Conformational diversity analysis reveals three functional mechanisms in proteins

Abstract

Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call “rigid” (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions.

Homology modeling in a dynamical world

“…We found that proteins containing IDRs have larger conformational diversity than those with full ordered structures, when disorder‐order transitions take place between protein conformations . Furthermore, we recently found that proteins with IDRs can be split into two groups with different structure‐function relationships, depending on how structure‐based features change among the available conformer population for each protein . Therefore, it is interesting to ask if the structure‐sequence relationship could be also separated into two groups, mainly proteins with and without IDRs, following the above‐mentioned results using CD.…”

“…Distributions in Figure show that CD could be as large as the MSD, but it is also evident that most of the proteins in our dataset have modest to low CD, meaning that they could function with very low or absent backbone movements …”

“…However, we know that there are few full‐ordered protein families with very large CDs. These proteins have been extensively studied thanks to the pioneering work of Chothia and coworkers and represent less than approximately 20% of our dataset . Removing these highly dynamic proteins with non‐disordered regions, we obtain the relationship shown in Figure where the Spearman's rank correlation rho is −0.71 for the ordered set of pairs.…”

“…Based on these correlation coefficients, we can say that the presence of disorder regions alone has a moderate capacity for predicting the presence of noise between structure and sequence variables. Moreover, these values were obtained considering that most ordered proteins do not have CD, or at least show moderate CD, as we have previously described . Taking into account these considerations, and the easy and reliable prediction capacity for disordered regions in proteins, this information could be still used as guidance in TBM approaches.…”

“…Conformational diversity is a key concept to understand many processes and mechanisms in protein function, such as enzyme catalysis, promiscuity in protein interactions, protein‐protein recognition, signal transduction, mechanisms of disease‐related mutations, immune escape, the origin of neurodegenerative diseases, protein evolutionary rates, conformer‐specific substitution patterns, the origins of new biological functions, molecular motors, and co‐evolutionary measurements between residues (for a recent review please see). Furthermore, we have recently shown that the distribution of CD in a large dataset of proteins, with experimentally determined CD (approximately 5000 proteins), results in three main groups of proteins with different structure‐function relationships . More recently, we found that the dynamical behavior in a given family could change with minor sequence variations making difficult to predict CD by homology …”