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Discriminating Residue Substitutions between Two Single Proteins with a Sub-Nanopore
348a
Tuesday, February 14, 2017
leading to its decomposition into aminoacetaldehyde and sulfite, where sulfite is a key sulfur containing metabolite in E. coli. The nonheme iron(II) center in TauD is formed from two histidine side chain residues and a glutamic acid coordinating to one face of the octahedral coordination geometry. This common metal binding motif has been termed the 2-His-1-carboxylate facial triad and is found in a number of nonheme manganese, iron, and cobalt containing proteins. Here we have focused our efforts to measure the thermodynamic driving forces that lead to formation of these bioinorganic centers in biology, by studying divalent metal ion coordination to TauD using isothermal titration calorimetry. Titrations of metal complexes into the metal-free (apo) TauD and the corresponding chelation experiments were performed under anaerobic environment. The thermodynamic terms associated with cobalt(II), iron(II), and manganese(II) binding to apoTauD were deconvoluted from complex experiments, where the pH and buffer independent binding constant (K) were measured to be 2.9 109, 2.4 107, and 9.8 105, respectively. (The corresponding DG values were calculated to be 12.8 kcal/mol, 10.1 kcal/mol, and 8.2 kcal/mol, respectively.) Interestingly the measured enthalpy changes for these binding events (DH) are 17.8 kcal/mol, 12.8 kcal/mol, and 12.2 kcal/mol, respectively. These data are fully consistent with the Irving-Williams series, which suggest there is increasing affinity for transition metal ions from left to right across the periodic table. However, it seems this the increasing affinity is derived from increasing favorability of both the related DH and DS terms. 1708-Pos Board B28 Discriminating Residue Substitutions between Two Single Proteins with a Sub-Nanopore Zhuxin Dong. Electrical Engineering, University of Notre Dame, Notre Dame, IN, USA. The two variants of human histone, H3.2 and H3.3, are essentially the same chains of 136 amino acids (AAs), differing by only four residue substitutions, yet the replacement of H3.2 with H3.3 in the chromatin structure is supposed to promote organismal aging through aberrant gene regulation.1 To discriminate between them, measurements of force and concomitant current blockade were performed as these histones, denatured in sodium dodecyl sulfate (SDS) and tethered to the tip of an AFM, were impelled systematically (one-at-a-time) through a sub-nanometer diameter pore, i.e. a sub-nanopore. The force measurements revealed that, once the denatured protein translocated through the sub-nanopore, a disproportionately large force was required to pull it back through, indicating that the SDS was cleaved from the protein allowing it to refold during the translocation. The force measurements also exposed a dichotomy in the translocation kinetics: either the molecule slid nearly frictionlessly through the pore or it slippedand-stuck. When it slid frictionlessly, regular patterns were observed intermittently in the force and blockade current fluctuations that corresponded to the distance between stretched residues. Furthermore, the amplitudes of the fluctuations in the current blockades were correlated with the occluded volume associated with the AAs in the pore waist.2 Finally, the difference in the patterns in the blockade current fluctuations associated with the two histones consistently peaked near position 91 in the sequence, where AA substitution (M->G) occurs, corresponding to volume difference of only 0.085 nm3 in a read. 1 Saade, E.; Pirozhkova, I.; Aimbetov, R.; Lipinski, M.; Ogryzko, V. Molecular turnover, the H3.3 dilemma and organismal aging. Aging Cell 2015,14, 322-333. 2 Kennedy, E.; Dong, Z.; Tennant, C.; Timp, G. Reading the primary structure of a protein with 0.07 nm3 resolution using a sub-nanometre-diameter pore. Nat. Nanotech. 2016, DOI: 10.1038/NNANO.2016.120 1709-Pos Board B29 Effective on-Demand Mining of Structural Databases Lukas Pravda, David Sehnal, Radka Svobodova Varekova, Jaroslav Koca. Central European Institute of Technology, Brno, Czech Republic. The majority of in silico experiments often heavily relies on a data collection. Indeed, identification of biomolecular substructures (patterns) within biomolecular databases, such as Protein Data Bank is a common procedure in structural bioinformatics and related fields. We are seeking for well-defined molecular patterns such as binding or catalytic sites, transcription factors, protein structural, or sequence motifs, etc. These are in turn used to aid structural and functional characterization and comparison of proteins, analysis of newly determined protein structures, identification of similar binding sites in offtarget proteins, discovery of new inhibitors, facilitation of protein-protein interaction and more. This is usually done using a plethora of one-time-only use
