Structure of chorismate synthase from Mycobacterium tuberculosis

Unraveling the possible inhibitors for Chorismate synthase to combat tuberculosis using in silico approach

Tuberculosis antibiotic resistance is a huge concern to the global population. The goal of this study was to find new and effective compounds to treat multidrug-resistant tuberculosis by targeting Chorismate synthase (CS), a crucial enzyme for Mycobacterium tuberculosis survival (MbT). The potential of a library of compounds as selective anti - tuberculosis drugs was investigated. Docking was first conducted using MoE to determine the effectiveness of the compounds. Molecular docking studies followed by MD simulation studies (total of 500 ns) in combination with free energy calculations grade the ligands in terms of their binding affinities. In the ligand bound state of the CS, MD simulations revealed a change from stretched to bended motional shift in loop L19. The RMSF analysis also revealed this flexibility, which was confirmed by visual inspection of L19 at various time intervals during the experiment. It appears that ZF1(-25.43Kcal/mol) and ZF2 (-22.04Kcal/mol) form hbonds and have a high binding energy in the active region of protein. Residues wise distribution of binding energy reveals that Arg144, Trp4, Thr6, and L19 amino acid residues are engaged in binding of CS with inhibitors. In summary, the findings suggest that compounds ZF1 and ZF2 may be more effective and selective anti-TB agents than currently available drugs. Also the role of L19, mediated by αH9 and αH5 in the retention of ligand inside the active pocket, through the formation of lid was also revealed. This knowledge will aid in the discovery of drugs that are potent CS inhibitors. More experimental research and a better understanding of the structure-activity relationship could aid in the development of possible candidates with better CS inhibition.Communicated by Ramaswamy H. Sarma.

Chorismate mutase peptide antibody enables specific detection of Acanthamoeba

Accurate and rapid diagnosis of Acanthamoeba keratitis (AK) is difficult. Although the diagnostic procedure for AK has improved, further development and effective diagnostic tool utilization for AK need to continue. Chorismate mutase is a key regulatory enzyme involved in the shikimate pathway, a metabolic pathway absent in mammals but central for amino acid biosynthesis in bacteria, fungi, algae, and plants. In this study, we describe the identification and production of a polyclonal peptide antibody targeting chorismate mutase secreted by A. castellanii, which could be used for AK diagnosis. Western blot was performed using the protein lysates and conditioned media of the human corneal epithelial (HCE) cells, non-pathogenic Acanthamoeba, pathogenic Acanthamoeba, clinical isolate of Acanthamoeba spp., and other causes of keratitis such as Fusarium solani, Pseudomonas aeruginosa, and Staphylococcus aureus. Polyclonal antibodies raised against A. castellanii chorismate mutase specifically interacted with lysates of Acanthamoeba origin and their culture media, while such interactions were not observed from other samples. Acanthamoeba-specificity of chorismate mutase was also confirmed using immunocytochemistry after co-culturing Acanthamoeba with HCE cells. Specific binding of the chorismate mutase antibody to Acanthamoeba was observed, which were absent in the case of HCE cells. These results indicate that the chorismate mutase antibody of Acanthamoeba may serve as a method for rapid and differential Acanthamoeba identification.

Mycobacterium tuberculosis Shikimate Pathway Enzymes as Targets for the Rational Design of Anti-Tuberculosis Drugs

Roughly a third of the world’s population is estimated to have latent Mycobacterium tuberculosis infection, being at risk of developing active tuberculosis (TB) during their lifetime. Given the inefficacy of prophylactic measures and the increase of drug-resistant M. tuberculosis strains, there is a clear and urgent need for the development of new and more efficient chemotherapeutic agents, with selective toxicity, to be implemented on patient treatment. The component enzymes of the shikimate pathway, which is essential in mycobacteria and absent in humans, stand as attractive and potential targets for the development of new drugs to treat TB. This review gives an update on published work on the enzymes of the shikimate pathway and some insight on what can be potentially explored towards selective drug development.

