Structural and Dynamic Studies of Enzymes involved in Multidrug Resistant Pathogens

Abstract

The flexible and dynamic nature of biological macromolecules has been well explored using experimentally determined structures in different environments. Synergistically, the experimental studies when complemented with conformational changes in biological molecules culminated the field of computation biology and drug discovery to the zenith of success, Structural details of a particular pathway between the end points with respect to time is not directly accessible. Such data can only be gathered using advanced computational approaches such as Molecular Dynamic Simulation and Quantum Mechanics calculations. Drug design and discovery is one of the main areas of research where bioinformatics approaches have an ever increasing impact. The pace of antibiotics discovery has been greatly decreased in 21st century due to the challenges of antibiotic resistance which has been listed as one of the greatest threats that has put global health system under pressure. The application of advanced computational techniques can aid in accelerating the process of designing novel compounds that can address the fundamental challenges of drug resistance. Keeping this in view, critical multidrug resistance pathogens including Enterobacter aerogenes, Orientia tsutsugamushi, Staphylococcus lugdunensis have been targeted to identify potential drug candidates and explore the conformational dynamics of receptor-ligand interactions. In addition to this, due to increased prevalence of bacterial infections reported in diabetic patients, comparative dynamics studies have also been conducted on negative regulator of insulin signaling pathways, Protein Tyrosine Phosphatase 1B (PTP1B) to identify Zinc containing ligands as inhibitors which has given us a final clue about the future use of Zinc containing drugs. The research work included in this dissertation addresses the problem of multidrug resistance by using a blend of advanced computational techniques in line with the experimental verification involving the large-scale screening of compound databases. This further implies and identifies potent inhibitors against the selected drug target proteins. In addition to this, molecular modeling for Zinc-based ligands have also been performed to explore the inhibition potential of metal-based inhibitors. MD simulations have also been employed to understand the receptor ligand dynamics and conformational changes that occur after the binding of ligand to the protein. The overall flow of the work starts with giving a brief overview of multidrug resistance, its implications and role of bioinformatics in in silico drug design and discovery. Following this, a theoretical overview of computational methods used in discussed research studies have been described in detail. xiv As the life-saving antibiotics are vulnerable to inactivation by a primary resistance determinant i.e., β-lactamase in multi-drug resistance pathogens. In the third chapter, we have exploited the strategy of novel Site-Identification by Ligand Competitive Saturation (SILCS) technology-based method to scrutinize potential inhibitor against extended spectrum β-lactamase (CMY-10). Furthermore, we have also applied combination therapy approach in which the β lactamase enzyme of the pathogen is occupied by the β-lactamase inhibitor while allowing the β lactam antibiotic to act against its penicillin-binding protein target. Inhibitor discovery applied the SILCS to map the functional group requirements of the β-lactamase CMY-10 and generate pharmacophore models of active site. SILCS-MC, Ligand-grid Free Energy (LGFE) analysis and Machine-learning based random-forest (RF) scoring methods were then utilized to screen and filter a library of 700,000 compounds. From the computational screening 74 compounds were subjected to experimental validation. As an unambiguous finding of this collection of experiments both computationally and experimentally it was established that compounds identified have the potential to be used in combination therapy. This further yields us the non-β-lactam-based β lactamase inhibitors against multidrug resistant clinical isolates that have been found resistant against antibiotics of last resort. The fourth chapter discusses Orientia tsutsugamushi, a pathogen which has also been found resistant to various classes of antibiotics such as penicillins, gentamycin and cephalosporins. In this series of our work subtractive proteomics approach is employed which revealed Fis as a potential drug target. This protein is involved in two component system (TCS), a signaling pathway crucial for bacterial survival under variable circumstances. Binding pattern investigation and simulation studies have revealed compound-356 as a potential inhibitor in both chains A and B of the Fis protein. Significant conformational changes including a unique hinge motion were observed in the DNA binding domain. The presence of salt bridge between Glu 910 and Arg 417, rearrangement of interaction residues and displacement of ATP in the central AAA+ domain upon binding to the inhibitor were also observed playing a role in stabilizing the protein structure. In the next chapter, research work conducted on Farnesyl diphosphate synthase protein of S. lugdunensis previously was extended in the current study in order to better compare the potential of proposed inhibitors with the reported drugs against the targeted pathogen. Proposed inhibitors exhibited increased binding affinity and stability in both the conventional and allosteric xv pocket of the protein compared to the reported drugs which shows the potential of these compounds to act as promising drugs in times to come. The following section has discussed the role of Zinc(II) complexes as antidiabetic targets against Protein Tyrosine Phosphatase 1B (PTP1B) which negatively regulates insulin signaling pathways. The study has employed advanced computational methods to explore the binding orientation of Zinc(II) complexes in the active site of apoenzyme, phosphoenzyme, and TSA 2 of PTP1B. Metal ion modeling was performed for Zinc metal center (Zn-OOOO) utilizing a Python based Metal Center Parameter Builder (MCPB.py). Findings obtained suggest that Zinc(II) complex binds to structurally and functionally important residues in open and closed conformation as well as in the phosphorylated state of the enzyme. It was observed that during the phosphorylation of catalytic residue cysteine in a closed conformation, the Zinc(II) complex forms significant interactions with PHE182, VAL184, GLY183, and PRO180 while pushing away Q-loop GLN262 which is crucial for the hydrolysis of phosphoenzyme. Subsequently, the reported inhibitor has also demonstrated its potential to function as allosteric modulator of the enzyme occupying catalytic WPD loop residues. These results hint towards a metallodrug approach that builds on the research evidence of inhibition effects of Zn2+ in the binding pocket of PTP1B. The prominent finding of utilizing Zinc II complexes preferably in comparison of exploiting Zinc ion alone, presented by this work is directly related to clinical applications. The final section of this dissertation elaborates the molecular docking studies conducted on bioactive heteroleptic Bismuth (V) carboxylates and Bismuth (III) complexes with substituted hydrazones which were synthesized and experimentally studied in the Department of Chemistry, Quaid-i-Azam University. Experimental studies were then followed by computational analysis in which docking studies were employed for exploring ligand-receptor interactions. Binding affinity of targeted compounds extracted against helicobacter pylori urease (1E9Y), human pancreatic alpha amylase (5U3A), and epidermal growth factor receptor (EGFR) tyrosine kinase (1M17) proteins have been reported.