pre-clinical assessment of pharmacological and molecular properties

SARS-CoV-2, the cause of the COVID-19 pandemic, exploits host cell proteins for viral entry into human lung cells. One of them, the protease TMPRSS2, is required to activate the viral spike protein (S). Even though two inhibitors, camostat and nafamostat, are known to inhibit TMPRSS2 and block cell entry of SARS-CoV-2, finding further potent therapeutic options is still an important task. In this study, we report that a late-stage drug candidate, otamixaban, inhibits SARS-CoV-2 cell entry. We show that otamixaban suppresses TMPRSS2 activity and SARS-CoV-2 infection of a human lung cell line, although with lower potency than camostat or nafamostat. In contrast, otamixaban inhibits SARS-CoV-2 infection of precision cut lung slices with the same potency as camostat. Furthermore, we report that otamixaban's potency can be significantly enhanced by (sub-) nanomolar nafamostat or camostat supplementation. Dominant molecular TMPRSS2-otamixaban interactions are assessed by extensive 109 μs of atomistic molecular dynamics simulations. Our findings suggest that combinations of otamixaban with supplemental camostat or nafamostat are a promising option for the treatment of COVID-19

A community effort in SARS-CoV-2 drug discovery.

peer reviewedThe COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against Covid-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments.R-AGR-3826 - COVID19-14715687-CovScreen (01/06/2020 - 31/01/2021) - GLAAB Enric

Infekcije uzrokovane klamidijama

Bakterije roda Chlamydia sitne su (250-1.000 nm), kokoidne i nepokretne. Zbog svojih ograničenih metaboličkih sposobnosti klamidije obvezatno parazitiraju u citoplazmi domaćinove stanice. Od ostalih se bakterija razlikuju po svom jedinstevnom načinu razmnožavanja. Poznate su tri vrste patogene za čovjeka Chlamydia trachomatis, Chlamydophila pneumoniae i Chlamydiphila psittaci. Sojevi vrste C. trachomatis patogeni su isključivo za čovjeka te se većinom prenose spolnim kontaktom, uzrokuju trahom, inkluzijski konjuktivitis kod odraslih i novorođenčadi, urogenitalne infekcije, novorođenačku pneumoniju i lymphogranuloma venereum. C. pneumoniae, najčešće uzrokuje faringitis, ali se mogu javiti i sinusitisi, bronhitisi i pneumonija. C. psittaci uzrokuje psitakozu koja se u ljudi očituje klinički različito. Sve se klamidijske infekcije mogu lijeĉiti tetraciklinima i makrolidima. Cilj rada je analizirati rezultate dobivene od 1.1. 2017. do 31.12. 2018. godine na Odjelu za molekularnu dijagnostiku Hrvatskog zavoda za javno zdravstvo. Metoda korištena za dokaz klamidijske infekcije je lančana reakcija polimerazom u stvarnom vremenu (engl. real time polymerase chain reaction – rt-PCR), koja koristi fluorescentnu boju za prikaz proizvodnje produkta amplifikacije u svakom ciklusu PCR reakcije. Od ukupno 26 080 testiranih uzoraka u promatranom periodu, najveći se pozitivitet javlja u dobnoj skupini osoba mlađih od 19 godina (13 od 346, 3.76%). Budući da je većina infekcija asimptomatska, mnoge europske zemlje potiču na češće preventivne preglede, posebice kod mladih spolno aktivnih žena i trudnica

Nasilništvo i samopoimanje u djece osnovnoškolske dobi

Glavni cilj istraživanja bio je ispitati pojavnost nasilnog ponašanja (broj žrtava i nasilnika) među djecom osnovnoškolske dobi. Osim toga, izvršena je usporedba percepcije pojedinih dimenzija samopoimanja (školska kompetentnost, socijalna prihvaćenost, regulacija ponašanja, sportska kompetentnost, tjelesni izgled) te općeg samopoštovanja djevojčica i dječaka kategoriziranih u četiri kategorije (neutralni, nasilnici, žrtve, nasilnici/žrtve). Istraživanje je provedeno na uzorku od 309 učenika petih, šestih, sedmih i osmih razreda dviju osnovnih škola. Primjenjeni su upitnik Nasilnik/Žrtva, D. Olweus (1996) i adaptirana verzija skale (Brajša-Žganec i sur., 2000) za mjerenje različitih aspekata samopomanja koje je razvila S. Harter (1985). Rezultati su pokazali da je od strane školskih kolega zlostavljano (prema kriteriju "2-3 puta mjesečno") ukupno 20,1% sudionika (žrtve). Udio djece koji ispoljavaju nasilno ponašanje "2-3 puta mjesečno" iznosi 17,4% sudionika (nasilnici). Pretpostavka da žrtve imaju nižu razinu općeg samopoštovanja i pojedinih dimenzija dječje slike o sebi za djevojčice je potvrđena na skalama općeg samopoštovanja i percepcije socijalne prihvaćenosti, dok za dječake nije potvrđena samo na skali sportske kompetentnosti

