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Abstract The Golgi apparatus is essential for protein sorting, yet its quality control mechanisms are poorly understood. Here we show that the Dsc ubiquitin ligase complex uses its rhomboid pseudo-protease subunit, Dsc2, to assess the hydrophobic length of α-helical transmembrane domains (TMDs) at the Golgi. Thereby the Dsc complex likely interacts with orphaned ER and Golgi proteins that have shorter TMDs and ubiquitinates them for targeted degradation. Some Dsc substrates will be extracted by Cdc48 for endosome and Golgi associated proteasomal degradation (EGAD), while others will undergo ESCRT dependent vacuolar degradation. Some substrates are degraded by both, EGAD- or ESCRT pathways. The accumulation of Dsc substrates entails a specific increase in glycerophospholipids with shorter and asymmetric fatty acyl chains. Hence, the Dsc complex mediates the selective degradation of orphaned proteins at the sorting center of cells, which prevents their spreading across other organelles and thereby preserves cellular membrane protein and lipid composition.

Abstract Skeletal muscle contractions are initiated by action potentials, which are sensed by the voltage-gated calcium channel (CaV1.1) and are conformationally coupled to calcium release from intracellular stores. Notably, CaV1.1 contains four separate voltage-sensing domains (VSDs), which activate channel gating and excitation-contraction (EC-) coupling at different voltages and with distinct kinetics. Here we show that a single VSD of CaV1.1 controls skeletal muscle EC-coupling. Whereas mutations in VSDs I, II and IV affect the current properties but not EC-coupling, only mutations in VSD III alter the voltage-dependence of depolarization-induced calcium release. Molecular dynamics simulations reveal comprehensive, non-canonical state transitions of VSD III in response to membrane depolarization. Identifying the voltage sensor that activates EC-coupling and detecting its unique conformational changes opens the door to unraveling the downstream events linking VSD III motion to the opening of the calcium release channel, and thus resolving the signal transduction mechanism of skeletal muscle EC-coupling.

Allergens are substances that cause abnormal immune responses and can originate from various sources. IgE-mediated allergies are one of the most common and severe types of allergies, affecting more than 20% of the population in Western countries. Allergens can be subdivided into a limited number of families based on their structure, but this does not necessarily indicate the origin or the route of administration of the allergen, nor is the molecular basis of allergenicity clearly understood. This review examines how understanding the allergenicity of proteins involves their structural characterization and elucidates the study of conformational diversity by nuclear magnetic resonance spectroscopy. This article also discusses allergen cross-reactivity and the mechanisms by which IgE antibodies recognize and bind to allergens based on their conformational and linear epitopes. In addition, we outline how the pH, the proteolytic susceptibility and the endosomal degradation affect the outcome of allergic reactions, and how this is correlated with conformational changes and secondary structure rearrangement events. We want to emphasize the importance of considering structural diversity and dynamics, proteolytic susceptibility and pH-dependent factors to fully comprehend allergenicity.

Abstract A primary objective in malaria vaccine design is the generation of high-quality antibody responses against the circumsporozoite protein of the malaria parasite, Plasmodium falciparum (PfCSP). To enable rational antigen design, we solved a cryo-EM structure of the highly potent anti-PfCSP antibody L9 in complex with recombinant PfCSP. We found that L9 Fab binds multivalently to the minor (NPNV) repeat domain, which is stabilized by a unique set of affinity-matured homotypic, antibody-antibody contacts. Molecular dynamics simulations revealed a critical role of the L9 light chain in integrity of the homotypic interface, which likely impacts PfCSP affinity and protective efficacy. These findings reveal the molecular mechanism of the unique NPNV selectivity of L9 and emphasize the importance of anti-homotypic affinity maturation in protective immunity against P. falciparum.

ABSTRACTBeyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

ABSTRACTAdvances 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.

Poly (N-isopropylacrylamide) (PNIPAM) is a famous representative of thermosensitive polymers. Thermosensitive polymers undergo a phase transition with lower critical solution temperature. Commonly, their phase behavior is linked to a conformational collapse above a certain temperature. This thermosensitive conformational transition is called Coil-Globule transition. In contrast, most other polymers usually show inverse temperature behavior, i.e., an upper critical solution temperature, corresponding to a Globule-Coil transition. Besides their numerous possible applications, thermosensitive polymers are of interest for fundamental research, because of similarities to macromolecular conformational transitions, e.g., protein folding. The counter-intuitive behavior of thermosensitive polymers is commonly associated with solvation effects. Thus, an accurate description of the solvent is crucial for the investigation of thermosensitive polymers in molecular simulations. Here, we investigate the influence of the in silico water model on the thermosensitive Coil-Globule transition in molecular dynamics simulations. To this end, we performed extensive atomistic simulations of the syndiotactic PNIPAM 20-mer at multiple temperatures with eight different water models–four of which are 3-point water models (TIP3P-type) and four are 4-point water models (TIP4P-type). We found that the thermosensitive Coil-Globule transition is strongly influenced by the water model in the simulations. Depending on the water model, the conformational ensemble of the polymer is shifted significantly, which leads to dramatically different results: The estimated transition temperature may span between 255 and 350 K. Consequently, depending on the description of the solvent, the physicochemical and mechanical properties of these polymers, e.g., the polymer-solvent affinity and persistence length, vary. These divergent results originate from the strength of interactions between polymer and solvent, but also on the bulk state of the solvent. Both these quantities vary between water models. We found that the Lennard-Jones interaction parameter ϵ of the water model correlates with the transition temperature of the polymer. Indeed, the quadrupole moment of the water model shows an even higher correlation with this quantity. Our results suggest a connection between the phase diagram of the solvent and the thermosensitive transition of the polymer.

