Conservation of Specificity in Two Low-Specificity Proteins

Protein binding and folding through an evolutionary lens

Protein-protein associations are often mediated by an intrinsically disordered protein region interacting with a folded domain in a coupled binding and folding reaction. Classic physical organic chemistry approaches together with structural biology have shed light on mechanistic aspects of such reactions. Further insight into general principles may be obtained by interpreting the results through an evolutionary lens. This review attempts to provide an overview on how the analysis of binding and folding reactions can benefit from an evolutionary approach, and is aimed at protein scientists without a background in evolution. Evolution constantly reshapes existing proteins by sampling more or less fit variants. Most new variants are weeded out as generations and new species come and go over hundreds to hundreds of millions of years. The huge ongoing genome sequencing efforts have provided us with a snapshot of existing adapted fit-for-purpose protein homologs in thousands of different organisms. Comparison of present-day orthologs and paralogs highlights general principles of the evolution of coupled binding and folding reactions and demonstrate a great potential for evolution to operate on disordered regions and modulate affinity and specificity of the interactions.

Mint/X11 PDZ domains from non-bilaterian animals recognize and bind CaV2 calcium channel C-termini in vitro

PDZ domain mediated interactions with voltage-gated calcium (CaV) channel C-termini play important roles in localizing membrane Ca2+ signaling. The first such interaction was described between the scaffolding protein Mint-1 and CaV2.2 in mammals. In this study, we show through various in silico analyses that Mint is an animal-specific gene with a highly divergent N-terminus but a strongly conserved C-terminus comprised of a phosphotyrosine binding domain, two tandem PDZ domains (PDZ-1 and PDZ-2), and a C-terminal auto-inhibitory element that binds and inhibits PDZ-1. In addition to CaV2 chanels, most genes that interact with Mint are also deeply conserved including amyloid precursor proteins, presenilins, neurexin, and CASK and Veli which form a tripartite complex with Mint in bilaterians. Through yeast and bacterial 2-hybrid experiments, we show that Mint and CaV2 channels from cnidarians and placozoans interact in vitro, and in situ hybridization revealed co-expression in dissociated neurons from the cnidarian Nematostella vectensis. Unexpectedly, the Mint orthologue from the ctenophore Hormiphora californiensis strongly bound the divergent C-terminal ligands of cnidarian and placozoan CaV2 channels, despite neither the ctenophore Mint, nor the placozoan and cnidarian orthologues, binding the ctenophore CaV2 channel C-terminus. Altogether, our analyses suggest that the capacity of Mint to bind CaV2 channels predates bilaterian animals, and that evolutionary changes in CaV2 channel C-terminal sequences resulted in altered binding modalities with Mint.

Mint/X11 PDZ domains from non-bilaterian animals recognize and bind Ca V 2 calcium channel C-termini in vitro

PDZ domain mediated interactions with voltage-gated calcium (Ca V ) channel C-termini play important roles in localizing membrane Ca 2+ signaling. The first such interaction was described between the scaffolding protein Mint-1 and Ca V 2.2 in mammals. In this study, we show through various in silico analyses that Mint is an animal-specific gene with a highly divergent N-terminus but a strongly conserved C-terminus comprised of a phosphotyrosine binding domain, two tandem PDZ domains (PDZ-1 and PDZ-2), and a C-terminal auto-inhibitory element that binds and inhibits PDZ-1. In addition to Ca V 2 channels, most genes that interact with Mint are also deeply conserved including amyloid precursor proteins, presenilins, neurexin, and CASK and Veli which form a tripartite complex with Mint in bilaterians. Through yeast and bacterial 2-hybrid experiments, we show that Mint and Ca V 2 channels from cnidarians and placozoans interact in vitro , and in situ hybridization revealed co-expression in dissociated neurons from the cnidarian Nematostella vectensis . Unexpectedly, the Mint orthologue from the ctenophore Hormiphora californiensis strongly binds the divergent C-terminal ligands of cnidarian and placozoan Ca V 2 channels, despite neither the ctenophore Mint, nor the placozoan and cnidarian orthologues, binding the ctenophore Ca V 2 channel C-terminus. Altogether, our analyses suggest that the capacity of Mint to bind CaV2 channels predates pre-bilaterian animals, and that evolutionary changes in Ca V 2 channel C-terminal sequences resulted in altered binding modalities with Mint.

