Adamantane derivatives, such as amantadine and rimantadine, have been reported to block the transmembrane domain (TM) of the M2 protein of influenza A virus (A/M2) but their clinical use has been discontinued due to evolved resistance in humans. Although experiments and simulations have provided adequate information about the binding interaction of amantadine or rimantadine to the M2 protein, methods for predicting binding affinities of whole series of M2 inhibitors have so far been scarcely applied. Such methods could assist in the development of novel potent inhibitors that overcome A/M2 resistance. Here we show that alchemical free energy calculations of ligand binding using the Bennett acceptance ratio (BAR) method are valuable for determining the relative binding potency of A/M2 inhibitors of the aminoadamantane type covering a binding affinity range of only ∼2 kcal mol(-1). Their binding affinities measured by isothermal titration calorimetry (ITC) against the A/M2TM tetramer from the Udorn strain in its closed form at pH 8 were used as experimental probes. The binding constants of rimantadine enantiomers against M2TMUdorn were measured for the first time and found to be equal. Two series of alchemical free energy calculations were performed using 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) lipids to mimic the membrane environment. A fair correlation was found for DPPC that was significantly improved using DMPC, which resembles more closely the DPC lipids used in the ITC experiments. This demonstrates that binding free energy calculations by the BAR approach can be used to predict relative binding affinities of aminoadamantane derivatives toward M2TM with good accuracy.

The development of novel anti-influenza drugs is of great importance because of the capability of influenza viruses to occasionally cross interspecies barriers and to rapidly mutate. One class of anti-influenza agents, aminoadamantanes, including the drugs amantadine and rimantadine now widely abandoned due to virus resistance, bind to and block the pore of the transmembrane domain of the M2 proton channel (M2TM) of influenza A. Here, we present one of the still rare studies that interprets thermodynamic profiles from isothermal titration calorimetry (ITC) experiments in terms of individual energy contributions to binding, calculated by the computationally inexpensive implicit solvent/implicit membrane molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach, for aminoadamantane compounds binding to M2TM of the avian "Weybridge" strain. For all eight pairs of aminoadamantane compounds considered, the trend of the predicted relative binding free energies and their individual components, effective binding energies and changes in the configurational entropy, agrees with experimental measures (ΔΔG, ΔΔH, TΔΔS) in 88, 88, and 50% of the cases. In addition, information yielded by the MM-PBSA approach about determinants of binding goes beyond that available in component quantities (ΔH, ΔS) from ITC measurements. We demonstrate how one can make use of such information to link thermodynamic profiles from ITC with structural causes on the ligand side and, ultimately, to guide decision making in lead optimization in a prospective manner, which results in an aminoadamantane derivative with improved binding affinity against M2TM(Weybridge).

While aminoadamantanes are well-established inhibitors of the influenza A M2 proton channel, the mechanisms by which they are rendered ineffective against M2 S31N are unclear. Solid state NMR, isothermal titration calorimetry, electrophysiology, antiviral assays, and molecular dynamics simulations suggest stronger binding interactions for aminoadamantanes to M2 WT compared to negligible or weak binding to M2 S31N . This is due to reshaping of the M2 pore when N31 is present, which, in contrast to wild-type (WT), leads (A) to the loss of the V27 pocket for the adamantyl cage and to a predominant orientation of the ligand's ammonium group toward the N-terminus and (B) to the lack of a helical kink upon ligand binding. The kink, which reduces the tilt of the C-terminal helical domain relative to the bilayer normal, includes the W41 primary gate for proton conductance and may prevent the gate from opening, representing an alternative view for how these drugs prevent proton conductance.

This review is focused on methods for detecting small molecules and, in particular, the characterisation of their interaction with natural proteins (e.g. receptors, ion channels). Because there are intrinsic advantages to using label-free methods over labelled methods (e.g. fluorescence, radioactivity), this review only covers label-free techniques. We briefly discuss available techniques and their advantages and disadvantages, especially as related to investigating the interaction between small molecules and proteins. The reviewed techniques include well-known and widely used standard analytical methods (e.g. HPLC-MS, NMR, calorimetry, and X-ray diffraction), newer and more specialised analytical methods (e.g. biosensors), biological systems (e.g. cell lines and animal models), and in-silico approaches.

Molecularly imprinted nanospheres obtained by miniemulsion polymerization have been applied as the sensitive layer for label-free direct optical sensing of small molecules. Using these particles as the sensitive layer allowed for improving response times in comparison to sensors using MIP layers. As a model compound, well-characterized nanospheres imprinted against L-Boc-phenylalanine anilide (L-BFA) were chosen. For immobilization, a simple concept based on electrostatic adsorption was used, showing its applicability to different types of surfaces, leading to a good surface coverage. The sensor showed short response times, good selectivity, and high reversibility with a limit of detection down to 60 μM and a limit of quantitation of 94 μM. Furthermore, reproducibility, selectivity, and long-term stability of the sensitive layers were tested. The best results were achieved with an adsorption on aminopropylsilane layers, showing a chip-to-chip reproducibility of 22%. Furthermore, the sensors showed no loss in signal after a storage time of 1 year.

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