scholarly journals Development of “Imprint-and-Report” Dynamic Combinatorial Libraries for Differential Sensing Applications

2021 ◽  
Vol 143 (36) ◽  
pp. 14845-14854
Author(s):  
Emily E. Harrison ◽  
Benjamin A. Carpenter ◽  
Lauren E. St. Louis ◽  
Alexandria G. Mullins ◽  
Marcey L. Waters
2020 ◽  
Vol 90 (3) ◽  
pp. 30502
Author(s):  
Alessandro Fantoni ◽  
João Costa ◽  
Paulo Lourenço ◽  
Manuela Vieira

Amorphous silicon PECVD photonic integrated devices are promising candidates for low cost sensing applications. This manuscript reports a simulation analysis about the impact on the overall efficiency caused by the lithography imperfections in the deposition process. The tolerance to the fabrication defects of a photonic sensor based on surface plasmonic resonance is analysed. The simulations are performed with FDTD and BPM algorithms. The device is a plasmonic interferometer composed by an a-Si:H waveguide covered by a thin gold layer. The sensing analysis is performed by equally splitting the input light into two arms, allowing the sensor to be calibrated by its reference arm. Two different 1 × 2 power splitter configurations are presented: a directional coupler and a multimode interference splitter. The waveguide sidewall roughness is considered as the major negative effect caused by deposition imperfections. The simulation results show that plasmonic effects can be excited in the interferometric waveguide structure, allowing a sensing device with enough sensitivity to support the functioning of a bio sensor for high throughput screening. In addition, the good tolerance to the waveguide wall roughness, points out the PECVD deposition technique as reliable method for the overall sensor system to be produced in a low-cost system. The large area deposition of photonics structures, allowed by the PECVD method, can be explored to design a multiplexed system for analysis of multiple biomarkers to further increase the tolerance to fabrication defects.


2020 ◽  
Author(s):  
Ryan Weber ◽  
Martin McCullagh

<p>pH-switchable, self-assembling materials are of interest in biological imaging and sensing applications. Here we propose that combining the pH-switchability of RXDX (X=Ala, Val, Leu, Ile, Phe) peptides and the optical properties of coumarin creates an ideal candidate for these materials. This suggestion is tested with a thorough set of all-atom molecular dynamics simulations. We first investigate the dependence of pH-switchabiliy on the identity of the hydrophobic residue, X, in the bare (RXDX)<sub>4</sub> systems. Increasing the hydrophobicity stabilizes the fiber which, in turn, reduces the pH-switchabilty of the system. This behavior is found to be somewhat transferable to systems in which a single hydrophobic residue is replaced with a coumarin containing amino acid. In this case, conjugates with X=Ala are found to be unstable and both pHs while conjugates with X=Val, Leu, Ile and Phe are found to form stable β-sheets at least at neutral pH. The (RFDF)<sub>4</sub>-coumarin conjugate is found to have the largest relative entropy value of 0.884 +/- 0.001 between neutral and acidic coumarin ordering distributions. Thus, we posit that coumarin-(RFDF)<sub>4</sub> containing peptide sequences are ideal candidates for pH-sensing bioelectronic materials.</p>


2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>


Author(s):  
Jorge Pérez Bailón ◽  
Jaime Ramírez-Angulo ◽  
Belén Calvo ◽  
Nicolás Medrano

This paper presents a Variable Gain Amplifier (VGA) designed in a 0.18 μm CMOS process to operate in an impedance sensing interface. Based on a transconductance-transimpedance (TC-TI) approach with intermediate analog-controlled current steering, it exhibits a gain ranging from 5 dB to 38 dB with a constant bandwidth around 318 kHz, a power consumption of 15.5 μW at a 1.8 V supply and an active area of 0.021 mm2.


Sign in / Sign up

Export Citation Format

Share Document