As the current biotherapeutic market is dominated by antibodies, the design of different antibody formats, like bispecific antibodies, is critical to the advancement of the field. In contrast to monovalent antibodies, which consist of two identical antigen-binding sites, bispecific antibodies can target two different epitopes by containing two different antigen-binding sites. Thus, the rise of new formats as successful therapeutics has reignited the interest in advancing and facilitating the efficient production of bispecific antibodies. Here, we investigate the influence of point mutations in the antigen-binding site, the paratope, on heavy and light chain pairing preferences by using molecular dynamics simulations. In agreement with experiments, we find that specific residues in the antibody variable domain (Fv), i.e., the complementarity-determining region (CDR) L3 and H3 loops, determine heavy and light chain pairing preferences. Excitingly, we observe substantial population shifts in CDR-H3 and CDR-L3 loop conformations in solution accompanied by a decrease in bispecific IgG yield. These conformational changes in the CDR3 loops induced by point mutations also influence all other CDR loop conformations and consequentially result in different CDR loop states in solution. However, besides their effect on the obtained CDR loop ensembles, point mutations also lead to distinct interaction patterns in the VH-VL interface. By comparing the interaction patterns among all investigated variants, we observe specific contacts in the interface that drive heavy and light chain pairing. Thus, these findings have broad implications in the field of antibody engineering and design because they provide a mechanistic understanding of antibody interfaces, by identifying critical factors driving the pairing preferences, and thus can help to advance the design of bispecific antibodies.

Allergies related to kiwi consumption have become a growing health concern, with their prevalence on the rise. Many of these allergic reactions are attributed to cross-reactivity, particularly with the major allergen found in birch pollen. This cross-reactivity is associated with proteins belonging to the pathogenesis-related class 10 (PR-10) protein family. In our study, we determined the three-dimensional structures of the two PR-10 proteins in gold and green kiwi fruits, Act c 8 and Act d 8, using nuclear magnetic resonance (NMR) spectroscopy. The structures of both kiwi proteins closely resemble the major birch pollen allergen, Bet v 1, providing a molecular explanation for the observed immunological cross-reactivity between kiwi and birch pollen. Compared to Act d 11, however, a kiwi allergen that shares the same architecture as PR-10 proteins, structural differences are apparent. Moreover, despite both Act c 8 and Act d 8 containing multiple cysteine residues, no disulfide bridges are present within their structures. Instead, all the cysteines are accessible on the protein’s surface and exposed to the surrounding solvent, where they are available for reactions with components of the natural food matrix. This structural characteristic sets Act c 8 and Act d 8 apart from other kiwi proteins with a high cysteine content. Furthermore, we demonstrate that pyrogallol, the most abundant phenolic compound found in kiwi, binds into the internal cavities of these two proteins, albeit with low affinity. Our research offers a foundation for further studies aimed at understanding allergic reactions associated with this fruit and exploring how interactions with the natural food matrix might be employed to enhance food safety.

Antibodies and other new antibody-like formats have emerged as one of the most rapidly growing classes of biotherapeutic proteins. Understanding the structural features that drive antibody function and, consequently, their molecular recognition is critical for engineering antibodies. Here, we present the structural architecture of conventional IgG antibodies alongside other formats. We emphasize the importance of considering antibodies as conformational ensembles in solution instead of focusing on single-static structures because their functions and properties are strongly governed by their dynamic nature. Thus, in this review, we provide an overview of the unique structural and dynamic characteristics of antibodies with respect to their antigen recognition, biophysical properties, and effector functions. We highlight the numerous technical advances in antibody structure prediction and design, enabled by the vast number of experimentally determined high-quality structures recorded with cryo-EM, NMR, and X-ray crystallography. Lastly, we assess antibody and vaccine design strategies in the context of structure and dynamics.

