Browsing by Author "Naumann, Christoph"
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Item Chemometric Analysis of Volatile Organic Compound Biomarkers of Disease and Development of Solid Phase Microextraction Fibers to Evaluate Gas Sensing Layers(2022-08) Woollam, Mark David; Agarwal, Mangilal; Deiss, Frédérique; Goodpaster, John; Naumann, ChristophCanines can detect different diseases simply by smelling different biological sample types, including urine, breath and sweat. This has led researchers to try and discovery unique volatile organic compound (VOC) biomarkers. The power of VOC biomarkers lies in the fact that one day they may be able to be utilized for noninvasive, rapid and accurate diagnostics at a point of care using miniaturized biosensors. However, the identity of the specific VOC biomarkers must be demonstrated before designing and fabricating sensing systems. Through an extensive series of experiments, VOCs in urine are profiled by solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS) to identify biomarkers for breast cancer using murine models. The results from these experiments indicated that unique classes of urinary VOCs, primarily terpene/terpenoids and carbonyls, are potential biomarkers of breast cancer. Through implementing chemometric approaches, unique panels of VOCs were identified for breast cancer detection, identifying tumor location, determining the efficacy of dopaminergic antitumor treatments, and tracking cancer progression. Other diseases, including COVID-19 and hypoglycemia (low blood sugar) were also probed to identify volatile biomarkers present in breath samples. VOC biomarker identification is an important step toward developing portable gas sensors, but another hurdle that exists is that current sensors lack selectivity toward specific VOCs of interest. Furthermore, testing sensors for sensitivity and selectivity is an extensive process as VOCs must be tested individually because the sensors do not have modes of chromatographic separation or compound identification. Another set of experiments is presented to demonstrate that SPME fibers can be coated with materials, used to extract standard solutions of VOCs, and analyzed by GC-MS to determine the performance of various gas sensing layers. In the first of these experiments, polyetherimide (PEI) was coated onto a SPME fiber and compared to commercial polyacrylate (PAA) fibers. The second experiment tuned the extraction efficiency of polyvinylidene fluoride (PVDF) - carbon black (CB) composites and showed that they had higher sensitivity for urinary VOC extraction relative to a polydimethylsiloxane (PDMS) SPME fiber. These results demonstrate SPME GC-MS can rapidly characterize and tune the VOC adsorption capabilities of gas sensing layers.Item Combining Semiempirical QM Methods with Atom Dipole Interaction Model for Accurate and Efficient Polarizability Calculations(2022-12) Young, Ryan; Pu, Jingzhi; Long, Eric C.; Naumann, Christoph; Sardar, RajeshMolecular polarizability plays a significant role in chemistry, biology, and medicine. Classical prediction of polarizability often relies on atomic-type specific polarizability optimized for training set molecules, which limits the calculations to systems of similar chemical environment. Although ab initio (AI) quantum mechanical (QM) methods are more transferable in predicting molecular polarizability, their high computational costs especially when used with large basis sets for obtaining quantitatively reliable results make them less practical. To obtain accurate QM polarizability in an efficient manner, we have developed a dual-level approach, where the polarizability (α) obtained from the efficient semiempirical QM (SE) method is corrected using a set of element-base atomic polarizabilities derived from the atomic dipole interaction model (ADIM) to reproduce the density functional theory (DFT) results. We have optimized the atomic polarizability correction parameters for CHON-containing systems using a small training set of molecules and tested the resulting SE-ADIM model on the neutral drug-like molecules in the QM7B database. SE-ADIM corrected AM1 showed substantial improvement with its relative percent error (RPE) compared to B3LYP reduced from 33.81% to 3.35%. To further test its robustness for larger molecules in broader chemical bonding situations, we applied this method to a collection of drug molecules from the e-Drug3D database. For the 1004 molecules tested, our SE-ADIM model, which only contains four empirical parameters, greatly reduces the RPE in AM1 polarizability relative to B3LYP from 26.8% to 2.9%. Error decomposition shows consistent improvements across molecules with diverse bond saturations, molecular sizes, and charge states. In addition, we have applied AlphaML, a promising