Teaching of drug disposition using physiologically based pharmacokinetic modeling software: GastroPlus as an educational tool.

Physiologically based pharmacokinetic (PBPK) modeling requires an understanding of chemical, physiologic, and pharmacokinetic principles. Active learning with PBPK modeling software (GastroPlus) may be useful to teach these scientific principles while also teaching software operation. To examine this issue, a graduate-level course was designed using learning objectives in science, software use, and PBPK model application. These objectives were taught through hands-on PBPK modeling to answer clinically relevant questions. Students demonstrated proficient use of software, based on their responses to these questions, and showed an improved understanding of scientific principles on a pre- and post-course assessment. These outcomes support the effectiveness of simultaneous teaching of interdependent software and science.NEW & NOTEWORTHY Physiologically based pharmacokinetic (PBPK) modeling is a major growth area in drug development, regulatory submissions, and clinical applications. There is a demand for experts in this area with multidisciplinary backgrounds. In this article, we describe a course designed to teach PBPK modeling and the underlying scientific principles in parallel.

Prediction of Water Distributions and Displacement at Protein-Ligand Interfaces.

The retention and displacement of water molecules during formation of ligand-protein interfaces play a major role in determining ligand binding. Understanding these effects requires a method for positioning of water molecules in the bound and unbound proteins and for defining water displacement upon ligand binding. We describe an algorithm for water placement and a calculation of ligand-driven water displacement in >9000 protein-ligand complexes. The algorithm predicts approximately 38% of experimental water positions within 1.0 Å and about 83% within 1.5 Å. We further show that the predicted water molecules can complete water networks not detected in crystallographic structures of the protein-ligand complexes. The algorithm was also applied to solvation of the corresponding unbound proteins, and this allowed calculation of water displacement upon ligand binding based on differences in the water network between the bound and unbound structures. We illustrate use of this approach through comparison of water displacement by structurally related ligands at the same binding site. This method for evaluation of water displacement upon ligand binding may be of value for prediction of the effects of ligand modification in drug design.

Ligand-specific pharmacogenetic effects of nonsynonymous mutations.

In pharmacogenomics, variable receptor phenotypes, resulting from genetic polymorphisms, are often described as a change in protein function or regulation observed upon exposure to a drug. However, in some instances, phenotypes are defined using a class of medications rather than individual drugs. This paradigm assumes that a variation associated with a drug response phenotype will retain the magnitude and direction of the effect for other drugs with the same mechanism of action. However, nonsynonymous polymorphisms may have ligand-specific effects. The purpose of this study was to investigate the potential for point mutations to asymmetrically affect the binding of different drugs to a common target. Ligand binding data from site-directed mutagenesis studies on five G-protein coupled receptors (beta-1 and -2 adrenergic, dopamine D2, angiotensin II and mu-opioid receptor) were collected and analyzed. Binding data from 81 studies for 253 ligands with 447 mutant proteins, including 10 naturally occurring human variants, were analyzed, yielding 1989 mutation-ligand pairs. Fold change in binding affinity for mutant proteins, relative to the wild-type, for different drugs was examined for ligand-specific effects, with a fold-change difference of one or more orders of magnitude between agents considered significant. Of the mutations examined, 49% were associated with ligand-specific effects. One human variant (T164I, beta-2 adrenergic receptor) showed ligand-specific effects for antiasthmatic agents. These results indicate that ligand-specific changes in binding are a possible consequence of missense mutations. This implies that caution needs to be exercised when grouping drugs together during design or interpretation of genotype-phenotype association studies.

Experimental Validation of the ALLNOX Program for Studying Protein-Nucleic Acid Complexes.

Measurement of distances between spectroscopic labels (e.g., spin labels, fluorophores) attached to specific sites of biomolecules is an important method for studying biomolecular complexes. ALLNOX (Addition of Labels and Linkers) has been developed as a program to model interlabel distances based on an input macromolecule structure. Here, we report validation of ALLNOX using measured distances between nitroxide spin labels attached to specific sites of a protein-DNA complex. The results demonstrate that ALLNOX predicts average interspin distances that matched with values measured with pairs of labels attached at the protein and/or DNA. This establishes a solid foundation for using spin labeling in conjunction with ALLNOX to investigate complexes without high-resolution structures. With its high degree of flexibility for the label or the target biomolecule, ALLNOX provides a useful tool for investigating the structure-function relationship in a large variety of biological molecules.

Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 2. Rational Bioavailability Design by Global Sensitivity Analysis To Identify Properties Affecting Bioavailability.

