Common molecular mechanism of the hepatic lesion and the cardiac parasympathetic regulation in chronic hepatitis C infection: a critical role for the muscarinic receptor type 3

Antibody VH domain sequence analysis by a bioinformatics approach based on electronic amino acid properties may help to predict paratop location

Gene as the basic functional unit of DNA encodes information about the product such as protein. The majority of proteins realize function through protein-protein interactions involving short protein motifs. However, some proteins such as antibodies are established by the rearrangement of several (V-D-J) gene segments with the potential addition of nontemplated nucleotides that may change information encoded by the respective gene segment used. Antibody VH domain sequence analysis by ISM bioinformatics approach that is based on amino acids physicochemical features, enable to distinguish the contribution of the information encoded by VH gene or generated during VDJ gene recombination for antibody-antigen interaction. The data presented in this report revealed the significance of CDRH3 for the interaction of antibody specific for immunogenic molecules while CDRH3 contribution is minor for antibody interaction with nonimmunogenic molecules such as haptens and native mammalian dsDNA. Thus, paratopes might be located in the CDRH3 or VH regions.

Cardiovascular risk assessment by electrocardiographic Holter monitoring in patients with chronic hepatitis C

INTRODUCTION

Cardiovascular diseases are ranked as the third cause of mortality among people infected with hepatitis C virus (HCV), but the relationship of infection with cardiovascular risk remains disputable. We have focused on the comprehensive use of parameters obtainable during long-term electrocardiographic (ECG) Holter monitoring.

MATERIAL AND METHODS

Heart rate variability and turbulence (HRV and HRT), deceleration/acceleration capacity (DC/AC), corrected QT interval (QTc) and late potential (LP) were used. 36 persons were included, and 30 healthy subjects formed a control group. All were submitted to 24-hour Holter ECG-monitoring.

RESULTS

The studied groups were not statistically significantly different with regards to basic anthropometric parameters. Statistically significantly higher medium and maximum heart rhythm and aminotransferase activities were recorded in patients with hepatitis C. The HRV parameters r-MSSD, p50NN, HF, and absolute DC/AC values were significantly lower in the subjects with hepatitis C than those in the control group. The QTc interval, measured for nocturnal hours, was also significantly longer in that group. There were no differences in the albumin level or basic echocardiographic parameters, including left ventricle ejection fraction. Nor was there any difference in the HRT parameters, or LP. The most interesting observation was the positive correlation among the number of viral RNA copies and DC, and LF.

CONCLUSIONS

We confirmed the presence of autonomic disorders with prevalence of sympathetic system activity and prolonged QTc interval in patients with chronic hepatitis C. Those parameters significantly correlated with infection intensity. Our results suggest that HCV infection could be an independent cardiovascular risk factor, not associated with the lipid profile. Further prospective studies are needed.

Time-Frequency Approach Applied to Finding Interaction Regions in Pathogenic Proteins

Protein-protein interactions govern all molecular processes for living organisms, even those involved in pathogen infection. Pathogens such as virus, bacteria, and parasites contain proteins that help the pathogen to attach, penetrate, and settle inside the target cell. Thus, it is necessary to know the regions in pathogenic proteins that interact with host cell receptors. Currently, powerful pathogen databases are available and many pathogenic proteins have been recognized, but many pathogenic proteins have not been characterized. This work developed a program in MATLAB environment based on the time-frequency analysis to recognize important sites in proteins. Our program highlights the highest energy patches in proteins from their time-frequency distribution and matches the corresponding frequency. We sought to know if this approach is able to recognize stretches residues related to interaction. Our approach was applied to five study cases from pathogenic co-crystallized structures that have been well characterized. We searched the frequencies that characterize interaction regions in pathogenic proteins and with this information tried to identify new interaction patches in either paralogs or orthologs. We found that our program generates a well-interpretable graphic under several descriptors that can show important regions in proteins even those related to interaction. We propose that this MATLAB program could be used as a tool to explore outstanding regions in uncharacterized proteins.