Chameleon Sequences Research Articles

Conformational Switch of a Peptide Provides a Novel Strategy to Design Peptide Loaded Porous Organic Polymer for Pyroptosis Pathway Mediated Cancer Therapy.

While peptide-based drug development is extensively explored, this strategy has limitations due to rapid excretion from the body (or shorter half-life in the body) and vulnerability to protease-mediated degradation. To overcome these limitations, a novel strategy for the development of a peptide-based anticancer agent is introduced, utilizing the conformation switch property of a chameleon sequence stretch (PEP1) derived from a mycobacterium secretory protein, MPT63. The selected peptide is then loaded into a new porous organic polymer (PG-DFC-POP) synthesized using phloroglucinol and a cresol derivative via a condensation reaction to deliver the peptide selectively to cancer cells. Utilizing ensemble and single-molecule approaches, this peptide undergoes a transition from a disordered to an alpha-helical conformation, triggered by the acidic environment within cancer cells that is demonstrated. This adopted alpha-helical conformation resulted in the formation of proteolysis-resistant oligomers, which showed efficient membrane pore-forming activity selectively for negatively charged phospholipids accumulated in cancer cell membranes. The experimental results demonstrated that the peptide-loaded PG-DFC-POP-PEP1 exhibited significant cytotoxicity in cancer cells, leading to cell death through the Pyroptosis pathway, which is established by monitoring numerous associated events starting from lysosome membrane damage to GSDMD-induced cell membrane demolition. This novel conformational switch-based drug design strategy is believed to have great potential in endogenous environment-responsive cancer therapy and the development of future drug candidates to mitigate cancers.

The Effect of Pulling and Twisting Forces on Chameleon Sequence Peptides.

Chameleon sequences are amino acid sequences found in several distinct configurations in experiment. They challenge our understanding of the link between sequence and structure, and provide insight into structural competition in proteins. Here, we study the energy landscapes for three such sequences, and interrogate how pulling and twisting forces impact the available structural ensembles. Chameleon sequences do not necessarily exhibit multiple structural ensembles on a multifunnel energy landscape when we consider them in isolation. The application of even small forces leads to drastic changes in the energy landscapes. For pulling forces, we observe transitions from helical to extended structures in a very small span of forces. For twisting forces, the picture is much more complex, and highly dependent on the magnitude and handedness of the applied force as well as the reference angle for the twist. Depending on these parameters, more complex and more simplistic energy landscapes are observed alongside more and less diverse structural ensembles. The impact of even small forces is significant, confirming their likely role in folding events. In addition, small forces exerted by the remaining scaffold of a protein may be sufficient to lead to the adoption of a specific structural ensemble by a chameleon sequence.

Computing Free Energies of Fold-Switching Proteins Using MELD x MD.

Some proteins are conformational switches, able to transition between relatively different conformations. To understand what drives them requires computing the free-energy difference ΔGAB between their stable states, A and B. Molecular dynamics (MD) simulations alone are often slow because they require a reaction coordinate and must sample many transitions in between. Here, we show that modeling employing limited data (MELD) x MD on known endstates A and B is accurate and efficient because it does not require passing over barriers or knowing reaction coordinates. We validate this method on two problems: (1) it gives correct relative populations of α and β conformers for small designed chameleon sequences of protein G; and (2) it correctly predicts the conformations of the C-terminal domain (CTD) of RfaH. Free-energy methods like MELD x MD can often resolve structures that confuse machine-learning (ML) methods.

Importin alpha family NAAT/IBB domain: Functions of a pleiotropic long chameleon sequence.

Nuclear transport is essential for eukaryotic cell survival and regulates the movement of functional molecules in and out of the nucleus via the nuclear pore. Transport is facilitated by protein-protein interactions between cargo and transport receptors, which contribute to the expression and regulation of downstream genetic information. This chapter focuses on the molecular basis of the multifunctional nature of the importin α family, the representative transport receptors that bring proteins into the nucleus. Importin α performs multiple functions during the nuclear transport cycle through interactions with multiple molecules by a single domain called the IBB domain. This domain is a long chameleon sequence, which can change its conformation and binding mode depending on the interaction partners. By considering the evolutionarily conserved biochemical/physicochemical propensities of the amino acids constituting the functional complex interfaces, together with their structural properties, the mechanisms of switching between multiple complexes formed via IBB and the regulation of downstream functions are examined in detail. The mechanism of regulation by IBB indicates that the time has come for a paradigm shift in the way we view the molecular mechanisms by which proteins regulate downstream functions through their interactions with other molecules.

