An official website of the United States government
Abstract Photo‐affinity adsorbents (i.e., translucent matrices functionalized with ligands featuring light‐controlled biorecognition) represent a futuristic technology for purifying labile biologics. In this study, a framework for prototyping photo‐affinity adsorbents comprising azobenzene‐cyclized peptides (ACPs) conjugated to translucent porous beads (ChemMatrix) is presented. This approach combines computational and experimental tools for designing ACPs and investigating their light‐controlled isomerization kinetics and protein biorecognition. First, a modular design for tailoring ACP's conformation, facilitating sequencing, and streamlining the in silico modeling of cis/trans isomers and their differential protein binding is introduced. Then, a spectroscopic system for measuring the photo‐isomerization kinetics of ACPs on ChemMatrix beads is reported; using this device, it is demonstrated that the isomerization at different light intensities is correlated to the cyclization geometry, specifically the energy difference of trans versus cis isomers as calculated in silico. Also, a microfluidic device for sorting ACP‐ChemMatrix beads to select and validate photo‐affinity ligands using Vascular Cell Adhesion Molecule 1 (VCAM‐1) as target protein and cycloAZOB[GVHAKQHRN‐K*]‐G‐ChemMatrix as model photo‐affinity adsorbent is presented. The proposed ACPs exhibit rapid and defined light‐controlled isomerization and biorecognition. Controlling the adsorption and release of VCAM‐1 using light demonstrates the potential of photo‐affinity adsorbents for targets whose biochemical liability poses challenges to its purification.
more »
« less
Affordable Microfluidic Bead-Sorting Platform for Automated Selection of Porous Particles Functionalized with Bioactive Compounds
Abstract The ability to rapidly and accurately evaluate bioactive compounds immobilized on porous particles is crucial in the discovery of drugs, diagnostic reagents, ligands, and catalysts. Existing options for solid phase screening of bioactive compounds, while highly effective and well established, can be cost-prohibitive for proof-of-concept and early stage work, limiting its applicability and flexibility in new research areas. Here, we present a low-cost microfluidics-based platform enabling automated screening of small porous beads from solid-phase peptide libraries with high sensitivity and specificity, to identify leads with high binding affinity for a biological target. The integration of unbiased computer assisted image processing and analysis tools, provided the platform with the flexibility of sorting through beads with distinct fluorescence patterns. The customized design of the microfluidic device helped with handling beads with different diameters (~100–300 µm). As a microfluidic device, this portable novel platform can be integrated with a variety of analytical instruments to perform screening. In this study, the system utilizes fluorescence microscopy and unsupervised image analysis, and can operate at a sorting speed of up to 125 beads/hr (~3.5 times faster than a trained operator) providing >90% yield and >90% bead sorting accuracy. Notably, the device has proven successful in screening a model solid-phase peptide library by showing the ability to select beads carrying peptides binding a target protein (human IgG).
more »
« less
- PAR ID:
- 10153393
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Droplet microfluidics enable high-throughput screening, sequencing, and formulation of biological and chemical systems at the microscale. Such devices are generally fabricated in a soft polymer such as polydimethylsiloxane (PDMS). However, developing design masks for PDMS devices can be a slow and expensive process, requiring an internal cleanroom facility or using an external vendor. Here, we present the first complete droplet-based component library using low-cost rapid prototyping and electrode integration. This fabrication method for droplet microfluidic devices costs less than $12 per device and a full design-build-test cycle can be completed within a day. Discrete microfluidic components for droplet generation, re-injection, picoinjection, anchoring, fluorescence sensing, and sorting were built and characterized. These devices are biocompatible, low-cost, and high-throughput. To show its ability to perform multistep workflows, these components were used to assemble droplet “pixel arrays, where droplets were generated, sensed, sorted, and anchored onto a grid to produce images.more » « less
-
Abstract Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel NaV1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to NaV1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.more » « less
-
null (Ed.)Lab-on-a-chip technology offers an ideal platform for low-cost, reliable, and easy-to-use diagnostics of key biomarkers needed for early screening of diseases and other health concerns. In this work, a graphene field-effect transistor (GFET) functionalized with target-binding aptamers is used as a biosensor for the detection of thrombin protein biomarker. Furthermore, this GFET is integrated with a microfluidic device for enhanced sensing performances in terms of detection limit, sensitivity, and continuous monitoring. Under this platform, a picomolar limit of detection was achieved for measuring thrombin; in our experiment measured as low as 2.6 pM. FTIR, Raman and UV-Vis spectroscopy measurements were performed to confirm the device functionalization steps. Based on the concentration-dependent calibration curve, a dissociation constant of K D = 375.8 pM was obtained. Continuous real-time measurements were also conducted under a constant gate voltage ( V GS ) to observe the transient response of the sensor when analyte was introduced to the device. The target selectivity of the sensor platform was evaluated and confirmed by challenging the GFET biosensor with various concentrations of lysozyme protein. The results suggest that this device technology has the potential to be used as a general diagnostic platform for measuring clinically relevant biomarkers for point-of-care applications.more » « less
-
Abstract Mechanical properties have emerged as a significant label-free marker for characterizing deformable particles such as cells. Here, we demonstrated the first single-particle-resolved, cytometry-like deformability-activated sorting in the continuous flow on a microfluidic chip. Compared with existing deformability-based sorting techniques, the microfluidic device presented in this work measures the deformability and immediately sorts the particles one-by-one in real time. It integrates the transit-time-based deformability measurement and active hydrodynamic sorting onto a single chip. We identified the critical factors that affect the sorting dynamics by modeling and experimental approaches. We found that the device throughput is determined by the summation of the sensing, buffering, and sorting time. A total time of ~100 ms is used for analyzing and sorting a single particle, leading to a throughput of 600 particles/min. We synthesized poly(ethylene glycol) diacrylate (PEGDA) hydrogel beads as the deformability model for device validation and performance evaluation. A deformability-activated sorting purity of 88% and an average efficiency of 73% were achieved. We anticipate that the ability to actively measure and sort individual particles one-by-one in a continuous flow would find applications in cell-mechanotyping studies such as correlational studies of the cell mechanical phenotype and molecular mechanism.more » « less
