Identifying prospective inhibitors against LdtMt5 from Mycobacterium tuberculosis as a potential drug target.

Masters Degree. University of KwaZulu-Natal, Durban.Tuberculosis (TB) caused by the bacterium, Mycobacterium tuberculosis (M.tb) has resulted in an unprecedented number of deaths over centuries. L,D-transpeptidase enzymes are known to play a crucial role in the biosynthesis of the cell wall, which confers resistance to most antibiotics. These enzymes catalyze the 3→3 peptidoglycan cross-links of the M.tb cell wall. Specific β-lactam antibiotics (carbapenems) have been reported to inhibit cell wall polymerization of M.tb and they inactivate L,D-transpeptidases through acylation. L,Dtranspeptidase 5 (LdtMt5) is a unique paralog and a vital protein in maintaining integrity of the cell wall specifically in peptidoglycan metabolism therefore making it an important protein target. Carbapenems inhibit LdtMt2, but do not show reasonable inhibitory activities against LdtMt5. We therefore sought to perform virtual screening in order to acquire potential inhibitors against LdtMt5 and to investigate the affinity and to calculate the binding free energies between LdtMt5 and potential inhibitors. Furthermore, we sought to investigate the nature of the transition state involved in the catalytic reaction mechanism; to determine the activation free energies of the mechanism using ONIOM through the thermodynamics and energetics of the reaction path and lastly to express, purify and perform inhibition studies on LdtMt5. A total of 12766 compounds were computationally screened from the ZINC database to identify potential leads against LdtMt5. Docking was performed using two different software programs. Molecular dynamics (MD) simulations were subsequently performed on compounds obtained through virtual screening. Density functional theory (DFT) calculations were then carried out to understand the catalytic mechanism of LdtMt5 with respect to β-lactam derivatives using a hybrid ONIOM quantum mechanics/molecular mechanics (QM/MM) method. LdtMt5 complexes with six selected β-lactam compounds were evaluated. Finally, a lyophilised pET28a-LdtMt5 was used to transform E. coli strain BL21 (DE3) and SDS-PAGE was used to verify the purity, molecular weight and protein profile determination. Finally, an in vitro binding thermodynamics analysis using isothermal titration calorimetry (ITC) was later on performed on a single compound (the strongest binder) from the final set, in a bid to further validate the calculated binding energy values. A number of compounds from four different antimicrobial classes (n = 98) were obtained from the virtual screening and those with docking scores ranging from -7.2 to -9.9 kcal mol-1 were considered for MD analysis (n = 37). A final set of 10 compounds which exhibited the greatest affinity, from four antibiotic classes was selected and Molecular Mechanics/Generalized Born iii Surface Area (MM-GBSA) binding free energies (ΔGbind) from the set were characterised. The calculated binding free energies ranged from -30.68 to -48.52 kcal mol-1 . The β-lactam class of compounds demonstrated the highest ΔGbind and also the greatest number of potential inhibitors. The DFT activation energies (∆G # ) obtained for the acylation of LdtMt5 by the six selected β-lactams were calculated as 13.67, 20.90, 22.88, 24.29, 27.86 and 28.26 kcal mol-1 . The ∆G# results from the 6-membered ring transition state (TS) revealed that all selected six βlactams were thermodynamically more favourable than previously calculated activation energy values for imipenem and meropenem complexed with LdtMt5. The results are also comparable to those observed for LdtMt2, however for compound 1 the values are considerably lower than those obtained for meropenem and imipenem in complex with LdtMt2, thus suggesting in theory that compound 1 is a more potent inhibitor of LdtMt5. We also report the successful expression and and purification of LdtMt5, however the molecule selected for the in vitro inhibition study gave a poor result. On further review, we concluded that the main cause of this outcome was due to the relatively low insolubility of the compound. The outcome of this study provides insight into the design of potential novel leads for LdtMt5. Our screening obtained ten novel compounds from four different antimicrobial classes. We suggest that further in vitro binding thermodynamics analysis of the novel compounds from the four classes, including the carbapenems be performed to evaluate inhibition of these compounds on LdtMt5. If the experimental observations suggest binding affinity to the protein, catalytic mechanistic studies can be undertaken. These results will also be used to verify or modify our computational model

Investigating the inhibition mechanism of L,D- transpeptidase 5 from Mycobacterium tuberculosis computational methods.

