A Closer Look at Type I Left-Handed ß-Helices Provides a Better Understanding in Their Sequence-Structure Relationship: Toward Their Rational Design.

Understanding the sequence-structure relationship in protein is of fundamental interest, but has practical applications such as the rational design of peptides and proteins. This relationship in the Type I left-handed ß-helix containing proteins is updated and revisited in this study. Analyzing the available experimental structures in the Protein Data Bank, we could describe, further in detail, the structural features that are important for the stability of this fold, as well as its nucleation and termination. This study is meant to complete previous work, as it provides a separate analysis of the N-terminal and C-terminal rungs of the helix. Particular sequence motifs of these rungs are described along with the structural element they form.

Evaluation of the Potential Impact of In Silico Humanization on VHH Dynamics.

Camelids have the peculiarity of having classical antibodies composed of heavy and light chains as well as single-chain antibodies. They have lost their light chains and one heavy-chain domain. This evolutionary feature means that their terminal heavy-chain domain, VH, called VHH here, has no partner and forms an independent domain. The VHH is small and easy to express alone; it retains thermodynamic and interaction properties. Consequently, VHHs have garnered significant interest from both biotechnological and pharmaceutical perspectives. However, due to their origin in camelids, they cannot be used directly on humans. A humanization step is needed before a possible use. However, changes, even in the constant parts of the antibodies, can lead to a loss of quality. A dedicated tool, Llamanade, has recently been made available to the scientific community. In a previous paper, we already showed the different types of VHH dynamics. Here, we have selected a representative VHH and tested two humanization hypotheses to accurately assess the potential impact of these changes. This example shows that despite the non-negligible change (1/10th of residues) brought about by humanization, the effect is not drastic, and the humanized VHH retains conformational properties quite similar to those of the camelid VHH.

Statistical proofs of the interdependence between nearest neighbor effects on polypeptide backbone conformations.

Backbone dihedral angles ϕ and ψ are the main structural descriptors of proteins and peptides. The distribution of these angles has been investigated over decades as they are essential for the validation and refinement of experimental measurements, as well as for structure prediction and design methods. The dependence of these distributions, not only on the nature of each amino acid but also on that of the closest neighbors, has been the subject of numerous studies. Although neighbor-dependent distributions are nowadays generally accepted as a good model, there is still some controversy about the combined effects of left and right neighbors. We have investigated this question using rigorous methods based on recently-developed statistical techniques. Our results unambiguously demonstrate that the influence of left and right neighbors cannot be considered independently. Consequently, three-residue fragments should be considered as the minimal building blocks to investigate polypeptide sequence-structure relationships.

Analysis of Integrin αIIb Subunit Dynamics Reveals Long-Range Effects of Missense Mutations on Calf Domains.

Integrin αIIbß3, a glycoprotein complex expressed at the platelet surface, is involved in platelet aggregation and contributes to primary haemostasis. Several integrin αIIbß3 polymorphisms prevent the aggregation that causes haemorrhagic syndromes, such as Glanzmann thrombasthenia (GT). Access to 3D structure allows understanding the structural effects of polymorphisms related to GT. In a previous analysis using Molecular Dynamics (MD) simulations of αIIbCalf-1 domain structure, it was observed that GT associated with single amino acid variation affects distant loops, but not the mutated position. In this study, experiments are extended to Calf-1, Thigh, and Calf-2 domains. Two loops in Calf-2 are unstructured and therefore are modelled expertly using biophysical restraints. Surprisingly, MD revealed the presence of rigid zones in these loops. Detailed analysis with structural alphabet, the Proteins Blocks (PBs), allowed observing local changes in highly flexible regions. The variant P741R located at C-terminal of Calf-1 revealed that the Calf-2 presence did not affect the results obtained with isolated Calf-1 domain. Simulations for Calf-1 + Calf-2, and Thigh + Calf-1 variant systems are designed to comprehend the impact of five single amino acid variations in these domains. Distant conformational changes are observed, thus highlighting the potential role of allostery in the structural basis of GT.

VHH Structural Modelling Approaches: A Critical Review.

VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.

A Perspective on the (Rise and Fall of) Protein ß-Turns.

The ß-turn is the third defined secondary structure after the α-helix and the ß-sheet. The ß-turns were described more than 50 years ago and account for more than 20% of protein residues. Nonetheless, they are often overlooked or even misunderstood. This poor knowledge of these local protein conformations is due to various factors, causes that I discuss here. For example, confusion still exists about the assignment of these local protein structures, their overlaps with other structures, the potential absence of a stabilizing hydrogen bond, the numerous types of ß-turns and the software's difficulty in assigning or visualizing them. I also propose some ideas to potentially/partially remedy this and present why ß-turns can still be helpful, even in the AlphaFold 2 era.