How Docking Programs Work

Protein-ligand docking simulations are of central interest for computer-aided drug design. Docking is also of pivotal importance to understand the structural basis for protein-ligand binding affinity. In the last decades, we have seen an explosion in the number of three-dimensional structures of protein-ligand complexes available at the Protein Data Bank. These structures gave further support for the development and validation of in silico approaches to address the binding of small molecules to proteins. As a result, we have now dozens of open source programs and web servers to carry out molecular docking simulations. The development of the docking programs and the success of such simulations called the attention of a broad spectrum of researchers not necessarily familiar with computer simulations. In this scenario, it is essential for those involved in experimental studies of protein-ligand interactions and biophysical techniques to have a glimpse of the basics of the protein-ligand docking simulations. Applications of protein-ligand docking simulations to drug development and discovery were able to identify hits, inhibitors, and even drugs. In the present chapter, we cover the fundamental ideas behind protein-ligand docking programs for non-specialists, which may benefit from such knowledge when studying molecular recognition mechanism.

Docking with GemDock

GEMDOCK is a protein-ligand docking software that makes use of an elegant biologically inspired computational methodology based on the differential evolution algorithm. As any docking program, GEMDOCK has two major features to predict the binding of a small-molecule ligand to the binding site of a protein target: the search algorithm and the scoring function to evaluate the generated poses. The GEMDOCK scoring function uses a piecewise potential energy function integrated into the differential evolutionary algorithm. GEMDOCK has been applied to a wide range of protein systems with docking accuracy similar to other docking programs such as Molegro Virtual Docker, AutoDock4, and AutoDock Vina. In this chapter, we explain how to carry out protein-ligand docking simulations with GEMDOCK. We focus this tutorial on the protein target cyclin-dependent kinase 2.

Electrostatic Energy in Protein-Ligand Complexes

Computational analysis of protein-ligand interactions is of pivotal importance for drug design. Assessment of ligand binding energy allows us to have a glimpse of the potential of a small organic molecule as a ligand to the binding site of a protein target. Considering scoring functions available in docking programs such as AutoDock4, AutoDock Vina, and Molegro Virtual Docker, we could say that they all rely on equations that sum each type of protein-ligand interactions to model the binding affinity. Most of the scoring functions consider electrostatic interactions involving the protein and the ligand. In this chapter, we present the main physics concepts necessary to understand electrostatics interactions relevant to molecular recognition of a ligand by the binding pocket of a protein target. Moreover, we analyze the electrostatic potential energy for an ensemble of structures to highlight the main features related to the importance of this interaction for binding affinity.

SAnDReS: A Computational Tool for Docking

Since the early 1980s, we have witnessed considerable progress in the development and application of docking programs to assess protein-ligand interactions. Most of these applications had as a goal the identification of potential new binders to protein targets. Another remarkable progress is taking place in the determination of the structures of protein-ligand complexes, mostly using X-ray diffraction crystallography. Considering these developments, we have a favorable scenario for the creation of a computational tool that integrates into one workflow all steps involved in molecular docking simulations. We had these goals in mind when we developed the program SAnDReS. This program allows the integration of all computational features related to modern docking studies into one workflow. SAnDReS not only carries out docking simulations but also evaluates several docking protocols allowing the selection of the best approach for a given protein system. SAnDReS is a free and open-source (GNU General Public License) computational environment for running docking simulations. Here, we describe the combination of SAnDReS and AutoDock4 for protein-ligand docking simulations. AutoDock4 is a free program that has been applied to over a thousand receptor-ligand docking simulations. The dataset described in this chapter is available for downloading at https://github.com/azevedolab/sandres.

Van der Waals Potential in Protein Complexes

Van der Waals forces are determinants of the formation of protein-ligand complexes. Physical models based on the Lennard-Jones potential can estimate van der Waals interactions with considerable accuracy and with a computational complexity that allows its application to molecular docking simulations and virtual screening of large databases of small organic molecules. Several empirical scoring functions used to evaluate protein-ligand interactions approximate van der Waals interactions with the Lennard-Jones potential. In this chapter, we present the main concepts necessary to understand van der Waals interactions relevant to molecular recognition of a ligand by the binding pocket of a protein target. We describe the Lennard-Jones potential and its application to calculate potential energy for an ensemble of structures to highlight the main features related to the importance of this interaction for binding affinity.

