Cyclin-dependent kinase 12 is a drug target for visceral leishmaniasis.

Visceral leishmaniasis causes considerable mortality and morbidity in many parts of the world. There is an urgent need for the development of new, effective treatments for this disease. Here we describe the development of an anti-leishmanial drug-like chemical series based on a pyrazolopyrimidine scaffold. The leading compound from this series (7, DDD853651/GSK3186899) is efficacious in a mouse model of visceral leishmaniasis, has suitable physicochemical, pharmacokinetic and toxicological properties for further development, and has been declared a preclinical candidate. Detailed mode-of-action studies indicate that compounds from this series act principally by inhibiting the parasite cdc-2-related kinase 12 (CRK12), thus defining a druggable target for visceral leishmaniasis.

Extracting binding energies and binding modes from biomolecular simulations of fragment binding to endothiapepsin.

Fragment-based drug discovery (FBDD) aims to discover a set of small binding fragments that may be subsequently linked together. Therefore, in-depth knowledge of the individual fragments' structural and energetic binding properties is essential. In addition to experimental techniques, the direct simulation of fragment binding by molecular dynamics (MD) simulations became popular to characterize fragment binding. However, former studies showed that long simulation times and high computational demands per fragment are needed, which limits applicability in FBDD. Here, we performed short, unbiased MD simulations of direct fragment binding to endothiapepsin, a well-characterized model system of pepsin-like aspartic proteases. To evaluate the strengths and limitations of short MD simulations for the structural and energetic characterization of fragment binding, we predicted the fragments' absolute free energies and binding poses based on the direct simulations of fragment binding and compared the predictions to experimental data. The predicted absolute free energies are in fair agreement with the experiment. Combining the MD data with binding mode predictions from molecular docking approaches helped to correctly identify the most promising fragments for further chemical optimization. Importantly, all computations and predictions were done within 5 days, suggesting that MD simulations may become a viable tool in FBDD projects.

Molecular Mechanisms of Glutamine Synthetase Mutations that Lead to Clinically Relevant Pathologies.

Glutamine synthetase (GS) catalyzes ATP-dependent ligation of ammonia and glutamate to glutamine. Two mutations of human GS (R324C and R341C) were connected to congenital glutamine deficiency with severe brain malformations resulting in neonatal death. Another GS mutation (R324S) was identified in a neurologically compromised patient. However, the molecular mechanisms underlying the impairment of GS activity by these mutations have remained elusive. Molecular dynamics simulations, free energy calculations, and rigidity analyses suggest that all three mutations influence the first step of GS catalytic cycle. The R324S and R324C mutations deteriorate GS catalytic activity due to loss of direct interactions with ATP. As to R324S, indirect, water-mediated interactions reduce this effect, which may explain the suggested higher GS residual activity. The R341C mutation weakens ATP binding by destabilizing the interacting residue R340 in the apo state of GS. Additionally, the mutation is predicted to result in a significant destabilization of helix H8, which should negatively affect glutamate binding. This prediction was tested in HEK293 cells overexpressing GS by dot-blot analysis: Structural stability of H8 was impaired through mutation of amino acids interacting with R341, as indicated by a loss of masking of an epitope in the glutamate binding pocket for a monoclonal anti-GS antibody by L-methionine-S-sulfoximine; in contrast, cells transfected with wild type GS showed the masking. Our analyses reveal complex molecular effects underlying impaired GS catalytic activity in three clinically relevant mutants. Our findings could stimulate the development of ATP binding-enhancing molecules by which the R324S mutant can be repaired extrinsically.

Complex long-distance effects of mutations that confer linezolid resistance in the large ribosomal subunit.

The emergence of multidrug-resistant pathogens will make current antibiotics ineffective. For linezolid, a member of the novel oxazolidinone class of antibiotics, 10 nucleotide mutations in the ribosome have been described conferring resistance. Hypotheses for how these mutations affect antibiotics binding have been derived based on comparative crystallographic studies. However, a detailed description at the atomistic level of how remote mutations exert long-distance effects has remained elusive. Here, we show that the G2032A-C2499A double mutation, located > 10 Å away from the antibiotic, confers linezolid resistance by a complex set of effects that percolate to the binding site. By molecular dynamics simulations and free energy calculations, we identify U2504 and C2452 as spearheads among binding site nucleotides that exert the most immediate effect on linezolid binding. Structural reorganizations within the ribosomal subunit due to the mutations are likely associated with mutually compensating changes in the effective energy. Furthermore, we suggest two main routes of information transfer from the mutation sites to U2504 and C2452. Between these, we observe cross-talk, which suggests that synergistic effects observed for the two mutations arise in an indirect manner. These results should be relevant for the development of oxazolidinone derivatives that are active against linezolid-resistant strains.

