Evaluation of Methods for the Calculation of the pKa of Cysteine Residues in Proteins

Chloride- and Hydrosulfide-Bound 2Fe Complexes as Models of the Oxygen-Stable State of [FeFe] Hydrogenase

[FeFe] hydrogenases demonstrate remarkable catalytic efficiency in hydrogen evolution and oxidation processes. However, susceptibility of these enzymes to oxygen-induced degradation impedes their practical deployment in hydrogen-production devices and fuel cells. Recent investigations into the oxygen-stable (Hinact) state of the H-cluster revealed its inherent capacity to resist oxygen degradation. Herein, we present findings on Cl- and SH-bound [2Fe-2S] complexes, bearing relevance to the oxygen-stable state within a biological context. A characteristic attribute of these complexes is the terminal Cl-/SH- ligation to the iron center bearing the CO bridge. Structural analysis of the t-Cl demonstrates a striking resemblance to the Hinact state of DdHydAB and CbA5H. The t-Cl/t-SH exhibit reversible oxidation, with both redox species, electronically, being the first biomimetic analogs to the Htrans and Hinact states. These complexes exhibit notable resistance against oxygen-induced decomposition, supporting the potential oxygen-resistant nature of the Htrans and Hinact states. The swift reductive release of the Cl-/SH-group demonstrates its labile and kinetically controlled binding. The findings garnered from these investigations offer valuable insights into properties of the enzymatic O2-stable state, and key factors governing deactivation and reactivation conversion. This work contributes to the advancement of bio-inspired molecular catalysts and the integration of enzymes and artificial catalysts into H2-evolution devices and fuel-cell applications.

A Comprehensive Study of Factors Affecting the Prediction of the pKa Shift of Asp26 in Thioredoxin Protein

The stable protonation state of ionizable amino acids in a protein can be predicted by computing the pKa shift of that residue within the protein environment. Thermodynamic Integration (TI) is an ideal molecular dynamics-based approach for predicting the pKa shift of ionizable protein residues. Here, we probe TI-based simulation protocols for their ability to accurately predict the pKa shift of Asp26 in thioredoxin. While implicit solvent models can predict the pKa shift accurately, explicit solvent models result in substantial errors. To understand the underlying reason for this surprising discrepancy, we investigate the role of various factors such as solvent models, conformational sampling, background charges, and polarization.

Recent Progress in the Endosomal Escape Mechanism and Chemical Structures of Polycations for Nucleic Acid Delivery

Nucleic acid-based therapies are seeing a spiralling surge. Stimuli-responsive polymers, especially pH-responsive ones, are gaining widespread attention because of their ability to efficiently deliver nucleic acids. These polymers can be synthesized and modified according to target requirements, such as delivery sites and the nature of nucleic acids. In this regard, the endosomal escape mechanism of polymer-nucleic acid complexes (polyplexes) remains a topic of considerable interest owing to various plausible escape mechanisms. This review describes current progress in the endosomal escape mechanism of polyplexes and state-of-the-art chemical designs for pH-responsive polymers. The importance is also discussed of the acid dissociation constant (i.e., pKa) in designing the new generation of pH-responsive polymers, along with assays to monitor and quantify the endosomal escape behavior. Further, the use of machine learning is addressed in pKa prediction and polymer design to find novel chemical structures for pH responsiveness. This review will facilitate the design of new pH-responsive polymers for advanced and efficient nucleic acid delivery.

Molecular Insights into the Impact of Mutations on the Binding Affinity of Targeted Covalent Inhibitors of BTK

Targeted covalent inhibitors (TCIs) have witnessed a significant resurgence in recent years, particularly in the kinase drug discovery field for treating diverse clinical indications. The inhibition of Bruton's tyrosine kinase (BTK) for treating B-cell cancers is a classic example where TCIs such as ibrutinib have had breakthroughs in targeted therapy. However, selectivity remains challenging, and the emergence of resistance mutations is a critical concern for clinical efficacy. Computational methods that can accurately predict the impact of mutations on inhibitor binding affinity could prove helpful in informing targeted approaches─providing insights into drug resistance mechanisms. In addition, such systems could help guide the systematic evaluation and impact of mutations in disease models for optimal experimental design. Here, we have employed in silico physics-based methods to understand the effects of mutations on the binding affinity and conformational dynamics of select TCIs of BTK. The TCIs studied include ibrutinib, acalabrutinib, and zanubrutinib─all of which are FDA-approved drugs for treating multiple forms of leukemia and lymphoma. Our results offer useful molecular insights into the structural determinants, thermodynamics, and conformational energies that impact ligand binding for this biological target of clinical relevance.

The expanding repertoire of covalent warheads for drug discovery

The reactive functionalities of drugs that engage in covalent interactions with the enzyme/receptor residue in either a reversible or an irreversible manner are called 'warheads'. Covalent warheads that were previously neglected because of safety concerns have recently gained center stage as a result of their various advantages over noncovalent drugs, including increased selectivity, increased residence time, and higher potency. With the approval of several covalent inhibitors over the past decade, research in this area has accelerated. Various strategies are being continuously developed to tune the characteristics of warheads to improve their potency and mitigate toxicity. Here, we review research progress in warhead discovery over the past 5 years to provide valuable insights for future drug discovery.

Understanding Cysteine Reactivity in Protein Environments with Electric Fields

The role cysteine residues play in proteins is mediated by their protonation state, whereby the thiolate form of the side chain is highly reactive while the thiol form is more inert. However, the pKa of cysteine residues is hard to predict as it can differ widely from its reference value in solution, an effect that is accentuated by local effects in the heterogeneous protein environment. Here, we present a new approach to the prediction of cysteine reactivity based on electric field calculations at the thiol/thiolate group. We validated our approach by predicting the protonation state of cysteine residues in different protein environments (in the active site, at the protein surface, and buried within the protein interior), including Cys-25 in papaya protease omega, which was proven problematic for the more traditional constant pH molecular dynamics (MD) technique. We predict pKa shifts consistent with experimental observations, and the decomposition of the electric fields into contributions from molecular fragments provides a direct handle to rationalize local pH and pKa effects in proteins without introducing parameters other than those of the force field used for MD simulations.

Accurately Predicting Protein pKa Values Using Nonequilibrium Alchemy

The stability, solubility, and function of a protein depend on both its net charge and the protonation states of its individual residues. pKa is a measure of the tendency for a given residue to (de)protonate at a specific pH. Although pKa values can be resolved experimentally, theory and computation provide a compelling alternative. To this end, we assess the applicability of a nonequilibrium (NEQ) alchemical free energy method to the problem of pKa prediction. On a data set of 144 residues that span 13 proteins, we report an average unsigned error of 0.77 ± 0.09, 0.69 ± 0.09, and 0.52 ± 0.04 pK for aspartate, glutamate, and lysine, respectively. This is comparable to current state-of-the-art predictors and the accuracy recently reached using free energy perturbation methods (e.g., FEP+). Moreover, we demonstrate that our open-source, pmx-based approach can accurately resolve the pKa values of coupled residues and observe a substantial performance disparity associated with the lysine partial charges in Amber14SB/Amber99SB*-ILDN, for which an underused fix already exists.

