High tolerance to simultaneous active-site mutations in TEM-1 beta-lactamase: Distinct mutational paths provide more generalized beta-lactam recognition

Restricted Rotational Flexibility of the C5α-Methyl-Substituted Carbapenem NA-1-157 Leads to Potent Inhibition of the GES-5 Carbapenemase

Carbapenem antibiotics are used as a last-resort treatment for infections caused by multidrug-resistant bacteria. The wide spread of carbapenemases in Gram-negative bacteria has severely compromised the utility of these drugs and represents a serious public health threat. To combat carbapenemase-mediated resistance, new antimicrobials and inhibitors of these enzymes are urgently needed. Here, we describe the interaction of the atypically C5α-methyl-substituted carbapenem, NA-1-157, with the GES-5 carbapenemase. MICs of this compound against Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii producing the enzyme were reduced 4-16-fold when compared to MICs of the commercial carbapenems, reaching clinically sensitive breakpoints. When NA-1-157 was combined with meropenem, a strong synergistic effect was observed. Kinetic and ESI-LC/MS studies demonstrated that NA-1-157 is a potent inhibitor of GES-5, with a high inactivation efficiency of (2.9 ± 0.9) × 105 M-1 s-1. Acylation of GES-5 by NA-1-157 was biphasic, with the fast phase completing within seconds, and the slow phase taking several hours and likely proceeding through a reversible tetrahedral intermediate. Deacylation was extremely slow (k3 = (2.4 ± 0.3) × 10-7 s-1), resulting in a residence time of 48 ± 6 days. MD simulation of the GES-5-meropenem and GES-5-NA-1-157 acyl-enzyme complexes revealed that the C5α-methyl group in NA-1-157 sterically restricts rotation of the 6α-hydroxyethyl group preventing ingress of the deacylating water into the vicinity of the scissile bond of the acyl-enzyme intermediate. These data demonstrate that NA-1-157 is a potent irreversible inhibitor of the GES-5 carbapenemase.

Blanket antimicrobial resistance gene database with structural information, BOARDS, provides insights on historical landscape of resistance prevalence and effects of mutations in enzyme structure

Antimicrobial resistance (AMR) in pathogenic bacteria poses a significant threat to public health, yet there is still a need for development in the tools to deeply understand AMR genes based on genetic or structural information. In this study, we present an interactive web database named Blanket Overarching Antimicrobial-Resistance gene Database with Structural information (BOARDS, sbml.unist.ac.kr), a database that comprehensively includes 3,943 reported AMR gene information for 1,997 extended spectrum beta-lactamase (ESBL) and 1,946 other genes as well as a total of 27,395 predicted protein structures. These structures, which include both wild-type AMR genes and their mutants, were derived from 80,094 publicly available whole-genome sequences. In addition, we developed the rapid analysis and detection tool of antimicrobial-resistance (RADAR), a one-stop analysis pipeline to detect AMR genes across whole-genome sequencing (WGSs). By integrating BOARDS and RADAR, the AMR prevalence landscape for eight multi-drug resistant pathogens was reconstructed, leading to unexpected findings such as the pre-existence of the MCR genes before their official reports. Enzymatic structure prediction-based analysis revealed that the occurrence of mutations found in some ESBL genes was found to be closely related to the binding affinities with their antibiotic substrates. Overall, BOARDS can play a significant role in performing in-depth analysis on AMR.IMPORTANCEWhile the increasing antibiotic resistance (AMR) in pathogen has been a burden on public health, effective tools for deep understanding of AMR based on genetic or structural information remain limited. In this study, a blanket overarching antimicrobial-resistance gene database with structure information (BOARDS)-a web-based database that comprehensively collected AMR gene data with predictive protein structural information was constructed. Additionally, we report the development of a RADAR pipeline that can analyze whole-genome sequences as well. BOARDS, which includes sequence and structural information, has shown the historical landscape and prevalence of the AMR genes and can provide insight into single-nucleotide polymorphism effects on antibiotic degrading enzymes within protein structures.

Natural variants modify Klebsiella pneumoniae carbapenemase (KPC) acyl-enzyme conformational dynamics to extend antibiotic resistance

Class A serine β-lactamases (SBLs) are key antibiotic resistance determinants in Gram-negative bacteria. SBLs neutralize β-lactams via a hydrolytically labile covalent acyl-enzyme intermediate. Klebsiella pneumoniae carbapenemase (KPC) is a widespread SBL that hydrolyzes carbapenems, the most potent β-lactams; known KPC variants differ in turnover of expanded-spectrum oxyimino-cephalosporins (ESOCs), for example, cefotaxime and ceftazidime. Here, we compare ESOC hydrolysis by the parent enzyme KPC-2 and its clinically observed double variant (P104R/V240G) KPC-4. Kinetic analyses show that KPC-2 hydrolyzes cefotaxime more efficiently than the bulkier ceftazidime, with improved ESOC turnover by KPC-4 resulting from enhanced turnover (kcat), rather than altered KM values. High-resolution crystal structures of ESOC acyl-enzyme complexes with deacylation-deficient (E166Q) KPC-2 and KPC-4 mutants show that ceftazidime acylation causes rearrangement of three loops; the Ω, 240, and 270 loops, which border the active site. However, these rearrangements are less pronounced in the KPC-4 than the KPC-2 ceftazidime acyl-enzyme and are not observed in the KPC-2:cefotaxime acyl-enzyme. Molecular dynamics simulations of KPC:ceftazidime acyl-enyzmes reveal that the deacylation general base E166, located on the Ω loop, adopts two distinct conformations in KPC-2, either pointing "in" or "out" of the active site; with only the "in" form compatible with deacylation. The "out" conformation was not sampled in the KPC-4 acyl-enzyme, indicating that efficient ESOC breakdown is dependent upon the ordering and conformation of the KPC Ω loop. The results explain how point mutations expand the activity spectrum of the clinically important KPC SBLs to include ESOCs through their effects on the conformational dynamics of the acyl-enzyme intermediate.