Convolutional ProteinUnetLM competitive with long short-term memory-based protein secondary structure predictors.

The protein secondary structure (SS) prediction plays an important role in the characterization of general protein structure and function. In recent years, a new generation of algorithms for SS prediction based on embeddings from protein language models (pLMs) is emerging. These algorithms reach state-of-the-art accuracy without the need for time-consuming multiple sequence alignment (MSA) calculations. Long short-term memory (LSTM)-based SPOT-1D-LM and NetSurfP-3.0 are the latest examples of such predictors. We present the ProteinUnetLM model using a convolutional Attention U-Net architecture that provides prediction quality and inference times at least as good as the best LSTM-based models for 8-class SS prediction (SS8). Additionally, we address the issue of the heavily imbalanced nature of the SS8 problem by extending the loss function with the Matthews correlation coefficient, and by proper assessment using previously introduced adjusted geometric mean (AGM) metric. ProteinUnetLM achieved better AGM and sequence overlap score than LSTM-based predictors, especially for the rare structures 310-helix (G), beta-bridge (B), and high curvature loop (S). It is also competitive on challenging datasets without homologs, free-modeling targets, and chameleon sequences. Moreover, ProteinUnetLM outperformed its previous MSA-based version ProteinUnet2, and provided better AGM than AlphaFold2 for 1/3 of proteins from the CASP14 dataset, proving its potential for making a significant step forward in the domain. To facilitate the usage of our solution by protein scientists, we provide an easy-to-use web interface under https://biolib.com/SUT/ProteinUnetLM/.

Information quantity for secondary structure propensities of protein subsequences in the Protein Data Bank.

Elucidating the principles of sequence–structure relationships of proteins is a long-standing issue in biology. The nature of a short segment of a protein is determined by both the subsequence of the segment itself and its environment. For example, a type of subsequence, the so-called chameleon sequences, can form different secondary structures depending on its environments. Chameleon sequences are considered to have a weak tendency to form a specific structure. Although many chameleon sequences have been identified, they are only a small part of all possible subsequences in the proteome. The strength of the tendency to take a specific structure for each subsequence has not been fully quantified. In this study, we comprehensively analyzed subsequences consisting of four to nine amino acid residues, or N-gram (4≤N≤9), observed in non-redundant sequences in the Protein Data Bank (PDB). Tendencies to form a specific structure in terms of the secondary structure and accessible surface area are quantified as information quantities for each N-gram. Although the majority of observed subsequences have low information quantity due to lack of samples in the current PDB, thousands of N-grams with strong tendencies, including known structural motifs, were found. In addition, machine learning partially predicted the tendency of unknown N-grams, and thus, this technique helps to extract knowledge from the limited number of samples in the PDB.

Foldability and chameleon propensity of fold-switching protein sequences.

It has been shown recently by Porter & Looger that a significant number of proteins exist that can form more than one stable fold. This note examines the sequences of these fold-switching proteins by (a) calculating their foldability scores recently introduced by the present author and (b) comparing the propensity of chameleon sequences in fold switchers and in non fold switchers. It has been found that the average foldability score of the fold switchers indicates weaker foldability. As for the propensity of chameleon sequences of length 5 to 7 it was found, somewhat surprisingly, that there is only a very small difference between the fold switchers and the non fold switchers. Furthermore, when looking at amino acid propensities, for several amino acids there was even an opposing trend in the deviation of their propensities from the overall amino acid propensities.

Turncoat Polypeptides: We Adapt to Our Environment.

A common interpretation of Anfinsen's hypothesis states that one amino acid sequence should fold into a single, native, ordered state, or a highly similar set thereof, coinciding with the global minimum in the folding-energy landscape, which, in turn, is responsible for the function of the protein. However, this classical view is challenged by many proteins and peptide sequences, which can adopt exchangeable, significantly dissimilar conformations that even fulfill different biological roles. The similarities and differences of concepts related to these proteins, mainly chameleon sequences, metamorphic proteins, and switch peptides, which are all denoted herein "turncoat" polypeptides, are reviewed. As well as adding a twist to the conventional view of protein folding, the lack of structural definition adds clear versatility to the activity of proteins and can be used as a tool for protein design and further application in biotechnology and biomedicine.

