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Prostate cancer is the most common neoplasm found in males and the second most frequent cause of cancer-related mortality in males in Greece. Among other pathogens, the detection frequency of human papillomavirus (HPV) has been found to be significantly increased in tumor tissues among patients with sexually transmitted diseases (STDs), depending on the geographical distribution of each population studied. The present study focused on the detection of HPV and the distribution of Arg72Pro p53 polymorphism in a cohort of healthy individuals, as well as prostate cancer patients. We investigated the presence of HPV in 50 paraffin-embedded prostate cancer tissues, as well as in 30 physiological tissue samples from healthy individuals by real-time PCR. Furthermore, the same group of patients was also screened for the presence of the Arg72Pro polymorphism of the p53 gene, a p53 polymorphism related to HPV. Out of the 30 control samples, only 1 was found positive for HPV (3.33 %). On the contrary, HPV DNA was detected in 8 out of the total 50 samples (16 %) in the prostate cancer samples. The distribution of the three genotypes, Arg/Arg, Arg/Pro, and Pro/Pro, was 69.6, 21.7, and 8.7 % in the cancer patients and 75.0, 17.86, and 7.14 % in healthy controls, respectively. No statistically significant association was observed between the HPV presence and the age, stage, p53 polymorphism status at codon 72, or PSA. The increased prevalence of HPV detected in the prostate cancer tissues is in agreement with that reported in previous studies, further supporting the association of HPV infection and prostate cancer.

The group IVA cytosolic phospholipase A(2) (GIVA cPLA(2)) plays a central role in inflammation. Long chain 2-oxoamides constitute a class of potent GIVA cPLA(2) inhibitors that exhibit potent in vivo anti-inflammatory and analgesic activity. We have now gained insight into the binding of 2-oxoamide inhibitors in the GIVA cPLA(2) active site through a combination of molecular docking calculations and molecular dynamics simulations. Recently, the location of the 2-oxoamide inhibitor AX007 within the active site of the GIVA cPLA(2) was determined using a combination of deuterium exchange mass spectrometry followed by molecular dynamics simulations. After the optimization of the AX007-GIVA cPLA(2) complex using the docking algorithm Surflex-Dock, a series of additional 2-oxoamide inhibitors have been docked in the enzyme active site. The calculated binding affinity presents a good statistical correlation with the experimental inhibitory activity (r(2) = 0.76, N = 11). A molecular dynamics simulation of the docking complex of the most active compound has revealed persistent interactions of the inhibitor with the enzyme active site and proves the stability of the docking complex and the validity of the binding suggested by the docking calculations. The combination of molecular docking calculations and molecular dynamics simulations is useful in defining the binding of small-molecule inhibitors and provides a valuable tool for the design of new compounds with improved inhibitory activity against GIVA cPLA(2).