Doctoral Degree, University of KwaZulu-Natal, Durban.Abstract available in pdf

Metallo \u3b2 lactamase: reactivity and site directed evolution pathways addressed by computational approaches

The indiscriminate prescription of antibiotics by physicians, along with their incorrect use [1] 1 has increased the exposition of bacteria to antibiotics, and thus has created a favorable environment for the Darwinian evolution of resistant strains [2]. Further increase of drug resistance is caused by the unnecessary massive use of antibiotics (70% of the total market is in the US!) to animals crammed into the unhygienic crowded quarters of factories [3, 4]. Diseases like tubercolosis, gonorrhea, malaria, and childhood ear infections, are increasingly becoming hard to treat with antibiotic drugs, posing serious concern in the human public health [5, 6]. The problem is even more serious if one considers that already in 70\u2019s and 80\u2019s that modification of the chemical structure of the already known antibiotics turned out to be exhausted and, at the same time, pharmacological companies decided not design of totally new antibiotics [2]

Contribution of Mutant Analysis to the Understanding of Enzyme Catalysis: The Case of Class a Beta-Lactamases

Class A beta-lactamases represent a family of well studied enzymes. They are responsible for many antibiotic resistance phenomena and thus for numerous failures in clinical chemotherapy. Despite the facts that five structures are known at high resolution and that detailed analyses of enzymes modified by site-directed mutagenesis have been performed, their exact catalytic mechanism remains controversial. This review attempts to summarize and to discuss the many available data

QM/MM molecular dynamics studies of metal binding proteins

Mixed quantum-classical (quantum mechanical/molecular mechanical (QM/MM)) simulations have strongly contributed to providing insights into the understanding of several structural and mechanistic aspects of biological molecules. They played a particularly important role in metal binding proteins, where the electronic effects of transition metals have to be explicitly taken into account for the correct representation of the underlying biochemical process. In this review, after a brief description of the basic concepts of the QM/MM method, we provide an overview of its capabilities using selected examples taken from our work. Specifically, we will focus on heme peroxidases, metallo-\u3b2-lactamases, a-synuclein and ligase ribozymes to show how this approach is capable of describing the catalytic and/or structural role played by transition (Fe, Zn or Cu) and main group (Mg) metals. Applications will reveal how metal ions influence the formation and reduction of high redox intermediates in catalytic cycles and enhance drug metabolism, amyloidogenic aggregate formation and nucleic acid synthesis. In turn, it will become manifest that the protein frame directs and modulates the properties and reactivity of the metalions

Computational Approaches to Understanding the Structure, Dynamics, Functions, and Mechanisms of Various Bacterial Proteins

The 3D structure of a protein can be fundamentally useful for understanding protein function. In the absence of an experimentally determined structure, the most common way to obtain protein structures is to use homology modeling, or the mapping of the target sequence onto a closely related homolog with an available structure. However, despite recent efforts in structural biology, the 3D structures of many proteins remain unknown. Recent advances in genomic and metagenomic sequencing coupled with coevolution analysis and protein structure prediction have allowed for highly accurate models of proteins that were previously considered intractable to model due to the lack of suitable templates. Structural models obtained from homology modeling, coevolution-based modeling, or crystallography can then be used with other computational tools such as small molecule docking or molecular dynamics (MD) simulations to help understand protein function, dynamics, and mechanism.Here coevolution-based modeling was used to build a structural model of the HgcAB complex involved in mercury methylation (Chapter I). Based on the model it was proposed that conserved cysteines in HgcB are involved in shuttling mercury, methylmercury, or both. MD simulations and docking to a homology model of E. coli inosine monophosphate dehydrogenase (IMPDH) provided insights into how a single amino acid mutation could relieve inhibition by altering protein structure and dynamics (Chapter II). Coevolution-based structure prediction was also combined with docking, and experimental activity data to generate machine learning models that predict enzyme substrate scope for a series of bacterial nitrilases (Chapter III). Machine learning was also used to identify physicochemical properties that describe outer membrane permeability and efflux in E. coli and P. aeruginosa and new efflux pump inhibitors for the E. coli AcrAB-TolC efflux pump were identified using existing physicochemical guidelines in combination with small molecule docking to a homology model of AcrA (Chapter IV). Lastly, quantum mechanical/molecular mechanical simulations were used to study the mechanism of a key proton transfer step in Toho-1 beta-lactamase using experimentally determined structures of both the apo and cefotaxime-bound forms. These simulations revealed that substrate binding promotes catalysis by enhancing the favorability of this initial proton transfer step (Chapter V)

