Molecular drug docking and biochemical performance of adenine specific glycosylase enzyme muty in conjunction with pharmaceutical medications

DNA repair mechanisms exist within all organisms and function to prevent permanent DNA damage. MutY is an enzyme found in a specific repair mechanism referred to as the base excision repair (BER) pathway. In this pathway, MutY prevents mutations in DNA from oxidative damage, making it a desirable target for treating cancer. This project focused on how FDA-approved drugs affect MutY activity using a computational docking method and a biochemical assay. The biochemical study suggests that adapalene, an acne medication, reduces Geobacillus stearothermophilus (GS) MutY activity by almost 50%. The computational docking study suggests that adapalene shows a strong and favorable binding interaction to the active site of GS MutY. Together, our data indicate that medicines can act on off-target interactions, potentially interfering with MutY activity. Cancer has been found to be dependent on these DNA repair pathways. It is imperative that we investigate how MutY activity changes in the presence of medicines that could kill cancer cells. Furthermore, understanding the drug-enzyme interactions will allow for efficient drug therapeutics to prevent abnormal mutation rates.

MOLECULAR DRUG DOCKING AND BIOCHEMICAL PERFORMANCE OF ADENINE SPECIFIC GLYCOSYLASE ENZYME MUTY IN CONJUNCTION WITH PHARMACEUTICAL MEDICATIONS by Harini Srinivasan A Senior Honors Thesis Submitted to the Faculty of College of Science The University of Utah In Partial Fulfillment of the Requirements for the Honors Degree in Bachelor of Science In Chemistry Approved ___ Martin P. Horvath Thesis Faculty Supervisor ______ _____________________________ Matthew S. Sigman Chair, Department of Chemistry _______________________________ Thomas G. Richmond Honors Faculty Advisor _____________________________ Sylvia D. Torti, PhD Dean, Honors College May 2022 Copyright © 2022 All Rights Reserved i ABSTRACT DNA repair mechanisms exist within all organisms and function to prevent permanent DNA damage. MutY is an enzyme found in a specific repair mechanism referred to as the base excision repair (BER) pathway. In this pathway, MutY prevents mutations in DNA from oxidative damage, making it a desirable target for treating cancer. This project focused on how FDA-approved drugs affect MutY activity using a computational docking method and a biochemical assay. The biochemical study suggests that adapalene, an acne medication, reduces Geobacillus stearothermophilus (GS) MutY activity by almost 50%. The computational docking study suggests that adapalene shows a strong and favorable binding interaction to the active site of GS MutY. Together, our data indicate that medicines can act on off-target interactions, potentially interfering with MutY activity. Cancer has been found to be dependent on these DNA repair pathways. It is imperative that we investigate how MutY activity changes in the presence of medicines that could kill cancer cells. Furthermore, understanding the drug-enzyme interactions will allow for efficient drug therapeutics to prevent abnormal mutation rates. ii ACKNOWLEDGEMENTS This research and work would not have been possible without my mentor, Dr. Martin Horvath, Professor in the Department of Biology, who has been extremely supportive of my career goals and my work accomplished under his guidance. Dr. Horvath’s patient instruction and constructive criticism helped me become a better student in his lab and I am fortunate to have had the opportunity to work with him and his lab members Payton Utzman and Peyton Russelberg for supplying many of the reagents and biological molecules. This research was also funded by the National Science Foundation (NSF) award number 1905249 under Dr. Horvath. I would also like to extend my sincerest gratitude to medical student Sonia Seghal whom I worked closely with in regard to my thesis project. Additionally, I am grateful to my department thesis advisor, Dr. Thomas Richmond, and the Department of Chemistry for their continued advice and support for the successful completion of my Bachelor of Science degree in Biochemistry. The Honors College and community at the University of Utah have been incredibly supportive of completing my thesis and undergraduate research. Finally, I would like to thank my family and friends for their constant support and words of encouragement in completing my undergraduate studies and my Honors thesis. iii TABLE OF CONTENTS ABSTRACT ii ACKNOWLEDGEMENTS iii INTRODUCTION 1 RESULTS 14 DISCUSSION 25 METHODS 33 REFERENCES 41 iv 1 INTRODUCTION The basis of life is built on the simple 4-letter genetic code which we know as deoxyribonucleic acid (DNA). The