Network expansion of genetic associations defines a pleiotropy map of human cell biology.

Interacting proteins tend to have similar functions, influencing the same organismal traits. Interaction networks can be used to expand the list of candidate trait-associated genes from genome-wide association studies. Here, we performed network-based expansion of trait-associated genes for 1,002 human traits showing that this recovers known disease genes or drug targets. The similarity of network expansion scores identifies groups of traits likely to share an underlying genetic and biological process. We identified 73 pleiotropic gene modules linked to multiple traits, enriched in genes involved in processes such as protein ubiquitination and RNA processing. In contrast to gene deletion studies, pleiotropy as defined here captures specifically multicellular-related processes. We show examples of modules linked to human diseases enriched in genes with known pathogenic variants that can be used to map targets of approved drugs for repurposing. Finally, we illustrate the use of network expansion scores to study genes at inflammatory bowel disease genome-wide association study loci, and implicate inflammatory bowel disease-relevant genes with strong functional and genetic support.

The IntAct database: efficient access to fine-grained molecular interaction data.

The IntAct molecular interaction database (https://www.ebi.ac.uk/intact) is a curated resource of molecular interactions, derived from the scientific literature and from direct data depositions. As of August 2021, IntAct provides more than one million binary interactions, curated by twelve global partners of the International Molecular Exchange consortium, for which the IntAct database provides a shared curation and dissemination platform. The IMEx curation policy has always emphasised a fine-grained data and curation model, aiming to capture the relevant experimental detail essential for the interpretation of the provided molecular interaction data. Here, we present recent curation focus and progress, as well as a completely redeveloped website which presents IntAct data in a much more user-friendly and detailed way.

Complex Portal 2022: new curation frontiers.

The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database of macromolecular complexes with known function from a range of model organisms. It summarizes complex composition, topology and function along with links to a large range of domain-specific resources (i.e. wwPDB, EMDB and Reactome). Since the last update in 2019, we have produced a first draft complexome for Escherichia coli, maintained and updated that of Saccharomyces cerevisiae, added over 40 coronavirus complexes and increased the human complexome to over 1100 complexes that include approximately 200 complexes that act as targets for viral proteins or are part of the immune system. The display of protein features in ComplexViewer has been improved and the participant table is now colour-coordinated with the nodes in ComplexViewer. Community collaboration has expanded, for example by contributing to an analysis of putative transcription cofactors and providing data accessible to semantic web tools through Wikidata which is now populated with manually curated Complex Portal content through a new bot. Our data license is now CC0 to encourage data reuse. Users are encouraged to get in touch, provide us with feedback and send curation requests through the 'Support' link.

IntAct App: a Cytoscape application for molecular interaction network visualization and analysis.

SUMMARY: IntAct App is a Cytoscape 3 application that grants in-depth access to IntAct's molecular interaction data. It build networks where nodes are interacting molecules (mainly proteins, but also genes, RNA, chemicals…) and edges represent evidence of interaction. Users can query a network by providing its molecules, identified by different fields and optionally include all their interacting partners in the resulting network. The app offers three visualizations: one only displaying interactions, another representing every evidence and the last one emphasizing evidence where mutated versions of proteins were used. Users can also filter networks and click on nodes and edges to access all their related details. Finally, the application supports automation of its main features via Cytoscape commands. AVAILABILITY AND IMPLEMENTATION: Implementation available at https://apps.cytoscape.org/apps/intactapp, while the source code is available at https://github.com/EBI-IntAct/IntactApp.

PM2.5 pollution from household solid fuel burning practices in Central India: 2. Application of receptor models for source apportionment.

USEPA's UNMIX, positive matrix factorization (PMF) and effective variance-chemical mass balance (EV-CMB) receptor models were applied to chemically speciated profiles of 125 indoor PM2.5 measurements, sampled longitudinally during 2012-2013 in low-income group households of Central India which uses solid fuels for cooking practices. Three step source apportionment studies were carried out to generate more confident source characterization. Firstly, UNMIX6.0 extracted initial number of source factors, which were used to execute PMF5.0 to extract source-factor profiles in second step. Finally, factor analog locally derived source profiles were supplemented to EV-CMB8.2 with indoor receptor PM2.5 chemical profile to evaluate source contribution estimates (SCEs). The results of combined use of three receptor models clearly describe that UNMIX and PMF are useful tool to extract types of source categories within small receptor dataset and EV-CMB can pick those locally derived source profiles for source apportionment which are analog to PMF-extracted source categories. The source apportionment results have also shown three fold higher relative contribution of solid fuel burning emissions to indoor PM2.5 compared to those measurements reported for normal households with LPG stoves. The previously reported influential source marker species were found to be comparatively similar to those extracted from PMF fingerprint plots. The comparison between PMF and CMB SCEs results were also found to be qualitatively similar. The performance fit measures of all three receptor models were cross-verified and validated and support each other to gain confidence in source apportionment results.

PM2.5 pollution from household solid fuel burning practices in central India: 1. Impact on indoor air quality and associated health risks.

