Application and Comprehensive Analysis of Neighbor Approximated Information Theoretic Configurational Entropy Methods to Protein-Ligand Binding Cases.

The binding entropy is an important thermodynamic quantity which has numerous applications in studies of the biophysical process, and configurational entropy is often one of the major contributors in it. Therefore, its accurate estimation is important, though it is challenging mostly due to sampling limitations, anharmonicity, and multimodality of atomic fluctuations. The present work reports a Neighbor Approximated Maximum Information Spanning Tree (A-MIST) method for conformational entropy and presents its performance and computational advantage over conventional Mutual Information Expansion (MIE) and Maximum Information Spanning Tree (MIST) for two protein-ligand binding cases: indirubin-5-sulfonate to Plasmodium falciparum Protein Kinase 5 (PfPK5) and P. falciparum RON2-peptide to P. falciparum Apical Membrane Antigen 1 (PfAMA1). Important structural regions considering binding configurational entropy are identified, and physical origins for such are discussed. A thorough performance evaluation is done of a set of four entropy estimators (Maximum Likelihood (ML), Miller-Madow (MM), Chao-Shen (CS), and James and Stein shrinkage (JS)) with known varying degrees of sensitivity of the entropy estimate on the extent of sampling, each with two schemes for discretization of fluctuation data of Degrees of Freedom (DFs) to estimate Probability Density Functions (PDFs). Our comprehensive evaluation of influences of variations of parameters shows Neighbor Approximated MIE (A-MIE) outperforms MIE in terms of convergence and computational efficiency. In the case of A-MIE/MIE, results are sensitive to the choice of root atoms, graph search algorithm used for the Bond-Angle-Torsion (BAT) conversion, and entropy estimator, while A-MIST/MIST are not. A-MIST yields binding entropy within 0.5 kcal/mol of MIST with only 20-30% computation. Moreover, all these methods have been implemented in an OpenMP/MPI hybrid parallel C++11 code, and also a python package for data preprocessing and entropy contribution analysis is developed and made available. A comparative analysis of features of current implementation and existing tools is also presented.

Coupling Supervised Molecular Dynamics (SuMD) with Entropy Estimations To Shine Light on the Stability of Multiple Binding Sites.

Exploring at the molecular level, all possible ligand-protein approaching pathways and, consequently, identifying the energetically favorable binding sites is considered crucial to depict a clear picture of the whole scenario of ligand-protein binding. In fact, a ligand can recognize a protein in multiple binding sites, adopting multiple conformations in every single binding site and inducing protein modifications upon binding. In the present work, we would like to present how it is possible to couple a supervised molecular dynamics (SuMD) approach to explore, from an unbound state, the most energetically favorable recognition pathways of the ligand to its protein, with an enthalpic and entropic characterization of the most stable ligand-protein bound states, using the protein kinase CK2α as a prototype study. We identified two accessory binding pockets surrounding the ATP-binding site having a strong enthalpic contribution but a different configurational entropy contribution, suggesting that they play a different role.

ProLego: tool for extracting and visualizing topological modules in protein structures.

BACKGROUND: In protein design, correct use of topology is among the initial and most critical feature. Meticulous selection of backbone topology aids in drastically reducing the structure search space. With ProLego, we present a server application to explore the component aspect of protein structures and provide an intuitive and efficient way to scan the protein topology space. RESULT: We have implemented in-house developed "topological representation" in an automated-pipeline to extract protein topology from given protein structure. Using the topology string, ProLego, compares topology against a non-redundant extensive topology database (ProLegoDB) as well as extracts constituent topological modules. The platform offers interactive topology visualization graphs. CONCLUSION: ProLego, provides an alternative but comprehensive way to scan and visualize protein topology along with an extensive database of protein topology. ProLego can be found at http://www.proteinlego.com.

In silico identification and characterization of stress and virulence associated repeats in Salmonella.