Pareto Optimization of Combinatorial Mutagenesis Libraries

In order to increase the hit rate of discovering diverse, beneficial protein variants via high-throughput screening, we have developed a computational method to optimize combinatorial mutagenesis libraries for overall enrichment in two distinct properties of interest. Given scoring functions for evaluating individual variants, POCoM (Pareto Optimal Combinatorial Mutagenesis) scores entire libraries in terms of averages over their constituent members, and designs optimal libraries as sets of mutations whose combinations make the best trade-offs between average scores. This represents the first general-purpose method to directly design combinatorial libraries for multiple objectives characterizing their constituent members. Despite being rigorous in mapping out the Pareto frontier, it is also very fast even for very large libraries (e.g., designing 30 mutation, billion-member libraries in only hours). We here instantiate POCoM with scores based on a target's protein structure and its homologs' sequences, enabling the design of libraries containing variants balancing these two important yet quite different types of information. We demonstrate POCoM's generality and power in case study applications to green fluorescent protein, cytochrome P450, and β-lactamase. Analysis of the POCoM library designs provides insights into the trade-offs between structure- and sequence-based scores, as well as the impacts of experimental constraints on library designs. POCoM libraries incorporate mutations that have previously been found favorable experimentally, while diversifying the contexts in which these mutations are situated and maintaining overall variant quality.

Advances in NMR Methods To Map Allosteric Sites: From Models to Translation

The last five years have witnessed major developments in the understanding of the allosteric phenomenon, broadly defined as coupling between remote molecular sites. Such advances have been driven not only by new theoretical models and pharmacological applications of allostery, but also by progress in the experimental approaches designed to map allosteric sites and transitions. Among these techniques, NMR spectroscopy has played a major role given its unique near-atomic resolution and sensitivity to the dynamics that underlie allosteric couplings. Here, we highlight recent progress in the NMR methods tailored to investigate allostery with the goal of offering an overview of which NMR approaches are best suited for which allosterically relevant questions. The picture of the allosteric "NMR toolbox" is provided starting from one of the simplest models of allostery (i.e., the four-state thermodynamic cycle) and continuing to more complex multistate mechanisms. We also review how such an "NMR toolbox" has assisted the elucidation of the allosteric molecular basis for disease-related mutations and the discovery of novel leads for allosteric drugs. From this overview, it is clear that NMR plays a central role not only in experimentally validating transformative theories of allostery, but also in tapping the full translational potential of allosteric systems.

Structure-based design of combinatorial mutagenesis libraries

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high-throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general-purpose method, called "Structure-based Optimization of Combinatorial Mutagenesis" (SOCoM), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library-averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β-lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure-based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large-scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure-based assessments, such as the energy gap between alternative conformational or bound states.

Combinatorial active-site variants confer sustained clavulanate resistance in BlaC β-lactamase from Mycobacterium tuberculosis

Bacterial resistance to β-lactam antibiotics is a global issue threatening the success of infectious disease treatments worldwide. Mycobacterium tuberculosis has been particularly resilient to β-lactam treatment, primarily due to the chromosomally encoded BlaC β-lactamase, a broad-spectrum hydrolase that renders ineffective the vast majority of relevant β-lactam compounds currently in use. Recent laboratory and clinical studies have nevertheless shown that specific β-lactam-BlaC inhibitor combinations can be used to inhibit the growth of extensively drug-resistant strains of M. tuberculosis, effectively offering new tools for combined treatment regimens against resistant strains. In the present work, we performed combinatorial active-site replacements in BlaC to demonstrate that specific inhibitor-resistant (IRT) substitutions at positions 69, 130, 220, and/or 234 can act synergistically to yield active-site variants with several thousand fold greater in vitro resistance to clavulanate, the most common clinical β-lactamase inhibitor. While most single and double variants remain sensitive to clavulanate, double mutants R220S-K234R and S130G-K234R are substantially less affected by time-dependent clavulanate inactivation, showing residual β-lactam hydrolytic activities of 46% and 83% after 24 h incubation with a clinically relevant inhibitor concentration (5 μg/ml, 25 µM). These results demonstrate that active-site alterations in BlaC yield resistant variants that remain active and stable over prolonged bacterial generation times compatible with mycobacterial proliferation. These results also emphasize the formidable adaptive potential of inhibitor-resistant substitutions in β-lactamases, potentially casting a shadow on specific β-lactam-BlaC inhibitor combination treatments against M. tuberculosis.

Screening of inhibitors for S130G inhibitor resistant mutants of TEM type beta-lactamase

Bacteria are remarkably adaptable organisms that acquire an almost limitless competence to survive under unpleasant conditions. The drastic emergence of antibiotic resistance among β-Lactamases is the most serious threat to hospitals and nosocomial settings. β-lactam inhibitors came into existence in order to overcome the problem of antibibiotic resistance in bacteria. The emergence of inhibitor resistant mutants has raised the alarms. In this study we have used structured based virtual screening approach and have screened out some inhibitors against S130G TEM mutant. All the compounds were tested in presence and absence of conserved active site water molecules. These compounds were found be showing much higher efficacy than known β-lactamase inhibitors. Amino acids G130, S70, N132, G130, Y105 and V216 were found crucial for the interaction of inhibitors within the active site.