Probing Ligand Binding Mechanisms in Insulin-Regulated Aminopeptidases : Computational analysis and free energy calculations of binding modes

In recent years insulin-regulated aminopeptidase (IRAP) has emerged as a new therapeutic target for the treatment of Alzheimer’s disease and other memory-related disorders. So far, many potent and specific IRAP inhibitors had been disclosed, including peptides, peptidomimetics, and low-molecular-weight sulfonamides. In this thesis, various computational approaches such as docking, molecular dynamics (MD), linear interaction energy (LIE), and free energy perturbations (FEP) are used to understand the molecular basis for the binding of these inhibitors to the IRAP. By applying MD and LIE, the binding mode of Ang IV and the critical role of its N-terminal tripeptide in the binding to IRAP were described. The stark difference in the binding properties of two stereoisomers of a peptidomimetic inhibitor, HA08 and HA09, was determined using MD simulations and LIE binding affinity estimations. With the help of the FEP method, we discriminate the most probable, between two alternative binding poses for the sulfonamide family of compounds. The binding modes of the HFI family of compounds (competitive inhibitors), and spiro-oxindole compounds (allosteric, uncompetitive inhibitors) were also proposed utilizing a combination of related computational approaches. In this thesis, the specificity of the diverse class of inhibitors and substrates (oxytocin and vasopressin) for IRAP compared to other M1 aminopetidase family members was disclosed as a result of the unique Gly-Ala-Met-Glu-Asn (GAMEN) loop orientation. The different studies performed along this thesis resulted in several proposed binding modes, which were evaluated by different free energy calculation approaches, namely LIE and FEP methods. In all cases, the calculated free energies are in excellent agreement with the experimental data, which strongly supports the final binding models here proposed. These results of this thesis will be useful in future lead generation and optimization process and hopefully in the development of better cognitive enhancers for the treatment of dementia and other related diseases such as Alzheimer’s disease

Probing Ligand Binding Mechanisms in Insulin-Regulated Aminopeptidases : Computational analysis and free energy calculations of binding modes

In recent years insulin-regulated aminopeptidase (IRAP) has emerged as a new therapeutic target for the treatment of Alzheimer’s disease and other memory-related disorders. So far, many potent and specific IRAP inhibitors had been disclosed, including peptides, peptidomimetics, and low-molecular-weight sulfonamides. In this thesis, various computational approaches such as docking, molecular dynamics (MD), linear interaction energy (LIE), and free energy perturbations (FEP) are used to understand the molecular basis for the binding of these inhibitors to the IRAP. By applying MD and LIE, the binding mode of Ang IV and the critical role of its N-terminal tripeptide in the binding to IRAP were described. The stark difference in the binding properties of two stereoisomers of a peptidomimetic inhibitor, HA08 and HA09, was determined using MD simulations and LIE binding affinity estimations. With the help of the FEP method, we discriminate the most probable, between two alternative binding poses for the sulfonamide family of compounds. The binding modes of the HFI family of compounds (competitive inhibitors), and spiro-oxindole compounds (allosteric, uncompetitive inhibitors) were also proposed utilizing a combination of related computational approaches. In this thesis, the specificity of the diverse class of inhibitors and substrates (oxytocin and vasopressin) for IRAP compared to other M1 aminopetidase family members was disclosed as a result of the unique Gly-Ala-Met-Glu-Asn (GAMEN) loop orientation. The different studies performed along this thesis resulted in several proposed binding modes, which were evaluated by different free energy calculation approaches, namely LIE and FEP methods. In all cases, the calculated free energies are in excellent agreement with the experimental data, which strongly supports the final binding models here proposed. These results of this thesis will be useful in future lead generation and optimization process and hopefully in the development of better cognitive enhancers for the treatment of dementia and other related diseases such as Alzheimer’s disease

Perceptions and Motivations of User Engagement for Social Media Marketing : A Quantitative Study of Facebook and Instagram Users

Social media marketing has gained tremendous attention in recent years and has become a powerful tool for companies, entrepreneurs and marketers to approach their target customers and cultivate longtime customer relationship with increased engagement. Despite the increasing investment on social media marketing and the increasingly important roles users play today, few of previous studies, however, were focused on the user behavior or the key factors that influence user engagement with brands on social media. We chose the technology acceptance model (TAM) and uses and gratifications theory (UGT) as our theoretical foundation to investigate user behaviors on social media and the factors that influence user engagement with brands. We tested our model in two different social media platforms; Facebook and Instagram. The conclusions were based on inputs from a survey with 126 respondents with diverse background and age groups. We tested the hypotheses utilizing statistic correlation analyses. Among the five researched variables, H1 (perceived usefulness) and H5 (motivation for information) are proved to be statically significant. Despite a number of limitations, our research sheds a light on the study of user behavior on social media platforms. Understanding user behavior is useful for entrepreneurs and marketers in shaping more efficient ways to target the right audience on the right platform(s) to achieve their marketing objectives by effectively exploiting the potential of social media

Perceptions and Motivations of User Engagement for Social Media Marketing : A Quantitative Study of Facebook and Instagram Users

Social media marketing has gained tremendous attention in recent years and has become a powerful tool for companies, entrepreneurs and marketers to approach their target customers and cultivate longtime customer relationship with increased engagement. Despite the increasing investment on social media marketing and the increasingly important roles users play today, few of previous studies, however, were focused on the user behavior or the key factors that influence user engagement with brands on social media. We chose the technology acceptance model (TAM) and uses and gratifications theory (UGT) as our theoretical foundation to investigate user behaviors on social media and the factors that influence user engagement with brands. We tested our model in two different social media platforms; Facebook and Instagram. The conclusions were based on inputs from a survey with 126 respondents with diverse background and age groups. We tested the hypotheses utilizing statistic correlation analyses. Among the five researched variables, H1 (perceived usefulness) and H5 (motivation for information) are proved to be statically significant. Despite a number of limitations, our research sheds a light on the study of user behavior on social media platforms. Understanding user behavior is useful for entrepreneurs and marketers in shaping more efficient ways to target the right audience on the right platform(s) to achieve their marketing objectives by effectively exploiting the potential of social media

