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Revealing the Mechanism of Binding Selectivity in Undecaprenyl Diphosphate Synthase
Tuesday, February 14, 2017 Specifically, we characterize variants within all four repeats in the MTBR and at both N- (R5L and R5H) and C-termini (R406W). To investigate this, we used fluorescence correlation spectroscopy (FCS) to quantify the binding of tau variants to soluble tubulin. Changes in the affinity and function were correlated with the topological features of each tau mutant in solution or upon interaction with soluble tubulin by using single-molecule FRET. Together, our work allows to identify domain/region specific conformational changes in tau relevant to tauopathies and to explore the effect on its intrinsically disordered features. This provides a structural basis for understanding the impact of tau disease mutations in the tau-tubulin complex.
Platform: Protein Dynamics and Allostery II 1557-Plat Predicting Residues that Increase Antibiotic Resistance of CTX-M9 Enzymes using Molecular Simulation and Statistical Learning George A. Cortina, Malgorzata J. Latallo, Peter M. Kasson. Biomedical Engineering, University of Virginia, Charlottesville, VA, USA. Over 2 million people annually contract a serious antibiotic resistant bacterial infection. Beta-lactamases contribute to antibiotic resistance by hydrolyzing beta-lactam antibiotics, the most commonly used class of antibiotics, and enzymes such as CTX-M9 confer resistance to nearly all commonly used outpatient beta-lactams. We seek to understand how point mutations of these enzymes, both within and away from the drug-binding pocket, alter drug resistance. We have performed molecular dynamics simulations of CTX-M9 and a number of point mutants that increase drug resistance. We then analyzed these with information theoretic methods to (1) prospectively identify residues that alter drug specificity and (2) explain the effect of previously identified gain of function mutations distant from the pocket. In order to globally identify residues contributing to drug activity, we employed positional mutual information, a non-linear measure of atom association based on movement, to detect residues most associated with the drug. We tested these predictions experimentally via alanine mutagenesis. High-ranking residues had a significantly greater loss of activity than low-ranking ones, suggesting that this metric can be used to identify residues important for drug resistance. We also utilized machine learning methods in the form of mutual-informationguided feature selection and decision trees to understand how the effect of distant mutations is transmitted to the drug-binding pocket. Using this technique, we were able to identify a small set of atoms in the binding pocket where particular positional changes identify enhanced drug resistance with >90% accuracy. 1558-Plat Modeling Proteins’ Hidden Conformations to Predict Antibiotic Resistance Gregory Bowman. Washington University in St. Louis, St Louis, MO, USA. TEM b-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models (MSMs) to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometricfootprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced U-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design. 1559-Plat Revealing the Mechanism of Binding Selectivity in Undecaprenyl Diphosphate Synthase Fareeha Kanwal1, Donald Jacobs2,3. 1 Bioinformatics and Genomics, University of North Carolina, Charlotte, NC, USA, 2Physics and Optical Science, University of North Carolina, Charlotte, NC, USA, 3Center for Biomedical Engineering and Science, University of North Carolina, Charlotte, NC, USA. Undecaprenyl Pyrophosphate Synthase (UPPS) represents an excellent drug target to combat bacterial virulence because it disrupts the glycan biosynthesis pathway when inhibited. Binding of a substrate causes the activity in UPPS from different species to respond differently, making it potentially possible to develop a suite of narrow-spectrum antibiotics. Here, we investigate the
317a
differential effects of protein dynamics on the mechanism of action in different species by performing a comparative analysis over the UPPS superfamily, Cis-Isoprenyl Pyrophosphate Synthase (Cis-IPPS) using protein dynamics and pharmacophore modeling. We used MOE and Ligand Scout to compute protein structure and ligand-based pharmacophore models of 14 UPPS protein structures. Molecular dynamics simulation and an ensemblebased statistical mechanics model are used to quantify mobility and stability of UPPS in the apo form, and with bound substrates. We find that quantitative stability flexibility relationships (QSFR) identify conserved flexibly correlated motifs. We find that the binding event affects backbone flexibility over an extended range, suggesting a mechanism of allostery. The most conserved regions in the QSFR motifs include the active site and hydrophobic tunnel, which reflects evolutionary conservation. However, variations are substantial at the interface, particularly in the coiled-coil arm that glues the two monomers together. Interestingly, we observe slight differences in structurebased pharamacophore features across species. We corroborate results obtained from evolutionary trees, pharmacophore modeling, characterization of dynamics and stability to reveal the mechanism of binding selectively. With 14 proteins studied in detail thus far, our results suggest a critical flexibly correlated motion spans both domains of the UPPS homodimer, which creates an allosteric pathway responsible for modulating binding selectively. 1560-Plat Dynamic Flexibility Index Sheds Light on Pin1 Allostery Paul Campitelli1, Huan-Xiang Zhou2, Giovanna Ghirlanda3, S. Banu Ozkan1. 