Doctor of Philosophy

dissertationThe characterization of novel and reactive Phase I metabolites of xenobiotics, such as those frequently produced by P450 enzymes, is an area of interest that has led to increased research efforts during preclinical drug-testing and development. A key interest is improving our understanding of factors that contribute to competing Phase I reaction mechanisms, some of which produce stable products that can be further metabolized and excreted, and others that produce reactive metabolites capable of causing toxicities. Due to the highenergy nature of the P450 catalytic oxyferryl heme species, Compound I, P450 enzymes can also catalyze different oxidation reaction mechanisms, including dehydrogenation reactions. Dehydrogenation reactions are more difficult to predict than the more common P450 oxygenation and dealkylation reactions. Moreover, dehydrogenation mechanisms can compete with hydroxylation mechanisms to produce unstable desaturated electrophilic metabolites capable of forming potentially toxic biomolecular adducts. The work presented here focuses on improving existing computational tools for the prediction of P450 metabolism of two model substrates, raloxifene and 4-hydroxy-tamoxifen. These two compounds are FDA-approved selective estrogen receptor modulators currently used in the treatment of breast cancer. In Chapter 2 the development, iv testing and refinement of molecular mechanics parameters for key species of the heme prosthetic group during the P450 catalytic cycle is presented. It is shown that the assignment of atomic partial charges for key heme species improves the identification of the sites of metabolism of raloxifene by CYP3A4. Building on this work, in Chapter 3 it is shown that despite using these new heme parameters, extensive quantum mechanics calculations to probe substrate reactivity, molecular dynamics of the enzyme structure to find representative active site conformations makes the greatest improvement in the identification of the sites of metabolism for 4-hydroxy-tamoxifen. In summary, this work identifies that heme electrostatics and enzyme conformational dynamics play important roles in enzyme function and that the ability to predict sites of metabolism for P450- substrates requires the integration of both for the improvement of future in silico tools

Unravelling the role of transient redox partner complexes in P450 electron transfer mechanics

The molecular evolution of cytochromes P450 and associated redox-driven oxidative catalysis remains a mystery in biology. It is widely believed that sterol 14α-demethylase (CYP51), an essential enzyme of sterol biosynthesis, is the ancestor of the whole P450 superfamily given its conservation across species in different biological kingdoms. Herein we have utilized X-ray crystallography, molecular dynamics simulations, phylogenetics and electron transfer measurements to interrogate the nature of P450-redox partner binding using the naturally occurring fusion protein, CYP51-ferredoxin found in the sterol-producing bacterium Methylococcus capsulatus. Our data advocates that the electron transfer mechanics in the M. capsulatus CYP51-ferredoxin fusion protein involves an ensemble of ferredoxin molecules in various orientations and the interactions are transient. Close proximity of ferredoxin, however, is required to complete the substrate-induced large-scale structural switch in the P450 domain that enables proton-coupled electron transfer and subsequent oxygen scission and catalysis. These results have fundamental implications regarding the early evolution of electron transfer proteins and for the redox reactions in the early steps of sterol biosynthesis. They also shed new light on redox protein mechanics and the subsequent diversification of the P450 electron transfer machinery in nature

Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure-activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein-ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance.JK, MJW, JT, PJB, AB and RCG thank Unilever for funding

Single-Site Mutation Induces Water-Mediated Promiscuity in Lignin Breaking Cytochrome P450GcoA

Cytochrome P450 GcoA is an enzyme that catalyses the guaiacol unit of lignin during the lignin breakdown via aryl-O-demethylation reaction. This reaction is intriguing and is of commercial importance for its potential application in the production of biofuel and plastic from biomass feedstock. Recently, the F169A mutation in the P450 GcoA elicits a promiscuous activity for syringol while maintaining the native activity for guaiacol. Using comprehensive MD simulations and hybrid QM/MM calculations we address, herein, the origin of promiscuity in P450 GcoA and its relevance to the specific activity toward lignin-derived substrates. Our study shows a crucial role of an aromatic dyad, F169, and F395 through regulating the water access to the catalytic center. The F169A mutation opens a water aqueduct and hence increases the native activity for the G-lignin. We show that syringol binds very tightly in the WT enzyme which blocks the conformational rearrangement needed for the second step of O-demethylation. The F169A creates an extra room favoring the conformational rearrangement in the demethylated syringol (3MC) and second dose of the dioxygen insertion. Therefore, using MD simulations and complemented by thorough QM/MM calculations, our study shows how does a single site mutation re-architect active site engineering for promiscuous syringol activity