The family of profilin allergens is a common class of proteins found in plants, viruses and various eukaryotes including mammals. Profilins are characterized by an evolutionary conserved structural fold, which is responsible for their cross-reactive nature of Immunoglobulin E (IgE) antibodies. Despite their high overall structural similarity, they exhibit substantial differences in their biophysical properties, such as thermal and pH stability. To understand the origin of these functional differences of Amb a 8, Art v 4 and Bet v 2, we performed constant pH molecular dynamics simulation in combination with Gaussian accelerated MD simulations. Depending on the respective protonation at different pH levels, we find distinct differences in conformational flexibility, which are consistent with experimentally determined melting temperatures. These variations in flexibility are accompanied by ensemble shifts in the conformational landscape and quantified and localized by residue-wise B-factors and dihedral entropies. These findings strengthen the link between flexibility of profilin allergens and their thermal stability. Thus, our results clearly show the importance of considering protonation dependent conformational ensembles in solution to elucidate biophysical differences between these structurally similar allergens.

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.

While antibody-based therapeutics have grown to be one of the major classes of novel medicines, some antibody development candidates face significant challenges regarding expression levels, solubility, as well as stability and aggregation, under physiological and storage conditions. A major determinant of those properties is surface hydrophobicity, which promotes unspecific interactions and has repeatedly proven problematic in the development of novel antibody-based drugs. Multiple computational methods have been devised for in-silico prediction of antibody hydrophobicity, often using hydrophobicity scales to assign values to each amino acid. Those approaches are usually validated by their ability to rank potential therapeutic antibodies in terms of their experimental hydrophobicity. However, there is significant diversity both in the hydrophobicity scales and in the experimental methods, and consequently in the performance of in-silico methods to predict experimental results. In this work, we investigate hydrophobicity of monoclonal antibodies using hydrophobicity scales. We implement several scoring schemes based on the solvent-accessibility and the assigned hydrophobicity values, and compare the different scores and scales based on their ability to predict retention times from hydrophobic interaction chromatography. We provide an overview of the strengths and weaknesses of several commonly employed hydrophobicity scales, thereby improving the understanding of hydrophobicity in antibody development. Furthermore, we test several datasets, both publicly available and proprietary, and find that the diversity of the dataset affects the performance of hydrophobicity scores. We expect that this work will provide valuable guidelines for the optimization of biophysical properties in future drug discovery campaigns.

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.

Abstract A major proportion of allergic reactions to hazelnuts (Corylus avellana) are caused by immunologic cross-reactivity of IgE antibodies to pathogenesis-related class 10 (PR-10) proteins. Intriguingly, the four known isoforms of the hazelnut PR-10 allergen Cor a 1, denoted as Cor a 1.0401–Cor a 1.0404, share sequence identities exceeding 97% but possess different immunologic properties. In this work we describe the NMR solution structures of these proteins and provide an in-depth study of their biophysical properties. Despite sharing highly similar three-dimensional structures, the four isoforms exhibit remarkable differences regarding structural flexibility, hydrogen bonding and thermal stability. Our experimental data reveal an inverse relation between structural flexibility and IgE-binding in ELISA experiments, with the most flexible isoform having the lowest IgE-binding potential, while the isoform with the most rigid backbone scaffold displays the highest immunologic reactivity. These results point towards a significant entropic contribution to the process of antibody binding.

The proto-oncogene myc has been intensively studied primarily in vertebrate cell culture systems. Myc transcription factors control fundamental cellular processes such as cell proliferation, cell cycle control and stem cell maintenance. Myc interacts with the Max protein and Myc/Max heterodimers regulate thousands of target genes. The genome of the freshwater polyp Hydra encodes four myc genes (myc1-4). Previous structural and biochemical characterization showed that the Hydra Myc1 and Myc2 proteins share high similarities with vertebrate c-Myc, and their expression patterns suggested a function in adult stem cell maintenance. In contrast, an additional Hydra Myc protein termed Myc3 is highly divergent, lacking the common N-terminal domain and all conserved Myc-boxes. Single cell transcriptome analysis revealed that the myc3 gene is expressed in a distinct population of interstitial precursor cells committed to nerve- and gland-cell differentiation, where the Myc3 protein may counteract the stemness actions of Myc1 and Myc2 and thereby allow the implementation of a differentiation program. In vitro DNA binding studies showed that Myc3 dimerizes with Hydra Max, and this dimer efficiently binds to DNA containing the canonical Myc consensus motif (E-box). In vivo cell transformation assays in avian fibroblast cultures further revealed an unexpected high potential for oncogenic transformation in the conserved Myc3 C-terminus, as compared to Hydra Myc2 or Myc1. Structure modeling of the Myc3 protein predicted conserved amino acid residues in its bHLH-LZ domain engaged in Myc3/Max dimerization. Mutating these amino acid residues in the human c-Myc (MYC) sequence resulted in a significant decrease in its cell transformation potential. We discuss our findings in the context of oncogenic transformation and cell differentiation, both relevant for human cancer, where Myc represents a major driver.

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.

