Solution Conformations of Wild-Type and Mutated Bak BH3 Peptides via Dynamical Conformational Sampling and Implication to Their Binding to Antiapoptotic Bcl-2 Proteins

Abstract

The BH3 (Bcl-2 homology 3) domain of the Bcl-2 family of proteins plays a critical role in the regulation of programmed cell death, or apoptosis. A 16-residue peptide derived from the BH3 domain of the proapoptotic protein Bak potently binds to the antiapoptotic proteins Bcl-2 and Bcl-xL. While this Bak BH3 peptide adopts a well-defined helical conformation in the experimental NMR solution structure in complex with Bcl-xL, it does not adopt a stable helical conformation in water. Experimental structural determination of peptides without a stable and well-defined solution conformation remains a difficult task. In this paper, we investigated the solution conformations of this Bak BH3 peptide through extensive molecular dynamics (MD) simulations in water using a recently developed self-guided MD simulation (SGMD) method. Our simulations showed that the Bak peptide exhibits a partially formed helical structure with a fairly stable 6-residue helical segment at the N terminus and a less stable approximately 4-residue helical segment at the C terminus. Additionally, we also performed extensive SGMD simulations of two mutated Bak peptides, in which the arginine residue at position 5 is mutated to either an alanine or a glycine residue (R5A or R5G mutant) to investigate the influence of mutation on the solution conformations of the Bak peptide. We found that the R5G mutation greatly affects the solution conformations of the peptide, and the overall helix ratio decreases by a factor of 2 as compared to the wild-type Bak peptide. In contrast, the R5A mutation does not affect significantly the peptide solution conformations observed in the wild type. By use of a fluorescence-polarization-based binding assay, we quantitatively determined the binding affinities of these three Bak BH3 peptides to Bcl-xL protein. We found that the R5G and R5A mutants are 24 and 6 times less potent than the wild-type Bak peptide, respectively, suggesting that the helical ratio of the peptides is an important but not the only factor for their binding to Bcl-xL. Analysis of representative conformations of the R5A mutant suggested that the relatively stable helical segment close to the N terminus may greatly facilitate its binding to Bcl-xL.

Molecular dynamics simulations of pro-apoptotic BH3 peptide helices in aqueous medium: relationship between helix stability and their binding affinities to the anti-apoptotic protein Bcl-XL

“…During the initial stage of the simulation, the peptide shows presence of two helical segments from residues 75-81 and a shorter segment at the C-terminal region from residues 83-86. A similar behavior was observed in an independent simulation of the 16-mer Bak peptide by Yang et al [31] in which the peptide was simulated for 2 ns using conventional MD followed by 8 ns simulation using self-guided molecular dynamics (SGMD) technique developed by Wu and Wang [42]. It must be pointed out that SGMD can achieve a better conformational sampling compared to conventional MD.…”

“…Previous simulation studies to investigate the secondary structure of a peptide have been carried out on alanine-based peptides [26,27], a prion peptide [28], amyloid b-peptide [29] and stapled p53 peptide analogs [30] in explicit solvent. Recently, a molecular dynamics simulation study on the solution conformation of 16-mer peptide belonging to the BH3 region of pro-apoptotic Bak protein showed the presence of substantially stable short helices [31]. This observation was implicated to be important for their binding to Bcl-X L .…”

Unconstrained enhanced sampling for free energy calculations of biomolecules: a review

“…Along with the theoretical development of the SGMD and SGLD methods, they have been applied for enhanced sampling of a wide range of systems, such as peptide conformational change[50], surface adsorption of complementary peptides[80], flexible fitting of biomolecular structures into electron microscopic density maps[81], protein folding and conformational rearrangements[49, 51], molecular docking[82], ligand binding[83, 84], crystallization and phase transitions[85], and so on.…”

Efficient and Unbiased Sampling of Biomolecular Systems in the Canonical Ensemble: A Review of Self‐Guided Langevin Dynamics

“…The enhanced conformational searching ability of SGMD and SGLD are demonstrated by their many applications in protein folding (Lee & Chang 2010; Lee & Olson 2010; Wu & Wang 2000; 2001; Wu et al 2002), ligand binding (Lung et al 2001; Varady et al 2002; Yang et al 2004), conformational transitions (Damjanovic et al 2009; Damjanovic et al 2008a; Damjanovic et al 2008b; Pendse et al 2010), phase transitions (Abe & Jitsukawa 2009; Choudhary & Clancy 2002; Chowdhury et al 2003; Tsuru et al 2010; Wu & Wang 1999), and surface adsorption (Sheng et al 2010a; 2010b). There are several method developments along the same concept of SGLD.…”

“…The self-guided molecular dynamics (SGMD) (Wu & Wang 1998; 1999) and the self-guided Langevin dynamics (SGLD) (Wu & Brooks 2003; Wu & Brooks 2011a; 2011b) simulation methods were developed for an efficient conformational search and have found many applications to study rare events, such as protein folding (Lee & Chang 2010; Lee & Olson 2010; Wen et al 2004; Wen & Luo 2004; Wu & Sung 1999; Wu & Brooks 2004; Wu & Wang 2000; 2001; Wu et al 2002), and ligand binding (Lung et al 2001; Varady et al 2002; Yang et al 2004), docking (Chandrasekaran et al 2009), conformational transitions (Damjanovic et al 2009; Damjanovic et al 2008a; Damjanovic et al 2008b; Pendse et al 2010), crystallization (Abe & Jitsukawa 2009; Choudhary & Clancy 2005a; 2005b; Tsuru et al 2010; Wu & Wang 1999), and surface absorption (Sheng et al 2010a; 2010b)…”