Ancestral Reconstruction and the Evolution of Protein Energy Landscapes

A protein's sequence determines its conformational energy landscape. This, in turn, determines the protein's function. Understanding the evolution of new protein functions therefore requires understanding how mutations alter the protein energy landscape. Ancestral sequence reconstruction (ASR) has proven a valuable tool for tackling this problem. In ASR, one phylogenetically infers the sequences of ancient proteins, allowing characterization of their properties. When coupled to biophysical, biochemical, and functional characterization, ASR can reveal how historical mutations altered the energy landscape of ancient proteins, allowing the evolution of enzyme activity, altered conformations, binding specificity, oligomerization, and many other protein features. In this article, we review how ASR studies have been used to dissect the evolution of energy landscapes. We also discuss ASR studies that reveal how energy landscapes have shaped protein evolution. Finally, we propose that thinking about evolution from the perspective of an energy landscape can improve how we approach and interpret ASR studies.

Evolution of a plant growth-regulatory protein interaction specificity

Specific protein-protein interactions (PPIs) enable biological regulation. However, the evolution of PPI specificity is little understood. Here we trace the evolution of the land-plant growth-regulatory DELLA-SLY1/GID2 PPI, revealing progressive increase in specificity of affinity of SLY1/GID2 for a particular DELLA form. While early-diverging SLY1s display relatively broad-range DELLA affinity, later-diverging SLY1s tend towards increasingly stringent affinity for a specific DELLA A' form generated by the growth-promoting phytohormone gibberellin (GA). Our novel mutational strategy reveals amino acid substitutions contributing to the evolution of Arabidopsis thaliana SLY1 A' specificity, also showing that routes permitting reversion to broader affinity became increasingly constrained over evolutionary time. We suggest that progressive affinity narrowing may be an important evolutionary driver of PPI specificity and that increase in SLY1/GID2-DELLA specificity enabled the enhanced flexibility of plant physiological environmental adaptation conferred by the GA-DELLA growth-regulatory mechanism.

Topiary: Pruning the manual labor from ancestral sequence reconstruction

Ancestral sequence reconstruction (ASR) is a powerful tool to study the evolution of proteins and thus gain deep insight into the relationships among protein sequence, structure, and function. A major barrier to its broad use is the complexity of the task: it requires multiple software packages, complex file manipulations, and expert phylogenetic knowledge. Here we introduce topiary, a software pipeline that aims to overcome this barrier. To use topiary, users prepare a spreadsheet with a handful of sequences. Topiary then: (1) Infers the taxonomic scope for the ASR study and finds relevant sequences by BLAST; (2) Does taxonomically informed sequence quality control and redundancy reduction; (3) Constructs a multiple sequence alignment; (4) Generates a maximum-likelihood gene tree; (5) Reconciles the gene tree to the species tree; (6) Reconstructs ancestral amino acid sequences; and (7) Determines branch supports. The pipeline returns annotated evolutionary trees, spreadsheets with sequences, and graphical summaries of ancestor quality. This is achieved by integrating modern phylogenetics software (Muscle5, RAxML-NG, GeneRax, and PastML) with online databases (NCBI and the Open Tree of Life). In this paper, we introduce non-expert readers to the steps required for ASR, describe the specific design choices made in topiary, provide a detailed protocol for users, and then validate the pipeline using datasets from a broad collection of protein families. Topiary is freely available for download: https://github.com/harmslab/topiary.