Extension of the free energy workflow FEW towards implicit solvent/implicit membrane MM-PBSA calculations.

BACKGROUND: The number of high-resolution structures of pharmacologically relevant membrane proteins has been strongly increasing. This makes computing relative affinities of chemically similar compounds binding to a membrane protein possible in order to guide decision making in drug design. However, the preparation step of such calculations is time-consuming and complex. METHODS: We extended the free energy workflow tool FEW, available in AMBER, towards facilitating the setup of molecular dynamics simulations with explicit membrane, and the setup and execution of effective binding energy calculations according to a 1-trajectory implicit solvent/implicit membrane MM-PBSA approach for multiple ligands binding to the same membrane protein. RESULTS: We validated the implemented protocol initially on two model systems, a sodium ion in the presence of an implicit membrane slab and a proton traversing the M2 proton-channel of the influenza A virus. For the latter, we found a good agreement for several important events along the proton pathway with those obtained in a recent computational study. Finally, we performed a case study on effective binding energy calculations for a set of inhibitors binding to the M2 proton-channel. CONCLUSIONS: From the case study, we estimate a considerable speed up in the setup and analysis times for implicit solvent/implicit membrane MM-PBSA calculations by the extended version of FEW compared to a manual preparation. GENERAL SIGNIFICANCE: Together with the overall runtime and the analysis results, this suggests that such type of calculations can be valuable in later stages of drug design projects on membrane proteins. This article is part of a Special Issue entitled Recent developments of molecular dynamics.

Interpreting Thermodynamic Profiles of Aminoadamantane Compounds Inhibiting the M2 Proton Channel of Influenza A by Free Energy Calculations.

The development of novel anti-influenza drugs is of great importance because of the capability of influenza viruses to occasionally cross interspecies barriers and to rapidly mutate. One class of anti-influenza agents, aminoadamantanes, including the drugs amantadine and rimantadine now widely abandoned due to virus resistance, bind to and block the pore of the transmembrane domain of the M2 proton channel (M2TM) of influenza A. Here, we present one of the still rare studies that interprets thermodynamic profiles from isothermal titration calorimetry (ITC) experiments in terms of individual energy contributions to binding, calculated by the computationally inexpensive implicit solvent/implicit membrane molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach, for aminoadamantane compounds binding to M2TM of the avian "Weybridge" strain. For all eight pairs of aminoadamantane compounds considered, the trend of the predicted relative binding free energies and their individual components, effective binding energies and changes in the configurational entropy, agrees with experimental measures (ΔΔG, ΔΔH, TΔΔS) in 88, 88, and 50% of the cases. In addition, information yielded by the MM-PBSA approach about determinants of binding goes beyond that available in component quantities (ΔH, ΔS) from ITC measurements. We demonstrate how one can make use of such information to link thermodynamic profiles from ITC with structural causes on the ligand side and, ultimately, to guide decision making in lead optimization in a prospective manner, which results in an aminoadamantane derivative with improved binding affinity against M2TM(Weybridge).

Alchemical Free Energy Calculations and Isothermal Titration Calorimetry Measurements of Aminoadamantanes Bound to the Closed State of Influenza A/M2TM.

Adamantane derivatives, such as amantadine and rimantadine, have been reported to block the transmembrane domain (TM) of the M2 protein of influenza A virus (A/M2) but their clinical use has been discontinued due to evolved resistance in humans. Although experiments and simulations have provided adequate information about the binding interaction of amantadine or rimantadine to the M2 protein, methods for predicting binding affinities of whole series of M2 inhibitors have so far been scarcely applied. Such methods could assist in the development of novel potent inhibitors that overcome A/M2 resistance. Here we show that alchemical free energy calculations of ligand binding using the Bennett acceptance ratio (BAR) method are valuable for determining the relative binding potency of A/M2 inhibitors of the aminoadamantane type covering a binding affinity range of only ∼2 kcal mol(-1). Their binding affinities measured by isothermal titration calorimetry (ITC) against the A/M2TM tetramer from the Udorn strain in its closed form at pH 8 were used as experimental probes. The binding constants of rimantadine enantiomers against M2TMUdorn were measured for the first time and found to be equal. Two series of alchemical free energy calculations were performed using 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipids to mimic the membrane environment. A fair correlation was found for DPPC that was significantly improved using DMPC, which resembles more closely the DPC lipids used in the ITC experiments. This demonstrates that binding free energy calculations by the BAR approach can be used to predict relative binding affinities of aminoadamantane derivatives toward M2TM with good accuracy.

