Smartwatch-derived heart rate variability: a head-to-head comparison with the gold standard in cardiovascular disease.

Aims: We aimed to investigate the concordance between heart rate variability (HRV) derived from the photoplethysmographic (PPG) signal of a commercially available smartwatch compared with the gold-standard high-resolution electrocardiogram (ECG)-derived HRV in patients with cardiovascular disease. Methods and results: We prospectively enrolled 104 survivors of acute ST-elevation myocardial infarction, 129 patients after an ischaemic stroke, and 30 controls. All subjects underwent simultaneous recording of a smartwatch (Garmin vivoactive 4; Garmin Ltd, Olathe, KS, USA)-derived PPG signal and a high-resolution (1000 Hz) ECG for 30 min under standardized conditions. HRV measures in time and frequency domain, non-linear measures, as well as deceleration capacity (DC) were calculated according to previously published technologies from both signals. Lin's concordance correlation coefficient (ρc) between smartwatch-derived and ECG-based HRV markers was used as a measure of diagnostic accuracy. A very high concordance within the whole study cohort was observed for the mean heart rate (ρc = 0.9998), standard deviation of the averages of normal-to-normal (NN) intervals in all 5min segments (SDANN; ρc = 0.9617), and very low frequency power (VLF power; ρc = 0.9613). In contrast, detrended fluctuation analysis (DF-α1; ρc = 0.5919) and the square mean root of the sum of squares of adjacent NN-interval differences (rMSSD; ρc = 0.6617) showed only moderate concordance. Conclusion: Smartwatch-derived HRV provides a practical alternative with excellent accuracy compared with ECG-based HRV for global markers and those characterizing lower frequency components. However, caution is warranted with HRV markers that predominantly assess short-term variability.

ArpC5 isoforms regulate Arp2/3 complex-dependent protrusion through differential Ena/VASP positioning.

Regulation of the Arp2/3 complex is required for productive nucleation of branched actin networks. An emerging aspect of regulation is the incorporation of subunit isoforms into the Arp2/3 complex. Specifically, both ArpC5 subunit isoforms, ArpC5 and ArpC5L, have been reported to fine-tune nucleation activity and branch junction stability. We have combined reverse genetics and cellular structural biology to describe how ArpC5 and ArpC5L differentially affect cell migration. Both define the structural stability of ArpC1 in branch junctions and, in turn, by determining protrusion characteristics, affect protein dynamics and actin network ultrastructure. ArpC5 isoforms also affect the positioning of members of the Ena/Vasodilator-stimulated phosphoprotein (VASP) family of actin filament elongators, which mediate ArpC5 isoform-specific effects on the actin assembly level. Our results suggest that ArpC5 and Ena/VASP proteins are part of a signaling pathway enhancing cell migration.

pH-dependent structural diversity of profilin allergens determines thermal stability.

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.

Grid inhomogeneous solvation theory for cross-solvation in rigid solvents.

Grid Inhomogeneous Solvation Theory (GIST) has proven useful to calculate localized thermodynamic properties of water around a solute. Numerous studies have leveraged this information to enhance structure-based binding predictions. We have recently extended GIST toward chloroform as a solvent to allow the prediction of passive membrane permeability. Here, we further generalize the GIST algorithm toward all solvents that can be modeled as rigid molecules. This restriction is inherent to the method and is already present in the inhomogeneous solvation theory. Here, we show that our approach can be applied to various solvent molecules by comparing the results of GIST simulations with thermodynamic integration (TI) calculations and experimental results. Additionally, we analyze and compare a matrix consisting of 100 entries of ten different solvent molecules solvated within each other. We find that the GIST results are highly correlated with TI calculations as well as experiments. For some solvents, we find Pearson correlations of up to 0.99 to the true entropy, while others are affected by the first-order approximation more strongly. The enthalpy-entropy splitting provided by GIST allows us to extend a recently published approach, which estimates higher order entropies by a linear scaling of the first-order entropy, to solvents other than water. Furthermore, we investigate the convergence of GIST in different solvents. We conclude that our extension to GIST reliably calculates localized thermodynamic properties for different solvents and thereby significantly extends the applicability of this widely used method.

