Are Most Human-Specific Proteins Encoded by Long Noncoding RNAs?

By looking for a lack of homologs in a reference database of 27 well-annotated proteomes of primates and 52 well-annotated proteomes of other mammals, 170 putative human-specific proteins were identified. While most of them are deemed uncertain, 2 are known at the protein level and 23 at the transcript level, according to UniProt. Interestingly, 23 of these 25 proteins are found to be encoded or to have close homologs in an open reading frame of a long noncoding human RNA. However, half of them are predicted to be at least 80% globular, with a single structural domain, according to IUPred, and with at least 80% of ordered residues, according to flDPnn. Strikingly, there is a near-complete lack of structural knowledge about these proteins, with no tertiary structure presently available in the Protein Data Bank and a fair prediction for one of them in the AlphaFold Protein Structure Database. Moreover, knowledge about the function of these possibly key proteins remains scarce.

On the Unknown Proteins of Eukaryotic Proteomes.

To study unknown proteins on a large scale, a reference system has been set up for the three better studied eukaryotic kingdoms, built with 36 proteomes as taxonomically diverse as possible. Proteins from 362 other eukaryotic proteomes with no known homologue in this set were then analyzed, focusing noteworthy on singletons, that is, on such proteins with no known homologue in their own proteome. Consistently, for a given species, no more than 12% of the singletons thus found are known at the protein level, according to Uniprot. In addition, since they rely on the information found in the alignment of homologous sequences, predictions of AlphaFold2 for their tridimensional structure are poor. In the case of metazoan species, the number of singletons rarely exceeds 1000 for the species the closest to the reference system (divergence times below 75 Myr). Interestingly, in the cases of viridiplantae and fungi, larger amounts of singletons are found for such species, as if the timescale on which singletons are added to proteomes were different in metazoa and in other eukaryotic kingdoms. In order to confirm this phenomenon, further studies of proteomes closer to those of the reference system are, however, needed.

At least three xenon binding sites in the glycine binding domain of the N-methyl D-aspartate receptor.

Xenon can produce general anesthesia. Its main protein target is the N-methyl-D-aspartate receptor, a ionotropic channel playing a pivotal role in the function of the central nervous system. The molecular mechanisms allowing this noble gas to have such a specific effect remain obscure, probably as a consequence of the lack of structural data at the atomic level of detail. As a result of five independent molecular dynamics simulations, three different binding sites were found for xenon in the glycine binding domain of the N-methyl-D-aspartate receptor, the xenon binding constant being of the order of 2 108 s-1⋅M-1. On the other hand, the absolute binding free energy of xenon in these sites ranges between -3 and -14 kJ⋅mole-1. Noteworthy, it depends significantly upon the protein conformer chosen for performing the calculation, suggesting that larger values could be obtained, if other conformers were considered. These three sites are next to each other, one of them being next to the glycine site. This could noteworthy explain why the F758W and F758Y mutations can prevent competitive inhibition by xenon without affecting glycine binding.

Normal-mode driven exploration of protein domain motions.

Domain motions involved in the function of proteins can often be well described as a combination of motions along a handfull of low-frequency modes, that is, with the values of a few normal coordinates. This means that, when the functional motion of a protein is unknown, it should prove possible to predict it, since it amounts to guess a few values. However, without the help of additional experimental data, using normal coordinates for generating accurate conformers far away from the initial one is not so straightforward. To do so, a new approach is proposed: instead of building conformers directly with the values of a subset of normal coordinates, they are built in two steps, the conformer built with normal coordinates being just used for defining a set of distance constraints, the final conformer being built so as to match them. Note that this approach amounts to transform the problem of generating accurate protein conformers using normal coordinates into a better known one: the distance-geometry problem, which is herein solved with the help of the ROSETTA software. In the present study, this approach allowed to rebuild accurately six large amplitude conformational changes, using at most six low-frequency normal coordinates. As a consequence of the low-dimensionality of the corresponding subspace, random exploration also proved enough for generating low-energy conformers close to the known end-point of the conformational change of the LAO binding protein, lysozyme T4 and adenylate kinase.

Rational Enzyme Design without Structural Knowledge: A Sequence-Based Approach for Efficient Generation of Transglycosylases.

