Direct evidence of a low barrier hydrogen bond in the catalytic triad of a Serine protease

Charge Relay Without Proton Transfer: Coupling of Two Short Hydrogen Bonds via Imidazole in Models of Catalytic Triad of Serine Protease Active Site

A homologous series of 20 substituted alcohol-imidazole-acetate model complexes imitating the charge relay system in Ser-His-Asp catalytic triad of serine proteases is considered quantum-chemically. We show qualitatively that the geometries of alcohol-imidazole and imidazole-acetate short hydrogen bonds are strongly coupled via the central imidazole and such complexes are capable of effectively relaying the charge from acetate to alcohol moiety upon relatively small concerted proton displacements. We hypothesize an alternative catalytic mechanism of serine proteases that does not require two complete proton transfers or hydrogen bond breakage between Ser and His residues.

Alternate recognition by dengue protease: Proteolytic and binding assays provide functional evidence beyond an induced-fit

Proteases are key enzymes in viral replication, and interfering with these targets is the basis for therapeutic interventions. We previously introduced a hypothesis about conformational selection in the protease of dengue virus and related flaviviruses, based on conformational plasticity noted in X-ray structures. The present work presents the first functional evidence for alternate recognition by the dengue protease, in a mechanism based primarily on conformational selection rather than induced-fit. Recognition of distinct substrates and inhibitors in proteolytic and binding assays varies to a different extent, depending on factors reported to influence the protease structure. The pH, salinity, buffer type, and temperature cause a change in binding, proteolysis, or inhibition behavior. Using representative inhibitors with distinct structural scaffolds, we identify two contrasting binding profiles to dengue protease. Noticeable effects are observed in the binding assay upon inclusion of a non-ionic detergent in comparison to the proteolytic assay. The findings highlight the impact of the selection of testing conditions on the observed ligand affinity or inhibitory potency. From a broader scope, the dengue protease presents an example, where the induced-fit paradigm appears insufficient to explain binding events with the biological target. Furthermore, this protein reveals the complexity of comparing or combining biochemical assay data obtained under different conditions. This can be particularly critical for artificial intelligence (AI) approaches in drug discovery that rely on large datasets of compounds activity, compiled from different sources using non-identical testing procedures. In such cases, mismatched results will compromise the model quality and its predictive power.

Imidazoles are Tunable Nucleofuges for Developing Tyrosine-Reactive Electrophiles

Imidazole-1-sulfonyl and -sulfonate (imidazylate) are widely used in synthetic chemistry as nucleofuges for diazotransfer, nucleophilic substitution, and cross-coupling reactions. The utility of these reagents for protein bioconjugation, in contrast, have not been comprehensively explored and important considering the prevalence of imidazoles in biomolecules and drugs. Here, we synthesized a series of alkyne-modified sulfonyl- and sulfonate-imidazole probes to investigate the utility of this electrophile for protein binding. Alkylation of the distal nitrogen activated the nucleofuge capability of the imidazole to produce sulfonyl-imidazolium electrophiles that were highly reactive but unstable for biological applications. In contrast, arylsulfonyl imidazoles functioned as a tempered electrophile for assessing ligandability of select tyrosine and lysine sites in cell proteomes and when mated to a recognition element could produce targeted covalent inhibitors with reduced off-target activity. In summary, imidazole nucleofuges show balanced stability and tunability to produce sulfone-based electrophiles that bind functional tyrosine and lysine sites in the proteome.

Designing Efficient Enzymes: Eight Predicted Mutations Convert a Hydroxynitrile Lyase into an Efficient Esterase

Hydroxynitrile lyase from rubber tree (HbHNL) shares 45% identical amino acid residues with the homologous esterase from tobacco, SABP2, but the two enzymes catalyze different reactions. The x-ray structures reveal a serine-histidine-aspartate catalytic triad in both enzymes along with several differing amino acid residues within the active site. Previous exchange of three amino acid residues in the active site of HbHNL with the corresponding amino acid residue in SABP2 (T11G-E79H-K236M) created variant HNL3, which showed low esterase activity toward p-nitrophenyl acetate. Further structure comparison reveals additional differences surrounding the active site. HbHNL contains an improperly positioned oxyanion hole residue and differing solvation of the catalytic aspartate. We hypothesized that correcting these structural differences would impart good esterase activity on the corresponding HbHNL variant. To predict the amino acid substitutions needed to correct the structure, we calculated shortest path maps for both HbHNL and SABP2, which reveal correlated movements of amino acids in the two enzymes. Replacing four amino acid residues (C81L-N104T-V106F-G176S) whose movements are connected to the movements of the catalytic residues yielded variant HNL7TV (stabilizing substitution H103V was also added), which showed an esterase catalytic efficiency comparable to that of SABP2. The x-ray structure of an intermediate variant, HNL6V, showed an altered solvation of the catalytic aspartate and a partially corrected oxyanion hole. This dramatic increase in catalytic efficiency demonstrates the ability of shortest path maps to predict which residues outside the active site contribute to catalytic activity.

