Structure- and Ligand-Based Design of Novel Antimicrobial Agents

The use of computer based techniques in the design of novel therapeutic agents is a rapidly emerging field. Although the drug-design techniques utilized by Computational Medicinal Chemists vary greatly, they can roughly be classified into structure-based and ligand-based approaches. Structure-based methods utilize a solved structure of the design target, protein or DNA, usually obtained by X-ray or NMR methods to design or improve compounds with activity against the target. Ligand-based methods use active compounds with known affinity for a target that may yet be unresolved. These methods include Pharmacophore-based searching for novel active compounds or Quantitative Structure-Activity Relationship (QSAR) studies. The research presented here utilized both structure and ligand-based methods against two bacterial targets: Bacillus anthracis and Mycobacterium tuberculosis. The first part of this thesis details our efforts to design novel inhibitors of the enzyme dihydropteroate synthase from B. anthracis using crystal structures with known inhibitors bound. The second part describes a QSAR study that was performed using a series of novel nitrofuranyl compounds with known, whole-cell, inhibitory activity against M. tuberculosis. Dihydropteroate synthase (DHPS) catalyzes the addition of p-amino benzoic acid (pABA) to dihydropterin pyrophosphate (DHPP) to form pteroic acid as a key step in bacterial folate biosynthesis. It is the traditional target of the sulfonamide class of antibiotics. Unfortunately, bacterial resistance and adverse effects have limited the clinical utility of the sulfonamide antibiotics. Although six bacterial crystal structures are available, the flexible loop regions that enclose pABA during binding and contain key sulfonamide resistance sites have yet to be visualized in their functional conformation. To gain a new understanding of the structural basis of sulfonamide resistance, the molecular mechanism of DHPS action, and to generate a screening structure for high-throughput virtual screening, molecular dynamics simulations were applied to model the conformations of the unresolved loops in the active site. Several series of molecular dynamics simulations were designed and performed utilizing enzyme substrates and inhibitors, a transition state analog, and a pterin-sulfamethoxazole adduct. The positions of key mutation sites conserved across several bacterial species were closely monitored during these analyses. These residues were shown to interact closely with the sulfonamide binding site. The simulations helped us gain new understanding of the positions of the flexible loops during inhibitor binding that has allowed the development of a DHPS structural model that could be used for high-through put virtual screening (HTVS). Additionally, insights gained on the location and possible function of key mutation sites on the flexible loops will facilitate the design of new, potent inhibitors of DHPS that can bypass resistance mutations that render sulfonamides inactive. Prior to performing high-throughput virtual screening, the docking and scoring functions to be used were validated using established techniques against the B. anthracis DHPS target. In this validation study, five commonly used docking programs, FlexX, Surflex, Glide, GOLD, and DOCK, as well as nine scoring functions, were evaluated for their utility in virtual screening against the novel pterin binding site. Their performance in ligand docking and virtual screening against this target was examined by their ability to reproduce a known inhibitor conformation and to correctly detect known active compounds seeded into three separate decoy sets. Enrichment was demonstrated by calculated enrichment factors at 1% and Receiver Operating Characteristic (ROC) curves. The effectiveness of post-docking relaxation prior to rescoring and consensus scoring were also evaluated. Of the docking and scoring functions evaluated, Surflex with SurflexScore and Glide with GlideScore performed best overall for virtual screening against the DHPS target. The next phase of the DHPS structure-based drug design project involved high-throughput virtual screening against the DHPS structural model previously developed and docking methodology validated against this target. Two general virtual screening methods were employed. First, large, virtual libraries were pre-filtered by 3D pharmacophore and modified Rule-of-Three fragment constraints. Nearly 5 million compounds from the ZINC databases were screened generating 3,104 unique, fragment-like hits that were subsequently docked and ranked by score. Second, fragment docking without pharmacophore filtering was performed on almost 285,000 fragment-like compounds obtained from databases of commercial vendors. Hits from both virtual screens with high predicted affinity for the pterin binding pocket, as determined by docking score, were selected for in vitro testing. Activity and structure-activity relationship of the active fragment compounds have been developed. Several compounds with micromolar activity were identified and taken to crystallographic trials. Finally, in our ligand-based research into M. tuberculosis active agents, a series of nitrofuranylamide and related aromatic compounds displaying potent activity was investigated utilizing 3-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) techniques. Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods were used to produce 3D-QSAR models that correlated the Minimum Inhibitory Concentration (MIC) values against M. tuberculosis with the molecular structures of the active compounds. A training set of 95 active compounds was used to develop the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 15 compounds was used for the external validation. Different alignment and ionization rules were investigated as well as the effect of global molecular descriptors including lipophilicity (cLogP, LogD), Polar Surface Area (PSA), and steric bulk (CMR), on model predictivity. Models with greater than 70% predictive ability, as determined by external validation and high internal validity (cross validated r2 \u3e .5) were developed. Incorporation of lipophilicity descriptors into the models had negligible effects on model predictivity. The models developed will be used to predict the activity of proposed new structures and advance the development of next generation nitrofuranyl and related nitroaromatic anti-tuberculosis agents

