stored on the EHR server. The system has been implemented to comply with the last X73 and EN13606 available versions and tested in a laboratory environment to demonstrate the feasibility of an end-to-end standard-based solution.

As modeling of changes in backbone conformation still lacks a computationally efficient solution, we developed a discretisation of the conformational states accessible to the protein backbone similar to the successful rotamer approach in side chains. The BriX fragment database, consisting of fragments from 4 to 14 residues long, was realized through identification of recurrent backbone fragments from a non-redundant set of high-resolution protein structures. BriX contains an alphabet of more than 1,000 frequently observed conformations per peptide length for 6 different variation levels. Analysis of the performance of BriX revealed an average structural coverage of protein structures of more than 99% within a root mean square distance (RMSD) of 1 Angstrom. Globally, we are able to reconstruct protein structures with an average accuracy of 0.48 Angstrom RMSD. As expected, regular structures are well covered, but, interestingly, many loop regions that appear irregular at first glance are also found to form a recurrent structural motif, albeit with lower frequency of occurrence than regular secondary structures. Larger loop regions could be completely reconstructed from smaller recurrent elements, between 4 and 8 residues long. Finally, we observed that a significant amount of short sequences tend to display strong structural ambiguity between alpha helix and extended conformations. When the sequence length increases, this so-called sequence plasticity is no longer observed, illustrating the context dependency of polypeptide structures.

Evolutionary conservation of protein interaction properties has been shown to be a valuable indication for functional importance. Here we use homology interface modeling of 10 Ras-effector complexes by selecting ortholog proteins from 12 organisms representing the major eukaryotic branches, except plants. We find that with increasing divergence time the sequence similarity decreases with respect to the human protein, but the affinities and association rate constants are conserved as predicted by the protein design algorithm, FoldX. In parallel we have done computer simulations on a minimal network based on Ras-effector interactions, and our results indicate that in the absence of negative feedback, changes in kinetics that result in similar binding constants have strong consequences on network behavior. This, together with the previous results, suggests an important biological role, not only for equilibrium binding constants but also for kinetics in signaling processes involving Ras-effector interactions. Our findings are important to take into consideration in system biology approaches and simulations of biological networks.

Current experiments likely cover only a fraction of all protein-protein interactions. Here, we developed a method to predict SH2-mediated protein-protein interactions using the structure of SH2-phosphopeptide complexes and the FoldX algorithm. We show that our approach performs similarly to experimentally derived consensus sequences and substitution matrices at predicting known in vitro and in vivo targets of SH2 domains. We use our method to provide a set of high-confidence interactions for human SH2 domains with known structure filtered on secondary structure and phosphorylation state. We validated the predictions using literature-derived SH2 interactions and a probabilistic score obtained from a naive Bayes integration of information on coexpression, conservation of the interaction in other species, shared interaction partners, and functions. We show how our predictions lead to a new hypothesis for the role of SH2 domains in signaling.

Numerous studies have noted that the evolution of new enzymatic specificities is accompanied by loss of the protein's thermodynamic stability (DeltaDeltaG), thus suggesting a tradeoff between the acquisition of new enzymatic functions and stability. However, since most mutations are destabilizing (DeltaDeltaG>0), one should ask how destabilizing mutations that confer new or altered enzymatic functions relative to all other mutations are. We applied DeltaDeltaG computations by FoldX to analyze the effects of 548 mutations that arose from the directed evolution of 22 different enzymes. The stability effects, location, and type of function-altering mutations were compared to DeltaDeltaG changes arising from all possible point mutations in the same enzymes. We found that mutations that modulate enzymatic functions are mostly destabilizing (average DeltaDeltaG = +0.9 kcal/mol), and are almost as destabilizing as the "average" mutation in these enzymes (+1.3 kcal/mol). Although their stability effects are not as dramatic as in key catalytic residues, mutations that modify the substrate binding pockets, and thus mediate new enzymatic specificities, place a larger stability burden than surface mutations that underline neutral, non-adaptive evolutionary changes. How are the destabilizing effects of functional mutations balanced to enable adaptation? Our analysis also indicated that many mutations that appear in directed evolution variants with no obvious role in the new function exert stabilizing effects that may compensate for the destabilizing effects of the crucial function-altering mutations. Thus, the evolution of new enzymatic activities, both in nature and in the laboratory, is dependent on the compensatory, stabilizing effect of apparently "silent" mutations in regions of the protein that are irrelevant to its function.

