Pathogenicity of de novo CACNA1D Ca2+ channel variants predicted from sequence co-variation.

Voltage-gated L-type Cav1.3 Ca2+ channels support numerous physiological functions including neuronal excitability, sinoatrial node pacemaking, hearing, and hormone secretion. De novo missense mutations in the gene of their pore-forming α1-subunit (CACNA1D) induce severe gating defects which lead to autism spectrum disorder and a more severe neurological disorder with and without endocrine symptoms. The number of CACNA1D variants reported is constantly rising, but their pathogenic potential often remains unclear, which complicates clinical decision-making. Since functional tests are time-consuming and not always available, bioinformatic tools further improving pathogenicity potential prediction of novel variants are needed. Here we employed evolutionary analysis considering sequences of the Cav1.3 α1-subunit throughout the animal kingdom to predict the pathogenicity of human disease-associated CACNA1D missense variants. Co-variation analyses of evolutionary information revealed residue-residue couplings and allowed to generate a score, which correctly predicted previously identified pathogenic variants, supported pathogenicity in variants previously classified as likely pathogenic and even led to the re-classification or re-examination of 18 out of 80 variants previously assessed with clinical and electrophysiological data. Based on the prediction score, we electrophysiologically tested one variant (V584I) and found significant gating changes associated with pathogenic risks. Thus, our co-variation model represents a valuable addition to complement the assessment of the pathogenicity of CACNA1D variants completely independent of clinical diagnoses, electrophysiology, structural or biophysical considerations, and solely based on evolutionary analyses.

The Role of Force Fields and Water Models in Protein Folding and Unfolding Dynamics.

Protein folding is a fascinating, not fully understood phenomenon in biology. Molecular dynamics (MD) simulations are an invaluable tool to study conformational changes in atomistic detail, including folding and unfolding processes of proteins. However, the accuracy of the conformational ensembles derived from MD simulations inevitably relies on the quality of the underlying force field in combination with the respective water model. Here, we investigate protein folding, unfolding, and misfolding of fast-folding proteins by examining different force fields with their recommended water models, i.e., ff14SB with the TIP3P model and ff19SB with the OPC model. To this end, we generated long conventional MD simulations highlighting the perks and pitfalls of these setups. Using Markov state models, we defined kinetically independent conformational substates and emphasized their distinct characteristics, as well as their corresponding state probabilities. Surprisingly, we found substantial differences in thermodynamics and kinetics of protein folding, depending on the combination of the protein force field and water model, originating primarily from the different water models. These results emphasize the importance of carefully choosing the force field and the respective water model as they determine the accuracy of the observed dynamics of folding events. Thus, the findings support the hypothesis that the water model is at least equally important as the force field and hence needs to be considered in future studies investigating protein dynamics and folding in all areas of biophysics.

Addressing Challenges of Macrocyclic Conformational Sampling in Polar and Apolar Solvents: Lessons for Chameleonicity.

We evaluated a workflow to reliably sample the conformational space of a set of 47 peptidic macrocycles. Starting from SMILES strings, we use accelerated molecular dynamics simulations to overcome high energy barriers, in particular, the cis-trans isomerization of peptide bonds. We find that our approach performs very well in polar solvents like water and dimethyl sulfoxide. Interestingly, the protonation state of a secondary amine in the ring only slightly influences the conformational ensembles of our test systems. For several of the macrocycles, determining the conformational distribution in chloroform turns out to be considerably more challenging. Especially, the choice of partial charges crucially influences the ensembles in chloroform. We address these challenges by modifying initial structures and the choice of partial charges. Our results suggest that special care has to be taken to understand the configurational distribution in apolar solvents, which is a key step toward a reliable prediction of membrane permeation of macrocycles and their chameleonic properties.

Evolution of the Immunoglobulin Isotypes-Variations of Biophysical Properties among Animal Classes.

