Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: Meeting new challenges

© 2014 Elsevier Ltd All rights reserved. Despite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the progress in molecular modeling and ligand docking for GPCRs. The four targets in the present third assessment round presented new and diverse challenges for modelers, including prediction of allosteric ligand interaction and activation states in 5-hydroxytryptamine receptors 1B and 2B, and modeling by extremely distant homology for smoothened receptor. Forty-four modeling groups participated in the assessment. State-of-the-art modeling approaches achieved close-to-experimental accuracy for small rigid orthosteric ligands and models built by close homology, and they correctly predicted protein fold for distant homology targets. Predictions of long loops and GPCR activation states remain unsolved problems

Reconstruction of apo A2A receptor activation pathways reveal ligand-competent intermediates and state-dependent cholesterol hotspots

G-protein coupled receptors (GPCRs) play a pivotal role in transmitting signals at the cellular level. Structural insights can be exploited to support GPCR structure-based drug discovery endeavours. Despite advances in GPCR crystallography, active state structures are scarce. Molecular dynamics (MD) simulations have been used to explore the conformational landscape of GPCRs. Efforts have been made to retrieve active state conformations starting from inactive structures, however to date this has not been possible without using an energy bias. Here, we reconstruct the activation pathways of the apo adenosine receptor (A2A), starting from an inactive conformation, by applying adaptive sampling MD combined with a goal-oriented scoring function. The reconstructed pathways reconcile well with experiments and help deepen our understanding of A2A regulatory mechanisms. Exploration of the apo conformational landscape of A2A reveals the existence of ligand-competent states, active intermediates and state-dependent cholesterol hotspots of relevance for drug discovery. To the best of our knowledge this is the first time an activation process has been elucidated for a GPCR starting from an inactive structure only, using a non-biased MD approach, opening avenues for the study of ligand binding to elusive yet pharmacologically relevant GPCR states

Reconstruction of apo A2A receptor activation pathways reveal ligand-competent intermediates and state-dependent cholesterol hotspots

G-protein coupled receptors (GPCRs) play a pivotal role in transmitting signals at the cellular level. Structural insights can be exploited to support GPCR structure-based drug discovery endeavours. Despite advances in GPCR crystallography, active state structures are scarce. Molecular dynamics (MD) simulations have been used to explore the conformational landscape of GPCRs. Efforts have been made to retrieve active state conformations starting from inactive structures, however to date this has not been possible without using an energy bias. Here, we reconstruct the activation pathways of the apo adenosine receptor (A2A), starting from an inactive conformation, by applying adaptive sampling MD combined with a goal-oriented scoring function. The reconstructed pathways reconcile well with experiments and help deepen our understanding of A2A regulatory mechanisms. Exploration of the apo conformational landscape of A2A reveals the existence of ligand-competent states, active intermediates and state-dependent cholesterol hotspots of relevance for drug discovery. To the best of our knowledge this is the first time an activation process has been elucidated for a GPCR starting from an inactive structure only, using a non-biased MD approach, opening avenues for the study of ligand binding to elusive yet pharmacologically relevant GPCR states

Looking to the future

<div><p>The putative Major Facilitator Superfamily (MFS) transporter, SV2A, is the target for levetiracetam (LEV), which is a successful anti-epileptic drug. Furthermore, SV2A knock out mice display a severe seizure phenotype and die after a few weeks. Despite this, the mode of action of LEV is not known at the molecular level. It would be extremely desirable to understand this more fully in order to aid the design of improved anti-epileptic compounds. Since there is no structure for SV2A, homology modelling can provide insight into the ligand-binding site. However, it is not a trivial process to build such models, since SV2A has low sequence identity to those MFS transporters whose structures are known. A further level of complexity is added by the fact that it is not known which conformational state of the receptor LEV binds to, as multiple conformational states have been inferred by tomography and ligand binding assays or indeed, if binding is exclusive to a single state. Here, we explore models of both the inward and outward facing conformational states of SV2A (according to the alternating access mechanism for MFS transporters). We use a sequence conservation analysis to help guide the homology modelling process and generate the models, which we assess further with Molecular Dynamics (MD). By comparing the MD results in conjunction with docking and simulation of a LEV-analogue used in radioligand binding assays, we were able to suggest further residues that line the binding pocket. These were confirmed experimentally. In particular, mutation of D670 leads to a complete loss of binding. The results shed light on the way LEV analogues may interact with SV2A and may help with the on-going design of improved anti-epileptic compounds.</p></div