FEW: a workflow tool for free energy calculations of ligand binding.

In the later stages of drug design projects, accurately predicting relative binding affinities of chemically similar compounds to a biomolecular target is of utmost importance for making decisions based on the ranking of such compounds. So far, the extensive application of binding free energy approaches has been hampered by the complex and time-consuming setup of such calculations. We introduce the free energy workflow (FEW) tool that facilitates setup and execution of binding free energy calculations with the AMBER suite for multiple ligands. FEW allows performing free energy calculations according to the implicit solvent molecular mechanics (MM-PB(GB)SA), the linear interaction energy, and the thermodynamic integration approaches. We describe the tool's architecture and functionality and demonstrate in a show case study on Factor Xa inhibitors that the time needed for the preparation and analysis of free energy calculations is considerably reduced with FEW compared to a fully manual procedure.

Determinants of the species selectivity of oxazolidinone antibiotics targeting the large ribosomal subunit.

Oxazolidinone antibiotics bind to the highly conserved peptidyl transferase center in the ribosome. For developing selective antibiotics, a profound understanding of the selectivity determinants is required. We have performed for the first time technically challenging molecular dynamics simulations in combination with molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) free energy calculations of the oxazolidinones linezolid and radezolid bound to the large ribosomal subunits of the eubacterium Deinococcus radiodurans and the archaeon Haloarcula marismortui. A remarkably good agreement of the computed relative binding free energy with selectivity data available from experiment for linezolid is found. On an atomic level, the analyses reveal an intricate interplay of structural, energetic, and dynamic determinants of the species selectivity of oxazolidinone antibiotics: A structural decomposition of free energy components identifies influences that originate from first and second shell nucleotides of the binding sites and lead to (opposing) contributions from interaction energies, solvation, and entropic factors. These findings add another layer of complexity to the current knowledge on structure-activity relationships of oxazolidinones binding to the ribosome and suggest that selectivity analyses solely based on structural information and qualitative arguments on interactions may not reach far enough. The computational analyses presented here should be of sufficient accuracy to fill this gap.

Design and Synthesis of Covalent Inhibitors of FabA.

There is an urgent need for the development of new therapeutics with novel modes of action to target Gram-negative bacterial infections, due to resistance to current drugs. Previously, FabA, an enzyme in the bacterial type II fatty acid biosynthesis pathway, was identified as a potential drug target in Pseudomonas aeruginosa, a Gram-negative bacteria of significant clinical concern. A chemical starting point was also identified. There is a cysteine, Cys15, in the active site of FabA, adjacent to where this compound binds. This paper describes the preparation of analogues containing an electrophilic warhead with the aim of covalent inhibition of the target. A wide variety of analogues were successfully prepared. Unfortunately, these analogues did not increase inhibition, which may be due to a loop within the enzyme partially occluding access to the cysteine.

Mechanism of Fully Reversible, pH-Sensitive Inhibition of Human Glutamine Synthetase by Tyrosine Nitration.

Glutamine synthetase (GS) catalyzes an ATP-dependent condensation of glutamate and ammonia to form glutamine. This reaction-and therefore GS-are indispensable for the hepatic nitrogen metabolism. Nitration of tyrosine 336 (Y336) inhibits human GS activity. GS nitration and the consequent loss of GS function are associated with a broad range of neurological diseases. The mechanism by which Y336 nitration inhibits GS, however, is not understood. Here, we show by means of unbiased MD simulations, binding, and configurational free energy computations that Y336 nitration hampers ATP binding but only in the deprotonated and negatively charged state of residue 336. By contrast, for the protonated and neutral state, our computations indicate an increased binding affinity for ATP. pKa computations of nitrated Y336 within GS predict a pKa of ∼5.3. Thus, at physiological pH, nitrated Y336 exists almost exclusively in the deprotonated and negatively charged state. In vitro experiments confirm these predictions, in that, the catalytic activity of nitrated GS is decreased at pH 7 and 6 but not at pH 4. These results indicate a novel, fully reversible, pH-sensitive mechanism for the regulation of GS activity by tyrosine nitration.

A platform for target prediction of phenotypic screening hit molecules.