When medicinal chemists need to improve oral bioavailability (%F) during lead optimization, they systematically modify compound properties mainly based on their own experience and general rules of thumb. However, at least a dozen properties can influence %F, and the difficulty of multiparameter optimization for such complex nonlinear processes grows combinatorially with the number of variables. Furthermore, strategies can be in conflict. For example, adding a polar or charged group will generally increase solubility but decrease permeability. Identifying the 2 or 3 properties that most influence %F for a given compound series would make %F optimization much more efficient. We previously reported an adaptation of physiologically based pharmacokinetic (PBPK) simulations to predict %F for lead series from purely computational inputs within a 2-fold average error. Here, we run thousands of such simulations to generate a comprehensive "bioavailability landscape" for each series. A key innovation was recognition that the large and variable number of p Ka's in drug molecules could be replaced by just the two straddling the isoelectric point. Another was use of the ZINC database to cull out chemically inaccessible regions of property space. A quadratic partial least squares regression (PLS) accurately fits a continuous surface to these thousands of bioavailability predictions. The PLS coefficients indicate the globally sensitive compound properties. The PLS surface also displays the %F landscape in these sensitive properties locally around compounds of particular interest. Finally, being quick to calculate, the PLS equation can be combined with models for activity and other properties for multiobjective lead optimization.

Physiologically Based Pharmacokinetic Modeling in Lead Optimization. 1. Evaluation and Adaptation of GastroPlus To Predict Bioavailability of Medchem Series.

When medicinal chemists need to improve bioavailability (%F) within a chemical series during lead optimization, they synthesize new series members with systematically modified properties mainly by following experience and general rules of thumb. More quantitative models that predict %F of proposed compounds from chemical structure alone have proven elusive. Global empirical %F quantitative structure-property (QSPR) models perform poorly, and projects have too little data to train local %F QSPR models. Mechanistic oral absorption and physiologically based pharmacokinetic (PBPK) models simulate the dissolution, absorption, systemic distribution, and clearance of a drug in preclinical species and humans. Attempts to build global PBPK models based purely on calculated inputs have not achieved the <2-fold average error needed to guide lead optimization. In this work, local GastroPlus PBPK models are instead customized for individual medchem series. The key innovation was building a local QSPR for a numerically fitted effective intrinsic clearance (CLloc). All inputs are subsequently computed from structure alone, so the models can be applied in advance of synthesis. Training CLloc on the first 15-18 rat %F measurements gave adequate predictions, with clear improvements up to about 30 measurements, and incremental improvements beyond that.

Rational drug design and synthesis of new α-Santonin derivatives as potential COX-2 inhibitors.

Sesquiterpene compounds are widely known for their numerous pharmacological activities. Herein the focus of the authors was on α-Santonin, a sesquiterpene lactone from the Artemisia genus: the aim was to determine whether α-Santonin could be considered in the treatment of inflammation and pain. To this purpose, a small series of derivatives was designed and screened in silico against the enzyme COX-2 along with the parent compound. Drug-likeness parameters were also assessed. The compounds were eventually synthesized, and few were tested to determine their efficacy in the inhibition of COX-2 activity and expression. Overall, compound A2 was the only one with a detectable inhibitory potential of COX-2 activity whilst two of its ether derivatives demonstrated improved ability in the inhibition of COX-2 expression.

A curcumin-diglutaric acid conjugated prodrug with improved water solubility and antinociceptive properties compared to curcumin.

In this work, a curcumin-diglutaric acid (CurDG) prodrug was synthesized by conjugation of curcumin with glutaric acid via an ester linkage. The water solubility, partition coefficient, release characteristics, and antinociceptive activity of CurDG were compared to those of curcumin. The aqueous solubility of CurDG (7.48 µg/mL) is significantly greater than that of curcumin (0.068 µg/mL). A study in human plasma showed that the CurDG completely releases curcumin within 2 h, suggesting the ability of CurDG to serve as a prodrug of curcumin. A hot plate test in mice showed the highest antinociceptive effect dose of curcumin at 200 mg/kg p.o., whereas CurDG showed the same effect at an effective dose of 100 mg/kg p.o., indicating that CurDG significantly enhanced the antinociceptive effect compared to curcumin. The enhanced antinociceptive effect of CurDG may be due to improved water solubility and increased oral bioavailability compared to curcumin.

The role of the C-terminal helix of U1A protein in the interaction with U1hpII RNA.