Alchembed: A Computational Method for Incorporating Multiple Proteins into Complex Lipid Geometries

A necessary step prior to starting any membrane protein computer simulation is the creation of a well-packed configuration of protein(s) and lipids. Here, we demonstrate a method, <i>alchembed</i>, that can simultaneously and rapidly embed multiple proteins into arrangements of lipids described using either atomistic or coarse-grained force fields. During a short simulation, the interactions between the protein(s) and lipids are gradually switched on using a soft-core van der Waals potential. We validate the method on a range of membrane proteins and determine the optimal soft-core parameters required to insert membrane proteins. Since all of the major biomolecular codes include soft-core van der Waals potentials, no additional code is required to apply this method. A tutorial is included in the Supporting Information

Alchembed: A Computational Method for Incorporating Multiple Proteins into Complex Lipid Geometries

A necessary step prior to starting any membrane protein computer simulation is the creation of a well-packed configuration of protein(s) and lipids. Here, we demonstrate a method, <i>alchembed</i>, that can simultaneously and rapidly embed multiple proteins into arrangements of lipids described using either atomistic or coarse-grained force fields. During a short simulation, the interactions between the protein(s) and lipids are gradually switched on using a soft-core van der Waals potential. We validate the method on a range of membrane proteins and determine the optimal soft-core parameters required to insert membrane proteins. Since all of the major biomolecular codes include soft-core van der Waals potentials, no additional code is required to apply this method. A tutorial is included in the Supporting Information

(A) Conservation pattern of residues (M, A, V, I, L, C, Y, W and F) as ascertained by an alignment of 758 sequences form a BLAST search against rat SV2A

<p>. The degree of conservation is coloured from blue to red as a function of percentage. The position of the TM helices as predicted from the consensus prediction (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116589#pone.0116589.s001" target="_blank">S1 Fig</a>.) are indicated. (B) Chemical structure of ucb 30889, a commonly used radio-ligand that is an analogue of LEV.</p

(A) Change in RMSDs from 80 ns of the Inward-ucb 30889 simulation (green) and (B) the Outward-ucb 30889 simulation (red lines) from the initial snapshot from the respective apo simulations

<p>. Helix conservation in the (C) Inward-ucb 30889 and (D) Outward-ucb 30889 simulations.</p

The ligand binding sites in the Inward-apo model of SV2A (A) and the Outward-apo model (B) from simulation (60 ns)

<p>. The ligand (black stick) was docked to a snapshot the apo-model after 80 ns simulation. Key residues identified by mutagenesis are highlighted as stick representations. Schematic interaction maps of the docked ligand, generated via MOE with an interaction cut-off of 6 Å are shown for the Inward (C) and Outward (D) models. Residues starred are conserved hydrophobic residues common to both the Inward and Outward ligand binding pockets. (E) Affinity of ucb 30889 for recombinant rat SV2A (wt and mutants). A concentration range of ucb 30889 was incubated with 5 nM of [³H]ucb 30889 during 120 min at 4°C. B0 is the binding of [³H]ucb 30889 in the absence of any competing compound. Data are representative of three independent experiments. pIC₅₀ values were calculated from untransformed raw data by non-linear regression using a model describing a sigmoidal dose-response curve with variable slope and are reported in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116589#pone.0116589.t003" target="_blank">Table 3</a>. The position of the mutants with respect to the ligand in the Outward model is shown in (F).</p