Alchemical Calculation of Relative Free Energies for Charge-Changing Mutations at Protein-Protein Interfaces Considering Fixed and Variable Protonation States

The calculation of relative free energies (ΔΔG) for charge-changing mutations at protein-protein interfaces through alchemical methods remains challenging due to variations in the system's net charge during charging steps, the possibility of mutated and contacting ionizable residues occurring in various protonation states, and undersampling issues. In this study, we present a set of strategies, collectively termed TIRST/TIRST-H+, to address some of these challenges. Our approaches combine thermodynamic integration (TI) with the prediction of pKa shifts to calculate ΔΔG values. Moreover, special sets of restraints are employed to keep the alchemically transformed molecules separated. The accuracy of the devised approaches was assessed on a large and diverse data set comprising 164 point mutations of charged residues (Asp, Glu, Lys, and Arg) to Ala at the protein-protein interfaces of complexes with known three-dimensional structures. Mean absolute and root-mean-square errors ranging from 1.38 to 1.66 and 1.89 to 2.44 kcal/mol, respectively, and Pearson correlation coefficients of ∼0.6 were obtained when testing the approaches on the selected data set using the GPU-TI module of Amber18 suite and the ff14SB force field. Furthermore, the inclusion of variable protonation states for the mutated acid residues improved the accuracy of the predicted ΔΔG values. Therefore, our results validate the use of TIRST/TIRST-H+ in prospective studies aimed at evaluating the impact of charge-changing mutations to Ala on the stability of protein-protein complexes.

Interactions between selectivity filter and pore helix control filter gating in the MthK channel

K+ channel activity can be limited by C-type inactivation, which is likely initiated in part by dissociation of K+ ions from the selectivity filter and modulated by the side chains that surround it. While crystallographic and computational studies have linked inactivation to a "collapsed" selectivity filter conformation in the KcsA channel, the structural basis for selectivity filter gating in other K+ channels is less clear. Here, we combined electrophysiological recordings with molecular dynamics simulations, to study selectivity filter gating in the model potassium channel MthK and its V55E mutant (analogous to KcsA E71) in the pore-helix. We found that MthK V55E has a lower open probability than the WT channel, due to decreased stability of the open state, as well as a lower unitary conductance. Simulations account for both of these variables on the atomistic scale, showing that ion permeation in V55E is altered by two distinct orientations of the E55 side chain. In the "vertical" orientation, in which E55 forms a hydrogen bond with D64 (as in KcsA WT channels), the filter displays reduced conductance compared to MthK WT. In contrast, in the "horizontal" orientation, K+ conductance is closer to that of MthK WT; although selectivity filter stability is lowered, resulting in more frequent inactivation. Surprisingly, inactivation in MthK WT and V55E is associated with a widening of the selectivity filter, unlike what is observed for KcsA and reminisces recent structures of inactivated channels, suggesting a conserved inactivation pathway across the potassium channel family.

Structural and functional fine mapping of cysteines in mammalian glutaredoxin reveal their differential oxidation susceptibility

Protein-S-glutathionylation is a post-translational modification involving the conjugation of glutathione to protein thiols, which can modulate the activity and structure of key cellular proteins. Glutaredoxins (GLRX) are oxidoreductases that regulate this process by performing deglutathionylation. However, GLRX has five cysteines that are potentially vulnerable to oxidative modification, which is associated with GLRX aggregation and loss of activity. To date, GLRX cysteines that are oxidatively modified and their relative susceptibilities remain unknown. We utilized molecular modeling approaches, activity assays using recombinant GLRX, coupled with site-directed mutagenesis of each cysteine both individually and in combination to address the oxidizibility of GLRX cysteines. These approaches reveal that C8 and C83 are targets for S-glutathionylation and oxidation by hydrogen peroxide in vitro. In silico modeling and experimental validation confirm a prominent role of C8 for dimer formation and aggregation. Lastly, combinatorial mutation of C8, C26, and C83 results in increased activity of GLRX and resistance to oxidative inactivation and aggregation. Results from these integrated computational and experimental studies provide insights into the relative oxidizability of GLRX's cysteines and have implications for the use of GLRX as a therapeutic in settings of dysregulated protein glutathionylation.

Cysteine Redox Chemistry in Peptide Self-Assembly to Modulate Hydrogelation

Cysteine redox chemistry is widely used in nature to direct protein assembly, and in recent years it has inspired chemists to design self-assembling peptides too. In this concise review, we describe the progress in the field focusing on the recent advancements that make use of Cys thiol-disulfide redox chemistry to modulate hydrogelation of various peptide classes.

Integrated Covalent Drug Design Workflow Using Site Identification by Ligand Competitive Saturation

Covalent drug design is an important component in drug discovery. Traditional drugs interact with their target in a reversible equilibrium, while irreversible covalent drugs increase the drug-target interaction duration by forming a covalent bond with targeted residues and thus may offer a more effective therapeutic approach. To facilitate the design of this class of ligands, computational methods can be used to help identify reactive nucleophilic residues, frequently cysteines, on a target protein for covalent binding, to test various warhead groups for their potential reactivities, and to predict noncovalent contributions to binding that can facilitate drug-target interactions that are important for binding specificity. To further aid covalent drug design, we extended a functional group mapping approach based on explicit solvent all-atom molecular simulations (SILCS: site identification by ligand competitive saturation) that intrinsically considers protein flexibility, functional group, and protein desolvation along with functional group-protein interactions. Through docking of a library of representative warhead fragments using SILCS-Monte Carlo (SILCS-MC), reactive cysteines can be correctly identified for proteins being tested. Furthermore, a machine learning model was trained to quantify the effectiveness of various warhead groups for proteins using metrics from SILCS-MC as well as experimental model compound warhead reactivity data. The ability to rank covalent molecular binders with similar warheads using SILCS ligand grid free energy (LGFE) ranking was also tested for several proteins. Based on these tools, an integrated SILCS-based workflow was developed, named SILCS-Covalent, which can both qualitatively and quantitatively inform covalent drug discovery.

Cu+/Ag+ Competition in Type I Copper Proteins (T1Cu)

Due to the similarity in the basic coordination behavior of their mono-charged cations, silver biochemistry is known to be linked to that of copper in biological systems. Still, Cu⁺/²⁺ is an essential micronutrient in many organisms, while no known biological process requires silver. In human cells, copper regulation and trafficking is strictly controlled by complex systems including many cytosolic copper chaperones, whereas some bacteria exploit the so-called "blue copper" proteins. Therefore, evaluating the controlling factors of the competition between these two metal cations is of enormous interest. By employing the tools of computational chemistry, we aim to delineate the extent to which Ag⁺ might be able to compete with the endogenous copper in its Type I (T1Cu) proteins, and where and if, alternatively, it is handled uniquely. The effect of the surrounding media (dielectric constant) and the type, number, and composition of amino acid residues are taken into account when modelling the reactions in the present study. The obtained results clearly indicate the susceptibility of the T1Cu proteins to a silver attack due to the favorable composition and geometry of the metal-binding centers, along with the similarity between the Ag⁺/Cu⁺-containing structures. Furthermore, by exploring intriguing questions of both metals' coordination chemistry, an important background for understanding the metabolism and biotransformation of silver in organisms is provided.