So much genomic similarities yet causing different diseases, is like a paradox in Salmonella biology. Repeat is one of the probes that can explain such differences. Here, a comparative genomics approach is followed to identify and characterize repeats that might play role in adaptation and pathogenesis. Repeats are non-randomly distributed in the genomes except few typhoid causing strains. Perfect long repeats are rare compare to polymorphic ones and both are statistically consistent. Significant differences in repeat densities in stress related genes manifest its probable participation in survival and virulence. 573 and 1053 repeat loci have been identified which are exclusively associated with stress and virulent genes respectively. In Salmonella Typhi, an octameric VNTR locus is found in between acrD and yffB genes having more than 25 perfect copies across Salmonella Typhi but possesses only single copy in other serovars. This repeat can be used as a diagnostic probe for typhoid.

Semantics based approach for analyzing disease-target associations.

BACKGROUND: A complex disease is caused by heterogeneous biological interactions between genes and their products along with the influence of environmental factors. There have been many attempts for understanding the cause of these diseases using experimental, statistical and computational methods. In the present work the objective is to address the challenge of representation and integration of information from heterogeneous biomedical aspects of a complex disease using semantics based approach. METHODS: Semantic web technology is used to design Disease Association Ontology (DAO-db) for representation and integration of disease associated information with diabetes as the case study. The functional associations of disease genes are integrated using RDF graphs of DAO-db. Three semantic web based scoring algorithms (PageRank, HITS (Hyperlink Induced Topic Search) and HITS with semantic weights) are used to score the gene nodes on the basis of their functional interactions in the graph. RESULTS: Disease Association Ontology for Diabetes (DAO-db) provides a standard ontology-driven platform for describing genes, proteins, pathways involved in diabetes and for integrating functional associations from various interaction levels (gene-disease, gene-pathway, gene-function, gene-cellular component and protein-protein interactions). An automatic instance loader module is also developed in present work that helps in adding instances to DAO-db on a large scale. CONCLUSIONS: Our ontology provides a framework for querying and analyzing the disease associated information in the form of RDF graphs. The above developed methodology is used to predict novel potential targets involved in diabetes disease from the long list of loose (statistically associated) gene-disease associations.

Modularity in protein structures: study on all-alpha proteins.

Modularity is known as one of the most important features of protein's robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism's growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein's secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or "building blocks" in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.

An Ab Initio Method for Designing Multi-Target Specific Pharmacophores using Complementary Interaction Field of Aspartic Proteases.

For past few decades, key objectives of rational drug discovery have been the designing of specific and selective ligands for target proteins. Infectious diseases like malaria are continuously becoming resistant to traditional medicines, which inculcates need for new approaches to design inhibitors for antimalarial targets. A novel method for ab initio designing of multi target specific pharmacophores using the interaction field maps of active sites of multiple proteins has been developed to design 'specificity' pharmacophores for aspartic proteases. The molecular interaction field grid maps of active sites of aspartic proteases (plasmepsin II & IV from Plasmodium falciparum, plasmepsin from Plasmodium vivax, pepsin & cathepsin D from human) are calculated and common pharmacophoric features for favourable binding spots in active sites are extracted in the form of cliques of graphs using inductive logic programming (ILP). The two pharmacophore ensembles are constructed from largest common cliques by imposing size of receptor active site (L) and domain-specific receptor-ligand information (S). The overlap of chemical space between two ensembles and the results of virtual screening of inhibitor database with known activities show that this method can design efficient pharmacophores with no prior ligand information.

PfalDB: an integrated drug target and chemical database for Plasmodium falciparum.

