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Presentation given at the Database session of the 12th International Conference on Atomic and Molecular Data and Their Applications (ICAMDATA), {"references":["Albert, D.; Antony, B.; Ba, Y.A.; Babikov, Y.L.; Bollard, P.; Boudon, V.; Delahaye, F.; Del Zanna, G.; Dimitrijević, M.S.; Drouin, B.J.; Dubernet, M.-L.; Duensing, F.; Emoto, M.; Endres, C.; Fazliev, A.Z.; Glorian, J.-M.; Gordon, I.E.; Gratier, P.; Hill, C.; Jevremović, D.; Joblin, C.; Kwon, D.-H.; Kochanov, R.V.; Krishnakumar, E.; Leto, G.; Loboda, P.A.; Lukashevskaya, A.A.; Lyulin, O.M.; Marinković, B.P.; Markwick, A.; Marquart, T.; Mason, N.J.; Mendoza, C.; Millar, T.J.; Moreau, N.; Morozov, S.V.; Möller, T.; Müller, H.S.P.; Mulas, G.; Murakami, I.; Pakhomov, Y.; Palmeri, P.; Penguen, J.; Perevalov, V.I.; Piskunov, N.; Postler, J.; Privezentsev, A.I.; Quinet, P.; Ralchenko, Y.; Rhee, Y.-J.; Richard, C.; Rixon, G.; Rothman, L.S.; Roueff, E.; Ryabchikova, T.; Sahal-Bréchot, S.; Scheier, P.; Schilke, P.; Schlemmer, S.; Smith, K.W.; Schmitt, B.; Skobelev, I.Y.; Srecković, V.A.; Stempels, E.; Tashkun, S.A.; Tennyson, J.; Tyuterev, V.G.; Vastel, C.; Vujčić, V.; Wakelam, V.; Walton, N.A.; Zeippen, C.; Zwölf, C.M. A Decade with VAMDC: Results and Ambitions. Atoms 2020, 8, 76. https://doi.org/10.3390/atoms8040076"]}

Scrobicularia plana is a coastal and estuarine bivalve widely used in ecotoxicological studies. However, the underlying molecular mechanisms for S. plana pollutant responses are hardly known due to the lack of molecular databases. Thus, in this study we present a holistic approach to assess a robust reference transcriptome and proteome of this clam. A mixture of control and metal-exposed individuals was used for mRNA isolation. Four sets of high quality filtered preprocessed reads were generated (two quality scores and two sequenced lengths) and assembled with Mira, Ray and Trinity algorithms. The sixty-four generated assemblies were refined, filtered and evaluated for their proteomic quality. Eight assemblies presented top Detonate scores but one was selected due to its compactness and biological representation, which was generated: (i) from the highest quality dataset (Q20L100), (ii) using Trinity algorithm with all k-mers (AtKa), (iii) removing redundancy by CD-HIT (RR80), and (iv) filtering out poor contigs (F), that was subsequently named Q20L100AtKaRR80F. S. plana proteomic analysis revealed 10,017 peptide groups that corresponded to 2066 proteins with a wide coverage of molecular functions and biological processes, confirming the strength of the database generated., This study was supported by the Ministry of Economy and Competitiveness, Spain (CTM2016-75908-R). We would like to thank Dr. Mercedes Cousinou and Ms. Laura Redondo (Genomic Unit, SCAI, UCO) for their technical help in transcriptome sequencing. A.M. Herruzo-Ruiz received a predoctoral contract of the University of Cordoba (“Plan Propio”).