Sequence-Dependent Nanofiber Structures of Phenylalanine and Isoleucine Tripeptides.

The molecular design of short peptides to achieve a tailor-made functional architecture has attracted attention during the past decade but remains challenging as a result of insufficient understanding of the relationship between peptide sequence and assembled supramolecular structures. We report a hybrid-resolution model to computationally explore the sequence-structure relationship of self-assembly for tripeptides containing only phenylalanine and isoleucine. We found that all these tripeptides have a tendency to assemble into nanofibers composed of laterally associated filaments. Molecular arrangements within the assemblies are diverse and vary depending on the sequences. This structural diversity originates from (1) distinct conformations of peptide building blocks that lead to different surface geometries of the filaments and (2) unique sidechain arrangements at the filament interfaces for each sequence. Many conformations are available for tripeptides in solution, but only an extended ß-strand and another resembling a right-handed turn are observed in assemblies. It was found that the sequence dependence of these conformations and the packing of resulting filaments are determined by multiple competing noncovalent forces, with hydrophobic interactions involving Phe being particularly important. The sequence pattern for each type of assembly conformation and packing has been identified. These results highlight the importance of the interplay between conformation, molecular packing, and sequences for determining detailed nanostructures of peptides and provide a detailed insight to support a more precise design of peptide-based nanomaterials.

Increased sequence hydrophobicity reduces conformational specificity: A mutational case study of the Arc repressor protein.

The amino-acid sequences of soluble, globular proteins must have hydrophobic residues to form a stable core, but excess sequence hydrophobicity can lead to loss of native state conformational specificity and aggregation. Previous studies of polar-to-hydrophobic mutations in the ß-sheet of the Arc repressor dimer showed that a single substitution at position 11 (N11L) leads to population of an alternate dimeric fold in which the ß-sheet is replaced by helix. Two additional hydrophobic mutations at positions 9 and 13 (Q9V and R13V) lead to population of a differently folded octamer along with both dimeric folds. Here we conduct a comprehensive study of the sequence determinants of this progressive loss of fold specificity. We find that the alternate dimer-fold specifically results from the N11L substitution and is not promoted by other hydrophobic substitutions in the ß-sheet. We also find that three highly hydrophobic substitutions at positions 9, 11, and 13 are necessary and sufficient for oligomer formation, but the oligomer size depends on the identity of the hydrophobic residue in question. The hydrophobic substitutions increase thermal stability, illustrating how increased hydrophobicity can increase folding stability even as it degrades conformational specificity. The oligomeric variants are predicted to be aggregation-prone but may be hindered from doing so by proline residues that flank the ß-sheet region. Loss of conformational specificity due to increased hydrophobicity can manifest itself at any level of structure, depending upon the specific mutations and the context in which they occur.

Classification of ß-hairpin repeat proteins.

In recent years, a number of new protein structures that possess tandem repeats have emerged. Many of these proteins are comprised of tandem arrays of ß-hairpins. Today, the amount and variety of the data on these ß-hairpin repeat (BHR) structures have reached a level that requires detailed analysis and further classification. In this paper, we classified the BHR proteins, compared structures, sequences of repeat motifs, functions and distribution across the major taxonomic kingdoms of life and within organisms. As a result, we identified six different BHR folds in tandem repeat proteins of Class III (elongated structures) and one BHR fold (up-and-down ß-barrel) in Class IV ("closed" structures). Our survey reveals the high incidence of the BHR proteins among bacteria and viruses and their possible relationship to the structures of amyloid fibrils. It indicates that BHR folds will be an attractive target for future structural studies, especially in the context of age-related amyloidosis and emerging infectious diseases. This work allowed us to update the RepeatsDB database, which contains annotated tandem repeat protein structures and to construct sequence profiles based on BHR structural alignments.

Understanding and designing head-to-tail cyclic peptides.

Cyclic peptides (CPs) are an exciting class of molecules with a variety of applications. However, design strategies for CP therapeutics, for example, are generally limited by a poor understanding of their sequence-structure relationships. This knowledge gap often leads to a trial-and-error approach for designing CPs for a specific purpose, which is both costly and time-consuming. Herein, we describe the current experimental and computational efforts in understanding and designing head-to-tail CPs along with their respective challenges. In addition, we provide several future directions in the field of computational CP design to improve its accuracy, efficiency and applicability. These advances, combined with experimental techniques, shall ultimately provide a better understanding of these interesting molecules and a reliable working platform to rationally design CPs with desired characteristics.