Structural Basis of Inhibition of Human Insulin-Regulated Aminopeptidase (IRAP) by Benzopyran-based Inhibitors

Inhibition of the insulin-regulated aminopeptidase (IRAP) improves memory and cognition in animal models. The enzyme has been recently crystallized and several series of inhibitors reported. We herein focused on one series of benzopyran-based inhibitors of IRAP, known as HFI series, and developed a robust computational model to explain the SAR and potentially guide the optimization of this scaffold. Our binding model positions the benzopyran ring in the catalytic binding site, coordinating the Zn+2 ion through the oxygen in position 3 of the, in contrast to previous hypothesis. The whole series of HFI compounds was systematically simulated using molecular dynamics in this binding orientation and binding affinity estimated with the linear interaction energy (LIE) method. The agreement with experimental affinities supports the binding mode proposed, which was further challenged by rigorous free energy perturbation calculations. Here, we found excellent correlation between experimental and calculated binding affinity differences, both between selected compound pairs and also for recently reported experimental data concerning the site directed mutagenesis of residue Phe544. The computationally derived structure-activity relationship of the HFI series and the demonstrated involvement of Phe544 in the binding of this scaffold provide valuable information for further lead optimization of novel IRAP inhibitors

Structural Basis of Inhibition of Human Insulin-Regulated Aminopeptidase (IRAP) by Aryl Sulfonamides

The insulin-regulated aminopeptidase (IRAP) is a membrane-bound zinc metallopeptidase with many important regulatory functions. It has been demonstrated that inhibition of IRAP by angiotensin IV (Ang IV) and other peptides, as well as more druglike inhibitors, improves cognition in several rodent models. We recently reported a series of aryl sulfonamides as small-molecule IRAP inhibitors and a promising scaffold for pharmacological intervention. We have now expanded with a number of derivatives, report their stability in liver microsomes, and characterize the activity of the whole series in a new assay performed on recombinant human IRAP. Several compounds, such as the new fluorinated derivative <b>29</b>, present submicromolar affinity and high metabolic stability. Starting from the two binding modes previously proposed for the sulfonamide scaffold, we systematically performed molecular dynamics simulations and binding affinity estimation with the linear interaction energy method for the full compound series. The significant agreement with experimental affinities suggests one of the binding modes, which was further confirmed by the excellent correlation for binding affinity differences between the selected pair of compounds obtained by rigorous free energy perturbation calculations. The new experimental data and the computationally derived structure–activity relationship of the sulfonamide series provide valuable information for further lead optimization of novel IRAP inhibitors

Synthesis, Evaluation and Proposed Binding Pose of Substituted Spiro-Oxindole Dihydroquinazolinones as IRAP Inhibitors

Insulin‐regulated aminopeptidase (IRAP) is a new potential macromolecular target for drugs aimed for treatment of cognitive disorders. Inhibition of IRAP by angiotensin IV (Ang IV) improves the memory and learning in rats. The majority of the known IRAP inhibitors are peptidic in character and suffer from poor pharmacokinetic properties. Herein, we present a series of small non‐peptide IRAP inhibitors derived from a spiro‐oxindole dihydroquinazolinone screening hit (pIC50 5.8). The compounds were synthesized either by a simple microwave (MW)‐promoted three‐component reaction, or by a two‐step one‐pot procedure. For decoration of the oxindole ring system, rapid MW‐assisted Suzuki‐Miyaura cross‐couplings (1 min) were performed. A small improvement of potency (pIC50 6.6 for the most potent compound) and an increased solubility could be achieved. As deduced from computational modelling and MD simulations it is proposed that the S‐configuration of the spiro‐oxindole dihydroquinazolinones accounts for the inhibition of IRAP

Conformational Selection in Biocatalytic Plastic Degradation by PETase

Due to the steric effects imposed by bulky polymers, the formation of catalytically competent enzyme and substrate conformations is critical in the biodegradation of plastics. In poly(ethylene terephthalate) (PET), the backbone adopts different conformations, gauche and trans, coexisting to different extents in amorphous and crystalline regions. However, which conformation is susceptible to biodegradation and the extent of enzyme and substrate conformational changes required for expedient catalysis remain poorly understood. To overcome this obstacle, we utilized molecular dynamics simulations, docking, and enzyme engineering in concert with high-resolution microscopy imaging and solid-state nuclear magnetic resonance (NMR) to demonstrate the importance of conformational selection in biocatalytic plastic hydrolysis. Our results demonstrate how single-amino acid substitutions in Ideonella sakaiensis PETase can alter its conformational landscape, significantly affecting the relative abundance of productive ground-state structures ready to bind discrete substrate conformers. We experimentally show how an enzyme binds to plastic and provide a model for key residues involved in the recognition of gauche and trans conformations supported by in silico simulations. We demonstrate how enzyme engineering can be used to create a trans-selective variant, resulting in higher activity when combined with an all-trans PET-derived oligomeric substrate, stemming from both increased accessibility and conformational preference. Our work cements the importance of matching enzyme and substrate conformations in plastic hydrolysis, and we show that also the noncanonical trans conformation in PET is conducive for degradation. Understanding the contribution of enzyme and substrate conformations to biocatalytic plastic degradation could facilitate the generation of designer enzymes with increased performance