As the current biotherapeutic market is dominated by antibodies, the design of different antibody formats, like bispecific antibodies and other new formats, represent a key component in advancing antibody therapy. When designing new formats, a targeted modulation of pairing preferences is key. Several existing approaches are successful, but expanding the repertoire of design possibilities would be desirable. Cognate immunoglobulin G antibodies depend on homodimerization of the fragment crystallizable regions of two identical heavy chains. By modifying the dimeric interface of the third constant domain (CH3-CH3), with different mutations on each domain, the engineered Fc fragments form rather heterodimers than homodimers. The first constant domain (CH1-CL) shares a very similar fold and interdomain orientation with the CH3-CH3 dimer. Thus, numerous well-established design efforts for CH3-CH3 interfaces, have also been applied to CH1-CL dimers to reduce the number of mispairings in the Fabs. Given the high structural similarity of the CH3-CH3 and CH1-CL domains we want to identify additional opportunities in comparing the differences and overlapping interaction profiles. Our vision is to facilitate a toolkit that allows for the interchangeable usage of different design tools from crosslinking the knowledge between these two interface types. As a starting point, here, we use classical molecular dynamics simulations to identify differences of the CH3-CH3 and CH1-CL interfaces and already find unexpected features of these interfaces shedding new light on possible design variations. Apart from identifying clear differences between the similar CH3-CH3 and CH1-CL dimers, we structurally characterize the effects of point-mutations in the CH3-CH3 interface on the respective dynamics and interface interaction patterns. Thus, this study has broad implications in the field of antibody engineering as it provides a structural and mechanistical understanding of antibody interfaces and thereby presents a crucial aspect for the design of bispecific antibodies.

Antibodies have emerged as one of the fastest growing classes of biotherapeutic proteins. To improve the rational design of antibodies, we investigate the conformational diversity of 16 different germline combinations, which are composed of 4 different kappa light chains paired with 4 different heavy chains. In this study, we systematically show that different heavy and light chain pairings strongly influence the paratope, interdomain interaction patterns and the relative VH-VL interface orientations. We observe changes in conformational diversity and substantial population shifts of the complementarity determining region (CDR) loops, resulting in distinct dominant solution structures and differently favored canonical structures. Additionally, we identify conformational changes in the structural diversity of the CDR-H3 loop upon different heavy and light chain pairings, as well as upon changes in sequence and structure of the neighboring CDR loops, despite having an identical CDR-H3 loop amino acid sequence. These results can also be transferred to all CDR loops and to the relative VH-VL orientation, as certain paratope states favor distinct interface angle distributions. Furthermore, we directly compare the timescales of sidechain rearrangements with the well-described transition kinetics of conformational changes in the backbone of the CDR loops. We show that sidechain flexibilities are strongly affected by distinct heavy and light chain pairings and decipher germline-specific structural features co-determining stability. These findings reveal that all CDR loops are strongly correlated and that distinct heavy and light chain pairings can result in different paratope states in solution, defined by a characteristic combination of CDR loop conformations and VH-VL interface orientations. Thus, these results have broad implications in the field of antibody engineering, as they clearly show the importance of considering paired heavy and light chains to understand the antibody binding site, which is one of the key aspects in the design of therapeutics.

Abstract Background There is increasing evidence that de novo CACNA1D missense mutations inducing increased Cav1.3 L-type Ca2+-channel-function confer a high risk for neurodevelopmental disorders (autism spectrum disorder with and without neurological and endocrine symptoms). Electrophysiological studies demonstrating the presence or absence of typical gain-of-function gating changes could therefore serve as a tool to distinguish likely disease-causing from non-pathogenic de novo CACNA1D variants in affected individuals. We tested this hypothesis for mutation S652L, which has previously been reported in twins with a severe neurodevelopmental disorder in the Deciphering Developmental Disorder Study, but has not been classified as a novel disease mutation. Methods For functional characterization, wild-type and mutant Cav1.3 channel complexes were expressed in tsA-201 cells and tested for typical gain-of-function gating changes using the whole-cell patch-clamp technique. Results Mutation S652L significantly shifted the voltage-dependence of activation and steady-state inactivation to more negative potentials (~ 13–17 mV) and increased window currents at subthreshold voltages. Moreover, it slowed tail currents and increased Ca2+-levels during action potential-like stimulations, characteristic for gain-of-function changes. To provide evidence that only gain-of-function variants confer high disease risk, we also studied missense variant S652W reported in apparently healthy individuals. S652W shifted activation and inactivation to more positive voltages, compatible with a loss-of-function phenotype. Mutation S652L increased the sensitivity of Cav1.3 for inhibition by the dihydropyridine L-type Ca2+-channel blocker isradipine by 3–4-fold. Conclusions and limitations Our data provide evidence that gain-of-function CACNA1D mutations, such as S652L, but not loss-of-function mutations, such as S652W, cause high risk for neurodevelopmental disorders including autism. This adds CACNA1D to the list of novel disease genes identified in the Deciphering Developmental Disorder Study. Although our study does not provide insight into the cellular mechanisms of pathological Cav1.3 signaling in neurons, we provide a unifying mechanism of gain-of-function CACNA1D mutations as a predictor for disease risk, which may allow the establishment of a more reliable diagnosis of affected individuals. Moreover, the increased sensitivity of S652L to isradipine encourages a therapeutic trial in the two affected individuals. This can address the important question to which extent symptoms are responsive to therapy with Ca2+-channel blockers.