Benchmarking In Silico Tools for Cysteine pKa Prediction

Accurate estimation of the pK_a's of cysteine residues in proteins could inform targeted approaches in hit discovery. The pK_a of a targetable cysteine residue in a disease-related protein is an important physiochemical parameter in covalent drug discovery, as it influences the fraction of nucleophilic thiolate amenable to chemical protein modification. Traditional structure-based in silico tools are limited in their predictive accuracy of cysteine pK_a's relative to other titratable residues. Additionally, there are limited comprehensive benchmark assessments for cysteine pK_a predictive tools. This raises the need for extensive assessment and evaluation of methods for cysteine pK_a prediction. Here, we report the performance of several computational pK_a methods, including single-structure and ensemble-based approaches, on a diverse test set of experimental cysteine pK_a's retrieved from the PKAD database. The dataset consisted of 16 wildtype and 10 mutant proteins with experimentally measured cysteine pK_a values. Our results highlight that these methods are varied in their overall predictive accuracies. Among the test set of wildtype proteins evaluated, the best method (MOE) yielded a mean absolute error of 2.3 pK units, highlighting the need for improvement of existing pK_a methods for accurate cysteine pK_a estimation. Given the limited accuracy of these methods, further development is needed before these approaches can be routinely employed to drive design decisions in early drug discovery efforts.

Advances in the Spectroscopic and Structural Characterization of Core Light-Harvesting Complexes from Purple Phototrophic Bacteria

Purple phototrophic bacteria are ancient anoxygenic phototrophs and attractive research tools because they capture light energy in the near-infrared (NIR) region of the spectrum and transform it into chemical energy by way of uphill energy transfers. The heart of this reaction occurs in light-harvesting 1-reaction center (LH1-RC) complexes, which are the simplest model systems for understanding basic photosynthetic reactions within type-II (quinone-utilizing) reaction centers. In this Perspective, we highlight structure-function relationships concerning unresolved fundamental processes in purple bacterial photosynthesis, including the diversified light-harvesting capacity of LH1-associated BChl molecules, energies necessary for photoelectric conversion in the RC special pairs, and quinone transport mechanisms. Based on recent progress in the spectroscopic and structural analysis of LH1-RC complexes from a variety of purple phototrophs, we discuss several key factors for understanding how purple bacteria resource light energy in the inherently energy-poor NIR region of the electromagnetic spectrum.

Molecular determinants of acrylamide neurotoxicity through covalent docking

Acrylamide (ACR) is formed during food processing by Maillard reaction between sugars and proteins at high temperatures. It is also used in many industries, from water waste treatment to manufacture of paper, fabrics, dyes and cosmetics. Unfortunately, cumulative exposure to acrylamide, either from diet or at the workplace, may result in neurotoxicity. Such adverse effects arise from covalent adducts formed between acrylamide and cysteine residues of several neuronal proteins via a Michael addition reaction. The molecular determinants of acrylamide reactivity and its impact on protein function are not completely understood. Here we have compiled a list of acrylamide protein targets reported so far in the literature in connection with neurotoxicity and performed a systematic covalent docking study. Our results indicate that acrylamide binding to cysteine is favored in the presence of nearby positively charged amino acids, such as lysines and arginines. For proteins with more than one reactive Cys, docking scores were able to discriminate between the primary ACR modification site and secondary sites modified only at high ACR concentrations. Therefore, docking scores emerge as a potential filter to predict Cys reactivity against acrylamide. Inspection of the ACR-protein complex structures provides insights into the putative functional consequences of ACR modification, especially for non-enzyme proteins. Based on our study, covalent docking is a promising computational tool to predict other potential protein targets mediating acrylamide neurotoxicity.

AMOEBA Force Field Trajectories Improve Predictions of Accurate pKa Values of the GFP Fluorophore: The Importance of Polarizability and Water Interactions

Precisely quantifying the magnitude, direction, and biological functions of electric fields in proteins has long been an outstanding challenge in the field. The most widely implemented experimental method to measure such electric fields at a particular residue in a protein has been through changes in pKa of titratable residues. While many computational strategies exist to predict these values, it has been difficult to do this accurately or connect predicted results to key structural or mechanistic features of the molecule. Here, we used experimentally determined pKa values of the fluorophore in superfolder green fluorescent protein (GFP) with amino acid mutations made at position Thr 203 to evaluate the pKa prediction ability of molecular dynamics (MD) simulations using a polarizable force field, AMOEBA. Structure ensembles from AMOEBA were used to calculate pKa values of the GFP fluorophore. The calculated pKa values were then compared to trajectories using a conventional fixed charge force field (Amber03 ff). We found that the position of water molecules included in the pKa calculation had opposite effects on the pKa values between the trajectories from AMOEBA and Amber03 force fields. In AMOEBA trajectories, the inclusion of water molecules within 35 Å of the fluorophore decreased the difference between the predicted and experimental values, resulting in calculated pKa values that were within an average of 0.8 pKa unit from the experimental results. On the other hand, in Amber03 trajectories, including water molecules that were more than 5 Å from the fluorophore increased the differences between the calculated and experimental pKa values. The inaccuracy of pKa predictions determined from Amber03 trajectories was caused by a significant stabilization of the deprotonated chromophore's free energy compared to the result in AMOEBA. We rationalize the cutoffs for explicit water molecules when calculating pKa to better predict the electrostatic environment surrounding the fluorophore buried in GFP. We discuss how the results from this work will assist the prospective prediction of pKa values or other electrostatic effects in a wide variety of folded proteins.

Electrophile versus oxidant modification of cysteine residues: Kinetics as a key driver of protein modification

Humans have widespread exposure to both oxidants, and soft electrophilic compounds such as alpha,beta-unsaturated aldehydes and quinones. Electrophilic motifs are commonly found in a drugs, industrial chemicals, pollutants and are also generated via oxidant-mediated degradation of biomolecules including lipids (e.g. formation of 4-hydroxynonenal, 4-hydroxyhexenal, prostaglandin J2). All of these classes of compounds react efficiently with Cys residues, and the particularly the thiolate anion, with this resulting in Cys modification via either oxidation or adduct formation. This can result in deleterious or beneficial effects, that are either reversible (e.g. in cell signalling) or irreversible (damaging). For example, acrolein is a well-established toxin, whereas dimethylfumarate is used in the treatment of multiple sclerosis and psoriasis. This short review discusses the targets of alpha,beta-unsaturated aldehydes, and particularly two prototypic cases, acrolein and dimethylfumarate, and the factors that control the selectivity and kinetics of reaction of these species. Comparison is made between the reactivity of oxidants versus soft electrophiles. These rate constants indicate that electrophiles can be significant thiol modifying agents in some situations, as they have rate constants similar to or greater than species such as H₂O₂, can be present at higher concentrations, and are less efficiently removed by protective systems when compared to H₂O₂. They may also induce similar or higher levels of modification than highly reactive oxidants, due to the very low concentrations of oxidants formed in most in vivo situations.

Cysteine Oxidation in Proteins: Structure, Biophysics, and Simulation

Cysteine side chains can exist in distinct oxidation states depending on the pH and redox potential of the environment, and cysteine oxidation plays important yet complex regulatory roles. Compared with the effects of post-translational modifications such as phosphorylation, the effects of oxidation of cysteine to sulfenic, sulfinic, and sulfonic acid on protein structure and function remain relatively poorly characterized. We present an analysis of the role of cysteine reactivity as a regulatory factor in proteins, emphasizing the interplay between electrostatics and redox potential as key determinants of the resulting oxidation state. A review of current computational approaches suggests underdeveloped areas of research for studying cysteine reactivity through molecular simulations.