Ancestral reconstruction of duplicated signaling proteins reveals the evolution of signaling specificity

Gene duplication is crucial to generating novel signaling pathways during evolution. However, it remains unclear how the redundant proteins produced by gene duplication ultimately acquire new interaction specificities to establish insulated paralogous signaling pathways. Here, we used ancestral sequence reconstruction to resurrect and characterize a bacterial two-component signaling system that duplicated in α-proteobacteria. We determined the interaction specificities of the signaling proteins that existed before and immediately after this duplication event and then identified key mutations responsible for establishing specificity in the two systems. Just three mutations, in only two of the four interacting proteins, were sufficient to establish specificity of the extant systems. Some of these mutations weakened interactions between paralogous systems to limit crosstalk. However, others strengthened interactions within a system, indicating that the ancestral interaction, although functional, had the potential to be strengthened. Our work suggests that protein-protein interactions with such latent potential may be highly amenable to duplication and divergence.

Promiscuity mapping of the S100 protein family using a high-throughput holdup assay

S100 proteins are small, typically homodimeric, vertebrate-specific EF-hand proteins that establish Ca²⁺-dependent protein-protein interactions in the intra- and extracellular environment and are overexpressed in various pathologies. There are about 20 distinct human S100 proteins with numerous potential partner proteins. Here, we used a quantitative holdup assay to measure affinity profiles of most members of the S100 protein family against a library of chemically synthetized foldamers. The profiles allowed us to quantitatively map the binding promiscuity of each member towards the foldamer library. Since the library was designed to systematically contain most binary natural amino acid side chain combinations, the data also provide insight into the promiscuity of each S100 protein towards all potential naturally occurring S100 partners in the human proteome. Such information will be precious for future drug design to interfere with S100 related pathologies.

Resurrecting Enzymes by Ancestral Sequence Reconstruction

Ancestral Sequence Reconstruction (ASR) allows one to infer the sequences of extinct proteins using the phylogeny of extant proteins. It consists of disclosing the evolutionary history-i.e., the phylogeny-of a protein family of interest and then inferring the sequences of its ancestors-i.e., the nodes in the phylogeny. Assisted by gene synthesis, the selected ancestors can be resurrected in the lab and experimentally characterized. The crucial step to succeed with ASR is starting from a reliable phylogeny. At the same time, it is of the utmost importance to have a clear idea on the evolutionary history of the family under study and the events that influenced it. This allows us to implement ASR with well-defined hypotheses and to apply the appropriate experimental methods. In the last years, ASR has become popular to test hypotheses about the origin of functionalities, changes in activities, understanding physicochemical properties of proteins, among others. In this context, the aim of this chapter is to present the ASR approach applied to the reconstruction of enzymes-i.e., proteins with catalytic roles. The spirit of this contribution is to provide a basic, hands-to-work guide for biochemists and biologists who are unfamiliar with molecular phylogenetics.

Were Ancestral Proteins Less Specific?

Some have hypothesized that ancestral proteins were, on average, less specific than their descendants. If true, this would provide a universal axis along which to organize protein evolution and suggests that reconstructed ancestral proteins may be uniquely powerful tools for protein engineering. Ancestral sequence reconstruction studies are one line of evidence used to support this hypothesis. Previously, we performed such a study, investigating the evolution of peptide-binding specificity for the paralogs S100A5 and S100A6. The modern proteins appeared more specific than their last common ancestor (ancA5/A6), as each paralog bound a subset of the peptides bound by ancA5/A6. In this study, we revisit this transition, using quantitative phage display to measure the interactions of 30,533 random peptides with human S100A5, S100A6, and ancA5/A6. This unbiased screen reveals a different picture. While S100A5 and S100A6 do indeed bind to a subset of the peptides recognized by ancA5/A6, they also acquired new peptide partners outside of the set recognized by ancA5/A6. Our previous work showed that ancA5/A6 had lower specificity than its descendants when measured against biological targets; our new work shows that ancA5/A6 has similar specificity to the modern proteins when measured against a random set of peptide targets. This demonstrates that altered biological specificity does not necessarily indicate altered intrinsic specificity, and sounds a cautionary note for using ancestral reconstruction studies with biological targets as a means to infer global evolutionary trends in specificity.

