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Recent biochemical, biophysical, and genetic studies have shown that heparan sulfate, a major component of the cellular glycocalyx, participates in infection of SARS-CoV-2 by facilitating the so-called open conformation of the spike protein, which is required for binding to ACE2. This review highlights the involvement of heparan sulfate in the SARS-CoV-2 infection cycle and argues that there is a high degree of coordination between host cell heparan sulfate and asparagine-linked glycans on the spike in enabling ACE2 binding and subsequent infection. The discovery that spike protein binding and infection depends on both viral and host glycans provides insights into the evolution, spread and potential therapies for SARS-CoV-2 and its variants.

High-fidelity replication of the large RNA genome of coronaviruses (CoVs) is mediated by a 3'-to-5' exoribonuclease (ExoN) in nonstructural protein 14 (nsp14), which excises nucleotides including antiviral drugs misincorporated by the low-fidelity viral RNA-dependent RNA polymerase (RdRp) and has also been implicated in viral RNA recombination and resistance to innate immunity. Here, we determined a 1.6-Å resolution crystal structure of severe acute respiratory syndrome CoV 2 (SARS-CoV-2) ExoN in complex with its essential cofactor, nsp10. The structure shows a highly basic and concave surface flanking the active site, comprising several Lys residues of nsp14 and the N-terminal amino group of nsp10. Modeling suggests that this basic patch binds to the template strand of double-stranded RNA substrates to position the 3' end of the nascent strand in the ExoN active site, which is corroborated by mutational and computational analyses. We also show that the ExoN activity can rescue a stalled RNA primer poisoned with sofosbuvir and allow RdRp to continue its extension in the presence of the chain-terminating drug, biochemically recapitulating proofreading in SARS-CoV-2 replication. Molecular dynamics simulations further show remarkable flexibility of multidomain nsp14 and suggest that nsp10 stabilizes ExoN for substrate RNA binding to support its exonuclease activity. Our high-resolution structure of the SARS-CoV-2 ExoN-nsp10 complex serves as a platform for future development of anticoronaviral drugs or strategies to attenuate the viral virulence.

The discovery of new drugs is a time consuming and expensive process. Methods such as virtual screening, which can filter out ineffective compounds from drug libraries prior to expensive experimental study, have become popular research topics. As the computational drug discovery community has grown, in order to benchmark the various advances in methodology, organizations such as the Drug Design Data Resource have begun hosting blinded grand challenges seeking to identify the best methods for ligand pose-prediction, ligand affinity ranking, and free energy calculations. Such open challenges offer a unique opportunity for researchers to partner with junior students (e.g., high school and undergraduate) to validate basic yet fundamental hypotheses considered to be uninteresting to domain experts. Here, we, a group of high school-aged students and their mentors, present the results of our participation in Grand Challenge 4 where we predicted ligand affinity rankings for the Cathepsin S protease, an important protein target for autoimmune diseases. To investigate the effect of incorporating receptor dynamics on ligand affinity rankings, we employed the Relaxed Complex Scheme, a molecular docking method paired with molecular dynamics-generated receptor conformations. We found that Cathepsin S is a difficult target for molecular docking and we explore some advanced methods such as distance-restrained docking to try to improve the correlation with experiments. This project has exemplified the capabilities of high school students when supported with a rigorous curriculum, and demonstrates the value of community-driven competitions for beginners in computational drug discovery.

To investigate the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the immune population, we coincupi bated the authentic virus with a highly neutralizing plasma from a COVID-19 convalescent patient. The plasma fully neutralized the virus for seven passages, but, after 45 d, the deletion of F140 in the spike N-terminal domain (NTD) N3 loop led to partial breakthrough. At day 73, an E484K substitution in the receptor-binding domain (RBD) occurred, followed, at day 80, by an insertion in the NTD N5 loop containing a new glycan sequon, which generated a variant completely resistant to plasma neutralization. Computational modeling predicts that the deletion and insertion in loops N3 and N5 prevent binding of neutralizing antibodies. The recent emergence in the United Kingdom, South Africa, Brazil, and Japan of natural variants with similar changes suggests that SARS-CoV-2 has the potential to escape an effective immune response and that vaccines and antibodies able to control emerging variants should be developed.