Estimating the binding energetics of reversible covalent inhibitors of the SARS-CoV-2 main protease: an in silico study

The main protease (M^pro) of the SARS-CoV-2 virus is an attractive therapeutic target for developing antivirals to combat COVID-19. M^pro is essential for the replication cycle of the SARS-CoV-2 virus, so inhibiting M^pro blocks a vital piece of the cell replication machinery of the virus. A promising strategy to disrupt the viral replication cycle is to design inhibitors that bind to the active site cysteine (Cys145) of the M^pro. Cysteine targeted covalent inhibitors are gaining traction in drug discovery owing to the benefits of improved potency and extended drug-target engagement. An interesting aspect of these inhibitors is that they can be chemically tuned to form a covalent, but reversible bond, with their targets of interest. Several small-molecule cysteine-targeting covalent inhibitors of the M^pro have been discovered-some of which are currently undergoing evaluation in early phase human clinical trials. Understanding the binding energetics of these inhibitors could provide new insights to facilitate the design of potential drug candidates against COVID-19. Motivated by this, we employed rigorous absolute binding free energy calculations and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations to estimate the energetics of binding of some promising reversible covalent inhibitors of the M^pro. We find that the inclusion of enhanced sampling techniques such as replica-exchange algorithm in binding free energy calculations can improve the convergence of predicted non-covalent binding free energy estimates of inhibitors binding to the M^pro target. In addition, our results indicate that binding free energy calculations coupled with multiscale simulations can be a useful approach to employ in ranking covalent inhibitors to their targets. This approach may be valuable in prioritizing and refining covalent inhibitor compounds for lead discovery efforts against COVID-19 and other coronavirus infections.

Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces

We have used molecular dynamics (MD) simulations with hybrid quantum mechanics/molecular mechanics (QM/MM) potentials to investigate the reaction mechanism for covalent inhibition of cathepsin K and assess the reversibility of inhibition. The computed free energy profiles suggest that a nucleophilic attack by the catalytic cysteine on the inhibitor warhead and proton transfer from the catalytic histidine occur in a concerted manner. The results indicate that the reaction is more strongly exergonic for the alkyne-based inhibitors, which bind irreversibly to cathepsin K, than for the nitrile-based inhibitor odanacatib, which binds reversibly. Gas-phase energies were also calculated for the addition of methanethiol to structural prototypes for a number of warheads of interest in cysteine protease inhibitor design in order to assess electrophilicity. The approaches presented in this study are particularly applicable to assessment of novel warheads, and computed transition state geometries can be incorporated into molecular models for covalent docking.

Proteome-Wide Profiling of the Covalent-Druggable Cysteines with a Structure-Based Deep Graph Learning Network

Covalent ligands have attracted increasing attention due to their unique advantages, such as long residence time, high selectivity, and strong binding affinity. They also show promise for targets where previous efforts to identify noncovalent small molecule inhibitors have failed. However, our limited knowledge of covalent binding sites has hindered the discovery of novel ligands. Therefore, developing in silico methods to identify covalent binding sites is highly desirable. Here, we propose DeepCoSI, the first structure-based deep graph learning model to identify ligandable covalent sites in the protein. By integrating the characterization of the binding pocket and the interactions between each cysteine and the surrounding environment, DeepCoSI achieves state-of-the-art predictive performances. The validation on two external test sets which mimic the real application scenarios shows that DeepCoSI has strong ability to distinguish ligandable sites from the others. Finally, we profiled the entire set of protein structures in the RCSB Protein Data Bank (PDB) with DeepCoSI to evaluate the ligandability of each cysteine for covalent ligand design, and made the predicted data publicly available on website.

Dithiol Based on l-Cysteine and Cysteamine as a Disulfide-Reducing Agent

We report the synthesis, chemical properties, and disulfide bond-reducing performance of a dithiol called NACMEAA, conceived as a hybrid of two biologically relevant thiols: cysteine and cysteamine. NACMEAA is conveniently prepared from inexpensive l-cystine in an efficient manner. As a nonvolatile, highly soluble, and neutral compound at physiological pH with the first thiol pK_a value of 8.0, NACMEAA is reactive and user-friendly. We also demonstrate that NACMEAA reduces disulfide bonds in GSSG and lysozyme.

Genetic validation of Aspergillus fumigatus phosphoglucomutase as a viable therapeutic target in invasive aspergillosis

Aspergillus fumigatus is the causative agent of invasive aspergillosis, an infection with mortality rates of up to 50%. The glucan-rich cell wall of A. fumigatus is a protective structure that is absent from human cells and is a potential target for antifungal treatments. Glucan is synthesized from the donor uridine diphosphate glucose, with the conversion of glucose-6-phosphate to glucose-1-phosphate by the enzyme phosphoglucomutase (PGM) representing a key step in its biosynthesis. Here, we explore the possibility of selectively targeting A. fumigatus PGM (AfPGM) as an antifungal treatment strategy. Using a promoter replacement strategy, we constructed a conditional pgm mutant and revealed that pgm is required for A. fumigatus growth and cell wall integrity. In addition, using a fragment screen, we identified the thiol-reactive compound isothiazolone fragment of PGM as targeting a cysteine residue not conserved in the human ortholog. Furthermore, through scaffold exploration, we synthesized a para-aryl derivative (ISFP10) and demonstrated that it inhibits AfPGM with an IC50 of 2 μM and exhibits 50-fold selectivity over the human enzyme. Taken together, our data provide genetic validation of PGM as a therapeutic target and suggest new avenues for inhibiting AfPGM using covalent inhibitors that could serve as tools for chemical validation.

Salt- and pH-Dependent Thermal Stability of Photocomplexes from Extremophilic Bacteriochlorophyll b-Containing Halo-rhodospira Species

Halorhodospira (Hlr.) species are the most halophilic and alkaliphilic of all purple bacteria. Hlr. halochloris exhibits the lowest LH1 Q_y transition energy among phototrophic organisms and is the only known triply extremophilic anoxygenic phototroph, displaying a thermophilic, halophilic, and alkaliphilic phenotype. Recently, we reported that electrostatic charges are responsible for the unusual spectroscopic properties of the Hlr. halochloris LH1 complex. In the present work, we examined the effects of salt and pH on the spectroscopic properties and thermal stability of LH1-RCs from Hlr. halochloris compared with its mesophilic counterpart, Hlr. abdelmalekii. Experiments in which the photocomplexes were subjected to different levels of salt or variable pH revealed that the thermal stability of LH1-RCs from both species was largely retained in the presence of high salt concentrations and/or at alkaline pH but was markedly reduced by lowering the salt concentration and/or pH. Based on the amino acid sequences of LH1 polypeptides and their composition of acidic/basic residues and the Hofmeister series for cation/anion species, we discuss the importance of electrostatic charge in stabilizing the Hlr. halochloris LH1-RC complex to allow it to perform photosynthesis in its warm, hypersaline, and alkaline habitat.

Deamidation of the human eye lens protein γS-crystallin accelerates oxidative aging

Cataract, a clouding of the eye lens from protein precipitation, affects millions of people every year. The lens proteins, the crystallins, show extensive post-translational modifications (PTMs) in cataractous lenses. The most common PTMs, deamidation and oxidation, promote crystallin aggregation; however, it is not clear precisely how these PTMs contribute to crystallin insolubilization. Here, we report six crystal structures of the lens protein γS-crystallin (γS): one of the wild-type and five of deamidated γS variants, from three to nine deamidation sites, after sample aging. The deamidation mutations do not change the overall fold of γS; however, increasing deamidation leads to accelerated disulfide-bond formation. Addition of deamidated sites progressively destabilized protein structure, and the deamidated variants display an increased propensity for aggregation. These results suggest that the deamidated variants are useful as models for accelerated aging; the structural changes observed provide support for redox activity of γS-crystallin in the lens.

