Redirecting raltitrexed from cancer cell thymidylate synthase to Mycobacterium tuberculosis phosphopantetheinyl transferase.

There is a compelling need to find drugs active against Mycobacterium tuberculosis (Mtb). 4'-Phosphopantetheinyl transferase (PptT) is an essential enzyme in Mtb that has attracted interest as a potential drug target. We optimized a PptT assay, used it to screen 422,740 compounds, and identified raltitrexed, an antineoplastic antimetabolite, as the most potent PptT inhibitor yet reported. While trying unsuccessfully to improve raltitrexed's ability to kill Mtb and remove its ability to kill human cells, we learned three lessons that may help others developing antibiotics. First, binding of raltitrexed substantially changed the configuration of the PptT active site, complicating molecular modeling of analogs based on the unliganded crystal structure or the structure of cocrystals with inhibitors of another class. Second, minor changes in the raltitrexed molecule changed its target in Mtb from PptT to dihydrofolate reductase (DHFR). Third, the structure-activity relationship for over 800 raltitrexed analogs only became interpretable when we quantified and characterized the compounds' intrabacterial accumulation and transformation.

Green Pervious Concrete Containing Diatomaceous Earth as Supplementary Cementitous Materials for Pavement Applications.

Portland cement porous concrete (PCPC) has received immense interest recently due to its environmental aids. Its porous structure helps to reduce the water runoff amount while improving the recharge of groundwater. Earlier studies have concentrated on illustrating and knowing the functional as well as structural properties of PCPC. However, very few studies are available on PCPC in combination with natural silica sources as supplementary cementitious materials (SCMs). Most SCMs are by-products of industrial manufacturing processes and cause some environmental concerns, but with their pozzolanic effect, they could be utilized as partial substitute materials for ordinary Portland cement (OPC) to enhance the strength as well as durability performance. The aim of this study is to evaluate the effects of diatomaceous earth (DE) as a supplementary cementitious material for partial substitution of OPC for Portland cement porous concrete application. Compression strength, split tensile strength, and flexural strength tests were performed to determine the effect of partial replacement. To investigate the impact of test variables, basic tests, including void content and water permeability, were also performed. Compared to the control concrete, the results show that a 15% replacement of cement with DE significantly increased the compressive strength (by 53%) while also providing adequate porosity and better water permeability. Statistical analysis (ANOVA) and regression analysis showed that there is a significant (p < 0.05) growth within the physical characteristics of concrete upon the replacement of cement by 15% DE. Collectively, the replacement of cement with DE could not only improve the concrete strength but also reduce the consumption of cement, thereby lessening the cost of construction as well as indirectly reducing the carbon footprint.

Predicting collision-induced dissociation mass spectra: understanding the role of the mobile proton in small molecule fragmentation.

RATIONALE: Intramolecular proton migration has been reported to be required for fragmentation by collision-induced dissociation (CID). If the collision energy is required to provide energy for proton movement to a 'dissociative' site, it may be possible to predict the optimal collision energy for fragmentation using quantum computational chemistry software. A greater understanding of the mechanism(s) of proton migration is necessary. METHODS: The product ion spectra of seven compounds were obtained at collision energies stepped in the range from 5 to 50 eV, with precursor ions being generated in positive ion mode by both atmospheric pressure chemical ionization (APCI) and electrospray ionisation (ESI) (using an ESCi ionisation source with or without corona discharge, respectively). The products ions observed at each collision energy were assessed in terms of structure to ascertain if they were formed as a result of protonation at the initial ionisation site or if the proton had migrated to a dissociative site. RESULTS: Proton migration was shown to be independent of collision energy, stability of the protonated molecule and the distance that the proton moved. Therefore, proton migration is not a barrier to fragmentation as the proton appears to be fully mobile at 5 eV. As proton migration is independent of collision energy for these compounds, whereas fragmentation is energy dependent, protonation at the dissociative site alone is not sufficient to cause bond cleavage. CONCLUSIONS: The role of collision energy in bond cleavage may be to increase the vibrational energy of the bond and/or increase the rate of bond cleavage such that it occurs within the residence time of the ion within the collision cell rather than to supply the energy for proton migration. Therefore, quantum chemistry alone cannot predict the collision energies appropriate for fragmentation on the basis of modelling proton movements.