Infekcije uzrokovane klamidijama

Bakterije roda Chlamydia sitne su (250-1.000 nm), kokoidne i nepokretne. Zbog svojih ograničenih metaboličkih sposobnosti klamidije obvezatno parazitiraju u citoplazmi domaćinove stanice. Od ostalih se bakterija razlikuju po svom jedinstevnom načinu razmnožavanja. Poznate su tri vrste patogene za čovjeka Chlamydia trachomatis, Chlamydophila pneumoniae i Chlamydiphila psittaci. Sojevi vrste C. trachomatis patogeni su isključivo za čovjeka te se većinom prenose spolnim kontaktom, uzrokuju trahom, inkluzijski konjuktivitis kod odraslih i novorođenčadi, urogenitalne infekcije, novorođenačku pneumoniju i lymphogranuloma venereum. C. pneumoniae, najčešće uzrokuje faringitis, ali se mogu javiti i sinusitisi, bronhitisi i pneumonija. C. psittaci uzrokuje psitakozu koja se u ljudi očituje klinički različito. Sve se klamidijske infekcije mogu lijeĉiti tetraciklinima i makrolidima. Cilj rada je analizirati rezultate dobivene od 1.1. 2017. do 31.12. 2018. godine na Odjelu za molekularnu dijagnostiku Hrvatskog zavoda za javno zdravstvo. Metoda korištena za dokaz klamidijske infekcije je lančana reakcija polimerazom u stvarnom vremenu (engl. real time polymerase chain reaction – rt-PCR), koja koristi fluorescentnu boju za prikaz proizvodnje produkta amplifikacije u svakom ciklusu PCR reakcije. Od ukupno 26 080 testiranih uzoraka u promatranom periodu, najveći se pozitivitet javlja u dobnoj skupini osoba mlađih od 19 godina (13 od 346, 3.76%). Budući da je većina infekcija asimptomatska, mnoge europske zemlje potiču na češće preventivne preglede, posebice kod mladih spolno aktivnih žena i trudnica

Possibility of Determining Reliability and Construct Validity of Three Rating Scales for Some Aspects of the Preschool Children’s Giftedness

U praksi se koristi manji broj skala procjene za utvrđivanje različitih aspekta darovitosti predškolske djece u uvjetima njihova boravka u dječjem vrtiću, a njihove metrijske karakteristike su još rjeđe provjeravane. Cilj ovog istraživanja bio je utvrditi pouzdanost i valjanost tri skale procjene određenih aspekata darovitosti djece, te međusobnu povezanost njihovih dimenzija. Ispitan je namjerni uzorak djece (74) starije predškolske dobi iz Dječjeg vrtića „Ivanić Grad“, a primijenjene su tri skale za procjenu: ponašanja karakterističnih za darovito dijete, likovne te glazbene darovitosti. Rezultati su pokazali da su sve skale procjene zadovoljavajuće pouzdane i konstruktno valjane. Utvrdili smo postojanje latentnih dimenzija u osnovi različitih aspekata darovitosti djeteta: dva faktora defi niraju likovnu darovitost, a po jedan glazbenu darovitost te ponašanja karakteristična za darovito dijete. Sve dimenzije tri različite skale procjene darovitosti su međusobno statistički značajno i pozitivno povezane. Međutim, mogućnost generalizacije rezultata ovog istraživanja je mala.In practice, a small number of scales were used to determine various aspects of gifted preschool children, in conditions of their stay in kindergarten; their psychometric properties are very rarely examined. The aim of this study was to determine the reliability and validity of three scales for certain aspects of the children’s giftedness children and correlations of their dimensions. We examined an intentional sample (74) of older preschool children from Kindergarten “Ivanic Grad,” the three scales were used to assess: the behavior characteristic of a gifted child, artistic and musical talent. The results showed that all scales used in research were satisfactorily reliable and construct valid. We found the existence of latent dimensions in various aspects of children’s giftedness, as following: two factors define the artistic talent, one defines musical talent, and one defines behaviors characteristic for the gifted child. All dimensions of three different estimation scales for the assessment of giftedness were statistically significantly and positively related. However, the possibility of generalization of the results of this study is small