Homology Modeling of Protein Targets with MODELLER

Homology modeling is a computational approach to generate three-dimensional structures of protein targets when experimental data about similar proteins are available. Although experimental methods such as X-ray crystallography and nuclear magnetic resonance spectroscopy successfully solved the structures of nearly 150,000 macromolecules, there is still a gap in our structural knowledge. We can fulfill this gap with computational methodologies. Our goal in this chapter is to explain how to perform homology modeling of protein targets for drug development. We choose as a homology modeling tool the program MODELLER. To illustrate its use, we describe how to model the structure of human cyclin-dependent kinase 3 using MODELLER. We explain the modeling procedure of CDK3 apoenzyme and the structure of this enzyme in complex with roscovitine.

Hydrogen Bonds in Protein-Ligand Complexes

Fast and reliable evaluation of the hydrogen bond potential energy has a significant impact in the drug design and development since it allows the assessment of large databases of organic molecules in virtual screening projects focused on a protein of interest. Semi-empirical force fields implemented in molecular docking programs make it possible the evaluation of protein-ligand binding affinity where the hydrogen bond potential is a common term used in the calculation. In this chapter, we describe the concepts behind the programs used to predict hydrogen bond potential energy employing semi-empirical force fields as the ones available in the programs AMBER, AutoDock4, TreeDock, and ReplicOpter. We described here the 12-10 potential and applied it to evaluate the binding affinity for an ensemble of crystallographic structures for which experimental data about binding affinity are available.

Rational Discovery of (+) (S) Abscisic Acid as a Potential Antifungal Agent: a Repurposing Approach

Fungal infections are spreading widely worldwide, and the types of treatment are limited due to the lack of diverse therapeutic agents and their associated side effects and toxicity. The discovery of new antifungal classes is vital and critical. We discovered the antifungal activity of abscisic acid through a rational drug design methodology that included the building of homology models for fungal chorismate mutases and a pharmacophore model derived from a transition state inhibitor. Ligand-based virtual screening resulted in some hits that were filtered using molecular docking and molecular dynamic simulations studies. Both in silico methods and in vitro antifungal assays were used as tools to select and validate the abscisic acid repurposing. Abscisic acid inhibition assays confirmed the inhibitory effect of abscisic acid on chorismate mutase through the inhibition of phenylpyruvate production. The repositioning of abscisic acid, the well-known and naturally occurring plant growth regulator, as a potential antifungal agent because of its suggested action as an inhibitor to several fungal chorismate mutases was the main result of this work.

Insights into a divergent phenazine biosynthetic pathway governed by a plasmid-born esmeraldin gene cluster

Phenazine-type metabolites arise from either phenazine-1-carboxylic acid (PCA) or phenazine-1,6-dicarboxylic acid (PDC). Although the biosynthesis of PCA has been studied extensively, PDC assembly remains unclear. Esmeraldins and saphenamycin, the PDC originated products, are antimicrobial and antitumor metabolites isolated from Streptomyces antibioticus Tü 2706. Herein, the esmeraldin biosynthetic gene cluster was identified on a dispensable giant plasmid. Twenty-four putative esm genes were characterized by bioinformatics, mutagenesis, genetic complementation, and functional protein expressions. Unlike enzymes involved in PCA biosynthesis, EsmA1 and EsmA2 together decisively promoted the PDC yield. The resulting PDC underwent a series of conversions to give 6-acetylphenazine-1-carboxylic acid, saphenic acid, and saphenamycin through a unique one-carbon extension by EsmB1-B5, a keto reduction by EsmC, and an esterification by EsmD1-D3, the atypical polyketide sythases, respectively. Two transcriptional regulators, EsmT1 and EsmT2, are required for esmeraldin production.

New tuberculosis drug development: targeting the shikimate pathway

BACKGROUND

Tuberculosis (TB) remains a leading cause of morbidity and mortality worldwide, yet no new drugs have been developed in the last 40 years.

OBJECTIVE

The exceedingly lengthy TB chemotherapy and the increasing emergence of drug resistance complicated by HIV co-infection call for the development of new TB drugs. These problems are further compounded by a poor understanding of the biology of persister bacteria.

