SH2db, an information system for the SH2 domain

SH2 domains are key mediators of phosphotyrosine-based signalling, and therapeutic targets for diverse, mostly oncological, disease indications. They have a highly conserved structure with a central beta sheet that divides the binding surface of the protein into two main pockets, responsible for phosphotyrosine binding (pY pocket) and substrate specificity (pY + 3 pocket). In recent years, structural databases have proven to be invaluable resources for the drug discovery community, as they contain highly relevant and up-to-date information on important protein classes. Here, we present SH2db, a comprehensive structural database and webserver for SH2 domain structures. To organize these protein structures efficiently, we introduce (i) a generic residue numbering scheme to enhance the comparability of different SH2 domains, (ii) a structure-based multiple sequence alignment of all 120 human wild-type SH2 domain sequences and their PDB and AlphaFold structures. The aligned sequences and structures can be searched, browsed and downloaded from the online interface of SH2db (http://sh2db.ttk.hu), with functions to conveniently prepare multiple structures into a Pymol session, and to export simple charts on the contents of the database. Our hope is that SH2db can assist researchers in their day-to-day work by becoming a one-stop shop for SH2 domain related research

The PARP inhibitor rucaparib blocks SARS-CoV-2 virus binding to cells and the immune reaction in models of COVID-19

\ua9 2024 The Author(s). British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.Background and Purpose: To date, there are limited options for severe Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2 virus. As ADP-ribosylation events are involved in regulating the life cycle of coronaviruses and the inflammatory reactions of the host; we have, here, assessed the repurposing of registered PARP inhibitors for the treatment of COVID-19. Experimental Approach: The effects of PARP inhibitors on virus uptake were assessed in cell-based experiments using multiple variants of SARS-CoV-2. The binding of rucaparib to spike protein was tested by molecular modelling and microcalorimetry. The anti-inflammatory properties of rucaparib were demonstrated in cell-based models upon challenging with recombinant spike protein or SARS-CoV-2 RNA vaccine. Key Results: We detected high levels of oxidative stress and strong PARylation in all cell types in the lungs of COVID-19 patients, both of which negatively correlated with lymphocytopaenia. Interestingly, rucaparib, unlike other tested PARP inhibitors, reduced the SARS-CoV-2 infection rate through binding to the conserved 493–498 amino acid region located in the spike-ACE2 interface in the spike protein and prevented viruses from binding to ACE2. In addition, the spike protein and viral RNA-induced overexpression of cytokines was down-regulated by the inhibition of PARP1 by rucaparib at pharmacologically relevant concentrations. Conclusion and Implications: These results point towards repurposing rucaparib for treating inflammatory responses in COVID-19

Biopsia muscular em miastenia grave: estudo histoquímico e morfométrico de 4 casos

Miastenia grave é doença neuromuscular caracterizada por excessiva fatigabilidade da junção muscular e envolve, particularmente, músculos inervados por nervos cranianos. Acredita-se que o defeito esteja localizado na junção neuromuscular. Os autores estudaram os achados histoquímicos e e morfométricos em 4 pacientes com miastenia grave mostrando que as fibras do tipo II eram significativamente menores que as fibras do tipo I

Modelling methods and cross-validation variants in QSAR: a multi-level analysis^$

Prediction performance often depends on the cross- and test validation protocols applied. Several combinations of different cross-validation variants and model-building techniques were used to reveal their complexity. Two case studies (acute toxicity data) were examined, applying five-fold cross-validation (with random, contiguous and Venetian blind forms) and leave-one-out cross-validation (CV). External test sets showed the effects and differences between the validation protocols. The models were generated with multiple linear regression (MLR), principal component regression (PCR), partial least squares (PLS) regression, artificial neural networks (ANN) and support vector machines (SVM). The comparisons were made by the sum of ranking differences (SRD) and factorial analysis of variance (ANOVA). The largest bias and variance could be assigned to the MLR method and contiguous block cross-validation. SRD can provide a unique and unambiguous ranking of methods and CV variants. Venetian blind cross-validation is a promising tool. The generated models were also compared based on their basic performance parameters (r2 and Q2). MLR produced the largest gap, while PCR gave the smallest. Although PCR is the best validated and balanced technique, SVM always outperformed the other methods, when experimental values were the benchmark. Variable selection was advantageous, and the modelling had a larger influence than CV variants.</p