genetic code refers to the four bases of DNA including adenine (A), guanine (G), cytosine (C), and thymine (T). The sequence and combination of these four DNA bases encode many products needed for cell survival. Some of these products include ribonucleic acids (RNA), various types of proteins (enzymatic, structural, transport, etc.), and other molecules that come from one of DNA’s products. The genetic code may also be found in DNA conserved across different species. This might suggest the similarity of cellular mechanisms and maybe how important these processes are (Aravind, Walker, and Koonin, 1999). With much important information encoded within DNA, there are numerous mechanisms that protect DNA from permanent damage (Rastogi et al. 2010). When these mechanisms fail to protect DNA from damage, mutations can arise and cause complications. DNA damage can occur from external and internal sources leading to mutations. Some of the ways by which a mutation can be induced can include prolonged exposure to ultraviolet (UV) light and extreme temperatures. Fortunately, all organisms possess mechanisms to prevent and reverse structural damage to DNA. On the contrary, mutations can arise when DNA repair mechanisms fail to suppress DNA damage, resulting in serious health consequences that could lead to the progression of cancer. (American Cancer Society). A group of molecules that are known to impact cell survival and cell growth are reactive oxygen species (ROS). ROS molecules are oxygen-containing radicals. ROS damages DNA which can cause breaks in the DNA strand (Auten and Davis, 2009). The 2 breaking of the DNA strand can cause stress resulting in the loss of the bond between the nitrogenous bases and the DNA sugar-phosphate backbone (Srinivas et al. 2019). This can be a big problem for DNA replication. Out of the four nucleotides, guanine has the lowest redox potential so it is easily oxidized by ROS. One of the products of ROS-induced DNA damage is 8-oxo-7,8-dihydroguanine (OG) (Lee et al., 2020),. Structural studies have identified that OG can adopt two conformations (syn and anti). Guanine assumes the anti conformation and this allows it to correctly bind to cytosine. The difference in the structure of guanine and OG is shown in Figure 1 presented by Nakabeppu (Nakabeppu, 2014). The OG nucleotide in the syn conformation mimics thymine (Fromme et al. 2004). Because of this, an adenine can be mispaired with the OG nucleotide (Porello, Leyes, and David 1998), complicating DNA replication and leading to mutations. The ambiguity of the OG nucleotide allows pairing with adenine or cytosine, complicating DNA replication and increasing the probability of mutation rates. 4 Evolution recognized the risk of the OG nucleotide and as a result, all organisms possess DNA repair mechanisms to prevent mutations. This repair pathway contains enzymes that work together to return the DNA strand back to its original structure. One of the enzymes that function to repair DNA by recognizing the OG nucleotide in bacteria is MutM (Tajiri, Maki, and Sekiguchi, 1995). This enzyme acts in the early stages of the Base Excision Repair (BER) pathway. MutM functions to recognize and excise the OG nucleotide, making it possible for the BER enzymes to pair cytosine with guanine again. If MutM fails to excise OG, there is a backup enzyme that protects DNA from permanent mutation. All organisms possess a conserved adenine DNA glycosylase enzyme that participates in the base excision of adenine when paired to OG. This enzyme functions near the end of the BER pathway as the last measure of protection of DNA from mutation. As part of the BER pathway, the excision of adenine creates an empty (abasic) site (Manlove et al. 2017). An abasic site is a gap in DNA where no base exists, which many enzymes recognize apart from the BER mechanism. This intermediate is more unstable and other enzymes in the BER pathway work to recover the original DNA strand. This glycosylase enzyme is referred to as MutY in bacteria and MutY homolog (hMYH) in humans. Figure 2 depicts the exposed DNA site where DNA damage has occurred and how MutY in conjunction with the BER enzymes works together to retrieve its original structure. MutY is unique in that it recognizes the OG nucleotide but excises adenine from the OG:A pair. The BER pathway, including MutY and MutM, holds relevance to the human body as we try to understand mutation rates and find therapeutic targets to prevent DNA damage. A study by Xie et al suggested a significant role for the 5 MutY homolog in mice that were deficient in this DNA glycosylase enzyme. The study revealed that the genetically altered mice were prone to increased mutation rates and in turn had a higher likelihood of developing cancer, shortening their lifespan (Xie et al. 2004). We have learned a lot about MutY from x-ray structures of the enzyme in rod-shaped Geobacillus stearothermophilus (GS; Figure 3) - a thermophilic bacterium containing the MutY enzyme, a heavy focus in the Horvath Lab. The MutY enzyme in GS was the first of the DNA glycosylase enzymes to have the full structure completely determined by the Verdine group. This finding accelerated researchers to investigate the structure of hMYH. It is important to use GS MutY as a model to investigate enzyme activity and to understand how hMYH might affect cancer and the gut microbiota. 