Synthesis and bioactivity of ß-substituted fosmidomycin analogues targeting 1-deoxy-D-xylulose-5-phosphate reductoisomerase.

Blocking the 2-C-methyl-d-erythrithol-4-phosphate (MEP) pathway for isoprenoid biosynthesis offers interesting prospects for inhibiting Plasmodium or Mycobacterium spp. growth. Fosmidomycin (1) and its homologue FR900098 (2) potently inhibit 1-deoxy-d-xylulose-5-phosphate reductoisomerase (Dxr), a key enzyme in this pathway. Here we introduced aryl or aralkyl substituents at the ß-position of the hydroxamate analogue of 2. While direct addition of a ß-aryl moiety resulted in poor inhibition, longer linkers between the carbon backbone and the phenyl ring were generally associated with better binding to the enzymes. X-ray structures of the parasite Dxr-inhibitor complexes show that the "longer" compounds generate a substantially different flap structure, in which a key tryptophan residue is displaced, and the aromatic group of the ligand lies between the tryptophan and the hydroxamate's methyl group. Although the most promising new Dxr inhibitors lack activity against Escherichia coli and Mycobacterium smegmatis, they proved to be highly potent inhibitors of Plasmodium falciparum in vitro growth.

Predicting collision-induced dissociation spectra: semi-empirical calculations as a rapid and effective tool in software-aided mass spectral interpretation.

RATIONALE: Fifteen molecules were modelled using quantum chemistry, prior to interpreting their collision-induced dissociation (CID) product ion spectra, in a 'blind trial' to establish if calculated protonation-induced bond elongation could be used to predict which bonds cleaved during CID. Bond elongation has the potential to be used as a descriptor predicting bond cleavage. METHODS: The 15 molecules were modelled with respect to protonation-induced bond length changes using Density Functional Theory (DFT). Significant bond elongations were highlighted to flag potential bond cleavages. CID product ion spectra, obtained using positive ion electrospray ionisation (Waters Synapt G1), were interpreted to establish if observed bond cleavages correlated with calculated bond elongations. Calculations were also undertaken using AM1 (Austin Model 1) to see if this rapid approach gave similar results to the computationally demanding DFT. RESULTS: The AM1-calculated bond elongations were found to be similar to those generated by DFT. All the polarised bonds observed to cleave (n = 82) had been calculated to elongate significantly. Protonation, possibly via proton migration, on the most electronegative atom in the bond appeared to initiate cleavage, leading to a 100% success rate in predicting the bonds that broke as a result of protonation on a heteroatom. Cleavage of carbon-carbon bonds was not predicted. CONCLUSIONS: Cleavage of the polarised bonds appears to result from protonation on the more electronegative atom of the bond, inducing conformational changes leading to bond weakening. AM1-calculated bond length changes act as a descriptor for predicting bond cleavage. However, the impetus for cleavage of the unpolarised bonds may be product ion stability rather than bond weakening.

Understanding collision-induced dissociation of dofetilide: a case study in the application of density functional theory as an aid to mass spectral interpretation.

Fragmentation of molecules under collision-induced dissociation (CID) conditions is not well-understood. This may make interpretation of MSMS spectra difficult and limit the effectiveness of software tools intended to aid mass spectral interpretation. Density Functional Theory (DFT) has been successfully applied to explain the thermodynamics of fragmentation in the gas phase by the modelling the effect that protonation has on the bond lengths (and hence bond strengths). In this study, dofetilide and four methylated analogues were used to investigate further the potential for using DFT to understand and predict the CID fragmentation routes. The products ions present in the CID spectra of all five compounds were consistent with charge-directed fragmentation, with protonation adjacent to the cleavage site being required to initiate fragmentation. Protonation at the dissociative site may have occurred either directly or via proton migration. A correlation was observed between protonation-induced bond lengthening and the bonds which were observed to break in the CID spectra. This correlation was quantitative in that the bonds calculated to elongate to the greatest extent gave rise to the most abundant of the major product ions. Thus such quantum calculations may offer the potential for contributing to a predictive tool for aiding the accuracy and speed mass spectral interpretation by generating numerical data in the form of bond length increases to act as descriptors flagging potential bond cleavages.

Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets.