Background:Multi-valent based vaccines have advantage over conventional vaccines because of its multi-faceted action targeted at antigen; thereby raising hope of a more sustained actions against allergens. Escherichia coli(E. coli)is a bacterium that is commonly found in the gut of humans and warm-blooded animals. An increasing number of outbreaks are associated with the consumption of fruits and vegetables (including sprouts, spinach, lettuce, coleslaw, and salad) thereby contamination may be due to contact with faeces from domestic or wild animals at some stages during cultivation or handling. Due to the reported increase in resistance to antibiotics used forEscherichia colicontrol; an effective vaccine is a would-be alternative of proven interest. Hence, a need for a rational, strategic, and efficient vaccine candidate againstE.coliis of paramount necessity by the use of the most current bioinformatics tools to achieve this task.Method:In this study, immunoinformatics tools mined from diverse molecular databases were used for a novel putative epitope based oral vaccine againstE.coli. The prospective vaccine proteins were carefully screened and validated to achieve a high thorough-put three-dimensional protein structure. The eventual propsective vaccine candidate proteins was evaluated for its non-allergenicity, antigenicity, solubility, appropriate molecular weight testing and isoelectric point evaluation.Conclusion:The resultant vaccine candidate could serve as a promisinganti-E.colivaccine candidate. Immunoinformatics is a new field over pharmaco-therapeutics; this newest technology should continue to be a rescue from age-long traditional approach in vaccine developments.

Molecular databases have enabled scientists across the globe to collaborate and contribute to the growth of the databases The current form of the databases involves researcher input which is acted upon by algorithms developed by bioinformaticians leading to outputs for researchers the database The rapid rise of artificial intelligence (Al) can be used to enhance molecular databases through incorporation of deep learning and deep reasoning to enable the molecular databases to partially self-maintain, bringing novel applications and the potential for an improved user-friendly interface for researchers who are not trained in bioinformatics to generate data that require bioinformatics-related analysis The current challenge of big data analysis may be ameliorated by development of Al that performs a comparative analysis of recently submitted big data sets against existing similar data sets and possibly suggests areas that need modification in terms of analysis for bioinformaticians to develop

Per and polyfluoroalkyl substances (PFASs) are an important class of organic pollutants. Many diverse PFASs are used in commerce and most are not amenable to conventional targeted chemical analysis due to lack of reference standards. Therefore, methods for elucidating the chemical structure of previously unreported or unexpected PFASs in the environment rely extensively on high-resolution mass spectrometry (HRMS). High-throughput structure identification by HRMS is hindered by a lack of PFAS molecular databases and tandem mass spectral libraries. Here, we report a new approach for generating an environmentally relevant PFAS molecular database constructed from curated structure lists and biotic/abiotic in silico predicted transformation products. Further, we have generated a predicted tandem mass spectral library using computational mass spectrometry tools. Results demonstrate the utility of the generated database and approach for identifying PFASs in HRMS-enabled suspect- and nontarget screening studies.

International audience; The BASECOL database has been created and scientifically enriched since 2004. It contains collisional excitation rate coefficients of molecules for application to the interstellar medium and to cometary atmospheres. Recently, major technical updates have been performed in order to be compliant with international standards for management of data and in order to provide a more friendly environment to query and to present the data. The current paper aims at presenting the key features of the technical updates and to underline the compatibility of BASECOL database with the Virtual Atomic and Molecular Data Center. This latter aims to interconnect atomic and molecular databases, thus providing a single location where users can access atomic and molecular data.

A biological database is a big, structured body of continuous information, generally connected with computerized software intended to update, query, and recover information elements deposited within the framework. A straightforward database could be a single folder comprising several data, each carrying the same number of data. Such famous databases are GenBank from the National Center for Biotechnology Information, SwissProt from the Swiss Institute of Bioinformatics and PIR from the Protein Information Resource. Biological databases are bibliotheques of life science data, gathered from science studies, published literature, high-performance experimental technology, and computational analysis. Here we brefly described some recently published molecular databases.

