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11	Computational Modeling of Cancer-Related Mutations in DNA Repair Enzymes Using Molecular Dynamics and Quantum Mechanics/Molecular Mechanics Leddin, Emmett Michael 05 1900 (has links) This dissertation details the use of computational methods to understand the effect that cancer-related mutations have on proteins that complex with nucleic acids. Firstly, we perform molecular dynamics (MD) simulations of various mutations in DNA polymerase κ (pol κ). Through an experimental collaboration, we classify the mutations as more or less active than the wild type complex, depending upon the incoming nucleotide triphosphate. From these classifications we use quantum mechanics/molecular mechanics (QM/MM) to explore the reaction mechanism. Preliminary analysis points to a novel method for nucleotide addition in pol κ. Secondly, we study the ten-eleven translocation 2 (TET2) enzyme in various contexts. We find that the identities of both the substrate and complementary strands (or lack thereof) are crucial for maintaining the complex structure. Separately, we find that point mutations within the protein can affect structural features throughout the complex, only at distal sites, or only within the active site. The mutation's position within the complex alone is not indicative of its impact. Thirdly, we share a new method that combines direct coupling analysis and MD to predict potential rescue mutations using poly(ADP-ribose) polymerase 1 as a model enzyme. Fourthly, we perform MD simulations of mutations in the protection of telomeres 1 (POT1) enzyme. The investigated variants modify the POT1-ssDNA complex dynamics and protein—DNA interactions. Fifthly, we investigate the incorporation of remdesivir and other nucleotide analogue prodrugs into the protein-RNA complex of severe acute respiratory syndrome-coronavirus 2 RNA-dependent RNA polymerase. We find evidence for destabilization throughout the complex and differences in inter-subunit communication for most of the incorporation patterns studied. Finally, we share a method for determining a minimum active region for QM/MM simulations. The method is validated using 4-oxalocrotonate, TET2, and DNA polymerase λ as test cases. biochemistry cancer-related mutations computational chemistry DNA polymerase DNA repair molecular dynamics nucleic acids PARP1 POT1 proteins quantum mechanics/molecular mechanics RdRp SNP TET2 theoretical chemistry Chemistry, Biochemistry Biophysics, General
12	QM/MM Applications and Corrections for Chemical Reactions Bryant J Kim (15322279) 18 May 2023 (has links) <p>In this thesis, we present novel computational methods and frameworks to address the challenges associated with the determination of free energy profiles for condensed-phase chemical reactions using combined quantum mechanical and molecular mechanical (QM/MM) approaches. We focus on overcoming issues related to force matching, molecular polarizability, and convergence of free energy profiles. First, we introduce a method called Reaction Path-Force Matching in Collective Variables (RP-FM-CV) that efficiently carries out ab initio QM/MM free energy simulations through mean force fitting. This method provides accurate and robust simulations of solution-phase chemical reactions by significantly reducing deviations on the collective variables forces, thereby bringing simulated free energy profiles closer to experimental and benchmark AI/MM results. Second, we explore the role of pairwise repulsive correcting potentials in generating converged free energy profiles for chemical reactions using QM/MM simulations. We develop a free energy correcting model that sheds light on the behavior of repulsive pairwise potentials with large force deviations in collective variables. Our findings contribute to a deeper understanding of force matching models, paving the way for more accurate predictions of free energy profiles in chemical reactions. Next, we address the underpolarization problem in semiempirical (SE) molecular orbital methods by introducing a hybrid framework called doubly polarized QM/MM (dp-QM/MM). This framework improves the response property of SE/MM methods through high-level molecular polarizability fitting using machine learning (ML)-derived corrective polarizabilities, referred to as chaperone polarizabilities. We demonstrate the effectiveness of the dp-QM/MM method in simulating the Menshutkin reaction in water, showing that ML chaperones significantly reduce the error in solute molecular polarizability, bringing simulated free energy profiles closer to experimental results. In summary, this thesis presents a series of novel methods and frameworks that improve the accuracy and reliability of free energy profile estimations in condensed-phase chemical reactions using QM/MM simulations. By addressing the challenges of force matching, molecular polarizability, and convergence, these advancements have the potential to impact various fields, including computational chemistry, materials science, and drug design.</p> Computational chemistry Computational methods Free energy profiles Condensed-phase chemical reactions Force matching Mean force fitting Pairwise repulsive correcting potentials Free energy correcting model Semiempirical molecular orbital methods Doubly polarized QM/MM (dp-QM/MM) Chaperone polarizabilities Machine learning Computational chemistry