Chemical features and machine learning assisted predictions of protein-ligand short hydrogen bonds

There are continuous efforts to elucidate the structure and biological functions of short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms reside more than 0.3 Å closer than the sum of their van der Waals radii. In this work, we evaluate 1070 atomic-resolution protein structures and characterize the common chemical features of SHBs formed between the side chains of amino acids and small molecule ligands. We then develop a machine learning assisted prediction of protein-ligand SHBs (MAPSHB-Ligand) model and reveal that the types of amino acids and ligand functional groups as well as the sequence of neighboring residues are essential factors that determine the class of protein-ligand hydrogen bonds. The MAPSHB-Ligand model and its implementation on our web server enable the effective identification of protein-ligand SHBs in proteins, which will facilitate the design of biomolecules and ligands that exploit these close contacts for enhanced functions.

The Realm of Unconventional Noncovalent Interactions in Proteins: Their Significance in Structure and Function

Proteins and their assemblies are fundamental for living cells to function. Their complex three-dimensional architecture and its stability are attributed to the combined effect of various noncovalent interactions. It is critical to scrutinize these noncovalent interactions to understand their role in the energy landscape in folding, catalysis, and molecular recognition. This Review presents a comprehensive summary of unconventional noncovalent interactions, beyond conventional hydrogen bonds and hydrophobic interactions, which have gained prominence over the past decade. The noncovalent interactions discussed include low-barrier hydrogen bonds, C5 hydrogen bonds, C-H···π interactions, sulfur-mediated hydrogen bonds, n → π* interactions, London dispersion interactions, halogen bonds, chalcogen bonds, and tetrel bonds. This Review focuses on their chemical nature, interaction strength, and geometrical parameters obtained from X-ray crystallography, spectroscopy, bioinformatics, and computational chemistry. Also highlighted are their occurrence in proteins or their complexes and recent advances made toward understanding their role in biomolecular structure and function. Probing the chemical diversity of these interactions, we determined that the variable frequency of occurrence in proteins and the ability to synergize with one another are important not only for ab initio structure prediction but also to design proteins with new functionalities. A better understanding of these interactions will promote their utilization in designing and engineering ligands with potential therapeutic value.

Chemical Features and Machine Learning Assisted Predictions of Protein-Ligand Short Hydrogen Bonds

There are continuous efforts to elucidate the structure and biological functions of short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms reside more than 0.3 A closer than the sum of their van der Waals radii. In this work, we evaluate 1070 atomic-resolution protein structures and characterize the common chemical features of SHBs formed between the side chains of amino acids and small molecule ligands. We then develop a machine learning assisted prediction of protein-ligand SHBs (MAPSHB-Ligand) model and reveal that the types of amino acids and ligand functional groups as well as the sequence of neighboring residues are essential factors that determine the class of protein-ligand hydrogen bonds. The MAPSHB-Ligand model and its implementation on our web server enable the effective identification of protein-ligand SHBs in proteins, which will facilitate the design of biomolecules and ligands that exploit these close contacts for enhanced functions.

1H, 13C and 15N resonance assignment of backbone and IVL-methyl side chain of the S135A mutant NS3pro/NS2B protein of Dengue II virus reveals unique secondary structure features in solution

The serotype II Dengue (DENV 2) virus is the most prevalent of all four known serotypes. Herein, we present nearly complete ¹H, ¹⁵N, and ¹³C backbone and ¹H, ¹³C isoleucine, valine, and leucine methyl resonance assignment of the apo S135A catalytically inactive variant of the DENV 2 protease enzyme folded as a tandem formed between the serine protease domain NS3pro and the cofactor NS2B, as well as the secondary structure prediction of this complex based on the assigned chemical shifts using the TALOS-N software. Our results provide a solid ground for future elucidation of the structure and dynamic of the apo NS3pro/NS2B complex, key for adequate development of inhibitors, and a thorough molecular understanding of their function(s).