The use of epigenetic bromodomain inhibitors as anticancer therapeutics has transitioned from targeting bromodomain extraterminal domain (BET) proteins into targeting non-BET bromodomains. The two most relevant non-BET bromodomain oncology targets are cyclic AMP response element-binding protein (CBP) and E1A binding protein P300 (EP300). To explore the growing CBP/EP300 interest, we developed a highly efficient two-step synthetic route for dimethylisoxazole-attached imidazo[1,2-a]pyridine scaffold-containing inhibitors. Our efficient two-step reactions enabled high-throughput synthesis of compounds designed by molecular modeling, which together with structure-activity relationship (SAR) studies facilitated an overarching understanding of selective targeting of CBP/EP300 over non-BET bromodomains. This led to the identification of a new potent and selective CBP/EP300 bromodomain inhibitor, UMB298 (compound 23, CBP IC50 72 nM and bromodomain 4, BRD4 IC50 5193 nM). The SAR we established is in good agreement with literature-reported CBP inhibitors, such as CBP30, and demonstrates the advantage of utilizing our two-step approach for inhibitor development of other bromodomains.

Influenza neuraminidase is an important drug target. Glycans are present on neuraminidase and are generally considered to inhibit antibody binding via their glycan shield. In this work, we studied the effect of glycans on the binding kinetics of antiviral drugs to the influenza neuraminidase. We created all-atom in silico systems of influenza neuraminidase with experimentally derived glycoprofiles consisting of four systems with different glycan conformations and one system without glycans. Using Brownian dynamics simulations, we observe a two- to eightfold decrease in the rate of ligand binding to the primary binding site of neuraminidase due to the presence of glycans. These glycans are capable of covering much of the surface area of neuraminidase, and the ligand binding inhibition is derived from glycans sterically occluding the primary binding site on a neighboring monomer. Our work also indicates that drugs preferentially bind to the primary binding site (i.e., the active site) over the secondary binding site, and we propose a binding mechanism illustrating this. These results help illuminate the complex interplay between glycans and ligand binding on the influenza membrane protein neuraminidase.

Custom-designed ligand-binding proteins represent a promising class of macromolecules with exciting applications toward the design of new enzymes or the engineering of antibodies and small-molecule recruited proteins for therapeutic interventions. However, several challenges remain in designing a protein sequence such that the binding site organization results in high affinity interaction with a bound ligand. Here, we study the dynamics of explicitly solvated designed proteins through all-atom molecular dynamics (MD) simulations to gain insight into the causes that lead to the low affinity or instability of most of these designs, despite the prediction of their success by the computational design methodology. Simulations ranging from 500 to 1000 ns per replicate were conducted on 37 designed protein variants encompassing two distinct folds and a range of ligand affinities, resulting in more than 180 μs of combined sampling. The simulations provide retrospective insights into the properties affecting ligand affinity that can prove useful in guiding further steps of design optimization. Features indicate that entropic components are particularly important for affinity, which are not easily incorporated in the empirical models often used in design protocols. Additionally, we demonstrate that the application of machine learning approaches built upon the output from the simulations can help discriminate between successful and failed binders, such that MD could act as a screening step in protein design, resulting in a more efficient process.

Docking calculations can accelerate drug discovery by predicting the bound poses of ligands for a targeted protein. However, it is not clear which docking methods work best. Furthermore, predicting poses requires steps outside the docking algorithm itself, such as preparation of the protein and ligand, and it is not known which components are most in need of improvement. The Continuous Evaluation of Ligand Protein Predictions (CELPP) is a blinded prediction challenge designed to address these issues. Participants create a workflow to predict protein-ligand binding poses, which is then tasked with predicting 10-100 new protein-ligand crystal structures each week. CELPP evaluates the accuracy of each workflow's predictions and posts the scores online. The results can be used to identify the strengths and weaknesses of current approaches, help map docking problems to the algorithms most likely to overcome them, and illuminate areas of unmet need in structure-guided drug design.