machine learning (ML) technique for predicting molecular polarizability, to the e-Drug3D dataset to compare its performance with our SE-ADIM correction of AM1. We found SE-ADIM performs competitively with AlphaML bolstering our confidence in the value of our method. Errors distinct to AlphaML were also discovered. We found four molecules for which AlphaML predicts negative molecular polarizabilities, all of which were peroxides. In contrast, SE-ADIM has no such issue with these molecules or this chemical type. Finally, to improve performance of SE-ADIM when correcting AM1 molecular polarizability calculations for charged molecules, we introduce a charge dependent polarizability (CDP) enabled SE-ADIM. Training the CDP enabled SE-ADIM with a single additional parameter, B, we were able to reduce error in AM1 molecular polarizability calculations of charged molecules relative to B3LYP from 29.57% to 5.16%. By contrast, SE-ADIM without CDP corrected AM1 relative to B3LYP had an RPE of 8.56%. The most benefit of CDP was evident within negatively charged molecules where AM1 error relative to B3LYP fell from 32.20% to 3.77% while SE-ADIM without CDP enabled error for these same negative molecules was 10.06%.Item Developing a Cell-like Substrate to Investigate the Mechanosensitivity of Cell-to-Cell Junctions(2020-08) Shilts, Kent D.; Naumann, Christoph; Long, Eric; Lin, Chien-chi; Deiss, FrederiqueThe role of mechanical forces in the fate and function of adherent cells has been revealed to be a pivotal factor in understanding cell biology. Cells require certain physical cues to be present in their microenvironment or the cell will begin apoptosis. Mechanical signals from the environment are interpreted at the cellular level and biochemical responses are made due to the information from outside the cell, this process is known as mechanotransduction. Misinterpretation of physical cues has been indicated in many disease states, including heart disease and asthma. When a cell is bound to the ECM, proteins such as integrins are engaged at static and stable adhesion sites. These tight and static anchoring points found at the ECM exist in stark contrast to the dynamic conditions seen at intercellular junctions. Intercellular junctions, such as gap and adherens junctions, are formed between cells to act as a mechanism to relay information and exchange material. Due to the important role intercellular junctions play in processes of wound healing, epithelial-mesenchymal transition and cancer metastasis developing more sophisticated levels of understanding of these mechanisms would provide valuable insight. Complex biological processes, including immune cell signaling and cellular ECM adhesions, have been effectively replicated in model systems. These model systems have included the use of solid supported lipid bilayers and polymeric hydrogels that display cell adhesion molecules. Studies of cellular mechanotransduction at ECM adhesion sites has also been completed with covalently functionalized polymeric substrates of adjustable elasticity. However, developing model systems that allow the accurate reproduction of properties seen at intercellular junctions, while also allowing the investigation of cellular mechanosensitivity has proven to be a difficult task. Previous work has shown that polymer-tethered lipid bilayers (PTLBs) are a viable material to allow the replication of the dynamics and adhesion seen at intercellular junctions. Although efforts have been made to produce PTLBs with different mechanical properties, there is currently not a material with sufficient tunable elastic properties for the study of cellular mechanotransduction. To establish a system that allows the study of stiffness effects across a biologically relevant range (~0.50 – 40 kPa) while maintaining the dynamic properties seen at cell-to-cell junctions, polymer gel-tethered bilayers (PGTBs) were developed. A fabrication strategy was established to allow the incorporation of a hydrogel support with easily tunable stiffness and a tethered lipid bilayer coating, which produced a powerful platform to study the effects of stiffness at intercellular junctions. Careful attention was given to maintain the beneficial properties of membrane diffusion, and it was shown that on different linking architectures lipid bilayers could be established and diffusion was preserved. Microscopy-based FCS and FRAP methodology were utilized to measure lipid diffusion in these systems, while confocal microscopy was used to analyze cell spreading and adhesion. Three distinct architectures to link the lipid membrane to the underlying polyacrylamide hydrogel were pursued in this work, a non-covalent biotin-streptavidin system, a covalently linked design with fibronectin, and a direct covalent linkage utilizing crosslinker