Recent advances on polyproline II.

About half of the globular proteins are composed of regular secondary structures, α-helices, and ß-sheets, while the rest are constituted of irregular secondary structures, such as turns or coil conformations. Other regular secondary structures are often ignored, despite their importance in biological processes. Among such structures, the polyproline II helix (PPII) has interesting behaviours. PPIIs are not usually associated with conventional stabilizing interactions, and recent studies have observed that PPIIs are more frequent than anticipated. In addition, it is suggested that they may have an important functional role, particularly in protein-protein or protein-nucleic acid interactions and recognition. Residues associated with PPII conformations represent nearly 5% of the total residues, but the lack of PPII assignment approaches prevents their systematic analysis. This short review will present current knowledge and recent research in PPII area. In a first step, the different methodologies able to assign PPII are presented. In the second step, recent studies that have shown new perspectives in PPII analysis in terms of structure and function are underlined with three cases: (1) PPII in protein structures. For instance, the first crystal structure of an oligoproline adopting an all-trans polyproline II (PPII) helix had been presented; (2) the involvement of PPII in different diseases and drug designs; and (3) an interesting extension of PPII study in the protein dynamics. For instance, PPIIs are often linked to disorder region analysis and the precise analysis of a potential PPII helix in hypogonadism shows unanticipated PPII formations in the patient mutation, while it is not observed in the wild-type form of KISSR1 protein.

7TM Domain Structure of Adhesion GPCRs.

Schematic presentation of the overall adhesion G Protein-Coupled Receptor (aGPCR) structure and functional domains, covering an extracellular N-terminal fragment (NTF), a membrane-spanning C-terminal fragment (CTF) and a GPCR proteolysis site (GPS). (Left side) aGPCR model constructed based on the seven-transmembrane (7TM) structure (blue) of secretin family glucagon receptor (GCGR) (PDB, 4L6R) [11] and the GPCR autoproteolysis inducing (GAIN) domain (magenta) structure of latrophilin 1 (PDB, 4DLQ) [9]. The ß-13 strand residues are depicted in green. (Right side) The experimentally validated full-length secretin family GCGR structure combining structural and experimental information from the GCGR 7TM crystal structure (PDB, 4L6R) (blue), the GCGR extracellular domain (ECD) structure (PDB, 4ERS) (magenta) and the ECD structure of glucagon-like peptide-1 (GLP-1)-bound glucagon-like peptide-1 receptor (GLP-1R) (PDB, 3IOL) (green), complemented by site-directed mutagenesis, electron microscopy (EM), hydrogen-deuterium exchange (HDX) and cross-linking studies [11-13]) Despite the recent breakthroughs in the elucidation of the three-dimensional structures of the seven transmembrane (7TM) domain of the G protein-coupled receptor (GPCR) superfamily, a corresponding structure of a member of the adhesion GPCR (aGPCR) family has not yet been solved. In this chapter, we give an overview of the current knowledge of the 7TM domain of aGPCRs by comparative structure-based sequence similarity analyses between aGPCRs and GPCRs with known crystal structure. Of the GPCR superfamily, only the secretin family shares some sequence similarity with aGPCRs. This chapter will therefore emphasize on the comparison of these two GPCR families. Two 7TM domain structures of secretin family GPCRs are known that provide insight into the structure-function relationships of conserved sequence motifs that play important roles and are also present in most aGPCRs. This suggests that the 7TM domains of aGPCRs and secretin family GPCRs share a similar structural fold and that the conserved residues in both families may be involved in similar intermolecular interaction networks and facilitate similar conformational changes. Comparison of the residues that line the large peptide hormone binding pocket in the 7TM domain of secretin family GPCRs with corresponding residues in aGPCRs indicates that in the latter, the corresponding pocket in the 7TM domain is relatively hydrophobic and may be even larger. Improved knowledge on these conserved sequence motifs will help to understand the interactions of the aGPCR 7TM domain with ligands and gain insight into the activation mechanism of aGPCRs.

Sequence-dependent structural changes in a self-assembling DNA oligonucleotide.