Conformational Switch Driven Membrane Pore Formation by Mycobacterium Secretory Protein MPT63 Induces Macrophage Cell Death

Virulent Mycobacterium tuberculosis (MTB) strains cause cell death of macrophages (Mϕ) inside TB granuloma using a mechanism which is not well understood. Many bacterial systems utilize toxins to induce host cell damage, which occurs along with immune evasion. These toxins often use chameleon sequences to generate an environment-sensitive conformational switch, facilitating the process of infection. The presence of toxins is not yet known for MTB. Here, we show that MTB-secreted immunogenic MPT63 protein undergoes a switch from β-sheet to helix in response to mutational and environmental stresses. MPT63 in its helical form creates pores in both synthetic and Mϕ membranes, while the native β-sheet protein remains inert toward membrane interactions. Using fluorescence correlation spectroscopy and atomic force microscopy, we show further that the helical form undergoes self-association to produce toxic oligomers of different morphology. Trypan blue and flow cytometry analyses reveal that the helical state can be utilized by MTB for killing Mϕ cells. Collectively, our study emphasizes for the first time a toxin-like behavior of MPT63 induced by an environment-dependent conformational switch, resulting in membrane pore formation by toxic oligomers and Mϕ cell death.

β-sheet elasticity of peptide self-assembly mimic, PSAM, with a grafted sequence characterized by comprehensive analyses of isomorphous crystals

Peptides and proteins are self-assembled into β-rich self-assemblies such as amyloids in liquid water environments. Despite its importance, detailed structural analysis of this class is hindered by their insoluble and heterogeneous nature. For circumventing this problem, we designed a peptide self-assembly mimic (PSAM) that consists of a central single-layer β-sheet (SLB) capped by terminal domains. In a previous study, we grafted part of an amyloid forming chameleon sequence into a PSAM (termed PSAM-VLGDV1) and found a β-sheet bending at SLB induced by the grafted sequence using x-ray crystallography (Hori et al., 2019 [1]). Later, we found that another crystal structure of PSAM-VLGDV1 obtained from an isomorphous crystal had a different conformation and we gained an interest in the structural differences of PSAMs within isomorphous crystals. Herein, we report the structural variations trapped within isomorphous crystals by comprehensive structure determinations. Additionally, we demonstrate the structural plasticity of PSAM-VLGDV1 via molecular dynamics simulations. Hydration structure analysis revealed that water molecule locates on the β-sheet surface is important for its plasticity. Our findings suggest that a marginal structural difference can be trapped at the time of crystal core formation, which propagates during crystal growth. Our results suggest that structural plasticity of β-sheet would play an important role in the macroscopic shape formation of peptide self-assemblies.

Grafting a short chameleon sequence from αB crystallin into a β-sheet scaffold protein.

Many protein and peptide sequences are self-assembled into β-sheet-rich fibrous structures called amyloids. Their atomic details provide insights into fundamental knowledge related to amyloid diseases. To study the detailed structure of the amyloid, we have developed a model system that mimics the self-assembling process of the amyloid within a water-soluble protein, termed peptide self-assembly mimic (PSAM). PSAM enables capturing of a peptide sequence within a water-soluble protein, thus making structural and energetics-related studies possible. In this work, we extend our PSAM approach to a naturally occurring chameleon sequence from αB crystallin. We chose "Val-Leu-Gly-Asp-Val (VLGDV)", a five amino-acid sequence, which forms a β-turn in the native structure and a β-barrel in the amyloid oligomer cylindrin, as a grafting sequence to the PSAM scaffold. The crystal structure revealed that the sequence grafting induced β-sheet bending at the grafted site. We further investigated the role of the central glycine residue and found that its role in the β-sheet bending is dependent on the neighboring residues. The ability of PSAM to observe the structural alterations induced by the grafted sequence provides an opportunity to evaluate the structural impact of a sequence from the peptide self-assembly.

Multistep mutational transformation of a protein fold through structural intermediates.

New protein folds may evolve from existing folds through metamorphic evolution involving a dramatic switch in structure. To mimic pathways by which amino acid sequence changes could induce a change in fold, we designed two folded hybrids of Xfaso 1 and Pfl 6, a pair of homologous Cro protein sequences with ~40% identity but different folds (all-α vs. α + β, respectively). Each hybrid, XPH1 or XPH2, is 85% identical in sequence to its parent, Xfaso 1 or Pfl 6, respectively; 55% identical to its noncognate parent; and ~70% identical to the other hybrid. XPH1 and XPH2 also feature a designed hybrid chameleon sequence corresponding to the C-terminal region, which switched from α-helical to β-sheet structure during Cro evolution. We report solution nuclear magnetic resonance (NMR) structures of XPH1 and XPH2 at 0.3 Å and 0.5 Å backbone root mean square deviation (RMSD), respectively. XPH1 retains a global fold generally similar to Xfaso 1, and XPH2 retains a fold similar to Pfl 6, as measured by TM-align scores (~0.7), DALI Z-scores (7-9), and backbone RMSD (2-3 Å RMSD for the most ordered regions). However, these scores also indicate significant deviations in structure. Most notably, XPH1 and XPH2 have different, and intermediate, secondary structure content relative to Xfaso 1 and Pfl 6. The multistep progression in sequence, from Xfaso 1 to XPH1 to XPH2 to Pfl 6, thus involves both abrupt and gradual changes in folding pattern. The plasticity of some protein folds may allow for "polymetamorphic" evolution through intermediate structures.