Effectiveness of a home telemonitoring program for patients with chronic obstructive pulmonary disease in Germany: Evidence from the first three years.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) affects more than 6 million people in Germany. Monitoring the vital parameters of COPD patients remotely through telemonitoring may help doctors and patients prevent and treat acute exacerbations of COPD, improving patients' quality of life and saving costs for the statutory health insurance system. OBJECTIVE: To evaluate the effects from October 2012 until December 2015 of a structured home telemonitoring program implemented by a statutory health insurer in Germany. METHODS: We conducted a retrospective cohort study using administrative data. After building a balanced control group using Entropy Balancing, we calculated difference-in-difference estimators to account for time-invariant heterogeneity. We estimated differences in mortality rates using Cox regression and conducted subgroup and sensitivity analyses to check the robustness of the base case results. We observed each patient in the program for up to 3 years depending on his or her time of enrolment. RESULTS: Among patients in the telemonitoring cohort, we observed significantly higher inpatient costs due to COPD (€524.2, p<0,05; €434.6, p<0.05) and outpatient costs (102.5, p<0.01; 78.8 p<0.05) during the first two years of the program. Additional cost categories were significantly increased during the first year of telemonitoring. We also observed a significantly higher number of drug prescriptions during all three years of the observation period (2.0500, p < 0.05; 0.7260, p < 0.05; 3.3170, p < 0.01) and a higher number of outpatient contacts during the first two years (0.945, p<0.01, 0.683, p<0.05). Furthermore, we found significantly improved survival rates for participants in the telemonitoring program (HR 0.68, p<0.001). CONCLUSION: On one hand, telemonitoring was associated with higher health care expenditures, especially in the first year of the program. For example, we were able to identify a statistically significant increase in inpatient costs due to COPD, outpatient contacts and drug prescriptions among individuals participating in the telemonitoring program. On the other hand, the telemonitoring program was accompanied by a survival benefit, which might be related to higher adherence rates, more intense treatment, or an improved understanding of COPD among these patients.

Bacterial ribosome collision sensing by a MutS DNA repair ATPase paralogue.

Ribosome stalling during translation is detrimental to cellular fitness, but how this is sensed and elicits recycling of ribosomal subunits and quality control of associated mRNA and incomplete nascent chains is poorly understood1,2. Here we uncover Bacillus subtilis MutS2, a member of the conserved MutS family of ATPases that function in DNA mismatch repair3, as an unexpected ribosome-binding protein with an essential function in translational quality control. Cryo-electron microscopy analysis of affinity-purified native complexes shows that MutS2 functions in sensing collisions between stalled and translating ribosomes and suggests how ribosome collisions can serve as platforms to deploy downstream processes: MutS2 has an RNA endonuclease small MutS-related (SMR) domain, as well as an ATPase/clamp domain that is properly positioned to promote ribosomal subunit dissociation, which is a requirement both for ribosome recycling and for initiation of ribosome-associated protein quality control (RQC). Accordingly, MutS2 promotes nascent chain modification with alanine-tail degrons-an early step in RQC-in an ATPase domain-dependent manner. The relevance of these observations is underscored by evidence of strong co-occurrence of MutS2 and RQC genes across bacterial phyla. Overall, the findings demonstrate a deeply conserved role for ribosome collisions in mounting a complex response to the interruption of translation within open reading frames.

Structure and Zeatin Binding of the Peach Allergen Pru p 1.

Peach (Prunus persica) is among the fruits most frequently reported to cause food allergies. Allergic reactions commonly result from previous sensitization to the birch pollen allergen Bet v 1, followed by immunological cross-reactivity of IgE antibodies to structurally related proteins in peach. In this study, we present the three-dimensional NMR solution structure of the cross-reactive peach allergen Pru p 1 (isoform Pru p 1.0101). This 17.5 kDa protein adopts the canonical Bet v 1 fold, composed of a seven-stranded ß-sheet and three α-helices enclosing an internal cavity. In Pru p 1, the inner surface of the cavity contains an array of hydroxyl-bearing amino acids surrounded by a hydrophobic patch, constituting a docking site for amphiphilic molecules. NMR-guided docking of the cytokinin molecule zeatin to the internal cavity of Pru p 1 provides a structure-based rationale for the effect that zeatin binding has on the protein's RNase activity.

