Philip C. Biggin

Accurate calculation of the absolute free energy of binding for drug molecules

Free energy calculations based on molecular dynamics and thermodynamic cycles accurately reproduce experimental affinities of diverse bromodomain inhibitors.

Distinct Structural Pathways Coordinate the Activation of AMPA Receptor-Auxiliary Subunit Complexes

Summary Neurotransmitter-gated ion channels adopt different gating modes to fine-tune signaling at central synapses. At glutamatergic synapses, high and low activity of AMPA receptors (AMPARs) is observed when pore-forming subunits coassemble with or without auxiliary subunits, respectively. Whether a common structural pathway accounts for these different gating modes is unclear. Here, we identify two structural motifs that determine the time course of AMPAR channel activation. A network of electrostatic interactions at the apex of the AMPAR ligand-binding domain (LBD) is essential for gating by pore-forming subunits, whereas a conserved motif on the lower, D2 lobe of the LBD prolongs channel activity when auxiliary subunits are present. Accordingly, channel activity is almost entirely abolished by elimination of the electrostatic network but restored via auxiliary protein interactions at the D2 lobe. In summary, we propose that activation of native AMPAR complexes is coordinated by distinct structural pathways, favored by the association/dissociation of auxiliary subunits.

Predictions of Ligand Selectivity from Absolute Binding Free Energy Calculations.

Binding selectivity is a requirement for the development of a safe drug, and it is a critical property for chemical probes used in preclinical target validation. Engineering selectivity adds considerable complexity to the rational design of new drugs, as it involves the optimization of multiple binding affinities. Computationally, the prediction of binding selectivity is a challenge, and generally applicable methodologies are still not available to the computational and medicinal chemistry communities. Absolute binding free energy calculations based on alchemical pathways provide a rigorous framework for affinity predictions and could thus offer a general approach to the problem. We evaluated the performance of free energy calculations based on molecular dynamics for the prediction of selectivity by estimating the affinity profile of three bromodomain inhibitors across multiple bromodomain families, and by comparing the results to isothermal titration calorimetry data. Two case studies were considered. In the first one, the affinities of two similar ligands for seven bromodomains were calculated and returned excellent agreement with experiment (mean unsigned error of 0.81 kcal/mol and Pearson correlation of 0.75). In this test case, we also show how the preferred binding orientation of a ligand for different proteins can be estimated via free energy calculations. In the second case, the affinities of a broad-spectrum inhibitor for 22 bromodomains were calculated and returned a more modest accuracy (mean unsigned error of 1.76 kcal/mol and Pearson correlation of 0.48); however, the reparametrization of a sulfonamide moiety improved the agreement with experiment.

Crystal structures of a GABAA-receptor chimera reveal new endogenous neurosteroid-binding sites.

γ-Aminobutyric acid receptors (GABAARs) are vital for controlling excitability in the brain. This is emphasized by the numerous neuropsychiatric disorders that result from receptor dysfunction. A critical component of most native GABAARs is the α subunit. Its transmembrane domain is the target for many modulators, including endogenous brain neurosteroids that impact anxiety, stress and depression, and for therapeutic drugs, such as general anesthetics. Understanding the basis for the modulation of GABAAR function requires high-resolution structures. Here we present the first atomic structures of a GABAAR chimera at 2.8-Å resolution, including those bound with potentiating and inhibitory neurosteroids. These structures define new allosteric binding sites for these modulators that are associated with the α-subunit transmembrane domain. Our findings will enable the exploitation of neurosteroids for therapeutic drug design to regulate GABAARs in neurological disorders.

Steered Molecular Dynamics Simulations Predict Conformational Stability of Glutamate Receptors

The stability of protein-protein interfaces can be essential for protein function. For ionotropic glutamate receptors, a family of ligand-gated ion channels vital for normal function of the central nervous system, such an interface exists between the extracellular ligand binding domains (LBDs). In the full-length protein, the LBDs are arranged as a dimer of dimers. Agonist binding to the LBDs opens the ion channel, and briefly after activation the receptor desensitizes. Several residues at the LBD dimer interface are known to modulate desensitization, and conformational changes around these residues are believed to be involved in the state transition. The general hypothesis is that the interface is disrupted upon desensitization, and structural evidence suggests that the disruption might be substantial. However, when cross-linking the central part of this interface, functional data suggest that the receptor can still undergo desensitization, contradicting the hypothesis of major interface disruption. Here, we illustrate how opening the dimer interface using steered molecular dynamics (SMD) simulations, and analyzing the work values required, provides a quantitative measure for interface stability. For one subtype of glutamate receptors, which is regulated by ion binding to the dimer interface, we show that opening the interface without ions bound requires less work than with ions present, suggesting that ion binding indeed stabilizes the interface. Likewise, for interface mutants with longer-lived active states, the interface is more stable, while the work required to open the interface is reduced for less active mutants. Moreover, a cross-linked mutant can still undergo initial interface opening motions similar to the native receptor and at similar energetic cost. Thus, our results support that interface opening is involved in desensitization. Furthermore, they provide reconciliation of apparently opposing data and demonstrate that SMD simulations can give relevant biological insight into longer time scale processes without the need for expensive calculations.

