QM/MM simulations as an assay for carbapenemase activity in class A β-lactamases

Aromatic Diboronic Acids as Effective KPC/AmpC Inhibitors

Over 30 compounds, including para-, meta-, and ortho-phenylenediboronic acids, ortho-substituted phenylboronic acids, benzenetriboronic acids, di- and triboronated thiophenes, and pyridine derivatives were investigated as potential β-lactamase inhibitors. The highest activity against KPC-type carbapenemases was found for ortho-phenylenediboronic acid 3a, which at the concentration of 8/4 mg/L reduced carbapenems' MICs up to 16/8-fold, respectively. Checkerboard assays revealed strong synergy between carbapenems and 3a with the fractional inhibitory concentrations indices of 0.1-0.32. The nitrocefin hydrolysis test and the whole cell assay with E. coli DH5α transformant carrying blaKPC-3 proved KPC enzyme being its molecular target. para-Phenylenediboronic acids efficiently potentiated carbapenems against KPC-producers and ceftazidime against AmpC-producers, whereas meta-phenylenediboronic acids enhanced only ceftazidime activity against the latter ones. Finally, the statistical analysis confirmed that ortho-phenylenediboronic acids act synergistically with carbapenems significantly stronger than other groups. Since the obtained phenylenediboronic compounds are not toxic to MRC-5 human fibroblasts at the tested concentrations, they can be considered promising scaffolds for the future development of novel KPC/AmpC inhibitors. The complexation of KPC-2 with the most representative isomeric phenylenediboronic acids 1a, 2a, and 3a was modeled by quantum mechanics/molecular mechanics calculations. Compound 3a reached the most effective configuration enabling covalent binding to the catalytic Ser70 residue.

Tautomer-Specific Deacylation and Ω-Loop Flexibility Explain the Carbapenem-Hydrolyzing Broad-Spectrum Activity of the KPC-2 β-Lactamase

KPC-2 (Klebsiella pneumoniae carbapenemase-2) is a globally disseminated serine-β-lactamase (SBL) responsible for extensive β-lactam antibiotic resistance in Gram-negative pathogens. SBLs inactivate β-lactams via a mechanism involving a hydrolytically labile covalent acyl-enzyme intermediate. Carbapenems, the most potent β-lactams, evade the activity of many SBLs by forming long-lived inhibitory acyl-enzymes; however, carbapenemases such as KPC-2 efficiently deacylate carbapenem acyl-enzymes. We present high-resolution (1.25-1.4 Å) crystal structures of KPC-2 acyl-enzymes with representative penicillins (ampicillin), cephalosporins (cefalothin), and carbapenems (imipenem, meropenem, and ertapenem) obtained utilizing an isosteric deacylation-deficient mutant (E166Q). The mobility of the Ω-loop (residues 165-170) negatively correlates with antibiotic turnover rates (kcat), highlighting the role of this region in positioning catalytic residues for efficient hydrolysis of different β-lactams. Carbapenem-derived acyl-enzyme structures reveal the predominance of the Δ1-(2R) imine rather than the Δ2 enamine tautomer. Quantum mechanics/molecular mechanics molecular dynamics simulations of KPC-2:meropenem acyl-enzyme deacylation used an adaptive string method to differentiate the reactivity of the two isomers. These identify the Δ1-(2R) isomer as having a significantly (7 kcal/mol) higher barrier than the Δ2 tautomer for the (rate-determining) formation of the tetrahedral deacylation intermediate. Deacylation is therefore likely to proceed predominantly from the Δ2, rather than the Δ1-(2R) acyl-enzyme, facilitated by tautomer-specific differences in hydrogen-bonding networks involving the carbapenem C-3 carboxylate and the deacylating water and stabilization by protonated N-4, accumulating a negative charge on the Δ2 enamine-derived oxyanion. Taken together, our data show how the flexible Ω-loop helps confer broad-spectrum activity upon KPC-2, while carbapenemase activity stems from efficient deacylation of the Δ2-enamine acyl-enzyme tautomer.

