Label-free single-molecule detection has been achieved so far by funnelling a large number of ligands into a sequence of single-binding events with few recognition elements host on nanometric transducers. Such approaches are inherently unable to sense a cue in a bulk milieu. Conceptualizing cells’ ability to sense at the physical limit by means of highly-packed recognition elements, a millimetric sized field-effect-transistor is used to detect a single molecule. To this end, the gate is bio-functionalized with a self-assembled-monolayer of 1012 capturing anti-Immunoglobulin-G and is endowed with a hydrogen-bonding network enabling cooperative interactions. The selective and label-free single molecule IgG detection is strikingly demonstrated in diluted saliva while 15 IgGs are assayed in whole serum. The suggested sensing mechanism, triggered by the affinity binding event, involves a work-function change that is assumed to propagate in the gating-field through the electrostatic hydrogen-bonding network. The proposed immunoassay platform is general and can revolutionize the current approach to protein detection.

Background:Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program.Objectives:We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing.Methods:CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure–activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies.Results:Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing.Conclusion:This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points.Citation:Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. 2016. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect 124:1023–1033; http://dx.doi.org/10.1289/ehp.1510267

A significant number of different exchange correlation functionals, ranging from generalized gradient approximations to double hybrids, has been tested on a difficult playground represented by proton transfer reactions. In order to have a complete picture of their performances, both energetics and structural features have been compared and the obtained ranking compared with those issued from the standard test for kinetics (i.e., the DBH24/08 set). Among all of the functionals, the ωB97X, BMK, B1LYP, and PBE0-DH approaches are those providing a good error balance on all four trials. Beyond these figures, the obtained results allow for some general considerations, such as those on the role of Hartree-Fock exchange in reaction barriers or the relation between structure and energetics.

Aquaporin-4 (AQP4) is the predominant water channel in different organs and tissues. An alteration of its physiological functioning is responsible for several disorders of water regulation and, thus, is considered an attractive target with a promising therapeutic and diagnostic potential. Molecular dynamics (MD) simulations performed on the AQP4 tetramer embedded in a bilayer of lipid molecules allowed us to analyze the role of spontaneous fluctuations occurring inside the pore. Following the approach by Hashido et al. [Hashido M, Kidera A, Ikeguchi M (2007) Biophys J 93: 373-385], our analysis on 200ns trajectory discloses three domains inside the pore as key elements for water permeation. Herein, we describe the gating mechanism associated with the well-known selectivity filter on the extracellular side of the pore and the crucial regulation ensured by the NPA motifs (asparagine, proline, alanine). Notably, on the cytoplasmic side, we find a putative gate formed by two residues, namely, a cysteine belonging to the loop D (C178) and a histidine from loop B (H95). We observed that the spontaneous reorientation of the imidazole ring of H95 acts as a molecular switch enabling H-bond interaction with C178. The occurrence of such local interaction seems to be responsible for the narrowing of the pore and thus of a remarkable decrease in water flux rate. Our results are in agreement with recent experimental observations and may represent a promising starting point to pave the way for the discovery of chemical modulators of AQP4 water permeability.

Aiming at modulating two key enzymatic targets for Alzheimer's disease (AD), i.e., acetylcholinesterase (AChE) and monoamine oxidase B (MAO B), a series of multitarget ligands was properly designed by linking the 3,4-dimethylcoumarin scaffold to 1,3- and 1,4-substituted piperidine moieties, thus modulating the basicity to improve the hydrophilic/lipophilic balance. After in vitro enzymatic inhibition assays, multipotent inhibitors showing potencies in the nanomolar and in the low micromolar range for hMAO B and eeAChE, respectively, were prioritized and evaluated in human SH-SY5Y cell-based models for their cytotoxicity and neuroprotective effect against oxidative toxins (H2O2, rotenone, and oligomycin-A). The present study led to the identification of a promising multitarget hit compound (5b) exhibiting high hMAO B inhibitory activity (IC50 = 30 nM) and good MAO B/A selectivity (selectivity index, SI = 94) along with a micromolar eeAChE inhibition (IC50 = 1.03 μM). Moreover, 5b behaves as a water-soluble, brain-permeant neuroprotective agent against oxidative insults without interacting with P-gp efflux system.

Ligand efficiency metrics are almost universally accepted as a valuable indicator of compound quality and an aid to reduce attrition. Areas covered: In this review, the authors describe ligand efficiency metrics giving a balanced overview on their merits and points of weakness in order to enable the readers to gain an informed opinion. Relevant theoretical breakthroughs and drug-like properties are also illustrated. Several recent exemplary case studies are discussed in order to illustrate the main fields of application of ligand efficiency metrics. Expert opinion: As a medicinal chemist guide, ligand efficiency metrics perform in a context- and chemotype-dependent manner; thus, they should not be used as a magic box. Since the 'big bang' of efficiency metrics occurred more or less ten years ago and the average time to develop a new drug is over the same period, the next few years will give a clearer outlook on the increased rate of success, if any, gained by means of these new intriguing tools.

We explore the relation between the morphological and the charge transport properties of poly(3-hexylthiophene) (P3HT) and poly(2,5-bis(3-alkylthiophen-2-yl)thieno[3,2-b]thiophene) (PBTTT) semiconductor polymers in both amorphous and crystalline phases. Using molecular dynamics to simulate bulk supercells and the Marcus theory to analyze the transport properties we found that amorphous systems display a reduced hole mobility due to the loss of nematic order and π-π stacking leading to a reduction in the electronic coupling between two chains. In the crystal phase, PBTTT displays a larger charge mobility than P3HT due to the interdigitation of the side chains enhancing the stability of the conjugated rings on the backbones. This more stable π-π stacking reduces the energetic disorder with respect to P3HT and increases the electronic coupling. In contrast, in the amorphous phase, PBTTT displays a reduced charge mobility with respect to P3HT due to the absence of side chains attached to the thienothiophenes, which increases their fluctuations and the energetic disorder. In addition, we show that it is possible to calculate the reorganization energy neglecting the side chains of the polymers and thus saving computational time. Within this approximation, we obtained mobility values matching the experimental measurements, thus confirming that the side chains are crucial to shape the morphology of the polymeric systems but are not involved in the charge transport process.

Organic thin film transistors (OTFT) are metal-insulator-semiconductor field-effect transistors in which the semiconductor is a conjugated organic material. They are the subject of intense industrial research because their fabrication process is less expensive when compared with inorganic TFTs. Among the others, the organic material mostly employed in their construction consists of two semiconductor polymers, namely poly(3-hexylthiophene) (P3HT) and poly(2,5-bis(3-alkylthiophen-2-yl)thieno[3,2-b]thiophene) (PBTTT). Despite the large amount of experimental efforts in the characterization of the electronic properties of these devices, several questions regarding their morphological arrangement in bulk and at interfaces remain wide open. Here, we report results obtained by classical molecular dynamics simulations of P3HT and PBTTT inspired by OTFT fabrication techniques. In particular, we investigate how the annealing fabrication process and the presence of residual solvent molecules left over after spin coating might modify the morphology and the dynamics of the amorphous phase of these two polymers. Simulations of both polymer deposits at 300 K after annealing show an increase in the number of interdigitation events between the alkyl chains of two polymeric macromolecules; moreover, we find that the increased stability of the pi-pi stacking is caused by an improved layering of the films, which may account for the better charge transport properties reported in experiments. Our results strongly suggest that thin semiconductor films are required to boost the performances of the devices and that a minimal presence of residual solvent does not alter dramatically the microscopic structure and stability of the polymeric films