in-house programs often in combination with dedicated software tools. Development of such solutions is generally error-prone and time-consuming. Hence the question is, can we do any better? Do we really need all these single purpose programs? Or can we extract biologically important sites in an easy userdefined and customizable way? We have developed PatternQuery (PQ - http://ncbr.muni.cz/PatternQuery) - an online service for mining structural databases such as Protein Data Bank. It enables description of a relationship between atoms, residues, and other structural elements using a simple, yet robust, query language. Each query specifies the composition, topology, connectivity, and 3D structure of a pattern. This allows to relate the primary, secondary, and tertiary structure information simultaneously. Smaller datasets of hundreds of structures can be processed within seconds in interactively. The whole Protein Data Bank or its subset can be processed under an hour. All the results are made available for download and presented in a clear graphical form for online inspection. 1710-Pos Board B30 Interconnection between Parallel Assembly Pathways in Large Ribosome Subunit Biogenesis Riley C. Gentry, Eda Koculi. University of Central Florida, Orlando, FL, USA. The ribosome is the macromolecular machine responsible for protein production in every living cell. While structural studies have provided information on the fully assembled bacterial ribosome, knowledge of bacterial ribosome assembly remains limited. This knowledge is invaluable to facilitate the design of novel antibiotics that target the ribosome assembly process. Ribosome assembly involves rRNA folding, rRNA processing and post-transcriptional modification, r-protein associations, and both association and release of ribosomal maturation factors. In vivo, all of these processes are highly coordinated, but the nature and extent of their coordination is not well understood. In order to study this coordination in vivo, we will exploit the phenotype created by expressing the helicase inactive DbpA protein construct, R331A. DbpA is an Escherichia coli (E. coli) DEAD-box RNA helicase believed to perform RNA structural rearrangements near the peptidyl transferase center. E. coli cells expressing R331A DbpA accumulate three large subunit intermediates. More importantly, previous investigation by our lab of the large ribosomal subunit intermediates’ kinetics of conversion and the 5’ processing of the 23S rRNA demonstrated that these intermediates convert to the large subunit through parallel assembly pathways. Currently, we are probing the RNA processing and structural characteristics of the intermediates using chemical modification followed by next generation sequencing. Additionally, we are in the process of determining the protein composition of the intermediates with mass spectrometry. Combined, the RNA structure, processing, and protein composition of the particles from these three parallel assembly pathways will reveal how the maturation processes are interconnected during large subunit ribosome assembly in vivo.
Protein-Small Molecule Interactions I 1711-Pos Board B31 Kinetics and Pathways of Extremely Long Ligand Release Events Revealed by Wexplore and Conformation Space Networks Samuel D. Lotz, Alex Dickson. Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA. It has been reported on a set of applications that the binding kinetics is more predictive than the binding affinity of the efficacy of a drug molecule in vivo. Although the thermodynamics depends only on the endpoints of the binding pathway, the kinetics depends on details of the binding process, particularly the ligand binding transition state. Unfortunately, the ligand release timescales of pharmaceutically relevant drug molecules can extend up to thousands of seconds: far beyond the reach of conventional molecular sampling approaches. Using WExplore, an algorithm based on concurrent looselycoupled trajectories without biasing forces, we have characterized the ligand release pathways of a number of systems, with residence times extending up to thousands of seconds. By measuring the trajectory flux into the unbound state, we directly compute ligand residence times without using a Markovian assumption that show excellent agreement with those determined experimentally. Throughout we obtain broad sampling of ligand exit pathways, involving distinct exit channels and significant coupled motions between the ligand and the bound receptor. The broad set of ligand bound poses and exit pathways allows us to determine general physical principles of ligand binding, including the specific molecular interactions that govern binding kinetics.