CC chemokine receptor 2 (CCR2) is a part of the chemokine receptor family, an important class of therapeutic targets. These class A G-protein coupled receptors (GPCRs) are involved in mammalian signaling pathways and control cell migration toward endogenous CC chemokine ligands, named for the adjacent cysteine motif on their N terminus. Chemokine receptors and their associated ligands are involved in a wide range of diseases and thus have become important drug targets. CCR2, in particular, promotes the metastasis of cancer cells and is also implicated in autoimmunity-driven type-1 diabetes, diabetic nephropathy, multiple sclerosis, asthma, atherosclerosis, neuropathic pain, and rheumatoid arthritis. Although promising, CCR2 antagonists have been largely unsuccessful to date. Here, we investigate the effect of an orthosteric and an allosteric antagonist on CCR2 dynamics by coupling long-timescale molecular dynamics simulations with Markov-state model theory. We find that the antagonists shift CCR2 into several stable inactive conformations that are distinct from the crystal structure conformation and disrupt a continuous internal water and sodium ion pathway, preventing transitions to an active-like state. Several metastable conformations present a cryptic drug-binding pocket near the allosteric site that may be amenable to targeting with small molecules. Without antagonists, the apo dynamics reveal intermediate conformations along the activation pathway that provide insight into the basal dynamics of CCR2 and may also be useful for future drug design.

The atomic-level mechanisms that coordinate ligand release from protein pockets are only known for a handful of proteins. Here, we report results from accelerated molecular dynamics simulations for benzene dissociation from the buried cavity of the T4 lysozyme Leu99Ala mutant (L99A). In these simulations, benzene is released through a previously characterized, sparsely populated room-temperature excited state of the mutant, explaining the coincidence for experimentally measured benzene off rate and apo protein slow-timescale NMR relaxation rates between ground and excited states. The path observed for benzene egress is a multistep ligand migration from the buried cavity to ultimate release through an opening between the F/G-, H-, and I-helices and requires a number of cooperative multiresidue and secondary-structure rearrangements within the C-terminal domain of L99A. These rearrangements are identical to those observed along the ground state to excited state transitions characterized by molecular dynamic simulations run on the Anton supercomputer. Analyses of the molecular properties of the residues lining the egress path suggest that protein surface electrostatic potential may play a role in the release mechanism. Simulations of wild-type T4 lysozyme also reveal that benzene-egress-associated dynamics in the L99A mutant are potentially exaggerations of the substrate-processivity-related dynamics of the wild type.

The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017-2018, GC3 centered on the protein Cathepsin S and the kinases VEGFR2, JAK2, p38-α, TIE2, and ABL1, and included both pose-prediction and affinity-ranking components. GC3 was structured much like the prior challenges GC2015 and GC2. First, Stage 1 tested pose prediction and affinity ranking methods; then all available crystal structures were released, and Stage 2 tested only affinity rankings, now in the context of the available structures. Unique to GC3 was the addition of a Stage 1b self-docking subchallenge, in which the protein coordinates from all of the cocrystal structures used in the cross-docking challenge were released, and participants were asked to predict the pose of CatS ligands using these newly released structures. We provide an overview of the outcomes and discuss insights into trends and best-practices.

The "guardian of the genome", p53, functions as a tumor suppressor that responds to cell stressors such as DNA damage, hypoxia, and tumor formation by inducing cell-cycle arrest, senescence, or apoptosis. Mutation of p53 disrupts its tumor suppressor function, leading to various types of human cancers. One particular mutant, R175H, is a structural mutant that inactivates the DNA damage response pathway and acquires oncogenic functions that promotes both cancer and drug resistance. Our current work aims to understand how p53 wild-type function is disrupted due to the R175H mutation. We use a series of atomistic integrative models built previously from crystal structures of the full-length p53 tetramer bound to DNA and model the R175H mutant using in silico site-directed mutagenesis. Explicitly solvated all-atom molecular dynamics (MD) simulations on wild-type and the R175H mutant p53 reveal insights into how wild-type p53 searches and recognizes DNA, and how this mechanism is disrupted as a result of the R175H mutation. Specifically, our work reveals the optimal quaternary DNA binding mode of the DNA binding domain and shows how this binding mode is altered via symmetry loss as a result of the R175H mutation, indicating a recognition mechanism that is reminiscent of the asymmetry seen in wild type p53 binding to nonspecific genomic elements. Altogether our work sheds new light into the hitherto unseen molecular mechanisms governing transcription factor, DNA recognition.