The protein Mal d 1 is responsible for most allergic reactions to apples (Malus domestica) in the northern hemisphere. Mal d 1 contains a cysteine residue on its surface, with its reactive side chain thiol exposed to the surrounding food matrix. We show that, in vitro, this cysteine residue is prone to spontaneous chemical modification by ascorbic acid (vitamin C). Using NMR spectroscopy and mass spectrometry, we characterize the chemical structure of the cysteine adduct and provide a three-dimensional structural model of the modified apple allergen. The S-ascorbylated cysteine partially masks a major IgE antibody binding site on the surface of Mal d 1, which attenuates IgE binding in sera of apple-allergic patients. Our results illustrate, from a structural perspective, the role that chemical modifications of allergens with components of the natural food matrix can play.

Sharks and other cartilaginous fish are the phylogenetically oldest living organisms that have antibodies as part of their adaptive immune system. As part of their humoral adaptive immune response, they produce an immunoglobulin, the so-called immunoglobulin new antigen receptor (IgNAR), a heavy-chain only antibody. The variable domain of an IgNAR, also known as VNAR, binds the antigen as an independent soluble domain. In this study, we structurally and dynamically characterized the affinity maturation mechanism of the germline and somatically matured (PBLA8) VNAR to better understand their function and their applicability as therapeutics. We observed a substantial rigidification upon affinity maturation, which is accompanied by a higher number of contacts, thereby contributing to the decrease in flexibility. Considering the static x-ray structures, the observed rigidification is not obvious, as especially the mutated residues undergo conformational changes during the simulation, resulting in an even stronger network of stabilizing interactions. Additionally, the simulations of the VNAR in complex with the hen egg-white lysozyme show that the VNAR antibodies evidently follow the concept of conformational selection, as the binding-competent state already preexisted even without the presence of the antigen. To have a more detailed description of antibody–antigen recognition, we also present here the binding/unbinding mechanism between the hen egg-white lysozyme and both the germline and matured VNARs. Upon maturation, we observed a substantial increase in the resulting dissociation-free energy barrier. Furthermore, we were able to kinetically and thermodynamically describe the binding process and did not only identify a two-step binding mechanism, but we also found a strong population shift upon affinity maturation toward the native binding pose.

Characterizing and understanding the antibody binding interface have become a pre-requisite for rational antibody design and engineering. The antigen-binding site is formed by six hypervariable loops, known as the complementarity determining regions (CDRs) and by the relative interdomain orientation (VH–VL). Antibody CDR loops with a certain sequence have been thought to be limited to a single static canonical conformation determining their binding properties. However, it has been shown that antibodies exist as ensembles of multiple paratope states, which are defined by a characteristic combination of CDR loop conformations and interdomain orientations. In this study, we thermodynamically and kinetically characterize the prominent role of residue 71H (Chothia nomenclature), which does not only codetermine the canonical conformation of the CDR-H2 loop but also results in changes in conformational diversity and population shifts of the CDR-H1 and CDR-H3 loop. As all CDR loop movements are correlated, conformational rearrangements of the heavy chain CDR loops also induce conformational changes in the CDR-L1, CDR-L2, and CDR-L3 loop. These overall conformational changes of the CDR loops also influence the interface angle distributions, consequentially leading to different paratope states in solution. Thus, the type of residue of 71H, either an alanine or an arginine, not only influences the CDR-H2 loop ensembles, but co-determines the paratope states in solution. Characterization of the functional consequences of mutations of residue 71H on the paratope states and interface orientations has broad implications in the field of antibody engineering.

Stacking interactions play a crucial role in drug design, as we can find aromatic cores or scaffolds in almost any available small molecule drug. To predict optimal binding geometries and enhance stacking interactions, usually high-level quantum mechanical calculations are performed. These calculations have two major drawbacks: they are very time consuming, and solvation can only be considered using implicit solvation. Therefore, most calculations are performed in vacuum. However, recent studies have revealed a direct correlation between the desolvation penalty, vacuum stacking interactions and binding affinity, making predictions even more difficult. To overcome the drawbacks of quantum mechanical calculations, in this study we use neural networks to perform fast geometry optimizations and molecular dynamics simulations of heteroaromatics stacked with toluene in vacuum and in explicit solvation. We show that the resulting energies in vacuum are in good agreement with high-level quantum mechanical calculations. Furthermore, we show that using explicit solvation substantially influences the favored orientations of heteroaromatic rings thereby emphasizing the necessity to include solvation properties starting from the earliest phases of drug design.