Unveiling the structural features that regulate carbapenem deacylation in KPC-2 through QM/MM and interpretable machine learning

Resistance to carbapenem β-lactams presents major clinical and economical challenges for the treatment of pathogen infections. The fast hydrolysis of carbapenems by carbapenemase-producing bacterial strains enables the effective deactivation of carbapenem antibiotics. In this study, we aim to unravel the structural features that distinguish the notable deacylation activity of carbapenemases. The deacylation reactions between imipenem (IPM) and the KPC-2 class A serine-based β-lactamases (ASβLs) are modeled with combined quantum mechanical/molecular mechanical (QM/MM) minimum energy pathway (MEP) calculations and interpretable machine-learning (ML) methods. We first applied a dual-level computational protocol to achieve fast sampling of QM/MM MEPs. A tree-based ensemble ML model was employed to learn the MEP activation barriers from the conformational features of the KPC-2/IPM active site. The barrier-predicting model was then unboxed using the Shapley additive explanation (SHAP) importance attribution methods to derive mechanistic insights, which were also verified by additional QM/MM wavefunction analysis. Essentially, we show that potential hydrogen bonding interactions of the general base and the tautomerization states of the carbapenem pyrroline ring could concertedly regulate the activation barrier of KPC-2/IPM deacylation. Nonetheless, we demonstrate the efficacy of interpretable ML to assist the analysis of QM/MM simulation data for robust extraction of human-interpretable mechanistic insights.

QM/MM Simulations Reveal the Determinants of Carbapenemase Activity in Class A β-Lactamases

β-lactam antibiotic resistance in Gram-negative bacteria, primarily caused by β-lactamase enzymes that hydrolyze the β-lactam ring, has become a serious clinical problem. Carbapenems were formerly considered "last resort" antibiotics because they escaped breakdown by most β-lactamases, due to slow deacylation of the acyl-enzyme intermediate. However, an increasing number of Gram-negative bacteria now produce β-lactamases with carbapenemase activity: these efficiently hydrolyze the carbapenem β-lactam ring, severely limiting the treatment of some bacterial infections. Here, we use quantum mechanics/molecular mechanics (QM/MM) simulations of the deacylation reactions of acyl-enzyme complexes of eight β-lactamases of class A (the most widely distributed β-lactamase group) with the carbapenem meropenem to investigate differences between those inhibited by carbapenems (TEM-1, SHV-1, BlaC, and CTX-M-16) and those that hydrolyze them (SFC-1, KPC-2, NMC-A, and SME-1). QM/MM molecular dynamics simulations confirm the two enzyme groups to differ in the preferred acyl-enzyme orientation: carbapenem-inhibited enzymes favor hydrogen bonding of the carbapenem hydroxyethyl group to deacylating water (DW). QM/MM simulations of deacylation give activation free energies in good agreement with experimental hydrolysis rates, correctly distinguishing carbapenemases. For the carbapenem-inhibited enzymes, free energies for deacylation are significantly higher than for the carbapenemases, even when the hydroxyethyl group was restrained to prevent interaction with the DW. Analysis of these simulations, and additional simulations of mutant enzymes, shows how factors including the hydroxyethyl orientation, the active site volume, and architecture (conformations of Asn170 and Asn132; organization of the oxyanion hole; and the Cys69-Cys238 disulfide bond) collectively determine catalytic efficiency toward carbapenems.

Mechanistic Modeling of Monoglyceride Lipase Covalent Modification Elucidates the Role of Leaving Group Expulsion and Discriminates Inhibitors with High and Low Potency