Structural insights into the activation of blood coagulation factor XI zymogen by thrombin: A computational molecular dynamics study

Activation of human blood coagulation factor XI zymogen to factor XIa plays a significant role in the upstream coagulation pathway, in which factor XIa activates factor IX zymogen. The mechanistic details of the proteolytic activation of factor XI by the activating enzyme thrombin are not well-understood at atomic level. In this study, we employed a combination of molecular docking and microsecond time-scale molecular dynamics simulations to identify the key regions of interaction between fXI and thrombin. The activating complex between the substrate and enzyme was modeled to represent the initial acylation step of the serine-protease hydrolysis mechanism. The proposed solution structural complex, fIX:fIIa, obtained from 3 microseconds of MD refinement, suggests that the activation of factor XI is mediated by thrombin's anion binding exosite-II interactions with A3 and A4 domains. We predict that the two positively charged arginine residues (Arg409 and Arg413) in the exosite-2 region, the β- and γ-insertion loops of thrombin play an important structural role in the initial activating complex between fXI and thrombin.

Effective prediction of short hydrogen bonds in proteins via machine learning method

Short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms lie within 2.7 Å, exhibit prominent quantum mechanical characters and are connected to a wide range of essential biomolecular processes. However, exact determination of the geometry and functional roles of SHBs requires a protein to be at atomic resolution. In this work, we analyze 1260 high-resolution peptide and protein structures from the Protein Data Bank and develop a boosting based machine learning model to predict the formation of SHBs between amino acids. This model, which we name as machine learning assisted prediction of short hydrogen bonds (MAPSHB), takes into account 21 structural, chemical and sequence features and their interaction effects and effectively categorizes each hydrogen bond in a protein to a short or normal hydrogen bond. The MAPSHB model reveals that the type of the donor amino acid plays a major role in determining the class of a hydrogen bond and that the side chain Tyr-Asp pair demonstrates a significant probability of forming a SHB. Combining electronic structure calculations and energy decomposition analysis, we elucidate how the interplay of competing intermolecular interactions stabilizes the Tyr-Asp SHBs more than other commonly observed combinations of amino acid side chains. The MAPSHB model, which is freely available on our web server, allows one to accurately and efficiently predict the presence of SHBs given a protein structure with moderate or low resolution and will facilitate the experimental and computational refinement of protein structures.

Fluoride ion Coordination-Induced Turn-On Fluorescence of Tailored N-Methyl N-Confused Tripyrromonomethene Analogues

Inorder to achieve striking compromise between flexibility and rigidity, two unprecedented highly air-stable N-methyl N-Confused tripyrromonomethene analogues in near quantitative yields have been synthesized by chloranil oxidation under aerobic condition....

Hydrogen Bonds and n → π* Interactions in the Acetylation of Propranolol Catalyzed by Candida antarctica Lipase B: A QTAIM Study

Enzyme-substrate interactions play a crucial role in enzymatic catalysis. Quantum theory of atoms in molecules (QTAIM) calculations are extremely useful in computational studies of these interactions because they provide very detailed information about the strengths and types of molecular interactions. QTAIM also provides information about the intramolecular changes that occur in the catalytic reaction. Here, we analyze the enzyme-substrate interactions and the topological properties of the electron density in the enantioselective step of the acylation of (R,S)-propranolol, an aminoalcohol with therapeutic applications, catalyzed by Candida antarctica lipase B. Eight reaction paths (four for each enantiomer) are investigated and the energies, atomic charges, hydrogen bonds, and n → π* interactions of propranolol, the catalytic triad (composed of D187, H224, and S105), and the oxyanion hole are analyzed. It is found that D187 acts as an electron density reservoir for H224, and H224 acts as an electron density reservoir for the active site of the protein. It releases electron density when the tetrahedral intermediate is formed from the Michaelis complex and receives it when the enzyme-product complex is formed. Hydrogen bonds can be grouped into noncovalent and covalent hydrogen bonds. The latter are stronger and more important for the reaction than the former. We also found weak n → π* interactions, which are characterized by QTAIM and the natural bond orbital (NBO) analysis.

Protease-triggered bioresponsive drug delivery for the targeted theranostics of malignancy

Proteases have a fundamental role in maintaining physiological homeostasis, but their dysregulation results in severe activity imbalance and pathological conditions, including cancer onset, progression, invasion, and metastasis. This striking importance plus superior biological recognition and catalytic performance of proteases, combining with the excellent physicochemical characteristics of nanomaterials, results in enzyme-activated nano-drug delivery systems (nanoDDS) that perform theranostic functions in highly specific response to the tumor phenotype stimulus. In the tutorial review, the key advances of protease-responsive nanoDDS in the specific diagnosis and targeted treatment for malignancies are emphatically classified according to the effector biomolecule types, on the premise of summarizing the structure and function of each protease. Subsequently, the incomplete matching and recognition between enzyme and substrate, structural design complexity, volume production, and toxicological issues related to the nanocomposites are highlighted to clarify the direction of efforts in nanotheranostics. This will facilitate the promotion of nanotechnology in the management of malignant tumors.