8 Previously, graduate student Peyton Russelburg investigated the role of conserved structures of MutY in Geobacillus stearothermophilus (GS). She found three amino acids (Phe307, Ser308, and His309; FSH loop) that suggest a contribution to MutY specificity (Russelburg et al. 2020). The structural integrity of this enzyme is just as important as understanding its functions. Understanding the structure and interactions that MutY employs in the presence and absence of medications (over the counter or prescribed) can allow us to design medicines while minimizing potential side effects. It is difficult to design drugs that have little to no off-target interactions. Narrowing the list of targets for drug therapies in treating cancer becomes more difficult because of the proliferative cell growth. Prior studies validate that cancer cells depend on the GO DNA repair pathway that propels this uncontrolled growth (Grundy and Parsons, 2020). If we could design medications that can effectively inhibit one or more enzymes of the repair pathway, we might expect to see reduced cancer cell growth. Modern medicine has cultivated a culture where prescription of medications has become common for diagnoses as simple as a headache to taking blood thinners for minor inflammation. Drugs such as acetaminophen, ibuprofen, and aspirin are some of the most commonly consumed over-the-counter medications. Although the properties of these molecules are known, it’s difficult to predict the opportunistic reactions that may occur when ingested. In addition to this, we cannot predict what other physiological molecules would interact with the medication. In an attempt to study MutY enzyme activity, I wanted to explore the structural binding affinity of a substrate to the active site on MutY to see if there are differences when certain medications are taken. 9 Colon and rectal cancer patients were identified with mutations in hMYH genes that altered their capacity to participate in the BER mechanism (Al-Tassan et al. 2002). This finding illuminated just how important hMYH is for normal DNA repair functions. The probability of a mutation becomes high when the damaged DNA is not repaired, leading to the activation of other pathways that propel the transformation of a cell into a tumor. Exploring the functional activity of MutY - and potentially hMYH - can allow us to design effective therapeutic care for cancer. There is a large community of bacteria in the colon and surrounding organs that are commonly referred to as the gut microbiota. The gut microbiome is largely impacted by the foods we eat and the medications we consume (Weersma, Zhernakova, and Fu 2020). There is little literature on the interlink between the gut microbial community and hMYH. This is especially interesting in trying to connect how bacterial mutation rates change depending on hMYH activity in the presence of drugs. I was particularly interested in how medications altered the activity of MutY or hMYH. What appealed to me the most was the lack of literature studying the clinical significance of medications in coordination with MutY and whether MutY or hMYH activity changes depending on interactions with various drugs. In an attempt to understand the interplay between certain drugs and MutY, we applied molecular modeling facilitated by Autodock VINA and ChimeraX. In combination, both of these programs allowed me to find regions of the enzyme that are compatible with drug docking in terms of hydrogen bonding and other interactions. The programs also explore different orientations of the medicines until it binds to the enzyme. More specifically, 10 Autodock VINA ranks the compatible positions of the drug by binding affinity energy. The ChimeraX program displays 3D structures of the enzymes as seen in Figures 4 and 5. ChimeraX and Autodck VINA were previously used by lab member Sonia Seghal who studied the binding affinity of MutY to the OG nucleotide and other drugs. Specific to my thesis, I use the structure of GS MutY and mouse MUTYH because the structure is already well-established and has a 98% similarity to the hMYH structure (Bai et al., 2007). Looking at how different classes of drugs affect MutY activity may indicate a causal relationship. Observing structural differences in orientation of the substrate with the enzyme’s active site might hint at important structural motifs to consider when designing therapeutic drugs. 