The inhibition of dipeptidyl peptidase-IV (DPP-IV) has emerged over the last decade as one of the most effective treatments for type 2 diabetes mellitus, and consequently (a) 11 DPP-IV inhibitors have been on the market since 2006 (three in 2015), and (b) 74 noncovalent complexes involving human DPP-IV and drug-like inhibitors are available at the Protein Data Bank (PDB). The present review aims to (a) explain the most important activity cliffs for DPP-IV noncovalent inhibition according to the binding site structure of DPP-IV, (b) explain the most important selectivity cliffs for DPP-IV noncovalent inhibition in comparison with other related enzymes (i.e., DPP8 and DPP9), and (c) use the information deriving from this activity/selectivity cliff analysis to suggest how virtual screening protocols might be improved to favor the early identification of potent and selective DPP-IV inhibitors in molecular databases (because they have not succeeded in identifying selective DPP-IV inhibitors with IC50 ≤ 100 nM). All these goals are achieved with the help of available homology models for DPP8 and DPP9 and an analysis of the structure-activity studies used to develop the noncovalent inhibitors that form part of some of the complexes with human DPP-IV available at the PDB.

Design and development of antioxidant supplements constitute an essential aspect of research in order to derive molecules that would help to combat the free radical invasion to the human body and curb oxidative stress related diseases. The present work deals with the development of in silico models for a series of thiazolidine derivatives having antioxidant potential. The objective of the work is to obtain models that would help to design new thazolidine derivatives based on substituent modification and thereby predict their activity profile. The QSAR model thus developed helps in quantification of the extent of contribution of the various molecular fragments towards the activity of the molecules, while the 3D pharmacophore model provides a brief idea of the essential molecular features that help the molecules to interact with the neighbouring free radicals. Both the models have been extensively validated which ensures their predictive ability as well the potential to search molecular databases for selection of thiazolidine derivatives with potent antioxidant activity. The models can thus be utilised effectively for database searching with the aim to isolate active antioxidants belonging to the thiazolidine group.

Large-scale molecular databases play an essential role in the investigation of various subjects such as the development of organic materials, in silico drug design, and data-driven studies with machine learning. We have developed a large-scale quantum chemistry database based on first-principles methods. Our database currently contains the ground-state electronic structures of 3 million molecules based on density functional theory (DFT) at the B3LYP/6-31G* level, and we successively calculated 10 low-lying excited states of over 2 million molecules via time-dependent DFT with the B3LYP functional and the 6-31+G* basis set. To select the molecules calculated in our project, we referred to the PubChem Project, which was used as the source of the molecular structures in short strings using the InChI and SMILES representations. Accordingly, we have named our quantum chemistry database project "PubChemQC" ( http://pubchemqc.riken.jp/ ) and placed it in the public domain. In this paper, we show the fundamental features of the PubChemQC database and discuss the techniques used to construct the data set for large-scale quantum chemistry calculations. We also present a machine learning approach to predict the electronic structure of molecules as an example to demonstrate the suitability of the large-scale quantum chemistry database.

In this essay we want to shed some light on selected subjects of taxonomy that we think are worth looking at: the problems of the taxonomic workforce, the taxonomic knowledge growth based on the use of databases and web-portals and some suggestions for quality improvements in molecular databases for the benefit of the scientific community, conservation practitioners, regulators, policy-makers and citizen-scientists.

BRUSELAS (balanced rapid and unrestricted server for extensive ligand-aimed screening) is a novel, highly efficient web software architecture for 3D shape and pharmacophore searches in off the cuff libraries. A wide panel of shape and pharmacophore similarity algorithms are combined to avoid unbiased results while yielding consensus scoring functions. To evaluate its reliability, BRUSELAS was tested against other similar servers (e.g., USR-VS, SwissSimilarity, ChemMapper) to search for potential antidiabetic drugs. A web tool is developed for users to customize their tasks and is accessible free of any charge or login at http://bio-hpc.eu/software/Bruselas . Source code is available on request.

Multiple computational approaches are employed in order to find potentially strong binders of PAR1 from the two molecular databases: the Specs database containing more than 200,000 commercially available molecules and the traditional Chinese medicine (TCM) database. By combining the use of popular docking scoring functions together with detailed molecular dynamics simulation and protein-ligand free energy calculations, a total of fourteen molecules are found to be potentially strong binders of PAR1. The atomic details in protein-ligand interactions of these molecules with PAR1 are analyzed to help understand the binding mechanism which should be very useful in design of new drugs.