Inhibition of monoglyceride lipase (MGL), also known as monoacylglycerol lipase (MAGL), has emerged as a promising approach for treating neurological diseases. To gain useful insights in the design of agents with balanced potency and reactivity, we investigated the mechanism of MGL carbamoylation by the reference triazole urea SAR629 (IC₅₀ = 0.2 nM) and two recently described inhibitors featuring a pyrazole (IC₅₀ = 1800 nM) or a 4-cyanopyrazole (IC₅₀ = 8 nM) leaving group (LG), using a hybrid quantum mechanics/molecular mechanics (QM/MM) approach. Opposite to what was found for substrate 2-arachidonoyl-sn-glycerol (2-AG), covalent modification of MGL by azole ureas is controlled by LG expulsion. Simulations indicated that changes in the electronic structure of the LG greatly affect reaction energetics with triazole and 4-cyanopyrazole inhibitors following a more accessible carbamoylation path compared to the unsubstituted pyrazole derivative. The computational protocol provided reaction barriers able to discriminate between MGL inhibitors with different potencies. These results highlight how QM/MM simulations can contribute to elucidating structure–activity relationships and provide insights for the design of covalent inhibitors.

Multiscale Simulations Identify Origins of Differential Carbapenem Hydrolysis by the OXA-48 β-Lactamase

OXA-48 β-lactamases are frequently encountered in bacterial infections caused by carbapenem-resistant Gram-negative bacteria. Due to the importance of carbapenems in the treatment of healthcare-associated infections and the increasingly wide dissemination of OXA-48-like enzymes on plasmids, these β-lactamases are of high clinical significance. Notably, OXA-48 hydrolyzes imipenem more efficiently than other commonly used carbapenems, such as meropenem. Here, we use extensive multiscale simulations of imipenem and meropenem hydrolysis by OXA-48 to dissect the dynamics and to explore differences in the reactivity of the possible conformational substates of the respective acylenzymes. Quantum mechanics/molecular mechanics (QM/MM) simulations of the deacylation reaction for both substrates demonstrate that deacylation is favored when the 6α-hydroxyethyl group is able to hydrogen bond to the water molecule responsible for deacylation but disfavored by the increasing hydration of either oxygen of the carboxylated Lys73 general base. Differences in free energy barriers calculated from the QM/MM simulations correlate well with the experimentally observed differences in hydrolytic efficiency between meropenem and imipenem. We conclude that the impaired breakdown of meropenem, compared to imipenem, which arises from a subtle change in the hydrogen bonding pattern between the deacylating water molecule and the antibiotic, is most likely induced by the meropenem 1β-methyl group. In addition to increased insights into carbapenem breakdown by OXA β-lactamases, which may aid in future efforts to design antibiotics or inhibitors, our approach exemplifies the combined use of atomistic simulations in determining the possible different enzyme-substrate substates and their influence on enzyme reaction kinetics.

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.

Exploring Covalent Docking Mechanisms of Boron-Based Inhibitors to Class A, C and D β-Lactamases Using Time-dependent Hybrid QM/MM Simulations

Recently, molecular covalent docking has been extensively developed to design new classes of inhibitors that form chemical bonds with their biological targets. This strategy for the design of such inhibitors, in particular boron-based inhibitors, holds great promise for the vast family of β-lactamases produced, inter alia, by Gram-negative antibiotic-resistant bacteria. However, the description of covalent docking processes requires a quantum-mechanical approach, and so far, only a few studies of this type have been presented. This study accurately describes the covalent docking process between two model inhibitors - representing two large families of inhibitors based on boronic-acid and bicyclic boronate scaffolds, and three β-lactamases which belong to the A, C, and D classes. Molecular fragments containing boron can be converted from a neutral, trigonal, planar state with sp2 hybridization to the anionic, tetrahedral sp3 state in a process sometimes referred to as morphing. This study applies multi-scale modeling methods, in particular, the hybrid QM/MM approach which has predictive power reaching well beyond conventional molecular modeling. Time-dependent QM/MM simulations indicated several structural changes and geometric preferences, ultimately leading to covalent docking processes. With current computing technologies, this approach is not computationally expensive, can be used in standard molecular modeling and molecular design works, and can effectively support experimental research which should allow for a detailed understanding of complex processes important to molecular medicine. In particular, it can support the rational design of covalent boron-based inhibitors for β-lactamases as well as for many other enzyme systems of clinical relevance, including SARS-CoV-2 proteins.

