In plants, esterase/lipases perform transesterification reactions, playing an important role in t... more In plants, esterase/lipases perform transesterification reactions, playing an important role in the synthesis of useful molecules, such as those comprising the waxy coatings of leaf surfaces. Plant genomes and transcriptomes have provided a wealth of data about expression patterns and the circumstances under which these enzymes are upregulated, e.g. pathogen defense and response to drought; however, predicting their functional characteristics from genomic or transcriptome data is challenging due to weak sequence conservation among the diverse members of this group. Although functional sequence blocks mediating enzyme activity have been identified, progress to date has been hampered by the paucity of information on the structural relationships among these regions and how they affect substrate specificity. Here we present methodology for predicting overall protein flexibility and active site flexibility based on molecular modeling and analysis of protein structure networks (PSNs). We define two new types of specialized PSNs: sequence region networks (SRNs) and active site networks (ASNs), which provide parsimonious representations of molecular structure in reference to known features of interest. Our approach, intended as an aid to target selection for poorly characterized enzyme classes, is demonstrated for 26 previously uncharacterized esterase/lipases from the genome of the carnivorous plant Drosera capensis and
Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and othe... more Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and other biological macromolecules. Topological coarse-graining, in which biomolecules or sets thereof are represented via graph structures, is a particularly useful way of obtaining highly compressed representations of molecular structure, and simulations operating via such representations can achieve substantial computational savings. A drawback of coarse-graining, however, is the loss of atomistic detail-an effect that is especially acute for topological representations such as protein structure networks (PSNs). Here, we introduce an approach based on a combination of machine learning and physicallyguided refinement for inferring atomic coordinates from PSNs. This "neural upscaling" procedure exploits the constraints implied by PSNs on possible configurations, as well as differences in the likelihood of observing different configurations with the same PSN. Using a 1 µs atomistic molecular dynamics trajectory of Aβ 1−40 , we show that neural upscaling is able to effectively recapitulate detailed structural information for intrinsically disordered proteins, being particularly successful in recovering features such as transient secondary structure. These results suggest that scalable network-based models for protein structure and dynamics may be used in settings where atomistic detail is desired, with upscaling employed to impute atomic coordinates from PSNs.
One major function of social networks (e.g., massive online social networks) is the dissemination... more One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the information forwarding and feedback mechanisms in a social network that take into account the personalities of the sender and the receiver (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network.
Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and othe... more Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and other biological macromolecules. Topological coarse-graining, in which biomolecules or sets thereof are represented via graph structures, is a particularly useful way of obtaining highly compressed representations of molecular structures, and simulations operating via such representations can achieve substantial computational savings. A drawback of coarse-graining, however, is the loss of atomistic detail—an effect that is especially acute for topological representations such as protein structure networks (PSNs). Here, we introduce an approach based on a combination of machine learning and physically-guided refinement for inferring atomic coordinates from PSNs. This “neural upscaling” procedure exploits the constraints implied by PSNs on possible configurations, as well as differences in the likelihood of observing different configurations with the same PSN. Using a 1 μs atomistic molecular ...
One major function of social networks (e.g., massive online social networks) is the dissemination... more One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the two-way full duplex information forwarding and feedback mechanisms in a social network that take into account the personalities of the communicating actors (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network. The model demonstrates how the emergence of social networks can be explained in terms of maximizing game theoretical utility.
One major function of social networks (e.g., massive online social networks) is the dissemination... more One major function of social networks (e.g., massive online social networks) is the dissemination of information, such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to receivers and back (in the form of comments) involves all of the actors considering their knowledge, trust, and popularity, which shape their publishing and commenting strategies. To understand such human aspects of the information dissemination, we propose a game theoretical model of a one-way information forwarding and feedback mechanism in a star-shaped social network that takes into account the personalities of the communicating actors.
In plants, esterase/lipases perform transesterification reactions, playing an important role in t... more In plants, esterase/lipases perform transesterification reactions, playing an important role in the synthesis of useful molecules, such as those comprising the waxy coatings of leaf surfaces.
Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biote... more Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms. Using comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution. We utilize network analytic techniques to identify similarities and differences in chitinase topology. Here, we report molecular models and functional predictions from protein structure networks for eleven new chitinases from D. capensis, including a novel class IV chitinase with two active domains. This architecture has previously been observed in microorganisms but not in plants. We use a combination of comparati...