Functional Exploration and Characterization of the Deaminases of Cog0402

High throughput sequencing technology and availability of this information has changed the way enzyme families can be studied. Sequence information from large public databases such as GenBank and UniProtKB can easily retrieved for the purpose of identifying unique enzymatic activities. The strategy adopted for this study is to identify characterized enzymes and the sequence features which give rise to their substrate specificity. Homologues of these enzymes are retrieved, and any active site variations can be readily identified. Cluster of Orthologous Groups (cog) 0402 is a family of enzymes which comprise a portion of the amidohydrolase superfamily. This group catalyzes a deamination reaction, releasing free ammonia and replacing it with a tautomerized oxygen. Cog0402 is most well known for guanine and cytosine deaminase, however other functions exist. One such function was that of S-adenosylhomocysteine deaminase, which was related to a large group of uncharacterized enzymes. These enzymes were predicted by us to deaminate 5’-modified adenosines. The enzymes were physically characterized these predictions were confirmed and a 5’-deoxyadenosine deaminase was discovered in addition to an 8-oxoadenine deaminase. During this study it was noted that background isoguanine deaminase activity was found at appreciable rates in E. coli. This activity was purified and identified using nanoLC-MS/MS and found to be caused by E. coli cytosine deaminase. E. coli cytosine deaminase itself is found in a cluster of uncharacterized enzymes with a single amino acid difference in the active site. Representative enzymes were purified and a 5-methylcytosine deaminase was discovered. This enzyme is capable of rescuing thymine auxotrophs in the presence of 5-methylcytosine, and will confer sensitivity to 5-fluorocytosine. Finally, an enzyme distantly related to cytosine deaminase was purified and found to be a unique pterin deaminase. It was most efficient for oxidized pterin rings and would accept a variety of substituents on the C6 positions. Futhermore, it was thought to catalyze the first step of an undescribed pterin degradation pathway

Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs

Computer aided approaches against Human African Trypanosomiasis

The thesis presented here is divided into two parts under a common theme that is the use of computer based tools, genomics, and in vitro experiments to develop innovative ways of tackling Human African Trypanosomiasis (HAT). Part I of this thesis focused on the human host genetic determinants while Part II focused on the discovery of novel chemotherapeutics against the parasite. Part I is further sub-divided into two parts: The first involves a Candidate Gene Association Study (CGAS) on an African population to identify genetic determinants associated with disease and/or susceptibility to HAT. The second involves studying the effects of missense Single Nucleotide Variants (SNVs) on protein structure, dynamics, and function using Macrophage Migration Inhibitory Factor (MIF) as a case study. Part II is also sub-divided into two parts: The first involves a computer based rational drug discovery of potential inhibitors against the Trypanosoma the folate pathway; particularly by targeting Trypanosoma brucei Pteridine Reductase (TbPTR1) which is an enzyme used by trypanosomes to overcome T. brucei Dihydrofolate Reductase (TbDHFR) inhibition. Lastly the derivation of CHARMM force-field parameters that can be used to accurately model the geometry and dynamics of the T. brucei Phosphodiesterase B1 enzyme (TbrPDEB1) bimetallic active site center. The derived parameters were then used in MD simulations to characterise protein-ligand residue interactions that are important in TbrPDEB1 inhibition with the goal of targeting the cyclic Adenosine Monophosphate (cAMP) signalling pathway. In the CGAS we were unable to detect any genetic associations in the Ugandan cohort analysed that passed correction for multiple testing in spite of the study being sufficiently powered. Additionally, our study found no association of the Apo lipoprotein 1 (APOL1) G2 allele association with protection against acute HAT that has been previously reported. Future investigations for example, Genome Wide Association Studies using larger samples sizes (>3000 cases and controls) are required. Macrophage migration inhibitory factor (MIF) is a cytokine that is important in both innate and adaptive immunity that has been shown to play a role in T. brucei pathogenicity using murine models. A total of 27 missense SNVs were modelled using homology modelling to create MIF protein mutants that were investigated using in silico effect prediction tools, molecular dynamics (MD), Principal Component Analysis (PCA), and Dynamic Residue Network (DRN) analysis. Our results demonstrate that mutations P2Q, I5M, P16Q, L23F, T24S, T31I, Y37H, H41P, M48V, P44L, G52C, S54R, I65M, I68T, S75F, N106S, and T113S caused significant conformational changes. Further, DRN analysis showed that residues P2, T31, Y37, G52, I65, I68, S75, N106, and T113S are part of a similar local residue interaction network with functional significance. These results show how polymorphisms such as missense SNVs can affect protein conformation, dynamics, and function. Trypanosomes are auxotrophic for folates and pterins but require them for survival. They scavenge them from their hosts. PTR1 is a multifunctional enzyme that is unique to trypanosomatids that reduces both pterins and folates. In the presence of DHFR inhibitors, PTR1 is over-expressed thus providing an escape from the effects of DHFR inhibition. Both TbPTR1 and TbDHFR are pharmacologically and genetically validated drug targets. In this study 5742 compounds were screened using molecular docking, and 13 promising binding modes were further analysed using MD simulations. The trajectories were analysed using RMSD, Rg, RMSF, PCA, Essential Dynamics Analysis (EDA), Molecular Mechanics Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations, and DRN analysis. The computational screening approach allowed us to identify five of the compounds, named RUBi004, RUBi007, RUBi014, RUBi016 and RUBi018 that exhibited antitrypanosomal growth activities against trypanosomes in culture with IC50 values of 12.5 ± 4.8 μM, 32.4 ± 4.2 μM, 5.9 ± 1.4 μM, 28.2 ± 3.3 μM, and 9.7 ± 2.1 μM, respectively. Further when used in combination with WR99210 a known TbDHFR inhibitor RUBi004, RUBi007, RUBi014 and RUBi018 showed antagonism while RUBi016 showed an additive effect. These results indicate that the four compounds might be competing with TbDHFR while RUBi016 might be more specific for TbPTR1. These compounds provide scaffolds that can be further optimised to improve their potency and specificity. Lastly, using a systematic approach we derived CHARMM force-field parameters to accurately describe the TbrPDEB1 bi-metal catalytic center. For dynamics, we employed mixed bonded and non-bonded approach. We optimised the structure using a two-layer QM/MM ONIOM (B3LYP/6-31(g): UFF). The TbrPDEB1 bi-metallic center bonds, angles, and dihedrals were parameterized by fitting the energy profiles from Potential Energy Surface (PES) scans to the CHARMM potential energy function. The parameters were validated by means of MD simulations and analysed using RMSD, Rg, RMSF, hydrogen bonding, bond/angle/dihedral evaluations, EDA, PCA, and DRN analysis. The force-field parameters were able to accurately reproduce the geometry and dynamics of the TbrPDEB1 bi-metal catalytic center during MD simulations. Molecular docking was used to identify 6 potential hits, that inhibited trypanosome growth in vitro. The derived force-field parameters were used to simulate the 6 protein-ligand complexes with the aim of elucidating crucial protein-ligand residue interactions. Using the most potent ligand RUBi022 that had an IC50 of 14.96 μM we were able to identify key residue interactions that can be of use in in silico prediction of potential TbrPDEB1 inhibitors. Overall we demonstrate how bioinformatics tools can complement current disease eradication strategies. Future work will focus on identifying variants identified in Genome Wide Association Studies and partnering with wet labs to carry out further enzyme-ligand activity relationship studies, structure determination or characterisation of appropriate protein-ligand complexes by crystallography, and site specific mutation studie