Allosteric communication in class A β-lactamases occurs via cooperative coupling of loop dynamics

Understanding allostery in enzymes and tools to identify it offer promising alternative strategies to inhibitor development. Through a combination of equilibrium and nonequilibrium molecular dynamics simulations, we identify allosteric effects and communication pathways in two prototypical class A β-lactamases, TEM-1 and KPC-2, which are important determinants of antibiotic resistance. The nonequilibrium simulations reveal pathways of communication operating over distances of 30 Å or more. Propagation of the signal occurs through cooperative coupling of loop dynamics. Notably, 50% or more of clinically relevant amino acid substitutions map onto the identified signal transduction pathways. This suggests that clinically important variation may affect, or be driven by, differences in allosteric behavior, providing a mechanism by which amino acid substitutions may affect the relationship between spectrum of activity, catalytic turnover, and potential allosteric behavior in this clinically important enzyme family. Simulations of the type presented here will help in identifying and analyzing such differences.

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.

Benchmarking quantum mechanical methods for calculating reaction energies of reactions catalyzed by enzymes

To assess the accuracy of different quantum mechanical methods for biochemical modeling, the reaction energies of 20 small model reactions (chosen to represent chemical steps catalyzed by commonly studied enzymes) were calculated. The methods tested included several popular Density Functional Theory (DFT) functionals, second-order Møller Plesset perturbation theory (MP2) and its spin-component scaled variant (SCS-MP2), and coupled cluster singles and doubles and perturbative triples (CCSD(T)). Different basis sets were tested. CCSD(T)/aug-cc-pVTZ results for all 20 reactions were used to benchmark the other methods. It was found that MP2 and SCS-MP2 reaction energy calculation results are similar in quality to CCSD(T) (mean absolute error (MAE) of 1.2 and 1.3 kcal mol−1, respectively). MP2 calculations gave a large error in one case, and are more subject to basis set effects, so in general SCS-MP2 calculations are a good choice when CCSD(T) calculations are not feasible. Results with different DFT functionals were of reasonably good quality (MAEs of 2.5–5.1 kcal mol−1), whereas popular semi-empirical methods (AM1, PM3, SCC-DFTB) gave much larger errors (MAEs of 11.6–14.6 kcal mol−1). These results should be useful in guiding methodological choices and assessing the accuracy of QM/MM calculations on enzyme-catalyzed reactions.

Design and SAR Analysis of Covalent Inhibitors Driven by Hybrid QM/MM Simulations

Quantum mechanics/molecular mechanics (QM/MM) hybrid technique is emerging as a reliable computational method to investigate and characterize chemical reactions occurring in enzymes. From a drug discovery perspective, a thorough understanding of enzyme catalysis appears pivotal to assist the design of inhibitors able to covalently bind one of the residues belonging to the enzyme catalytic machinery. Thanks to the current advances in computer power, and the availability of more efficient algorithms for QM-based simulations, the use of QM/MM methodology is becoming a viable option in the field of covalent inhibitor design. In the present review, we summarized our experience in the field of QM/MM simulations applied to drug design problems which involved the optimization of agents working on two well-known drug targets, namely fatty acid amide hydrolase (FAAH) and epidermal growth factor receptor (EGFR). In this context, QM/MM simulations gave valuable information in terms of geometry (i.e., of transition states and metastable intermediates) and reaction energetics that allowed to correctly predict inhibitor binding orientation and substituent effect on enzyme inhibition. What is more, enzyme reaction modelling with QM/MM provided insights that were translated into the synthesis of new covalent inhibitor featured by a unique combination of intrinsic reactivity, on-target activity, and selectivity.

An Efficient Computational Assay for β-Lactam Antibiotic Breakdown by Class A β-Lactamases

Class A β-lactamases cause clinically relevant resistance to β-lactam antibiotics. Carbapenem degradation is a particular concern. We present an efficient QM/MM molecular simulation protocol that accurately predicts the activity of β-lactamases against carbapenems. Simulations take less than 24 CPU hours, a greater than 99% reduction, and do not require fitting against experimental data or significant parametrization. This computational assay also reveals mechanistic details of β-lactam breakdown and should assist in evaluating emerging β-lactamase variants and developing new antibiotics.