On the Case of the Misplaced Hydrogens

Few other elements play a more central role in biology than hydrogen. The interactions, bonding and movement of hydrogen atoms are central to biological catalysis, structure and function. Yet owing to the elusive nature of a single hydrogen atom few experimental and computational techniques can precisely determine its location. This is exemplified in short hydrogen bonds (SHBs) where the location of the hydrogen atom is indicative of the underlying strength of the bonds, which can vary from 1-5 kcal/mol in canonical hydrogen bonds, to an almost covalent nature in single-well hydrogen bonds. Owing to the often-times inferred position of hydrogen, the role of SHBs in biology has remained highly contested and debated. This has also led to discrepancies in computational, biochemical and structural studies of proteins thought to use SHBs in performing chemistry and stabilizing interactions. Herein, we discuss in detail two distinct examples, namely the conserved catalytic triad and the photoreceptor, photoactive yellow protein, where studies of these SHB-containing systems have permitted contextualization of the role these unique hydrogen bonds play in biology.

Low barrier hydrogen bonds in protein structure and function

Low-barrier hydrogen bonds (LBHBs) are a special type of short hydrogen bond (HB) that is characterized by the equal sharing of a hydrogen atom. The existence and catalytic role of LBHBs in proteins has been intensely contested. Advancements in X-ray and neutron diffraction methods has revealed delocalized hydrogen atoms involved in potential LBHBs in a number of proteins, while also demonstrating that short HBs are not necessarily LBHBs. More importantly, a series of experiments on ketosteroid isomerase (KSI) have suggested that LBHBs are significantly stronger than standard HBs in the protein microenvironment in terms of enthalpy, but not free energy. The discrepancy between the enthalpy and free energy of LBHBs offers clues to the challenges, and potential solutions, of the LBHB debate, where the unique strength of LBHBs plays a special role in the kinetic processes of enzyme function and structure, together with other molecular forces in a pre-organized environment.

TAAM: a reliable and user friendly tool for hydrogen-atom location using routine X-ray diffraction data

Hydrogen is present in almost all of the molecules in living things. It is very reactive and forms bonds with most of the elements, terminating their valences and enhancing their chemistry. X-ray diffraction is the most common method for structure determination. It depends on scattering of X-rays from electron density, which means the single electron of hydrogen is difficult to detect. Generally, neutron diffraction data are used to determine the accurate position of hydrogen atoms. However, the requirement for good quality single crystals, costly maintenance and the limited number of neutron diffraction facilities means that these kind of results are rarely available. Here it is shown that the use of Transferable Aspherical Atom Model (TAAM) instead of Independent Atom Model (IAM) in routine structure refinement with X-ray data is another possible solution which largely improves the precision and accuracy of X-H bond lengths and makes them comparable to averaged neutron bond lengths. TAAM, built from a pseudoatom databank, was used to determine the X-H bond lengths on 75 data sets for organic molecule crystals. TAAM parametrizations available in the modified University of Buffalo Databank (UBDB) of pseudoatoms applied through the DiSCaMB software library were used. The averaged bond lengths determined by TAAM refinements with X-ray diffraction data of atomic resolution (d_min ≤ 0.83 Å) showed very good agreement with neutron data, mostly within one single sample standard deviation, much like Hirshfeld atom refinement (HAR). Atomic displacements for both hydrogen and non-hydrogen atoms obtained from the refinements systematically differed from IAM results. Overall TAAM gave better fits to experimental data of standard resolution compared to IAM. The research was accompanied with development of software aimed at providing user-friendly tools to use aspherical atom models in refinement of organic molecules at speeds comparable to routine refinements based on spherical atom model.

Probing contacts of inhibitor locked in transition states in the catalytic triad of DENV2 type serine protease and its mutants by 1H, 19F and 15 N NMR spectroscopy

Background

Detailed structural knowledge of enzyme-inhibitor complexes trapped in intermediate state is the key for a fundamental understanding of reaction mechanisms taking place in enzymes and is indispensable as a structure-guided drug design tool. Solution state NMR uniquely allows the study of active sites of enzymes in equilibrium between different tautomeric forms. In this study 1H, 19F and 15 N NMR spectroscopy has been used to probe the interaction contacts of inhibitors locked in transition states of the catalytic triad of a serine protease. It was demonstrated on the serotype II Dengue virus NS2B:NS3pro serine protease and its mutants, H51N and S135A, in complex with high-affinity ligands containing trifluoromethyl ketone (tfk) and boronic groups in the C-terminal of tetra-peptides.