Previous kinetic investigations of the N-terminal RNA Recognition Motif (RRM) domain of spliceosomal A protein of the U1 small nuclear ribonucleoprotein particle (U1A) interacting with its RNA target U1 hairpin II (U1hpII) provided experimental evidence for a 'lure and lock' model of binding. The final step of locking has been proposed to involve conformational changes in an α-helix immediately C-terminal to the RRM domain (helix C), which occludes the RNA binding surface in the unbound protein. Helix C must shift its position to accommodate RNA binding in the RNA-protein complex. This results in a new hydrophobic core, an intraprotein hydrogen bond and a quadruple stacking interaction between U1A and U1hpII. Here, we used a surface plasmon resonance-based biosensor to gain mechanistic insight into the role of helix C in mediating the interaction with U1hpII. Truncation, removal or disruption of the helix exposes the RNA-binding surface, resulting in an increase in the association rate, while simultaneously reducing the ability of the complex to lock, reflected in a loss of complex stability. Disruption of the quadruple stacking interaction has minor kinetic effects when compared with removal of the intraprotein hydrogen bonds. These data provide new insights into the mechanism whereby sequences C-terminal to an RRM can influence RNA binding.

An Artificial Intelligence-Supported Medicinal Chemistry Project: An Example for Incorporating Artificial Intelligence Within the Pharmacy Curriculum.

OBJECTIVE: This study aims to integrate and use AI to teach core concepts in a medicinal chemistry course and to increase the familiarity of pharmacy students with AI in pharmacy practice and drug development. Artificial intelligence (AI) is a multidisciplinary science that aims to build software tools that mimic human intelligence. AI is revolutionizing pharmaceutical research and patient care. Hence, it is important to include AI in pharmacy education to prepare a competent workforce of pharmacists with skills in this area. METHODS: AI principles were introduced in a required medicinal chemistry course for first-year pharmacy students. An AI software, KNIME, was used to examine structure-activity relationships for 5 drugs. Students completed a data sheet that required comprehension of molecular structures and drug-protein interactions. These data were then used to make predictions for molecules with novel substituents using AI. The familiarity of students with AI was surveyed before and after this activity. RESULTS: There was an increase in the number of students indicating familiarity with use of AI in pharmacy (before vs after: 25.3% vs 74.5%). The introduction of AI stimulated interest in the course content (> 60% of students indicated increased interest in medicinal chemistry) without compromising the learning outcomes. Almost 70% of students agreed that more AI should be taught in the PharmD curriculum. CONCLUSION: This is a successful and transferable example of integrating AI in pharmacy education without changing the main learning objectives of a course. This approach is likely to stimulate student interest in AI applications in pharmacy.

Pharmacokinetic model of human exposure to ciprofloxacin through consumption of fish.

Fluoroquinolones are broad-spectrum antibiotics that accumulate in the environment. To assess human exposure through the food chain, we developed a pharmacokinetic model of fluoroquinolone accumulation in fish and a human pharmacokinetic model to predict gastrointestinal concentrations of ciprofloxacin, a common fluoroquinolone, following consumption of fish. At 70 ng/L ciprofloxacin, the average in North American surface waters, the fish steady-state concentration was calculated to be 7.5 × 10-6 µg/g. Upon human consumption of the FDA-recommended portion of 113 g of fish containing this ciprofloxacin level, the predicted human intestinal concentration was 2 × 10-6 µg/mL. At 4 × 106 ng/L (4 µg/mL) ciprofloxacin, the highest recorded environmental measurement, these numbers were 0.42 µg/g in fish and 0.1 µg/mL in the human intestine. Thus, based on the ciprofloxacin MIC for E. coli of 0.13 µg/mL, background environmental ciprofloxacin levels are unlikely to be problematic, but environmental pollution can result in high intestinal levels that may cause gut dysbiosis and antibiotic resistance.

Fibril structure of human islet amyloid polypeptide.

Misfolding and amyloid fibril formation by human islet amyloid polypeptide (hIAPP) are thought to be important in the pathogenesis of type 2 diabetes, but the structures of the misfolded forms remain poorly understood. Here we developed an approach that combines site-directed spin labeling with continuous wave and pulsed EPR to investigate local secondary structure and to determine the relative orientation of the secondary structure elements with respect to each other. These data indicated that individual hIAPP molecules take up a hairpin fold within the fibril. This fold contains two ß-strands that are much farther apart than expected from previous models. Atomistic structural models were obtained using computational refinement with EPR data as constraints. The resulting family of structures exhibited a left-handed helical twist, in agreement with the twisted morphology observed by electron microscopy. The fibril protofilaments contain stacked hIAPP monomers that form opposing ß-sheets that twist around each other. The two ß-strands of the monomer adopt out-of-plane positions and are staggered by about three peptide layers (∼15 Å). These results provide a mechanism for hIAPP fibril formation and could explain the remarkable stability of the fibrils. Thus, the structural model serves as a starting point for understanding and preventing hIAPP misfolding.