β-Lactamases and β-Lactamase Inhibitors in the 21st Century

The β-lactams retain a central place in the antibacterial armamentarium. In Gram-negative bacteria, β-lactamase enzymes that hydrolyze the amide bond of the four-membered β-lactam ring are the primary resistance mechanism, with multiple enzymes disseminating on mobile genetic elements across opportunistic pathogens such as Enterobacteriaceae (e.g., Escherichia coli) and non-fermenting organisms (e.g., Pseudomonas aeruginosa). β-Lactamases divide into four classes; the active-site serine β-lactamases (classes A, C and D) and the zinc-dependent or metallo-β-lactamases (MBLs; class B). Here we review recent advances in mechanistic understanding of each class, focusing upon how growing numbers of crystal structures, in particular for β-lactam complexes, and methods such as neutron diffraction and molecular simulations, have improved understanding of the biochemistry of β-lactam breakdown. A second focus is β-lactamase interactions with carbapenems, as carbapenem-resistant bacteria are of grave clinical concern and carbapenem-hydrolyzing enzymes such as KPC (class A) NDM (class B) and OXA-48 (class D) are proliferating worldwide. An overview is provided of the changing landscape of β-lactamase inhibitors, exemplified by the introduction to the clinic of combinations of β-lactams with diazabicyclooctanone and cyclic boronate serine β-lactamase inhibitors, and of progress and strategies toward clinically useful MBL inhibitors. Despite the long history of β-lactamase research, we contend that issues including continuing unresolved questions around mechanism; opportunities afforded by new technologies such as serial femtosecond crystallography; the need for new inhibitors, particularly for MBLs; the likely impact of new β-lactam:inhibitor combinations and the continuing clinical importance of β-lactams mean that this remains a rewarding research area.

The Driving Force for the Acylation of β-Lactam Antibiotics by L,D-Transpeptidase 2: Quantum Mechanics/Molecular Mechanics (QM/MM) Study

β-lactam antibiotics, which are used to treat infectious diseases, are currently the most widely used class of antibiotics. This study focused on the chemical reactivity of five- and six-membered ring systems attached to the β-lactam ring. The ring strain energy (RSE), force constant (FC) of amide (C-N), acylation transition states and second-order perturbation stabilization energies of 13 basic structural units of β-lactam derivatives were computed using the M06-2X and G3/B3LYP multistep method. In the ring strain calculations, an isodesmic reaction scheme was used to obtain the total energies. RSE is relatively greater in the five-(1a-2c) compared to the six-membered ring systems except for 4b, which gives a RSE that is comparable to five-membered ring lactams. These variations were also observed in the calculated inter-atomic amide bond distances (C-N), which is why the six-membered ring lactams C-N bond are more rigid than those with five-membered ring lactams. The calculated ΔG^# values from the acylation reaction of the lactams (involving the S-H group of the cysteine active residue from L,D transpeptidase 2) revealed a faster rate of C-N cleavage in the five-membered ring lactams especially in the 1-2 derivatives (17.58 kcal mol^-1 ). This observation is also reflected in the calculated amide bond force constant (1.26 mDyn/A) indicating a weaker bond strength, suggesting that electronic factors (electron delocalization) play more of a role on reactivity of the β-lactam ring, than ring strain.

Quantum Mechanics/Molecular Mechanics (QM/MM) Calculations Support a Concerted Reaction Mechanism for the Zika Virus NS2B/NS3 Serine Protease with Its Substrate