In plants, esterase/lipases perform transesterification reactions, playing an important role in t... more In plants, esterase/lipases perform transesterification reactions, playing an important role in the synthesis of useful molecules, such as those comprising the waxy coatings of leaf surfaces. Plant genomes and transcriptomes have provided a wealth of data about expression patterns and the circumstances under which these enzymes are upregulated, e.g. pathogen defense and response to drought; however, predicting their functional characteristics from genomic or transcriptome data is challenging due to weak sequence conservation among the diverse members of this group. Although functional sequence blocks mediating enzyme activity have been identified, progress to date has been hampered by the paucity of information on the structural relationships among these regions and how they affect substrate specificity. Here we present methodology for predicting overall protein flexibility and active site flexibility based on molecular modeling and analysis of protein structure networks (PSNs). We define two new types of specialized PSNs: sequence region networks (SRNs) and active site networks (ASNs), which provide parsimonious representations of molecular structure in reference to known features of interest. Our approach, intended as an aid to target selection for poorly characterized enzyme classes, is demonstrated for 26 previously uncharacterized esterase/lipases from the genome of the carnivorous plant Drosera capensis and
Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and othe... more Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and other biological macromolecules. Topological coarse-graining, in which biomolecules or sets thereof are represented via graph structures, is a particularly useful way of obtaining highly compressed representations of molecular structure, and simulations operating via such representations can achieve substantial computational savings. A drawback of coarse-graining, however, is the loss of atomistic detail-an effect that is especially acute for topological representations such as protein structure networks (PSNs). Here, we introduce an approach based on a combination of machine learning and physicallyguided refinement for inferring atomic coordinates from PSNs. This "neural upscaling" procedure exploits the constraints implied by PSNs on possible configurations, as well as differences in the likelihood of observing different configurations with the same PSN. Using a 1 µs atomistic molecular dynamics trajectory of Aβ 1−40 , we show that neural upscaling is able to effectively recapitulate detailed structural information for intrinsically disordered proteins, being particularly successful in recovering features such as transient secondary structure. These results suggest that scalable network-based models for protein structure and dynamics may be used in settings where atomistic detail is desired, with upscaling employed to impute atomic coordinates from PSNs.
One major function of social networks (e.g., massive online social networks) is the dissemination... more One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the information forwarding and feedback mechanisms in a social network that take into account the personalities of the sender and the receiver (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network.
Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and othe... more Coarse-graining is a powerful tool for extending the reach of dynamic models of proteins and other biological macromolecules. Topological coarse-graining, in which biomolecules or sets thereof are represented via graph structures, is a particularly useful way of obtaining highly compressed representations of molecular structures, and simulations operating via such representations can achieve substantial computational savings. A drawback of coarse-graining, however, is the loss of atomistic detail—an effect that is especially acute for topological representations such as protein structure networks (PSNs). Here, we introduce an approach based on a combination of machine learning and physically-guided refinement for inferring atomic coordinates from PSNs. This “neural upscaling” procedure exploits the constraints implied by PSNs on possible configurations, as well as differences in the likelihood of observing different configurations with the same PSN. Using a 1 μs atomistic molecular ...
One major function of social networks (e.g., massive online social networks) is the dissemination... more One major function of social networks (e.g., massive online social networks) is the dissemination of information such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to a receiver intrinsically involves both of them considering their self-perceived knowledge, reputation, and popularity, which further determine their decisions of whether or not to forward the information and whether or not to provide feedback. To understand such human aspects of the information dissemination, we propose a game theoretical model of the two-way full duplex information forwarding and feedback mechanisms in a social network that take into account the personalities of the communicating actors (including their perceived knowledgeability, reputation, and desire for popularity) and the global characteristics of the network. The model demonstrates how the emergence of social networks can be explained in terms of maximizing game theoretical utility.
One major function of social networks (e.g., massive online social networks) is the dissemination... more One major function of social networks (e.g., massive online social networks) is the dissemination of information, such as scientific knowledge, news, and rumors. Information can be propagated by the users of the network via natural connections in written, oral or electronic form. The information passing from a sender to receivers and back (in the form of comments) involves all of the actors considering their knowledge, trust, and popularity, which shape their publishing and commenting strategies. To understand such human aspects of the information dissemination, we propose a game theoretical model of a one-way information forwarding and feedback mechanism in a star-shaped social network that takes into account the personalities of the communicating actors.
In plants, esterase/lipases perform transesterification reactions, playing an important role in t... more In plants, esterase/lipases perform transesterification reactions, playing an important role in the synthesis of useful molecules, such as those comprising the waxy coatings of leaf surfaces.
Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biote... more Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms. Using comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution. We utilize network analytic techniques to identify similarities and differences in chitinase topology. Here, we report molecular models and functional predictions from protein structure networks for eleven new chitinases from D. capensis, including a novel class IV chitinase with two active domains. This architecture has previously been observed in microorganisms but not in plants. We use a combination of comparati...
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