1 Department of Physics, Arizona State University, Tempe, AZ, USA, 2 Department of Biophysics, Florida State University, Tallahasse, FL, USA, 3 Department of Chemistry and Biochemistry, Arizona State University, Tempe, AZ, USA. Allostery, which is regulation from distant sites, plays a major role in biology. Pin1 is a modular protein containing a WW domain and a larger peptidyl prolyl isomarase domain (PPIase) that isomerizes phospho-serine/threonineproline (pS/T-P) motifs, which are critical for signaling within intrinsically disordered loops of cell cycle proteins. Pin1 utilizes allosteric regulations for its function, and binds (pS/T-P) motifs in both domains. The WW domain serves as a docking module, whereas catalysis solely takes place within the PPIase domain. However, enzymatic activity gets enhanced when WW is in the bound form, highlighting PIN1’s allosteric regulation. Previous work using NMR and molecular dynamics analysis has shown that binding induced quenching of fast local motions and strengthening of the interaction between two domains, indicated in particular by decrease in flexibility of catalytic loops. Here we present a novel method, the dynamic flexibility index (DFI) analysis, for characterizing the underlying allosteric communications between two domains. DFI measures the resilience of a given position to the perturbations that occur at different parts of the protein, using linear response theory. This index captures multi-dimensional effects when the protein is displaced out of equilibrium. Moreover, we can also identify the allosteric response in dynamic flexibility based on the perturbation response fluctuation profile of the PPIase domain upon WW binding and distinguish the positions that contribute the most. Finally we also explore the mechanistic link between conformational dynamics and co-evolution to identify mutational positions to alter enzymatic function. 1561-Plat Intrinsic Disordered Controls Transcription of Bacterial Toxin-Antitoixn Modules Abel Garcia-Pino. Biologie Structurale et Biophysique, Universite´ Libre de Bruxelles, Gosselies, Belgium. Intrinsic disorder is highly prevalent in type II bacterial antitoxins. It has long being assumed their presence is linked to the rapid turnover of these antitoxins, however recent evidence suggest they provide unparalleled features that allow moonlighting between toxin neutralization and allosteric control of transcription. Conditional cooperativity the a common mechanism at play for transcription regulation of type II toxin-antitoxin operons and is intricately related to persistence. Conditional cooperativity allows the toxin component of toxinantitoxin modules to act as a co-repressor at low toxin dose respect to the antitoxin or de-repressor when the toxin level exceeds a certain threshold. It has been suggested that the presence of a disordered region in toxin-antitoxin system may play a central role in their transcription regulation.To address how the antitoxin IDR is involved in transcription regulation we studied the phd/doc operon as model transcription regulation system. We provide evidence that the intrinsically disordered region of Phd is a bona fide entropic barrier that precludes full operon repression in the absence of Doc. Binding of the Doc toxin to
Platform: Protein Dynamics and Allostery II 1557-Plat Predicting Residues that Increase Antibiotic Resistance of CTX-M9 Enzymes using Molecular Simulation and Statistical Learning George A. Cortina, Malgorzata J. Latallo, Peter M. Kasson. Biomedical Engineering, University of Virginia, Charlottesville, VA, USA. Over 2 million people annually contract a serious antibiotic resistant bacterial infection. Beta-lactamases contribute to antibiotic resistance by hydrolyzing beta-lactam antibiotics, the most commonly used class of antibiotics, and enzymes such as CTX-M9 confer resistance to nearly all commonly used outpatient beta-lactams. We seek to understand how point mutations of these enzymes, both within and away from the drug-binding pocket, alter drug resistance. We have performed molecular dynamics simulations of CTX-M9 and a number of point mutants that increase drug resistance. We then analyzed these with information theoretic methods to (1) prospectively identify residues that alter drug specificity and (2) explain the effect of previously identified gain of function mutations distant from the pocket. In order to globally identify residues contributing to drug activity, we employed positional mutual information, a non-linear measure of atom association based on movement, to detect residues most associated with the drug. We tested these predictions experimentally via alanine mutagenesis. High-ranking residues had a significantly greater loss of activity than low-ranking ones, suggesting that this metric can be used to identify residues important for drug resistance. We also utilized machine learning methods in the form of mutual-informationguided feature selection and decision trees to understand how the effect of distant mutations is transmitted to the drug-binding pocket. Using this technique, we were able to identify a small set of atoms in the binding pocket where particular positional changes identify enhanced drug resistance with >90% accuracy. 1558-Plat Modeling Proteins’ Hidden Conformations to Predict Antibiotic Resistance Gregory Bowman. Washington University in St. Louis, St Louis, MO, USA. TEM b-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models (MSMs) to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometricfootprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced U-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design. 1559-Plat Revealing the Mechanism of Binding Selectivity in Undecaprenyl Diphosphate Synthase Fareeha Kanwal1, Donald Jacobs2,3. 1 Bioinformatics and Genomics, University of North Carolina, Charlotte, NC, USA, 2Physics and Optical Science, University of North Carolina, Charlotte, NC, USA, 3Center for Biomedical Engineering and Science, University of North Carolina, Charlotte, NC, USA. Undecaprenyl Pyrophosphate Synthase (UPPS) represents an excellent drug target to combat bacterial virulence because it disrupts the glycan biosynthesis pathway when inhibited. Binding of a substrate causes the activity in UPPS from different species to respond differently, making it potentially possible to develop a suite of narrow-spectrum antibiotics. Here, we investigate the