11 Figure 4: GS MutY (PDB ID: 6u7t) enzyme structure on Chimera in complex with DNA analog. 12 Figure 5: Mouse MUTYH (PDB ID: 7EF9) enzyme structure in complex with DNA 13 I aimed to understand how the activity of MutY changes with the addition of medicines. If MutY activity changes, then there is a possibility for a change in DNA mutation rates. Drugs that can reduce MutY activity may have the potential to kill cancer cells that are dependent on the GO repair pathway. The first portion of my investigation explored the structural and binding affinity of MutY to a list of selected substrates in a computational docking experiment. The latter part of my investigation focused on GS MutY biochemical activity in the presence of four medications: adapalene, tadalafil, aspirin, and ibuprofen. While adapalene serves to treat acne prevention, tadalafil is a commonly prescribed medication to treat high blood pressure. Common over-the-counter drugs such as aspirin and ibuprofen were also analyzed to explore how they might alter MutY activity if at all. Our findings from the virtual docking experiments suggest that there are drug-enzyme interactions between the drugs and the MutY active site when compared to MutY-adenine binding affinity values. The binding affinity values also suggest possible drug-enzyme interactions when docked to MUTYH compared to adenine alone. Our biochemical analysis of the four drugs revealed that adapalene displayed significant reductions in GS MutY activity by almost 50%. The interactions between the drugs I studied and MutY can have medical applications, especially in clinical trials. The average success of a clinical trial is 14% which prompts researchers to increase the efficacy of clinical trials for the improvement of patient health (MIT). Understanding the off-target interactions in the body might help us determine better therapeutics for cancer treatment and promote a healthy gut microbiota. 14 RESULTS Molecular interactions between drugs and GS MutY active site. We used Autodock VINA and AutoDockTools (ADT) to dock molecular various drugs to the GS MutY active site. The GS MutY structure identified by the Verdine group is available on the Protein Data Bank (PDB ID: 6U7T). The drugs are characterized as ligands that could be identified by the Simplified Molecular-Input Line-Entry System (SMILES ). The drug is then docked to the receptor - the GS MutY active site (PDB ID: 6U7T). Autodock VINA generates a list of possible binding combinations with their corresponding binding affinities. The binding affinity value of each drug is then compared with the binding affinity value of adenine, MutY’s usual substrate. It is important to keep in mind that the reported binding affinity values are only an estimate of the best possible conformation of the drug to the GS MutY active site. Factors like torsional strain and solubility of the drug might affect the binding affinity value. More studies are needed to verify whether these drugs have a greater affinity for GS MutY than adenine. We observed many favorable interactions of the drugs to the GS MutY active site. More specifically, adapalene almost showed twice as much affinity (-10.2 Kcal/mol) for GS MutY active site as compared to adenine, which was one of the highest values we observed throughout the docking experiments. Figure 7 displays adapalene bound to the active site of GS MutY in two conformations that resulted in two binding affinity values. Other classes of drugs including hallucinogens, antidepressants, beta-blockers, and anticoagulants were also docked to the GS MutY enzyme active site and the binding 15 affinity values are reported in Table 1. The compilation of drugs in Table 1 allowed us to perform a biochemical analysis on four “candidate” drugs that showed a favorable interaction with GS MutY active site: adapalene, tadalafil, ibuprofen, and aspirin. Molecular interactions between drugs and MUTYH active sites. Autodock VINA was used again to dock a shorter list of drugs to the active site of MUTYH. The PDB ID for the MUTYH structure is 7EF9 and it’s important to note that this is the mouse MutY structure. Figure 6 displays MUTYH structure that is bound to DNA with adenine in the active site of the enzyme. Human MutY and MUTYH are 98% similar in structure, allowing us to infer our findings to study hMYH. I was interested in screening for “candidates” of drug-enzyme interaction in MUTYH. Doing so would help with finding cancer drug therapeutics that could reduce dependency on DNA repair mechanisms. Performing the computational docking experiments on MUTYH is just a start and seeing how medicines affect MUTYH can help us understand how drugs might affect hMYH activity. Table 2 only portrays the handful of drugs with binding affinities that don’t seem to deviate from adenine as much in comparison to the values when docked with GS MutY. Amoxapine seemed to generate the greatest affinity for the MUTYH active site compared to adenine in this list. Amoxapine is a prescribed antidepressant and this finding that it has a relatively high affinity for MUTYH is not only interesting but also opens doors for more scientific inquiry. 