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Carbon nanotube (CNT) chemiresistors have emerged as miniaturized platforms for wearable volatile organic compound (VOC) sensors. As a promising biorecognition element (BRE), a short peptide can functionalize CNT to be sensitive and selective to target VOCs. However, unveiling the VOC‐optimized peptide‐CNT pair for gas‐phase sensing remains unclear. Here, a novel multimodal molecular toolset for designing, building, and probing suitable BRE‐CNT sensors using machine learning, molecular dynamics, and near‐edge X‐ray absorption fine structure spectroscopy is presented. This computational and experimental suite predicts the peptide conformation on the CNT surface and probes how the peptide–CNT interfaces affect the VOC sensing. Then, peptide‐functionalized CNT chemiresistors are tested against various VOCs to confirm the efficacy of the toolkit. The results show that the vertically oriented peptide on the CNT surface hinders VOC access to the peptide–CNT interface, resulting in a significantly lower sensor signal than the CNT chemiresistor with the horizontally oriented peptide. The interactive computational and experimental results strongly indicate that a peptide conformation plays an important role in VOC sensing sensitivity. [ABSTRACT FROM AUTHOR]

The finely tuned structures of membrane channel proteins allow selective passage of ions through the available aqueous pores. To understand channel function, it is crucial to locate the pores and study their physical and chemical properties. Here, we propose a new pore-searching algorithm (TransPath), which uses the Configurational Bias Monte Carlo (CBMC) method to generate transmembrane trajectories driven by both geometric and electrostatic features. The trajectories are binned into groups determined by a vector distance criterion. From each group, a representative trajectory is selected based on the Rosenbluth weight, and the geometrically optimal path is obtained by simulated annealing. Candidate ion pathways can then be determined by analysis of the radius and potential profiles. The proposed method and its implementation are illustrated using the bacterial KcsA potassium channel as an example. The procedure is then applied to the more complex structures of the bacterial E. coli chloride channel homolog and a homology model of the ClC-0 channel. Proteins 2008. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

H+/Cl− antiport behavior has recently been observed in bacterial chloride channel homologs and eukaryotic CLC-family proteins. The detailed molecular-level mechanism driving the stoichiometric exchange is unknown. In the bacterial structure, experiments and modeling studies have identified two acidic residues, E148 and E203, as key sites along the proton pathway. The E148 residue is a major component of the fast gate, and it occupies a site crucial for both H+ and Cl− transport. E203 is located on the intracellular side of the protein; it is vital for H+, but not Cl−, transport. This suggests two independent ion transit pathways for H+ and Cl− on the intracellular side of the transporter. Previously, we utilized a new pore-searching algorithm, TransPath, to predict Cl− and H+ ion pathways in the bacterial ClC channel homolog, focusing on proton access from the extracellular solution. Here we employ the TransPath method and molecular dynamics simulations to explore H+ pathways linking E148 and E203 in the presence of Cl− ions located at the experimentally observed binding sites in the pore. A conclusion is that Cl− ions are required at both the intracellular (Sint) and central (Scen) binding sites in order to create an electrostatically favorable H+ pathway linking E148 and E203; this electrostatic coupling is likely related to the observed 1H+/2Cl− stoichiometry of the antiporter. In addition, we suggest that a tyrosine residue side chain (Y445), located near the Cl− ion binding site at Scen, is involved in proton transport between E148 and E203. Proteins 2007. © 2007 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Wearable sensors for human health, performance, and state monitoring, which have a linear response to the binding of biomarkers found in sweat, saliva, or urine, are of current interest for many applications. A critical part of any device is a biological recognition element (BRE) that is able to bind a biomarker at the surface of a sensor with a high affinity and selectivity to produce a measurable signal response. In this study, we discover and compare 12-mer peptides that bind to neuropeptide Y (NPY), a stress and human health biomarker, using independent and complimentary experimental and computational approaches. The affinities of the NPY-binding peptides discovered by both methods are equivalent and below the micromolar level, which makes them suitable for application in sensors. The in silico design protocol for peptide-based BREs is low cost, highly efficient, and simple, suggesting its utility for discovering peptide binders to a variety of biomarker targets.