Many drug discovery programmes, particularly for infectious diseases, are conducted phenotypically. Identifying the targets of phenotypic screening hits experimentally can be complex, time-consuming, and expensive. However, it would be valuable to know what the molecular target(s) is, as knowledge of the binding pose of the hit molecule in the binding site can facilitate the compound optimisation. Furthermore, knowing the target would allow de-prioritisation of less attractive chemical series or molecular targets. To generate target-hypotheses for phenotypic active compounds, an in silico platform was developed that utilises both ligand and protein-structure information to generate a ranked set of predicted molecular targets. As a result of the web-based workflow the user obtains a set of 3D structures of the predicted targets with the active molecule bound. The platform was exemplified using Mycobacterium tuberculosis, the causative organism of tuberculosis. In a test that we performed, the platform was able to predict the targets of 60% of compounds investigated, where there was some similarity to a ligand in the protein database.

Binding Free Energy Calculations for Lead Optimization: Assessment of Their Accuracy in an Industrial Drug Design Context.

Correctly ranking compounds according to their computed relative binding affinities will be of great value for decision making in the lead optimization phase of industrial drug discovery. However, the performance of existing computationally demanding binding free energy calculation methods in this context is largely unknown. We analyzed the performance of the molecular mechanics continuum solvent, the linear interaction energy (LIE), and the thermodynamic integration (TI) approach for three sets of compounds from industrial lead optimization projects. The data sets pose challenges typical for this early stage of drug discovery. None of the methods was sufficiently predictive when applied out of the box without considering these challenges. Detailed investigations of failures revealed critical points that are essential for good binding free energy predictions. When data set-specific features were considered accordingly, predictions valuable for lead optimization could be obtained for all approaches but LIE. Our findings lead to clear recommendations for when to use which of the above approaches. Our findings also stress the important role of expert knowledge in this process, not least for estimating the accuracy of prediction results by TI, using indicators such as the size and chemical structure of exchanged groups and the statistical error in the predictions. Such knowledge will be invaluable when it comes to the question which of the TI results can be trusted for decision making.

Free Energy Calculations by the Molecular Mechanics Poisson-Boltzmann Surface Area Method.

Detailed knowledge of how molecules recognize interaction partners and of the conformational preferences of biomacromolecules is pivotal for understanding biochemical processes. Such knowledge also provides the foundation for the design of novel molecules, as undertaken in pharmaceutical research. Computer-based free energy calculations enable a detailed investigation of the energetic factors that are responsible for molecular stability or binding affinity. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach is an efficient method for the calculation of free energies of diverse molecular systems. Here we describe the concepts of this approach and outline the practical proceeding. Furthermore we give an overview of the wide spectrum of problems that have been addressed with this method and of successful analyses carried out, thereby focussing on ambitious and recent studies. Limits of the approach in terms of accuracy and applicability are discussed. Despite these limitations MM-PBSA is a method with great potential that allows comparative free energy analyses for various molecular systems at low computational cost.

MMPBSA.py: An Efficient Program for End-State Free Energy Calculations.

MM-PBSA is a post-processing end-state method to calculate free energies of molecules in solution. MMPBSA.py is a program written in Python for streamlining end-state free energy calculations using ensembles derived from molecular dynamics (MD) or Monte Carlo (MC) simulations. Several implicit solvation models are available with MMPBSA.py, including the Poisson-Boltzmann Model, the Generalized Born Model, and the Reference Interaction Site Model. Vibrational frequencies may be calculated using normal mode or quasi-harmonic analysis to approximate the solute entropy. Specific interactions can also be dissected using free energy decomposition or alanine scanning. A parallel implementation significantly speeds up the calculation by dividing frames evenly across available processors. MMPBSA.py is an efficient, user-friendly program with the flexibility to accommodate the needs of users performing end-state free energy calculations. The source code can be downloaded at http://ambermd.org/ with AmberTools, released under the GNU General Public License.

Conformational switch upon phosphorylation: human CDK inhibitor p19INK4d between the native and partially folded state.

P19INK4d consists of five ankyrin repeats and controls the human cell cycle by inhibiting the cyclin D-dependent kinases 4 and 6. Posttranslational phosphorylation of p19INK4d has been described for Ser66 and Ser76. In the present study we show that mimicking the phosphorylation site of p19INK4d by a glutamate substitution at position 76 dramatically decreases the stability of the native but not an intermediate state. At body temperature the native conformation is completely lost and p19INK4d molecules exhibit the intermediate state as judged by kinetic and equilibrium analysis. High resolution NMR spectroscopy verified that the three C-terminal repeats remained folded in the intermediate state, whereas all cross-peaks of the two N-terminal repeats lost their native chemical shift. Molecular dynamic simulations of p19INK4d in different phosphorylation states revealed large-scale motions in phosphorylated p19INK4d, which cause destabilization of the interface between the second and third ankyrin repeat. Only doubly phosphorylated p19INK4d mimic mutants showed in vitro an increased accessibility for ubiquitination, which might be the signal for degradation in vivo.