Modeling the Binding and Conformational Energetics of a Targeted Covalent Inhibitor to Bruton's Tyrosine Kinase

Targeted covalent inhibitors (TCIs) bind to their targets in both covalent and noncovalent modes, providing exceptionally high affinity and selectivity. These inhibitors have been effectively employed as inhibitors of protein kinases, with Taunton and coworkers (Nat. Chem. Biol. 2015, 11, 525-531) reporting a notable example of a TCI with a cyanoacrylamide warhead that forms a covalent thioether linkage to an active-site cysteine (Cys481) of Bruton's tyrosine kinase (BTK). The specific mechanism of the binding and the relative importance of the covalent and noncovalent interactions is difficult to determine experimentally, and established simulation methods for calculating the absolute binding affinity of an inhibitor cannot describe the covalent bond-forming steps. Here, an integrated approach using alchemical free-energy perturbation and QM/MM molecular dynamics methods was employed to model the complete Gibbs energy profile for the covalent inhibition of BTK by a cyanoacrylamide TCI. These calculations provide a rigorous and complete absolute Gibbs energy profile of the covalent modification binding process. Following a classic thiol-Michael addition mechanism, the target cysteine is deprotonated to form a nucleophilic thiolate, which then undergoes a facile conjugate addition to the electrophilic functional group to form a bond with the noncovalently bound ligand. This model predicts that the formation of the covalent linkage is highly exergonic relative to the noncovalent binding alone. Nevertheless, noncovalent interactions between the ligand and individual amino acid residues in the binding pocket of the enzyme are also essential for ligand binding, particularly van der Waals dispersion forces, which have a larger contribution to the binding energy than the covalent component in absolute terms. This model also shows that the mechanism of covalent modification of a protein occurs through a complex series of steps and that entropy, conformational flexibility, noncovalent interactions, and the formation of covalent linkage are all significant factors in the ultimate binding affinity of a covalent drug to its target.

Reactivities of the Front Pocket N-Terminal Cap Cysteines in Human Kinases

The front pocket (FP) N-terminal cap (Ncap) cysteine is the most popular site of covalent modification in kinases. A long-standing hypothesis associates the Ncap position with cysteine hyper-reactivity; however, traditional computational predictions suggest that the FP Ncap cysteines are predominantly unreactive. Here we applied the state-of-the-art continuous constant pH molecular dynamics (CpHMD) to test the Ncap hypothesis. Simulations found that the Ncap cysteines of BTK/BMX/TEC/ITK/TXK, JAK3, and MKK7 are reactive to varying degrees; however, those of BLK and EGFR/ERBB2/ERBB4 possessing a Ncap+3 aspartate are unreactive. Analysis suggested that hydrogen bonding and electrostatic interactions drive the reactivity, and their absence renders the Ncap cysteine unreactive. To further test the Ncap hypothesis, we examined the FP Ncap+2 cysteines in JNK1/JNK2/JNK3 and CASK. Our work offers a systematic understanding of the cysteine structure-reactivity relationship and illustrates the use of CpHMD to differentiate cysteines toward the design of targeted covalent inhibitors with reduced chemical reactivities.

The Se-S Bond Formation in the Covalent Inhibition Mechanism of SARS-CoV-2 Main Protease by Ebselen-like Inhibitors: A Computational Study

The inhibition mechanism of the main protease (Mpro) of SARS-CoV-2 by ebselen (EBS) and its analog with a hydroxyl group at position 2 of the benzisoselenazol-3(2H)-one ring (EBS-OH) was studied by using a density functional level of theory. Preliminary molecular dynamics simulations on the apo form of Mpro were performed taking into account both the hydrogen donor and acceptor natures of the Nδ and Nε of His41, a member of the catalytic dyad. The potential energy surfaces for the formation of the Se-S covalent bond mediated by EBS and EBS-OH on Mpro are discussed in detail. The EBS-OH shows a distinctive behavior with respect to EBS in the formation of the noncovalent complex. Due to the presence of canonical H-bonds and noncanonical ones involving less electronegative atoms, such as sulfur and selenium, the influence on the energy barriers and reaction energy of the Minnesota hybrid meta-GGA functionals M06, M06-2X and M08HX, and the more recent range-separated hybrid functional wB97X were also considered. The knowledge of the inhibition mechanism of Mpro by the small protease inhibitors EBS or EBS-OH can enlarge the possibilities for designing more potent and selective inhibitor-based drugs to be used in combination with other antiviral therapies.

Regulation of the Dimerization and Activity of SARS-CoV-2 Main Protease through Reversible Glutathionylation of Cysteine 300

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent for coronavirus disease 2019 (COVID-19), encodes two proteases required for replication. The main protease (M^pro), encoded as part of two polyproteins, pp1a and pp1ab, is responsible for 11 different cleavages of these viral polyproteins to produce mature proteins required for viral replication. M^pro is therefore an attractive target for therapeutic interventions. Certain proteins in cells under oxidative stress undergo modification of reactive cysteines. We show M^pro is susceptible to glutathionylation, leading to inhibition of dimerization and activity. Activity of glutathionylated M^pro could be restored with reducing agents or glutaredoxin. Analytical studies demonstrated that glutathionylated M^pro primarily exists as a monomer and that modification of a single cysteine with glutathione is sufficient to block dimerization and inhibit its activity. Gel filtration studies as well as analytical ultracentrifugation confirmed that glutathionylated M^pro exists as a monomer. Tryptic and chymotryptic digestions of M^pro as well as experiments using a C300S M^pro mutant revealed that Cys300, which is located at the dimer interface, is a primary target of glutathionylation. Moreover, Cys300 is required for inhibition of activity upon M^pro glutathionylation. These findings indicate that M^pro dimerization and activity can be regulated through reversible glutathionylation of a non-active site cysteine, Cys300, which itself is not required for M^pro activity, and provides a novel target for the development of agents to block M^pro dimerization and activity. This feature of M^pro may have relevance to the pathophysiology of SARS-CoV-2 and related bat coronaviruses.

Electrostatic charge controls the lowest LH1 Qy transition energy in the triply extremophilic purple phototrophic bacterium, Halorhodospira halochloris

Halorhodospira (Hlr.) halochloris is a unique phototrophic purple bacterium because it is a triple extremophile-the organism is thermophilic, alkalophilic, and halophilic. The most striking photosynthetic feature of Hlr. halochloris is that the bacteriochlorophyll (BChl) b-containing core light-harvesting (LH1) complex surrounding its reaction center (RC) exhibits its LH1 Q_y absorption maximum at 1016 nm, which is the lowest transition energy among phototrophic organisms. Here we report that this extraordinarily red-shifted LH1 Q_y band of Hlr. halochloris exhibits interconvertible spectral shifts depending on the electrostatic charge distribution around the BChl b molecules. The 1016 nm band of the Hlr. halochloris LH1-RC complex was blue-shifted to 958 nm upon desalting or pH decrease but returned to its original position when supplemented with salts or pH increase. Resonance Raman analysis demonstrated that these interconvertible spectral shifts are not associated with the strength of hydrogen-bonding interactions between BChl b and LH1 polypeptides. Furthermore, circular dichroism signals for the LH1 Q_y transition of Hlr. halochloris appeared with a positive sign (as in BChl b-containing Blastochloris species) and opposite those of BChl a-containing purple bacteria, possibly due to a combined effect of slight differences in the transition dipole moments between BChl a and BChl b and in the interactions between adjacent BChls in their assembled state. Based on these findings and LH1 amino acid sequences, it is proposed that Hlr. halochloris evolved its unique and tunable light-harvesting system with electrostatic charges in order to carry out photosynthesis and thrive in its punishing hypersaline and alkaline habitat.

