A systematic study of minima in alanine dipeptide

Abstract

The alanine dipeptide is a standard system to model dihedral angles in proteins. It is shown that obtaining the Ramachandran plot accurately is a hard problem because of many local minima; depending on the details of geometry optimizations, different Ramachandran plots can be obtained. To locate all energy minima, starting from geometries from MD simulations, 250,000 geometry optimizations were performed at the level of RHF/6-31G*, followed by re-optimizations of the located 827 minima at the level of MP2/6-311++G**, yielding 30 unique minima, most of which were not previously reported in literature. Both in vacuo and solvated structures are discussed. The minima are systematically categorized based on four backbone dihedral angles. The Gibbs energies are evaluated and the structural factors determining the relative stabilities of conformers are discussed. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Side-Chain Polarity Modulates the Intrinsic Conformational Landscape of Model Dipeptides

“…However, it is destabilized by around 1.6 kcal/mol because of the axial orientation of the methyl group that results in a steric repulsion between the C β atom and the seven-membered ring. 45 The relative ordering of the different conformers is in agreement with previous studies on different alanine dipeptide analogues. 41 , 45 , 99 , 103 − 105 …”

“…Our results suggest that, for both the dipeptides in vacuo , the α D conformer is a high free energy minimum (if a true minimum at all), in accord with a number of previous studies employing different molecular mechanics force fields. 53 , 54 , 98 In fact, systematic benchmarking of different ab initio methods 40 , 41 , 45 , 99 shows that the α D conformer is not a minimum on most potential energy surfaces.…”

The emerging role of computational design in peptide macrocycle drug discovery

“…An important limitation of this approach is that it cannot easily be extended to non-canonical amino acids that are poorly represented in PDB structures, though we realized that the D-amino acids that are the mirror images of canonical L-amino acids are an exception: in this special case, statistical potentials can be used, provided that all dihedral values are inverted [23]. For the more general case, physics-based methods of precomputing torsional potentials, using either MD or quantum mechanics (QM) computations, are necessary [112,113]. Through all of this, we strove to preserve and augment the protein-centric energy function rather than replacing it.…”

“…Strategies that use one-time, computationally expensive simulations or computations to train lower-cost approaches could give drug designers more accurate results without repeatedly applying more expensive calculations. For example, QM calculations have been used to pre-compute potentials that can be incorporated into Newtonian force fields [112]. The idea of training ML models against accurate-but-expensive simulations is gaining traction in other fields as well: recently, astrophysicists trained neural networks to predict outputs of expensive cosmological simulations, yielding surprisingly accurate predictions of emergent properties of the simulated systems at much lower computational cost [151].…”

“…Fieldprogrammable gate arrays (FPGAs), which can be reconfigured on the fly for highly efficient evaluation of a given function, could also accelerate such computations [156], but to date, they have proven less popular, in part because the programming model is more complex and the hardware is available to fewer researchers. The massive parallelism of large supercomputing clusters can also be leveraged to accelerate minuteslong QM calculations [112,145] or to accelerate folding simulations by carrying out separate conformational sampling trajectories on separate computing cores [23,24], though the speed of inter-node communication limits the extent to which a large supercomputer can accelerate already-fast Newtonian energy calculations for a single conformation of a molecular system.…”