Implementation of the Freely Jointed Chain Model to Assess Kinetics and Thermodynamics of Thermosensitive Coil-Globule Transition by Markov States.

We revived and implemented a method developed by Kuhn in 1934, originally only published in German, that is, the so-called "freely jointed chain" model. This approach turned out to be surprisingly useful for analyzing state-of-the-art computer simulations of the thermosensitive coil-globule transition of N-Isopropylacrylamide 20-mer. Our atomistic computer simulations are orders of magnitude longer than those of previous studies and lead to a reliable description of thermodynamics and kinetics at many different temperatures. The freely jointed chain model provides a coordinate system, which allows us to construct a Markov state model of the conformational transitions. Furthermore, this guarantees a reliable reconstruction of the kinetics in back-and-forth directions. In addition, we obtain a description of the high diversity and variability of both conformational states. Thus, we gain a detailed understanding of the coil-globule transition. Surprisingly, conformational entropy turns out to play only a minor role in the thermodynamic balance of the process. Moreover, we show that the radius of gyration is an unexpectedly unsuitable coordinate to comprehend the transition kinetics because it does not capture the high conformational diversity within the different states. Consequently, the approach presented here allows for an exhaustive description and resolution of the conformational ensembles of arbitrary linear polymer chains.

Conformational Shifts of Stacked Heteroaromatics: Vacuum vs. Water Studied by Machine Learning.

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.

X-Entropy: A Parallelized Kernel Density Estimator with Automated Bandwidth Selection to Calculate Entropy.

X-Entropy is a Python package used to calculate the entropy of a given distribution, in this case, based on the distribution of dihedral angles. The dihedral entropy facilitates an alignment-independent measure of local protein flexibility. The key feature of our approach is a Gaussian kernel density estimation (KDE) using a plug-in bandwidth selection, which is fully implemented in a C++ backend and parallelized with OpenMP. We further provide a Python frontend, with predefined wrapper functions for classical coordinate-based dihedral entropy calculations, using a 1D approximation. This makes the package very straightforward to include in any Python-based analysis workflow. Furthermore, the frontend allows full access to the C++ backend, so that the KDE can be used on any binnable one-dimensional input data. In this application note, we discuss implementation and usage details and illustrate potential applications. In particular, we benchmark the performance of our module in calculating the entropy of samples drawn from a Gaussian distribution and the analytical solution thereof. Further, we analyze the computational performance of this module compared to well-established python libraries that perform KDE analyses. X-Entropy is available free of charge on GitHub (https://github.com/liedllab/X-Entropy).

Mutation of Framework Residue H71 Results in Different Antibody Paratope States in Solution.

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.

Inverse relation between structural flexibility and IgE reactivity of Cor a 1 hazelnut allergens.

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.

Profiling selectivity of chagasin mutants towards cysteine proteases cruzain or cathepsin L through molecular dynamics simulations.

Chagasin, an endogenous cysteine protease inhibitor from Trypanosoma cruzi, can control the activity of the parasitic cruzain and its homologous human cathepsin L. While chagasin inhibits both enzymes with similar potency, mutations have different effects on binding to these enzymes. Mutants T31A and T31A/T32A bind well to cathepsin L, but their affinity for cruzain drops ∼40 to 140-fold. On the other hand, the mutant W93A binds well to cruzain, but it loses potency against cathepsin L. Here, we employed molecular dynamics simulations to understand the selectivity in inhibition of cruzain or cathepsin L by chagasin mutants W93A, T31A, and T31A/T32A. Our results allowed profiling the nonbonded interactions in the interfaces of each mutant with these cysteine proteases. Additionally, we observed differences in the binding conformation of the chagasin loops L2 and L6 of the W93A mutant, favoring interactions with cruzain and reducing interactions with cathepsin L. These differences are associated with a partial dissociation of the W93A-cathepsin L complex, providing a likely cause for the selectivity of the mutant W93A towards cruzain.Communicated by Ramaswamy H. Sarma.