We present a substantial update to the open-source POVME binding pocket analysis software. New capabilities of POVME 3.0 include a flexible chemical coloring scheme for feature identification, postanalysis tools for comparing large ensembles of pockets (e.g., from molecular dynamics simulations), and the introduction of scripts and methods that facilitate binding pocket comparison and analysis. We envision the use of this software for visualization of binding pocket dynamics, selection of representative structures for ensemble docking, and incorporation of molecular dynamics results into ligand design efforts.

We present the Simulation Enabled Estimation of Kinetic Rates (SEEKR) package, a suite of open-source scripts and tools designed to enable researchers to perform multiscale computation of the kinetics of molecular binding, unbinding, and transport using a combination of molecular dynamics, Brownian dynamics, and milestoning theory. To demonstrate its utility, we compute the kon, koff, and ΔGbind for the protein trypsin with its noncovalent binder, benzamidine, and examine the kinetics and other results generated in the context of the new software, and compare our findings to previous studies performed on the same system. We compute a kon estimate of (2.1 ± 0.3) × 107 M-1 s-1, a koff estimate of 83 ± 14 s-1, and a ΔGbind of -7.4 ± 0.1 kcal·mol-1, all of which compare closely to the experimentally measured values of 2.9 × 107 M-1 s-1, 600 ± 300 s-1, and -6.71 ± 0.05 kcal·mol-1, respectively.

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ∼90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteins in complexes with C4BP. The structures revealed a uniform and tolerant 'reading head' in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M-C4BP interaction, and also inform a path towards vaccine design.

The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016. Two targets served as the framework to test community docking and scoring methods: (1) HSP90, donated by AbbVie and the Community Structure Activity Resource (CSAR), and (2) MAP4K4, donated by Genentech. The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses. An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy. Unlike previous blinded Challenges, we did not provide cognate receptors or receptors prepared with hydrogens and likewise did not require a specified crystal structure to be used for pose or affinity prediction in Stage 1. Given the freedom to select from over 200 crystal structures of HSP90 in the PDB, participants employed workflows that tested not only core docking and scoring technologies, but also methods for addressing water-mediated ligand-protein interactions, binding pocket flexibility, and the optimal selection of protein structures for use in docking calculations. Nearly 40 participating groups submitted over 350 prediction sets for Grand Challenge 2015. This overview describes the datasets and the organization of the challenge components, summarizes the results across all submitted predictions, and considers broad conclusions that may be drawn from this collaborative community endeavor.

Deletions in the stalk of the influenza neuraminidase (NA) surface protein are associated with increased virulence, but the mechanisms responsible for this enhanced virulence are unclear. Here we use microsecond molecular dynamics simulations to explore the effect of stalk deletion on enzymatic activity, contrasting NA proteins from the A/swine/Shandong/N1/2009 strain both with and without a stalk deletion. By modeling and simulating neuraminidase apo glycoproteins embedded in complex-mixture lipid bilayers, we show that the geometry and dynamics of the neuraminidase enzymatic pocket may differ depending on stalk length, with possible repercussions on the binding of the endogenous sialylated-oligosaccharide receptors. We also use these simulations to predict previously unrecognized druggable "hotspots" on the neuraminidase surface that may prove useful for future efforts aimed at structure-based drug design.

Cullin-RING E3 ligases (CRLs) are elongated and bowed protein complexes that transfer ubiquitin over 60 Å to proteins targeted for proteasome degradation. One such CRL contains the ankyrin repeat and SOCS box protein 9 (ASB9), which binds to and partially inhibits creatine kinase (CK). While current models for the ASB9-CK complex contain some known interface residues, the overall structure and precise interface of the ASB9-CK complex remains unknown. Through an integrative modeling approach, we report a third-generation model that reveals precisely the interface interactions and also fits the shape of the ASB9-CK complex as determined by small-angle X-ray scattering. We constructed an atomic model for the entire CK-targeting CRL to uncover dominant modes of motion that could permit ubiquitin transfer. Remarkably, only the correctly docked CK-containing E3 ligase and not incorrectly docked structures permitted close approach of ubiquitin to the CK substrate.

