A computational molecular design framework for crosslinked polymer networks

Abstract

Crosslinked polymers are important in a very wide range of applications including dental restorative materials. However, currently used polymeric materials experience limited durability in the clinical oral environment. Researchers in the dental polymer field have generally used a time-consuming experimental trial-and-error approach to the design of new materials. The application of computational molecular design (CMD) to crosslinked polymer networks has the potential to facilitate development of improved polymethacrylate dental materials. CMD uses quantitative structure property relations (QSPRs) and optimization techniques to design molecules possessing desired properties. This paper describes a mathematical framework which provides tools necessary for the application of CMD to crosslinked polymer systems. The novel parts of the system include the data structures used, which allow for simple calculation of structural descriptors, and the formulation of the optimization problem. A heuristic optimization method, Tabu Search, is used to determine candidate monomers. Use of a heuristic optimization algorithm makes the system more independent of the types of QSPRs used, and more efficient when applied to combinatorial problems. A software package has been created which provides polymer researchers access to the design framework. A complete example of the methodology is provided for polymethacrylate dental materials.

Prediction of elongation at break for linear polymers

“…Nevertheless, authors did not present the dataset and detailed explanations of results did not either. A similar work was carried on by Eslick et al [29], who used computational molecular design (CMD) in cross-linked polymer networks in order to facilitate the development of improved polymethacrylate dental materials. CMD employed QSPRs and optimization techniques to design molecules possessing desired properties, among others tensile strength and modulus of elasticity.…”

Computational Molecular Design of Drug Delivery Vehicles for Anti-HIV Microbicides

“…This optimization problem is an MILP, so long as the structural feasibility constraints are written in a linear form. The MILP will be solved with standard solvers, and the results compared in terms of solution quality and computation time with Tabu Search, a stochastic solver which has been used successfully on many molecular design optimization problems in the past (Eslick, et al, 2009) …”

Durable bonds at the adhesive/dentin interface:an impossible mission or simply a moving target?

“…mutans attachment and neutralization capabilities. The combinatorial optimization approach allows the relative importance of each property to be varied and predicts novel methacrylate structures for further evaluation [131].…”

“…These factors may be addressed by using an iterative combinatorial optimization (molecular design)/synthesis approach in conjunction with a/d interfacial multi-scale characterization and modeling to design, synthesize and develop water-compatible, esterase-resistant methacrylate-based dentin adhesives [28,29,49,50,54,55,68,69,74,76,78,82,86,96,97,110,112,131,137,138,140,144,145,147,150,154,155,[158][159][160][161][162][163][164][165][166][167][168][169]. Finite element (FE) modeling is used to project the long-term mechanical durability of the new adhesives under conditions that simulate function in the mouth [149,150].…”

“…Thus, our research team developed modeling methodologies to account for these underlying mechanisms. The modeling in conjunction with our multi-scalar structure/ property characterization has allowed us to project the long-term mechanical durability of the novel water-compatible, esterase-resistant adhesives under conditions that simulate function in the mouth [28,29,49,50,54,68,69,74,76,82,111,131,[133][134][135][136][137][138][139][140][143][144][145][146][147][148][149][150][151][152][153][154][155][156][157][158][159][160] .…”