Background: The present study was aimed at designing some potential candidates as HER2 inhibitors used in breast cancer. Methods: An energy optimized pharmacophore (E-pharmacophore) model was developed and used to screen the molecular databases (such as ASINEX and NCI databases) against a six site (ADHRRR) hypothesis. The shape similarity of the retrieved hits was calculated and then filtered applying ADME and Lipinski’s filters. Further, these hits were docked into the crystal structure of HER2 protein (3W32) using Glide XP protocol to obtain the docking poses and XP gscores. The performance of the virtual screening (VS) methods was evaluated using Schrödinger’s decoy set of 1000 molecules. Ranking of the actives in the VS protocol was assessed by a variety of well-established methods including the average rank of actives, EF, ROC, BEDROC, AUAC, and the RIE. The retrieved hits were submitted to Canvas for generating binary fingerprints (dendritic) to identify structural diversity among the hits and clustered on the basis of Tanimoto coefficient using hierarchical clustering. Results: Seven structurally diverse clusters were selected applying above protocol, having XP gscores >-10, and fitness scores > 1, considering top scoring cluster representative from each cluster. The best scoring hit 355682-ASINEX was submitted to Combiglide to discover some better candidates with improved scores. Finally, structural interaction fingerprint (SIFT) analysis was employed to study the binding interaction, which showed H-bond interaction with Met793, Gln791 and Thr854 residues of HER2 protein. Conclusion: The applied methodology and the retrieved hits could be useful in the design of potent inhibitors of HER2 proteins, commonly found to be expressed in the breast cancer patients.

This paper is intended to give a comprehensive overview of the the current status and developments of the Paris Observatory STARK-B, MOLAT and SESAM databases which can be interrogated thanks to interoperability tools. The STARK-B database provides shifting and broadening parameters of different atomic and ionic transitions due to impacts with charged particles (the so-called Stark broadening) for different temperatures and densities. The spectroscopic MOLAT and SESAM databases provide the wavelengths, the oscillator strengths or Einstein spontaneous emission coefficients of H 2 , CO and isotopologues molecules.

Background Latin America harbors some of the most biodiverse countries in the world, including Colombia. Despite the increasing use of cutting-edge technologies in genomics and bioinformatics in several biological science fields around the world, the region has fallen behind in the inclusion of these approaches in biodiversity studies. In this study, we used data mining methods to search in four main public databases of genetic sequences such as: NCBI Nucleotide and BioProject, Pathosystems Resource Integration Center, and Barcode of Life Data Systems databases. We aimed to determine how much of the Colombian biodiversity is contained in genetic data stored in these public databases and how much of this information has been generated by national institutions. Additionally, we compared this data for Colombia with other countries of high biodiversity in Latin America, such as Brazil, Argentina, Costa Rica, Mexico, and Peru. Results In Nucleotide, we found that 66.84% of total records for Colombia have been published at the national level, and this data represents less than 5% of the total number of species reported for the country. In BioProject, 70.46% of records were generated by national institutions and the great majority of them is represented by microorganisms. In BOLD Systems, 26% of records have been submitted by national institutions, representing 258 species for Colombia. This number of species reported for Colombia span approximately 0.46% of the total biodiversity reported for the country (56,343 species). Finally, in PATRIC database, 13.25% of the reported sequences were contributed by national institutions. Colombia has a better biodiversity representation in public databases in comparison to other Latin American countries, like Costa Rica and Peru. Mexico and Argentina have the highest representation of species at the national level, despite Brazil and Colombia, which actually hold the first and second places in biodiversity worldwide. Conclusions Our findings show gaps in the representation of the Colombian biodiversity at the molecular and genetic levels in widely consulted public databases. National funding for high-throughput molecular research, NGS technologies costs, and access to genetic resources are limiting factors. This fact should be taken as an opportunity to foster the development of collaborative projects between research groups in the Latin American region to study the vast biodiversity of these countries using ‘omics’ technologies.