BACKGROUND: Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins' dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pocket's boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible. RESULTS: We have developed a computational method, Provar, that provides a consistent representation of predicted binding pockets across sets of related protein structures. The outputs are probabilities that each atom or residue of the protein borders a predicted pocket. These probabilities can be readily visualised on a protein using existing molecular graphics software. We show how Provar simplifies comparison of the outputs of different pocket prediction algorithms, of pockets across multiple simulated conformations and between homologous structures. We demonstrate the benefits of use of multiple structures for protein-ligand and protein-protein interface analysis on a set of complexes and consider three case studies in detail: i) analysis of a kinase superfamily highlights the conserved occurrence of surface pockets at the active and regulatory sites; ii) a simulated ensemble of unliganded Bcl2 structures reveals extensions of a known ligand-binding pocket not apparent in the apo crystal structure; iii) visualisations of interleukin-2 and its homologues highlight conserved pockets at the known receptor interfaces and regions whose conformation is known to change on inhibitor binding. CONCLUSIONS: Through post-processing of the output of a variety of pocket prediction software, Provar provides a flexible approach to the analysis and visualization of the persistence or variability of pockets in sets of related protein structures.

Using density functional theory to rationalise the mass spectral fragmentation of maraviroc and its metabolites.

Tandem mass spectrometry (MS/MS) is widely used for the identification of metabolites at all stages of the pharmaceutical discovery and development process. The assignment of ions in the product ion spectra can be time-consuming and hence delay feedback of results that may influence the direction of a project. A deeper understanding of the processes involved in generation of the product ions formed via collision-induced dissociation may allow development of chemically intelligent software to aid spectral interpretation. Current commercially available spectral interpretation software takes a mainly arithmetical approach resulting in extensive lists of numerically plausible ions, many of which may not be chemically feasible. In this study, high-resolution MS/MS spectra were obtained for maraviroc and two of its synthetic metabolites, and structures for the product ions proposed. Density functional theory (DFT) based on in silico modelling was undertaken to investigate whether the fragmentation observed was potentially a result of bond lengthening (and hence weakening) as a consequence of protonation of the molecule at the most thermodynamically stable site(s). It was determined that for all three compounds, where the product ions resulted from simple bond cleavages (not rearrangements), the bonds that cleaved had been calculated to elongate after protonation. It was also noted that the protonated molecule may represent a mixture of singly charged protonated species and that the most basic sites in the molecule may not necessarily be the most thermodynamically stable for protonation.

Can density functional theory (DFT) be used as an aid to a deeper understanding of tandem mass spectrometric fragmentation pathways?

Prediction of tandem mass spectrometric (MS/MS) fragmentation for non-peptidic molecules based on structure is of immense interest to the mass spectrometrist. If a reliable approach to MS/MS prediction could be achieved its impact within the pharmaceutical industry could be immense. Many publications have stressed that the fragmentation of a molecular ion or protonated molecule is a complex process that depends on many parameters, making prediction difficult. Commercial prediction software relies on a collection of general heuristic rules of fragmentation, which involve cleaving every bond in the structure to produce a list of 'expected' masses which can be compared with the experimental data. These approaches do not take into account the thermodynamic or molecular orbital effects that impact on the molecule at the point of protonation which could influence the potential sites of bond cleavage based on the structural motif. A series of compounds have been studied by examining the experimentally derived high-resolution MS/MS data and comparing it with the in silico modelling of the neutral and protonated structures. The effect that protonation at specific sites can have on the bond lengths has also been determined. We have calculated the thermodynamically most stable protonated species and have observed how that information can help predict the cleavage site for that ion. The data have shown that this use of in silico techniques could be a possible way to predict MS/MS spectra.

Fragment-based drug discovery: what has it achieved so far?

Fragment-based drug discovery has proved to be a very useful approach particularly in the hit-to-lead process, providing a complementary tool to traditional high-throughput screening. Although often synonymous with fragment screening, fragment-based drug discovery is a far wider area covering high-throughput screening, fragment screening and virtual screening efforts. The unifying feature of fragment-based drug discovery is the low molecular weight of the hit rather than the approach it originates from. Over the last ten years, fragment-based drug discovery has provided in excess of 50 examples of small molecule hits that have been successfully advanced to leads and therefore resulted in useful substrate for drug discovery programs. To our knowledge, there are currently no marketed drugs that can be attributed to these efforts. However, due to the time scales of drug discovery and development it is likely that over the next few years the number of such examples will increase significantly.

