From local structure to a global framework: recognition of protein folds

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.

A Synopsis of Proteins and Their Purification

The goal of protein purification is to separate a specific protein from all other biomolecules. Classical chromatographic procedures have been designed to exploit particular distinguishing features of individual target proteins, such as size, shape, physicochemical properties, and binding affinity. Advances in molecular biology and bioinformatics have positively contributed at every level to the challenge of purifying individual proteins and more recently have led to the development of high-throughput proteomic platforms. In this chapter, a synopsis of advancements in the field of protein chromatography is presented, with reference to the principal tools and resources that are available to assist with protein purification strategies.

Protein remote homology recognition using local and global structural sequence alignment

Protein Remote Homology and fold Recognition (PRHR) is the most crucial task to predict the protein patterns. To achieve this task, Sequence-Order Frequency Matrix-Sampling and Deep learning with Smith-Waterman (SOFM-SDSW) were designed using large-scale Protein Sequences (PSs), which take more time to determine the high-dimensional attributes. Also, it was ineffective since the SW was only applied for local alignment, which cannot find the most matches between the PSs. Hence, in this manuscript, a rapid semi-global alignment algorithm called SOFM-SD-GlobalSW (SOFM-SDGSW) is proposed that facilitates the affine-gap scoring and uses sequence similarity to align the PSs. The major aim of this paper is to enhance the alignment of SW algorithm in both locally and globally for PRHR. In this algorithm, the Maximal Exact Matches (MEMs) are initially obtained by the bit-level parallelism rather than to align the individual characters. After that, a subgroup of MEMs is obtained to determine the global Alignment Score (AS) using the new adaptive programming scheme. Also, the SW local alignment scheme is used to determine the local AS. Then, both local and global ASs are combined to produce a final AS. Further, this resultant AS is considered to train the Support Vector Machine (SVM) classifier to recognize the PRH and folds. Finally, the test results reveal the SOFM-SDGSW algorithm on SCOP 1.53, SCOP 1.67 and Superfamily databases attains an ROC of 0.97, 0.941 and 0.938, respectively, as well as, an ROC50 of 0.819, 0.846 and 0.86, respectively compared to the conventional PRHR algorithms.

Quadruply Stranded Metallo-Supramolecular Helicate [Pd2(hextrz)4]4+ Acts as a Molecular Mimic of Cytolytic Peptides

[Pd₂(hextrz)₄]⁴⁺ is a quadruply stranded helicate, a novel bioinorganic complex designed to mimic the structure and function of proteins due to its high stability and supramolecular size. We have previously reported that [Pd₂(hextrz)₄]⁴⁺ exhibited cytotoxicity toward a range of cell lines, with IC₅₀ values ranging from 3 to 10 μM. Here we demonstrate that [Pd₂(hextrz)₄]⁴⁺ kills cells by forming pores within the cell membrane, a mechanism of cell death analogous to the naturally occurring cytolytic peptides. [Pd₂(hextrz)₄]⁴⁺ induced cell death is characterized by an initial influx of Ca²⁺, followed by nuclear condensation and mitochondrial swelling. This is accompanied by progressive cell membrane damage that results in the formation of large blebs at the cell surface. This allows the efflux of molecules from the cell leading to loss of cell viability. These data suggest that it may be possible to design metallo-supramolecular complexes to mimic the cytotoxic action of pore forming proteins and peptides and so provide a new class of drug to treat cancer, autoimmune disorders, and microbial infection.

Structural analysis of the Aβ(11-42) amyloid fibril based on hydrophobicity distribution

The structure of the Aβ(11–42) amyloid available in PDB makes possible the molecular analysis of the specificity of amyloid formation. This molecule (PDB ID 2MVX) is the object of analysis. This work presents the outcome of in silico experiments involving various alternative conformations of the Aβ(11–42) sequence, providing clues as to the amylodogenecity of its constituent fragments. The reference structure (PDB) has been compared with folds generated using I-Tasser and Robetta—the strongest contenders in the CASP challenge. Additionally, a polypeptide which matches the Aβ(11–42) sequence has been subjected to folding simulations based on the fuzzy oil drop model, which favors the production of a monocentric hydrophobic core. Computer simulations yielded 15 distinct structural forma (five per software package), which, when compared to the experimentally determined structure, allow us to study the role of structural elements which cause an otherwise globular protein to transform into an amyloid. The unusual positions of hydrophilic residues disrupting the expected hydrophobic core and propagating linearly along the long axis of fibril is recognized as the seed for amyloidogenic transformation in this polypeptide. This paper discusses the structure of the Aβ(11–42) amyloid fibril, listed in PDB under ID 2MXU (fragment od Aβ(1–42) amyloid).