Zika virus (ZIKV) is mainly transmitted to humans by Aedes species mosquitoes and is associated with serious pathological disorders including microcephaly in newborns and Guillain-Barré syndrome in adults. Currently, there is no vaccine or anti-ZIKV drug available for preventing or controlling ZIKV infection. An attractive drug target for ZIKV treatment is a two-compartment (NS2B/NS3) serine protease that processes viral polyprotein during infection. Here, conventional molecular dynamics simulations of the ZIKV protease in complex with peptide substrate (TGKRS) sequence at the C-terminus of NS2B show that the substrate is in the active conformation for the cleavage reaction by ZIKV protease. Hybrid quantum mechanics/molecular mechanics (QM/MM) umbrella sampling simulations (PM6/ff14SB) of acylation results reveal that proton transfer from S135 to H51 and nucleophilic attack on the substrate by S135 are concerted. The rate-limiting step involves the formation of a tetrahedral intermediate. In addition, the single-point energy QM/MM calculations, precisely at the level of coupled cluster theory (LCCSD(T)/(aug)-cc-pVTZ), were performed to correct the potential energy profiles for the first step of the acylation process. The average computed activation barrier at this level of theory is 16.3 kcal mol^-1. Therefore, the computational approaches presented here are helpful for further designing of NS2B/NS3 inhibitors based on transition-state analogues.

Predicting allostery and microbial drug resistance with molecular simulations

Beta-lactamase enzymes mediate the most common forms of gram-negative antibiotic resistance affecting clinical treatment. They also constitute an excellent model system for the difficult problem of understanding how allosteric mutations can augment catalytic activity of already-competent enzymes. Multiple allosteric mutations have been identified that alter catalytic activity or drug-resistance spectrum in class A beta lactamases, but predicting these in advance continues to be challenging. Here, we review computational techniques based on structure and/or molecular simulation to predict such mutations. Structure-based techniques have been particularly helpful in developing graph algorithms for analyzing critical residues in beta-lactamase function, while classical molecular simulation has recently shown the ability to prospectively predict allosteric mutations increasing beta-lactamase activity and drug resistance. These will ultimately achieve the greatest power when combined with simulation methods that model reactive chemistry to calculate activation free energies directly.

Multiscale Simulations of Clavulanate Inhibition Identify the Reactive Complex in Class A β-Lactamases and Predict the Efficiency of Inhibition

Clavulanate is used as an effective drug in combination with β-lactam antibiotics to treat infections of some antibiotic resistant bacteria. Here, we perform combined quantum mechanics/molecular mechanics simulations of several covalent complexes of clavulanate with class A β-lactamases KPC-2 and TEM-1. Simulations of the deacylation reactions identify the decarboxylated trans-enamine complex as being responsible for inhibition. Further, the obtained free energy barriers discriminate clinically relevant inhibition (TEM-1) from less effective inhibition (KPC-2).

QM/MM simulations identify the determinants of catalytic activity differences between type II dehydroquinase enzymes

Type II dehydroquinase enzymes (DHQ2), recognized targets for antibiotic drug discovery, show significantly different activities dependent on the species: DHQ2 from Mycobacterium tuberculosis (MtDHQ2) and Helicobacter pylori (HpDHQ2) show a 50-fold difference in catalytic efficiency. Revealing the determinants of this activity difference is important for our understanding of biological catalysis and further offers the potential to contribute to tailoring specificity in drug design. Molecular dynamics simulations using a quantum mechanics/molecular mechanics potential, with correlated ab initio single point corrections, identify and quantify the subtle determinants of the experimentally observed difference in efficiency. The rate-determining step involves the formation of an enolate intermediate: more efficient stabilization of the enolate and transition state of the key step in MtDHQ2, mainly by the essential residues Tyr24 and Arg19, makes it more efficient than HpDHQ2. Further, a water molecule, which is absent in MtDHQ2 but involved in generation of the catalytic Tyr22 tyrosinate in HpDHQ2, was found to destabilize both the transition state and the enolate intermediate. The quantification of the contribution of key residues and water molecules in the rate-determining step of the mechanism also leads to improved understanding of higher potencies and specificity of known inhibitors, which should aid ongoing inhibitor design.