Biological vs. Crystallographic protein interfaces : An overview of computational approaches for their classification

Complexes between proteins are at the basis of almost every process in cells. Their study, from a structural perspective, has a pivotal role in understanding biological functions and, importantly, in drug development. X-ray crystallography represents the broadest source for the experimental structural characterization of protein-protein complexes. Correctly identifying the biologically relevant interface from the crystallographic ones is, however, not trivial and can be prone to errors. Over the past two decades, computational methodologies have been developed to study the differences of those interfaces and automatically classify them as biological or crystallographic. Overall, protein-protein interfaces show differences in terms of composition, energetics and evolutionary conservation between biological and crystallographic ones. Based on those observations, a number of computational methods have been developed for this classification problem, which can be grouped into three main categories: Energy-, empirical knowledge-and machine learning-based approaches. In this review, we give a comprehensive overview of the training datasets and methods so far implemented, providing useful links and a brief description of each method

Biological vs. Crystallographic protein interfaces : An overview of computational approaches for their classification

Complexes between proteins are at the basis of almost every process in cells. Their study, from a structural perspective, has a pivotal role in understanding biological functions and, importantly, in drug development. X-ray crystallography represents the broadest source for the experimental structural characterization of protein-protein complexes. Correctly identifying the biologically relevant interface from the crystallographic ones is, however, not trivial and can be prone to errors. Over the past two decades, computational methodologies have been developed to study the differences of those interfaces and automatically classify them as biological or crystallographic. Overall, protein-protein interfaces show differences in terms of composition, energetics and evolutionary conservation between biological and crystallographic ones. Based on those observations, a number of computational methods have been developed for this classification problem, which can be grouped into three main categories: Energy-, empirical knowledge-and machine learning-based approaches. In this review, we give a comprehensive overview of the training datasets and methods so far implemented, providing useful links and a brief description of each method

Distinguishing crystallographic from biological interfaces in protein complexes: role of intermolecular contacts and energetics for classification

Abstract Background Study of macromolecular assemblies is fundamental to understand functions in cells. X-ray crystallography is the most common technique to solve their 3D structure at atomic resolution. In a crystal, however, both biologically-relevant interfaces and non-specific interfaces resulting from crystallographic packing are observed. Due to the complexity of the biological assemblies currently tackled, classifying those interfaces, i.e. distinguishing biological from crystal lattice interfaces, is not trivial and often prone to errors. In this context, analyzing the physico-chemical characteristics of biological/crystal interfaces can help researchers identify possible features that distinguish them and gain a better understanding of the systems. Results In this work, we are providing new insights into the differences between biological and crystallographic complexes by focusing on “pair-properties” of interfaces that have not yet been fully investigated. We investigated properties such intermolecular residue-residue contacts (already successfully applied to the prediction of binding affinities) and interaction energies (electrostatic, Van der Waals and desolvation). By using the XtalMany and BioMany interface datasets, we show that interfacial residue contacts, classified as a function of their physico-chemical properties, can distinguish between biological and crystallographic interfaces. The energetic terms show, on average, higher values for crystal interfaces, reflecting a less stable interface due to crystal packing compared to biological interfaces. By using a variety of machine learning approaches, we trained a new interface classification predictor based on contacts and interaction energetic features. Our predictor reaches an accuracy in classifying biological vs crystal interfaces of 0.92, compared to 0.88 for EPPIC (one of the main state-of-the-art classifiers reporting same performance as PISA). Conclusion In this work we have gained insights into the nature of intermolecular contacts and energetics terms distinguishing biological from crystallographic interfaces. Our findings might have a broader applicability in structural biology, for example for the identification of near native poses in docking. We implemented our classification approach into an easy-to-use and fast software, freely available to the scientific community from http://github.com/haddocking/interface-classifier