Tuesday, February 14, 2017
leading to its decomposition into aminoacetaldehyde and sulfite, where sulfite is a key sulfur containing metabolite in E. coli. The nonheme iron(II) center in TauD is formed from two histidine side chain residues and a glutamic acid coordinating to one face of the octahedral coordination geometry. This common metal binding motif has been termed the 2-His-1-carboxylate facial triad and is found in a number of nonheme manganese, iron, and cobalt containing proteins. Here we have focused our efforts to measure the thermodynamic driving forces that lead to formation of these bioinorganic centers in biology, by studying divalent metal ion coordination to TauD using isothermal titration calorimetry. Titrations of metal complexes into the metal-free (apo) TauD and the corresponding chelation experiments were performed under anaerobic environment. The thermodynamic terms associated with cobalt(II), iron(II), and manganese(II) binding to apoTauD were deconvoluted from complex experiments, where the pH and buffer independent binding constant (K) were measured to be 2.9 109, 2.4 107, and 9.8 105, respectively. (The corresponding DG values were calculated to be 12.8 kcal/mol, 10.1 kcal/mol, and 8.2 kcal/mol, respectively.) Interestingly the measured enthalpy changes for these binding events (DH) are 17.8 kcal/mol, 12.8 kcal/mol, and 12.2 kcal/mol, respectively. These data are fully consistent with the Irving-Williams series, which suggest there is increasing affinity for transition metal ions from left to right across the periodic table. However, it seems this the increasing affinity is derived from increasing favorability of both the related DH and DS terms. 1708-Pos Board B28 Discriminating Residue Substitutions between Two Single Proteins with a Sub-Nanopore Zhuxin Dong. Electrical Engineering, University of Notre Dame, Notre Dame, IN, USA. The two variants of human histone, H3.2 and H3.3, are essentially the same chains of 136 amino acids (AAs), differing by only four residue substitutions, yet the replacement of H3.2 with H3.3 in the chromatin structure is supposed to promote organismal aging through aberrant gene regulation.1 To discriminate between them, measurements of force and concomitant current blockade were performed as these histones, denatured in sodium dodecyl sulfate (SDS) and tethered to the tip of an AFM, were impelled systematically (one-at-a-time) through a sub-nanometer diameter pore, i.e. a sub-nanopore. The force measurements revealed that, once the denatured protein translocated through the sub-nanopore, a disproportionately large force was required to pull it back through, indicating that the SDS was cleaved from the protein allowing it to refold during the translocation. The force measurements also exposed a dichotomy in the translocation kinetics: either the molecule slid nearly frictionlessly through the pore or it slippedand-stuck. When it slid frictionlessly, regular patterns were observed intermittently in the force and blockade current fluctuations that corresponded to the distance between stretched residues. Furthermore, the amplitudes of the fluctuations in the current blockades were correlated with the occluded volume associated with the AAs in the pore waist.2 Finally, the difference in the patterns in the blockade current fluctuations associated with the two histones consistently peaked near position 91 in the sequence, where AA substitution (M->G) occurs, corresponding to volume difference of only 0.085 nm3 in a read. 1 Saade, E.; Pirozhkova, I.; Aimbetov, R.; Lipinski, M.; Ogryzko, V. Molecular turnover, the H3.3 dilemma and organismal aging. Aging Cell 2015,14, 322-333. 2 Kennedy, E.; Dong, Z.; Tennant, C.; Timp, G. Reading the primary structure of a protein with 0.07 nm3 resolution using a sub-nanometre-diameter pore. Nat. Nanotech. 2016, DOI: 10.1038/NNANO.2016.120 1709-Pos Board B29 Effective on-Demand Mining of Structural Databases Lukas Pravda, David Sehnal, Radka Svobodova Varekova, Jaroslav Koca. Central European Institute of Technology, Brno, Czech Republic. The majority of in silico experiments often heavily relies on a data collection. Indeed, identification of biomolecular substructures (patterns) within biomolecular databases, such as Protein Data Bank is a common procedure in structural bioinformatics and related fields. We are seeking for well-defined molecular patterns such as binding or catalytic sites, transcription factors, protein structural, or sequence motifs, etc. These are in turn used to aid structural and functional characterization and comparison of proteins, analysis of newly determined protein structures, identification of similar binding sites in offtarget proteins, discovery of new inhibitors, facilitation of protein-protein interaction and more. This is usually done using a plethora of one-time-only use