Susceptibility to endosomal degradation is a decisive contribution to a protein's immunogenicity. It is assumed that the processing kinetics of structured proteins are inherently linked to their probability of local unfolding. In this study, we quantify the impact of endosomal acidification on the conformational stability of the major timothy grass pollen allergen Phl p 6. We use state of the art sampling approaches in combination with constant pH MD techniques to profile pH-dependent local unfolding events in atomistic detail. Integrating our findings into the current view on type 1 allergic sensitization, we characterize local protein dynamics in the context of proteolytic degradation at neutral and acidic pH for the wild type protein and point mutants with varying proteolytic stability. We analyze extensive simulation data using Markov state models and retrieve highly reliable thermodynamic and kinetic information at varying pH levels. Thereby we capture the impact of endolysosomal acidification on the structure and dynamics of the Phl p 6 mutants. We find that upon protonation at lower pH values, the conformational flexibilities in key areas of the wild type protein, i.e., T-cell epitopes and early proteolytic cleavage sites, increase significantly. A decrease of the pH even leads to local unfolding in otherwise stable secondary structure elements, which is a prerequisite for proteolytic cleavage. This effect is even more pronounced in the destabilized mutant, while no unfolding was observed for the stabilized mutant. In summary, we report detailed structural models which rationalize the experimentally observed cleavage pattern during endosomal acidification.

The rise of antibodies as a promising and rapidly growing class of biotherapeutic proteins has motivated numerous studies to characterize and understand antibody structures. In the past decades, the number of antibody crystal structures increased substantially, which revolutionized the atomistic understanding of antibody functions. Even though numerous static structures are known, various biophysical properties of antibodies (i.e., specificity, hydrophobicity and stability) are governed by their dynamic character. Additionally, the importance of high-quality structures in structure–function relationship studies has substantially increased. These structure–function relationship studies have also created a demand for precise homology models of antibody structures, which allow rational antibody design and engineering when no crystal structure is available. Here, we discuss various aspects and challenges in antibody design and extend the paradigm of describing antibodies with only a single static structure to characterizing them as dynamic ensembles in solution.

Fab consist of a heavy and light chain and can be subdivided into a variable (VH and VL) and a constant region (CH1 and CL). The variable region contains the complementarity-determining region (CDR), which is formed by six hypervariable loops, shaping the antigen binding site, the paratope. Apart from the CDR loops, both the elbow angle and the relative interdomain orientations of the VH–VL and the CH1–CL domains influence the shape of the paratope. Thus, characterization of the interface and elbow angle dynamics is essential to antigen specificity. We studied nine antigen-binding fragments (Fab) to investigate the influence of affinity maturation, antibody humanization, and different light-chain types on the interface and elbow angle dynamics. While the CDR loops reveal conformational transitions in the micro-to-millisecond timescale, both the interface and elbow angle dynamics occur on the low nanosecond timescale. Upon affinity maturation, we observe a substantial rigidification of the VH and VL interdomain and elbow-angle flexibility, reflected in a narrower and more distinct distribution. Antibody humanization describes the process of grafting non-human CDR loops onto a representative human framework. As the antibody framework changes upon humanization, we investigated if both the interface and the elbow angle distributions are changed or shifted. The results clearly showed a substantial shift in the relative VH–VL distributions upon antibody humanization, indicating that different frameworks favor distinct interface orientations. Additionally, the interface and elbow angle dynamics of five antibody fragments with different light-chain types are included, because of their strong differences in elbow angles. For these five examples, we clearly see a high variability and flexibility in both interface and elbow angle dynamics, highlighting the fact that Fab interface orientations and elbow angles interconvert between each other in the low nanosecond timescale. Understanding how the relative interdomain orientations and the elbow angle influence antigen specificity, affinity, and stability has broad implications in the field of antibody modeling and engineering.

During the affinity maturation process the immune system produces antibodies with higher specificity and activity through various rounds of somatic hypermutations in response to an antigen. Elucidating the affinity maturation process is fundamental in understanding immunity and in the development of biotherapeutics. Therefore, we analyzed 10 pairs of antibody fragments differing in their specificity and in distinct stages of affinity maturation using metadynamics in combination with molecular dynamics (MD) simulations. We investigated differences in flexibility of the CDR-H3 loop and global changes in plasticity upon affinity maturation. Among all antibody pairs we observed a substantial rigidification in flexibility and plasticity reflected in a substantial decrease of conformational diversity. To visualize and characterize these findings we used Markov-states models to reconstruct the kinetics of CDR-H3 loop dynamics and for the first time provide a method to define and localize surface plasticity upon affinity maturation.

