Biological and physical approaches on the role of piplartine (piperlongumine) in cancer.

Chronic inflammation provides a favorable microenvironment for tumorigenesis, which opens opportunities for targeting cancer development and progression. Piplartine (PL) is a biologically active alkaloid from long peppers that exhibits anti-inflammatory and antitumor activity. In the present study, we investigated the physical and chemical interactions of PL with anti-inflammatory compounds and their effects on cell proliferation and migration and on the gene expression of inflammatory mediators. Molecular docking data and physicochemical analysis suggested that PL shows potential interactions with a peptide of annexin A1 (ANXA1), an endogenous anti-inflammatory mediator with therapeutic potential in cancer. Treatment of neoplastic cells with PL alone or with annexin A1 mimic peptide reduced cell proliferation and viability and modulated the expression of MCP-1 chemokine, IL-8 cytokine and genes involved in inflammatory processes. The results also suggested an inhibitory effect of PL on tubulin expression. In addition, PL apparently had no influence on cell migration and invasion at the concentration tested. Considering the role of inflammation in the context of promoting tumor initiation, the present study shows the potential of piplartine as a therapeutic immunomodulator for cancer prevention and progression.

Web Services for Molecular Docking Simulations.

Docking process is one of the most significant activities for the analysis of protein-protein or protein-ligand complexes. These tools have become of unique importance when allocated in web services, collaborating scientifically with several areas of knowledge in an interdisciplinary way. Among the several web services dedicated to carrying out molecular docking simulations, we selected the DockThor web service. To illustrate the application of DockThor to protein-ligand docking simulations, we analyzed the docking of a ligand against the structure of epidermal growth factor receptor, an essential molecular marker in cancer research.

Structural Bioinformatics Approach of Cyclin-Dependent Kinases 1 and 3 Complexed with Inhibitors.

The cyclin-dependent kinases or CDKs participate in the regulation of both the cell progression cycle and the RNA polymerase-II transcription cycle. In several human tumours deregulation of CDK-related mechanisms have been detected, e.g., overexpression of cyclins or deletion of genes encoding for CKIs. Regarding these observations, CDKs came up to be interesting targets for elaboration of novel antitumour drugs. Based on the importance of the CDKs, this research aimed to describe, to characterize and to compare the molecular models of CDK1 and CDK3. Since the structures of human CDK1 and CDK3 are unavailable in the Protein Data Bank -PDB, homology models were created based on the CDK2 as the template, once they share a substantial identity. The structural studies of the CDK1 and CDK3 biding sites were conducted by molecular docking with 15 different CDK inhibitors previously identified to CDK2. This study allowed the understanding of the structure of the complexes between CDK1/ CDK3 with inhibitors. The knowledge of their structural features mainly the biding sites might be useful to discovery and rationalization of drug design process.

Molecular models of NS3 protease variants of the Hepatitis C virus.

BACKGROUND: Hepatitis C virus (HCV) currently infects approximately three percent of the world population. In view of the lack of vaccines against HCV, there is an urgent need for an efficient treatment of the disease by an effective antiviral drug. Rational drug design has not been the primary way for discovering major therapeutics. Nevertheless, there are reports of success in the development of inhibitor using a structure-based approach. One of the possible targets for drug development against HCV is the NS3 protease variants. Based on the three-dimensional structure of these variants we expect to identify new NS3 protease inhibitors. In order to speed up the modeling process all NS3 protease variant models were generated in a Beowulf cluster. The potential of the structural bioinformatics for development of new antiviral drugs is discussed. RESULTS: The atomic coordinates of crystallographic structure 1CU1 and 1DY9 were used as starting model for modeling of the NS3 protease variant structures. The NS3 protease variant structures are composed of six subdomains, which occur in sequence along the polypeptide chain. The protease domain exhibits the dual beta-barrel fold that is common among members of the chymotrypsin serine protease family. The helicase domain contains two structurally related beta-alpha-beta subdomains and a third subdomain of seven helices and three short beta strands. The latter domain is usually referred to as the helicase alpha-helical subdomain. The rmsd value of bond lengths and bond angles, the average G-factor and Verify 3D values are presented for NS3 protease variant structures. CONCLUSIONS: This project increases the certainty that homology modeling is an useful tool in structural biology and that it can be very valuable in annotating genome sequence information and contributing to structural and functional genomics from virus. The structural models will be used to guide future efforts in the structure-based drug design of a new generation of NS3 protease variants inhibitors. All models in the database are publicly accessible via our interactive website, providing us with large amount of structural models for use in protein-ligand docking analysis.