Plasmodium falciparum is one of the deadliest protozoan parasite species among those that cause malaria. Uncontrolled use of antimalarial drugs has resulted in evolutionary selection pressure favoring high levels of resistance to antimalarials; currently P.falciparum shows resistance to all classes of antimalarials. Therefore it is essential to identify novel drug targets, and design selective anti-malarials which can overcome resistance. While many drug targets are freely available in various public domain resources, a single comprehensive source of data containing easily searchable and retrievable information is currently lacking. To facilitate the total integration and mining of data emerging from different drug consortia and also to prioritize drug targets for structure-based drug design, an open-access, inclusive comprehensive database for Plasmodium falciparum was established. Meta data of known/modeled structures along with binding site parameters of drug targets have been included in the database. Additionally, chemical compounds showing a positive inhibitory assay against Plasmodium falciparum or known drug targets have also been provided. The database is accessible at http://pfaldb.jnu.ac.in. The database provides diverse information regarding the structure, sequence, stage specific gene expression, pathway, action mechanism, essentiality and druggability for each drug target, and literature to assess the validation status of individual drug targets. It also includes information on individual anti-malarials with their activity and bioassay.

A plausible mechanism for the antimalarial activity of artemisinin: A computational approach.

Artemisinin constitutes the frontline treatment to aid rapid clearance of parasitaemia and quick resolution of malarial symptoms. However, the widespread promiscuity about its mechanism of action is baffling. There is no consensus about the biochemical target of artemisinin but recent studies implicate haem and PfATP6 (a calcium pump). We investigated the role of iron and artemisinin on PfATP6, in search of a plausible mechanism of action, via density functional theory calculations, docking and molecular dynamics simulations. Results suggest that artemisinin gets activated by iron which in turn inhibits PfATP6 by closing the phosphorylation, nucleotide binding and actuator domains leading to loss of function of PfATP6 of the parasite and its death. The mechanism elucidated here should help in the design of novel antimalarials.

Methylerythritol phosphate pathway to isoprenoids: kinetic modeling and in silico enzyme inhibitions in Plasmodium falciparum.

The methylerythritol phosphate (MEP) pathway of Plasmodium falciparum (P. falciparum) has become an attractive target for anti-malarial drug discovery. This study describes a kinetic model of this pathway, its use in validating 1-deoxy-d-xylulose 5-phosphate reductoisomerase (DXR) as drug target from the systemic perspective, and additional target identification, using metabolic control analysis and in silico inhibition studies. In addition to DXR, 1-deoxy-d-xylulose 5-phosphate synthase (DXS) can be targeted because it is the first enzyme of the pathway and has the highest flux control coefficient followed by that of DXR. In silico inhibition of both enzymes caused large decrement in the pathway flux. An added advantage of targeting DXS is its influence on vitamin B1 and B6 biosynthesis. Two more potential targets, 2-C-methyl-d-erythritol 2,4-cyclodiphosphate synthase and 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase, were also identified. Their inhibition caused large accumulation of their substrates causing instability of the system. This study demonstrates that both types of enzyme targets, one acting via flux reduction and the other by metabolite accumulation, exist in P. falciparum MEP pathway. These groups of targets can be exploited for independent anti-malarial drugs.

Unusual domain architecture of aminoacyl tRNA synthetases and their paralogs from Leishmania major.

BACKGROUND: Leishmania major, a protozoan parasite, is the causative agent of cutaneous leishmaniasis. Due to the development of resistance against the currently available anti-leishmanial drugs, there is a growing need for specific inhibitors and novel drug targets. In this regards, aminoacyl tRNA synthetases, the linchpins of protein synthesis, have received recent attention among the kinetoplastid research community. This is the first comprehensive survey of the aminoacyl tRNA synthetases, their paralogs and other associated proteins from L. major. RESULTS: A total of 26 aminoacyl tRNA synthetases were identified using various computational and bioinformatics tools. Phylogenetic analysis and domain architectures of the L. major aminoacyl tRNA synthetases suggest a probable archaeal/eukaryotic origin. Presence of additional domains or N- or C-terminal extensions in 11 aminoacyl tRNA synthetases from L. major suggests possibilities such as additional tRNA binding or oligomerization or editing activity. Five freestanding editing domains were identified in L. major. Domain assignment revealed a novel asparagine tRNA synthetase paralog, asparagine synthetase A which has been so far reported from prokaryotes and archaea. CONCLUSIONS: A comprehensive bioinformatic analysis revealed 26 aminoacyl tRNA synthetases and five freestanding editing domains in L. major. Identification of two EMAP (endothelial monocyte-activating polypeptide) II-like proteins similar to human EMAP II-like proteins suggests their participation in multisynthetase complex formation. While the phylogeny of tRNA synthetases suggests a probable archaeal/eukaryotic origin, phylogeny of asparagine synthetase A strongly suggests a bacterial origin. The unique features identified in this work provide rationale for designing inhibitors against parasite aminoacyl tRNA synthetases and their paralogs.