Electrophoretic mobility of duplex DNA cross-linked by mechlorethamine at a cytosine-cytosine mismatch pair.

The common nitrogen mustard, mechlorethamine, can form a covalent cross-link between the two bases of a cytosine-cytosine mismatch pair within a DNA duplex. The cross-linked species can be readily separated from DNA monoadducts and unreacted strands using denaturing polyacrylamide gel electrophoresis. Here, using DNA 19 mer duplexes that are mechlorethamine cross-linked at a C(4)-C(35), C(7)-C(32), C(10)-C(29), or C(13)-C(26) mismatch pair, we show that the denaturing polyacrylamide gel electrophoresis mobility of the cross-linked species is particularly sensitive to the proximity of the C-C cross-link to the duplex end. Species that are cross-linked at a C(4)-C(35) mismatch have greater mobilities than those cross-linked at C(7)-C(32) or C(13)-C(26), and the species with a central C(10)-C(29) cross-link have the lowest mobility. The mobility is also dependent on the proximity of the cross-link to a 5'-(32)P-phosphate or a 5'-fluorescein label. We interpret these results in terms of the conformational properties of the cross-linked species in the denaturing gel. The results are consistent with the retention of partial duplex character at the end proximal to the cross-link, with an influence on the mobility of the GC/AT ratio proximal to the cross-link and at the duplex end, and a small but discernible effect of the label.

Prediction of Peptide and TCR CDR3 Loops in Formation of Class I MHC-Peptide-TCR Complexes Using Molecular Models with Solvation.

Formation of major histocompatibility (MHC)-peptide-T cell receptor (TCR) complexes is central to initiation of an adaptive immune response. These complexes form through initial stabilization of the MHC fold via binding of a short peptide, and subsequent interaction of the TCR to form a ternary complex, with contacts made predominantly through the complementarity-determining region (CDR) loops of the TCR. Stimulation of an immune response is central to cancer immunotherapy. This approach depends on identification of the appropriate combinations of MHC molecules, peptides, and TCRs to elicit an antitumor immune response. This prediction is a current challenge in computational biochemistry. In this chapter, we introduce a predictive method that involves generation of multiple peptides and TCR CDR 3 loop conformations, solvation of these conformers in the context of the MHC-peptide-TCR ternary complex, extraction of parameters from the generated complexes, and use of an AI model to evaluate the potential for the assembled ternary complex to support an immune response.

Global structure of a three-way junction in a phi29 packaging RNA dimer determined using site-directed spin labeling.

The condensation of bacteriophage phi29 genomic DNA into its preformed procapsid requires the DNA packaging motor, which is the strongest known biological motor. The packaging motor is an intricate ring-shaped protein/RNA complex, and its function requires an RNA component called packaging RNA (pRNA). Current structural information on pRNA is limited, which hinders studies of motor function. Here, we used site-directed spin labeling to map the conformation of a pRNA three-way junction that bridges binding sites for the motor ATPase and the procapsid. The studies were carried out on a pRNA dimer, which is the simplest ring-shaped pRNA complex and serves as a functional intermediate during motor assembly. Using a nucleotide-independent labeling scheme, stable nitroxide radicals were attached to eight specific pRNA sites without perturbing RNA folding and dimer formation, and a total of 17 internitroxide distances spanning the three-way junction were measured using Double Electron-Electron Resonance spectroscopy. The measured distances, together with steric chemical constraints, were used to select 3662 viable three-way junction models from a pool of 65 billion. The results reveal a similar conformation among the viable models, with two of the helices (H(T) and H(L)) adopting an acute bend. This is in contrast to a recently reported pRNA tetramer crystal structure, in which H(T) and H(L) stack onto each other linearly. The studies establish a new method for mapping global structures of complex RNA molecules, and provide information on pRNA conformation that aids investigations of phi29 packaging motor and developments of pRNA-based nanomedicine and nanomaterial.

Idealized models of protofilaments of human islet amyloid polypeptide.