The purpose of this application, under Article 23.9.3, is to conserve current usage of the well-established genus-group name Cryptodacus Hendel, 1914 for a genus of Neotropical fruit flies by suppression of the earlier, unused name Cryptodacus Gundlach, 1862, currently a junior synonym of Arrhyton Gunther, 1858, a genus of snakes, under the plenary power of the Commission, in the interest of nomenclatural stability. Cryptodacus Gundlach has not been used as a valid name since 1883, whereas Cryptodacus Hendel has been used in a significant body of literature relating to fruit fly systematics, morphology and phylogeny and is the currently used name in various name and molecular databases.

The purpose of this application, under Article 23.9.3 of the Code, is to conserve the widely used oribatid mite genus name Collohmannia Sellnick, 1922, which is threatened by the obscure senior subjective synonym Embolacarus Sellnick, 1919. The latter is based on a single fossil species whose type and only known specimen is lost; most subsequent literature citations are simple, unenhanced listings. By contrast, Collohmannia has been used in a significant body of literature relating to morphology, reproductive biology, development, behavior, chemical ecology and phylogeny, as well as appearing in molecular databases. It is proposed that Collohmannia be given precedence over Embolacarus whenever they are considered to be synonyms.

An important role of atomic parameters and cross-sections in stellar spectroscopic analysis is demonstrated on different astrophysical applications: determination of fundamental stellar parameters and chemical composition, Galaxy chemical evolution, exoplanet formation. A range of the required accuracy in laboratory and theoretical data for these studies is discussed. The feedback of the high-precision modern astronomical spectroscopy to the improvement of the laboratory data is underlined. Finally, I review shortly the main atomic and molecular databases containing atomic parameters and cross-sections needed for detailed analysis of high resolution, high signal-to-noise ratio stellar spectra.

Over the past decades, virtual screening has proved itself to be a valuable asset to identify new bioactive compounds. The vast majority of commonly used techniques can be described in three steps: pre-processing the dataset i. e. small (ligands) and eventually larger (receptors) molecules, execute the method and finally analyse the results. Hence, the preparation of ligands is a critical step for success of commonly used virtual screening approaches such as protein-ligand docking, similarity or pharmacophore search. We present here a new workflow, VSPrep, for the pre-processing of small molecules; it is based on freely accessible tools for academics and is integrated within the KNIME platform. It can be used to perform several chemoinformatics tasks such as molecular database cleaning, tautomer and stereoisomer enumeration, focused library design and conformer generation. Additionally, graphical reports of the results are provided to the user as a convenient analysis tool.

Aim: Given that the information about the origin, genetic relationships, and diversity of Montenegrin grapevines is still partial, we performed a detailed analysis of the germplasm in this country using simple sequence repeat (SSR) markers. Our main goal was to determine the identity of cultivars unique to Montenegro and those shared with other countries, especially the neighbouring ones.Methods and results: Seventy samples were collected and 14 genotypes were found. After SSR profile comparison with available molecular databases and literature data, the identity of each genotype was established. Five well-known cultivars were found, the others being minor, lesser-known cultivars.Conclusion: This research provides an overview of the Montenegrin grapevine assortment. There are cultivars shared with other countries, mainly the neighbouring ones, while others are likely native to Montenegro. The Kratošija population (alias Primitivo, Zinfandel and Crljenak Kaštelanski) has a large number of different names in Montenegro and also a wide morphological variability. Therefore, Montenegro is the best candidate as the origin and spreading point of this cultivar.Significance and impact of the study: The present study adds information on the identity, origin, diffusion and variability of some grapevine cultivars, allowing us to reconstruct the history and evolution of national and transnational ampelographic assortment of Montenegro.