DNA has proved to be a remarkable molecule for the construction of sophisticated two-dimensional and three-dimensional architectures because of its programmability and structural predictability provided by complementary Watson-Crick base pairing. DNA oligonucleotides can, however, exhibit a great deal of local structural diversity. DNA conformation is strongly linked to both environmental conditions and the nucleobase identities inherent in the oligonucleotide sequence, but the exact relationship between sequence and local structure is not completely understood. This study examines how a single-nucleotide addition to a class of self-assembling DNA 13-mers leads to a significantly different overall structure under identical crystallization conditions. The DNA 13-mers self-assemble in the presence of Mg(2+) through a combination of Watson-Crick and noncanonical base-pairing interactions. The crystal structures described here show that all of the predicted Watson-Crick base pairs are present, with the major difference being a significant rearrangement of noncanonical base pairs. This includes the formation of a sheared A-G base pair, a junction of strands formed from base-triple interactions, and tertiary interactions that generate structural features similar to tandem sheared G-A base pairs. The adoption of this alternate noncanonical structure is dependent in part on the sequence in the Watson-Crick duplex region. These results provide important new insights into the sequence-structure relationship of short DNA oligonucleotides and demonstrate a unique interplay between Watson-Crick and noncanonical base pairs that is responsible for crystallization fate.

Sequence-structure relationship study in all-α transmembrane proteins using an unsupervised learning approach.

Transmembrane proteins (TMPs) are major drug targets, but the knowledge of their precise topology structure remains highly limited compared with globular proteins. In spite of the difficulties in obtaining their structures, an important effort has been made these last years to increase their number from an experimental and computational point of view. In view of this emerging challenge, the development of computational methods to extract knowledge from these data is crucial for the better understanding of their functions and in improving the quality of structural models. Here, we revisit an efficient unsupervised learning procedure, called Hybrid Protein Model (HPM), which is applied to the analysis of transmembrane proteins belonging to the all-α structural class. HPM method is an original classification procedure that efficiently combines sequence and structure learning. The procedure was initially applied to the analysis of globular proteins. In the present case, HPM classifies a set of overlapping protein fragments, extracted from a non-redundant databank of TMP 3D structure. After fine-tuning of the learning parameters, the optimal classification results in 65 clusters. They represent at best similar relationships between sequence and local structure properties of TMPs. Interestingly, HPM distinguishes among the resulting clusters two helical regions with distinct hydrophobic patterns. This underlines the complexity of the topology of these proteins. The HPM classification enlightens unusual relationship between amino acids in TMP fragments, which can be useful to elaborate new amino acids substitution matrices. Finally, two challenging applications are described: the first one aims at annotating protein functions (channel or not), the second one intends to assess the quality of the structures (X-ray or models) via a new scoring function deduced from the HPM classification.

Designability landscape reveals sequence features that define axial helix rotation in four-helical homo-oligomeric antiparallel coiled-coil structures.

Coiled coils are widespread protein domains comprising α-helices wound around each other in a regular fashion. Owing to their regularity, coiled-coil structures can be fully described by parametric equations. This in turn makes them an excellent model for studying sequence-structure relationships in proteins. Here, we used computational design to identify sequence features that determine the degree of helix axial rotation in four-helical homo-oligomeric antiparallel coiled coils. We designed 135,000 artificial sequences for a repertoire of backbone models representing all theoretically possible axial rotation states. Analysis of the designed sequences revealed features that precisely define the rotation of the helices. Based on these features we implemented a bioinformatic tool, which given a coiled-coil sequence, predicts the rotation of the helices in its structure. Moreover, we showed that another structural parameter, helix axial shift, is coupled to helix axial rotation and that dependence between these two parameters narrows the number of possible axial rotation states.

The blobulator: a webtool for identification and visual exploration of hydrophobic modularity in protein sequences.

Motivation: Clusters of hydrophobic residues are known to promote structured protein stability and drive protein aggregation. Recent work has shown that identifying contiguous hydrophobic residue clusters (termed "blobs") has proven useful in both intrinsically disordered protein (IDP) simulation and human genome studies. However, a graphical interface was unavailable. Results: Here, we present the blobulator: an interactive and intuitive web interface to detect intrinsic modularity in any protein sequence based on hydrophobicity. We demonstrate three use cases of the blobulator and show how identifying blobs with biologically relevant parameters provides useful information about a globular protein, two orthologous membrane proteins, and an IDP. Other potential applications are discussed, including: predicting protein segments with critical roles in tertiary interactions, providing a definition of local order and disorder with clear edges, and aiding in predicting protein features from sequence. Availability: The blobulator GUI can be found at www.blobulator.branniganlab.org, and the source code with pip installable command line tool can be found on GitHub at www.GitHub.com/BranniganLab/blobulator.

