Mechanistic insights into the activity of Ptf1-p48 (pancreas transcription factor 1a): probing the interactions levels of Ptf1-p48 with E2A-E47 (transcription factor E2-alpha) and ID3 (inhibitor of DNA binding 3)

Abstract

Ptf1-p48 (Pancreas specific transcription factor 1a) is transcription regulatory protein known for the activation of exocrine specific genes. Downregulation of its expression formulates early stages of pancreatic adenocarcinoma as deduced by its association with oncogenic bHLH (Basic Helix–Loop–Helix) protein ID3 (Inhibitor of DNA binding 3) protein whose overexpression induces cytoplasmic mislocalization of Ptf1-p48. The precise mechanism and/or functional role of Ptf1-p48in promoting pancreatic cancer is vague. The structural features of the Ptf1-p48 and its dimerization with E47 (Transcription factor E2-alpha) and ID3 mediated by their HLH (Helix–Loop–Helix) domain were perceived through MD (Molecular Dynamics) simulations of 50 ns. The interactions formed by the HLH domain in both Ptf1-E47 and Ptf1-ID3 complexes are favored by the synergistic movement of their domain helices. Accordingly, in the Ptf1-E47 complex α7 of Ptf1-p48 and α1 helix of E47 along with the loop residues of their HLH domain exhibit transitions marked by inward movement toward each other and forms polar and charged interactions. In the Ptf1-ID3 complex, α8 of Ptf1-p48 moves toward the α3 helix of ID3 and forms hydrogen bonds. The interface analysis also reveals better interface in the Ptf1-p48 complex than the Ptf1-ID3 evident by energetics and number of hydrogen bonds. The interactions in each of these complexes, supported by angular displacement and mode vector analyzes, comprehensibly describe the considerable structural changes induced upon dimer formation. It thereby gives an insight into the interfaces that could help in designing of potential inhibitors for ID3 to curb the cancer cell growth.

Keywords:

• protein structures
• molecular dynamics
• molecular docking
• protein–protein interaction
• free energy landscape

Acknowledgement

The authors thank University Grants Commission Research Award (No.F.30-1/2013 (SA-II)/RA-2012-14-OB-TAM-1399) and Rajiv Gandhi National Fellowship (No.F.14-2(ST)/2010(SA-III)) for providing the financial assistance. The authors also thank Department of Biotechnology, Government of India for supporting the research work at the Centre for Bioinformatics and Interdisciplinary Programme in Life Science, Pondicherry University for providing the computational facilities.