PM2.5 concentrations were measured in residential indoor environment in slums of central India during 2012-2013. In addition, a suite of chemical components including metals (Al, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Pb, Mo, Se, Sb, Na, Mg, K and Hg), ions (Na+, Mg2+, K+, Ca2+, F-, Cl-, NH4+, NO3- and SO42-) and carbon (OC and EC) were analyzed for all samples. Indoor PM2.5 concentrations were found to be several folds higher than the 24-h national ambient air quality standard (60 µg/m3) for PM2.5 in India, and the concentrations were found to vary from season to season. Mass closure was attempted for PM2.5 data, and close to 100 % mass was accounted for by organic matter, crustal material, secondary organic and inorganic aerosols and elemental carbon. Additionally, carcinogenic and non-carcinogenic health risks associated with exposure to indoor PM2.5 (inhalation, dermal and ingestion) were estimated and while exposures associated with dermal contact and ingestion were found to be within the acceptable limits, risk associated with inhalation exposure was found to be high for children and adults. Elements including Al, Cd, Co, Cr, Mn, Ni, As and Pb were present in high concentrations and contributed to carcinogenic and non-carcinogenic risks for residents' health. Results from this study highlight the need for efforts to reduce air pollution exposure in slum areas.

Topological designing of 4-piperazinylquinazolines as antagonists of PDGFR tyrosine kinase family.

Topological designing of a series of 4-piperazinylquinazolines as antagonists of platelet-derived growth factor receptor (PDGFR) tyrosine kinase family has been reported using a series of distance-based topological indices. Regression analysis of the data, using maximum R(2) method indicated that inhibitory activity, pIC(50) (microm), in cellular PGDFR phosphorylation assay can be modelled excellently in multi-parametric model. The results are discussed critically using cross-validated parameters.

Structural assignment of 2,6- and 2,7-disubstituted naphthalenes and prediction of (13)C nuclear magnetic resonance chemical shifts: applications of topology and two-dimensional NMR spectroscopy.

Unambiguous assignments of monocarboxymethylnapthalenes isolated as oxidation products of dimethylnaphthalenes by Pseudomonas putida, a bacterial strain, were made using two-dimensional nuclear Overhauser enhancement correlation spectroscopy (NOESEY). The two-dimensional long-range heteronuclear correlation NMR technique was also utilized for the assignment of quaternary carbons in the naphthalene system. In addition, we describe methods for prediction of 13C NMR chemical shifts of 2,6- and 2,7-disubstituted naphthalenes using topological approach. The method involves computation of molecular descriptors from topological representation of molecule, namely Wiener (W) and Szeged (Sz) indices. The results have shown that W and Sz indices can be successfully used for predicting 13C NMR chemical shifts and that Sigma13Cn can be used as a molecular property which in turn can be modeled by both W and Sz indices successfully.

Use of the PI index in predicting toxicity of nitrobenzene derivatives.

The PI Index is a Szeged-like topological index developed very recently. It has useful applications in chemistry which are yet to be investigated thoroughly. Herein, we report quantitative structure-toxicity relationship (QSTR) study using the PI Index. We have used 41 monosubstituted nitrobenzene for this purpose. The results have shown that the PI Index alone is not an appropriate index for modelling toxicity of nitrobenzene derivatives. Combinations of the PI Index with other distance-based topological indices resulted into statistically significant models and excellent results are obtained in pentaparametric models. The predictive potential of the models is discussed on the basis of cross-validation method, as well as by estimating root-mean-square error (RMS).

Study on quantitative structure-toxicity relationships of benzene derivatives acting by narcosis.

Hydrophobicity (logP) as well as quantiative structure-toxicity relationships (QSTRs) of some benzene derivatives acting by narcosis have been established based on narcotic mechanisms of action and toxicity data to the fathead minnow, Daphnia magna and Vibrio fischeri using information-theoretic topological index (Id). Excellent results are obtained in multiparametric regression upon introduction of dummy parameters (indicator variables). Consistent increase in R(2)(A) values indicated that inspite of collinarity between Id and one of the indicator variables (I(3-6)) the proposed models are statistically significant.

Novel estimation of lipophilic behaviour of polychlorinated biphenyls.

A novel method has been developed for the estimation of lipophilic behaviour of polychlorinated biphenyls (PCBs) using the recently introduced Padmakar-Ivan (PI) index. The results obtained are compared with the earlier reported Abraham method. The statistical analyses showed that the proposed method based on the PI index is quite useful.

QSAR study on toxicity to aqueous organisms using the PI index.

We have attempted to develop quantitative structure-toxicity relationships (QSTRs) to predict hydrophobicity (logP) as well as toxicity (pEC50 microm) of benzene derivatives using recently introduced Padmakar-Ivan (PI) index. The results have shown that both logP as well as pEC50 of benzene derivatives can be modelled excellently in multiparametric models in that the PI index and some indicator parameters are involved. The predictive ability of the models is discussed on the basis of the cross-validation method. The superiority of the PI index over several other topological indices is critically examined.