16 Table 1: Molecular docking experiments with GS MutY active site Drug Binding Affinity (Kcal/mol) Number of Torsional Strain Purpose of Drug Acebutolol -7 15 Beta blocker; treats high blood pressure Acetaminophen -5.8 3 moderate analgesic Acetazolamide -6.3 4 reduce edema Adapalene -10.3 6 treats acne Adenine -5.2 1 -- Amiloride -6.9 3 treats high blood pressure Amoxapine -7.6 1 Antidepressant Amphetamine -5.1 4 treat ADHD Apixaban -9.9 6 Anticoagulant/blood thinner Aripiprazole -8.9 7 treats bipolar and depressive disorder, and schizophrenia Aspirin -5.6 5 anti-inflammatory properties Atenolol -6.6 11 treats high blood pressure Azilsartan -10.3 9 treats high blood pressure Benazepril -8.5 12 treats high blood pressure Betaxolol -6.5 14 beta blocker; treats high blood pressure Buclizine -9.3 9 treats nausea and vomiting Bumetanide -7.7 11 treat edema Buprenorphine -6.5 12 treats opioid dependence Bupropion -5.7 8 antidepressant Candesartan -9.7 9 treats high blood pressure Capecitabine -7.5 11 chemotherapy drug Captopril -5.4 6 treats high blood pressure Cetuximab -4.8 19 used to treat head/neck cancer 17 Table 1 (continued): Molecular docking experiments with GS MutY active site Drug Binding Affinity (Kcal/mol) Number of Torsional Strain Purpose of Drug Chlorthalidone -8.9 4 treats high blood pressure Chlorothiazide -7.8 2 treat edema Chlorpheniramine -7.4 7 antihistamine Clomipramine -7 -7 treats OCD Codeine -7.5 4 type of opioid Cortisone -7.4 6 relieve pain and inflammation Dabigatran -8.6 12 Anticoagulant/blood thinner Desipramine -6.9 5 antidepressant Doxepin -7.2 5 antidepressant Edoxaban -9.3 9 Anticoagulant/blood thinner Emtricitabine -6.2 4 used to treat HIV Enalapril -7.8 13 treats high blood pressure Eprosartan -7.9 14 treats high blood pressure Fentanyl -8.8 7 treats severe pain Gabapentin -5.2 5 anticonvulsants Hydrochlorothiazide -7.8 2 treats high blood pressure Hydrocodone -7.3 3 narcotic analgesics Hydromorphone -7.8 2 opioid medication Hydroquinone -4.8 2 lightens hyperpigmented spots on skin Hydroxyzine -7.8 9 helps control anxiety Ibuprofen -6.3 8 non-steroidal anti-inflammatory drugs (NSAIDs) for pain Irinotecan -10.5 8 treat colon/rectal cancer Lamivudine -6.1 4 treats HIV Lisdexamfetamine -6.5 11 treats ADHD Lisinopril -7.8 15 treats high blood pressure 18 Table 1 (continued): Molecular docking experiments with GS MutY active site Drug Binding Affinity (Kcal/mol) Number of Torsional Strain Purpose of Drug Lonsurf -6.2 8 treats colorectal cancer Meperidine -6.2 6 opioid analgesics Methadone -6.9 11 Strong pain reliever Moexipril -8 17 angiotensin converting enzyme (ACE) inhibitor; lowers blood pressure Morphine -8 3 opioid medication Naproxen -7.4 6 pain reliever Nortriptyline -7.7 4 treats nerve pain Oxaliplatin -4 5 treats colon/rectal cancer Oxycodone -7.4 4 opioid medication Paroxetine -8.9 4 antidepressant Perindopril -6.7 13 angiotensin converting enzyme (ACE) inhibitor; lowers blood pressure Promethazine -6.5 6 reduces allergic reaction symptoms Quinapril -8.8 13 treats high blood pressure Ramipril -7.5 13 treats high blood pressure Regorafenib -9.7 7 treats colon/rectal cancer Rivaroxaban -9.4 5 Anticoagulant/blood thinner Rupatadine -9.1 3 antihistamine Spironolactone -7.5 5 Diuretic Tadalafil -10.1 2 sometimes treat pulmonary arterial hypertension Tapentadol -5.8 10 opioid medication Tramadol -7.5 11 relieves pain Trandolapril -8.2 13 treats high blood pressure Tranylcypromine -5.5 2 monoamine oxidase inhibitor (MAOI); antidepressants Trazodone -8.9 5 antidepressant 20 Table 2: Molecular docking experiments with MUTYH active site Drug Binding Affinity (Kcal/mol) Number of Torsional Strain Purpose of Drug Acetaminophen -5.3 3 moderate analgesic Acetazolamide -6.1 4 reduce edema Adenine -5.4 1 -- Amiloride -6.2 3 treats high blood pressure Amoxapine -7.5 1 Antidepressant Amphetamine -4.6 4 treat ADHD Aspirin -5.8 5 anti-inflammatory properties Chlorothiazide -7.6 2 treat edema Chlorthalidone -6.9 4 treats high blood pressure 21 GS MutY activity reduced with adapalene. We wanted to evaluate GS MutY