Search

The information technology revolution has among else led to the accelerated growth of the quantity and availability of accessible data as an indicatior of interactions in the ecosocial system. This study describes how atoms producing pollution translate into bites and digitaly transform into indicators and information. Through the example of the Serbian Environmental Information System, the study also shows how visualisation and effective communication are applied from the viewpoint of Luhmann's theory of society. According to Luhmann's theory, the society consists of closed systems of independent communications which continuously reproduce and develop by repeating their operations. The Serbian Environmental Information System represents a subcategory of the Luhmann's scientific subsystem and offers an answer to the question why there are, on the one hand, so many scientific facts on pollution, and on the other so few environmental measures that are undertaken. The answer lies in the fact that environmental pollution indicators belong to one social subsystem, while measures are expected to be taken within another social subsystem - law and economy, where each of them strives to preseve uniqueness and remain self-existent. According to Luhmann's social framework relevant for environmental protection, communication is a social system's response to environment that offers communicology a chance to examine the phenomena of environmental concerns in a more critical and detailed manner.

This paper describes the implementation of the SRPS ISO/IEC 17025:2006 standard in the Environmental Protection Agency, a state authority that performs the work of testing the quality of surface and ground water, sediment and air, according to the criteria of the Accreditation Body of Serbia (ATS). The success of maintenance of the acreditation system is presented by the new approach, by showing compliance indicator of the Accredation Body of Serbia as an objective indicator of competence for doing the given jobs. The paper contributes to the understanding of the importance of accreditation of jobs within the state administration, the body that examines the elements of the environment, which confirms its technical competence.

The genetic and environmental factors and their interaction contribute to sports performance. So far, it has been identified a large number of genetic markers associated with sports performance and risk of sports injuries. Sports genomics is a relatively young scientific discipline and the necessary additional complex research on a large number of participants is required before scientific results in this field could be applicable in practice. At present, the application of tests based on genetic information for sport talent identification or recommendations for personalized training, in order to achieve optimal sport performance, is not scientifically justified. It is also necessary to carefully consider all the ethical issues related to such testing in children.

By the ratification of the Protocol on water and health, the Republic of Serbia accepted the obligations of that international treaty, which is also the key instrument in advancing the water-and-sanitation- realted goal of the Commitment to Act of the Parma Declaration on Environment and Health. For the purpose of the achieving and maintaining the established and validated Protocol on Watwr and Health targets, and in order to obtain the high level of protection against water-related diseases, the continuous cooperation between ministries and institutions of health and environment is needed, as well as the mobilization on local and regional level, which will contribute to awareness raising in each individual of the necessity of the water resources and environmental protection, as well as of the hygienic promotion and health protection.

The widely accepted term ‘sustainable development’ is a comprehensive concept that requires multi-dimensional indicators showing links between economy, ecology and society. The concept of human development is obviously more complex than it could be understood from any aggregate economic index or from detailed sets of socio-economic statistical and ecological indicators. The research and analysis of the values of separation indicators for the Južna Morava basin agglomerations clearly show the impacts of industrial growth on the quality of the basin water bodies over the last three decades. Separation indicators have been derived from the statistical relationship between the situation indicators and drive indicators. The situation indicator SSWQIrb was derived as a composite index from ten chosen parameters which represent, by their quality, the characteristics of surface water, by reducing it to one index number weighed from the interrelation between the discharge at a given measurement station and the discharge at the exit profile of the basin. The index of the physical volume of industrial production (indexIND) has been accepted as the drive indicator. The indicators were calculated as a series of index numbers with 1981 as the base year. The values of separation indicators, i.e. degree of separation and factor of separation show the least separation in the first decade (1981-1990) when the volume of industrial production (indexIND) increased the most and the quality of the basin water bodies was the poorest (SSWQIrb). The improvement of the quality of basin water bodies in the last decade (2001-2010), marked by a higher value of the separation factor is a result of a slow growth of industrial production and positive impacts of an abrupt fall of total economic activity occurring already in the second decade (1991-2000). The research has confirmed the importance of applying the concepts of separation of economic growth from environmental impacts. Taking into consideration very low quantities of treated waters as opposed to the total amount of waste waters in Serbia, the separation indicators pose challenges to be faced in the near future. Separation indicators will serve to decision makers and the expert community as a key toolkit for verifying the results of the water resources protection policy.