Modeling and experimental analyses reveals signaling plasticity in a bi-modular assembly of CD40 receptor activated kinases.

Depending on the strength of signal dose, CD40 receptor (CD40) controls ERK-1/2 and p38MAPK activation. At low signal dose, ERK-1/2 is maximally phosphorylated but p38MAPK is minimally phosphorylated; as the signal dose increases, ERK-1/2 phosphorylation is reduced whereas p38MAPK phosphorylation is reciprocally enhanced. The mechanism of reciprocal activation of these two MAPKs remains un-elucidated. Here, our computational model, coupled to experimental perturbations, shows that the observed reciprocity is a system-level behavior of an assembly of kinases arranged in two modules. Experimental perturbations with kinase inhibitors suggest that a minimum of two trans-modular negative feedback loops are required to reproduce the experimentally observed reciprocity. The bi-modular architecture of the signaling pathways endows the system with an inherent plasticity which is further expressed in the skewing of the CD40-induced productions of IL-10 and IL-12, the respective anti-inflammatory and pro-inflammatory cytokines. Targeting the plasticity of CD40 signaling significantly reduces Leishmania major infection in a susceptible mouse strain. Thus, for the first time, using CD40 signaling as a model, we show how a bi-modular assembly of kinases imposes reciprocity to a receptor signaling. The findings unravel that the signalling plasticity is inherent to a reciprocal system and that the principle can be used for designing a therapy.

Different designs of kinase-phosphatase interactions and phosphatase sequestration shapes the robustness and signal flow in the MAPK cascade.

BACKGROUND: The three layer mitogen activated protein kinase (MAPK) signaling cascade exhibits different designs of interactions between its kinases and phosphatases. While the sequential interactions between the three kinases of the cascade are tightly preserved, the phosphatases of the cascade, such as MKP3 and PP2A, exhibit relatively diverse interactions with their substrate kinases. Additionally, the kinases of the MAPK cascade can also sequester their phosphatases. Thus, each topologically distinct interaction design of kinases and phosphatases could exhibit unique signal processing characteristics, and the presence of phosphatase sequestration may lead to further fine tuning of the propagated signal. RESULTS: We have built four architecturally distinct types of models of the MAPK cascade, each model with identical kinase-kinase interactions but unique kinases-phosphatases interactions. Our simulations unravelled that MAPK cascade's robustness to external perturbations is a function of nature of interaction between its kinases and phosphatases. The cascade's output robustness was enhanced when phosphatases were sequestrated by their target kinases. We uncovered a novel implicit/hidden negative feedback loop from the phosphatase MKP3 to its upstream kinase Raf-1, in a cascade resembling the B cell MAPK cascade. Notably, strength of the feedback loop was reciprocal to the strength of phosphatases' sequestration and stronger sequestration abolished the feedback loop completely. An experimental method to verify the presence of the feedback loop is also proposed. We further showed, when the models were activated by transient signal, memory (total time taken by the cascade output to reach its unstimulated level after removal of signal) of a cascade was determined by the specific designs of interaction among its kinases and phosphatases. CONCLUSIONS: Differences in interaction designs among the kinases and phosphatases can differentially shape the robustness and signal response behaviour of the MAPK cascade and phosphatase sequestration dramatically enhances the robustness to perturbations in each of the cascade. An implicit negative feedback loop was uncovered from our analysis and we found that strength of the negative feedback loop is reciprocally related to the strength of phosphatase sequestration. Duration of output phosphorylation in response to a transient signal was also found to be determined by the individual cascade's kinase-phosphatase interaction design.