METHODS

New molecular tools have offered insights into potential new drug targets, particularly the enzymes of the shikimate pathway, which is the focus of this review.

RESULTS/CONCLUSION

Shikimate pathway enzymes, especially shikimate kinase, may offer attractive targets for new TB drug and vaccine development.

Predicted essential proteins of Plasmodium falciparum for potential drug targets

OBJECTIVE

To identify novel drug targets for treatment of Plasmodium falciparum.

METHODS

Local BLASTP were used to find the proteins non-homologous to human essential proteins as novel drug targets. Functional domains of novel drug targets were identified by InterPro and Pfam, 3D structures of potential drug targets were predicated by the SWISS-MODEL workspace. Ligands and ligand-binding sites of the proteins were searched by Ef-seek.

RESULTS

Three essential proteins were identified that might be considered as potential drug targets. AAN37254.1 belonged to 1-deoxy-D-xylulose 5-phosphate reductoisomerase, CAD50499.1 belonged to chorismate synthase, CAD51220.1 belonged to FAD binging 3 family, but the function of CAD51220.1 was unknown. The 3D structures, ligands and ligand-binding sites of AAN37254.1 and CAD50499.1 were successfully predicated.

CONCLUSIONS

Two of these potential drug targets are key enzymes in 2-C-methyl-d-erythritol 4-phosphate pathway and shikimate pathway, which are absent in humans, so these two essential proteins are good potential drug targets. The function and 3D structures of CAD50499.1 is still unknown, it still need further study.

Structural analysis of chorismate synthase from Plasmodium falciparum: a novel target for antimalaria drug discovery

The shikimate pathway in Plasmodium falciparum provides several targets for designing novel antiparasitic agents for the treatment of malaria. Chorismate synthase (CS) is a key enzyme in the shikimate pathway which catalyzes the seventh and final step of the pathway. P. falciparum chorismate synthase (PfCS) is unique in terms of enzymatic behavior, cellular localization and in having two additional amino acid inserts compared to any other CS. The structure of PfCS along with cofactor FMN was predicted by homology modeling using crystal structure of Helicobacter pylori chorismate synthase (HpCS). The quality of the model was validated using structure analysis servers and molecular dynamics. Dimeric form of PfCS was generated and the FMN binding mechanism involving movement of loop near active site has been proposed. Active site pocket has been identified and substrate 5-enolpyruvylshikimate 3-phosphate (EPSP) along with screened potent inhibitors has been docked. The study resulted in identification of putative inhibitors of PfCS with binding efficiency in nanomolar range. The selected putative inhibitors could lead to the development of anti-malarial drugs.

Protein targets for structure-based anti-Mycobacterium tuberculosis drug discovery

Mycobacterium tuberculosis, which belongs to the genus Mycobacterium, is the pathogenic agent for most tuberculosis (TB). As TB remains one of the most rampant infectious diseases, causing morbidity and death with emergence of multi-drug-resistant and extensively-drug-resistant forms, it is urgent to identify new drugs with novel targets to ensure future therapeutic success. In this regards, the structural genomics of M. tuberculosis provides important information to identify potential targets, perform biochemical assays, determine crystal structures in complex with potential inhibitor(s), reveal the key sites/residues for biological activity, and thus validate drug targets and discover novel drugs. In this review, we will discuss the recent progress on novel targets for structure-based anti-M. tuberculosis drug discovery.

Validation of coevolving residue algorithms via pipeline sensitivity analysis: ELSC and OMES and ZNMI, oh my!