Computational Study of the Addition of Methanethiol to 40+ Michael Acceptors as a Model for the Bioconjugation of Cysteines

A long series of Michael acceptors are studied computationally as potential alternatives to the maleimides that are used in most antibody-drug conjugates to link Cys of mAbs with cytotoxic drugs. The products of the reaction of methanethiol (CH3SH/MeSH, as a simple model of Cys) with N-methylated ethynesulfonamide, 2-ethynylpyridinium ion, propynamide, and methyl ethynephosphonamidate (that is, with HC≡C-EWG) are predicted by the M06-2X/6-311+G(d,p) method to be thermodynamically more stable, in relation to their precursors, than that of MeSH with N-methylmaleimide and, in general, with H2C═CH-EWG; calculations with AcCysOMe and tBuSH are also included. However, for the addition of the anion (MeS-), which is the reactive species, the order changes and N-methylated 2-vinylpyridinium ion, 2,3-butadienamide, and maleimide may give more easily the anionic adducts than several activated triple bonds; moreover, the calculated ΔG⧧ values increase following the order HC≡C-SO2NHMe, N-methylmaleimide, HC≡C-PO(OMe)NHMe, and HC≡C-CONHMe. In other words, MeS- is predicted to react more rapidly with maleimides than with ethynephosphonamidates and with propynamides, in agreement with the experimental results. New mechanistic details are disclosed regarding the advantageous use of some amides, especially of ethynesulfonamides, which, however, are more prone to double additions and exchange reactions.

Regulation of the Dimerization and Activity of SARS-CoV-2 Main Protease through Reversible Glutathionylation of Cysteine 300

SARS-CoV-2 encodes main protease (M^pro), an attractive target for therapeutic interventions. We show M^pro is susceptible to glutathionylation leading to inhibition of dimerization and activity. Activity of glutathionylated M^pro could be restored with reducing agents or glutaredoxin. Analytical studies demonstrated that glutathionylated M^pro primarily exists as a monomer and that a single modification with glutathione is sufficient to block dimerization and loss of activity. Proteolytic digestions of M^pro revealed Cys300 as a primary target of glutathionylation, and experiments using a C300S M^pro mutant revealed that Cys300 is required for inhibition of activity upon M^pro glutathionylation. These findings indicate that M^pro dimerization and activity can be regulated through reversible glutathionylation of Cys300 and provides a novel target for the development of agents to block Mpro dimerization and activity. This feature of M^pro may have relevance to human disease and the pathophysiology of SARS-CoV-2 in bats, which develop oxidative stress during flight.

Covalent and non-covalent binding free energy calculations for peptidomimetic inhibitors of SARS-CoV-2 main protease

COVID-19, the disease caused by the newly discovered coronavirus-SARS-CoV-2, has created a global health, social, and economic crisis. As of mid-January 2021, there are over 90 million confirmed cases and more than 2 million reported deaths due to COVID-19. Currently, there are very limited therapeutics for the treatment or prevention of COVID-19. For this reason, it is important to find drug targets that will lead to the development of safe and effective therapeutics against the disease. The main protease (M^pro) of the virus is an attractive target for the development of effective antiviral therapeutics because it is required for proteolytic cleavage of viral polyproteins. Furthermore, the M^pro has no human homologues, so drugs designed to bind to this target directly have less risk for off-target effects. Recently, several high-resolution crystallographic structures of the M^pro in complex with inhibitors have been determined-to guide drug development and to spur efforts in structure-based drug design. One of the primary objectives of modern structure-based drug design is the accurate prediction of receptor-ligand binding affinities for rational drug design and discovery. Here, we perform rigorous alchemical absolute binding free energy calculations and QM/MM calculations to give insight into the total binding energy of two recently crystallized inhibitors of SARS-CoV-2 M^pro, namely, N3 and α-ketoamide 13b. The total binding energy consists of both covalent and non-covalent binding components since both compounds are covalent inhibitors of the M^pro. Our results indicate that the covalent and non-covalent binding free energy contributions of both inhibitors to the M^pro target differ significantly. The N3 inhibitor has more favourable non-covalent interactions, particularly hydrogen bonding, in the binding site of the M^pro than the α-ketoamide inhibitor. Also, the Gibbs energy of reaction for the M^pro-N3 covalent adduct is greater than the Gibbs reaction energy for the M^pro-α-ketoamide covalent adduct. These differences in the covalent and non-covalent binding free energy contributions for both inhibitors could be a plausible explanation for their in vitro differences in antiviral activity. Our findings are consistent with the reversible and irreversible character of both inhibitors as reported by experiment and highlight the importance of both covalent and non-covalent binding free energy contributions to the absolute binding affinity of a covalent inhibitor towards its target. This information could prove useful in the rational design, discovery, and evaluation of potent SARS-CoV-2 M^pro inhibitors for targeted antiviral therapy.

Insights into Ubiquitin Product Release in Hydrolysis Catalyzed by the Bacterial Deubiquitinase SdeA

We report the co-crystal structure of the (catalytic Cys)-to-Ala mutant of the deubiquitinase domain of the Legionella pneumophila effector SdeA (SdeA_DUB) with its ubiquitin (Ub) product. Most of the intermolecular interactions are preserved in this product-bound structure compared to that of the previously characterized complex of SdeA_DUB with the suicide inhibitor ubiquitin vinylmethyl ester (Ub-VME), whose structure models the acyl-enzyme thioester intermediate. Nuclear magnetic resonance (NMR) titration studies show a chemical shift perturbation pattern that suggests that the same interactions also exist in solution. Isothermal titration calorimetry and NMR titration data reveal that the affinity of wild-type (WT) SdeA_DUB for Ub is significantly lower than that of the Cys-to-Ala mutant. This is potentially due to repulsive interaction between the thiolate ion of the catalytic Cys residue in WT SdeA_DUB and the carboxylate group of the C-terminal Gly76 residue in Ub. In the context of SdeA_DUB catalysis, this electrostatic repulsion arises after the hydrolysis of the scissile isopeptide bond in the acyl-enzyme intermediate and the consequent formation of the C-terminal carboxylic group in the Ub fragment. We hypothesize that this electrostatic repulsion may expedite the release of the Ub product by SdeA_DUB. We note that similar repulsive interactions may also occur in other deubiquitinases and hydrolases of ubiquitin-like protein modifiers and may constitute a fairly general mechanism of product release within this family. This is a potentially important feature for a family of enzymes that form extensive protein-protein interactions during enzyme-substrate engagement.

Metal- and Affinity-Specific Dual Labeling of Cysteine-Rich Proteins for Identification of Metal-Binding Sites

Here, using human metallothionein (MT2) as an example, we describe an improved strategy based on differential alkylation coupled to MS, assisted by zinc probe monitoring, for identification of cysteine-rich binding sites with nanomolar and picomolar metal affinity utilizing iodoacetamide (IAM) and N-ethylmaleimide reagents. We concluded that an SN2 reaction provided by IAM is more suitable to label free Cys residues, avoiding nonspecific metal dissociation. Afterward, metal-bound Cys can be easily labeled in a nucleophilic addition reaction after separation by reverse-phase C18 at acidic pH. Finally, we evaluated the efficiency of the method by mapping metal-binding sites of Zn7-xMT species using a bottom-up MS approach with respect to metal-to-protein affinity and element(al) resolution. The methodology presented might be applied not only for MT2 but to identify metal-binding sites in other Cys-containing proteins.

