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Protein structures are often represented as seen in crystals as (i) rigid macromolecules (ii) with helices, sheets and coils. However, both definitions are partial because (i) proteins are highly dynamic macromolecules and (ii) the description of protein structures could be more precise. With regard to these two points, we analyzed and quantified the stability of helices by considering α-helices as well as 310- and π-helices. Molecular dynamic (MD) simulations were performed on a large set of 169 representative protein domains. The local protein conformations were followed during each simulation and analyzed. The classical flexibility index (B-factor) was confronted with the MD root mean square flexibility (RMSF) index. Helical regions were classified according to their level of helicity from high to none. For the first time, a precise quantification showed the percentage of rigid and flexible helices that underlie unexpected behaviors. Only 76.4% of the residues associated with α-helices retain the conformation, while this tendency drops to 40.5% for 310-helices and is never observed for π-helices. α-helix residues that do not remain as an α-helix have a higher tendency to assume β-turn conformations than 310- or π-helices. The 310-helices that switch to the α-helix conformation have a higher B-factor and RMSF values than the average 310-helix but are associated with a lower accessibility. Rare π-helices assume a β-turn, bend and coil conformations, but not α- or 310-helices. The view on π-helices drastically changes with the new DSSP (Dictionary of Secondary Structure of Proteins) assignment approach, leading to behavior similar to 310-helices, thus underlining the importance of secondary structure assignment methods.

Camelids produce a special type of antibody, known as VHHs, that has lost the VL domain, providing a more optimised VH domain. This particular highly stable antibody domain has interesting properties for biotechnological development. Ordinarily, those molecules possess only one disulphide bridge, but surprisingly, at least a quarter of these VHHs have a second one. Curiously, this does not seem to be essential for the stability and the function of this domain. In an attempt to characterise precisely the role and impact of this disulphide bridge at the molecular level, several in silico mutants of a VHH were created to disrupt this second disulphide bridge and those systems were submitted to molecular dynamics simulation. The loss of the second disulphide bridge leads to an increase in the flexibility of CDR1 and CDR3 and an unexpected rigidification of CDR2. Local conformational analysis shows local differences in the observed protein conformations. However, in fact, there is no exploration of new conformations but a change in the equilibrium between the different observed conformations. This explains why the interaction of VHHs is not really affected by the presence or absence of this second bridge, but their rigidity is slightly reduced. Therefore, the additional disulphide bridge does not seem to be an essential part of VHHs function. [ABSTRACT FROM AUTHOR]

The text discusses the importance of 3D protein structures in understanding biological functions and highlights the use of molecular modelling approaches to create high-quality structural models. Various deep learning approaches have enabled significant progress in this field, with molecular dynamics simulations playing a crucial role in understanding protein dynamics. The document also presents specific research articles focusing on protein structures, including the modelling of Helicobacter pylori proteins, the analysis of human cyclin-dependent kinase CDK8, and the study of human vitamin K epoxide reductase. Additionally, reviews on protein kinase C isoforms and peptides as allosteric modulators of protein kinase C are provided, along with a new perspective on the study of Fos-related antigen-2 in respiratory diseases. [Extracted from the article]

BioMedInformatics is a journal that focuses on the intersection of medical science and bioinformatics. It covers a wide range of topics, including computational biology, medicine, and the application of computational tools to biological data. The journal has published over 130 articles and reviews since its creation in 2021 and is indexed by SCOPUS. The articles cover various areas such as oncogenic markers, genomic analysis of dementia, genomic techniques for detecting and monitoring pathogens, immunoglobulin annotation, artificial intelligence in biomedical research, and deep learning in computational pathology. The journal aims to contribute to advancements in personalized medicine and therapeutic strategies. The document provides a summary of several articles published in the field of bioinformatics, including topics such as novel biomarkers for Uterine Corpus Endometrial Carcinoma (UCEC), protein structure prediction methods, evaluation of transmembrane protein models, applications of deep learning in drug discovery, physical and functional training for the elderly, medical devices for the rehabilitation of bedridden patients, automatic detection of facial paralysis, age, and gender, and evaluation of heart rate patterns in patients with arrhythmia problems. These articles showcase the diverse topics and advancements in the field of bioinformatics. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

Conformational flexibility plays an essential role in antibodies' functional and structural stability. They facilitate and determine the strength of antigen–antibody interactions. Camelidae express an interesting subtype of single-chain antibody, named Heavy Chain only Antibody. They have only one N-terminal Variable domain (VHH) per chain, composed of Frameworks (FRs) and Complementarity Determining regions (CDRs) like their VH and VL counterparts in IgG. Even when expressed independently, VHH domains display excellent solubility and (thermo)stability, which helps them to retain their impressive interaction capabilities. Sequence and structural features of VHH domains contributing to these abilities have already been studied compared to classical antibodies. To have the broadest view and understand the changes in dynamics of these macromolecules, large-scale molecular dynamics simulations for a large number of non-redundant VHH structures have been performed for the first time. This analysis reveals the most prevalent movements in these domains. It reveals the four main classes of VHHs dynamics. Diverse local changes were observed in CDRs with various intensities. Similarly, different types of constraints were observed in CDRs, while FRs close to CDRs were sometimes primarily impacted. This study sheds light on the changes in flexibility in different regions of VHH that may impact their in silico design. [ABSTRACT FROM AUTHOR]

Background: Scianna (Sc) antigens, seven high and two of low prevalence, are expressed on erythrocyte membrane‐associated protein (ERMAP). We investigated SC (ERMAP) in individuals who made antibodies to high prevalence Scianna antigens, and propose a 3D model for ERMAP to precisely localize the residues associated with the known antigens. Methods: Serological testing and DNA sequencing was performed by standard methods. A 3D structural model was built using a multi‐template homology approach. Protein structures representing missense variants associated with the loss or gain of an antigen were generated. Residue accessibility and intraprotein interactions were compared with the wild‐type protein. Results: Two new SC alleles, one with c.349C > T (p.Arg117Cys) in a woman from South India with anti‐Sc3 in her plasma, and a c.217_219delinsTGT (p.Arg73Cys) in an African‐American woman with an antibody to a new high prevalence antigen, termed SCAC, were identified. Six structural templates were used to model ERMAP. 3D analysis showed that residues key for Scianna antigen expression were all exposed at the surface of the extracellular domain. The p.Arg117Cys change was predicted to abolish interactions between residues 93 and 117, with no compensating interactions. Conclusion: We confirm the extracellular location of Scianna residues responsible for antigen expression which predicts direct accessibility to antibodies. Loss of intraprotein interactions appear to be responsible for a Sc null and production of anti‐Sc3 with p.117Cys, SC*01 N.03, and for loss of a high prevalence antigen with p.73Cys, termed SCAC for Sc Arg to Cys. Comparative modeling aids our understanding of new alleles and Scianna antigen expression. [ABSTRACT FROM AUTHOR]