Glycobiology is dogged by the relative scarcity of synthetic, defined oligosaccharides. Enzyme-catalysed glycosylation using glycoside hydrolases is feasible but is hampered by the innate hydrolytic activity of these enzymes. Protein engineering is useful to remedy this, but it usually requires prior structural knowledge of the target enzyme, and/or relies on extensive, time-consuming screening and analysis. Here, a straightforward strategy that involves rational rapid in silico analysis of protein sequences is described. The method pinpoints 6-12 single-mutant candidates to improve transglycosylation yields. Requiring very little prior knowledge of the target enzyme other than its sequence, the method is generic and procures catalysts for the formation of glycosidic bonds involving various d/l-, α/ß-pyranosides or furanosides, and exo or endo action. Moreover, mutations validated in one enzyme can be transposed to others, even distantly related enzymes.

On the vibrational free energy of hydrated proteins.

When the hydration shell of a protein is filled with at least 0.6 gram of water per gram of protein, a significant anti-correlation between the vibrational free energy and the potential energy of energy-minimized conformers is observed. This means that low potential energy, well-hydrated, protein conformers tend to be more rigid than high-energy ones. On the other hand, in the case of CASP target 624, when its hydration shell is filled, a significant energy gap is observed between the crystal structure and the best conformers proposed during the prediction experiment, strongly suggesting that including explicit water molecules may help identifying unlikely conformers among good-looking ones.

Numerous severely twisted N-acetylglucosamine conformations found in the protein databank.

Taking advantage of the known planarity of the N-acetyl group of N-acetylglucosamine, an analysis of the quality of carbohydrate structures found in the protein databank was performed. Few obvious defects of the local geometry of the carbonyl group were observed. However, the N-acetyl group was often found in the less favorable cis conformation (12% of the cases). It was also found severely twisted in numerous instances, especially in structures with a resolution poorer than 1.9 Å determined between 2000 and 2015. Though the automated PDB-REDO procedure has proved able to improve nearly 85% of the structural models deposited to the PDB, and does prove able to cure most severely twisted conformations of the N-acetyl group, it fails to correct its high rate of cis conformations. More generally, for structures with a resolution poorer than 1.6 Å, it produces N-acetylglucosamine models in slightly poorer agreement with experimental data, as measured using real-space correlation coefficients. Significant improvements are thus still needed, at least as far as this carbohydrate structure is concerned.

Toward the design of efficient transglycosidases: the case of the GH1 of Thermus thermophilus.

Using the information available in the sequences of well-characterized transglycosidases found in plants, mutations were introduced in the glycoside hydrolase of the bacterium Thermus thermophilus, with the aim of turning it into an efficient transglycosidase. All mutants happen to have fair catalytic efficiencies, being at worst 25 times less efficient than the wild type. Noteworthy, W120F, one of our high transglycosylation yield (≈ 50%) mutants, is only two times less efficient than the wild type. Interestingly, while in the wild type the sidechain of the acid-base is only found able to sample a pair of equivalent conformations during 0.5-µs-long molecular dynamics simulations, its flexibility is much higher in the case of the high transglycosylation yield mutants. Our results thus suggest that engineering the flexibility of the acid-base of a retaining glycoside hydrolase could be a general way to turn it into an efficient transglycosidase.

Knowledge-based prediction of protein backbone conformation using a structural alphabet.

Libraries of structural prototypes that abstract protein local structures are known as structural alphabets and have proven to be very useful in various aspects of protein structure analyses and predictions. One such library, Protein Blocks, is composed of 16 standard 5-residues long structural prototypes. This form of analyzing proteins involves drafting its structure as a string of Protein Blocks. Predicting the local structure of a protein in terms of protein blocks is the general objective of this work. A new approach, PB-kPRED is proposed towards this aim. It involves (i) organizing the structural knowledge in the form of a database of pentapeptide fragments extracted from all protein structures in the PDB and (ii) applying a knowledge-based algorithm that does not rely on any secondary structure predictions and/or sequence alignment profiles, to scan this database and predict most probable backbone conformations for the protein local structures. Though PB-kPRED uses the structural information from homologues in preference, if available. The predictions were evaluated rigorously on 15,544 query proteins representing a non-redundant subset of the PDB filtered at 30% sequence identity cut-off. We have shown that the kPRED method was able to achieve mean accuracies ranging from 40.8% to 66.3% depending on the availability of homologues. The impact of the different strategies for scanning the database on the prediction was evaluated and is discussed. Our results highlight the usefulness of the method in the context of proteins without any known structural homologues. A scoring function that gives a good estimate of the accuracy of prediction was further developed. This score estimates very well the accuracy of the algorithm (R2 of 0.82). An online version of the tool is provided freely for non-commercial usage at http://www.bo-protscience.fr/kpred/.