Analysing the Structural Effect of Point Mutations of Cytotoxic Necrotizing Factor 1 (CNF1) on Lu/BCAM Adhesion Glycoprotein Association

Cytotoxic Necrotizing Factor 1 (CNF1) was identified in 1983 as a protein toxin produced by certain pathogenic strains of Escherichia coli. Since then, numerous studies have investigated its particularities. For instance, it is associated with the single chain AB-toxin family, and can be divided into different functional and structural domains, e.g., catalytic and transmembrane domain and interaction sites. A few years ago, the identification of the Lutheran (Lu) adhesion glycoprotein/basal cell adhesion molecule (BCAM) as a cellular receptor for CNF1 provided new insights into the adhesion process of CNF1. Very recently, the Ig-like domain 2 of Lu/BCAM was confirmed as the main interaction site using protein-protein interaction and competition studies with various different mutants. Here, I present in silico approaches that precisely explain the impact of these mutations, leading to a better explanation of these experimental studies. These results can be used in the development of future antitoxin strategies.

A Synopsis of Proteins and Their Purification

The isolation of a given protein, free of all other biomolecules, is the primary objective of any protein purification scheme. Classical chromatographic procedures have been designed to exploit particular distinguishing features of individual target proteins, such as size, physicochemical properties, and binding affinity. Advances in molecular biology and bioinformatics have positively contributed at every level to the challenge of purifying individual proteins and more recently have led to the development of high-throughput proteomic platforms. Here, a synopsis of developments in the field of protein chromatography is given, with reference to the principal tools and resources that are available to assist with protein purification processes.

Using Local States To Drive the Sampling of Global Conformations in Proteins

Conformational changes associated with protein function often occur beyond the time scale currently accessible to unbiased molecular dynamics (MD) simulations, so that different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in precalculated libraries known as structural alphabets (SA), can be used to explore the landscape of protein conformations in MD simulations. We find that (a) enhancing the sampling of native local states in both metadynamics and steered MD simulations allows the recovery of global folded states in small proteins; (b) folded states can still be recovered when the amount of information on the native local states is reduced by using a low-resolution version of the SA, where states are clustered into macrostates; and (c) sequences of SA states derived from collections of structural motifs can be used to sample alternative conformations of preselected protein regions. The present findings have potential impact on several applications, ranging from protein model refinement to protein folding and design.

Protein flexibility in the light of structural alphabets

Protein structures are valuable tools to understand protein function. Nonetheless, proteins are often considered as rigid macromolecules while their structures exhibit specific flexibility, which is essential to complete their functions. Analyses of protein structures and dynamics are often performed with a simplified three-state description, i.e., the classical secondary structures. More precise and complete description of protein backbone conformation can be obtained using libraries of small protein fragments that are able to approximate every part of protein structures. These libraries, called structural alphabets (SAs), have been widely used in structure analysis field, from definition of ligand binding sites to superimposition of protein structures. SAs are also well suited to analyze the dynamics of protein structures. Here, we review innovative approaches that investigate protein flexibility based on SAs description. Coupled to various sources of experimental data (e.g., B-factor) and computational methodology (e.g., Molecular Dynamic simulation), SAs turn out to be powerful tools to analyze protein dynamics, e.g., to examine allosteric mechanisms in large set of structures in complexes, to identify order/disorder transition. SAs were also shown to be quite efficient to predict protein flexibility from amino-acid sequence. Finally, in this review, we exemplify the interest of SAs for studying flexibility with different cases of proteins implicated in pathologies and diseases.