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).

Molecular simulations were used to design large scale loop motions in the enzyme cyclophilin A and NMR and biophysical methods were employed to validate the models.

Molecular simulations led to the discovery of a new class of small molecules that inhibit the cyclophilin family of proteins.

Fragment-based drug discovery is an increasingly popular method to identify novel small-molecule drug candidates. One of the limitations of the approach is the difficulty of accurately characterizing weak binding events. This work reports a combination of X-ray diffraction, surface plasmon resonance experiments and molecular dynamics simulations for the characterization of binders to different isoforms of the cyclophilin (Cyp) protein family. Although several Cyp inhibitors have been reported in the literature, it has proven challenging to achieve high binding selectivity for different isoforms of this protein family. The present studies have led to the identification of several structurally novel fragments that bind to diverse Cyp isoforms in distinct pockets with low millimolar dissociation constants. A detailed comparison of the merits and drawbacks of the experimental and computational techniques is presented, and emerging strategies for designing ligands with enhanced isoform specificity are described.

The mechanism of amantadine binding to the S31 variant of the M2 protein of Influenza A is well understood, but the reasons behind N31 M2 amantadine insensitivity remain under investigation. Many molecular dynamics studies have evaluated the influence of amantadine position within the channel pore on its ability to inhibit proton conductance in M2, but little is known about the influence of amantadine rotational orientation. Replica-exchange umbrella sampling, steered, and classic molecular dynamics simulations were performed on amantadine in the solid-state NMR structure of S31 M2 and an N31 M2 homologue, both in the homotetramer configuration, to explore the effects of the position and tilt angle of amantadine on inhibition of the M2 channel. Steered simulations show that amantadine rotates with the amine toward the bulk water as it passes into the hydrophobic entryway lined by Val27 side chains. Results from all simulation types performed indicate that amantadine has a strong, specific orientation with the amine turned inward toward the central cavity in the S31 M2 pore but has variable orientation and a strong propensity to remain outward pointing in N31 M2. Free energy profiles from umbrella sampling, measured relative to bulk water, show amantadine binds more strongly to the S31 M2 pore by 8 kcal/mol in comparison to amantadine in the N31 pore, suggesting that it can escape more readily from the N31 channel through the Val27 secondary gate, whereas it is captured by the S31 channel in the same region. Lower water density and distribution near amantadine in S31 M2 reveal that the drug inhibits proton conductance in S31 M2 because of its inward-pointing configuration, whereas in N31 M2, amantadine forms hydrogen bonds with an N31 side chain and does not widely occlude water occupancy in any configuration. Both amantadine's weaker binding to and weaker water occlusion in N31 M2 might contribute to its inefficacy as an inhibitor of the mutant protein.

proven challenging to achieve high binding selectivity for different isoforms of this protein family. The present studies have led to the identification of several structurally novel fragments that bind to diverse Cyp isoforms in distinct pockets with low millimolar dissociation constants. A detailed comparison of the merits and drawbacks of the experimental and computational techniques is presented, and emerging strategies for designing ligands with enhanced isoform specificity are described.

Proteins need to interconvert between many conformations in order to function, many of which are formed transiently, and sparsely populated. Particularly when the lifetimes of these states approach the millisecond timescale, identifying the relevant structures and the mechanism by which they inter-convert remains a tremendous challenge. Here we introduce a novel combination of accelerated MD (aMD) simulations and Markov State modelling (MSM) to explore these 'excited' conformational states . Applying this to the highly dynamic protein CypA, a protein involved in immune response and associated with HIV infection, we identify five principally populated conformational states and the atomistic mechanism by which they interconvert. A rational design strategy predicted that the mutant D66A should stabilise the minor conformations and substantially alter the dynamics whereas the similar mutant H70A should leave the landscape broadly unchanged. These predictions are confirmed using CPMG and R1ρ solution state NMR measurements. By accurately and reliably exploring functionally relevant, but sparsely populated conformations with milli-second lifetimes in silico, our aMD/MSM method has tremendous promise for the design of dynamic protein free energy landscapes for both protein engineering and drug discovery.