Background/Aim. High sera reactivity with a peptide derived from human immunodeficiency virus HIV-1 envelope protein gp120, NTM1, correlate with non-progressive HIV-1 infection and also may have protective role in breast and prostate cancer. We also detected a low NTM1 reactive antibodies titer in healthy HIV negative sera and showed that antibody levels can be significantly increased with vigorous physical activity. However, the immune system seems to be unresponsive or tolerant to this peptide, implicating that the NTM1 sequence encompasses or overlaps a certain innate immune epitope. The aim of this study was to present evidences that NTM1 - binding antibodies - are components of innate immune humoral response, by confirming their presence in sera of newborn babies. For this purpose we collected a set of 225 innate antigen sequences reported in the literature and screened it for candidate antigens with the highest sequence and spectral similarity to NTM1 derived from HIV-1 gp120. Methods. Sera from 18 newborns were tested using ELISA, with peptide NTM1. Sequences from innate antigen database were aligned by an EMBOSS Water bioinformatics tool. Results. We identified NTM1 reactive antibodies in sera of HIV negative newborn babies. Further, in order to identify which of already known innate antigens are the most similar to NTM1 peptide we screened innate immune antigen sequence database collected from the literature. This screening revealed that the most similar sequence are ribonucleoproteins RO60, in addition to previously identified Nterminus of vasoactive intestinal peptide. Conclusion. The results of this study confirm the hypothesis that NTM1 recognizing antibodies are a part of humoral innate immune response. Further, computational similarity screening revealed a vasoactive intestinal peptide and RO60 as the most similar sequences and the strongest candidate antigens. In the light of the presented results, it is appealing that testing blood reactivity at birth, with specific innate antigens, particularly a vasoactive intestinal peptide, can reveal the potential to develop or boost protective immune response in breast and prostate cancer and HIV infection later in life. [Projekat Ministarstva nauke Republike Srbije, br. 173001]

The subject of research is elaboration and evaluation of indicators of sustainable development in the field of river basin management. Aggregate indicator entitled Ecoregion Sustainable Development Index is identified by calculation of average value by the procedure of leveling of proportion changes of three key indicators (demographic emission index, water quality index, industrial production index). Developed aggregate indicator of sustainable development is calculated and analyzed for South Morava river basin in Serbia, for the period from 1980 to 2010. The beneficiaries of these indicators are the experts from the field of environmental protection and water management who should use it for elaboration of reports directed towards the creators of economic development policy and river basin management planning. Elaborated according to the given methodology, the indicator Ecoregion Sustainable Development Index is available for the decision makers on the national level, internationally comparative and it provides the conditions for further elaboration and application.

This study analyses the process of purifying waste waters from textile fibre dyeing by adsorption of colour on natural zeolites from “Nemetali” mine, Vranjska Banja, Serbia. The process has been analyzed in an adsorption column filled with natural zeolite as the adsorbent. Adsorbents are organic substances, i.e. colour residues from waste waters, left after textile fibres dyeing. The concentration change in waste waters is represented with the parameter of chemical oxygen demand (COD). Two models of diffusion have been considered: diffusion in pores and diffusion in adsorbent phase on solid adsorbent, for different input loads and two zeolite granulations (13 and 35 mm). It was found that the diffusion in zeolite pores that were in adsorbed phase is dominant in this case, which can be explained by large dimensions of used colours’ molecules. This is the reason why its adsorption in zeolite micro pores is minimal, and yet it diffuse well in already adsorbed phase on solid adsorbents. Since this process is slower, it will determine the overall rate of colour adsorption from waste waters. Specific equilibrium capacity, specific dynamic capacity, as well as the level of adsorbent utilization were determined by the use of mass transfer zone concept. It has been shown that the adsorption of organic substances from waste waters is satisfactory, and is around 80%. The highest degree of adsorbent utilization is obtained at the lowest flow of 0.167 cm3 s-1, while the lowest degree of utilization of 30%, is obtained at the highest flow of 3.27 cm3 s-1. Input load has significant influence on the degree of column utilization, while higher values of COD0 result in lower degrees of column utilization. Key words: waste waters, natural zeolite, adsorption, colour adsorption, textile dyes

