7^th International Conference on Bioinformatics October 24-25, 2016 Rome, Italy

Marina Holyavka is a Senior Researcher and Associate Professor in the Department of Biophysics and Biotechnology at Voronezh State University, Russia. She received her Bachelors in Science in 2005 and her Masters in 2007. She has completed her PhD in the year 2010. She is currently working on structural & functional properties of homogeneous and heterogeneous biocatalysts on the basis of hydrolytic enzymes.

It is known that the immobilization of the enzyme on an insoluble carrier solves several important problems in medicine: 1) preparing prolonged action formulations due to stabilization and increase half-life of the enzyme, 2) a possibility of obtaining the directed delivery of the drug solution, and its diffusion into the body, 3) directed regulation of optimums of preparation operation (temperature optimum, pH optimum). Molecules of trypsin (pdb 3UY9), papain (pdb 9PAP) and collagenase (pdb 2CLT) taken from the database of protein structures (PDB) was used as protein models. Virtual screening of ligands for immobilization of some proteases for medical application was performed. The set of ligands included high-molecular compounds (polycation and polyanion exchange fibers) and chitosan. Based on the comparative analysis of the total energy values and the localization of the ligand binding sites, and several literature data, we made several suppositions concerning the mechanisms of interaction of the suggested matrices for the immobilization with enzyme molecules and the structural features of such complexes. The adsorptive method of enzyme immobilization on the above matrices proposed here allowed us to keep the enzyme’s initial catalytic activity up to 70% for trypsin, papain and collagenase.

Gabriel is a 23 years old Masters Student at University of São Paulo, the top ranked university in Latin America. Under the guidance of Professor Silvana Giuliatti, PhD, he presented an Oral Session aboout Virtual Screening at EUROGIN 2015 Multidisciplinary Congress, and has extensive experience in deploying In Silico methods aimed towards the inhibition of HPV’s oncogenic viral proteins. He also worked in two papers pending publication, both in the fields of Structural Bioinformatics and Drug-Discovery

The viral oncoprotein E6 is related with the development of cervical cancer in HPV positive patients. E6 has been reported to bind to TNF-α, p53, p600 and p21 (Moody, C. et al., 2010), blocking the traditional pathways to apoptosis and leading to unregulated cell growth. This work aimed to use computational methods such as virtual screening (both target-based and ligand-based), molecular dynamics simulation, toxicity prediction and rational ligand design in order to search for potential inhibitors to Human Papillomavirus E6 oncoprotein. We also conducted a parallel study using other in silico methods such as binding site prediction and pharmacophore identification in order to thoroughly uncover the oncoprotein’s properties. The most common European variants of E6 oncoproteins, previously modeled by Tamarozzi & Giuliatti (2015), were submitted to target-based virtual screening by using GOLD and Autodock Vina software, and the molecules within the FDA-Approved database as ligand pool. The highest scoring protein/ligand complexes were submitted to molecular dynamics simulation using GROMACS, and then underwent visual analysis in both PyMOL and Chimera, in order to evaluate their molecular interactions with the active site of E6. Finally, we performed theoretical toxicity predictions and pharmacokinetics simulations through a series of open-source web servers, in order to select only the safest ligands, which were used as pivot molecules for the rational design of hybrids – novel molecules that combine the desired characteristics of the best ranked ligands, leading us to a considerable pool of potential inhibitors to Oncoprotein E6.