Accuracy vs time dilemma on the prediction of NMR chemical shifts: a case study (chloropyrimidines).

The nuclear magnetic shieldings of two chloropyrimidine species have been predicted and analyzed by means of ab initio and DFT methods. The results have been compared with the experimental values and with those from other database-related approaches. These dataset-based techniques are found to be particularly valuable because of the accurate and instantaneous prediction of the 13C chemical shifts. On the other hand, only a few quantum chemistry based approaches were showed to be the most precise to predict 1H chemical shifts and to elucidate unequivocally the 1H NMR spectra of the regioisomeric mixture under study. Special emphasis was put on incorporating the solvent effect, implicitly, or explicitly. The influence of the level of theory and basis set in the predicted values has also been discussed.

The ethylene/metal(0) and ethylene/metal(I) redox system: model ab initio calculations.

Ab initio calculations (coupled cluster with single and double excitations; CCSD) have been used to investigate the model redox systems ethylene:M(0) (M = Li, Na, K, Rb, Cs) and ethylene:M(I) (M = Be, Mg, Ca, Sr, Ba, Zn, Cd, Hg). Within C2v symmetry, the ground (2A1) states correspond to the charge distribution given in the title. The lowest (2B2) excited states correspond, somewhat counter intuitively, to the ethylene*-/=M(II)ion pair. These trends can be rationalized on the basis of simple electrostatic and configuration-mixing arguments that lead to two simple equations for predicting the electron-transfer energies for oxidation or reduction of the ethylene. The electron-transfer energies to the 2B2 ion pairs are dominated by the electrostatic ion-pairing energies.

Theoretical prediction of the enantiomeric excess in asymmetric catalysis. An alignment-independent molecular interaction field based approach.

[reaction: see text] The enantiomeric excess of three different asymmetric catalyses has been predicted in excellent agreement with the experiments using a 3D-QSPR approach. In particular, GRid INdependent Descriptors generated from molecular interaction fields together with a simple partial least-squares method were found to be adequate to describe the enantioselectivity induced by these metal-ligand complexes.

Characterisation of sulphoxides by atmospheric pressure ionisation mass spectrometry.

An observation that a series of proprietary compounds containing a methyl thiophenyl group all underwent metabolic S-oxidation, and that the product ion spectra of the resulting S-oxides showed methyl radical loss under low-energy atmospheric pressure ionisation tandem mass spectrometry (API-MS/MS) conditions, has led to an investigation of the fragmentation of commercially available sulphoxides. The phenyl methyl sulphoxides studied do lose methyl radicals under MS/MS conditions on triple quadrupole mass spectrometers. In addition, the phenyl sulphoxides, with simple substituents other than a methyl group, also showed a tendency to lose the substituent as a radical. It was concluded that radical loss from these simple sulphoxides was characteristic of S-oxidation of these molecules. Radical losses, such as those reported here, are used in-house to distinguish S-oxidation from N- and C-oxidation in metabolism studies.

Enhancing the effectiveness of virtual screening by fusing nearest neighbor lists: a comparison of similarity coefficients.

This paper evaluates the effectiveness of various similarity coefficients for 2D similarity searching when multiple bioactive target structures are available. Similarity searches using several different activity classes within the MDL Drug Data Report and the Dictionary of Natural Products databases are performed using BCI 2D fingerprints. Using data fusion techniques to combine the resulting nearest neighbor lists we obtain group recall results which, in many cases, are a considerable improvement on standard average recall values obtained for individual structures. It is shown that the degree of improvement can be related to the structural diversity of the activity class that is searched for, the best results being found for the most diverse groups. The group recall of active compounds using subsets of the class is also investigated: for highly self-similar activity classes, the group recall improvement saturates well before the full activity class size is reached. A rough correlation is found between the relative improvement using the group recall and the square of the number of unique compounds available in all of the merged lists. The Tanimoto coefficient is found unambiguously to be the best coefficient to use for the recovery of active compounds using multiple targets. Furthermore, when using the Tanimoto coefficient, the "MAX" fusion rule is found to be more effective than the "SUM" rule for the combination of similarity searches from multiple targets. The use of group recall can lead to improved enrichment in database searches and virtual screening.

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.