Exploring Structure-Dynamics-Function Relationship in Proteins, Protein: Ligand and Protein: Protein Systems through Computational Methods

The study focuses on understanding the dynamic nature of interactions between molecules and macromolecules. Molecular modeling and simulation technologies are employed to understand how the chemical constitution of the protein, specific interactions and dynamics of its structure provide the basis of its mechanism of function. The structure-dynamics-function relationship is investigated from quantum to macromolecular-assembly level, with applications in the field of rationale drug discovery and in improving efficiency of renewable sources of energy. Results presented include investigating the role of dynamics in the following: 1) In interactions between molecules: analyzing dynamic nature of a specific non-covalent interaction known as “anion-π [pi]” in RmlC protein. 2) In interactions between molecules and macromolecules: defining the structural basis of testosterone activation of GPRC6A. 3) In disrupting the function using specific substrate interactions: incorporating protein dynamics and flexibility in structure-based drug-discovery approach targeting the prothrombinase coagulation complex. 4) In interactions between macromolecules: elucidating the protein-protein binding and dynamics of electron-transport proteins, Ferrodoxin and Cytochrome c6, with Cyanobacterial Photosystem I

Targeting farnesyl pyrophosphate synthase of Trypanosoma cruzi by fragment-based lead discovery

Trypanosoma cruzi (T. cruzi) is the causative agent of Chagas disease (CD), which mostly affects underprivileged populations in South and Central America. The current standard of care for this disease are the two empirically discovered drugs benznidazole and nifurtimox. They show low efficacy, difficulties in administration and severe side effects. Moreover, there are T. cruzi strains that have formed resistances. Thus, the development of a safe and efficient drug is urgently needed. T. cruzi is dependent on isoprenoid biosynthesis as ergosterol and other 24 alkylsterols are essential metabolites that cannot be acquired by other mechanisms. Therefore, it was hypothesised that enzymes along this pathway are promising drug targets. A number of compounds targeting these enzymes were tested and have been shown to inhibit parasite growth. Among those enzymes is farnesyl pyrophosphate synthase (FPPS), a key branch-point enzyme in the isoprenoid pathway, which is in the focus of this work. It catalyses the synthesis of farnesyl pyrophosphate (FPP), a C15 building block in sterol biosynthesis and in protein prenylation of signalling proteins. Bisphosphonates (BPs) are known active site directed FPPS inhibitors, which exhibit ideal pharmacokinetics to target bone mineral and are used to treat bone diseases. BPs can also combat T. cruzi flagellates but are not ideal to treat CD due to their pharmacokinetics. In the search for new chemotypes, several non-BP inhibitors that bind to another pocket were found for human FPPS (hFPPS) by fragment based screening (FBS). Recently, it was shown that the product of FPPS, farnesyl pyrophosphate (FPP), can bind to this pocket and locks the enzyme in an open and inactive state, thus showing the allosteric character of this pocket. The current work aims at the discovery of non-BP inhibitors of T. cruzi FPPS (TcFPPS), which could be starting points for the development of a treatment against CD. Towards this goal, recombinant expression in E. coli cells and purification by means of IMAC and SEC yielded pure und homogenous TcFPPS (chapter 5.1). This includes unlabelled, 13C15N labelled and in vivo biotinylated avi-tagged TcFPPS. Furthermore, a novel, reliable, highly reproducible, and well diffracting crystallization system was established. The system exhibits excellent properties for FBS as it was compatible with different types of 96-well plates. Apo crystals were stable for up to 24 h in 15% DMSO and allowed collection of data sets with a diffraction limit of around 