Homology modeling in a dynamical world

Abstract

A key concept in template-based modeling (TBM) is the high correlation between sequence and structural divergence, with the practical consequence that homologous proteins that are similar at the sequence level will also be similar at the structural level. However, conformational diversity of the native state will reduce the correlation between structural and sequence divergence, because structural variation can appear without sequence diversity. In this work, we explore the impact that conformational diversity has on the relationship between structural and sequence divergence. We find that the extent of conformational diversity can be as high as the maximum structural divergence among families. Also, as expected, conformational diversity impairs the well-established correlation between sequence and structural divergence, which is nosier than previously suggested. However, we found that this noise can be resolved using a priori information coming from the structure-function relationship. We show that protein families with low conformational diversity show a well-correlated relationship between sequence and structural divergence, which is severely reduced in proteins with larger conformational diversity. This lack of correlation could impair TBM results in highly dynamical proteins. Finally, we also find that the presence of order/disorder can provide useful beforehand information for better TBM performance.

Ensembles from ordered and disordered proteins reveal similar structural constraints during evolution

“…This effect operates over SCPE substitution matrices which are site and conformer specific but are evaluated using sequence alignments from corresponding homologous families. Thus, evolutionary information contained in those alignments reflects constraints of several sorts, such as structural divergence 41 or dynamical adaptations 52,53 which could certainly modify the contact pattern in the homologous proteins. It is then expected that this ~40% of structurally constrained sites on average obtained for both ensembles does not capture subtle inter-residue contacts originated in functional adaptations for individual proteins.…”

An in silico structural approach to characterize human and rainbow trout estrogenicity of mycotoxins: Proof of concept study using zearalenone and alternariol

“…There are no 3D structures of rainbow trout ER available in the PDB databank (http://www.rcsb.org) (last database access in January 17 th , 2019). Therefore, the rainbow trout ER (rbER) model was designed using homology modelling, a technique which can provide reliable 3D models of biological targets when the structure of homologous proteins are available (Lohning, Levonis, Williams-Noonan, & Schweiker, 2017;Monzon, Zea, Marino-Buslje, & Parisi, 2017). Notably, homology modelling may be particularly suitable to model the ligand binding domain of ERs given the strong conservation of 3D structures along the evolutionary path of nuclear receptors, and especially among the ER orthologous (Pike, Brzozowski, & Hubbard, 2000).…”

Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies

“…So far, this demand has been met by only a handful of tools. Several strategies were proposed in an attempt to address the problem of protein structure flexibility [25] , [26] , [27] based on molecular modeling [28] , [29] or comparative 3D-structure analysis [30] , [31] . Most molecular visualization and manipulation packages implement tools to calculate root mean square deviation/fluctuation or perform principal component/normal mode analysis over the ensemble of full-size structures [32] , [33] .…”