Conformational Ensembles of Antibodies Determine Their Hydrophobicity.

A major challenge in the development of antibody biotherapeutics is their tendency to aggregate. One root cause for aggregation is exposure of hydrophobic surface regions to the solvent. Many current techniques predict the relative aggregation propensity of antibodies via precalculated scales for the hydrophobicity or aggregation propensity of single amino acids. However, those scales cannot describe the nonadditive effects of a residue's surrounding on its hydrophobicity. Therefore, they are inherently limited in their ability to describe the impact of subtle differences in molecular structure on the overall hydrophobicity. Here, we introduce a physics-based approach to describe hydrophobicity in terms of the hydration free energy using grid inhomogeneous solvation theory (GIST). We apply this method to assess the effects of starting structures, conformational sampling, and protonation states on the hydrophobicity of antibodies. Our results reveal that high-quality starting structures, i.e., crystal structures, are crucial for the prediction of hydrophobicity and that conformational sampling can compensate errors introduced by the starting structure. On the other hand, sampling of protonation states only leads to good results when combined with high-quality structures, whereas it can even be detrimental otherwise. We conclude by pointing out that a single static homology model may not be adequate for predicting hydrophobicity.

Polarizable and non-polarizable force fields: Protein folding, unfolding, and misfolding.

Molecular dynamics simulations are an invaluable tool to characterize the dynamic motions of proteins in atomistic detail. However, the accuracy of models derived from simulations inevitably relies on the quality of the underlying force field. Here, we present an evaluation of current non-polarizable and polarizable force fields (AMBER ff14SB, CHARMM 36m, GROMOS 54A7, and Drude 2013) based on the long-standing biophysical challenge of protein folding. We quantify the thermodynamics and kinetics of the ß-hairpin formation using Markov state models of the fast-folding mini-protein CLN025. Furthermore, we study the (partial) folding dynamics of two more complex systems, a villin headpiece variant and a WW domain. Surprisingly, the polarizable force field in our set, Drude 2013, consistently leads to destabilization of the native state, regardless of the secondary structure element present. All non-polarizable force fields, on the other hand, stably characterize the native state ensembles in most cases even when starting from a partially unfolded conformation. Focusing on CLN025, we find that the conformational space captured with AMBER ff14SB and CHARMM 36m is comparable, but the ensembles from CHARMM 36m simulations are clearly shifted toward disordered conformations. While the AMBER ff14SB ensemble overstabilizes the native fold, CHARMM 36m and GROMOS 54A7 ensembles both agree remarkably well with experimental state populations. In addition, GROMOS 54A7 also reproduces experimental folding times most accurately. Our results further indicate an over-stabilization of helical structures with AMBER ff14SB. Nevertheless, the presented investigations strongly imply that reliable (un)folding dynamics of small proteins can be captured in feasible computational time with current additive force fields.

In silico Design of Phl p 6 Variants With Altered Fold-Stability Significantly Impacts Antigen Processing, Immunogenicity and Immune Polarization.

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.

Solvation Thermodynamics in Different Solvents: Water-Chloroform Partition Coefficients from Grid Inhomogeneous Solvation Theory.

Reliable information on partition coefficients plays a key role in drug development, as solubility decisively affects bioavailability. In a physicochemical context, the partition coefficient of a solute between two different solvents can be described as a function of solvation free energies. Hence, substantial scientific efforts have been made toward accurate predictions of solvation free energies in various solvents. The grid inhomogeneous solvation theory (GIST) facilitates the calculation of solvation free energies. In this study, we introduce an extended version of the GIST algorithm, which enables the calculation for chloroform in addition to water. Furthermore, GIST allows localization of enthalpic and entropic contributions. We test our approach by calculating partition coefficients between water and chloroform for a set of eight small molecules. We report a Pearson correlation coefficient of 0.96 between experimentally determined and calculated partition coefficients. The capability to reliably predict partition coefficients between water and chloroform and the possibility to localize their contributions allow the optimization of a compound's partition coefficient. Therefore, we presume that this methodology will be of great benefit for the efficient development of pharmaceuticals.

