Ravinder Abrol

Predictions of CCR1 Chemokine Receptor Structure and BX 471 Antagonist Binding Followed by Experimental Validation

A major challenge in the application of structure-based drug design methods to proteins belonging to the superfamily of G protein-coupled receptors (GPCRs) is the paucity of structural information (1). The 19 chemokine receptors, belonging to the Class A family of GPCRs, are important drug targets not only for autoimmune diseases like multiple sclerosis but also for the blockade of human immunodeficiency virus type 1 entry (2). Using the MembStruk computational method (3), we predicted the three-dimensional structure of the human CCR1 receptor. In addition, we predicted the binding site of the small molecule CCR1 antagonist BX 471, which is currently in Phase II clinical trials (4). Based on the predicted antagonist binding site we designed 17 point mutants of CCR1 to validate the predictions. Subsequent competitive ligand binding and chemotaxis experiments with these mutants gave an excellent correlation to these predictions. In particular, we find that Tyr-113 and Tyr-114 on transmembrane domain 3 and Ile-259 on transmembrane 6 contribute significantly to the binding of BX 471. Finally, we used the predicted and validated structure of CCR1 in a virtual screening validation of the Maybridge data base, seeded with selective CCR1 antagonists. The screen identified 63% of CCR1 antagonists in the top 5% of the hits. Our results indicate that rational drug design for GPCR targets is a feasible approach.

Elucidating glycosaminoglycan–protein–protein interactions using carbohydrate microarray and computational approaches

Glycosaminoglycan polysaccharides play critical roles in many cellular processes, ranging from viral invasion and angiogenesis to spinal cord injury. Their diverse biological activities are derived from an ability to regulate a remarkable number of proteins. However, few methods exist for the rapid identification of glycosaminoglycan–protein interactions and for studying the potential of glycosaminoglycans to assemble multimeric protein complexes. Here, we report a multidisciplinary approach that combines new carbohydrate microarray and computational modeling methodologies to elucidate glycosaminoglycan–protein interactions. The approach was validated through the study of known protein partners for heparan and chondroitin sulfate, including fibroblast growth factor 2 (FGF2) and its receptor FGFR1, the malarial protein VAR2CSA, and tumor necrosis factor-α (TNF-α). We also applied the approach to identify previously undescribed interactions between a specific sulfated epitope on chondroitin sulfate, CS-E, and the neurotrophins, a critical family of growth factors involved in the development, maintenance, and survival of the vertebrate nervous system. Our studies show for the first time that CS is capable of assembling multimeric signaling complexes and modulating neurotrophin signaling pathways. In addition, we identify a contiguous CS-E-binding site by computational modeling that suggests a potential mechanism to explain how CS may promote neurotrophin-tyrosine receptor kinase (Trk) complex formation and neurotrophin signaling. Together, our combined microarray and computational modeling methodologies provide a general, facile means to identify new glycosaminoglycan–protein–protein interactions, as well as a molecular-level understanding of those complexes.

Community-wide assessment of GPCR structure modelling and ligand docking

Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment — GPCR Dock 2008 — was conducted in coordination with the publication of the crystal structure of the human adenosine A2A receptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops.

Genetically Encoded Photo-cross-linkers Map the Binding Site of an Allosteric Drug on a G Protein-Coupled Receptor

G protein-coupled receptors (GPCRs) are dynamic membrane proteins that bind extracellular molecules to transduce signals. Although GPCRs represent the largest class of therapeutic targets, only a small percentage of their ligand-binding sites are precisely defined. Here we describe the novel application of targeted photo-cross-linking using unnatural amino acids to obtain structural information about the allosteric binding site of a small molecule drug, the CCR5-targeted HIV-1 co-receptor blocker maraviroc.

An optimal adiabatic-to-diabatic transformation of the 1 2A′ and 2 2A′ states of H3

Molecular reaction dynamics in the adiabatic representation is complicated by the existence of conical intersections and the associated geometric phase effect. The first-derivative coupling vector between the corresponding electronically adiabatic states can, in general, be decomposed into longitudinal (removable) and transverse (nonremovable) parts. At intersection geometries, the longitudinal part is singular, whereas the transverse part is not. In a two-electronic-state Born–Huang expansion, an adiabatic-to-diabatic transformation completely eliminates the contribution of the longitudinal part to the nuclear motion Schrodinger equation, leaving however the transverse part contribution. We report here the results of an accurate calculation of this transverse part for the 1 2A′ and 2 2A′ electronic states of H3 obtained by solving a three-dimensional Poisson equation over the entire domain U of internal nuclear configuration space Q of importance to reactive scattering. In addition to requiring a knowled...

