An evolutionarily conserved allosteric site modulates beta-lactamase activity

Conserved proline residues prevent dimerization and aggregation in the β-lactamase BlaC

Evolution leads to conservation of amino acid residues in protein families. Conserved proline residues are usually considered to ensure the correct folding and to stabilize the three-dimensional structure. Surprisingly, proline residues that are highly conserved in class A β-lactamases were found to tolerate various substitutions without large losses in enzyme activity. We investigated the roles of three conserved prolines at positions 107, 226, and 258 in the β-lactamase BlaC from Mycobacterium tuberculosis and found that mutations can lead to dimerization of the enzyme and an overall less stable protein that is prone to aggregate over time. For the variant Pro107Thr, the crystal structure shows dimer formation resembling domain swapping. It is concluded that the proline substitutions loosen the structure, enhancing multimerization. Even though the enzyme does not lose its properties without the conserved proline residues, the prolines ensure the long-term structural integrity of the enzyme.

Structure and function of prodrug-activating peptidases

Bacteria protect themselves from the toxicity of antimicrobial metabolites they produce through several strategies. In one resistance mechanism, bacteria assemble a non-toxic precursor on an N-acyl-d-asparagine prodrug motif in the cytoplasm, then export it to the periplasm where a dedicated d-amino peptidase hydrolyzes the prodrug motif. These prodrug-activating peptidases contain an N-terminal periplasmic S12 hydrolase domain and C-terminal transmembrane domains (TMDs) of varying lengths: type I peptidases contain three transmembrane helices, and type II peptidases have an additional C-terminal ABC half-transporter. We review studies which have addressed the role of the TMD in function, the substrate specificity, and the biological assembly of ClbP, the type I peptidase that activates colibactin. We use modeling and sequence analyses to extend those insights to other prodrug-activating peptidases and ClbP-like proteins which are not part of prodrug resistance gene clusters. These ClbP-like proteins may play roles in the biosynthesis or degradation of other natural products, including antibiotics, may adopt different TMD folds, and have different substrate specificity compared to prodrug-activating homologs. Finally, we review the data supporting the long-standing hypothesis that ClbP interacts with transporters in the cell and that this association is important for the export of other natural products. Future investigations of this hypothesis as well as of the structure and function of type II peptidases will provide a complete account of the role of prodrug-activating peptidases in the activation and secretion of bacterial toxins.

The biogenesis of β-lactamase enzymes

The discovery of penicillin by Alexander Fleming marked a new era for modern medicine, allowing not only the treatment of infectious diseases, but also the safe performance of life-saving interventions, like surgery and chemotherapy. Unfortunately, resistance against penicillin, as well as more complex β-lactam antibiotics, has rapidly emerged since the introduction of these drugs in the clinic, and is largely driven by a single type of extra-cytoplasmic proteins, hydrolytic enzymes called β-lactamases. While the structures, biochemistry and epidemiology of these resistance determinants have been extensively characterized, their biogenesis, a complex process including multiple steps and involving several fundamental biochemical pathways, is rarely discussed. In this review, we provide a comprehensive overview of the journey of β-lactamases, from the moment they exit the ribosomal channel until they reach their final cellular destination as folded and active enzymes.

Functional Dynamics of Substrate Recognition in TEM Beta-Lactamase

The beta-lactamase enzyme provides effective resistance to beta-lactam antibiotics due to substrate recognition controlled by point mutations. Recently, extended-spectrum and inhibitor-resistant mutants have become a global health problem. Here, the functional dynamics that control substrate recognition in TEM beta-lactamase are investigated using all-atom molecular dynamics simulations. Comparisons are made between wild-type TEM-1 and TEM-2 and the extended-spectrum mutants TEM-10 and TEM-52, both in apo form and in complex with four different antibiotics (ampicillin, amoxicillin, cefotaxime and ceftazidime). Dynamic allostery is predicted based on a quasi-harmonic normal mode analysis using a perturbation scan. An allosteric mechanism known to inhibit enzymatic function in TEM beta-lactamase is identified, along with other allosteric binding targets. Mechanisms for substrate recognition are elucidated using multivariate comparative analysis of molecular dynamics trajectories to identify changes in dynamics resulting from point mutations and ligand binding, and the conserved dynamics, which are functionally important, are extracted as well. The results suggest that the H10-H11 loop (residues 214-221) is a secondary anchor for larger extended spectrum ligands, while the H9-H10 loop (residues 194-202) is distal from the active site and stabilizes the protein against structural changes. These secondary non-catalytically-active loops offer attractive targets for novel noncompetitive inhibitors of TEM beta-lactamase.