MOTIVATION: One of the more challenging problems in biology is to determine the cellular protein interaction network. Progress has been made to predict protein-protein interactions based on structural information, assuming that structural similar proteins interact in a similar way. In a previous publication, we have determined a genome-wide Ras-effector interaction network based on homology models, with a high accuracy of predicting binding and non-binding domains. However, for a prediction on a genome-wide scale, homology modelling is a time-consuming process. Therefore, we here successfully developed a faster method using position energy matrices, where based on different Ras-effector X-ray template structures, all amino acids in the effector binding domain are sequentially mutated to all other amino acid residues and the effect on binding energy is calculated. Those pre-calculated matrices can then be used to score for binding any Ras or effector sequences. RESULTS: Based on position energy matrices, the sequences of putative Ras-binding domains can be scanned quickly to calculate an energy sum value. By calibrating energy sum values using quantitative experimental binding data, thresholds can be defined and thus non-binding domains can be excluded quickly. Sequences which have energy sum values above this threshold are considered to be potential binding domains, and could be further analysed using homology modelling. This prediction method could be applied to other protein families sharing conserved interaction types, in order to determine in a fast way large scale cellular protein interaction networks. Thus, it could have an important impact on future in silico structural genomics approaches, in particular with regard to increasing structural proteomics efforts, aiming to determine all possible domain folds and interaction types. AVAILABILITY: All matrices are deposited in the ADAN database (http://adan-embl.ibmc.umh.es/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5) interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3) interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

The set of four equations in the Materials and Methods section had three extra minus signs, which were incorrect. The following are the correct equations.

This expanding scientific discipline is proving extremely popular and is attracting engineering and system design experts to the field of Biology. As Bioinformatics and Computational Biology will be essential components of new technical and scientific developments, it is vital to follow the discussion generated by the recent ESF Exploratory Workshop (October 13–16, 2005, Constructing and de-constructing Life, Magalia, Spain) and the 2005 report of the NEST High-Level Expert Group on Synthetic Biology: Applying Engineering to Biology Author Webpage) Synthetic Biology stands at the meeting-point of two cultures. The first, represented by those interested in ‘deconstructing life’, dissects biological systems in the search for simplified and minimal forms that will help us understand the adaptation and evolution of natural processes. This approach includes experiments to obtain information on isolated parts of biological systems, the simulation of these systems and then the prediction of associated properties followed by further experimental verification. Well-known examples include work on metabolic pathways such as glycolysis (Hans Westerhoff, Free University of Amsterdam) and the simulation of cell systems using stochastic approaches (Luis Serrano, EMBL, Heidelberg). Simplified systems, based on phospholipids (Doron Lancet, Weizmann Institute, Rehovot) or polymers (Steen Rasmussen, Los Alamos National Laboratory), are used to explore possible prebiotic systems. Directly related to this activity is research into minimal forms of life and minimal genomes Tom Knight (MIT Artificial Intelligence Laboratory). An essential part of this approach is the definition of biological systems that make modeling and simulation feasible: biodegradation networks (Alfonso Valencia, National Center of Biotechnology, Madrid), minimal genomes (Andres Moya, Instituto Cavanilles, Valencia), etc.). The development of computer viruses (Chris Adami, Santa Fe Institute) to study properties of biological evolution can also be included in this kind of research. In short, this approach focuses on the definition of material or virtual systems that help investigate the properties of complex biological problems. The second, complementary and symmetrical culture is the ‘Construction of life’ approach. In this case, the goal is to build systems that inspired by general biological principles, use biological or chemical components to reproduce the behavior of live systems. Highlights of this kind of approach are the designs of Drew Endy (MIT Department of Biology) and Ron Weiss (Department Electrical Engineering Princeton University) who have started to address biological phenomena with the conceptual weaponry of electrical engineering. The general underlying notion is to combine autonomous, modular, robust and reusable components. Characteristic specimens of this sort are the input components that sense a given environment, such as interfacing with biological signals, internal components, processing of biological input information inside a synthetic system to minimize side-effects, and output components, which send the signal processed by the synthetic setup back to the endogenous biological system. A very attractive and on-going by-product of this research is the development of a registry of Standard Biological Parts (Author Webpage), which includes lists of formated components, which, as they comply with international standards, can be easily distributed and shared. The second step will involve the combination of these components into working devices: associated research is seeking to define containers for these machines, which could range from simple lipid vesicles (Peter Walde, ETH; Albert Libchaber, the Rockefeller University) to minimal genomes (Hamilton Smith, Venter Institute). There is a clear difference between the intellectual goals of these two fields. The ‘deconstruction’ community seeks to understand biological systems and their evolution, whereas the ‘construction’ community searches for general design principles regardless of their relationship to actual Biology. Both communities, however, hope that the exploration and/or construction of these (biological) systems will expand our understanding of the organizational principles of living molecular systems, and both are linked by their dependence on very similar theoretical, experimental and computational techniques. This new drive towards ‘construction’ and ‘deconstruction’ of biological phenomena gives a new dimension and adds a new value to traditional research into the origin of life on Earth. Such research, now under the umbrella of Synthetic Biology, was for decades restricted to the field of the Chemistry of prebiotic systems. The body of theories and simulations on primitive, pre-cellular metabolism (Eric Smith, Santa Fe Institute) and on the transitions between living and non-living systems (Steen Rasmussen, Los Alamos National Laboratory; Norman Packard, Protolife Srl) provides a wealth of conceptual and material assets that the new field will be able to build on. Both the ‘deconstruction’ and the ‘construction’ approach generate extremely interesting scientific and technical challenges, among which there are at least two that are likely to influence the future of Computational Biology and Bioinformatics. The first issue is how to synthesize chromosomes containing well-defined functional regions (genes) under clear controllable replication, transcription and translation conditions. This fascinating prospect will require all our skills in analyzing, predicting and designing genome elements, with many implications for genome analysis, comparative genomics and transcription regulation. The second key issue is the modulation of functional specificity. Both newly designed components and those extracted from biological systems require a clear understanding of how they adapt to specific working conditions and how the interactions that determine the properties of stability and adaptation of molecular systems could be engineered. A clear example is the design of Transcription factors able to trigger the activation of specific genes, whether these are designed rationally (Homme Hellinga, Duke University) or obtained by directed evolution (Víctor de Lorenzo, National Center of Biotechnology). Computational analysis of protein families and of protein/DNA structures is, of course, essential for the development of these components. Apart of the instrumental role of Bioinformatics in Synthetic Biology in the design of synthetic chromosomes and components of a desired specificity, there are interesting additional opportunities as well for the development of computational models to analyze, simulate and predict the behavior of artificial and synthetic systems, in what is a new growing field.