Molecular modelling of thymidylate synthase and rational design of its inhibitors as novel anticancer drugs

In search of novel anticancer drugs, putative inhibitors of the enzyme thymidylate synthase were investigated. The dissertation presents several steps of computationally aided drug design. Two targets are described: active site of the enzyme, for competitive inhibitors, and an allosteric pocket at the dimer interface. The potential hits were selected by computational high-throughput screening (molecular docking calculations) of available drug and prodrug databases. The selected compounds were then modified and scored further to indicate potential leads. Molecular dynamics simulations were performed for selected putative inhibitors of thymidylate synthase, both competitive and allosteric, in order to assess their dynamical behaviour, binding properties and arrangement of the ligands, and to select lead compounds for further tests in vitro. Moreover, a library of peptoids is described, created with the aim to design novel compounds with the desired peptide-like properties. Furthermore, quantum mechanics calculations were conducted to aid the synthesis and investigation of novel enzyme inhibitors, including boron containing compounds.W poszukiwaniu leków przeciwnowotworowych nowej generacji badano potencjalne inhibitory enzymu syntazy tymidylanowej. Opisano szereg etapów komputerowo wspomaganego projektowania leków. Wybrano dwa miejsca docelowe dla poszukiwanych inhibitorów: kieszeń aktywną enzymu oraz kieszeń allosteryczną między podjednostkami białka. Potencjalnie obiecujące związki wybrano w drodze wysokowydajnej procedury przesiewania (przy zastosowaniu metod dokowania molekularnego) dostępnych baz danych leków i proleków, a następnie modyfikację i dalszą selekcję wyników dokowania. Dla wybranych potencjalnych inhibitorów syntazy tymidylanowej, zarówno kompetycyjnych, jak i allosterycznych, przeprowadzono symulacje metodą dynamiki molekularnej w celu oceny dynamiki układu, parametrów wiązania i ułożenia ligandów, jak również wskazania wiodących związków do dalszych badań in vitro. Ponadto opisano bibliotekę peptoidów, stworzoną w celu projektowania nowej generacji związków o pożądanych właściwościach peptydomimetycznych. Wykonano również obliczenia metodami mechaniki kwantowej mające na celu wspomaganie badań i syntezy nowych inhibitorów enzymów, w tym związków zawierających bor