The purpose of this work was to construct a consensus prediction algorithm of ‘aggregation-prone’ peptides in globular proteins, combining existing tools. This allows comparison of the different algorithms and the production of more objective and accurate results. Eleven (11) individual methods are combined and produce AMYLPRED2, a publicly, freely available web tool to academic users (http://biophysics.biol.uoa.gr/AMYLPRED2), for the consensus prediction of amyloidogenic determinants/‘aggregation-prone’ peptides in proteins, from sequence alone. The performance of AMYLPRED2 indicates that it functions better than individual aggregation-prediction algorithms, as perhaps expected. AMYLPRED2 is a useful tool for identifying amyloid-forming regions in proteins that are associated with several conformational diseases, called amyloidoses, such as Altzheimer's, Parkinson's, prion diseases and type II diabetes. It may also be useful for understanding the properties of protein folding and misfolding and for helping to the control of protein aggregation/solubility in biotechnology (recombinant proteins forming bacterial inclusion bodies) and biotherapeutics (monoclonal antibodies and biopharmaceutical proteins).

Linear B-cell epitope prediction research has received a steadily growing interest ever since the first method was developed in 1981. B-cell epitope identification with the help of an accurate prediction method can lead to an overall faster and cheaper vaccine design process, a crucial necessity in the COVID-19 era. Consequently, several B-cell epitope prediction methods have been developed over the past few decades, but without significant success. In this study, we review the current performance and methodology of some of the most widely used linear B-cell epitope predictors which are available via a command-line interface, namely, BcePred, BepiPred, ABCpred, COBEpro, SVMTriP, LBtope, and LBEEP. Additionally, we attempted to remedy performance issues of the individual methods by developing a consensus classifier, which combines the separate predictions of these methods into a single output, accelerating the epitope-based vaccine design. While the method comparison was performed with some necessary caveats and individual methods might perform much better for specialized datasets, we hope that this update in performance can aid researchers towards the choice of a predictor, for the development of biomedical applications such as designed vaccines, diagnostic kits, immunotherapeutics, immunodiagnostic tests, antibody production, and disease diagnosis and therapy.

Within the genus Streptococcus, only Streptococcus thermophilus is used as a starter culture in food fermentations. Streptococcus macedonicus though, which belongs to the Streptococcus bovis/Streptococcus equinus complex (SBSEC), is also frequently isolated from fermented foods mainly of dairy origin. Members of the SBSEC have been implicated in human endocarditis and colon cancer. Here we compare the genome sequence of the dairy isolate S. macedonicus ACA-DC 198 to the other SBSEC genomes in order to assess in silico its potential adaptation to milk and its pathogenicity status.

Urinary bladder cancer is a common malignancy, being characterized by substantial patient mortality and management cost. Its high somatic-mutation frequency and molecular heterogeneity usually renders tumors refractory to the applied regimens. Hitherto, methotrexate-vinblastine-adriamycin-cisplatin and gemcitabine-cisplatin represent the backbone of systemic chemotherapy. However, despite the initial chemosensitivity, the majority of treated patients will eventually develop chemoresistance, which severely reduces their survival expectancy. Since chromatin regulation genes are more frequently mutated in muscle-invasive bladder cancer, as compared to other epithelial tumors, targeted therapies against chromatin aberrations in chemoresistant clones may prove beneficial for the disease. “Acetyl-chromatin” homeostasis is regulated by the opposing functions of histone acetyltransferases (HATs) and histone deacetylases (HDACs). The HDAC/SIRT (super-)family contains 18 members, which are divided in five classes, with each family member being differentially expressed in normal urinary bladder tissues. Since a strong association between irregular HDAC expression/activity and tumorigenesis has been previously demonstrated, we herein attempt to review the accumulated published evidences that implicate HDACs/SIRTs as critical regulators in urothelial bladder cancer. Moreover, the most extensively investigated HDAC inhibitors (HDACis) are also analyzed, and the respective clinical trials are also described. Interestingly, it seems that HDACis should be preferably used in drug-combination therapeutic schemes, including radiation.