Revisiting Chameleon Sequences in the Protein Data Bank

The steady growth of the Protein Data Bank (PDB) suggests the periodic repetition of searches for sequences that form different secondary structures in different protein structures; these are called chameleon sequences. This paper presents a fast (nlog(n)) algorithm for such searches and presents the results on all protein structures in the PDB. The longest such sequence found consists of 20 residues.

The Cancer Mutation D83V Induces an α-Helix to β-Strand Conformation Switch in MEF2B

MEF2B is a major target of somatic mutations in non-Hodgkin lymphoma. Most of these mutations are non-synonymous substitutions of surface residues in the MADS-box/MEF2 domain. Among them, D83V is the most frequent mutation found in tumor cells. The link between this hotspot mutation and cancer is not well understood. Here we show that the D83V mutation induces a dramatic α-helix to β-strand switch in the MEF2 domain. Located in an α-helix region rich in β-branched residues, the D83V mutation not only removes the extensive helix stabilization interactions but also introduces an additional β-branched residue that further shifts the conformation equilibrium from α-helix to β-strand. Cross-database analyses of cancer mutations and chameleon sequences revealed a number of well-known cancer targets harboring β-strand favoring mutations in chameleon α-helices, suggesting a commonality of such conformational switch in certain cancers and a new factor to consider when stratifying the rapidly expanding cancer mutation data.

Prediction of Protein Aggregation Propensities using GOR Method

The original GOR method published by Garnier, Osguthorpe, and Robson in 1978 was one of the first successful methods to predict protein secondary structure from amino acid sequence [1]. The method is based on information theory. The analysis of frequencies of occurrence of secondary structure for singlets and doublets of residues in a protein database enables prediction of secondary structure for new amino acid sequences. Because of these simple physical assumptions and the ability to predict the probability of formation of beta-strands for each residue in protein sequence GOR method has a conceptual advantage over other later developed methods such as PHD, PSIPRED, and others that are based on Machine Learning methods that have a “black box” nature. The GOR method has been continuously improved and modified for 30 years with the last GOR V version published in 2002 [2], its modification in 2006 [3] and the GOR V server developed in 2005 [4]. Recently we applied GOR method to chameleon sequences in protein folding simulations, and for prediction of protein aggregation propensities [5]. Fibril prone regions of polypeptides were predicted by estimation the probability to form beta-strand secondary structure. The probability of amino acid to form beta-strand corresponds to its aggregation propensity. Our preliminary studies show that the GOR method is a promising and efficient alternative to other protein aggregation predicting tools. A web server for prediction of protein aggregation propensities is currently being developed.

A network biology approach to understanding the importance of chameleon proteins in human physiology and pathology.

Chameleon proteins are proteins which include sequences that can adopt α-helix-β-strand (HE-chameleon) or α-helix-coil (HC-chameleon) or β-strand-coil (CE-chameleon) structures to operate their crucial biological functions. In this study, using a network-based approach, we examined the chameleon proteins to give a better knowledge on these proteins. We focused on proteins with identical chameleon sequences with more than or equal to seven residues long in different PDB entries, which adopt HE-chameleon, HC-chameleon, and CE-chameleon structures in the same protein. One hundred and ninety-one human chameleon proteins were identified via our in-house program. Then, protein-protein interaction (PPI) networks, Gene ontology (GO) enrichment, disease network, and pathway enrichment analyses were performed for our derived data set. We discovered that there are chameleon sequences which reside in protein-protein interaction regions between two proteins critical for their dual function. Analysis of the PPI networks for chameleon proteins introduced five hub proteins, namely TP53, EGFR, HSP90AA1, PPARA, and HIF1A, which were presented in four PPI clusters. The outcomes demonstrate that the chameleon regions are in critical domains of these proteins and are important in the development and treatment of human cancers. The present report is the first network-based functional study of chameleon proteins using computational approaches and might provide a new perspective for understanding the mechanisms of diseases helping us in developing new medical therapies along with discovering new proteins with chameleon properties which are highly important in cancer.