activity in the presence of the four “candidates'' chosen from the computational docking experiment. Ibuprofen and aspirin are considered to be common over-the-counter medications while adapalene and tadalafil are prescription-based medications used to treat acne and high blood pressure, respectively. The drugs were combined with GS MutY and fluorescently tagged OG:A DNA strand. Once adenine is excised by MutY, sodium hydroxide is added to break the DNA strand at the abasic site(s). This process creates different sizes of DNA strands that are then eluted through fluorescence size exclusion chromatography (FSEC) where the strands are separated by size. Smaller DNA strands will generally have longer elution times than the longer DNA strands as they travel through the column. The instrument detected the number of products (short, cleaved DNA strands) and substrates (longer DNA strands) that were present and generated a chromatogram. The chromatogram portrayed two peaks: one for the substrate and the other for the products (Figure 8). The product eluted more slowly because it is smaller in size compared to the substrate and can be seen as the second peak on the chromatogram. The product peaks of each group were normalized to the product peak of the control which contained dimethyl sulfoxide (DMSO). We observed no significant activity changes in GS MutY in the presence of ibuprofen, aspirin, or tadalafil. Interestingly, the addition of adapalene seems to decrease GS MutY activity by almost a half as seen in Figure 9. This allows room for exploration with adapalene, maybe investigating how adapalene modulates bacterial growth. 22 A B Figure 7: Adapalene docked to GS Muty in two different binding sites. The Adapalene molecule highlighted in orange is closest to the iron-sulfur cluster, located in the enzyme’s active site, and measured -10.2 Kcal/mol for its binding affinity value. The adapalene molecule highlighted in blue is found in the OG binding site and measured -9.7 Kcal/mol for its binding affinity value. Panel A shows the overview image of both adapalene conformations. Panel B shows a zoomed image of Panel A. 25 DISCUSSION I investigated whether certain drugs could impact MutY activity using computational modeling and biochemical analysis. As suggested by our findings from the FSEC analysis, we found one of the drugs, adapalene, to reduce the function of GS MutY. The docking study of adapalene suggests a binding affinity value almost twice as much as adenine, the primary substrate for MutY. Together this might suggest that adapalene binds to the GS MutY active site and reduces its ability to excise adenine by competitive inhibition. This portrays that medicines can have an impact on processes that exceed their designated target. It is possible to infer how adapalene might affect GS MutY’s activity, but we would need to evaluate structural interactions, kinetics, and more to confirm this competitive model for the drug’s mode of action. Using the computational docking method and biochemical analysis gives us a starting point to uncover possible drugs that interfere with MutY activity. I generated a list of possible medicines to evaluate by selecting from classes with different applications.. This list includes different classes of drugs like antidepressants, hallucinogens, anticoagulants, antihistamines, diuretics, and pain killers. I was interested in how antidepressants interact with MutY’s active site because of the increased prevalence of depression and anxiety among college students. The risk of depression is substantially higher in college students than in the general population (Ibrahim, Kelly, Adams, and Glazebrook, 2013). In contrast; however, the general population has a higher incidence of cardiovascular disease (Roth et al., 2020), which piqued my interest in evaluating how anticoagulants might bind to MutY. A large part of the general population 26 also uses antihistamines for allergies and pain killers for somatic symptoms. These high-priority health concerns helped me create the list of different classes of drugs I was interested in docking to the enzyme active site. I picked a few drugs from each of the classes that were FDA-approved. The docking study showed promising drug-enzyme interactions for many of the drugs and we chose four of the drugs (adapalene, tadalafil, aspirin, and ibuprofen) to perform a biochemical analysis. Part of the reasoning for choosing the 4 medicines was due to the availability of the drug and the familiarity of both ibuprofen and aspirin by the general population. The drug-enzyme interaction can be biochemically assessed by many factors, one of which includes the binding affinity. The dissociation constant (Kd) is an equilibrium constant that measures the