Correlated amino acid substitution algorithms attempt to discover groups of residues that co-fluctuate due to either structural or functional constraints. Although these algorithms could inform both ab initio protein folding calculations and evolutionary studies, their utility for these purposes has been hindered by a lack of confidence in their predictions due to hard to control sources of error. To complicate matters further, naive users are confronted with a multitude of methods to choose from, in addition to the mechanics of assembling and pruning a dataset. We first introduce a new pair scoring method, called ZNMI (Z-scored-product Normalized Mutual Information), which drastically improves the performance of mutual information for co-fluctuating residue prediction. Second and more important, we recast the process of finding coevolving residues in proteins as a data-processing pipeline inspired by the medical imaging literature. We construct an ensemble of alignment partitions that can be used in a cross-validation scheme to assess the effects of choices made during the procedure on the resulting predictions. This pipeline sensitivity study gives a measure of reproducibility (how similar are the predictions given perturbations to the pipeline?) and accuracy (are residue pairs with large couplings on average close in tertiary structure?). We choose a handful of published methods, along with ZNMI, and compare their reproducibility and accuracy on three diverse protein families. We find that (i) of the algorithms tested, while none appear to be both highly reproducible and accurate, ZNMI is one of the most accurate by far and (ii) while users should be wary of predictions drawn from a single alignment, considering an ensemble of sub-alignments can help to determine both highly accurate and reproducible couplings. Our cross-validation approach should be of interest both to developers and end users of algorithms that try to detect correlated amino acid substitutions.

Molecular modeling and dynamics studies of Shikimate Kinase from Bacillus anthracis

Bacillus anthracis has been used as weapon in bioterrorist activities, with high mortality, despite anti-microbial treatment, which strongly indicates a need of new drugs to treat anthrax. Shikimate Pathway is a seven-step biosynthetic route which generates chorismic acid. The shikimate pathway is essential for many pathological organisms, whereas it is absent in mammals. Therefore, these enzymes are potential targets for the development of non-toxic anti-microbial agents and herbicides and have been submitted to intensive structural studies. Shikimate Kinase is the fifth enzyme of shikimate pathway and catalyzes the specific phosphorylation of the 3-hydroxyl group of shikimate using ATP as a co-substrate, resulting in shikimate-3-phosphate and ADP. The present work describes for the first time a structural model for the Shikimate Kinase from B. anthracis using molecular modeling approach and molecular dynamics simulations. This study was able to identify the main residues of the ATP-binding and the shikimate pockets responsible for ligand affinities. Analysis of the molecular dynamics simulations indicates the structural features responsible for the stability of the structure. This study may help in the identification of new inhibitors for this enzyme.

The Mycobacterium tuberculosis Rv2540c DNA sequence encodes a bifunctional chorismate synthase

BACKGROUND

The emergence of multi- and extensively-drug resistant Mycobacterium tuberculosis strains has created an urgent need for new agents to treat tuberculosis (TB). The enzymes of shikimate pathway are attractive targets to the development of antitubercular agents because it is essential for M. tuberculosis and is absent from humans. Chorismate synthase (CS) is the seventh enzyme of this route and catalyzes the NADH- and FMN-dependent synthesis of chorismate, a precursor of aromatic amino acids, naphthoquinones, menaquinones, and mycobactins. Although the M. tuberculosis Rv2540c (aroF) sequence has been annotated to encode a chorismate synthase, there has been no report on its correct assignment and functional characterization of its protein product.

RESULTS

In the present work, we describe DNA amplification of aroF-encoded CS from M. tuberculosis (MtCS), molecular cloning, protein expression, and purification to homogeneity. N-terminal amino acid sequencing, mass spectrometry and gel filtration chromatography were employed to determine identity, subunit molecular weight and oligomeric state in solution of homogeneous recombinant MtCS. The bifunctionality of MtCS was determined by measurements of both chorismate synthase and NADH:FMN oxidoreductase activities. The flavin reductase activity was characterized, showing the existence of a complex between FMNox and MtCS. FMNox and NADH equilibrium binding was measured. Primary deuterium, solvent and multiple kinetic isotope effects are described and suggest distinct steps for hydride and proton transfers, with the former being more rate-limiting.

CONCLUSION

This is the first report showing that a bacterial CS is bifunctional. Primary deuterium kinetic isotope effects show that C4-proS hydrogen is being transferred during the reduction of FMNox by NADH and that hydride transfer contributes significantly to the rate-limiting step of FMN reduction reaction. Solvent kinetic isotope effects and proton inventory results indicate that proton transfer from solvent partially limits the rate of FMN reduction and that a single proton transfer gives rise to the observed solvent isotope effect. Multiple isotope effects suggest a stepwise mechanism for the reduction of FMNox. The results on enzyme kinetics described here provide evidence for the mode of action of MtCS and should thus pave the way for the rational design of antitubercular agents.