Protein interaction networks are an important part of the post-genomic effort to integrate a part-list view of the cell into system-level understanding. Using a set of 11 yeast genomes we show that combining comparative genomics and secondary structure information greatly increases consensus-based prediction of SH3 targets. Benchmarking of our method against positive and negative standards gave 83% accuracy with 26% coverage. The concept of an optimal divergence time for effective comparative genomics studies was analyzed, demonstrating that genomes of species that diverged very recently from Saccharomyces cerevisiae(S. mikatae, S. bayanus, and S. paradoxus), or a long time ago (Neurospora crassa and Schizosaccharomyces pombe), contain less information for accurate prediction of SH3 targets than species within the optimal divergence time proposed. We also show here that intrinsically disordered SH3 domain targets are more probable sites of interaction than equivalent sites within ordered regions. Our findings highlight several novel S. cerevisiae SH3 protein interactions, the value of selection of optimal divergence times in comparative genomics studies, and the importance of intrinsic disorder for protein interactions. Based on our results we propose novel roles for the S. cerevisiae proteins Abp1p in endocytosis and Hse1p in endosome protein sorting.

Personal communications services (PCS) key objective is to provide ubiquitous communication services. The success of PCS will depend on the network resources to ensure the quality-of-service required by service subscribers. Performance evaluation studies of different system configurations and implementation alternatives will play a major role in the planning and dimensioning of successful PCS networks. We undertake the analysis of some major implementation issues of a PCS architecture based on the IN system architecture. Different system configurations and traffic scenarios are considered in the study. The overall system performance is evaluated in terms of utilization rate of the key network elements and the end-to-end response time of the signaling network for various IN services.

In this paper we summarise the necessary properties that a nullor conceived to be a universal active device, must have. This approach lead us to propose a practical implementation of a nullor, consisting of a four terminal, fully floating transconductor with high gain. These design conditions are validated with some unconventional applications.>