1.6 Å. The best achieved diffraction limit was 1.28 Å for a soaked TcFPPS crystal (PDB ID 6R09). The allosteric region in TcFPPS was investigated by means of sequence analysis and structural superimposition of various orthologous FPPSs (chapter 5.2). This revealed that the allosteric region is less conserved than the active site. Differences among residues in equivalent positions that form the allosteric site were observed, which is surprising if it is assumed that all FPPSs can be product inhibited as hFPPS. A remarkable finding is that residue Phe50 in TcFPPS is an exception in an otherwise highly conserved position. It causes steric hindrance of the pocket in TcFPPS. An attempt to reposition established allosteric inhibitors of hFPPS showed binding affinity to TcFPPS but the two obtained crystal structures demonstrated their binding to sites on the protein surface (sites S1 and S2, PDB IDs 6R08 and 6R07, respectively). The Novartis core and fluorine library (1336 and 482 compounds) were screened on TcFPPS, which resulted in 63 and 45 validated fragment hits, respectively (chapter 5.3). Performing the same screen with T. brucei FPPS (TbFPPS), the causative agent of African sleeping sickness, and counter screening on hFPPS led to unique, pairwise and triple binders demonstrating selectivity at the early stage of FBS. Strikingly, TcFPPS has generally more binders than TbFPPS, and TcFPPS has many unique hits when compared to TbFPPS. Subsequent crystallization experiments with the core library hits resulted in 3D structures of two TcFPPS complexes. One ligand binds to the homodimer interface (site S12) and the other one in the active site. The latter was identified by using the statistical analysis tool Pan-Dataset Density Analysis (PanDDA). FBS by X-ray crystallography at the XChem facility in Harwell, UK, and the HTXlab in Grenoble, France, were conducted (chapter 5.4). The XChem screen identified 35 fragment binders (PDB IDs 5QPD – Z, 5QQ0 – 9, 5QQA – C) in binding sites that were distributed over the entire protein. This includes the active site, the allosteric site, the homodimer interface, sites on the surface and a new site in close proximity to the active site. Strikingly, the first two fragments binding to the allosteric site of TcFPPS in its open state were identified. Rotation of the phenyl side chain of Phe50 led to opening of the former closed pocket. The HTXlab screen identified additional binders for the active and allosteric site. In total 1244 data sets were collected and analysed. This process was accelerated using PanDDA. The first fragment-to-lead optimization by means of virtual screening using the web-based platform ANCHOR.QUERY was based on fragment hit LUY (chapter 5.5). Compounds were synthesised using one-pot one-step multi-component reactions. Synthesis of 11 compounds (MCR 1 – 11) was successful, but poor solubility was detrimental in subsequent testing on TcFPPS and crystallization experiments did not lead to a structural model of a complex. A second fragment to lead optimization using a fragment merging approach for chemical optimization was based on the active site directed binders AWM, LVV, LUY, LDV and AWV (chapter 5.6). A library of 12 compounds (MCN 1 – 12) was synthesised by reductive amination. X-ray structures revealed unexpected binding modes for compounds MCN-1, -4 and -8. Instead of retaining the binding site of the fragment, the merged compounds bind to the surface directed binding site S1 (PDB IDs 6R09, 6R0A, 6R0B). Nevertheless, the 50 new crystal structures of TcFPPS fragment complexes discussed in this work will pave the way for future drug discovery campaigns for CD. The large diversity of the fragments’ scaffolds and different binding sites are potential starting points for inhibitors with different physicochemical properties and a novel mode of action that might help to overcome the limitations related to the BP scaffold

Role of the complement factor H-related protein 5 in renal disease by protein expression and molecular solution structural studies