affinity of a ligand (drug) to a biomolecule (MutY). The higher the value of Kd the weaker the binding affinity of the ligand to the target. The lower the Kd value, the stronger the binding affinity of the ligand to the target. There are a lot of factors that influence the binding affinity interactions including hydrogen bonding, electrostatic interactions, hydrophobic, and Van der Waals interactions. More specific to drug therapeutics, the Kd value can better help us design medicines to bind more selectively to designated targets. The calculated Kd value for adapalene is 0.3 nM when using the binding affinity value from the computational docking experiment (-10.3 kcal/mol). McCann and Berti state that the Kd value for MutY bound to DNA containing OG:A lesion (dsDNA) is around 50 -120 pM; the adenine paired to OG substantially increases the DNA binding affinity (McCann and Berti, 2003). The binding affinity measured for adenine alone using Autodock VINA should be viewed as an underestimate 27 since in the context of DNA, the OG:A lesion has a much lower K d value measured experimentally. Nevertheless, adenine provides a benchmark binding affinity value that can be measured with Autodock VINA. With our collected data and understanding of drug-enzyme interactions, we can hypothesize a possible interaction of adapalene to MutY’s active site. The structure of adapalene as shown in Figure 10 displays a system of highly conjugated aromatic rings with a lot of hydrophobic regions present. Compared to the structure of adenine in Figure 11, adapalene does not seem to resemble the polarity of adenine. I predict that adapalene reduces GS MutY activity by binding directly to the active site due to hydrophobic interactions. As suggested by the computational docking experiment, this interaction may be more favorable than adenine. The Kd value suggests that MutY more strongly binds to adenine than adapalene. When adenine is in excess with adapalene present, I suspect that MutY activity might return to full capacity. This fits the competitive inhibitor model, suggestive of adapalene acting as the competitive inhibitor. In the scope of cancer, we want a drug that can reduce glycosylase enzyme activity and eventually kill cancer cells that are dependent on the GO repair pathway as described further in the next paragraph. 30 The BER pathway has been validated by multiple studies as a target to kill cancer cells. Donley et al. and Edwards et al. generated a list of inhibitors that block the 8-oxoguanine DNA glycosylase enzyme1 (hOGG1) that participates in the GO DNA repair pathway. The hOGG1 enzyme is analogous in function to the MutM enzyme of the GO repair pathway (Park et al., 2004). Similar to MutM, hOGG1 excises the OG nucleotide as a primary defense against permanent mutation. This is important because MYH possesses a domain that is homologous to the hOGG1, meaning that we predict it may display similar drug-enzyme interactions. In fact, human MutY, hOGG1, and other glycosylase enzymes part of the BER pathway are grouped under the endonuclease III (EndoIII) family (Yang et al., 2018). EndoIII enzymes function to cleave oxidized nucleotides from damaged DNA (Yang et al., 2018). It would be really interesting to see how other glycosylase enzyme activities in the BER pathway change with the addition of medicines. Interestingly, few studies have looked at the connection between gut microbiota and the activity of MUTYH. The gut microbiota possesses trillions of bacteria that metabolize the food we eat and circulate the metabolites throughout our body. In a healthy individual, the gut microbiota population is quite diverse which is largely contributed by eating a diet rich in nutrition. This is unlike individuals that depend on a high salt diet; their gut microbiota is composed of opportunistic bacteria that metabolize foods into metabolites harmful to the body including trimethylamine N-oxide (TMAO) which comes from high red meat consumption (Liu and Dai, 2020). Although cardiovascular and metabolic diseases are often the outcome of a damaged gut 31 microbiome, colorectal cancer has been recently studied as implicated by certain microbial metabolites (Rooks and Garett, 2016). This is interesting, especially regarding how a mutation in the glycosylase enzyme sequence has also been studied in colorectal cancer. I suspect there to be a connection between the metabolites implicated and MutY function. More specifically, I am curious to know if the medications prescribed for colorectal cancer affect MutY activity in a way that prevents or induces cancer cell growth. Having just scratched the surface of the story, there is still more to explore with drug interaction and MutY with respect to off-target interactions, especially