Avian influenza virus subtype H5N1 is a potential pandemic threat with human-adapted strains resistant to antiviral drugs. Although virtual screening (VS) against a crystal or relaxed receptor structure is an established method to identify potential inhibitors, the more dynamic changes within binding sites are neglected. To accommodate full receptor flexibility, we use AutoDock4 to screen the NCI diversity set against representative receptor ensembles extracted from explicitly solvated molecular dynamics simulations of the neuraminidase system. The top hits are redocked to the entire nonredundant receptor ensemble and rescored using the relaxed complex scheme (RCS). Of the 27 top hits reported, half ranked very poorly if only crystal structures are used. These compounds target the catalytic cavity as well as the newly identified 150- and 430-cavities, which exhibit dynamic properties in electrostatic surface and geometric shape. This ensemble-based VS and RCS approach may offer improvement over existing strategies for structure-based drug discovery.

The spiroindolones, a new class of antimalarial medicines discovered in a cellular screen, are rendered less active by mutations in a parasite P-type ATPase, PfATP4. We show here that S. cerevisiae also acquires mutations in a gene encoding a P-type ATPase (ScPMA1) after exposure to spiroindolones and that these mutations are sufficient for resistance. KAE609 resistance mutations in ScPMA1 do not confer resistance to unrelated antimicrobials, but do confer cross sensitivity to the alkyl-lysophospholipid edelfosine, which is known to displace ScPma1p from the plasma membrane. Using an in vitro cell-free assay, we demonstrate that KAE609 directly inhibits ScPma1p ATPase activity. KAE609 also increases cytoplasmic hydrogen ion concentrations in yeast cells. Computer docking into a ScPma1p homology model identifies a binding mode that supports genetic resistance determinants and in vitro experimental structure-activity relationships in both P. falciparum and S. cerevisiae. This model also suggests a shared binding site with the dihydroisoquinolones antimalarials. Our data support a model in which KAE609 exerts its antimalarial activity by directly interfering with P-type ATPase activity. [ABSTRACT FROM AUTHOR]

The tumor suppressor protein p53 can lose its function upon single-point missense mutations in the core DNA-binding domain (''cancer mutants''). Activity can be restored by second-site suppressor mutations (''rescue mutants''). This paper relates the functional activity of p53 cancer and rescue mutants to their overall molecular dynamics (MD), without focusing on local structural details. A novel global measure of protein flexibility for the p53 core DNA-binding domain, the number of clusters at a certain RMSD cutoff, was computed by clustering over 0.7 ms of explicitly solvated all-atom MD simulations. For wild-type p53 and a sample of p53 cancer or rescue mutants, the number of clusters was a good predictor of in vivo p53 functional activity in cell-based assays. This number-of-clusters (NOC) metric was strongly correlated (r2 = 0.77) with reported values of experimentally measured DDG protein thermodynamic stability. Interpreting the number of clusters as a measure of protein flexibility: (i) p53 cancer mutants were more flexible than wild-type protein, (ii) second-site rescue mutations decreased the flexibility of cancer mutants, and (iii) negative controls of non-rescue second-site mutants did not. This new method reflects the overall stability of the p53 core domain and can discriminate which second-site mutations restore activity to p53 cancer mutants. INSET: Author Summary. [ABSTRACT FROM AUTHOR]

We have combined equilibrium and steered molecular dynamics (SMD) simulations with principal component and correlation analyses to probe the mechanism of allosteric regulation in imidazole glycerol phosphate (IGP) synthase. An evolutionary analysis of IGP synthase revealed a conserved network of interactions leading from the effector binding site to the glutaminase active site, forming conserved communication pathways between the remote active sites. SMD simulations of the undocking of the ribonucleotide effector N¹-[(5′-phosphoribulosyl)-formino]-5′-aminoimidazole carboxamide ribonucleotide (PRFAR) resulted in a large scale hinge-opening motion at the interface. Principal component analysis and a correlation analysis of the equilibration protein motion indicate that the dynamics involved in the allosteric transition are mediated by coupled motion between sites that are more than 25 Å apart. Furthermore, conserved residues at the substrate-binding site, within the barrel, and at the interface were found to exhibit highly correlated motion during the allosteric transition. The coupled motion between PRFAR unbinding and the directed opening of the interface is interpreted in combination with kinetic assays for the wild-type and mutant systems to develop a model of allosteric regulation in IGP synthase that is monitored and investigated with atomic resolution. [ABSTRACT FROM AUTHOR]