Quality assessment of VHH models.

Heavy Chain Only Antibodies are specific to Camelid species. Despite the lack of the light chain variable domain, their heavy chain variable domain (VH) domain, named VHH or nanobody, has promising potential applications in research and therapeutic fields. The structural study of VHH is therefore of great interest. Unfortunately, considering the huge amount of sequences that might be produced, only about one thousand of VHH experimental structures are publicly available in the Protein Data Bank, implying that structural model prediction of VHH is a necessary alternative to obtaining 3D information besides its sequence. The present study aims to assess and compare the quality of predictions from different modelling methodologies. Established comparative & homology modelling approaches to recent Deep Learning-based modelling strategies were applied, i.e. Modeller using single or multiple structural templates, ModWeb, SwissModel (with two evaluation schema), RoseTTAfold, AlphaFold 2 and NanoNet. The prediction accuracy was evaluated using RMSD, TM-score, GDT-TS, GDT-HA and Protein Blocks distance metrics. Besides the global structure assessment, we performed specific analyses of Frameworks and CDRs structures. We observed that AlphaFold 2 and especially NanoNet performed better than the other evaluated softwares. Importantly, we performed molecular dynamics simulations of an experimental structure and a NanoNet predicted model of a VHH in order to compare the global structural flexibility and local conformations using Protein Blocks. Despite rather similar structures, substantial differences in dynamical properties were observed, which underlies the complexity of the task of model evaluation.Communicated by Ramaswamy H. Sarma.

Local sequence-structure relationships in proteins.

We seek to understand the interplay between amino acid sequence and local structure in proteins. Are some amino acids unique in their ability to fit harmoniously into certain local structures? What is the role of sequence in sculpting the putative native state folds from myriad possible conformations? In order to address these questions, we represent the local structure of each Cα atom of a protein by just two angles, θ and µ, and we analyze a set of more than 4,000 protein structures from the PDB. We use a hierarchical clustering scheme to divide the 20 amino acids into six distinct groups based on their similarity to each other in fitting local structural space. We present the results of a detailed analysis of patterns of amino acid specificity in adopting local structural conformations and show that the sequence-structure correlation is not very strong compared with a random assignment of sequence to structure. Yet, our analysis may be useful to determine an effective scoring rubric for quantifying the match of an amino acid to its putative local structure.

Discrete analysis of camelid variable domains: sequences, structures, and in-silico structure prediction.

Antigen binding by antibodies requires precise orientation of the complementarity- determining region (CDR) loops in the variable domain to establish the correct contact surface. Members of the family Camelidae have a modified form of immunoglobulin gamma (IgG) with only heavy chains, called Heavy Chain only Antibodies (HCAb). Antigen binding in HCAbs is mediated by only three CDR loops from the single variable domain (VHH) at the N-terminus of each heavy chain. This feature of the VHH, along with their other important features, e.g., easy expression, small size, thermo-stability and hydrophilicity, made them promising candidates for therapeutics and diagnostics. Thus, to design better VHH domains, it is important to thoroughly understand their sequence and structure characteristics and relationship. In this study, sequence characteristics of VHH domains have been analysed in depth, along with their structural features using innovative approaches, namely a structural alphabet. An elaborate summary of various studies proposing structural models of VHH domains showed diversity in the algorithms used. Finally, a case study to elucidate the differences in structural models from single and multiple templates is presented. In this case study, along with the above-mentioned aspects of VHH, an exciting view of various factors in structure prediction of VHH, like template framework selection, is also discussed.

Folding by numbers: primary sequence statistics and their use in studying protein folding.

The exponential growth over the past several decades in the quantity of both primary sequence data available and the number of protein structures determined has provided a wealth of information describing the relationship between protein primary sequence and tertiary structure. This growing repository of data has served as a prime source for statistical analysis, where underlying relationships between patterns of amino acids and protein structure can be uncovered. Here, we survey the main statistical approaches that have been used for identifying patterns within protein sequences, and discuss sequence pattern research as it relates to both secondary and tertiary protein structure. Limitations to statistical analyses are discussed, and a context for their role within the field of protein folding is given. We conclude by describing a novel statistical study of residue patterning in beta-strands, which finds that hydrophobic (i,i+2) pairing in beta-strands occurs more often than expected at locations near strand termini. Interpretations involving beta-sheet nucleation and growth are discussed.