Effects of histidine protonation and phosphorylation on histidine-containing phosphocarrier protein structure, dynamics, and physicochemical properties.

Previous structural studies of the histidine-containing phosphocarrier protein (HPr) have shown that active site residue His15 can adopt two distinct conformations which were termed OPEN and CLOSED. Using molecular dynamics simulations and protonation probability calculations, we were able to show that these two conformations correspond to different protonation forms of the histidine ring. The CLOSED-to-OPEN transition requires His15 to adopt a conformation with higher energy, which is compensated by the favorable energetic consequences of protonation. Calculations of the conformational energy of His15 show that HPr exists mainly in the CLOSED form at pH 7. The very low apparent pKa value (3.2-4.5) of the CLOSED conformation and the fact that the imidazole ring of residue 15 is primarily unprotonated at Ndelta1 at neutral pH ensure that His15 is ideally primed to be specifically phosphorylated at Ndelta1. In contrast to unphosphorylated HPr, the phosphorylated form exhibits no conformational transitions, and the CLOSED state is stable even for the protonated imidazole ring due to favorable interactions between the phosphate group and the backbone of Ala16 and Arg17. These observations from MD simulations are confirmed by a simple four-microstate model which can explain both the pH-dependent conformational change of unphosphorylated HPr and the conformational rigidity of phosphorylated HPr. Our study suggests that the predominant CLOSED conformation is relevant for HPr function in the phosphotransfer reaction, while the OPEN form of unphosphorylated HPr might be important for its additional regulatory function, in which an OPEN conformation of His15 is recognized by the transcriptional regulator CcpA.

Effect of HPr phosphorylation on structure, dynamics, and interactions in the course of transcriptional control.

The serine46-phosphorylated form of the bacterial protein HPr fulfils an essential function in carbon catabolite repression (CCR). Using molecular dynamics (MD) we studied the effect of Ser46 phosphorylation on the molecular properties of HPr and its capability to act as the co-repressor of carbon catabolite protein A (CcpA). The calculated pK (a) values for a representative set of HPr(Ser46P) structures indicate that the phosphate group of HPr(Ser46P) exists predominantly in the unprotonated form under neutral conditions. A hydrogen bond detected in HPr(Ser46P) between one phosphate-group oxygen and a side-chain hydrogen of Asn43-an amino acid conserved in all HPr proteins of Gram-positive bacteria that regulate their carbon consumption by CCR-might fulfil an important role in CcpA-HPr(Ser46P) complex formation. MD simulations show that the Ser46P-Asn43 hydrogen bond present in the unbound structure is replaced by intermolecular interactions upon complex formation. The degree to which amino acids in the CcpA-HPr(Ser46P) interface contribute to cofactor binding was analyzed by in silico alanine scanning. Lys307, Arg303, Asp296, Val300, and Tyr295 of CcpA were identified as important amino acids for the CcpA-HPr(Ser46P) interaction. Three of these residues are directly involved in sensing the correct phosphorylation state at His15(HPr) and Ser46(HPr). A substitution of interface residues Val319, Val314, Ser316, Leu321 and Gln320 by alanine showed that these amino acids, which contact helix alpha2 of HPr(Ser46P), play a less prominent role for complex formation.

AMBER force-field parameters for phosphorylated amino acids in different protonation states: phosphoserine, phosphothreonine, phosphotyrosine, and phosphohistidine.

We report a consistent set of AMBER force-field parameters for the most common phosphorylated amino acids, phosphoserine, phosphothreonine, phosphotyrosine, and phosphohistidine in different protonation states. The calculation of atomic charges followed the original restrained electrostatic potential fitting procedure used to determine the charges for the parm94/99 parameter set, taking alpha-helical and beta-strand conformations of the corresponding ACE-/NME-capped model peptide backbone into account. Missing force-field parameters were taken directly from the general AMBER force field (gaff) and the parm99 data set with minor modifications, or were newly generated based on ab initio calculations for model systems. Final parameters were validated by geometry optimizations and molecular-dynamics simulations. Template libraries for the phosphorylated amino acids in Leap format and corresponding frcmod parameter files are made available. [Figure: see text].