The role of the DSB system in antimicrobial resistance

Extensive use of antibiotics in medicine and agriculture has led to increasing emergence of antimicrobial resistance in bacterial populations. Dwindling resources in the discovery of novel active compound leads and the increasing demands for safety and efficacy of new drugs mean that we are now faced with treatment failures due to multi-drug resistant pathogens. In the quest for new targets that will enable us to counter antibiotic resistance, it is often ignored that many resistance mechanisms precede the clinical use of antibiotics. Instead, the ability to adapt, survive and bypass the toxicity of many chemical compounds is wired within the bacterial genome. Continuous inter-strain and inter-species competition have given microorganisms tools to thrive under conditions of chemical warfare. Recognising this is important when characterising mechanisms underpinning bacterial antimicrobial resistance, as it can lead to novel strategies that can help us bypass it. The work described here explores the connection between the disulfide bond formation system, a key oxidative protein folding pathway in the cell envelope of Gram-negative bacteria, and two widespread antimicrobial resistance mechanisms, b-lactamase catalysed hydrolysis of b-lactam antibiotics and efflux-mediated drug expulsion. It is demonstrated that oxidative-protein-folding-mediated proteostasis is crucial for both resistance mechanisms, and its inhibition can sensitise multidrug-resistant pathogens to existing antibiotics. Preliminary results from an experimental evolution approach, set the scene for future exploration of the importance of disulfide linkages for the capacity of b-lactamase enzymes to evolve under selective pressure. Together, these findings aim to address the mechanistic basis of a new avenue for antibiotic adjuvant therapy, whereby targeting a non-essential process would allow us to potentiate existing antibiotics towards previously resistant bacterial strains. With novel essential targets against bacteria being scarce, adjuvant approaches like this one could prolong the use and efficacy of existing drugs against some of the most resistant Gram-negative pathogens.Open Acces

On the origins of enzyme inhibitor selectivity and promiscuity: a case study of protein kinase binding to staurosporine

Protein kinases are important regulatory enzymes in signal transduction and in cell regulation. Understanding inhibition mechanisms of kinases is important for the further development of new therapies for cancer and inflammatory diseases. I have developed a statistical approach based on the Mantel test to find the relationship between the shapes of ATP binding sites and their affinities for inhibitors. My shape-based dendrogram shows clustering of the kinases based on similarity in shape. I investigate the pocket in terms of conservation of surrounding amino acids and atoms in order to identify the key determinants of ligand binding. I find that the most conserved regions are the main chain atoms in the hinge region and I show that the tetrahydropyran ring of staurosporine causes induced-fit of the glycine rich loop. I apply multiple linear regression to select distances measured between the distinctive parts of residues which correlate with the binding constants. This method allows me to understand the importance of the size of the gatekeeper residue and the closure between the first glycine of the GXGXXG motif and the aspartate of the DFG loop, which act together to promote tight binding to staurosporine. I also find that the greater the number of hydrogen bonds made by the kinase around the methylamine group of staurosporine, the tighter the binding to staurosporine. The website I have developed allows a better understanding of cross reactivity and may be useful for narrowing down the options for a synthetic strategy to design kinase inhibitors.This work was supported by the Royal Thai Government