The Role of Hydrophobic Nodes in the Dynamics of Class A β-Lactamases

Class A β-lactamases are known for being able to rapidly gain broad spectrum catalytic efficiency against most β-lactamase inhibitor combinations as a result of elusively minor point mutations. The evolution in class A β-lactamases occurs through optimisation of their dynamic phenotypes at different timescales. At long-timescales, certain conformations are more catalytically permissive than others while at the short timescales, fine-grained optimisation of free energy barriers can improve efficiency in ligand processing by the active site. Free energy barriers, which define all coordinated movements, depend on the flexibility of the secondary structural elements. The most highly conserved residues in class A β-lactamases are hydrophobic nodes that stabilize the core. To assess how the stable hydrophobic core is linked to the structural dynamics of the active site, we carried out adaptively sampled molecular dynamics (MD) simulations in four representative class A β-lactamases (KPC-2, SME-1, TEM-1, and SHV-1). Using Markov State Models (MSM) and unsupervised deep learning, we show that the dynamics of the hydrophobic nodes is used as a metastable relay of kinetic information within the core and is coupled with the catalytically permissive conformation of the active site environment. Our results collectively demonstrate that the class A enzymes described here, share several important dynamic similarities and the hydrophobic nodes comprise of an informative set of dynamic variables in representative class A β-lactamases.

Inhibition of Class A β-Lactamase (TEM-1) by Narrow Fractions of Humic Substances

Antimicrobial resistance is a global threat. The use of biologically active natural products alone or in combination with the clinically proven antimicrobial agents might be a useful strategy to fight the resistance. The scientific hypotheses of this study were twofold: (1) the natural humic substances rich in dicarboxyl, phenolic, heteroaryl, and other fragments might possess inhibitory activity against β-lactamases, and (2) this inhibitory activity might be linked to the molecular composition of the humic ensemble. To test these hypotheses, we used humic substances (HS) from different sources (coal, peat, and soil) and of different fractional compositions (humic acids, hymatomelanic acids, and narrow fractions from solid-phase extraction) for inhibiting serine β-lactamase TEM-1. Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) was used to characterize the molecular composition of all humic materials used in this study. The kinetic assay with chromogenic substrate CENTA was used for assessment of inhibitory activity. The inhibition data have shown that among all humic materials tested, a distinct activity was observed within apolar fractions of hymatomelanic acid isolated from lignite. The decrease in the hydrolysis rate in the presence of most active fractions was 42% (with sulbactam-87%). Of particular importance is that these very fractions caused a synergistic effect (2-fold) for the combinations with sulbactam. Linking the observed inhibition effects to molecular composition revealed the preferential contribution of low-oxidized aromatic and acyclic components such as flavonoid-, lignin, and terpenoid-like molecules. The binding of single low-molecular-weight components to the cryptic allosteric site along with supramolecular interactions of humic aggregates with the protein surface could be considered as a major contributor to the observed inhibition. We believe that fine fractionation of hydrophobic humic materials along with molecular modeling studies on the interaction between humic molecules and β-lactamases might contribute to the development of novel β-lactamase inhibitors of humic nature.

Conserved residues Glu37 and Trp229 play an essential role in protein folding of β‐lactamase

Evolutionary robustness requires that the number of highly conserved amino acid residues in proteins is minimized. In enzymes, such conservation is observed for catalytic residues but also for some residues in the second shell or even further from the active site. β‐Lactamases evolve in response to changing antibiotic selection pressures and are thus expected to be evolutionarily robust, with a limited number of highly conserved amino acid residues. As part of the effort to understand the roles of conserved residues in class A β‐lactamases, we investigate the reasons leading to the conservation of two amino acid residues in the β‐lactamase BlaC, Glu37, and Trp229. Using site‐directed mutagenesis, we have generated point mutations of these residues and observed a drastic decrease in the levels of soluble protein produced in Escherichia coli, thus abolishing completely the resistance of bacteria against β‐lactam antibiotics. However, the purified proteins are structurally and kinetically very similar to the wild‐type enzyme, only differing by exhibiting a slightly lower melting temperature. We conclude that conservation of Glu37 and Trp229 is solely caused by an essential role in the folding process, and we propose that during folding Glu37 primes the formation of the central β‐sheet and Trp229 contributes to the hydrophobic collapse into a molten globule.