Comparative analysis between bottled and tap waters as well as its comparison with current Serbian regulations, European Union Directives and World Health Organization standard are shown in this paper. Thirteen bottled waters and fourteen tap waters from the territory of Serbia were analyzed in the Federal Institute for Geosciences and Natural Resources (BGR) laboratory in Berlin, for the purpose of the “Geochemistry of European Bottled Water“ project conducted by EuroGeo Survey Geochemistry (EGS). Macrocomponents (main cations and anions) of ground waters usually reflect on lithogeochemistry of the aquifer, while microcomponents indicate the circulation of ground water through the different lithological environment. Analyzed bottled waters could be classified as those with low mineral content (M500 mg/L) with prevailing HCO3 anion and Na cation. Waters with low mineral content were mainly from limestone and dolomite, while mineral waters mainly originated from magmatic and metamorphic rocks. Higher content of Cs, Li, Ge, Rb and F in bottled waters indicates the importance of the magmatic intrusions influence on their chemical composition. In some waters higher content of B, I, NH4, as well as of Tl and W has been observed which can be attributed to water’s circulation through different lithological complexes. Tap water was mostly obtained from groundwater (from Neogen and alluvial aquifers and karst springs) with rest being those of rivers and surface accumulations. Tap waters from Central Serbia were with low mineral content, with prevailing HCO3 anion and Ca and Mg cations, while waters from Vojvodina, the northern province of Serbia, were with higher mineralization, HCO3-Na. Chemical analyses of the sampled tap waters showed good quality, with exception of waters from the cities of Senta and Zrenjanin in Vojvodina. High values of B (1170 and 895 g/L), As (20.9 and 71.9 g/l), Na (208 and 275 mg/L), as well as EC (715 and 928 S/cm) have been registered in these waters.

A broad range of similarities between HIV-1 gp120 and human proteins-especially those participating in immune responses-highlight gp120 as a pleiotropic protein which can influence many important functions of the human immune system. The molecular mimicry that serves to the human immunodeficiency virus as potent destructive arms against immune system could be the weak point we are in search of over decades. Examples involving sequence and informational similarities of HIV-1 gp120 and immunerelated host cell proteins important for prevention and treatment of HIV infection are presented. .

Introduction: Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals., Objective: The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process., Methods: Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals., Results: Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15-60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development., Conclusions: Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost-benefit of integrating these analyses at this stage of signal management requires further research., (© 2023. The Author(s).)

The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The complete understanding of the genomic contribution to complex traits, diseases, and response to treatments, as well as genomic medicine application to the well-being of all humans will be achieved through the global variome that encompasses fine-scale genetic diversity. Despite significant efforts in recent years, uneven representation still characterizes genomic resources and among the underrepresented European populations are the Western Balkans including the Serbian population. Our research addresses this gap and presents the first ever targeted sequencing dataset of variants in clinically relevant genes. By measuring population differentiation and applying the Principal Component and Admixture analysis we demonstrated that the Serbian population differs little from other European populations, yet we identified several novel and more frequent variants that appear as its unique genetic determinants. We explored thoroughly the functional impact of frequent variants and its correlation with the health burden of the population of Serbia based on a sample of 144 individuals. Our variants catalogue improves the understanding of genetics of modern Serbia, contributes to research on ancestry, and aids in improvements of well-being and health equity. In addition, this resource may also be applicable in neighboring regions and valuable in worldwide functional analyses of genetic variants in individuals of European descent.