Macrocycle Cell Permeability Measured by Solvation Free Energies in Polar and Apolar Environments.

The relation of surface polarity and conformational preferences is decisive for cell permeability and thus bioavailability of macrocyclic drugs. Here, we employ grid inhomogeneous solvation theory (GIST) to calculate solvation free energies for a series of six macrocycles in water and chloroform as a measure of passive membrane permeability. We perform accelerated molecular dynamics simulations to capture a diverse structural ensemble in water and chloroform, allowing for a direct profiling of solvent-dependent conformational preferences. Subsequent GIST calculations facilitate a quantitative measure of solvent preference in the form of a transfer free energy, calculated from the ensemble-averaged solvation free energies in water and chloroform. Hence, the proposed method considers how the conformational diversity of macrocycles in polar and apolar solvents translates into transfer free energies. Following this strategy, we find a striking correlation of 0.92 between experimentally determined cell permeabilities and calculated transfer free energies. For the studied model systems, we find that the transfer free energy exceeds the purely water-based solvation free energies as a reliable estimate of cell permeability and that conformational sampling is imperative for a physically meaningful model. We thus recommend this purely physics-based approach as a computational tool to assess cell permeabilities of macrocyclic drug candidates.

Comorbidities cluster with impaired functional capacities and depressive mood and predict adverse outcome in older patients with hematological malignancies.

This study evaluates prevalence of comorbidities and their association with impairments in older patients with hematological malignancies at initial diagnosis (n = 209). At least one comorbidity was present in 62.2%, 68.5% and 93.8% as defined by CCI (Charlson Comorbidity Index), Cumulative Illness Rating Scale-Geriatric (CIRS-G) and HCT-Comorbidity Index, respectively. Severe comorbidities (CIRS-G Grade 3/4) were present in 57.9%. The mean number of affected organ systems was 3.6 (CIRS-G categories), with diabetes (18.2%), congestive heart failure and prior solid tumors (each 17.7%) detected most frequently. Comorbidities were significantly correlated with reduced functional and objective physical capacities, impaired performance and depressive mood. Both CCI and CIRS-G were found to be prognostic factors for OS (p < 0.05). CCI scoring of comorbidities, diagnosis MDS/AML and a body mass index <23kg/m2 were independent adverse predictors for OS. This first prospective analysis reveals a prognostic significance of comorbidities. Clustering of comorbidities with impairments suggests common mechanisms.

Catalytic Site pKa Values of Aspartic, Cysteine, and Serine Proteases: Constant pH MD Simulations.

Enzymatic function and activity of proteases is closely controlled by the pH value. The protonation states of titratable residues in the active site react to changes in the pH value, according to their pKa, and thereby determine the functionality of the enzyme. Knowledge of the titration behavior of these residues is crucial for the development of drugs targeting the active site residues. However, experimental pKa data are scarce, since the systems' size and complexity make determination of these pKa values inherently difficult. In this study, we use single pH constant pH MD simulations as a fast and robust tool to estimate the active site pKa values of a set of aspartic, cysteine, and serine proteases. We capture characteristic pKa shifts of the active site residues, which dictate the experimentally determined activity profiles of the respective protease family. We find clear differences of active site pKa values within the respective families, which closely match the experimentally determined pH preferences of the respective proteases. These shifts are caused by a distinct network of electrostatic interactions characteristic for each protease family. While we find convincing agreement with experimental data for serine and aspartic proteases, we observe clear deficiencies in the description of the titration behavior of cysteines within the constant pH MD framework and highlight opportunities for improvement. Consequently, with this work, we provide a concise set of active site pKa values of aspartic and serine proteases, which could serve as reference for future theoretical as well as experimental studies.