Prediction of Function Determining and Buried Residues Through Analysis of Saturation Mutagenesis Datasets

Mutational scanning can be used to probe effects of large numbers of point mutations on protein function. Positions affected by mutation are primarily at either buried or at exposed residues directly involved in function, hereafter designated as active-site residues. In the absence of prior structural information, it has not been easy to distinguish between these two categories of residues. We curated and analyzed a set of twelve published deep mutational scanning datasets. The analysis revealed differential patterns of mutational sensitivity and substitution preferences at buried and exposed positions. Prediction of buried-sites solely from the mutational sensitivity data was facilitated by incorporating predicted sequence-based accessibility values. For active-site residues we observed mean sensitivity, specificity and accuracy of 61, 90 and 88% respectively. For buried residues the corresponding figures were 59, 90 and 84% while for exposed non active-site residues these were 98, 44 and 82% respectively. We also identified positions which did not follow these general trends and might require further experimental re-validation. This analysis highlights the ability of deep mutational scans to provide important structural and functional insights, even in the absence of three-dimensional structures determined using conventional structure determination techniques, and also discuss some limitations of the methodology.

Toward Developing Intuitive Rules for Protein Variant Effect Prediction Using Deep Mutational Scanning Data

Protein structure and function can be severely altered by even a single amino acid mutation. Predictions of mutational effects using extensive artificial intelligence (AI)-based models, although accurate, remain as enigmatic as the experimental observations in terms of improving intuitions about the contributions of various factors. Inspired by Lipinski's rules for drug-likeness, we devise simple thresholding criteria on five different descriptors such as conservation, which have so far been limited to qualitative interpretations such as high conservation implies high mutational effect. We analyze systematic deep mutational scanning data of all possible single amino acid substitutions on seven proteins (25153 mutations) to first define these thresholds and then to evaluate the scope and limits of the predictions. At this stage, the approach allows us to comment easily and with a low error rate on the subset of mutations classified as neutral or deleterious by all of the descriptors. We hope that complementary to the accurate AI predictions, these thresholding rules or their subsequent modifications will serve the purpose of codifying the knowledge about the effects of mutations.

Can We Exploit β-Lactamases Intrinsic Dynamics for Designing More Effective Inhibitors?

β-lactamases (BLs) represent the most frequent cause of antimicrobial resistance in Gram-negative bacteria. Despite the continuous efforts in the development of BL inhibitors (BLIs), new BLs able to hydrolyze the last developed antibiotics rapidly emerge. Moreover, the insurgence rate of effective mutations is far higher than the release of BLIs able to counteract them. This results in a shortage of antibiotics that is menacing the effective treating of infectious diseases. The situation is made even worse by the co-expression in bacteria of BLs with different mechanisms and hydrolysis spectra, and by the lack of inhibitors able to hit them all. Differently from other targets, BL flexibility has not been deeply exploited for drug design, possibly because of the small protein size, for their apparent rigidity and their high fold conservation. In this mini-review, we discuss the evidence for BL binding site dynamics being crucial for catalytic efficiency, mutation effect, and for the design of new inhibitors. Then, we report on identified allosteric sites in BLs and on possible allosteric inhibitors, as a strategy to overcome the frequent occurrence of mutations in BLs and the difficulty of competing efficaciously with substrates. Nevertheless, allosteric inhibitors could work synergistically with traditional inhibitors, increasing the chances of restoring bacterial susceptibility towards available antibiotics.