Guiding lead optimization with GPCR structure modeling and molecular dynamics

G-protein coupled receptor (GPCR) modeling approaches are widely used in the hit-to-lead and lead optimization stages of drug discovery. Modern protocols that involve molecular dynamics simulation can address key issues such as the free energy of binding (affinity), ligand-induced GPCR flexibility, ligand binding kinetics, conserved water positions and their role in ligand binding and the effects of mutations. The goals of these calculations are to predict the structures of the complexes between existing ligands and their receptors, to understand the key interactions and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this review we present a brief survey of various computational approaches illustrated through a hierarchical GPCR modeling protocol and its prospective application in three industrial drug discovery projects.

A Numbering System for MFS Transporter Proteins

The Major Facilitator Superfamily (MFS) is one of the largest classes of secondary active transporters and is widely expressed in many domains of life. It is characterized by a common 12-transmembrane helix motif that allows the selective transport of a vast range of diverse substrates across the membrane. MFS transporters play a central role in many physiological processes and are increasingly recognized as potential drug targets. Despite intensive efforts, there are still only a handful of crystal structures and therefore homology modeling is likely to be a necessary process for providing models to interpret experiments for many years to come. However, the diversity of sequences and the multiple conformational states these proteins can exist in makes the process significantly more complicated, especially for sequences for which there is very little sequence identity to known templates. Inspired by the approach adopted many years ago for GPCRs, we have analyzed the large number of MFS sequences now available alongside the current structural information to propose a series of conserved contact points that can provide additional guidance for the homology modeling process. To enable cross-comparison across MFS models we also present a numbering scheme that can be used to provide a point of reference within each of the 12 transmembrane regions.

Statistical Analysis on the Performance of Molecular Mechanics Poisson–Boltzmann Surface Area versus Absolute Binding Free Energy Calculations: Bromodomains as a Case Study

Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson–Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain–inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson () and Spearman () correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ( = 0.64 and = 0.66 for ABFE; = 0.39 and = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: = 0.55 and = 0.56 when including an entropy estimate, and = 0.53 and = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein–ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost.

Role of the Cys loop and transmembrane domain in the allosteric modulation of α4β2 nicotinic acetylcholine receptors

Allosteric modulators of pentameric ligand-gated ion channels are thought to act on elements of the pathways that couple agonist binding to channel gating. Using α4β2 nicotinic acetylcholine receptors and the α4β2-selective positive modulators 17β-estradiol (βEST) and desformylflustrabromine (dFBr), we have identified pathways that link the binding sites for these modulators to the Cys loop, a region that is critical for channel gating in all pentameric ligand-gated ion channels. Previous studies have shown that the binding site for potentiating βEST is in the C-terminal (post-M4) region of the α4 subunit. Here, using homology modeling in combination with mutagenesis and electrophysiology, we identified the binding site for potentiating dFBr on the top half of a cavity between the third (M3) and fourth transmembrane (M4) α-helices of the α4 subunit. We found that the binding sites for βEST and dFBr communicate with the Cys loop, through interactions between the last residue of post-M4 and Phe170 of the conserved FPF sequence of the Cys loop, and that these interactions affect potentiating efficacy. In addition, interactions between a residue in M3 (Tyr309) and Phe167, a residue adjacent to the Cys loop FPF motif, also affect dFBr potentiating efficacy. Thus, the Cys loop acts as a key control element in the allosteric transduction pathway for potentiating βEST and dFBr. Overall, we propose that positive allosteric modulators that bind the M3-M4 cavity or post-M4 region increase the efficacy of channel gating through interactions with the Cys loop.

Kainate receptor pore‐forming and auxiliary subunits regulate channel block by a novel mechanism

Kainate receptor heteromerization and auxiliary subunits, Neto1 and Neto2, attenuate polyamine ion‐channel block by facilitating blocker permeation. Relief of polyamine block in GluK2/GluK5 heteromers results from a key proline residue that produces architectural changes in the channel pore α‐helical region. Auxiliary subunits exert an additive effect to heteromerization, and thus relief of polyamine block is due to a different mechanism. Our findings have broad implications for work on polyamine block of other cation‐selective ion channels.