A promiscuous cytochrome P450 aromatic O-demethylase for lignin bioconversion

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOMicrobial aromatic catabolism offers a promising approach to convert lignin, a vast source of renewable carbon, into useful products. Aryl-O-demethylation is an essential biochemical reaction to ultimately catabolize coniferyl and sinapyl lignin-derived a9FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO2013/08293-72014/10448-12016/22956-7We acknowledge funding from NSF grants to J.L.D. (MCB-1715176), K.N.H. (CHE-1361104), and E.L.N. (DEB-1556541 and MCB-1615365) and BBSRC grants to J.E.M. (BB/P011918/1, BB/L001926/1 and a studentship to S.J.B.M.). G.T.B., M.M.M., C.W.J., M.F.C., E.L.N.,

Molecular dynamics and virtual screening approaches in drug discovery

Computer-aided drug discovery (CADD) methods are now routinely used in the preclinical phase of drug development. Powerful high-performance computing facilities and the extremely fast CADD methods constantly scale up the coverage of drug-like chemical space achievable in rational drug development. In this thesis, CADD approaches were applied to address several early-phase drug discovery problems. Namely, small molecule binding site detection on a novel target protein, virtual screening (VS) of molecular databases, and characterization of small molecule interactions with metabolic enzymes were studied. Various CADD methods, including molecular dynamics (MD) simulations in mixed solvents, molecular docking, and binding free energy calculations, were employed. Co-solvent MD simulations detected biologically relevant binding sites and provided guidance for screening potential protein-protein interaction inhibitors for a crucial protein of the SARS-CoV-2. VS with fragment- and negative image-based (F-NIB) models identified three active and structurally novel inhibitors of the putative drug target phosphodiesterase 10A. MD simulations and docking provided detailed insights on the effects of active site structural flexibility and variation on the binding and resultant metabolism of small molecules with the cytochrome P450 enzymes. The results presented in this thesis contribute to the increasing evidence that supports employment and further development of CADD approaches in drug discovery. Ultimately, rational drug development coupled with CADD may enable higher quality drug candidates to the human studies in the future, reducing the risk of financially and temporally costly clinical failure. KEYWORDS: Structure-based drug development, Computer-aided drug discovery (CADD), Molecular dynamics (MD) simulation, Virtual screening (VS), Fragmentand negative image-based (F-NIB) model, Structure-activity relationship (QSAR), Cytochrome P450 ligand binding predictionMolekyylidynamiikka- ja virtuaaliseulontamenetelmät lääkeaine-etsinnässä Tietokoneavusteista lääkeaine-etsintää käytetään nykyisin yleisesti prekliinisessä lääketutkimuksessa. Suurteholaskenta ja äärimmäisen nopeat tietokoneavusteiset lääkeaine-etsintämenetelmät mahdollistavat jatkuvasti kattavamman lääkkeenkaltaisten molekyylien kemiallisen avaruuden seulonnan. Tässä väitöskirjassa tietokonepohjaisia menetelmiä hyödynnettiin lääketutkimuksen prekliiniseen vaiheeseen liittyvissä tyypillisissä tutkimusongelmissa. Työhön kuului pienmolekyylien sitoutumisalueiden tunnistus uuden kohdeproteiinin rakenteesta, molekyylitietokantojen virtuaaliseulonta sekä pienmolekyylien ja metabolian entsyymien välisten vuorovaikutusten tietokonemallinnus. Työssä käytettiin useita tietokoneavusteisen lääkeaine-etsinnän menetelmiä, sisältäen molekyylidynamiikkasimulaatiot (MD-simulaatiot) vaihtuvissa liuottimissa, molekulaarisen telakoinnin ja sitoutumisenergian laskennan. Orgaanisen liuottimen ja veden sekoituksessa tehdyt MD-simulaatiot tunnistivat biologisesti merkittäviä sitoutumisalueita SARS-CoV-2:n tärkeästä proteiinista ja ohjasivat infektioon liittyvän proteiini-proteiinivuorovaikutuksen potentiaalisten estäjien etsintää. Virtuaaliseulonnalla tunnistettiin kolme rakenteellisesti uudenlaista tunnetun lääkekehityskohteen, fosfodiesteraasi 10A:n, estäjää hyödyntäen fragmentti- ja negatiivikuvamalleja. MD-simulaatiot ja telakointi tuottivat yksityiskohtaista tietoa sytokromi P450 entsyymien aktiivisen kohdan rakenteen jouston ja muutosten vaikutuksesta pienmolekyylien sitoutumiseen ja metaboliaan. Tämän väitöskirjan tulokset tukevat kasvavaa todistusaineistoa tietokoneavusteisen lääkeaine-etsinnän käytön ja kehityksen hyödyllisyydestä prekliinisessä lääketutkimuksessa. Tietokoneavusteinen lääkeaine-etsintä voi lopulta mahdollistaa korkeampilaatuisten lääkekandidaattien päätymisen ihmiskokeisiin, pienentäen taloudellisesti ja ajallisesti kalliin kliinisen tutkimuksen epäonnistumisen riskiä. AVAINSANAT: Rakennepohjainen lääkeainekehitys, Tietokoneavusteinen lääkeaine-etsintä, Molekyylidynamiikkasimulaatio (MD-simulaatio), Virtuaaliseulonta, Fragmentti- ja negatiivikuvamalli, Rakenne-aktiivisuussuhde, Sytokromi P450 ligandien sitoutumisen ennustu