Introduction: The analysis of cell-free DNA (cfDNA) for genetic abnormalities is a promising new approach for the diagnosis and prognosis of pancreatic cancer patients. Insights into the molecular characteristics of pancreatic cancer may provide valuable information, leading to its earlier detection and the development of targeted therapies., Material and Methods: We conducted a systematic review and a meta-analysis of studies that reported cfDNA in pancreatic ductal adenocarcinoma (PDAC). The studies were considered eligible if they included patients with PDAC, if they had blood tests for cfDNA/ctDNA, and if they analyzed the prognostic value of cfDNA/ctDNA for patients' survival. The studies published before 22 October 2020 were identified through the PubMED, EMBASE, Web of Science and Cochrane Library databases. The assessed outcomes were the overall (OS) and progression-free survival (PFS), expressed as the log hazard ratio (HR) and standard error (SE). The summary of the HR effect size was estimated by pooling the individual trial results using the Review Manager, version 5.3, Cochrane Collaboration. The heterogeneity was assessed using the Cochran Q test and I 2 statistic., Results: In total, 48 studies were included in the qualitative review, while 44 were assessed in the quantitative synthesis, with the total number of patients included being 3524. Overall negative impacts of cfDNA and KRAS mutations on OS and PFS in PDAC (HR = 2.42, 95% CI: 1.95-2.99 and HR = 2.46, 95% CI: 2.01-3.00, respectively) were found. The subgroup analysis of the locally advanced and metastatic disease presented similar results (HR = 2.51, 95% CI: 1.90-3.31). In the studies assessing the pre-treatment presence of KRAS , there was a moderate to high degree of heterogeneity (I 2 = 87% and I 2 = 48%, for OS and PFS, respectively), which was remarkably decreased in the analysis of the studies measuring post-treatment KRAS (I 2 = 24% and I 2 = 0%, for OS and PFS, respectively). The patients who were KRAS positive before but KRAS negative after treatment had a better prognosis than the persistently KRAS -positive patients (HR = 5.30, 95% CI: 1.02-27.63)., Conclusion: The assessment of KRAS mutation by liquid biopsy can be considered as an additional tool for the estimation of the disease course and outcome in PDAC patients.

For the last couple of decades, there has been a significant growth in sequencing data, leading to an extraordinary increase in the number of gene variants. This places a challenge on the bioinformatics research community to develop and improve computational tools for functional annotation of new variants. Genes coding for epigenetic regulators have important roles in cancer pathogenesis and mutations in these genes show great potential as clinical biomarkers, especially in hematologic malignancies. Therefore, we developed a model that specifically focuses on these genes, with an assumption that it would outperform general models in predicting the functional effects of amino acid substitutions. EpiMut is a standalone software that implements a sequence based alignment-free method. We applied a two-step approach for generating sequence based features, relying on the biophysical and biochemical indices of amino acids and the Fourier Transform as a sequence transformation method. For each gene in the dataset, the machine learning algorithm-Naïve Bayes was used for building a model for prediction of the neutral or disease-related status of variants. EpiMut outperformed state-of-the-art tools used for comparison, PolyPhen-2, SIFT and SNAP2. Additionally, EpiMut showed the highest performance on the subset of variants positioned outside conserved functional domains of analysed proteins, which represents an important group of cancer-related variants. These results imply that EpiMut can be applied as a first choice tool in research of the impact of gene variants in epigenetic regulators, especially in the light of the biomarker role in hematologic malignancies. EpiMut is freely available at https://www.vin.bg.ac.rs/180/tools/epimut.php., Competing Interests: The authors have declared that no competing interests exist.

Based on the finding that a central antihypertensive agent with high affinity for I1-type imidazoline receptors - rilmenidine, shows cytotoxic effects on cultured cancer cell lines, it has been suggested that imidazoline receptors agonists might have a therapeutic potential in the cancer therapy. Nevertheless, potential rilmenidine side effects caused by activation of α-adrenoceptors, or other associated receptors and enzymes, might hinder its therapeutic benefits. Considering that human α-adrenoceptors belong to the rhodopsin-like class A of G-protein-coupled receptors (GPCRs) it is reasonable to assume that imidazolines might have the affinity for other receptors from the same class. Therefore, to investigate possible off-target effects of imidazoline ligands we have prepared a reverse docking protocol on class A GPCRs, using imidazoline ligands and their decoys. To verify our in silico results, three ligands with high scores and three ligands with low scores were tested for antagonistic activity on α 2 - adrenoceptors., (© 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Motivation: Proteins containing tandem repeats (TRs) are abundant, frequently fold in elongated non-globular structures and perform vital functions. A number of computational tools have been developed to detect TRs in protein sequences. A blurred boundary between imperfect TR motifs and non-repetitive sequences gave rise to necessity to validate the detected TRs., Results: Tally-2.0 is a scoring tool based on a machine learning (ML) approach, which allows to validate the results of TR detection. It was upgraded by using improved training datasets and additional ML features. Tally-2.0 performs at a level of 93% sensitivity, 83% specificity and an area under the receiver operating characteristic curve of 95%., Availability and Implementation: Tally-2.0 is available, as a web tool and as a standalone application published under Apache License 2.0, on the URL https://bioinfo.crbm.cnrs.fr/index.php? route=tools&tool=27. It is supported on Linux. Source code is available upon request., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the 'dark' proteome., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function., Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory., Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β 2 -adrenergic receptor (β 2 -AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β 2 -AR were analysed using the informational spectrum method (ISM) and β 2 -AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β 2 -AR:P3 complex of ΔG = (-7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β 2 -AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC 50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β 2 -AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β 2 -AR.