chemistry. In this work, it was shown that cells were able to spread and adhere on these substrates, with cell adhesion zones visualized under plated cells that demonstrate the capability of the cell to rearrange the presented linkers, while maintaining a stable material. Also confirmed is the tunability of the polymer hydrogel across a wide range of stiffness, this was shown by quantitative changes in cell spreading area in response to polymer properties.Item Fabrication of Lspr-Based Multiplexed and High-Throughput Biosensor Platforms for Cancer and Sars-Cov-2 Diagnosis(2022-05) Masterson, Adrianna Nichole; Sardar, Rajesh; Long, Eric; Manicke, Nicholas; Naumann, ChristophDesigning and developing a diagnostic technology that is capable of highly sensitive and specific, multiplexed, high-throughput, and quantitative biomarker assays for disease diagnosis and progression is of the upmost importance in modern medicine and patient care. Current diagnostic assays capable of multiplexed and high-throughput analysis include mass spectrometry, electrochemistry, polymerase chain reaction (PCR), and fluorescence-based techniques, however, these techniques suffer from a lack in sensitivity, false responses, or extensive sample processing that are detrimental to clinical diagnostics. To overcome these sensitivity challenges, the field of nanoplasmonics has become utilized when developing diagnostic assays. Plasmonic-based diagnostic tests utilize the unique optical, chemical, and physical property of nanoparticles to increase the sensitivity of the assay. In this dissertation, novel diagnostic platforms that utilize nanoparticles and their localized surface plasmon resonance (LSPR) property will be introduced. LSPR is an optical property in noble metallic nanoparticles that is referred to as the collective oscillation of free electrons upon light irradiation. It is highly dependent on the shape, size, and dielectric constant (refractive index) of the surrounding medium of the nanoparticle and LSPR sensing is based on a change in these properties. In this dissertation, the LSPR property is utilized to fabricate nanoplasmonic-based diagnostic platforms that are capable of multiplexed and high-throughput biomarker assays, with high sensitivity and specificity. The work presented in this dissertation is presented as six chapters, (1) Introduction. (2) Methods, (3) Fabrication of a LSPR-based multiplexed and high-throughput biosensor platform and its application in performing microRNA assays for the diagnosis of bladder cancer. In this chapter, the advancement of single-plex solid state LSPR-based biosensors into a multiplexed and high-throughput diagnostic biosensor platform is reported for the first time. The diagnostic biosensor platform is first fabricated utilizing different gold nanoparticles (spherical nanoparticles, nanorods, and triangular nanoprisms), and then with the gold triangular nanoprisms as the nanoparticle of choice, microRNA assays were performed. The developed biosensor platform is capable of assaying five different types of microRNAs simultaneously at an attomolar limit of detection. Additionally, five microRNA were assayed in 20-bladder cancer patient plasma samples. (4) Development/optimization of the biosensor platform presented in Chapter 3 for the detection of COVID-19 biomarkers. In this chapter, the biosensor platform utilized in Chapter 3 was designed to assay 10 different COVID-19 specific biomarkers from three classes (six viral nucleic acid gene sequences, two spike protein subunits, and two antibodies) with limit of detections in the attomolar range and with high specificity. The high-throughput capability of the biosensor platform was advanced, with the platform performing analysis of a single biomarker in 92 patient samples simultaneously. Additionally, the biomarker platform was utilized to assay all 10 biomarkers in a total of 80 COVID-19 patient samples. (5) Further optimization of the biosensor platform for the development of a highly specific antibody detection test for COVID-19. During the COVID-19 pandemic, knowledge was gained on the specificity of antibodies produced against COVID-19. In this chapter, that knowledge was applied towards the optimization of the biosensor platform presented in Chapter 4 in order to assay SARS-CoV-2 neutralizing antibody IgG. The optimization of the biosensor platform included the size of the gold triangular nanoprisms and the receptor molecule of choice. The biosensor platform assayed this highly specific COVID-19 IgG antibody with a limit of detection as low as 30.0 attomolar with high specificity and no cross reactivity. Additionally, as a proof of concept, the biosensor platform was utilized in a high-throughput format to assay SARS-CoV-2 IgG in a large cohort of 121 COVID-19 patient