in-house programs often in combination with dedicated software tools. Development of such solutions is generally error-prone and time-consuming. Hence the question is, can we do any better? Do we really need all these single purpose programs? Or can we extract biologically important sites in an easy userdefined and customizable way? We have developed PatternQuery (PQ - http://ncbr.muni.cz/PatternQuery) - an online service for mining structural databases such as Protein Data Bank. It enables description of a relationship between atoms, residues, and other structural elements using a simple, yet robust, query language. Each query specifies the composition, topology, connectivity, and 3D structure of a pattern. This allows to relate the primary, secondary, and tertiary structure information simultaneously. Smaller datasets of hundreds of structures can be processed within seconds in interactively. The whole Protein Data Bank or its subset can be processed under an hour. All the results are made available for download and presented in a clear graphical form for online inspection. 1710-Pos Board B30 Interconnection between Parallel Assembly Pathways in Large Ribosome Subunit Biogenesis Riley C. Gentry, Eda Koculi. University of Central Florida, Orlando, FL, USA. The ribosome is the macromolecular machine responsible for protein production in every living cell. While structural studies have provided information on the fully assembled bacterial ribosome, knowledge of bacterial ribosome assembly remains limited. This knowledge is invaluable to facilitate the design of novel antibiotics that target the ribosome assembly process. Ribosome assembly involves rRNA folding, rRNA processing and post-transcriptional modification, r-protein associations, and both association and release of ribosomal maturation factors. In vivo, all of these processes are highly coordinated, but the nature and extent of their coordination is not well understood. In order to study this coordination in vivo, we will exploit the phenotype created by expressing the helicase inactive DbpA protein construct, R331A. DbpA is an Escherichia coli (E. coli) DEAD-box RNA helicase believed to perform RNA structural rearrangements near the peptidyl transferase center. E. coli cells expressing R331A DbpA accumulate three large subunit intermediates. More importantly, previous investigation by our lab of the large ribosomal subunit intermediates’ kinetics of conversion and the 5’ processing of the 23S rRNA demonstrated that these intermediates convert to the large subunit through parallel assembly pathways. Currently, we are probing the RNA processing and structural characteristics of the intermediates using chemical modification followed by next generation sequencing. Additionally, we are in the process of determining the protein composition of the intermediates with mass spectrometry. Combined, the RNA structure, processing, and protein composition of the particles from these three parallel assembly pathways will reveal how the maturation processes are interconnected during large subunit ribosome assembly in vivo.
Protein-Small Molecule Interactions I 1711-Pos Board B31 Kinetics and Pathways of Extremely Long Ligand Release Events Revealed by Wexplore and Conformation Space Networks Samuel D. Lotz, Alex Dickson. Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA. It has been reported on a set of applications that the binding kinetics is more predictive than the binding affinity of the efficacy of a drug molecule in vivo. Although the thermodynamics depends only on the endpoints of the binding pathway, the kinetics depends on details of the binding process, particularly the ligand binding transition state. Unfortunately, the ligand release timescales of pharmaceutically relevant drug molecules can extend up to thousands of seconds: far beyond the reach of conventional molecular sampling approaches. Using WExplore, an algorithm based on concurrent looselycoupled trajectories without biasing forces, we have characterized the ligand release pathways of a number of systems, with residence times extending up to thousands of seconds. By measuring the trajectory flux into the unbound state, we directly compute ligand residence times without using a Markovian assumption that show excellent agreement with those determined experimentally. Throughout we obtain broad sampling of ligand exit pathways, involving distinct exit channels and significant coupled motions between the ligand and the bound receptor. The broad set of ligand bound poses and exit pathways allows us to determine general physical principles of ligand binding, including the specific molecular interactions that govern binding kinetics.