Advances in sequencing techniques and statistical methods have made it possible not only to predict sequences of ancestral proteins but also to identify thousands of mutations in the human exome, some of which are disease associated. These developments have motivated numerous theories and raised many questions regarding the fundamental principles behind protein evolution, which have been traditionally investigated horizontally using the tip of the phylogenetic tree through comparative studies of extant proteins within a family. In this article, we review a vertical comparison of the modern and resurrected ancestral proteins. We focus mainly on the dynamical properties responsible for a protein's ability to adapt new functions in response to environmental changes. Using the Dynamic Flexibility Index and the Dynamic Coupling Index to quantify the relative flexibility and dynamic coupling at a site-specific, single-amino-acid level, we provide evidence that the migration of hinges, which are often functionally critical rigid sites, is a mechanism through which proteins can rapidly evolve. Additionally, we show that disease-associated mutations in proteins often result in flexibility changes even at positions distal from mutational sites, particularly in the modulation of active site dynamics.
Amino acid substitutions at nonconserved protein positions can have non-canonical and “long-distance” outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities (“DFI”) and dynamic coupling (“DCI”) for positions in the linker region of the lactose repressor protein (“LacI”). This region contains nonconserved positions for which substitutions alter DNA binding affinity. We first chose to study eleven substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA binding positions, and the degree of flexibility change correlated with experimentally-measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA binding positions in a manner that captured other experimentally-determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated almost no substitutions (“toggle”), ten nonconserved positions showed progressive changes from a range of substitutions (“rheostat”), and three nonconserved positions tolerated almost all substitutions (“neutral”). In computations with wild-type LacI, the dynamic couplings between the DNA binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and non-canonical substitutions outcomes at nonconserved positions arise from re-wiring long-range communication among functionally-important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.
Allostery, which is regulation from distant sites, plays a major role in biology. While traditional allostery is described in terms of conformational change upon ligand binding as an underlying principle, it is possible to have allosteric regulations without significant conformational change through modulating the conformational dynamics by altering the local effective elastic modulus of the protein upon ligand binding. Pin1 utilizes this dynamic allostery to regulate its function. It is a modular protein containing a WW domain and a larger peptidyl prolyl isomerase domain (PPIase) that isomerizes phosphoserine/threonine-proline (pS/TP) motifs. The WW domain serves as a docking module, whereas catalysis solely takes place within the PPIase domain. Here, we analyze the change in the dynamic flexibility profile of the PPIase domain upon ligand binding to the WW domain. Substrate binding to the WW domain induces the formation of a new rigid hinge site around the interface of the two domains and loosens the flexibility of a rigid site existing in the Apo form around the catalytic site. This hinge-shift mechanism enhances the dynamic coupling of the catalytic positions with the PPIase domain, where the rest of the domain can cooperatively respond to the local conformational changes around the catalytic site, leading to an increase in catalytic efficiency.
Understanding the underlying mechanisms behind protein allostery and non-additivity of substitution outcomes (i.e., epistasis) is critical when attempting to predict the functional impact of mutations, particularly at non-conserved sites. In an effort to model these two biological properties, we extend the framework of our metric to calculate dynamic coupling between residues, the Dynamic Coupling Index (DCI) to two new metrics: (i) EpiScore, which quantifies the difference between the residue fluctuation response of a functional site when two other positions are perturbed with random Brownian kicks simultaneously versus individually to capture the degree of cooperativity of these two other positions in modulating the dynamics of the functional site and (ii) DCIasym, which measures the degree of asymmetry between the residue fluctuation response of two sites when one or the other is perturbed with a random force. Applied to four independent systems, we successfully show that EpiScore and DCIasym can capture important biophysical properties in dual mutant substitution outcomes. We propose that allosteric regulation and the mechanisms underlying non-additive amino acid substitution outcomes (i.e., epistasis) can be understood as emergent properties of an anisotropic network of interactions where the inclusion of the full network of interactions is critical for accurate modeling. Consequently, mutations which drive towards a new function may require a fine balance between functional site asymmetry and strength of dynamic coupling with the functional sites. These two tools will provide mechanistic insight into both understanding and predicting the outcome of dual mutations.
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