Fibrils formed by assembly of human islet amyloid polypeptide (hIAPP) are found in most patients with type II diabetes. Structurally, these fibrils are composed of multiple protofilaments and are characterized by extended beta sheets, variable helical twists, and different morphologies. We have previously derived models for the hIAPP protofilament using simulations constrained by data from EPR spectroscopy. In the current work, these models were used as a basis for generating idealized hIAPP protofilaments with symmetrical geometrical properties using a new algorithm, MFIBRIL. We show good agreement of the idealized protofilaments with experimental data for amino acid side chain orientations and geometrical features including the inter-ß sheet distance and the protofilament radius. These idealized protofilaments can be used in MFIBRIL to generate fibril models that may be experimentally testable at the molecular level. MFIBRIL can also be used for building structures of any repetitive molecular assembly starting with a single building block obtained from any source.

Information intervention in the pharmaceutical sciences.

Professional guidelines state that higher-order thinking skills are a desirable outcome of pharmacy education. In this context, courses in pharmaceutics at the University of Southern California are taught in a learner-centered manner that requires use of chemical reference sources and interpretation of physicochemical information for drug molecules. To facilitate these activities, a librarian worked with faculty to design a class on reference sources and primary literature. Students believed the librarian instruction was beneficial. After the intervention, faculty fielded fewer information-related questions and the librarian received more sophisticated questions. The class emphasizes the importance of collaboration between librarians and faculty in achieving these results.

Assessment of the impact of co-curricular activities on achievement of Doctor of Pharmacy program outcomes.

INTRODUCTION: Co-curricular activities are recognized as an increasingly important aspect of pharmacy education. However, the impact of these activities on student learning is not well understood compared to that of curricular learning. The purpose of this study was to assess student-perceived progress in achieving program outcomes through voluntary co-curricular activities compared with learning of the same outcomes through mandatory curricular activities. METHODS: The study was performed over six semesters between fall 2017 and spring 2020 at the University of Southern California School of Pharmacy. Separate surveys were sent to all first- through third-year doctor of pharmacy students each semester to assess the impact of curricular and co-curricular activities on improvement in six program outcomes. Graduating student survey data were also mapped to learning outcomes to assess improvement of these outcomes upon graduation. RESULTS: Three main results emerged from these data. First, there was greater variation in the impact of co-curricular activities on different learning outcomes compared to the effect of curricular activities on the same outcomes. Second, co-curricular activities had a greater impact on "soft skills," including leadership and professionalism, compared to concrete knowledge in areas such as therapeutic mechanisms. Finally, the impact of co-curricular activities on most learning outcomes diminished with progression through the curriculum while the impact of curricular activities remained relatively constant. CONCLUSIONS: Student-perceived improvement in learning of program outcomes differs when based on co-curricular compared to curricular activities. These results show how these activities can complement each other in achievement of program outcomes.

Roles of amphipathic helices and the bin/amphiphysin/rvs (BAR) domain of endophilin in membrane curvature generation.

Control of membrane curvature is required in many important cellular processes, including endocytosis and vesicular trafficking. Endophilin is a bin/amphiphysin/rvs (BAR) domain protein that induces vesicle formation by promotion of membrane curvature through membrane binding as a dimer. Using site-directed spin labeling and EPR spectroscopy, we show that the overall BAR domain structure of the rat endophilin A1 dimer determined crystallographically is maintained under predominantly vesiculating conditions. Spin-labeled side chains on the concave surface of the BAR domain do not penetrate into the acyl chain interior, indicating that the BAR domain interacts only peripherally with the surface of a curved bilayer. Using a combination of EPR data and computational refinement, we determined the structure of residues 63-86, a region that is disordered in the crystal structure of rat endophilin A1. Upon membrane binding, residues 63-75 in each subunit of the endophilin dimer form a slightly tilted, amphipathic alpha-helix that directly interacts with the membrane. In their predominant conformation, these helices are located orthogonal to the long axis of the BAR domain. In this conformation, the amphipathic helices are positioned to act as molecular wedges that induce membrane curvature along the concave surface of the BAR domain.

Modeling of the water network at protein-RNA interfaces.

Water plays an important role in the mediation of biomolecular interactions. Thus, accurate prediction and evaluation of water-mediated interactions is an important element in the computational design of interfaces involving proteins, RNA, and DNA. Here, we use an algorithm (WATGEN) to predict the locations of interfacial water molecules for a data set of 224 protein-RNA interfaces. The accuracy of the prediction is validated against water molecules present in the X-ray structures of 105 of these complexes. The complexity of the water networks is deconvoluted through definition of the characteristics of each water molecule based on its bridging properties between the protein and RNA and on its depth in the interface with respect to the bulk solvent. This approach has the potential for scoring the water network for incorporation into the computational design of protein-RNA complexes.