Due to role of the Keap1−Nrf2 protein−protein interaction (PPI) in protecting cells from oxidative stress, the development of small molecule inhibitors that inhibit this interaction has arisen as a viable approach to combat maladies caused by oxidative stress, such as cancers, neurodegenerative disease and diabetes. To obtain specific and genuine Keap1−Nrf2 inhibitors, many efforts have been made towards developing new screening approaches. However, there is no inhibitor for this target entering the clinic for the treatment of human diseases. New strategies to identify novel bioactive compounds from large molecular databases and accelerate the developmental process of the clinical application of Keap1−Nrf2 protein−protein interaction inhibitors are greatly needed. In this review, we have summarized virtual screening and other methods for discovering new lead compounds against the Keap1−Nrf2 protein−protein interaction. We also discuss the advantages and limitations of different strategies, and the potential of this PPI as a drug target in disease therapy.

Remote drug loading into nano-liposomes is in most cases the best method for achieving high concentrations of active pharmaceutical ingredients (API) per nano-liposome that enable therapeutically viable API-loaded nano-liposomes, referred to as nano-drugs. This approach also enables controlled drug release. Recently, we constructed computational models to identify APIs that can achieve the desired high concentrations in nano-liposomes by remote loading. While those previous models included a broad spectrum of experimental conditions and dealt only with loading, here we reduced the scope to the molecular characteristics alone. We model and predict API suitability for nano-liposomal delivery by fixing the main experimental conditions: liposome lipid composition and size to be similar to those of Doxil® liposomes. On that basis, we add a prediction of drug leakage from the nano-liposomes during storage. The latter is critical for having pharmaceutically viable nano-drugs. The "load and leak" models were used to screen two large molecular databases in search of candidate APIs for delivery by nano-liposomes. The distribution of positive instances in both loading and leakage models was similar in the two databases screened. The screening process identified 667 molecules that were positives by both loading and leakage models (i.e., both high-loading and stable). Among them, 318 molecules received a high score in both properties and of these, 67 are FDA-approved drugs. This group of molecules, having diverse pharmacological activities, may be the basis for future liposomal drug development.

The ubiquitous role of microRNAs (miRNAs) in a number of pathological processes has suggested that they could act as potential drug targets. RNA-binding small molecules offer an attractive means for modulating miRNA function. The availability of bioassay data sets for a variety of biological assays and molecules in public domain provides a new opportunity toward utilizing them to create models and further utilize them for in silico virtual screening approaches to prioritize or assign potential functions for small molecules. Here, we describe a computational strategy based on machine learning for creation of predictive models from high-throughput biological screens for virtual screening of small molecules with the potential to inhibit microRNAs. Such models could be potentially used for computational prioritization of small molecules before performing high-throughput biological assay.

Correct species identifications are of tremendous importance for invasion ecology, as mistakes could lead to misdirecting limited resources against harmless species or inaction against problematic ones. DNA barcoding is becoming a promising and reliable tool for species identifications, however the efficacy of such molecular taxonomy depends on gene region(s) that provide a unique sequence to differentiate among species and on availability of reference sequences in existing genetic databases. Here, we assembled a list of aquatic and terrestrial non-indigenous species (NIS) and checked two leading genetic databases for corresponding sequences of six genome regions used for DNA barcoding. The genetic databases were checked in 2010, 2012, and 2016. All four aquatic kingdoms (Animalia, Chromista, Plantae and Protozoa) were initially equally represented in the genetic databases, with 64, 65, 69, and 61 % of NIS included, respectively. Sequences for terrestrial NIS were present at rates of 58 and 78 % for Animalia and Plantae, respectively. Six years later, the number of sequences for aquatic NIS increased to 75, 75, 74, and 63 % respectively, while those for terrestrial NIS increased to 74 and 88 % respectively. Genetic databases are marginally better populated with sequences of terrestrial NIS of plants compared to aquatic NIS and terrestrial NIS of animals. The rate at which sequences are added to databases is not equal among taxa. Though some groups of NIS are not detectable at all based on available data—mostly aquatic ones—encouragingly, current availability of sequences of taxa with environmental and/or economic impact is relatively good and continues to increase with time. Electronic supplementary material The online version of this article (doi:10.1007/s10530-016-1134-1) contains supplementary material, which is available to authorized users.