Summary: Although various tools for Gene Ontology (GO) term enrichment analysis are available, there is still room for improvement. Hence, we present DiNGO, a standalone application based on an open source code from BiNGO, a widely-used application to assess the overrepresentation of GO categories. Besides facilitating GO term enrichment analyses, DiNGO has been developed to allow for convenient Human Phenotype Ontology (HPO) term overrepresentation investigation. This is an important contribution considering the increasing interest in HPO in scientific research and its potential in clinical settings. DiNGO supports gene/protein identifier conversion and an automatic updating of GO and HPO annotation resources. Finally, DiNGO can rapidly process a large amount of data due to its multithread design., Availability and Implementation: DiNGO is implemented in the JAVA language, and its source code, example datasets and instructions are available on GitHub: https://github.com/radoslav180/DiNGO. A pre-compiled jar file is available at: https://www.vin.bg.ac.rs/180/tools/DiNGO.php., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Over the last decade, various machine learning (ML) and statistical approaches for protein-protein interaction (PPI) predictions have been developed to help annotating functional interactions among proteins, essential for our system-level understanding of life. Efficient ML approaches require informative and non-redundant features. In this paper, we introduce novel types of expert-crafted sequence, evolutionary and graph features and apply automatic feature engineering to further expand feature space to improve predictive modeling. The two-step automatic feature-engineering process encompasses the hybrid method for feature generation and unsupervised feature selection, followed by supervised feature selection through a genetic algorithm (GA). The optimization of both steps allows the feature-engineering procedure to operate on a large transformed feature space with no considerable computational cost and to efficiently provide newly engineered features. Based on GA and correlation filtering, we developed a stacking algorithm GA-STACK for automatic ensembling of different ML algorithms to improve prediction performance. We introduced a unified method, HP-GAS, for the prediction of human PPIs, which incorporates GA-STACK and rests on both expert-crafted and 40% of newly engineered features. The extensive cross validation and comparison with the state-of-the-art methods showed that HP-GAS represents currently the most efficient method for proteome-wide forecasting of protein interactions, with prediction efficacy of 0.93 AUC and 0.85 accuracy. We implemented the HP-GAS method as a free standalone application which is a time-efficient and easy-to-use tool. HP-GAS software with supplementary data can be downloaded from: http://www.vinca.rs/180/tools/HP-GAS.php .

This study aimed to functionally characterize β 2 -adrenergic (β 2 AR) and insulin receptor (IR) heteromers in regard to β-arrestin 2 (βarr2) recruitment and cAMP signaling and to examine the involvement of the cytoplasmic portion of the IR β chain in heteromerization with β 2 AR. Evidence for β 2 AR:IR:βarr2 complex formation and the specificity of the IR:βarr2 interaction was first provided by bioinfomatics analysis. Receptor-heteromer investigation technology (HIT) then provided functional evidence of β 2 AR:IR heterodimerization by showing isoproterenol-induced but not insulin-induced GFP 2 -βarr2 recruitment to the β 2 AR:IR complex; the IR:βarr2 interaction was found to only be constitutive. The constitutive IR:βarr2 BRET signal (BRET const ) was significantly smaller in cells coexpressing IR-RLuc8 and a GFP 2 -βarr2 1-185 mutant lacking the proposed IR binding domain. β 2 AR:IR heteromerization also influenced the pharmacological phenotype of β 2 AR, i.e., its efficacy in recruiting βarr2 and activating cAMP signaling. Evidence suggesting involvement of the cytoplasmic portion of the IR β chain in the interaction with β 2 AR was provided by BRET 2 saturation and HIT assays using an IR 1-1271 stop mutant lacking the IR C-terminal tail region. For the complex consisting of IR 1-1271-RLuc8:β 2 AR-GFP 2 , saturation was not reached, most likely reflecting random collisions between IR 1-1271 and β 2 AR. Furthermore, in the HIT assay, no substantial agonist-induced increase in the BRET 2 signal was detected that would be indicative of βarr2 recruitment to the IR 1-1271:β 2 AR heteromer. Complementary 3D visualization of β 2 AR:IR provided supporting evidence for stability of the heterotetramer complex and identified amino acid residues involved in β 2 AR:IR heteromerization. This article is part of the Special Issue entitled 'Receptor heteromers and their allosteric receptor-receptor interactions'., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Influenza A virus (IAV) matrix protein 2 (M2), an ion channel, is crucial for virus infection, and therefore, an important anti-influenza drug target. Adamantanes, also known as M2 channel blockers, are one of the two classes of Food and Drug Administration-approved anti-influenza drugs, although their use was discontinued due to prevalent drug resistance. Fast emergence of resistance to current anti-influenza drugs have raised an urgent need for developing new anti-influenza drugs against resistant forms of circulating viruses. Here we propose a simple theoretical criterion for fast virtual screening of molecular libraries for candidate anti-influenza ion channel inhibitors both for wild type and adamantane-resistant influenza A viruses. After in silico screening of drug space using the EIIP/AQVN filter and further filtering of drugs by ligand based virtual screening and molecular docking we propose the best candidate drugs as potential dual inhibitors of wild type and adamantane-resistant influenza A viruses. Finally, guanethidine, the best ranked drug selected from ligand-based virtual screening, was experimentally tested. The experimental results show measurable anti-influenza activity of guanethidine in cell culture.