Sampling molecular conformations and dynamics in a multiuser virtual reality framework

We describe a framework for interactive molecular dynamics in a multiuser virtual reality (VR) environment, combining rigorous cloud-mounted atomistic physics simulations with commodity VR hardware, which we have made accessible to readers (see isci.itch.io/nsb-imd). It allows users to visualize and sample, with atomic-level precision, the structures and dynamics of complex molecular structures "on the fly" and to interact with other users in the same virtual environment. A series of controlled studies, in which participants were tasked with a range of molecular manipulation goals (threading methane through a nanotube, changing helical screw sense, and tying a protein knot), quantitatively demonstrate that users within the interactive VR environment can complete sophisticated molecular modeling tasks more quickly than they can using conventional interfaces, especially for molecular pathways and structural transitions whose conformational choreographies are intrinsically three-dimensional. This framework should accelerate progress in nanoscale molecular engineering areas including conformational mapping, drug development, synthetic biology, and catalyst design. More broadly, our findings highlight the potential of VR in scientific domains where three-dimensional dynamics matter, spanning research and education.

Conformational Intermediate That Controls KPC-2 Catalysis and Beta-Lactam Drug Resistance

The KPC-2 carbapenemase enzyme is responsible for drug resistance in the majority of carbapenem-resistant gram-negative bacterial infections in the United States. A better understanding of what permits KPC-2 to hydrolyze carbapenem antibiotics and how this might be inhibited is thus of fundamental interest and great practical importance to development of better anti-infectives. By correlating molecular dynamics simulations with experimental enzyme kinetics, we have identified conformational changes that control KPC-2's ability to hydrolyze carbapenem antibiotics. Related beta-lactamase enzymes can interconvert between catalytically permissive and catalytically nonpermissive forms of an acylenzyme intermediate critical to drug hydrolysis. Using molecular dynamics simulations, we identify a similar equilibrium in KPC-2 and analyze the determinants of this conformational change. Because the conformational dynamics of KPC-2 are complex and sensitive to allosteric changes, we develop an information-theoretic approach to identify key determinants of this change. We measure unbiased estimators of the reaction coordinate between catalytically permissive and nonpermissive states, perform information-theoretic feature selection and, using restrained molecular dynamics simulations, validate the protein conformational changes predicted to control catalytically permissive geometry. We identify two binding-pocket residues that control the conformational transitions between catalytically active and inactive forms of KPC-2. Mutations to one of these residues, Trp105, lower the stability of the catalytically permissive state in simulations and have reduced experimental k _cat values that show a strong linear correlation with the simulated catalytically permissive state lifetimes. This understanding can be leveraged to predict the drug resistance of further KPC-2 mutants and help design inhibitors to combat extreme drug resistance.

Multiscale Methods in Drug Design Bridge Chemical and Biological Complexity in the Search for Cures

Drug action is inherently multiscale: it connects molecular interactions to emergent properties at cellular and larger scales. Simulation techniques at each of these different scales are already central to drug design and development, but methods capable of connecting across these scales will extend understanding of complex mechanisms and the ability to predict biological effects. Improved algorithms, ever-more-powerful computing architectures and the accelerating growth of rich datasets are driving advances in multiscale modeling methods capable of bridging chemical and biological complexity from the atom to the cell. Particularly exciting is the development of highly detailed, structure-based, physical simulations of biochemical systems, which are now able to access experimentally relevant timescales for large systems and, at the same time, achieve unprecedented accuracy. In this Perspective, we discuss how emerging data-rich, physics-based multiscale approaches are of the cusp of realizing long-promised impact in the discovery, design and development of novel therapeutics. We highlight emerging methods and applications in this growing field, and outline how different scales can be combined in practical modelling and simulation strategies.

Predicting allosteric mutants that increase activity of a major antibiotic resistance enzyme

Allosteric mutations increasing k_cat in a beta lactamase act by changing conformational ensembles of active-site residues identified by machine learning.

