Molecular recognition with soft biomaterials

Abstract

Biomacromolecules and engineered materials can achieve molecular recognition if they engage their ligand with properly oriented and chemically complementary moieties. Recently, there has been significant interest in fabricating recognitive soft materials, which possess specific affinity for biological analytes. We present a summary and evaluation of current recognitive materials for biosensing, drug delivery, and regenerative medicine applications. We highlight the impact of material composition on the extent and specificity of ligand adsorption, citing new theoretical and empirical evidence. We conclude with a guide for synthesizing and characterizing novel recognitive materials, as well as recommendations for ligand selection and experimental design.

Fig. 1

Solute interactions with functional networks. (A) A ligand and cavity of known ionization (neutral, negative, positive) were allowed to interact in water. (B) The enthalpic and entropic contributions to the Gibbs free energy were computed for each ligand–cavity interaction. Water actively contributed to the thermodynamics of the ligand–receptor interaction becasuse of water–water, water–ligand, and water–cavity interactions. Adapted with permission from ref. 22, available from https://pubs.acs.org/doi/abs/10.1021/ja1050082. Copyright (2010) American Chemical Society (ACS). Further permissions related to this figure should be directed to ACS. (C–E) Schematic representation of the diffusion of solutes with a range of diameter in hydrogels (r_FV = radius of free volume, r_s = solute radius, ξ = mesh size). Adapted with permission from ref. 24, Available from https://pubs.acs.org/doi/abs/10.1021/acs.macromol.9b00753. Copyright (2019) ACS. Further permissions related to this figure should be directed to ACS.

Fig. 2

Recognitive biomaterials for drug delivery applications. (A) Nanoscale complexes of ligand-functionalized Cas9 ribonucleoprotein, guide RNA, and an endosomolytic peptide were successfully delivered to liver cells, where they edited a target gene in a cell-specific manner. Adapted with permission from ref. 40. Copyright (2018) American Chemical Society. (B) Exosomes decorated with an adhesive c(RDGyK) peptide enhanced the delivery of curcumin to reduce inflammatory markers in a mouse model of ischemic injury. Adapted with permission from ref. 41. Copyright (2019) American Chemical Society.

Fig. 3

Recognitive biomaterials for regenerative medicine applications. (A) Hydrogel scaffolds with pendant VEGF and bFGF aptamers successfully retained the soluble growth factor for more than three days, (B) promoted cell mobility in vitro, and (C) enhanced tissue vascularization in vivo. Adapted with permission from ref. 42. Copyright (2019) American Chemical Society. (D and E) Electrospun hydrogel sponges composed of gelatin and the EUP3 polysaccharide were capable of retaining endogenous PDGF-BB through high affinity PDGF-EUP3 interactions. Cytokine retention resulted enhanced wound healing in a full-thickness wound mouse model (images: blue = DAPI nuclear stain, green = fluorescent PDGF-BB). Adapted with permission from ref. 45. Copyright (2017) Elsevier.

Fig. 4

Protein adsorption behavior of molecularly imprinted polymers. (A) Molecularly imprinted polymers (MIPs) bound more of their template (lysozyme) than control non-imprinted polymers (NIPs), but no difference in the association constant was observed. (B) Lysozyme imprinting increased MIPs’ adsorption of all tested proteins, indicating that imprinting induced a change in network structure rather than specific affinity. (C) The MIPs’ composition imparted specificity for high isoelectric point biomarkers, as well as exclusion of low isoelectric point proteins. This indicated that the polymer composition, rather than the imprinting process, determined protein–polymer affinity. Adapted with permission from ref. 63. Copyright (2016) American Chemical Society. (D) Descriptive schematic for the protein imprinting process. MIPs are formed through the self-assembly and polymerization of functional monomers around a protein template. Following template extraction, nanocavities remain within the network. Adapted with permission from ref. 46. Copyright (2017) American Chemical Society.

Fig. 5

Model protein identification and composition analysis. (left) Most researchers look at the molecular weight and isoelectric point of low-cost model proteins, and select one for their study that is similar in size and charge to a biomarker of interest. Here, we show the surface projection, molecular weight, and isoelectric point of four of the most common model proteins, lysozyme (Lys), cytochrome c (Cyt c), hemoglobin (Hgb) and, bovine serum albumin (BSA) (green = carbon, blue = nitrogen, red = oxygen). (right) Solvent accessible surface analysis reveals differences in the relative composition of each protein. Lysozyme and cytochrome c, for example, which are very similar in molecular weight and isoelectric point, are significantly different in surface composition. Protein surface composition will influence protein–polymer interactions (blue = low, relative to model protein group, red = high, relative to model protein group).

Fig. 6

Synthesis of recognitive soft biomaterials. (A) There is a tradeoff between engineering control over polymer synthesis (i.e. influence over monomer incorporation and molecular weight distribution) and ease of synthesis. When designing a new recognitive biomaterial, it is important to consider the extent to which synthesis complexity improves the material or device’s functionality. (B) Natural and synthetic materials are each useful for molecular recognition applications. Biohybrid systems typically combine the structural integrity and environmental responsiveness of synthetic materials with the specific activity of biomacromolecules.