Introduction: Understanding, which factors determine the immunogenicity and immune polarizing properties of proteins, is an important prerequisite for designing better vaccines and immunotherapeutics. While extrinsic immune modulatory factors such as pathogen associated molecular patterns are well-understood, far less is known about the contribution of protein inherent features. Protein fold-stability represents such an intrinsic feature contributing to immunogenicity and immune polarization by influencing the amount of peptide-MHC II complexes (pMHCII). Here, we investigated how modulation of the fold-stability of the grass pollen allergen Phl p 6 affects its ability to stimulate immune responses and T cell polarization.Methods: MAESTRO software was used for in silico prediction of stabilizing or destabilizing point mutations. Mutated proteins were expressed in E. coli, and their thermal stability and resistance to endolysosomal proteases was determined. Resulting peptides were analyzed by mass spectrometry. The structure of the most stable mutant protein was assessed by X-ray crystallography. We evaluated the capacity of the mutants to stimulate T cell proliferation in vitro, as well as antibody responses and T cell polarization in vivo in an adjuvant-free BALB/c mouse model.Results: In comparison to wild-type protein, stabilized or destabilized mutants displayed changes in thermal stability ranging from −5 to +14°. While highly stabilized mutants were degraded very slowly, destabilization led to faster proteolytic processing in vitro. This was confirmed in BMDCs, which processed and presented the immunodominant epitope from a destabilized mutant more efficiently compared to a highly stable mutant. In vivo, stabilization resulted in a shift in immune polarization from TH2 to TH1/TH17 as indicated by higher levels of IgG2a and increased secretion of TNF-α, IFN-γ, IL-17, and IL-21.Conclusion: MAESTRO software was very efficient in detecting single point mutations that increase or reduce fold-stability. Thermal stability correlated well with the speed of proteolytic degradation and presentation of peptides on the surface of dendritic cells in vitro. This change in processing kinetics significantly influenced the polarization of T cell responses in vivo. Modulating the fold-stability of proteins thus has the potential to optimize and polarize immune responses, which opens the door to more efficient design of molecular vaccines.

T-cell receptors are an important part in the adaptive immune system as they are responsible for detecting foreign proteins presented by the major histocompatibility complex (MHC). The affinity is predominantly determined by structure and sequence of the complementarity determining regions (CDRs), of which the CDR3 loops are responsible for peptide recognition. We present a kinetic classification of T-cell receptor CDR3 loops with different loop lengths into canonical and non-canonical solution structures. Using molecular dynamics simulations, we do not only sample available X-ray structures, but we also observe a substantially broader CDR3 loop ensemble with various distinct kinetic minima in solution. Our results strongly imply, that for given CDR3 loop sequences several canonical structures have to be considered to characterize the conformational diversity of these loops. Our suggested dominant solution structures could extend the repertoire of available canonical clusters by including kinetic minimum structures present in solution. Thus, the CDR3 loops need to be characterized as conformational ensembles in solution. Furthermore, the conformational changes of the CDR3 loops follow the paradigm of conformational selection, because the experimentally determined binding competent state is present within this ensemble of pre-existing conformations without the presence of the antigen. We also identify strong correlations between the CDR3 loops and include combined state descriptions. Additionally, we observe a strong dependency of the CDR3 loop conformations on the relative Vα-Vβ interdomain orientations, revealing that certain CDR3 loop states favor specific interface orientations.

Proteolytic susceptibility during endolysosomal degradation is decisive for allergic sensitization. In the major birch pollen allergen Bet v 1 most protease cleavage sites are located within its secondary structure elements, which are inherently inaccessible to proteases. The allergen thus must unfold locally, exposing the cleavage sites to become susceptible to proteolysis. Hence, allergen cleavage rates are presumed to be linked to their fold stability, i.e., unfolding probability. Yet, these locally unfolded structures have neither been captured in experiment nor simulation due to limitations in resolution and sampling time, respectively. Here, we perform classic and enhanced molecular dynamics (MD) simulations to quantify fold dynamics on extended timescales of Bet v 1a and two variants with higher and lower cleavage rates. Already at the nanosecond-timescale we observe a significantly higher flexibility for the destabilized variant compared to Bet v 1a and the proteolytically stabilized mutant. Estimating the thermodynamics and kinetics of local unfolding around an initial cleavage site, we find that the Bet v 1 variant with the highest cleavage rate also shows the highest probability for local unfolding. For the stabilized mutant on the other hand we only find minimal unfolding probability. These results strengthen the link between the conformational dynamics of allergen proteins and their stability during endolysosomal degradation. The presented approach further allows atomistic insights in the conformational ensemble of allergen proteins and provides probability estimates below experimental detection limits.

FAH domain containing protein 1 (FAHD1) acts as oxaloacetate decarboxylase in mitochondria, contributing to the regulation of the tricarboxylic acid cycle. Guided by a high-resolution X-ray structure of FAHD1 liganded by oxalate, the enzymatic mechanism of substrate processing is analyzed in detail. Taking the chemical features of the FAHD1 substrate oxaloacetate into account, the potential inhibitor structures are deduced. The synthesis of drug-like scaffolds afforded first-generation FAHD1-inhibitors with activities in the low micromolar IC50 range. The investigations disclosed structures competing with the substrate for binding to the metal cofactor, as well as scaffolds, which may have a novel binding mode to FAHD1.