Conformational Dynamics of the Helix 10 Region as an Allosteric Site in Class A β-Lactamase Inhibitory Binding

β-Lactamase inhibitory protein (BLIP) can effectively inactivate class A β-lactamases, but with very different degrees of potency. Understanding the different roles of BLIP in class A β-lactamases inhibition can provide insights for inhibitor design. However, this problem was poorly solved on the basis of the static structures obtained by X-ray crystallography. In this work, ion mobility mass spectrometry, hydrogen-deuterium exchange mass spectrometry, and molecular dynamics simulation revealed the conformational dynamics of three class A β-lactamases with varying inhibition efficiencies by BLIP. A more extended conformation of PC1 was shown compared to those of TEM1 and SHV1. Localized dynamics differed in several important loop regions, that is, the protruding loop, H10 loop, Ω loop, and SDN loop. Upon binding with BLIP, these loops cooperatively rearranged to enhance the binding interface and to inactivate the catalytic sites. In particular, unfavorable changes in conformational dynamics were found in the protruding loop of SHV1 and PC1, showing less effective binding. Intriguingly, the single mutation on BLIP could compensate for the unfavored changes in this region, and thus exhibit enhanced inhibition toward SHV1 and PC1. Additionally, the H10 region was revealed as an important allosteric site that could modulate the inhibition of class A β-lactamases. It was suggested that the rigid protruding loop and flexible H10 region might be determinants for the effective inhibition of TEM1. Our findings provided unique and explicit insights into the conformational dynamics of β-lactamases and their bindings with BLIP. This work can be extended to other β-lactamases of interest and inspire the design of novel inhibitors.

Machine Learning Classification Model for Functional Binding Modes of TEM-1 β-Lactamase

TEM family of enzymes is one of the most commonly encountered β-lactamases groups with different catalytic capabilities against various antibiotics. Despite the studies investigating the catalytic mechanism of TEM β-lactamases, the binding modes of these enzymes against ligands in different functional catalytic states have been largely overlooked. But the binding modes may play a critical role in the function and even the evolution of these proteins. In this work, a newly developed machine learning analysis approach to the recognition of protein dynamics states was applied to compare the binding modes of TEM-1 β-lactamase with regard to penicillin in different catalytic states. While conventional analysis methods, including principal components analysis (PCA), could not differentiate TEM-1 in different binding modes, the application of a machine learning method led to excellent classification models differentiating these states. It was also revealed that both reactant/product states and apo/product states are more differentiable than the apo/reactant states. The feature importance generated by the training procedure of the machine learning model was utilized to evaluate the contribution from residues at active sites and in different secondary structures. Key active site residues, Ser70 and Ser130, play a critical role in differentiating reactant/product states, while other active site residues are more important for differentiating apo/product states. Overall, this study provides new insights into the different dynamical function states of TEM-1 and may open a new venue for β-lactamases functional and evolutional studies in general.

Targeting a hidden site on class A beta-lactamases

Increasing resistance against available orthosteric beta-lactamase inhibitors necessitates the search for novel and powerful inhibitor molecules. In this respect, allosteric inhibitors serve as attractive alternatives. Here, we examine the structural basis of inhibition in a hidden, druggable pocket in TEM-1 beta-lactamase. Based on crystallographic evidence that 6-cyclohexyl-1-hexyl-β-D-maltoside (CYMAL-6) binds to this site, first we determined the kinetic mechanism of inhibition by CYMAL-6. Activity measurements with CYMAL-6 showed that it competitively inhibits the wild type enzyme. Interestingly, it exhibits a steep dose-response curve with an IC50 of 100 μM. The IC50 value changes neither with different enzyme concentration nor with incubation of the enzyme with the inhibitor, showing that inhibition is not aggregation-based. The presence of the same concentrations of CYMAL-6 does not influence the activity of lactate dehydrogenase, further confirming the specificity of CYMAL-6 for TEM-1 beta-lactamase. Then, we identified compounds with high affinity to this allosteric site by virtual screening using Glide and Schrödinger Suite. Virtual screening performed with 500,000 drug like compounds from the ZINC database showed that top scoring compounds interact with the hydrophobic pocket that forms between H10 and H11 helices and with the catalytically important Arg244 residue through pi-cation interactions. Discovery of novel chemical scaffolds that target this allosteric site will pave the way for a new avenue in the design of new antimicrobials.