Binding modes of Bcl-2 homology 3 (BH3) peptides with anti-apoptotic protein A1 and redesign of peptide inhibitors: a computational study

Abstract

The interaction between protein and peptide ligand is a challenging problem in molecular biology and drug design. The binding of the Bcl-2 homology 3 (BH3) peptide to the anti-apoptotic protein A1 was revealed as a critical step in the regulation of apoptosis. These BH3 peptides hold high structural similarity, but are diverse in their regulation abilities. Based on molecular simulations and MM-P(G)BSA methods, this work presented a detailed analysis on binding mechanism of the BH3 peptides derived from PUMA and BMF. Residue-level energy decomposition showed that the core regions of BH3 peptides maintain in stable helical conformations and the four conserved hydrophobic residues together with an invariant aspartic acid contribute the major driving force for binding, whereas their two terminal segments exhibit obvious flexibility and various binding modes. Such kind of behavior was suggested as the reason for binding diversity and selectivity of BH3 peptides. As a further step, several BH3-mimetic peptides have been redesigned by computational mutation. Those new peptides showed not only stronger affinities when binding to protein A1, as well transferable binding patterns at some specific positions. A long-range coupling effect was disclosed for BH3 peptides, side-chain orientation and binding contribution of terminal residues were even affected by mutations at large sequence interval. Overall, this work reports that the binding modes of BH3 peptides are primarily dependent on its two terminal segments. The computational methods applied herein are also demonstrated to be of great assistance in the rational design of peptide inhibitors.

Keywords:

• protein A1
• BH3 peptides
• free energy analysis
• binding affinity
• mutation effect

Acknowledgments

The authors gratefully acknowledge financial support from the NSF of China (Nos. 21174088, 81270740, and 11334004), the National Basic Research Program of China (973 Program) (No. 2013CB834100), and Shenzhen Scientific Technology Research Program (No. JCYJ20160520170646118). The authors are also grateful for the computing resources provided by the High Performance Computing Center (HPCC) of Nanjing University and the National Supercomputing Centre in Shenzhen of China.