A singular mutation in the hemagglutinin of the 1918 pandemic virus.

The influenza pandemic of 1918-1919 killed at least 50 million people. The reasons why this pandemic was so deadly remain largely unknown [9]. However, It has been shown that the 1918 viral hemagglutinin allows to reproduce the hallmarks of the illness observed during the original pandemic [11]. Thanks to the wealth of hemagglutinin sequences accumulated over the last decades, amino-acid substitutions that are found in the 1918-1919 sequences but rare otherwise can be identified with high confidence. Noteworthy, Gly 188, which is located within a key motif of the receptor binding site, has never been observed again in sequences of human viruses of subtype H1. Monitoring this singular mutation in viral sequences may help prevent another dramatic pandemic.

Jumping between protein conformers using normal modes.

The relationship between the normal modes of a protein and its functional conformational change has been studied for decades. However, using this relationship in a predictive context remains a challenge. In this work, we demonstrate that, starting from a given protein conformer, it is possible to generate in a single step model conformers that are less than 1 Å (Cα -RMSD) from the conformer which is the known endpoint of the conformational change, particularly when the conformational change is collective in nature. Such accurate model conformers can be generated by following either the so-called robust or the 50 lowest-frequency modes obtained with various Elastic Network Models (ENMs). Interestingly, the quality of many of these models compares well with actual crystal structures, as assessed by the ROSETTA scoring function and PROCHECK. The most accurate and best quality conformers obtained in the present study were generated by using the 50 lowest-frequency modes of an all-atom ENM. However, with less than ten robust modes, which are identified without any prior knowledge of the nature of the conformational change, nearly 90% of the motion described by the 50 lowest-frequency modes of a protein can be captured. Such results strongly suggest that exploring the robust modes of ENMs may prove efficient for sampling the functionally relevant conformational repertoire of many proteins. © 2017 Wiley Periodicals, Inc.

On the relationship between low-frequency normal modes and the large-scale conformational changes of proteins.

Normal mode analysis is a computational technique that allows to study the dynamics of biological macromolecules. It was first applied to small protein cases, more than thirty years ago. The interest in this technique then raised when it was realized that it can provide insights about the large-scale conformational changes a protein can experience, for instance upon ligand binding. As it was also realized that studying highly simplified protein models can provide similar insights, meaning that this kind of analysis can be both quick and simple to handle, several applications were proposed, in the context of various structural biology techniques. This review focuses on these applications, as well as on how the functional relevance of the lowest-frequency modes of proteins was established.

Semi-rational approach for converting a GH36 α-glycosidase into an α-transglycosidase.

A large number of retaining glycosidases catalyze both hydrolysis and transglycosylation reactions. In order to use them as catalysts for oligosaccharide synthesis, the balance between these two competing reactions has to be shifted toward transglycosylation. We previously designed a semi-rational approach to convert the Thermus thermophilus ß-glycosidases into transglycosidases by mutating highly conserved residues located around the -1 subsite. In an attempt to verify that this strategy could be a generic approach to turn glycosidases into transglycosidases, Geobacillus stearothermophilus α-galactosidase (AgaB) was selected in order to obtain α-transgalactosidases. This is of particular interest as, to date, there are no efficient α-galactosynthases, despite the considerable importance of α-galactooligosaccharides. Thus, by site-directed mutagenesis on 14 AgaB residues, 26 single mutants and 22 double mutants were created and screened, of which 11 single mutants and 6 double mutants exhibited improved synthetic activity, producing 4-nitrophenyl α-d-galactopyranosyl-(1,6)-α-d-galactopyranoside in 26-57% yields against only 22% when native AgaB was used. It is interesting to note that the best variant was obtained by mutating a second-shell residue, with no direct interaction with the substrate or a catalytic amino acid. As this approach has proved to be efficient with both α- and ß-glycosidases, it is a promising route to convert retaining glycosidases into transglycosidases.