The adaptive immune system arose around 500 million years ago in jawed fish, and, since then, it has mediated the immune defense against pathogens in all vertebrates. Antibodies play a central role in the immune reaction, recognizing and attacking external invaders. During the evolutionary process, several immunoglobulin isotypes emerged, each having a characteristic structural organization and dedicated function. In this work, we investigate the evolution of the immunoglobulin isotypes, in order to highlight the relevant features that were preserved over time and the parts that, instead, mutated. The residues that are coupled in the evolution process are often involved in intra- or interdomain interactions, meaning that they are fundamental to maintaining the immunoglobulin fold and to ensuring interactions with other domains. The explosive growth of available sequences allows us to point out the evolutionary conserved residues and compare the biophysical properties among different animal classes and isotypes. Our study offers a general overview of the evolution of immunoglobulin isotypes and advances the knowledge of their characteristic biophysical properties, as a first step in guiding protein design from evolution.

Structural Characterization of Nanobodies during Germline Maturation.

Camelid heavy-chain antibody variable domains (VHH), nanobodies, are the smallest-known functional antibody fragments with high therapeutic potential. In this study, we investigate a VHH binding to hen egg-white lysozyme (HEL). We structurally and dynamically characterized the conformational diversity of four VHH variants to elucidate the antigen-binding process. For two of these antibodies, not only are the dissociation constants known, but also the experimentally determined crystal structures of the VHH in complex with HEL are available. We performed well-tempered metadynamics simulations in combination with molecular dynamics simulations to capture a broad conformational space and to reconstruct the thermodynamics and kinetics of conformational transitions in the antigen-binding site, the paratope. By kinetically characterizing the loop movements of the paratope, we found that, with an increase in affinity, the state populations shift towards the binding competent conformation. The contacts contributing to antigen binding, and those who contribute to the overall stability, show a clear trend towards less variable but more intense contacts. Additionally, these investigated nanobodies clearly follow the conformational selection paradigm, as the binding competent conformation pre-exists within the structural ensembles without the presence of the antigen.

Challenges in antibody structure prediction.

Advances in structural biology and the exponential increase in the amount of high-quality experimental structural data available in the Protein Data Bank has motivated numerous studies to tackle the grand challenge of predicting protein structures. In 2020 AlphaFold2 revolutionized the field using a combination of artificial intelligence and the evolutionary information contained in multiple sequence alignments. Antibodies are one of the most important classes of biotherapeutic proteins. Accurate structure models are a prerequisite to advance biophysical property predictions and consequently antibody design. Specialized tools used to predict antibody structures based on different principles have profited from current advances in protein structure prediction based on artificial intelligence. Here, we emphasize the importance of reliable protein structure models and highlight the enormous advances in the field, but we also aim to increase awareness that protein structure models, and in particular antibody models, may suffer from structural inaccuracies, namely incorrect cis-amide bonds, wrong stereochemistry or clashes. We show that these inaccuracies affect biophysical property predictions such as surface hydrophobicity. Thus, we stress the importance of carefully reviewing protein structure models before investing further computing power and setting up experiments. To facilitate the assessment of model quality, we provide a tool "TopModel" to validate structure models.

The influence of antibody humanization on shark variable domain (VNAR) binding site ensembles.

Sharks and other cartilaginous fish produce new antigen receptor (IgNAR) antibodies, as key part of their humoral immune response and are the phylogenetically oldest living organisms that possess an immunoglobulin (Ig)-based adaptive immune system. IgNAR antibodies are naturally occurring heavy-chain-only antibodies, that recognize antigens with their single domain variable regions (VNARs). In this study, we structurally and biophysically elucidate the effect of antibody humanization of a previously published spiny dogfish VNAR (parent E06), which binds with high affinity to the human serum albumin (HSA). We analyze different humanization variants together with the parental E06 VNAR and the human Vκ1 light chain germline DPK9 antibody to characterize the influence of point mutations in the framework and the antigen binding site on the specificity of VNARs as reported by Kovalenko et al. We find substantially higher flexibility in the humanized variants, reflected in a broader conformational space and a higher conformational entropy, as well as population shifts of the dominant binding site ensembles in solution. A further variant, in which some mutations are reverted, largely restores the conformational stability and the dominant binding minimum of the parent E06. We also identify differences in surface hydrophobicity between the human Vκ1 light chain germline DPK9 antibody, the parent VNAR E06 and the humanized variants. Additional simulations of VNAR-HSA complexes of the parent E06 VNAR and a humanized variant reveal that the parent VNAR features a substantially stronger network of stabilizing interactions. Thus, we conclude that a structural and dynamic understanding of the VNAR binding site upon humanization is a key aspect in antibody humanization.