hMYH. This novel study suggests the possibility of off-target interactions that may occur between a drug and other molecules in our body. I am curious to know the mechanism of action taken by these drugs in these off-target interactions. Are these interactions reversible? Should we redesign drugs to ensure limited off-target interactions? Ultimately, we still need to conduct more trials and look at in vivo interactions with other molecules. Prospects of this project might include redesigning this experiment and using hMYH with the four drugs that were used to dock with GS MutY. In addition to that, we can expand the number of drugs tested to see how other classes of drugs bind to the glycosylase enzymes’ active site. This study allowed me to inquire just how many mechanisms our body possesses to counteract the potentially harmful effects of the drugs we may take. DNA holds the genetic information to life and damage to the sequence can result in permanent mutations. Over time, evolution assembled DNA repair mechanisms to protect organisms from inheriting incorrect sequences. Understanding these repair 32 pathways gives us the key to creating better therapeutics for cancer and metabolic diseases. 33 METHODS DNA Annealing A-Cy5 Fluorescent-tagged DNA strand (obtained from graduate student Petyon Russelburg) was resuspended in 27.7 uL of Annealing Buffer (1X) to obtain 100 uM stock concentration. The 100 uM A-Cy5’ fluorescent-tagged DNA was diluted to a 0.5 uM working concentration prepared in a new Eppendorf tube. To the same tube, 0.5 uM of OG DNA strand (obtained from graduate student Peyton) was added. To facilitate the annealing of these two strands, the final tube of the DNA was heated on a heating block for 5 minutes at 90°C. The annealing DNA with its heating block was placed in a Styrofoam box at 4°C overnight to slowly cool. Adenine Glycosylase Reaction Approximately 0.1 g of the 4 drugs (adapalene, tadalafil, aspirin, and ibuprofen) were diluted in 10 mL of 100% dimethyl sulfoxide (DMSO). The annealed 0.5 uM DNA substrate was mixed with 10 uL of one of the four drugs or 10 uL of 100% DMSO. The 0.4 uM GS MutY enzyme (obtained from Payton Utzman) was added last to prevent reaction with the DNA strand prior to adding the medicines. Table 3 reports volumes and concentration of reagents to assemble a reaction. Each reaction tube was heated for 25 minutes on a thermocycler block at 60 °C. The reactions were quenched by the addition of 50 uL of 0.06 M NaOH to inactivate the reaction reagent. An equal 50 uL of 100% DMSO was added to the reaction tube to reach a final volume of 200 uL. The reaction 34 tube is placed on a thermocycler block at 90 °C for 5 minutes to be quenched and allowed for strand cleavage. A fixed volume of 200 uL of the reaction mixture was measured and placed into Fluorescence size-exclusion chromatography (FSEC) vials. The FSEC vials were spun down in a centrifuge at 8,000 rpm for about 10 seconds and placed in the autosampler (Figure 12). 35 Table 3: Concentration and volume of solutions used in adenine glycosylase reactions Solution Concentration (mM) Volume (uL) OG:A DNA Strand 0.0005 45 GS MutY 0.0004 45 NaOH 63 50 Adapalene* 24 10 Tadalafil* 26 10 Aspirin* 56 10 Ibuprofen* 48 10 100 % DMSO -- 50 *dissolved in 100% DMSO 36 Figure 12: Image of 717 plus Autosampler. 37 Fluorescence Size-Exclusion Chromatography FSEC instrumentation (Figure 13) was used to quantitate the activity of GS MutY in the presence of 4 different drugs (adapalene, Tadalafil, Aspirin, or Ibuprofen). The FSEC vials were stored inside the autosampler until a volume of the contents were used to be run through the column. The flow rate was set to 0.35 mL/min for water and the mobile phase (running buffer containing 0.1 M potassium phosphate of pH 7.21 with 10% acetonitrile). The injection volume was adjusted to 20 uL per FSEC vial. The reaction was eluted in the Zenix SEC-80 column in the mobile phase and the instrument detected fluorophores from the cleaved A-Cy5’ product with excitation at 645 nm and emission at 670 nm. 38 Figure 13: Image of fluorescence size-exclusion chromatography (FSEC) with Zenix SEC-80 Column 39 UCSF Chimera and AutoDock VINA with AutoDockTools (ADT) Drug molecules were prepared as ligands for docking experiments with the use of Autodock Tools (Morris et al., 2009). Likewise, the GS MutY (PDB ID: 6u7t) was prepared as the receptor with use of Autodock Tools, after removing the DNA portion. The GS MutY prior to having the DNA portion removed is shown in Figure 14. Ligands were docked to the MutY receptor using Autodock VINA (Oleg and Olsen, 2010) as implemented with the interface provided by UCSF Chimera (Pettersen et al., 2004). 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