Complement Factor H-Related 5 (CFHR5) belongs to the same complement family as the major regulator Factor H. CFHR5 comprises nine short complement regulator (SCR) domains. The duplication of the N-terminal SCR-1/2 domains causes CFHR5 nephropathy, a cause of kidney failure in Cypriots. To clarify the molecular basis of CFHR5 nephropathy, E. coli expression systems were developed for SCR-1 and SCR-1/2 of CFHR5, and recombinant CFHR5 SCR-1/9 was obtained from a commercial mammalian expression system. First, the domain arrangement of CFHR5 SCR-1/9 was studied by analytical ultracentrifugation and X-ray scattering. Sedimentation velocity reported a molecular mass of 134 kDa, indicating that CFHR5 is dimeric. The CFHR5 sedimentation coefficient of 5-6 S decreased with increased NaCl, showing that this became more extended. X-ray scattering also showed that CFHR5 was dimeric. The X-ray mean radius of gyration RG was 5.5 ± 0.2 nm, and its maximum length was 20 nm. This length is low compared to that of 32 nm for monomeric Factor H with 20 SCR domains, indicating that CFHR5 possessed a more compact SCR arrangement than that of Factor H. Atomistic scattering curve modelling of CFHR5 that involved Monte Carlo simulations to generate physically realistic atomistic SCR structures showed that CFHR5 possessed a folded-back compact domain structure. Second, sedimentation velocity showed that SCR-1 was monomeric, while SCR-1/2 was dimeric, thus locating a CFHR5 dimerization site to its N-terminus. In summary, the solution structure of CFHR5 is markedly more compact than previously thought, and its dimerization site was located to SCR-1/2. The perturbation of SCR-1/2 may have a major role in causing CFHR5 nephropathy

In Silico Design and Selection of CD44 Antagonists:implementation of computational methodologies in drug discovery and design

Drug discovery (DD) is a process that aims to identify drug candidates through a thorough evaluation of the biological activity of small molecules or biomolecules. Computational strategies (CS) are now necessary tools for speeding up DD. Chapter 1 describes the use of CS throughout the DD process, from the early stages of drug design to the use of artificial intelligence for the de novo design of therapeutic molecules. Chapter 2 describes an in-silico workflow for identifying potential high-affinity CD44 antagonists, ranging from structural analysis of the target to the analysis of ligand-protein interactions and molecular dynamics (MD). In Chapter 3, we tested the shape-guided algorithm on a dataset of macrocycles, identifying the characteristics that need to be improved for the development of new tools for macrocycle sampling and design. In Chapter 4, we describe a detailed reverse docking protocol for identifying potential 4-hydroxycoumarin (4-HC) targets. The strategy described in this chapter is easily transferable to other compounds and protein datasets for overcoming bottlenecks in molecular docking protocols, particularly reverse docking approaches. Finally, Chapter 5 shows how computational methods and experimental results can be used to repurpose compounds as potential COVID-19 treatments. According to our findings, the HCV drug boceprevir could be clinically tested or used as a lead molecule to develop compounds that target COVID-19 or other coronaviral infections. These chapters, in summary, demonstrate the importance, application, limitations, and future of computational methods in the state-of-the-art drug design process

Molecular dynamic simulation studies of the South African HIV-1 Integrase subtype C protein to understand the structural impact of naturally occurring polymorphisms

>Magister Scientiae - MScThe viral Integrase (IN) protein is an essential enzyme of all known retroviruses, including HIV-1. It is responsible for the insertion of viral DNA into the human genome. It is known that HIV-1 is highly diverse with a high mutation rate as evidenced by the presence of a large number of subtypes and even strains that have become resistant to antiretroviral drugs. It remains inconclusive what effect this diversity in the form of naturally occurring polymorphisms/variants exert on IN in terms of its function, structure and susceptibility to IN inhibitory antiretroviral drugs. South Africa is home to the largest HIV-1 infected population, with (group M) subtype C being the most prevalent subtype. An investigation into IN is therefore pertinent, even more so with the introduction of the IN strand-transfer inhibitor (INSTI) Dolutegravir (DTG)

Molecular dynamic simulation studies of the South African HIV-1 Integrase subtype C protein to understand the structural impact of naturally occurring polymorphisms

