Trio-pharmacophore DNA-encoded chemical library for simultaneous selection of fragments and linkers.

The split-and-pool method has been widely used to synthesize chemical libraries of a large size for early drug discovery, albeit without the possibility of meaningful quality control. In contrast, a self-assembled DNA-encoded chemical library (DEL) allows us to construct an m x n-member library by mixing an m-member and an n-member pre-purified sub-library. Herein, we report a trio-pharmacophore DEL (T-DEL) of m x l x n members through assembling three pre-purified and validated sub-libraries. The middle sub-library is synthesized using DNA-templated synthesis with different reaction mechanisms and designed as a linkage connecting the fragments displayed on the flanking two sub-libraries. Despite assembling three fragments, the resulting compounds do not exceed the up-to-date standard of molecular weight regarding drug-likeness. We demonstrate the utility of T-DEL in linker optimization for known binding fragments against trypsin and carbonic anhydrase II and by de novo selections against matrix metalloprotease-2 and -9.

Nonlinear manipulation and analysis of large DNA datasets.

Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a type of biased competition is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, a biased competition method for nonlinear manipulation and analysis of mixtures of DNA sequences was developed. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among a myriad of different DNA sequences was carried out to reduce the information entropy. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiments with DNA-encoded chemical libraries against protein targets.

A Self-Assembled Matrix System for Cell-Bioengineering Applications in Different Dimensions, Scales, and Geometries.

Stem cell bioengineering and therapy require different model systems and materials in different stages of development. If a chemically defined biomatrix system can fulfill most tasks, it can minimize the discrepancy among various setups. By screening biomaterials synthesized through a coacervation-mediated self-assembling mechanism, a biomatrix system optimal for 2D human mesenchymal stromal cell (hMSC) culture and osteogenesis is identified. Its utility for hMSC bioengineering is further demonstrated in coating porous bioactive glass scaffolds and nanoparticle synthesis for esiRNA delivery to knock down the SOX-9 gene with high delivery efficiency. The self-assembled injectable system is further utilized for 3D cell culture, segregated co-culture of hMSC with human umbilical vein endothelial cells (HUVEC) as an angiogenesis model, and 3D bioprinting. Most interestingly, the coating of bioactive glass with the self-assembled biomatrix not only supports the proliferation and osteogenesis of hMSC in the 3D scaffold but also induces the amorphous bioactive glass (BG) scaffold surface to form new apatite crystals resembling bone-shaped plate structures. Thus, the self-assembled biomatrix system can be utilized in various dimensions, scales, and geometries for many different bioengineering applications.