BackgroundSince there is no effective treatment or vaccine against the congenital cytomegalovirus (cCMV) infection, knowledge and awareness of medical doctor’s (MDs) especially family doctors are essential for preventive strategies and it also seems to be usually ignored by healthcare providers. Aim of this study was to investigate awareness of MDs about cCMV infection in Iran.MethodsA single page questionnaire was randomly distributed among 450 MDs including general practitioners, pediatricians, gynecologists, internal and other medical specialists concerning of their knowledge in clinical presentation, diagnosis, prevention, prognosis, epidemiology, transmission, and management of cCMV infection. All statistical analyses were performed using SPSS version 16.ResultsMore than half of questionnaire recipients refused to take part in any of the questionnaire items. The most of the respondents were agreed for newborn CMV screening tests and mandatory CMV test for women trying to get pregnant, which, are not routinely tested. The knowledge of general practitioners about cCMV was less than usual. The field of expertise had a profound effect in this survey, but age and gender did not.ConclusionsOur results indicated that the knowledge of cCMV infection, especially among family doctors contains several gaps. Urgent action is required to improve family doctor’s knowledge of CMV infection. Surveys to evaluate CMV awareness among MDs, healthcare professionals and women of childbearing age are proposed.Electronic supplementary materialThe online version of this article (10.1186/s13052-018-0470-4) contains supplementary material, which is available to authorized users.

Background: Functional cure for Hepatitis B virus (HBV) by inhibiting HBV surface antigen (HBsAg) is crucial. We aimed to develop a predictive quantitative structure-activity relationship (QSAR) model on a ligand-based pharmacophore (LBP) derived from already known HBsAg secretion inhibitors in the present study.Methods: A LBP model was developed using active HBsAg secretion inhibitors as both trainings- and test-sets using LigandScout v3.12 software. The best model with the highest score was used for high throughput screening (HTS) screening of a virtual library comprising 720,000 compounds. A QSAR model was developed by a stepwise multiple linear regression (MLR) on ~2700 descriptors with a confidence interval (CI) of 95%. The test set validated the QSAR model. The goodness of fit statistics evaluated the fitness of the model. A comparable R2 and adjusted R2 were considered as the lack of overfitting. Further RMSE and Q2 statistics were measured for testing the model on the validation set. Principal component analysis (PCA) was also evaluated to estimate the predictor variables' associations and impact on the model.Results: 34 active anti-HBsAg compounds were used to develop an LBP model. 9/34 of compounds with higher clustering pharmacophore-fit scores were tagged as the training set, and the rest of the inhibitors were used as the test set. The best model had a 0.8832 fit score. HTS resulted in 10 potential hit compounds with a fit score of 101.44±0.65. A QSAR model was developed with two response variables, including Yindex and GATS8m, with substantial variance information (p < 0.05). The model was well fitted (R2 = 0.9563, MSE = 0.0023). The model was not predictive on the test set (Q2 = 0.00, RMSE = 0.8153). The PCA results of two factors demonstrated a substantial variance data of both predictor variables. Conclusion: The present study showed a reliable pharmacophore modeling based on known active inhibitors of HBsAg and a well-fitted predictive QSAR model on the LBP. The model can be applied to the chemical libraries fitted to the LBP model, and the QSAR equation would estimate the biological activities of the hit compounds with 95.63% accuracy with only two Yindex and GATS8m descriptors.

Background and objectives: Cyclophilin A (CypA) is involved in various human biological processes. Its role in many pathological conditions makes it a promising target for treating human diseases, such as viral infections. The aim of the present study was to investigate docking of CypA mutants with its potential inhibitors using molecular dynamic simulation ((MDS). Methods: The crystallographic structure of CypA was extracted from the protein database (PDB). Important CypA substitutions were obtained from the literature. CypA inhibitors were taken from chemical databases. The affinity and binding sites of the compounds to CypA and its mutants were also scaled through Autodock Vina. Root-mean-square deviation (RMSD), radios gyration, Lenard-jones potential, and hydrogen bonding were investigated by using MDS for 600 ps. Results:The findings revealed that SangfA and HBF-0259 had more affinity to the CypA (-7.8Kcal/mol and -7.5Kcal/mol, respectively). Conformational changes were observed in CypA W121A/F mutants. SangfA complexed with CypA and its mutants had relatively stable RMSD. Higher Lenard-Jones potential has been observed in the interaction of SangfA to W121A, HBF-0259 to M61, and SCY-635 to H70F. The SangfA had a higher HBs ratio with CypA. Conclusion: Given the higher affinity of SangfA and HBF-0259 to CypA and its mutants, they would influence the stability of the protein. RMSD analysis revealed that SangfA is probably ligated to CypA and its mutants, which are relatively stable. Substitution at W121 residue would reduce inhibitor binding to CypA.