The GOR Method of Protein Secondary Structure Prediction and Its Application as a Protein Aggregation Prediction Tool.

The GOR method of protein secondary structure prediction is described. The original method was published by Garnier, Osguthorpe, and Robson in 1978 and was one of the first successful methods to predict protein secondary structure from amino acid sequence. The method is based on information theory, and an assumption that information function of a protein chain can be approximated by a sum of information from single residues and pairs of residues. The analysis of frequencies of occurrence of secondary structure for singlets and doublets of residues in a protein database enables prediction of secondary structure for new amino acid sequences. Because of these simple physical assumptions the GOR method has a conceptual advantage over other later developed methods such as PHD, PSIPRED, and others that are based on Machine Learning methods (like Neural Networks), give slightly better predictions, but have a "black box" nature. The GOR method has been continuously improved and modified for 30 years with the last GOR V version published in 2002, and the GOR V server developed in 2005. We discuss here the original GOR method and the GOR V program and the web server. Additionally we discuss new highly interesting and important applications of the GOR method to chameleon sequences in protein folding simulations, and for prediction of protein aggregation propensities. Our preliminary studies show that the GOR method is a promising and efficient alternative to other protein aggregation predicting tools. This shows that the GOR method despite being almost 40 years old is still important and has significant potential in application to new scientific problems.

Aggregation of Chameleon Peptides: Implications of α-Helicity in Fibril Formation.

We investigate the relationship between the inherent secondary structure and aggregation propensity of peptides containing chameleon sequences (i.e., sequences that can adopt either α or β structure depending on context) using a combination of replica exchange molecular dynamics simulations, ion-mobility mass spectrometry, circular dichroism, and transmission electron microscopy. We focus on an eight-residue long chameleon sequence that can adopt an α-helical structure in the context of the iron-binding protein from Bacillus anthracis (PDB id 1JIG ) and a β-strand in the context of the baculovirus P35 protein (PDB id 1P35 ). We show that the isolated chameleon sequence is intrinsically disordered, interconverting between α-helical and β-rich conformations. The inherent conformational plasticity of the sequence can be constrained by addition of flanking residues with a given secondary structure propensity. Intriguingly, we show that the chameleon sequence with helical flanking residues aggregates rapidly into fibrils, whereas the chameleon sequence with flanking residues that favor β-conformations has weak aggregation propensity. This work sheds new insights into the possible role of α-helical intermediates in fibril formation.

Chameleon sequences in neurodegenerative diseases.

Chameleon sequences can adopt either alpha helix sheet or a coil conformation. Defining chameleon sequences in PDB (Protein Data Bank) may yield to an insight on defining peptides and proteins responsible in neurodegeneration. In this research, we benefitted from the large PDB and performed a sequence analysis on Chameleons, where we developed an algorithm to extract peptide segments with identical sequences, but different structures. In order to find new chameleon sequences, we extracted a set of 8315 non-redundant protein sequences from the PDB with an identity less than 25%. Our data was classified to “helix to strand (HE)”, “helix to coil (HC)” and “strand to coil (CE)” alterations. We also analyzed the occurrence of singlet and doublet amino acids and the solvent accessibility in the chameleon sequences; we then sorted out the proteins with the most number of chameleon sequences and named them Chameleon Flexible Proteins (CFPs) in our dataset. Our data revealed that Gly, Val, Ile, Tyr and Phe, are the major amino acids in Chameleons. We also found that there are proteins such as Insulin Degrading Enzyme IDE and GTP-binding nuclear protein Ran (RAN) with the most number of chameleons (640 and 405 respectively). These proteins have known roles in neurodegenerative diseases. Therefore it can be inferred that other CFP's can serve as key proteins in neurodegeneration, and a study on them can shed light on curing and preventing neurodegenerative diseases.

Sequence-to-Structure Relation in Proteins-Amyloidogenic Proteins with Chameleon Sequences

The existence of polypeptide chain fragments in which identical sequences translate into different secondary folds gives rise to questions concerning the structural variability associated with amyloidogenesis. In this paper the structural contribution of identical sequences to a common hydrophobic core is assessed on the basis of the fuzzy oil drop model. The model compares the observed hydrophobicity density distribution in a protein molecule to its idealized counterpart, where all hydrophilic residues are exposed on the surface while all hydrophobic residues are internalized. The conformational variability of such fragments is thought to be associated with their role: they either participate in the formation of a stable core, or become involved in mediating the protein’s biological function. The fuzzy oil drop model provides clues as to the role of chameleon sequences in prions, seen as potential loci of conformational changes resulting in amyloidogenesis.