Using normal mode analysis on protein structural models. How far can we go on our predictions?

Abstract

Normal mode analysis (NMA) is a fast and inexpensive approach that is largely used to gain insight into functional protein motions, and more recently to create conformations for further computational studies. However, when the protein structure is unknown, the use of computational models is necessary. Here, we analyze the capacity of NMA in internal coordinate space to predict protein motion, its intrinsic flexibility, and atomic displacements, using protein models instead of native structures, and the possibility to use it for model refinement. Our results show that NMA is quite insensitive to modeling errors, but that calculations are strictly reliable only for very accurate models. Our study also suggests that internal NMA is a more suitable tool for the improvement of structural models, and for integrating them with experimental data or in other computational techniques, such as protein docking or more refined molecular dynamics simulations.

Internal Normal Mode Analysis applied to RNA flexibility and conformational changes

“…As already highlighted in our previous works on iNMA applied to proteins, 17,31,40 also for RNAs only few residues show significant torsional changes when low-frequency modes are used, but these residues account for a large part of the overall motion. It is important to point out that the knowledge of the key nucleotides responsible for the conformational change is an another intrinsic feature of iNMA, but it is difficult to dermine using Cartesian Normal Mode Analysis.…”

“…As we have already shown in our previous works on a large set of proteins and models, iNMA is generally capable of describing large conformational changes and also deals with models. 40 First, as we demonstrated for proteins, in the same way we computed iNMA on a set of RNA molecules and for a given mode we increased the parameter ( β k to verify if our approach is capable to preserve the structure. To do so, we computed the RMSD of the bonds and the virtual P i -P i +1 bonds for each RNA molecule.…”

“…After many decades of applications to classical physical problems, molecular applications to biomolecules, in particular proteins, confirmed the importance of low-frequency motions in biological processes. 30,38,39 Although NMA has largely been applied to study proteins and protein deformations induced by ligand binding, allosteric processes and conformational changes occurring between isolated proteins and their complexes, 30,40–43 the use of NMA for nucleic acids is still quite limited, in particular for single-stranded RNA. For example, NMA has been used in combination with experimental data such as SAXS 44,45 and SHAPE 26 to take into account RNA flexibility and its structural rearrangements.…”

Mutational landscape of SARS-CoV-2 genome in Turkey and impact of mutations on spike protein structure

“…Deformation analysis reflecting the local flexibility such as atomic motion with respect to the neighboring atoms exhibited similar local flexibility in the region just below the RBD structure. Although the fluctuation intensities and the location of the fluctuations were similar, residues 474–488 of the Asp614Gly mutant were mapped to a relatively more upward extended conformation [ 46 , 48 ].…”

Multiscale molecular simulations to investigate adenylyl cyclase‐based signaling in the brain

“…Comparison was made with the results from MD simulations (see Section 5). 33,34 The calculations were performed on the backbone dihedral angles ( and ) that capture proteins' global movements well 59,61,62 . iNMA was used to investigate the global movements of AC5 alone and in complex with Gα olf and/or Gα I (i), the flexibility of the different molecular species (ii) and the impact on the flexibility of AC5 in the presence of either Gα olf and/or Gα i (iii), using similar strategies to the ones applied in the MD simulations.…”