Vy Duong - Academia.edu (original) (raw)

Papers by Vy Duong

Research paper thumbnail of Protein structure networks provide insight into active site flexibility in esterase/lipases from the carnivorous plant<i>Drosera capensis</i>

Integrative Biology, 2018

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

Research paper thumbnail of Neural Upscaling from Residue-level Protein Structure Networks to Atomistic Structure

arXiv (Cornell University), Aug 25, 2021

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.

Research paper thumbnail of A Game Theoretical Approach to Modeling Information Dissemination in Social Networks

arXiv (Cornell University), Jun 29, 2010

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.

Research paper thumbnail of Neural Upscaling from Residue-Level Protein Structure Networks to Atomistic Structures

Biomolecules, 2021

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 ...

Research paper thumbnail of A game theoretical approach to modeling full-duplex information dissemination

Summer Computer Simulation Conference, Jul 11, 2010

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.

Research paper thumbnail of A game theoretical approach to broadcast information diffusion in social networks

Annual Simulation Symposium, Apr 3, 2011

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.

Research paper thumbnail of Reconstructing atomistic structures from residue-level protein structure networks using artificial neural networks

Biophysical Journal, 2022

Research paper thumbnail of Protein structure networks provide insight into active site flexibility in esterase/lipases from the carnivorous plantDrosera capensis

Integrative Biology, 2018

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.

Research paper thumbnail of Structure prediction and network analysis of chitinases from the Cape sundew, Drosera capensis

Biochimica et biophysica acta, Mar 28, 2016

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...

Research paper thumbnail of Toward Understanding Friendship in Online Social Networks

The International Journal of Technology, Knowledge, and Society, 2009

Research paper thumbnail of Spam, Scams and Shams

The International Journal of Technology, Knowledge, and Society: Annual Review, 2009

Research paper thumbnail of Protein structure networks provide insight into active site flexibility in esterase/lipases from the carnivorous plant<i>Drosera capensis</i>

Integrative Biology, 2018

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

Research paper thumbnail of Neural Upscaling from Residue-level Protein Structure Networks to Atomistic Structure

arXiv (Cornell University), Aug 25, 2021

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.

Research paper thumbnail of A Game Theoretical Approach to Modeling Information Dissemination in Social Networks

arXiv (Cornell University), Jun 29, 2010

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.

Research paper thumbnail of Neural Upscaling from Residue-Level Protein Structure Networks to Atomistic Structures

Biomolecules, 2021

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 ...

Research paper thumbnail of A game theoretical approach to modeling full-duplex information dissemination

Summer Computer Simulation Conference, Jul 11, 2010

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.

Research paper thumbnail of A game theoretical approach to broadcast information diffusion in social networks

Annual Simulation Symposium, Apr 3, 2011

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.

Research paper thumbnail of Reconstructing atomistic structures from residue-level protein structure networks using artificial neural networks

Biophysical Journal, 2022

Research paper thumbnail of Protein structure networks provide insight into active site flexibility in esterase/lipases from the carnivorous plantDrosera capensis

Integrative Biology, 2018

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.

Research paper thumbnail of Structure prediction and network analysis of chitinases from the Cape sundew, Drosera capensis

Biochimica et biophysica acta, Mar 28, 2016

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...

Research paper thumbnail of Toward Understanding Friendship in Online Social Networks

The International Journal of Technology, Knowledge, and Society, 2009

Research paper thumbnail of Spam, Scams and Shams

The International Journal of Technology, Knowledge, and Society: Annual Review, 2009