Proof of concept for poor inhibitor binding and efficient formation of covalent adducts of KRASG12C and ARS compounds

The use of selective covalent inhibitors with low binding affinity and high reactivity with the target enzyme is a promising way to solve a long-standing problem of the "undruggable" RAS-like proteins. Specifically, compounds of the ARS family that prevent the activation of the GDP-bound G12C mutant of Kirsten RAS (KRAS) are in the focus of recent experimental research. We report the first computational characterization of the entire reaction mechanism of the covalent binding of ARS-853 to the KRASG12C·GDP complex. The application of molecular dynamics, molecular docking and quantum mechanics/molecular mechanics approaches allowed us to model the inhibitor binding to the protein and the chemical reaction of ARS-853 with Cys12 in the enzyme binding site. We estimated a full set of kinetic constants and carried out numerical kinetic analysis of the process. Thus, we were able to compare directly the physicochemical parameters of the reaction obtained in silico and the macroscopic parameters observed in experimental studies. From our computational results, we explain the observed unusual dependence of the rate constant of covalent complex formation, kobs, on the ARS concentration. The latter depends both on the non-covalent binding step with the equilibrium constant, Ki, and on the rate constant of covalent adduct formation, kinact. The calculated ratio kinact/Ki = 213 M-1 s-1 reproduces the corresponding experimental value of 250 ± 30 M-1 s-1 for the interaction of ARS-853 with KRASG12C. Electron density analysis in the reactive region demonstrates that covalent bond formation occurs efficiently according to the Michael addition mechanism, which assumes the activation of the C[double bond, length as m-dash]C bond of ARS-853 by a water molecule and Lys16 in the binding site of KRASG12C. We also refine the kinact and Ki constants of the ARS-107 compound, which shares common features with ARS-853, and show that the decrease in the kinact/Ki ratio in the case of ARS-107 is explained by changes in both Ki and kinact constants.

Computing pKa Shifts Using Traditional Molecular Dynamics: Example of Acid-Base Indicator Dyes in Organized Solutions

A compound's acidity constant (K_a) in a given medium determines its protonation state and, thus, its behavior and physicochemical properties. Therefore, it is among the key characteristics considered during the design of new compounds for the needs of advanced technology, medicine, and biological research, a notable example being pH sensors. The computational prediction of K_a for weak acids and bases in homogeneous solvents is presently rather well developed. However, it is not the case for more complex media, such as microheterogeneous solutions. The constant-pH molecular dynamics (MD) method is a notable contribution to the solution of the problem, but it is not commonly used. Here, we develop an approach for predicting K_a changes of weak small-molecule acids upon transfer from water to colloid solutions by means of traditional classical molecular dynamics. The approach is based on free energy (ΔG) computations and requires limited experiment data input during calibration. It was successfully tested on a series of pH-sensitive acid-base indicator dyes in micellar solutions of surfactants. The difficulty of finite-size effects affecting ΔG computation between states with different total charges is taken into account by evaluating relevant corrections; their impact on the results is discussed, and it is found non-negligible (0.1-0.4 pK_a units). A marked bias is found in the ΔG values of acid deprotonation, as computed from MD, which is apparently caused by force-field issues. It is hypothesized to affect the constant-pH MD and reaction ensemble MD methods as well. Consequently, for these methods, a preliminary calibration is suggested.

The Effect of Thiol Structure on Allyl Sulfide Photodegradable Hydrogels and their Application as a Degradable Scaffold for Organoid Passaging

Intestinal organoids are useful in vitro models for basic and translational studies aimed at understanding and treating disease. However, their routine culture relies on animal-derived matrices that limit translation to clinical applications. In fact, there are few fully defined, synthetic hydrogel systems that allow for the expansion of intestinal organoids. Here, an allyl sulfide photodegradable hydrogel is presented, achieving rapid degradation through radical addition-fragmentation chain transfer (AFCT) reactions, to support routine passaging of intestinal organoids. Shear rheology to first characterize the effect of thiol and allyl sulfide crosslink structures on degradation kinetics is used. Irradiation with 365 nm light (5 mW cm-2 ) in the presence of a soluble thiol (glutathione at 15 × 10-3 m), and a photoinitiator (lithium phenyl-2,4,6-trimethylbenzoylphosphinate at 1 × 10-3 m), leads to complete hydrogel degradation in less than 15 s. Allyl sulfide hydrogels are used to support the formation of epithelial colonies from single intestinal stem cells, and rapid photodegradation is used to achieve repetitive passaging of stem cell colonies without loss in morphology or organoid formation potential. This platform could support long-term culture of intestinal organoids, potentially replacing the need for animal-derived matrices, while also allowing systematic variations to the hydrogel properties tailored for the organoid of interest.

Predicting Reactive Cysteines with Implicit-Solvent-Based Continuous Constant pH Molecular Dynamics in Amber

Cysteines existing in the deprotonated thiolate form or having a tendency to become deprotonated are important players in enzymatic and cellular redox functions and frequently exploited in covalent drug design; however, most computational studies assume cysteines as protonated. Thus, developing an efficient tool that can make accurate and reliable predictions of cysteine protonation states is timely needed. We recently implemented a generalized Born (GB) based continuous constant pH molecular dynamics (CpHMD) method in Amber for protein pKa calculations on CPUs and GPUs. Here we benchmark the performance of GB-CpHMD for predictions of cysteine pKa's and reactivities using a data set of 24 proteins with both down- and upshifted cysteine pKa's. We found that 10 ns single-pH or 4 ns replica-exchange CpHMD titrations gave root-mean-square errors of 1.2-1.3 and correlation coefficients of 0.8-0.9 with respect to experiment. The accuracy of predicting thiolates or reactive cysteines at physiological pH with single-pH titrations is 86 or 81% with a precision of 100 or 90%, respectively. This performance well surpasses the traditional structure-based methods, particularly a widely used empirical pKa tool that gives an accuracy less than 50%. We discuss simulation convergence, dependence on starting structures, common determinants of the pKa downshifts and upshifts, and the origin of the discrepancies from the structure-based calculations. Our work suggests that CpHMD titrations can be performed on a desktop computer equipped with a single GPU card to predict cysteine protonation states for a variety of applications, from understanding biological functions to covalent drug design.

Fully Atomistic Multiscale Approach for pKa Prediction

The ionization state of titratable amino acids strongly affects proteins structure and functioning in a large number of biological processes. It is therefore essential to be able to characterize the pK_a of ionizable groups inside proteins and to understand its microscopic determinants in order to gain insights into many functional properties of proteins. A big effort has been devoted to the development of theoretical approaches for the prediction of deprotonation free energies, yet the accurate theoretical/computational calculation of pK_a values is recognized as a current challenge. A methodology based on a hybrid quantum/classical approach is here proposed for the computation of deprotonation free energies. The method is applied to calculate the pK_a of formic acid, methylammonium, and methanethiol, providing results in good agreement with the corresponding experimental estimates. The pK_a is also calculated for aspartic acid and lysine as single residues in solution and for three aspartic/glutamic acids inside a well-characterized protein: hen egg white lysozyme. While for small molecules the method is able to deal with multiple protonation states of all titratable groups, this becomes computationally very expensive for proteins. The calculated pK_a values for the single amino acids (except for the zwitterionic aspartic acid) and inside the protein display a systematic shift with respect to the experimental values that suggests that the fine balance between hydrophobic and polar interactions might be not accurately reproduced by the usual classical force-fields, thus affecting the computation of deprotonation free energies. The calculated pK_a shifts inside the protein are in good agreement with the corresponding experimental ones (within 1 pK_a unit), well reproducing the pK_a changes due to the protein environment even in the case of large pK_a shifts.