Oscillations in MAPK cascade triggered by two distinct designs of coupled positive and negative feedback loops.

BACKGROUND: Feedback loops, both positive and negative are embedded in the Mitogen Activated Protein Kinase (MAPK) cascade. In the three layer MAPK cascade, both feedback loops originate from the terminal layer and their sites of action are either of the two upstream layers. Recent studies have shown that the cascade uses coupled positive and negative feedback loops in generating oscillations. Two plausible designs of coupled positive and negative feedback loops can be elucidated from the literature; in one design the positive feedback precedes the negative feedback in the direction of signal flow and vice-versa in another. But it remains unexplored how the two designs contribute towards triggering oscillations in MAPK cascade. Thus it is also not known how amplitude, frequency, robustness or nature (analogous/digital) of the oscillations would be shaped by these two designs. RESULTS: We built two models of MAPK cascade that exhibited oscillations as function of two underlying designs of coupled positive and negative feedback loops. Frequency, amplitude and nature (digital/analogous) of oscillations were found to be differentially determined by each design. It was observed that the positive feedback emerging from an oscillating MAPK cascade and functional in an external signal processing module can trigger oscillations in the target module, provided that the target module satisfy certain parametric requirements. The augmentation of the two models was done to incorporate the nuclear-cytoplasmic shuttling of cascade components followed by induction of a nuclear phosphatase. It revealed that the fate of oscillations in the MAPK cascade is governed by the feedback designs. Oscillations were unaffected due to nuclear compartmentalization owing to one design but were completely abolished in the other case. CONCLUSION: The MAPK cascade can utilize two distinct designs of coupled positive and negative feedback loops to trigger oscillations. The amplitude, frequency and robustness of the oscillations in presence or absence of nuclear compartmentalization were differentially determined by two designs of coupled positive and negative feedback loops. A positive feedback from an oscillating MAPK cascade was shown to induce oscillations in an external signal processing module, uncovering a novel regulatory aspect of MAPK signal processing.

Functional relevance of dynamic properties of Dimeric NADP-dependent Isocitrate Dehydrogenases.

BACKGROUND: Isocitrate Dehydrogenases (IDHs) are important enzymes present in all living cells. Three subfamilies of functionally dimeric IDHs (subfamilies I, II, III) are known. Subfamily I are well-studied bacterial IDHs, like that of Escherischia coli. Subfamily II has predominantly eukaryotic members, but it also has several bacterial members, many being pathogens or endosymbionts. subfamily III IDHs are NAD-dependent. The eukaryotic-like subfamily II IDH from pathogenic bacteria such as Mycobacterium tuberculosis IDH1 are expected to have regulation similar to that of bacteria which use the glyoxylate bypass to survive starvation. Yet they are structurally different from IDHs of subfamily I, such as the E. coli IDH. RESULTS: We have used phylogeny, structural comparisons and molecular dynamics simulations to highlight the similarity and differences between NADP-dependent dimeric IDHs with an emphasis on regulation. Our phylogenetic study indicates that an additional subfamily (IV) may also be present. Variation in sequence and structure in an aligned region may indicate functional importance concerning regulation in bacterial subfamily I IDHs. Correlation in movement of prominent loops seen from molecular dynamics may explain the adaptability and diversity of the predominantly eukaryotic subfamily II IDHs. CONCLUSION: This study discusses possible regulatory mechanisms operating in various IDHs and implications for regulation of eukaryotic-like bacterial IDHs such as that of M. tuberculosis, which may provide avenues for intervention in disease.

Characterization of Leishmania donovani aquaporins shows presence of subcellular aquaporins similar to tonoplast intrinsic proteins of plants.