317a
differential effects of protein dynamics on the mechanism of action in different species by performing a comparative analysis over the UPPS superfamily, Cis-Isoprenyl Pyrophosphate Synthase (Cis-IPPS) using protein dynamics and pharmacophore modeling. We used MOE and Ligand Scout to compute protein structure and ligand-based pharmacophore models of 14 UPPS protein structures. Molecular dynamics simulation and an ensemblebased statistical mechanics model are used to quantify mobility and stability of UPPS in the apo form, and with bound substrates. We find that quantitative stability flexibility relationships (QSFR) identify conserved flexibly correlated motifs. We find that the binding event affects backbone flexibility over an extended range, suggesting a mechanism of allostery. The most conserved regions in the QSFR motifs include the active site and hydrophobic tunnel, which reflects evolutionary conservation. However, variations are substantial at the interface, particularly in the coiled-coil arm that glues the two monomers together. Interestingly, we observe slight differences in structurebased pharamacophore features across species. We corroborate results obtained from evolutionary trees, pharmacophore modeling, characterization of dynamics and stability to reveal the mechanism of binding selectively. With 14 proteins studied in detail thus far, our results suggest a critical flexibly correlated motion spans both domains of the UPPS homodimer, which creates an allosteric pathway responsible for modulating binding selectively. 1560-Plat Dynamic Flexibility Index Sheds Light on Pin1 Allostery Paul Campitelli1, Huan-Xiang Zhou2, Giovanna Ghirlanda3, S. Banu Ozkan1. 1 Department of Physics, Arizona State University, Tempe, AZ, USA, 2 Department of Biophysics, Florida State University, Tallahasse, FL, USA, 3 Department of Chemistry and Biochemistry, Arizona State University, Tempe, AZ, USA. Allostery, which is regulation from distant sites, plays a major role in biology. Pin1 is a modular protein containing a WW domain and a larger peptidyl prolyl isomarase domain (PPIase) that isomerizes phospho-serine/threonineproline (pS/T-P) motifs, which are critical for signaling within intrinsically disordered loops of cell cycle proteins. Pin1 utilizes allosteric regulations for its function, and binds (pS/T-P) motifs in both domains. The WW domain serves as a docking module, whereas catalysis solely takes place within the PPIase domain. However, enzymatic activity gets enhanced when WW is in the bound form, highlighting PIN1’s allosteric regulation. Previous work using NMR and molecular dynamics analysis has shown that binding induced quenching of fast local motions and strengthening of the interaction between two domains, indicated in particular by decrease in flexibility of catalytic loops. Here we present a novel method, the dynamic flexibility index (DFI) analysis, for characterizing the underlying allosteric communications between two domains. DFI measures the resilience of a given position to the perturbations that occur at different parts of the protein, using linear response theory. This index captures multi-dimensional effects when the protein is displaced out of equilibrium. Moreover, we can also identify the allosteric response in dynamic flexibility based on the perturbation response fluctuation profile of the PPIase domain upon WW binding and distinguish the positions that contribute the most. Finally we also explore the mechanistic link between conformational dynamics and co-evolution to identify mutational positions to alter enzymatic function. 1561-Plat Intrinsic Disordered Controls Transcription of Bacterial Toxin-Antitoixn Modules Abel Garcia-Pino. Biologie Structurale et Biophysique, Universite´ Libre de Bruxelles, Gosselies, Belgium. Intrinsic disorder is highly prevalent in type II bacterial antitoxins. It has long being assumed their presence is linked to the rapid turnover of these antitoxins, however recent evidence suggest they provide unparalleled features that allow moonlighting between toxin neutralization and allosteric control of transcription. Conditional cooperativity the a common mechanism at play for transcription regulation of type II toxin-antitoxin operons and is intricately related to persistence. Conditional cooperativity allows the toxin component of toxinantitoxin modules to act as a co-repressor at low toxin dose respect to the antitoxin or de-repressor when the toxin level exceeds a certain threshold. It has been suggested that the presence of a disordered region in toxin-antitoxin system may play a central role in their transcription regulation.To address how the antitoxin IDR is involved in transcription regulation we studied the phd/doc operon as model transcription regulation system. We provide evidence that the intrinsically disordered region of Phd is a bona fide entropic barrier that precludes full operon repression in the absence of Doc. Binding of the Doc toxin to