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 pK_a, 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 pK_a data are scarce, since the systems’ size and complexity make determination of these pK_a 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 pK_a values of a set of aspartic, cysteine, and serine proteases. We capture characteristic pK_a 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 pK_a 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 pK_a values of aspartic and serine proteases, which could serve as reference for future theoretical as well as experimental studies.

Redox Systems Biology: Harnessing the Sentinels of the Cysteine Redoxome

Significance: Cellular redox processes are highly interconnected, yet not in equilibrium, and governed by a wide range of biochemical parameters. Technological advances continue refining how specific redox processes are regulated, but broad understanding of the dynamic interconnectivity between cellular redox modules remains limited. Systems biology investigates multiple components in complex environments and can provide integrative insights into the multifaceted cellular redox state. This review describes the state of the art in redox systems biology as well as provides an updated perspective and practical guide for harnessing thousands of cysteine sensors in the redoxome for multiparameter characterization of cellular redox networks. Recent Advances: Redox systems biology has been applied to genome-scale models and large public datasets, challenged common conceptions, and provided new insights that complement reductionist approaches. Advances in public knowledge and user-friendly tools for proteome-wide annotation of cysteine sentinels can now leverage cysteine redox proteomics datasets to provide spatial, functional, and protein structural information. Critical Issues: Careful consideration of available analytical approaches is needed to broadly characterize the systems-level properties of redox signaling networks and be experimentally feasible. The cysteine redoxome is an informative focal point since it integrates many aspects of redox biology. The mechanisms and redox modules governing cysteine redox regulation, cysteine oxidation assays, proteome-wide annotation of the biophysical and biochemical properties of individual cysteines, and their clinical application are discussed. Future Directions: Investigating the cysteine redoxome at a systems level will uncover new insights into the mechanisms of selectivity and context dependence of redox signaling networks.

A bifunctional asparaginyl endopeptidase efficiently catalyzes both cleavage and cyclization of cyclic trypsin inhibitors

Asparaginyl endopeptidases (AEPs) catalyze the key backbone cyclization step during the biosynthesis of plant-derived cyclic peptides. Here, we report the identification of two AEPs from Momordica cochinchinensis and biochemically characterize MCoAEP2 that catalyzes the maturation of trypsin inhibitor cyclotides. Recombinantly produced MCoAEP2 catalyzes the backbone cyclization of a linear cyclotide precursor (MCoTI-II-NAL) with a k_cat/K_m of 620 mM⁻¹ s⁻¹, making it one of the fastest cyclases reported to date. We show that MCoAEP2 can mediate both the N-terminal excision and C-terminal cyclization of cyclotide precursors in vitro. The rate of cyclization/hydrolysis is primarily influenced by varying pH, which could potentially control the succession of AEP-mediated processing events in vivo. Furthermore, MCoAEP2 efficiently catalyzes the backbone cyclization of an engineered MCoTI-II analog with anti-angiogenic activity. MCoAEP2 provides enhanced synthetic access to structures previously inaccessible by direct chemistry approaches and enables the wider application of trypsin inhibitor cyclotides in biotechnology applications.

Asparaginyl endopeptidases (AEPs) catalyze the cyclization step during the biosynthesis of cyclic peptides in plants. Here, the authors report a recombinantly produced AEP that catalyzes the backbone cyclization of a linear cyclotide precursor and an engineered analog with high efficiency and in a pH-dependent manner.

Assessment of the Cruzain Cysteine Protease Reversible and Irreversible Covalent Inhibition Mechanism

Reversible and irreversible covalent ligands are advanced cysteine protease inhibitors in the drug development pipeline. K777 is an irreversible inhibitor of cruzain, a necessary enzyme for the survival of the Trypanosoma cruzi (T. cruzi) parasite, the causative agent of Chagas disease. Despite their importance, irreversible covalent inhibitors are still often avoided due to the risk of adverse effects. Herein, we replaced the K777 vinyl sulfone group with a nitrile moiety to obtain a reversible covalent inhibitor (Neq0682) of cysteine protease. Then, we used advanced experimental and computational techniques to explore details of the inhibition mechanism of cruzain by reversible and irreversible inhibitors. The isothermal titration calorimetry (ITC) analysis shows that inhibition of cruzain by an irreversible inhibitor is thermodynamically more favorable than by a reversible one. The hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) and Molecular Dynamics (MD) simulations were used to explore the mechanism of the reaction inhibition of cruzain by K777 and Neq0682. The calculated free energy profiles show that the Cys25 nucleophilic attack and His162 proton transfer occur in a single step for a reversible inhibitor and two steps for an irreversible covalent inhibitor. The hybrid QM/MM calculated free energies for the inhibition reaction correspond to -26.7 and -5.9 kcal mol^-1 for K777 and Neq0682 at the MP2/MM level, respectively. These results indicate that the ΔG of the reaction is very negative for the process involving K777, consequently, the covalent adduct cannot revert to a noncovalent protein-ligand complex, and its binding tends to be irreversible. Overall, the present study provides insights into a covalent inhibition mechanism of cysteine proteases.

Evaluating QM/MM Free Energy Surfaces for Ranking Cysteine Protease Covalent Inhibitors

One tactic for cysteine protease inhibition is to form a covalent bond between an electrophilic atom of the inhibitor and the thiol of the catalytic cysteine. In this study, we evaluate the reaction free energy obtained from a hybrid quantum mechanical/molecular mechanical (QM/MM) free energy profile as a predictor of affinity for reversible, covalent inhibitors of rhodesain. We demonstrate that the reaction free energy calculated with the PM6/MM potential is in agreement with the experimental data and suggest that the free energy profile for covalent bond formation in a protein environment may be a useful tool for the inhibitor design.

Catalytic Mechanism and Covalent Inhibition of UDP-N-Acetylglucosamine Enolpyruvyl Transferase (MurA): Implications to the Design of Novel Antibacterials

UDP-N-acetylglucosamine enolpyruvyl transferase (MurA) catalyzes the first step in the biosynthesis of the bacterial cell wall. This pathway is essential for the growth of bacteria but missing in mammals, that nominates MurA as an attractive antibacterial target. MurA has a flexible loop whose conformational change is known to be part of the activation mechanism of the enzyme. We have shown that the loop closed conformation makes the proton transfer from Cys115 to His394 possible by a low barrier exothermic process. QM/MM MD simulations revealed that the activated thiolate is able to react with phosphoenolpyruvate (PEP), the natural substrate of MurA. The binding free energy profile of several covalent inhibitors with various warheads reacting with the activated Cys115 was calculated by QM/MM MD simulations and confirmed that reaction barrier heights tend to separate active from inactive compounds. Our results give new insight into the catalytic mechanism and covalent inhibition of MurA and suggest that QM/MM MD simulations are able to support ligand design by providing sensible relative free energy barriers for covalent inhibitors with various warheads reacting with thiolate nucleophiles.