samples simultaneously. (6) Advancement of the biosensor platform from a 96-well plate to a 384-well plate and its application in assaying microRNA for early diagnosis of pancreatic cancer. In this chapter, the high-throughput capabilities of the biosensor platform presented in Chapters 3-5 was expanded by increasing the sensor amount in one platform from 92 to 359. The 384-well plate biosensor platform was designed, optimized, and utilized to perform microRNA assays for early-stage pancreatic cancer diagnosis. The optimization of the biosensor platform included the manipulation of LSPR-based parameters and the -ssDNA receptor molecule in order to obtain low limit of detections (high sensitivity). Additionally, the biosensor platform assayed two microRNA in a large cohort (n=110) of pancreatic cancer and chronic pancreatitis patient samples.Item Integrated Nanosystems Development Institute(Office of the Vice Chancellor for Research, 2011-04-08) El-Mounayri, Hazim; Witzmann, Frank; Agarwal, Mangilal; Naumann, Christoph; Rizkalla, Maher; Decca, RicardoIntegrated Nanosystems Development Institute (INDI) has been recognized and sponsored as a center under the IUPUI Signature Centers Initiative (SCI). INDI is a multidisciplinary institute dedicated to micro/nanoscale systems research, education, and commercialization while providing cluster of analytical equipment and labs serving over 30 faculty members from different departments and schools in support of their research. Specifically, the vision of the INDI is to be a world-class resource for the realization of nanotechnology-based systems that contribute to the economic growth and social advancement of Indiana and the nation and benefit humanity as a whole. The mission of the center is to: 1) Advance nanotechnology research at IUPUI by promoting innovative interdisciplinary research efforts that will lead to external funding; 2) Enhance IUPUI’s research reputation in nanotechnology, nationally and internationally, by providing an identifiable entity that draws in a diverse group of researchers and promotes the combined strength of the group; and 3) Be a leader in translating bionanotechnology and nanoenergy research into innovations that will contribute to the social well being and economic growth of central Indiana and the nation. INDI builds on an excellent research infrastructure at IUPUI. The core facilities of the institute include cleanroom, nano/microfabrication & characterization facilities, and high power simulation and computational resources. Currently, faculty from the Schools of Science, Engineering & Technology, Dentistry, and Medicine, are associated with INDI. The given faculty have expertise in a wide range of fields, including chemistry, physics, biology, material science, electrical and computer engineering, mechanical engineering, orthopaedics, and pathology & laboratory medicine. The research focus of the faculty ranges from nanostructured materials fabrication, study of properties, applications in sensors, energy, and biomedicine, and integration of the devices resulting in realization of nanosystems. As part of the INDI initiatives to developing new undergraduate and graduate track in nanotechnology, center members have been instrumental in the recent development of two interdisciplinary courses, Nanosystems Principles and Integrated Nanosystems Process & Devices which are now being offered by various departments. Moreover, INDI associated faculty members were recently awarded $200,000 from NSF Nanotechnology Undergraduate Education Program for integrating nanotechnology in engineering curricula at IUPUI. To increase the awareness in the community and promote recruitment of future students in nanotechnology, INDI is organizing workshops, offering short courses for industrial employees, and hosting summer camps for high school teachers and students. Summer of 2010 attracted more than 30 high school students for the Nanotechnology Discovery Summer Camp hosted by INDI at IUPUI. Moreover, this program has been extended to include a session for high school teachers in summer of 2011. The poster will summarize the mission, vision, faculty and center collaboration, research projects, achievements, and future plans of INDI.Item Integrative Click Chemistry for Tuning Physicochemical Properties of Cancer Cell-Laden Hydrogels(2020-05) Johnson, Hunter C.; Lin, Chien-Chi; Naumann, Christoph; Na, SungsooThe pancreas is a vital organ that secretes key metabolic hormones and digestive enzymes. In pancreatic ductal adenocarcinoma (PDAC), one of the leading causes of cancer-related death in the world, limited advances in diagnosis or therapies have been made over decades. Key features of PDAC progression include an elevated matrix sti ness and an increased deposition of extracellular matrices (ECM), such as hyaluronic acid (HA). Understanding how cells interact with components in the tumor microenvironment (TME) as PDAC progresses can assist in developing diagnostic tools and therapeutic treatment options. In recent years, hydrogels have proven to be an excellent platform for studying cell-cell and cell-matrix interactions. Utilizing chemically modi ed and naturally derived materials, hydrogel networks can be formed to encompass not only the components, but also the physicochemical properties of the dynamic TME. In this work, a dynamic hydrogel system that integrates multiple click chemistries was developed for tuning matrix physicochemical properties in a manner similar to the temporally increased matrix sti ness and depositions of HA. Subsequently, these dynamic hydrogels were used to investigate how matrix sti ening and increased HA presentation might a ect survival of PDAC cells and their response to chemotherapeutics.Item Machine Learning Facilitated Quantum Mechanic/Molecular Mechanic Free Energy Simulations(2023-08) Snyder, Ryan; Pu, Jingzhi; Naumann, Christoph; Webb, Ian; Deng, YongmingBridging the accuracy of ab initio (AI) QM/MM with the efficiency of semi-empirical (SE) QM/MM methods has long been a goal in computational chemistry. This dissertation presents four ∆-Machine learning schemes aimed at achieving this objective. Firstly, the incorporation of negative force observations into the Gaussian process regression (GPR) model, resulting in GPR with derivative observations, demonstrates the remarkable capability to attain high-quality potential energy surfaces, accurate Cartesian force descriptions, and reliable free energy profiles using a training set of just 80 points. Secondly, the adaptation of the sparse streaming GPR algorithm showcases the potential of memory retention from previous phasespace, enabling energy-only models to converge using simple descriptors while faithfully reproducing high-quality potential energy surfaces and accurate free energy profiles. Thirdly, the utilization of GPR with atomic environmental vectors as input features proves effective in enhancing both potential energy surface and free energy description. Furthermore, incorporating derivative information on solute atoms further improves the accuracy of force predictions on molecular mechanical (MM) atoms, addressing discrepancies arising from QM/MM interaction energies between the target and base levels of theory. Finally, a comprehensive comparison of three distinct GPR schemes, namely GAP, GPR with an average kernel, and GPR with a system-specific sum kernel, is conducted to evaluate the impact of permutational invariance and atomistic learning on the model’s quality. Additionally, this dissertation introduces the adaptation of the GAP method to be compatible with the sparse variational Gaussian processes scheme and the streaming sparse GPR scheme, enhancing their efficiency and applicability. Through these four ∆-Machine learning schemes, this dissertation makes significant contributions to the field of computational chemistry, advancing the quest for accurate potential energy surfaces, reliable force descriptions, and informative free energy profiles in QM/MM simulations.Item Nanoplasmonic efficacy of gold triangular nanoprisms in measurement science: applications ranging from biomedical to forensic sciences(2019-12) Liyanage, Thakshila; Sardar, Rajesh; Goodpaster, John; Naumann, Christoph; Agarwal, MangilalNoble metal nanostructures display collective oscillation of the surface conduction electrons upon light irradiation as a form of localized surface plasmon resonance (LSPR) properties. Size, shape, and refractive index of the surrounding environment are the key features that control the LSPR properties. Surface passivating ligands on to the nanostructure can modify the charge density of nanostructures. Further, allow resonant wavelengths to match that of the incident light. This unique phenomenon called the “plasmoelectric effect.” According to the Drude model, red and blue shifts of LSPR peak of nanostructures are observed in the event of reducing and increasing charge density, respectively. However, herein, we report unusual LSPR properties of gold triangular nanoprisms (Au TNPs) upon functionalization with para-substituted thiophenols (X-Ph-SH, X = -NH2, -OCH3, -CH3, -H, -Cl, -CF3, and -NO2). Accordingly, we hypothesized that an appropriate energy level alignment between the Au Fermi energy and the HOMO or LUMO of ligands allows the delocalization of surface plasmon excitation at the hybrid inorganic-organic interface. Thus, provides a thermodynamically driven plasmoelectric effect. We further validated our hypothesis by calculating the HOMO and LUMO levels and work function changes of Au TNPs upon functionalization with