Leishmania donovani, a protozoan parasite, resides in the macrophages of the mammalian host. The aquaporin family of proteins form important components of the parasite-host interface. The parasite-host interface could be a potential target for chemotherapy. Analysis of L. major and L. infantum genomes showed the presence of five aquaporins (AQPs) annotated as AQP9 (230aa), AQP putative (294aa), AQP-like protein (279aa), AQP1 (314aa) and AQP-like protein (596aa). We report here the structural modeling, localization and functional characterization of the AQPs from L. donovani. LdAQP1, LdAQP9, LdAQP2860 and LdAQP2870 have the canonical NPA-NPA motifs, whereas LdAQP putative has a non-canonical NPM-NPA motif. In the carboxyl terminal to the second NPA box of all AQPs except AQP1, a valine/alanine residue was found instead of the arginine. In that respect these four AQPs are similar to tonoplast intrinsic proteins in plants, which are localized to intracellular organelles. Confocal microscopy of L. donovani expressing GFP-tagged AQPs showed an intracellular localization of LdAQP9 and LdAQP2870. Real-time PCR assays showed expression of all aquaporins except LdAQP2860, whose level was undetectable. Three-dimensional homology modeling of the AQPs showed that LdAQP1 structure bears greater topological similarity to the aquaglyceroporin than to aquaporin of E. coli. The pore of LdAQP1 was very different from the rest in shape and size. The cavity of LdAQP2860 was highly irregular and undefined in geometry. For functional characterization, four AQP proteins were heterologously expressed in yeast. In the fps1Δ yeast cells, which lacked the key aquaglyceroporin, LdAQP1 alone displayed an osmosensitive phenotype indicating glycerol transport activity. However, expression of LdAQP1 and LdAQP putative in a yeast gpd1Δ strain, deleted for glycerol production, conferred osmosensitive phenotype indicating water transport activity or aquaporin function. Our analysis for the first time shows the presence of subcellular aquaporins and provides structural and functional characterization of aquaporins in Leishmania donovani.

Fractal symmetry of protein interior: what have we learned?

The application of fractal dimension-based constructs to probe the protein interior dates back to the development of the concept of fractal dimension itself. Numerous approaches have been tried and tested over a course of (almost) 30 years with the aim of elucidating the various facets of symmetry of self-similarity prevalent in the protein interior. In the last 5 years especially, there has been a startling upsurge of research that innovatively stretches the limits of fractal-based studies to present an array of unexpected results on the biophysical properties of protein interior. In this article, we introduce readers to the fundamentals of fractals, reviewing the commonality (and the lack of it) between these approaches before exploring the patterns in the results that they produced. Clustering the approaches in major schools of protein self-similarity studies, we describe the evolution of fractal dimension-based methodologies. The genealogy of approaches (and results) presented here portrays a clear picture of the contemporary state of fractal-based studies in the context of the protein interior. To underline the utility of fractal dimension-based measures further, we have performed a correlation dimension analysis on all of the available non-redundant protein structures, both at the level of an individual protein and at the level of structural domains. In this investigation, we were able to separately quantify the self-similar symmetries in spatial correlation patterns amongst peptide-dipole units, charged amino acids, residues with the π-electron cloud and hydrophobic amino acids. The results revealed that electrostatic environments in the interiors of proteins belonging to 'α/α toroid' (all-α class) and 'PLP-dependent transferase-like' domains (α/ß class) are highly conducive. In contrast, the interiors of 'zinc finger design' ('designed proteins') and 'knottins' ('small proteins') were identified as folds with the least conducive electrostatic environments. The fold 'conotoxins' (peptides) could be unambiguously identified as one type with the least stability. The same analyses revealed that peptide-dipoles in the α/ß class of proteins, in general, are more correlated to each other than are the peptide-dipoles in proteins belonging to the all-α class. Highly favorable electrostatic milieu in the interiors of TIM-barrel, α/ß-hydrolase structures could explain their remarkably conserved (evolutionary) stability from a new light. Finally, we point out certain inherent limitations of fractal constructs before attempting to identify the areas and problems where the implementation of fractal dimension-based constructs can be of paramount help to unearth latent information on protein structural properties.

Collaborative development of predictive toxicology applications.

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals.The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation.Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way.