Use of a structural alphabet to find compatible folds for amino acid sequences.

The structural annotation of proteins with no detectable homologs of known 3D structure identified using sequence-search methods is a major challenge today. We propose an original method that computes the conditional probabilities for the amino-acid sequence of a protein to fit to known protein 3D structures using a structural alphabet, known as "Protein Blocks" (PBs). PBs constitute a library of 16 local structural prototypes that approximate every part of protein backbone structures. It is used to encode 3D protein structures into 1D PB sequences and to capture sequence to structure relationships. Our method relies on amino acid occurrence matrices, one for each PB, to score global and local threading of query amino acid sequences to protein folds encoded into PB sequences. It does not use any information from residue contacts or sequence-search methods or explicit incorporation of hydrophobic effect. The performance of the method was assessed with independent test datasets derived from SCOP 1.75A. With a Z-score cutoff that achieved 95% specificity (i.e., less than 5% false positives), global and local threading showed sensitivity of 64.1% and 34.2%, respectively. We further tested its performance on 57 difficult CASP10 targets that had no known homologs in PDB: 38 compatible templates were identified by our approach and 66% of these hits yielded correctly predicted structures. This method scales-up well and offers promising perspectives for structural annotations at genomic level. It has been implemented in the form of a web-server that is freely available at http://www.bo-protscience.fr/forsa.

Semi-rational approach for converting a GH1 ß-glycosidase into a ß-transglycosidase.

A large number of retaining glycosidases catalyze both hydrolysis and transglycosylation reactions, but little is known about what determines the balance between these two activities (transglycosylation/hydrolysis ratio). We previously obtained by directed evolution the mutants F401S and N282T of Thermus thermophilus ß-glycosidase (Ttß-gly, glycoside hydrolase family 1 (GH1)), which display a higher transglycosylation/hydrolysis ratio than the wild-type enzyme. In order to find the cause of these activity modifications, and thereby set up a generic method for easily obtaining transglycosidases from glycosidases, we determined their X-ray structure. No major structural changes could be observed which could help to rationalize the mutagenesis of glycosidases into transglycosidases. However, as these mutations are highly conserved in GH1 ß-glycosidases and are located around the -1 site, we pursued the isolation of new transglycosidases by targeting highly conserved amino acids located around the active site. Thus, by single-point mutagenesis on Ttß-gly, we created four new mutants that exhibit improved synthetic activity, producing disaccharides in yields of 68-90% against only 36% when native Ttß-gly was used. As all of the chosen positions were well conserved among GH1 enzymes, this approach is most probably a general route to convert GH1 glycosidases into transglycosidases.

Conserved water molecules in family 1 glycosidases: a DXMS and molecular dynamics study.

By taking advantage of the wealth of structural data available for family 1 glycoside hydrolases, a study of the conservation of internal water molecules found in this ubiquitous family of enzymes was undertaken. Strikingly, seven water molecules are observed in more than 90% of the known structures. To gain insight into their possible function, the water dynamics inside Thermus thermophilus ß-glycosidase was probed using deuterium exchange mass spectroscopy, allowing the pinpointing of peptide L117-A125, which exchanges most of its amide hydrogens quickly in spite of the fact that it is for the most part buried in the crystal structure. To help interpret this result, a molecular dynamics simulation was performed whose analysis suggests that two water channels are involved in the process. The longest one (∼16 Å) extends between the protein surface and W120, whose side chain interacts with E164 (the acid-base residue involved in the catalytic mechanism), whereas the other channel allows for the exchange with the bulk of the highly conserved water molecules belonging to the hydration shell of D121, a deeply buried residue. Our simulation also shows that another chain of highly conserved water molecules, going from the protein surface to the bottom of the active site cleft close to the nucleophile residue involved in the catalytic mechanism, is able to exchange with the bulk on the nanosecond time scale. It is tempting to speculate that at least one of these three water channels could be involved in the function of family 1 glycoside hydrolases.