13	QM/MM Applications and Corrections for Chemical Reactions Kim, Bryant 05 1900 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / In this thesis, we present novel computational methods and frameworks to address the challenges associated with the determination of free energy profiles for condensed-phase chemical reactions using combined quantum mechanical and molecular mechanical (QM/MM) approaches. We focus on overcoming issues related to force matching, molecular polarizability, and convergence of free energy profiles. First, we introduce a method called Reaction Path-Force Matching in Collective Variables (RP-FM-CV) that efficiently carries out ab initio QM/MM free energy simulations through mean force fitting. This method provides accurate and robust simulations of solution-phase chemical reactions by significantly reducing deviations on the collective variables forces, thereby bringing simulated free energy profiles closer to experimental and benchmark AI/MM results. Second, we explore the role of pairwise repulsive correcting potentials in generating converged free energy profiles for chemical reactions using QM/MM simulations. We develop a free energy correcting model that sheds light on the behavior of repulsive pairwise potentials with large force deviations in collective variables. Our findings contribute to a deeper understanding of force matching models, paving the way for more accurate predictions of free energy profiles in chemical reactions. Next, we address the underpolarization problem in semiempirical (SE) molecular orbital methods by introducing a hybrid framework called doubly polarized QM/MM (dp-QM/MM). This framework improves the response property of SE/MM methods through high-level molecular polarizability fitting using machine learning (ML)-derived corrective polarizabilities, referred to as chaperone polarizabilities. We demonstrate the effectiveness of the dp-QM/MM method in simulating the Menshutkin reaction in water, showing that ML chaperones significantly reduce the error in solute molecular polarizability, bringing simulated free energy profiles closer to experimental results. In summary, this thesis presents a series of novel methods and frameworks that improve the accuracy and reliability of free energy profile estimations in condensed-phase chemical reactions using QM/MM simulations. By addressing the challenges of force matching, molecular polarizability, and convergence, these advancements have the potential to impact various fields, including computational chemistry, materials science, and drug design. Computational Methods Free Energy Profiles Condensed-Phase Chemical Reactions Force Matching Mean Force Fitting Pairwise Repulsive Correcting Potentials Free Energy Correcting Model Sempiempirical Molecular Orbital Methods Doubly Polarized QM/MM (dp-QM/MM) Chaperone Polarizabilities Machine Learning Computational Chemistry
14	Electrostaticanalisys the Ras active site Khan, Abdul Kareem 05 March 2009 (has links) La preorganització electrostàtica del centre actiu s'ha postulat com el mecanisme genèric de l'acció dels enzims. Així, alguns residus "estratègics" es disposarien per catalitzar reaccions interaccionant en una forma més forta amb l'estat de transició, baixant d'aquesta manera el valor de l'energia dactivació g cat. S'ha proposat que aquesta preorientació electrostática s'hauria de poder mostrar analitzant l'estabilitat electrostàtica de residus individuals en el centre actiu.Ras es una proteïna essencial de senyalització i actúa com un interruptor cel.lular. Les característiques estructurals de Ras en el seu estat actiu (ON) són diferents de les que té a l'estat inactiu (OFF). En aquesta tesi es duu a terme una anàlisi exhaustiva de l'estabilitat dels residus del centre actiu deRas en l'estat actiu i inactiu. / The electrostatic preorganization of the active site has been put forward as the general framework of action of enzymes. Thus, enzymes would position "strategic" residues in such a way to be prepared to catalyze reactions byinteracting in a stronger way with the transition state, in this way decreasing the activation energy g cat for the catalytic process. It has been proposed thatsuch electrostatic preorientation should be shown by analyzing the electrostatic stability of individual residues in the active site.Ras protein is an essential signaling molecule and functions as a switch in thecell. The structural features of the Ras protein in its active state (ON state) are different than those in its inactive state (OFF state). In this thesis, an exhaustive analysis of the stability of residues in the active and inactive Ras active site is performed. dinàmica centre actiu relacions d'estructura activitat preorganització reorganització estat de transició estat actiu estabilitat electrostàtica interacción proteïna-proteïna test de ranks de Wilcoxon P-loop G1 motif HVR metastability RMSD substrate assisted catalysis sequence alignment beta sheet helix Z-test wilcoxon rank test protein-protein interactions electrostatic stability active state dynamics signal transduction electrostatic stabilization ras effectors guanine exchange factor GTPase-activating proteins quantum mechanics/molecular PDLD/S-LRA X-ray crystallography solvation energy free energy perturbation statistical analysis GTP hydrolysis guanosine diphosphate guanosine triphosphate computer simulation thermodynamics protein conformation electrostatics interruptor II interruptor I llaç P motiu G1 HVR (regions altament variables) metaestabilita RMSD catàlisi assistida pel substrat aliniament de seqüència fulla beta hèlix test Z transducció del senyal estabilització electrostàtica efectors de ras factor de bescamvi de guanina proteïnes activadores de l'activitat mecànica quàntica/mecànica PDLD/S-LRA cristalografia de raigs X energia de solvatació perturbació de l'energia lliure anàlisi estadística hidròlisi de GTP difosfat de guanosina trifosfat de guanosina simulació computacional termodinàmica conformació proteïca electrostàtica switch-I switch-II 537 576

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