para-substituted thiol. This reported unique finding then utilized to design ultrasensitive plasmonic substrate for biosensing of cancer microRNA in bladder cancer and cardiovascular diseases. In the discovery of early bladder cancer diagnosis platform, for the first time, we have been utilized to analyze the tumor suppressor microRNA for a more accurate diagnosis of BC. Additionally, we have been advancing our sensing platform to mitigate the false positive and negative responses of the sensing platform using surface-enhanced fluorescence technique. This noninvasive, highly sensitive, highly specific, also does not have false positives techniques that provide the strong key to detect cancer at a very early stage, hence increase the cancer survival rate. Moreover, the electromagnetic field enhancement of Surface-Enhanced Raman Scattering (SERS) and other related surface-enhanced spectroscopic processes resulted from the LSPR property. This dissertation describes the design and development of entirely new SERS nanosensors using a flexible SERS substrate based on the unique LSPR property of Au TNPs. The developed sensor shows an excellent SERS activity (enhancement factor = ~6.0 x 106) and limit of detection (as low as 56 parts-per-quadrillions) with high selectivity by chemometric analyses among three commonly used explosives (TNT, RDX, and PETN). Further, we achieved the programmable self-assembly of Au TNPs using molecular tailoring to form a 3D supper lattice array based on the substrate effect. Here we achieved the highest reported sensitivity for potent drug analysis, including opioids and synthetic cannabinoids from human plasma obtained from the emergency room. This exquisite sensitivity is mainly due to the two reasons, including molecular resonance of the adsorbate molecules and the plasmonic coupling among the nanoparticles. Altogether we are highly optimistic that our research will not only increase the patient survival rate through early detection of cancer but also help to battle the “war against drugs” that together are expected to enhance the quality of human life.Item Nanotechnology Research, Education, and Outreach by the Integrated Nanosystems Development Institute (INDI)(Office of the Vice Chancellor for Research, 2012-04-13) Naumann, Christoph; Rizkalla, Maher; Decca, Ricardo; El-Mounayri, Hazim; Witzmann, Frank; Agarwal, MangilalAbstract: The Integrated Nanosystems Development Institute (INDI), sponsored under the IUPUI Signature Centers Initiative, with a vision of becoming a world-recognized resource for the realization of nanotechnology-based systems, is advancing both nanotechnology research and education on campus. Innovation in nanotechnology requires multidisciplinary approaches and INDI, a collective group of faculty members across departments and schools (including the School of Engineering and Technology, School of Science, School of Dentistry, and School of Medicine), enables interdisciplinary research collaborations and offers nanosystems coursework to students in science and engineering disciplines. Current research efforts span a range of critical issues in nanomaterials, nanodevices, nanosystems, energy, physics, and nanomedicine, and include projects such as the design and characterization of nanoarchitectures for biomedical applications, advancing fuel cell and energy storage technologies, and investigating nanoparticle toxicology. Several members of INDI have externally funded research and outreach projects. The nanotechnology research capabilities within INDI, including of a cluster of analytical equipment and lab resources for nanosystems development and characterization, support local industry needs as well as the research interests of over 30 faculty members and over 100 students (undergraduate, graduate and postdoctoral) on the IUPUI campus. INDI also provides, through the newly developed courses, students with both theory and hands-on experiences involving the fabrication, characterization, and applications of nanosystems. These courses are also part of IUPUI’s newly developed Nanotechnology Track in Mechanical Engineering and Electrical and Computer Engineering degree programs, and the Energy Engineering degree program. In addition, INDI’s active community outreach activities, including its nanotechnology summer camps for K-12 students and teachers, provide early exposure to nanofabrication techniques and research. These classroom and lab-based experiences are designed to encourage higher education and involvement in academic research in an effort to generate the advanced workforce needed by Indiana and the nation.Item QM/MM Applications and Corrections for Chemical Reactions(2023-05) Kim, Bryant; Pu, Jingzhi; Naumann, Christoph; Vilseck, Jonah; Webb, IanIn 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.