A BIOPHYSICAL INVESTIGATION OF STABILITY, LIGAND BINDING, AND IRON STATE OF CYP102A1

Cytochrome P450s (CYPs) are cysteine ligated Fe-heme monooxygenases that are found in all domains of life. In mammals, they have a role in xenobiotic metabolism and steroid synthesis, making them a fundamental requirement for survival. In addition, their ability to perform a variety of chemical reactions on an array of substrates makes CYPs highly sought for biotechnical applications such as wastewater remediation, production of potential drug candidates, and creation of drug metabolites. By mutating specific amino acids, these enzymes can be engineered to change their substrate binding profiles and achieve stereo- and regio-specific chemistry. While these mutations are essential to change CYP activity, the major drawback to using them on an industrial scale is a decrease in stability of the enzyme. This work elaborated how CYP stability is effected by mutations, binding of native and non-native substrates, and changes in iron oxidation state. Cytochrome P450BM3 (BM3, or CYP102A1), a bacterial enzyme, was used as a model system. In contrast to membrane associated human CYPs, BM3 is soluble and has efficient turnover due to the fusion of the reductase partner the heme domain. BM3 is naturally selective, but mutations can be incorporated to make it promiscuous, similar to CYPs responsible for xenobiotic breakdown. This allowed for the comparison of a selective vs. a promiscuous CYP while conserving the greatest possible sequence identity. An approach was used combining experimental solution phase data, x-ray crystallography, and molecular dynamic simulations. The results showed that mutations resulted in an cumulative decrease in stability as promiscuity increased. This reduction in stability was due to a decrease in the number of salt bridges and disruption of hydrophobic contacts. Regions of P450BM3 were found that could be targeted through mutation to increase the stability of a highly promiscuous and active variant known as the pentuple mutant (PM). Further investigations demonstrated the impact of native and non-native substrate binding. The Gibbs free energy of binding (ΔGb°) was determined for a small library of molecules and was rationalized computationally, concluding that attractive dispersion forces negated the impact of electrostatic and repulsive forces. In addition, the impact of the iron-heme charge state on CYP stability was examined as a function of promiscuity. In general, there was an association between promiscuity and similarities in the stability of the Fe(III) and Fe(II) states. This is consistent with a model where the promiscuous variants of the enzyme are in a more “reduction-ready” state, and can undergo catalysis with greater ease than the wild type enzyme. These findings have implications for the role of CYPs in human health and for biotechnical applications

Molecular basis for endocrine disruption by pesticides targeting aromatase and estrogen receptor

The intensive use of pesticides has led to their increasing presence in water, soil, and agricultural products. Mounting evidence indicates that some pesticides may be endocrine disrupting chemicals (EDCs), being therefore harmful for the human health and the environment. In this study, three pesticides, glyphosate, thiacloprid, and imidacloprid, were tested for their ability to interfere with estrogen biosynthesis and/or signaling, to evaluate their potential action as EDCs. Among the tested compounds, only glyphosate inhibited aromatase activity (up to 30%) via a non-competitive inhibition or a mixed inhibition mechanism depending on the concentration applied. Then, the ability of the three pesticides to induce an estrogenic activity was tested in MELN cells. When compared to 17\u3b2-estradiol, thiacloprid and imidacloprid induced an estrogenic activity at the highest concentrations tested with a relative potency of 5.4 7 10 1210 and 3.7 7 10 129, respectively. Molecular dynamics and docking simulations predicted the potential binding sites and the binding mode of the three pesticides on the structure of the two key targets, providing a rational for their mechanism as EDCs. The results demonstrate that the three pesticides are potential EDCs as glyphosate acts as an aromatase inhibitor, whereas imidacloprid and thiacloprid can interfere with estrogen induced signaling