The CTX-M family of beta lactamases mediate broad-spectrum antibiotic resistance and are present in the majority of drug-resistant Gram-negative bacterial infections worldwide. Allosteric mutations that increase catalytic rates of these drug resistance enzymes have been identified in clinical isolates but are challenging to predict prospectively. We have used molecular dynamics simulations to predict allosteric mutants increasing CTX-M9 drug resistance, experimentally testing top mutants using multiple antibiotics. Purified enzymes show an increase in catalytic rate and efficiency, while mutant crystal structures show no detectable changes from wild-type CTX-M9. We hypothesize that increased drug resistance results from changes in the conformational ensemble of an acyl intermediate in hydrolysis. Machine-learning analyses on the three top mutants identify changes to the binding-pocket conformational ensemble by which these allosteric mutations transmit their effect. These findings show how molecular simulation can predict how allosteric mutations alter active-site conformational equilibria to increase catalytic rates and thus resistance against common clinically used antibiotics.

Structural and Functional Aspects of Class A Carbapenemases

The fight against infectious diseases is probably one of the greatest public health challenges faced by our society, especially with the emergence of carbapenem-resistant gram-negatives that are in some cases pan-drug resistant. Currently,β-lactamase-mediated resistance does not spare even the newest and most powerful β-lactams (carbapenems), whose activity is challenged by carbapenemases. The worldwide dissemination of carbapenemases in gram-negative organisms threatens to take medicine back into the pre-antibiotic era since the mortality associated with infections caused by these "superbugs" is very high, due to limited treatment options. Clinically-relevant carbapenemases belong either to metallo-β- lactamases (MBLs) of Ambler class B or to serine-β-lactamases (SBLs) of Ambler class A and D enzymes. Class A carbapenemases may be chromosomally-encoded (SME, NmcA, SFC-1, BIC-1, PenA, FPH-1, SHV-38), plasmid-encoded (KPC, GES, FRI-1) or both (IMI). The plasmid-encoded enzymes are often associated with mobile elements responsible for their mobilization. These enzymes, even though weakly related in terms of sequence identities, share structural features and a common mechanism of action. They variably hydrolyse penicillins, cephalosporins, monobactams, carbapenems, and are inhibited by clavulanate and tazobactam. Three-dimensional structures of class A carbapenemases, in the apo form or in complex with substrates/inhibitors, together with site-directed mutagenesis studies, provide essential input for identifying the structural factors and subtle conformational changes that influence the hydrolytic profile and inhibition of these enzymes. Overall, these data represent the building blocks for understanding the structure-function relationships that define the phenotypes of class A carbapenemases and can guide the design of new molecules of therapeutic interest.

On the challenge of exploring the evolutionary trajectory from phosphotriesterase to arylesterase using computer simulations

The ability to design effective enzymes presents a fundamental challenge in biotechnology and also in biochemistry. Unfortunately, most of the progress on this field has been accomplished by bringing the reactants to a reasonable orientation relative to each other, rather than by rational optimization of the polar preorganization of the environment, which is the most important catalytic factor. True computer based enzyme design would require the ability to evaluate the catalytic power of designed active sites. This work considers the evolution from a phosphotriesterase (with the paraoxon substrate) to arylesterase (with the 2-naphthylhexanoate (2NH) substrate) catalysis. Both the original and the evolved enzymes involve two zinc ions and their ligands, making it hard to obtain a reliable quantum mechanical description and then to obtain an effective free energy sampling. Furthermore, the options for the reaction path are quite complicated. To progress in this direction we started with DFT calculations of the energetics of different mechanistic options of cluster models and then used the results to calibrate empirical valence bond (EVB) models and to generate properly sampled free energy surfaces for different mechanisms in the enzyme. Interestingly, it is found that the catalytic effect depends on the Zn-Zn distance making the mechanistic analysis somewhat complicated. Comparing the activation barriers of paraoxon and the 2NH ester at the beginning and end of the evolutionary path reproduced the observed evolutionary trend. However, although our findings provide an advance in exploring the nature of promiscuous enzymes, they also indicate that modeling the reaction mechanism in the case of enzymes with a binuclear zinc center is far from trivial and presents a challenge for computer-aided enzyme design.

Simulating the inhibition reaction of Mycobacterium tuberculosisl,d-transpeptidase 2 by carbapenems

The inactivation mechanism of LDT enzyme from M. tuberculosis by carbapenems is described by QM/MM and PMF analysis