Masters of ScienceThe viral Integrase (IN) protein is an essential enzyme of all known retroviruses, including HIV-1. It is responsible for the insertion of viral DNA into the human genome. It is known that HIV-1 is highly diverse with a high mutation rate as evidenced by the presence of a large number of subtypes and even strains that have become resistant to antiretroviral drugs. It remains inconclusive what effect this diversity in the form of naturally occurring polymorphisms/variants exert on IN in terms of its function, structure and susceptibility to IN inhibitory antiretroviral drugs. South Africa is home to the largest HIV-1 infected population, with (group M) subtype C being the most prevalent subtype. An investigation into IN is therefore pertinent, even more so with the introduction of the IN strand-transfer inhibitor (INSTI) Dolutegravir (DTG). This study makes use of computational methods to determine any structural and DTG drug binding differences between the South African subtype C IN protein and the subtype B IN protein. The methods employed included homology modelling to predict a three-dimensional model for HIV-1C IN, calculating the change in protein stability after variant introduction and molecular dynamics simulation analysis to understand protein dynamics. Here we compared subtype C and B IN complexes without DTG and with DTG

A novel graph-based method for targeted ligand-protein fitting

A thesis submitted to the Faculty of Creative Arts, Technologies & Science, University of Bedfordshire, in partial & fulfilment of the requirements for the degree of Master of Philosophy.The determination of protein binding sites and ligand -protein fitting are key to understanding the functionality of proteins, from revealing which ligand classes can bind or the optimal ligand for a given protein, such as protein/ drug interactions. There is a need for novel generic computational approaches for representation of protein-ligand interactions and the subsequent prediction of hitherto unknown interactions in proteins where the ligand binding sites are experimentally uncharacterised. The TMSite algorithms read in existing PDB structural data and isolate binding sites regions and identifies conserved features in functionally related proteins (proteins that bind the same ligand). The Boundary Cubes method for surface representation was applied to the modified PDB file allowing the creation of graphs for proteins and ligands that could be compared and caused no loss of geometric data. A method is included for describing binding site features of individual ligands conserved in terms of spatial relationships allowed identification of 3D motifs, named fingerprints, which could be searched for in other protein structures. This method combine with a modification of the pocket algorithm allows reduced search areas for graph matching. The methods allow isolation of the binding site from a complexed protein PDB file, identification of conserved features among the binding sites of individual ligand types, and search for these features in sequence data. In terms of spatial conservation create a fingerprint ofthe binding site that can be sought in other proteins of/mown structure, identifYing putative binding sites. The approach offers a novel and generic method for the identification of putative ligand binding sites for proteins for which there is no prior detailed structural characterisation of protein/ ligand interactions. It is unique in being able to convert PDB data into graphs, ready for comparison and thus fitting of ligand to protein with consideration of chemical charge and in the future other chemica! properties

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

Structure-function relationships in a glycosyltransferase, a phosphatase and an oxidoreductase

Dissertation presented to obtain the Ph.D degree in BiochemistryEnzyme evolution is often constrained by aspects of catalysis. Mechanistically diverse enzymes evolved from a common ancestor still preserve those structural signatures essential to the core chemistry retained by all members of the superfamily. Indeed, these shared features allow superfamilies to be accurately classified, while derived features allow nested families and subfamilies to be identified in a hierarchical fashion. Accurate classification has helped elucidate mechanisms promoting functional diversification, for example catalytic promiscuity, and protein engineering by rational design. Nowadays, a holistic view of enzymes` regulatory mechanisms and catalytic proficiency is provided by the identification of conserved features of molecular architecture in combination with aspects of reaction dynamics. My work focused on the structural elucidation and analysis of three enzymes: a glycosyltransferase; a phosphatase and an oxidorreductase. “Snapshots” along the reaction coordinate of each enzyme were obtained by combining X-ray diffraction with “cryo-trapping” ligand-binding methods. These were used to characterize the molecular mechanisms involved in substrate recognition and binding. They were also used to distinguish between models proposed for the catalytic mechanisms of each enzyme, and provide insights into enzyme dynamics essential for catalysis and the stereo and regio-selective strategies at work.(...)Apoio financeiro da FCT e do POPH/FSE no âmbito do Quadro Comunitário de Apoio, Bolsa Nº SFRH/BD/23222/2005