Background: The significant number of protein-protein interactions (PPIs) discovered by harnessing concomitant advances in the fields of sequencing, crystallography, spectrometry and two-hybrid screening suggests astonishing prospects for remodelling drug discovery. The PPI space which includes up to 650 000 entities is a remarkable reservoir of potential therapeutic targets for every human disease. In order to allow modern drug discovery programs to leverage this, we should be able to discern complete PPI maps associated with a specific disorder and corresponding normal physiology., Objective: Here, we will review community available computational programs for predicting PPIs and web-based resources for storing experimentally annotated interactions., Methods: We compared the capacities of prediction tools: iLoops, Struck2Net, HOMCOS, COTH, PrePPI, InterPreTS and PRISM to predict recently discovered protein interactions., Results: We described sequence-based and structure-based PPI prediction tools and addressed their peculiarities. Additionally, since the usefulness of prediction algorithms critically depends on the quality and quantity of the experimental data they are built on; we extensively discussed community resources for protein interactions. We focused on the active and recently updated primary and secondary PPI databases, repositories specialized to the subject or species, as well as databases that include both experimental and predicted PPIs., Conclusion: PPI complexes are the basis of important physiological processes and therefore, possible targets for cell-penetrating ligands. Reliable computational PPI predictions can speed up new target discoveries through prioritization of therapeutically relevant protein-protein complexes for experimental studies., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency.

Coronary artery disease (CAD) and myocardial infarction (MI) are recognized as leading causes of mortality in developed countries. Although typically associated with behavioral risk factors, such as smoking, sedentary lifestyle, and poor dietary habits, such vascular phenotypes have also long been recognized as being related to genetic background. We review the currently available data concerning genetic markers for CAD in English and non-English articles with English abstracts published between 2003 and 2018. As genetic testing is increasingly available, it may be possible to identify adequate genetic markers representing the risk profile and to use them in a clinical setting.

The Ebola virus outbreak in West Africa 2015 and Congo 2017, point out an urgent need for development of drugs against this important pathogen. Previously, by repurposing virtual screening of 6438 drugs from DrugBank, ibuprofen was selected as a possible inhibitor of the Ebola virus infection. The results of an additional docking analysis as well as experimental results showing measurable anti-Ebola effect of ibuprofen in cell culture suggest ibuprofen as a promising molecular template for the development of drugs for treatment of the infection by Ebola virus.