Divergent Evolution of a Protein-Protein Interaction Revealed through Ancestral Sequence Reconstruction and Resurrection

The postsynaptic density extends across the postsynaptic dendritic spine with discs large (DLG) as the most abundant scaffolding protein. DLG dynamically alters the structure of the postsynaptic density, thus controlling the function and distribution of specific receptors at the synapse. DLG contains three PDZ domains and one important interaction governing postsynaptic architecture is that between the PDZ3 domain from DLG and a protein called cysteine-rich interactor of PDZ3 (CRIPT). However, little is known regarding functional evolution of the PDZ3:CRIPT interaction. Here, we subjected PDZ3 and CRIPT to ancestral sequence reconstruction, resurrection, and biophysical experiments. We show that the PDZ3:CRIPT interaction is an ancient interaction, which was likely present in the last common ancestor of Eukaryotes, and that high affinity is maintained in most extant animal phyla. However, affinity is low in nematodes and insects, raising questions about the physiological function of the interaction in species from these animal groups. Our findings demonstrate how an apparently established protein-protein interaction involved in cellular scaffolding in bilaterians can suddenly be subject to dynamic evolution including possible loss of function.

Learning peptide recognition rules for a low-specificity protein

Many proteins interact with short linear regions of target proteins. For some proteins, however, it is difficult to identify a well-defined sequence motif that defines its target peptides. To overcome this difficulty, we used supervised machine learning to train a model that treats each peptide as a collection of easily-calculated biochemical features rather than as an amino acid sequence. As a test case, we dissected the peptide-recognition rules for human S100A5 (hA5), a low-specificity calcium binding protein. We trained a Random Forest model against a recently released, high-throughput phage display dataset collected for hA5. The model identifies hydrophobicity and shape complementarity, rather than polar contacts, as the primary determinants of peptide binding specificity in hA5. We tested this hypothesis by solving a crystal structure of hA5 and through computational docking studies of diverse peptides onto hA5. These structural studies revealed that peptides exhibit multiple binding modes at the hA5 peptide interface-all of which have few polar contacts with hA5. Finally, we used our trained model to predict new, plausible binding targets in the human proteome. This revealed a fragment of the protein α-1-syntrophin that binds to hA5. Our work helps better understand the biochemistry and biology of hA5, as well as demonstrating how high-throughput experiments coupled with machine learning of biochemical features can reveal the determinants of binding specificity in low-specificity proteins.

Friend or Foe: S100 Proteins in Cancer

S100 proteins are widely expressed small molecular EF-hand calcium-binding proteins of vertebrates, which are involved in numerous cellular processes, such as Ca²⁺ homeostasis, proliferation, apoptosis, differentiation, and inflammation. Although the complex network of S100 signalling is by far not fully deciphered, several S100 family members could be linked to a variety of diseases, such as inflammatory disorders, neurological diseases, and also cancer. The research of the past decades revealed that S100 proteins play a crucial role in the development and progression of many cancer types, such as breast cancer, lung cancer, and melanoma. Hence, S100 family members have also been shown to be promising diagnostic markers and possible novel targets for therapy. However, the current knowledge of S100 proteins is limited and more attention to this unique group of proteins is needed. Therefore, this review article summarises S100 proteins and their relation in different cancer types, while also providing an overview of novel therapeutic strategies for targeting S100 proteins for cancer treatment.

High-throughput competitive fluorescence polarization assay reveals functional redundancy in the S100 protein family

The calcium-binding, vertebrate-specific S100 protein family consists of 20 paralogs in humans (referred as the S100ome), with several clinically important members. To explore their protein-protein interactions (PPIs) quantitatively, we have chosen an unbiased, high-throughput, competitive fluorescence polarization (FP) assay that revealed a partial functional redundancy when the complete S100ome (n = 20) was tested against numerous model partners (n = 13). Based on their specificity, the S100ome can be grouped into two distinct classes: promiscuous and orphan. In the first group, members bound to several ligands (> 4-5) with comparable high affinity, while in the second one, the paralogs bound only one partner weakly, or no ligand was identified. Our results demonstrate that FP assays are highly suitable for quantitative interaction profiling of selected protein families. Moreover, we provide evidence that PPI-based phenotypic characterization can complement or even exceed the information obtained from the sequence-based phylogenetic analysis of the S100ome, an evolutionary young protein family.