Elastic network models: theoretical and empirical foundations.

Fifteen years ago, Monique Tirion showed that the low-frequency normal modes of a protein are not significantly altered when nonbonded interactions are replaced by Hookean springs, for all atom pairs whose distance is smaller than a given cutoff value. Since then, it has been shown that coarse-grained versions of Tirion's model are able to provide fair insights on many dynamical properties of biological macromolecules. In this chapter, theoretical tools required for studying these so-called Elastic Network Models are described, focusing on practical issues and, in particular, on possible artifacts. Then, an overview of some typical results that have been obtained by studying such models is given.

Changing the solvent accessibility of the prion protein disulfide bond markedly influences its trafficking and effect on cell function.

Prion diseases are fatal transmissible neurodegenerative diseases that result from structural conversion of the prion protein into a disease-associated isoform. The prion protein contains a single disulfide bond. Our analysis of all NMR structures of the prion protein (total of 440 structures over nine species) containing an explicit disulfide bond reveals that the bond exists predominantly in a stable low-energy state, but can also adopt a high-energy configuration. The side chains of two tyrosine residues and one phenylalanine residue control access of solvent to the disulfide bond. Notably, the side chains rotate away from the disulfide bond in the high-energy state, exposing the disulfide bond to solvent. The importance of these aromatic residues for protein function was analysed by mutating them to alanine residues and analysing the properties of the mutant proteins using biophysical and cell biological approaches. Whereas the mutant protein behaved similarly to wild-type prion protein in recombinant systems, the mutants were retained in the endoplasmic reticulum of mammalian cells and degraded by the proteasomal system. The cellular behaviour of the aromatic residue mutants was similar to the cellular behaviour of a disulfide bond mutant prion protein in which the cysteine residues were replaced with alanine, a result which is consistent with an unstable disulfide bond in the aromatic residue mutants. These observations suggest that the conformation of the prion protein disulfide bond may have implications for correct maturation and function of this protein.

Long-range energy transfer in proteins.

Proteins are large and complex molecular machines. In order to perform their function, most of them need energy, e.g. either in the form of a photon, as in the case of the visual pigment rhodopsin, or through the breaking of a chemical bond, as in the presence of adenosine triphosphate (ATP). Such energy, in turn, has to be transmitted to specific locations, often several tens of A away from where it is initially released. Here we show, within the framework of a coarse-grained nonlinear network model, that energy in a protein can jump from site to site with high yields, covering in many instances remarkably large distances. Following single-site excitations, few specific sites are targeted, systematically within the stiffest regions. Such energy transfers mark the spontaneous formation of a localized mode of nonlinear origin at the destination site, which acts as an efficient energy-accumulating center. Interestingly, yields are found to be optimum for excitation energies in the range of biologically relevant ones.

Discrete breathers in protein structures.

Recently, using a numerical surface cooling approach, we have shown that highly energetic discrete breathers (DBs) can form in the stiffest parts of nonlinear network models of large protein structures. In the present study, using an analytical approach, we extend our previous results to low-energy discrete breathers as well as to smaller proteins. We confirm and further scrutinize the striking site selectiveness of energy localization in the presence of spatial disorder. In particular, we find that, as a sheer consequence of disorder, a non-zero energy gap for exciting a DB at a given site either exists or not. Remarkably, in the former case, the gaps arise as a result of the impossibility of exciting small-amplitude modes in the first place. In contrast, in the latter case, a small subset of linear edge modes acts as accumulation points, whereby DBs can be continued to arbitrary small energies, while unavoidably approaching one of such normal modes. In particular, the case of the edge mode seems peculiar, its dispersion relation being simple and little system dependent. Concerning the structure-dynamics relationship, we find that the regions of protein structures where DBs form easily (zero or small gaps) are unfailingly the most highly connected ones, also characterized by weak local clustering. Remarkably, a systematic analysis on a large database of enzyme structures reveals that amino-acid residues involved in catalysis tend to be located in such regions. This finding reinforces the idea that localized modes of nonlinear origin may play an important biological role, e.g., by providing a ready channel for energy storage and/or contributing to lower energy barriers of chemical reactions.