Summary: Computational solvent fragment mapping is typically performed on a single structure of a protein to identify and characterize binding sites. However, the simultaneous analysis of several mutant structures or frames of a molecular dynamics simulation may provide more realistic detail about the behavior of the sites. Here we present a plug-in for Visual Molecular Dynamics that streamlines the comparison of the binding configurations of several FTMAP-generated structures.Availability: FTProd is a freely available and open-source plug-in that can be downloaded at http://amarolab.ucsd.edu/ftprodContact: ramaro@ucsd.eduSupplementary Information: Supplementary data are available at Bioinformatics online [ABSTRACT FROM PUBLISHER]

Summary: Hemagglutinin (HA) binds to sialylated glycans exposed on the host cell surface in the initial stage of avian influenza virus infection. It has been previously hypothesized that glycan topology plays a critical role in the human adaptation of avian flu viruses, such as the potentially pandemic H5N1. Comparative molecular dynamics studies are complementary to experimental techniques, including glycan microarray, to understand the mechanism of species-specificity switch better. The examined systems comprise explicitly solvated trimeric forms of avian H3, H5, and swine H9 in complex with avian and human glycan receptor analogues—LSTa (α-2,3-linked lactoseries tetrasaccharide a) and LSTc (α-2,6-linked lactoseries tetrasaccharide c), respectively. The glycans adopted distinct topological profiles with inducible torsional angles when bound to different HAs. The corresponding receptor binding domain amino acid contact profiles were also distinct. Avian H5 was able to accommodate LSTc in a tightly “folded umbrella”-like topology through interactions with all five sugar residues. After considering conformational entropy, the relative binding free-energy changes, calculated using the molecular mechanics-generalized Born surface area technique, were in agreement with previous experimental findings and provided insights on electrostatic, van der Waals, desolvation, and entropic contributions to HA–glycan interactions. The topology profile and the relative abundance of free glycan receptors may influence receptor binding kinetics. Glycan composition and topological changes upon binding different HAs may be important determinants in species-specificity switch. [Copyright &y& Elsevier]

The article presents a study which investigates the role of secondary sialic acid binding site in the avian N1 neuraminidase (NA) subtype. The study probes the binding site using hemagglutinin (HA) activity showed by the N9 NA in influenza isolates and proves the secondary sialic acid binding site with the use of X-ray crystallography experiments. Results show that the electrostatic actions at the avian NA's site may play an essential role in the detection process of the sialic receptors of NA.

Gram-negative bacteria are surrounded by a secondary membrane of which the outer leaflet is composed of the glycolipid lipopolysaccharide (LPS), which guards against hydrophobic toxins, including many antibiotics. Therefore, LPS synthesis in bacteria is an attractive target for antibiotic development. LpxH is a pyrophosphatase involved in LPS synthesis, and previous structures revealed that LpxH has a helical cap that binds its lipid substrates. Here, crystallography and hydrogen-deuterium exchange MS provided evidence for a highly flexible substrate-binding cap in LpxH. Furthermore, molecular dynamics simulations disclosed how the helices of the cap may open to allow substrate entry. The predicted opening mechanism was supported by activity assays of LpxH variants. Finally, we confirmed biochemically that LpxH is inhibited by a previously identified antibacterial compound, determined the potency of this inhibitor, and modeled its binding mode in the LpxH active site. In summary, our work provides evidence that the substratebinding cap of LpxH is highly dynamic, thus allowing for facile substrate binding and product release between the capping helices. Our results also pave the way for the rational design of more potent LpxH inhibitors. [ABSTRACT FROM AUTHOR]