α-Helical stabilization by side chain shielding of backbone hydrogen bonds

Abstract

We study atomic models of the thermodynamics of the structural transition of peptides that form ␣-helices. The effect of sequence variation on ␣-helix formation for alanine-rich peptides, Ac-Ala21-methyl amide (A21) and Ac-A5 (AAARA)3A-methyl amide (Fs peptide), is investigated by atomic simulation studies of the thermodynamics of the helix-coil transition in explicit water. The simulations show that the guanidinium group in the Arg side chains in the Fs peptide interacts with the carbonyl group four amino acids upstream in the chain and desolvates backbone hydrogen bonds. This desolvation can be directly correlated with a higher probability of hydrogen bond formation. We find that Fs has higher helical content than A21 at all temperatures. A small modification in the AMBER force field reproduces the experimental helical content and helix-coil transition temperatures for the Fs peptide.D etailed all-atom molecular simulation of protein folding has been limited by the inadequacy of sampling and possible inaccuracies of the semiempirical force fields used in classical simulations. The development of techniques for efficient sampling and the refinement of semiempirical force fields are crucial for modeling protein folding, structure prediction, and complex formation. Small peptides have many of the complexities associated with the energy landscape of proteins (1) and are ideal systems to understand the role of competing interactions in determining protein structures. In this work, we study the thermodynamics of the helix-coil transition of short peptides for which ample experimental data exist. We use highly parallel algorithms that enable the efficient sampling of configurational space. We validate our results through comparison with experimental data and test the sensitivity of our results to small changes in the semiempirical force field.The elucidation of ␣-helical formation energetics is relevant for understanding protein folding mechanisms. In spite of the large number of experimental studies conducted in peptides, there is still much debate concerning the propensity of Ala residues to stabilize ␣-helices. Ingwall et al. (2) studied runs of Ala n , with n ϭ 10-1,000, flanked by Lys runs, and concluded that short (n ϳ 10) sequences of Ala peptides do not form helices in water (2, 3). Similar conclusions were drawn from studies of Ala-rich random sequences. However, short (13-21) Ala-rich peptides containing interior charged amino acid side chains are found to form helices with 70-90% helical content (4-7), and short runs of Ala n (n ϭ 13) flanked by two ornithine charged amino acid are found to be about 40% helical in water (8, 9). These data have been interpreted in terms of a large intrinsic propensity of Ala residues to form helices in water. Within the Lifson-Roig (10, 11) and Zimm-Bragg (12) models for the helix-coil transition, the intrinsic propensity of an amino acid to form a helix is a measure of the interactions of the amino acid with its own and nearest-neighbor amino acid backbone (11, 13). Theore...

Comparison of multiple Amber force fields and development of improved protein backbone parameters

“…Another structural study of alanine dipeptide using 13 C NMR 49 confirmed the presence of PP II conformation, but also suggests that a mixture of PP II and α R is more likely in water. The dominance of PP II in trialanine was reiterated by two-dimensional vibrational spectroscopy studies of Woutersen & Hamm 50,51 and later modified by the same authors to include around 20% of α R apart from PP II 52 .…”

“…All molecular dynamics simulations for Gly 3 and Ala 3 tetrapeptides were carried out with the sander module in AMBER8 7 using several different force fields as discussed in the main text: ff94 5 , ff99 11 , Garcia's modification of ff94 13 with C-N-C α -C and N-C α -C-N terms zeroed (denoted ff94gs in the text), Pande's modified ff99 19 with C-N-C α -C term replaced by the one from ff94 (denoted ff99ϕ), ff03 24 (as present in AMBER8 distribution) and ff99SB developed as described above. The time step was 2 fs, and all bonds involving hydrogen were constrained by SHAKE with a tolerance of 10 −4 Å. Glycine and alanine tetrapeptide systems were solvated by approximately 520 TIP3P 33 water molecules in a periodic box.…”

“…Even though both ff99 and, particularly, ff94 parameter sets have been successfully used for many years, improvement in conformational sampling due to increased computer power and algorithmic advances revealed that both force fields over-stabilize α-helical peptide conformations 12,13 . On the other hand, the changes introduced in the less frequently used ff96 were observed to overestimate β-strand propensity [14][15][16][17] .…”

“…Because the backbone dihedral parameters are shared by all amino acids, regardless of the type of sidechain, their cumulative effect is most likely responsible for the bias towards the specific secondary structure. This recently motivated us 12,18 and others 13,19 to revisit backbone dihedral parametrization for ff94/ff99. Garcia and Sanbonmatsu 13 simply zeroed the torsion potential for φ and ψ (although as we explain below, only some of the φ/ψ terms were removed) and noted improved agreement with experimental helix-coil parameters.…”

“…This recently motivated us 12,18 and others 13,19 to revisit backbone dihedral parametrization for ff94/ff99. Garcia and Sanbonmatsu 13 simply zeroed the torsion potential for φ and ψ (although as we explain below, only some of the φ/ψ terms were removed) and noted improved agreement with experimental helix-coil parameters. More recently, Sorin and Pande 19,20 modified ff99 by replacing its φ dihedral parameters with the ones from ff94.…”