The TRI_tool, a sequence-based web tool for prediction of protein interactions in the human transcriptional regulation, is intended for biomedical investigators who work on understanding the regulation of gene expression. It has an improved predictive performance due to the training on updated, human specific, experimentally validated datasets. The TRI_tool is designed to test up to 100 potential interactions with no time delay and to report both probabilities and binarized predictions., Availability and Implementation: http://www.vin.bg.ac.rs/180/tools/tfpred.php CONTACT: vladaper@vinca.rs; nevenav@vinca.rsSupplementary information: Supplementary data are available at Bioinformatics online., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Influenza A virus (IAV) subtypes against which little or no pre-existing immunity exists in humans represent a serious threat to global public health. Monitoring of IAV in animal hosts is essential for early and rapid detection of potential pandemic IAV strains to prevent their spread. Recently, the increased pandemic potential of the avian-like swine H1N1 IAV A/swine/Guangdong/104/2013 has been suggested. The virus is infectious in humans and the general population seems to lack neutralizing antibodies against this virus. Here we present an in silico analysis that shows a strong human propensity of this swine virus further confirming its pandemic potential. We suggest mutations which would further enhance its human propensity. We also propose conserved antigenic determinants which could serve as a component of a prepandemic vaccine. The bioinformatics tool, which can be used to further monitor the evolution of swine influenza viruses towards a pandemic virus, are described here and are made publically available (http://www.vin.bg.ac.rs/180/tools/iav_mon.php; http://www.biomedprotection.com/iav_mon.php)., Competing Interests: The authors have declared that no competing interests exist.

Recent outbreaks of NDM-1-positive Entero-bacteriaceae in Great Britain and India and the highly pathogenic Escherichia coli strain EHEC O104:H4 in Germany and some other E.U. countries point out an urgent need for the ability to decide on appropriate antibiotics to treat multi-drug-resistant (MDR) bacteria. Here we propose a simple criterion for choosing antibiotics based on characteristics of electron donor and acceptor properties. Using molecular descriptors, such as electron-ion interaction potential (EIIP) and average quasi-valence number (AQVN), which can describe potential long-range interactions between therapeutic molecules and their targets, we have been able to suggest appropriate antibiotics for treatment of MDR bacterial infections. To demonstrate the prospective usefulness of these molecular descriptors we have used this informatics system to propose that pleuromutilins and nitrofurans could be effective against of NDM-1-positive Enterobacteriacea and that aminoglycosides, macrolides and pluromutilins (and possibly nitrofurans) could be suitable for treatment of the highly pathogenic Escherichia coli strain EHEC O104:H4. Similarly, because of their specific electronic properties, we can also suggest antibiotics that could be potentially effective against other MDR bacteria. The proposed antibiotics should be further evaluated for their treatment potentials., Competing Interests: Conflict of interests: The authors have no conflicts of interest to report., (Copyright: © 2016, Veljkovic et al. Applied Systems.)

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging., Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2., Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.

The clonidine-like central antihypertensive agent rilmenidine, which has high affinity for I1-type imidazoline receptors (I1-IR) was recently found to have cytotoxic effects on cultured cancer cell lines. However, due to its pharmacological effects resulting also from α2-adrenoceptor activation, rilmenidine cannot be considered a suitable anticancer drug candidate. Here, we report the identification of novel rilmenidine-derived compounds with anticancer potential and devoid of α2-adrenoceptor effects by means of ligand- and structure-based drug design approaches. Starting from a large virtual library, eleven compounds were selected, synthesized and submitted to biological evaluation. The most active compound 5 exhibited a cytotoxic profile similar to that of rilmenidine, but without appreciable affinity to α2-adrenoceptors. In addition, compound 5 significantly enhanced the apoptotic response to doxorubicin, and may thus represent an important tool for the development of better adjuvant chemotherapeutic strategies for doxorubicin-insensitive cancers., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Imidazoline I1 receptor signaling is associated with pathways that regulate cell viability leading to varied cell-type specific phenotypes. We demonstrated that the antihypertensive drug rilmenidine, a selective imidazoline I1 receptor agonist, modulates proliferation and stimulates the proapoptotic protein Bax thus inducing the perturbation of the mitochondrial pathway and apoptosis in human leukemic K562 cells. Rilmenidine acts through a mechanism which involves deactivation of Ras/MAP kinases ERK, p38 and JNK. Moreover, rilmenidine renders K562 cells, which are particularly resistant to chemotherapeutic agents, susceptible to the DNA damaging drug doxorubicin. The rilmenidine co-treatment with doxorubicin reverses G2/M arrest and triggers apoptotic response to DNA damage. Our data offer new insights into the pathways associated with imidazoline I1 receptor activation in K562 cells suggesting rilmenidine as a valuable tool to deepen our understanding of imidazoline I1 receptor signaling in hematologic malignancies and to search for medicinally active agents., (Copyright © 2015 Elsevier B.V. All rights reserved.)