In the past decade, the relevance of antibodies as therapeutics has increased substantially. Therefore, structural and functional characterization, in particular of the complementarity-determining regions (CDRs), is crucial to the design and engineering of antibodies with unique binding properties. Various studies have focused on classifying the CDR loops into a small set of main-chain conformations to facilitate antibody design by assuming that certain sequences can only adopt a limited number of conformations. Here, we present a kinetic classification of CDR loop structures as ensembles in solution. Using molecular dynamics simulations in combination with strong experimental structural information, we observe conformational transitions between canonical clusters and additional dominant solution structures in the micro-to-millisecond timescale for all CDR loops, independent of length and sequence composition. Besides identifying all relevant conformations in solution, our results revealed that various canonical cluster medians actually belong to the same kinetic minimum. Additionally, we reconstruct the kinetics and probabilities of the conformational transitions between canonical clusters, and thereby extend the model of static canonical structures to reveal a dynamic conformational ensemble in solution as a new paradigm in the field of antibody structure design.Abbreviations: CDR: Complementary-determining region; Fv: Antibody variable fragment; PCCA: Perron cluster analysis; tICA: Time-lagged independent component analysis; VH: Heavy chain variable region; VL: Light chain variable region

Sequence and structural diversity of antibodies are concentrated on six hypervariable loops, also known as the complementarity determining regions (CDRs). Five of six antibody CDR loops presumably adopt a so-called canonical structure out of a limited number of conformations. However, here we show for four antibody CDR-L3 loops differing in length and sequence, that each loop undergoes conformational transitions between different canonical structures. By extensive sampling in combination with Markov-state models we reconstruct the kinetics and probabilities of the transitions between canonical structures. Additionally, for these four CDR-L3 loops, we identify all relevant conformations in solution. Thereby we extend the model of static canonical structures to a dynamic conformational ensemble as a new paradigm in the field of antibody structure design.

We present an approach to assess antibody CDR-H3 loops according to their dynamic properties using molecular dynamics simulations. We selected six antibodies in three pairs differing substantially in their individual promiscuity respectively specificity. For two pairs of antibodies crystal structures are available in different states of maturation and used as starting structures for the analyses. For a third pair we chose two antibody CDR sequences obtained from a synthetic library and predicted the respective structures. For all three pairs of antibodies we performed metadynamics simulations to overcome the limitations in conformational sampling imposed by high energy barriers. Additionally, we used classic molecular dynamics simulations to describe nano- to microsecond flexibility and to estimate up to millisecond kinetics of captured conformational transitions. The methodology represents the antibodies as conformational ensembles and allows comprehensive analysis of structural diversity, thermodynamics of conformations and kinetics of structural transitions. Referring to the concept of conformational selection we investigated the link between promiscuity and flexibility of the antibodies' binding interfaces. The obtained detailed characterization of the binding interface clearly indicates a link between structural flexibility and binding promiscuity for this set of antibodies.

Dark chemical matter compounds are small molecules that have been recently identified as highly potent and selective hits. For this reason, they constitute a promising class of possible candidates in the process of drug discovery and raise the interest of the scientific community. To this purpose, Wassermann et al. (2015) have described the application of 2D descriptors to characterize dark chemical matter. However, their definition was based on the number of reported positive assays rather than the number of known targets. As there might be multiple assays for one single target, the number of assays does not fully describe target selectivity. Here, we propose an alternative classification of active molecules that is based on the number of known targets. We cluster molecules in four classes: black, gray, and white compounds are active on one, two to four, and more than four targets respectively, whilst inactive compounds are found to be inactive in the considered assays. In this study, black and inactive compounds are found to have not only higher solubility, but also a higher number of chiral centers, sp3 carbon atoms and aliphatic rings. On the contrary, white compounds contain a higher number of double bonds and fused aromatic rings. Therefore, the design of a screening compound library should consider these molecular properties in order to achieve target selectivity or polypharmacology. Furthermore, analysis of four main target classes (GPCRs, kinases, proteases, and ion channels) shows that GPCR ligands are more selective than the other classes, as the number of black compounds is higher in this target superfamily. On the other side, ligands that hit kinases, proteases, and ion channels bind to GPCRs more likely than to other target classes. Consequently, depending on the target protein family, appropriate screening libraries can be designed in order to minimize the likelihood of unwanted side effects early in the drug discovery process. Additionally, synergistic effects may be obtained by library design toward polypharmacology.

A pooling design can be used as a powerful strategy to compensate for limited amounts of samples or high biological variation. In this paper, we perform a comparative study to model and quantify the effects of virtual pooling on the performance of the widely applied classifiers, support vector machines (SVMs), random forest (RF), k-nearest neighbors (k-NN), penalized logistic regression (PLR), and prediction analysis for microarrays (PAMs). We evaluate a variety of experimental designs using mock omics datasets with varying levels of pool sizes and considering effects from feature selection. Our results show that feature selection significantly improves classifier performance for non-pooled and pooled data. All investigated classifiers yield lower misclassification rates with smaller pool sizes. RF mainly outperforms other investigated algorithms, while accuracy levels are comparable among all the remaining ones. Guidelines are derived to identify an optimal pooling scheme for obtaining adequate predictive power and, hence, to motivate a study design that meets best experimental objectives and budgetary conditions, including time constraints.