Results

Monitoring 19F resonances, shows that only one of the two isomers of the tfk tetra-peptide binds with NS2B:NS3pro and that access to the bulk of the active site is limited. Moreover, there were no bound water found in proximity of the active site for any of the ligands manifesting in a favorable condition for formation of low barrier hydrogen bonds (LBHB) in the catalytic triad. Based on this data we were able to identify a locked conformation of the protein active site. The data also indicates that the different parts of the binding site most likely act independently of each other.

Conclusions

Our reported findings increases the knowledge of the detailed function of the catalytic triad in serine proteases and could facilitate the development of rational structure based inhibitors that can selectively target the NS3 protease of Dengue type II (DENV2) virus. In addition the results shows the usefulness of probing active sites using ¹⁹F NMR spectroscopy.

Extreme Catalytic Power of Ketosteroid Isomerase Related to the Reversal of Proton Dislocations in Hydrogen-Bond Network

Dynamic electrostatic catalytic field (DECF) vectors derived from transition state and reactant wavefunctions for the two-step reaction occurring within ketosteroid isomerase (KSI) have been calculated using MP2/aug-cc-pVTZ and lower theory levels to determine the magnitude of the catalytic effect and the optimal directions of proton transfers in the KSI hydrogen-bond network. The most surprising and meaningful finding is that the KSI catalytic activity is enhanced by proton dislocations proceeding in opposite directions for each of the two consecutive reaction steps in the same hydrogen network. Such a mechanism allows an ultrafast switching of the catalytic proton wire environment, possibly related to the exceptionally high KSI catalytic power.

Symmetry and 1H NMR chemical shifts of short hydrogen bonds: impact of electronic and nuclear quantum effects

Electronic and nuclear quantum effects determine the symmetry and highly downfield ¹H NMR chemical shifts of short hydrogen bonds.

Unraveling the structural and chemical features of biological short hydrogen bonds

Short hydrogen bonds are ubiquitous in biological macromolecules and exhibit distinctive proton potential energy surfaces and proton sharing properties.

The three-dimensional architecture of biomolecules often creates specialized structural elements, notably short hydrogen bonds that have donor–acceptor separations below 2.7 Å. In this work, we statistically analyze 1663 high-resolution biomolecular structures from the Protein Data Bank and demonstrate that short hydrogen bonds are prevalent in proteins, protein–ligand complexes and nucleic acids. From these biological macromolecules, we characterize the preferred location, connectivity and amino acid composition in short hydrogen bonds and hydrogen bond networks, and assess their possible functional importance. Using electronic structure calculations, we further uncover how the interplay of the structural and chemical features determines the proton potential energy surfaces and proton sharing conditions in biological short hydrogen bonds.

The rhomboid protease GlpG has weak interaction energies in its active site hydrogen bond network

Rhomboid proteases are membrane-integrated enzymes that hydrolyze peptide bonds in the transmembrane domains of protein substrates. Gaffney and Hong experimentally determine interaction energies between active site residues to reveal weak coupling, which may explain the slow proteolysis mediated by GlpG.

Intramembrane rhomboid proteases are of particular interest because of their function to hydrolyze a peptide bond of a substrate buried in the membrane. Crystal structures of the bacterial rhomboid protease GlpG have revealed a catalytic dyad (Ser201-His254) and oxyanion hole (His150/Asn154/the backbone amide of Ser201) surrounded by the protein matrix and contacting a narrow water channel. Although multiple crystal structures have been solved, the catalytic mechanism of GlpG is not completely understood. Because it is a serine protease, hydrogen bonding interactions between the active site residues are thought to play a critical role in the catalytic cycle. Here, we dissect the interaction energies among the active site residues His254, Ser201, and Asn154 of Escherichia coli GlpG, which form a hydrogen bonding network. We combine double mutant cycle analysis with stability measurements using steric trapping. In mild detergent, the active site residues are weakly coupled with interaction energies (ΔΔG_Inter) of ‒1.4 kcal/mol between His254 and Ser201 and ‒0.2 kcal/mol between Ser201 and Asn154. Further, by analyzing the propagation of single mutations of the active site residues, we find that these residues are important not only for function but also for the folding cooperativity of GlpG. The weak interaction between Ser and His in the catalytic dyad may partly explain the unusually slow proteolysis by GlpG compared with other canonical serine proteases. Our result suggests that the weak hydrogen bonds in the active site are sufficient to carry out the proteolytic function of rhomboid proteases.