skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Molecular Modeling and Simulations of Peptide–Polymer Conjugates
Peptide–polymer conjugates are a class of soft materials composed of covalently linked blocks of protein/polypeptides and synthetic/natural polymers. These materials are practically useful in biological applications, such as drug delivery, DNA/gene delivery, and antimicrobial coatings, as well as nonbiological applications, such as electronics, separations, optics, and sensing. Given their broad applicability, there is motivation to understand the molecular and macroscale structure, dynamics, and thermodynamic behavior exhibited by such materials. We focus on the past and ongoing molecular simulation studies aimed at obtaining such fundamental understanding and predicting molecular design rules for the target function. We describe briefly the experimental work in this field that validates or motivates these computational studies. We also describe the various models (e.g., atomistic, coarse-grained, or hybrid) and simulation methods (e.g., stochastic versus deterministic, enhanced sampling) that have been used and the types of questions that have been answered using these computational approaches.  more » « less
Award ID(s):
1703402
PAR ID:
10174736
Author(s) / Creator(s):
;
Date Published:
Journal Name:
Annual Review of Chemical and Biomolecular Engineering
Volume:
11
Issue:
1
ISSN:
1947-5438
Page Range / eLocation ID:
257 to 276
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, 28TH ACM. SIGKDD. CONFERENCE. ON KNOWLEDGE DISCOVERY. AND DATA MINING)
    Metal-Organic Frameworks (MOFs) are a class of modular, porous crystalline materials that have great potential to revolutionize applications such as gas storage, molecular separations, chemical sensing, catalysis, and drug delivery. The Cambridge Structural Database (CSD) reports 10,636 synthesized MOF crystals which in addition contains ca. 114,373 MOF-like structures. The sheer number of synthesized (plus potentially synthesizable) MOF structures requires researchers pursue computational techniques to screen and isolate MOF candidates. In this demo paper, we describe our effort on leveraging knowledge graph methods to facilitate MOF prediction, discovery, and synthesis. We present challenges and case studies about (1) construction of a MOF knowledge graph (MOF-KG) from structured and unstructured sources and (2) leveraging the MOF-KG for discovery of new or missing knowledge. 
    more » « less
  2. ; (, Annual Review of Heat Transfer)
    Chu, Wilson (Ed.)
    Two-dimensional materials (e.g., graphene and transition metal dichalcogenides) and their heterostructures have enormous applications in electrochemical energy storage systems such as batteries. A comprehensive and solid understanding of these materials’ thermal transport and mechanism is essential for practical device design. Several advanced experimental techniques have been developed to measure the intrinsic thermal conductivity of materials. However, experiments have challenges in providing improved control and characterization of complex structures, especially for low-dimensional materials. Theoretical and simulation tools, such as first-principles calculations, Boltzmann transport equations, molecular dynamics simulations, lattice dynamics simulation, and nonequilibrium Green’s function, provide reliable predictions of thermal conductivity and physical insights to understand the underlying thermal transport mechanism in materials. However, doing these calculations requires high computational resources. The development of new materials synthesis technology and fast-growing demand for rapid and accurate prediction of physical properties requires novel computational approaches. The machine learning method provides a promising solution to address such needs. This review details the recent development in atomistic/molecular studies and machine learning of thermal transport in two-dimensional materials. The paper also addresses the latest significant experimental advances. However, designing the best two-dimensional materials-based heterostructures is like a multivariate optimization problem. For example, a particular heterostructure may be suitable for thermal transport but can have lower mechanical strength/stability. For bilayer and multilayer structures, the interlayer distance may influence the thermal transport properties and interlayer strength. Therefore, the last part of this review addresses the future research direction in two-dimensional materials-based heterostructure design for thermal transport in energy storage systems. 
    more » « less
  3. ; ; ; ; (, Elsevier)
    Soft materials are critical to the pharmaceutical industry for their role in formulations, delivery of active compounds or understanding relevant physiological processes. This chapter will focus on coarse-grained (CG) approaches and models that have been used in conjunction with the Molecular Dynamics (MD) simulation method to investigate soft materials of interest to various applications in pharmaceutical sciences. This chapter also discusses several examples of CG MD simulations used to scientifically probe molecules with different chemistries. 
    more » « less
  4. ; ; ; ; (, Processes)
    In this report we have discussed the important role of molecular modeling, especially the use of the molecular dynamics method, in investigating transport processes in nanoporous materials such as membranes. With the availability of high performance computers, molecular modeling can now be used to study rather complex systems at a fraction of the cost or time requirements of experimental studies. Molecular modeling techniques have the advantage of being able to access spatial and temporal resolution which are difficult to reach in experimental studies. For example, sub-Angstrom level spatial resolution is very accessible as is sub-femtosecond temporal resolution. Due to these advantages, simulation can play two important roles: Firstly because of the increased spatial and temporal resolution, it can help understand phenomena not well understood. As an example, we discuss the study of reverse osmosis processes. Before simulations were used it was thought the separation of water from salt was purely a coulombic phenomenon. However, by applying molecular simulation techniques, it was clearly demonstrated that the solvation of ions made the separation in effect a steric separation and it was the flux which was strongly affected by the coulombic interactions between water and the membrane surface. Additionally, because of their relatively low cost and quick turnaround (by using multiple processor systems now increasingly available) simulations can be a useful screening tool to identify membranes for a potential application. To this end, we have described our studies in determining the most suitable zeolite membrane for redox flow battery applications. As computing facilities become more widely available and new computational methods are developed, we believe molecular modeling will become a key tool in the study of transport processes in nanoporous materials. 
    more » « less
  5. ; (, Carbohydrate Polymers)
    Polysaccharides are ubiquitous, generally benign in nature, and compatible with many tissues in biomedical situations, making them appealing candidates or new materials such as therapeutic agents and sensors. Fluorescent labeling can create the ability to sensitively monitor distribution and transport o polysaccharide-based materials, which can or example urther illuminate drug-delivery mechanisms and thereore improve design o delivery systems. Herein, we review uorophore selection and ways o appending polysaccharides, utility o the product uorescent polysaccharides as new smart materials, and their stimulus-responsive nature, with ocus on their biomedical applications as environment-sensitive biosensors, imaging, and as molecular rulers. Further, we discuss the advantages and disadvantages o these methods, and uture prospects or creation and use o these sel-reporting materials. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email