3D Structure Prediction of TAS2R38 Bitter Receptors Bound to Agonists Phenylthiocarbamide (PTC) and 6-n-Propylthiouracil (PROP)

The G protein-coupled receptor (GPCR) TAS2R38 is a bitter taste receptor that can respond to bitter compounds such as phenylthiocarbamide (PTC) and 6-n-propylthiouracil (PROP). This receptor was chosen because its four haplotypes (based on three residue site polymorphism) hTAS2R38PAV, hTAS2R38AVI, hTAS2R38AAI, and hTAS2R38PVV are known to have dramatically different responses to PTC and PROP. We aimed to identify the protein-ligand interaction features that determine whether the bitter taste signal from this receptor is sent to the cortex. To do this we predicted the 3D structures of the TAS2R38 bitter taste receptor using our new BiHelix and SuperBiHelix Monte Carlo methods (No experimental determinations of the 3D structure have been reported for any taste receptors.). We find that residue 262 (2nd position in the polymorphism) is involved in the interhelical hydrogen bond network stabilizing the GPCR structure in tasters (hTAS2R38PAV, hTAS2R38AAI, and hTAS2R38PVV), while it is not in the nontaster (hTAS2R38AVI). This suggests that the hydrogen bond interactions between TM3 and TM6 or between TM5 and TM6 may play a role in activating this GPCR. To further validate these structures, we used the DarwinDock method to predict the binding sites and 3D structures for PTC and PROP bound to hTAS2R38PAV, hTAS2R38AVI, hTAS2R38AAI, and hTAS2R38PVV, respectively. Our results show that PTC and PROP can form H-bonds with the backbone of residue 262 in the tasters (hTAS2R38PAV, hTAS2R38AAI, and hTAS2R38PVV) but not in the nontaster (hTAS2R38AVI). Thus it appears that the hydrogen bond interaction between TM3 and TM6 may activate the receptor to pass the ligand binding signal to intracellular processes and that the H-bond between agonists and residue 262 in tasters is involved in the bitter tasting. This is in agreement with experimental observations, providing validation of the predicted ligand-protein complexes and also a potential activation mechanism for the TAS2R38 receptor.

Accurate first-derivative nonadiabatic couplings for the H3 system

A conical intersection exists between the ground (1 2 A[prime]) and the first-excited (2 2A[prime]) electronic potential energy surfaces (PESs) of the H3 system for C3v geometries. This intersection induces a geometric phase effect, an important factor in accurate quantum mechanical reactive scattering calculations, which at low energies can be performed using the ground PES only, together with appropriate nuclear motion boundary conditions. At higher energies, however, such calculations require the inclusion of both the 1 2A[prime] and 2 2A[prime] electronic PESs and the corresponding nuclear derivative couplings. Here we present ab initio first-derivative couplings for these states obtained by analytic gradient techniques and a fit to these results. We also present a fit to the corresponding 1 2A[prime] and 2 2A[prime] adiabatic electronic PESs, obtained from the ab initio electronic energies. The first-derivative couplings are compared with their approximate analytical counterparts obtained by Varandas et al. [J. Chem. Phys. 86, 6258 (1987)] using the double many-body expansion method. As expected, the latter are accurate close to conical intersection configurations but not elsewhere. We also present the contour integrals of the ab initio couplings along closed loops around the above-mentioned conical intersection, which contain information about possible interactions between the 2 2A[prime] and 3 2A[prime] states.

Predicted 3D structures for adenosine receptors bound to ligands: comparison to the crystal structure.

G protein-coupled receptors (GPCRs) are therapeutic targets for many diseases, but progress in developing active and selective therapeutics has been severely hampered by the difficulty in obtaining accurate structures. We have been developing methods for predicting the structures for GPCR ligand complexes, but validation has been hampered by a lack of experimental structures with which to compare our predictions. We report here the predicted structures of the human adenosine GPCR subtypes (A(1), A(2A), A(2B), and A(3)) and the binding sites for adenosine agonist and eight antagonists to this predicted structure, making no use of structural data, and compare with recent experimental crystal structure for ZM241385 bound human A(2A) receptor. The predicted structure correctly identifies 9 of the 12 crystal binding site residues. Moreover, the predicted binding energies of eight antagonists to the predicted structure of A(2A) correlate quite well with experiment. These excellent predictions resulted when we used Monte Carlo techniques to optimize the loop structures, particularly the cysteine linkages. Ignoring these linkages led to a much worse predicted binding site (identifying only 3 of the 12 important residues). These results indicate that computational methods can predict the three-dimensional structure of GPCR membrane proteins sufficiently accurately for use in designing subtype selective ligands for important GPCR therapeutics targets.

FOXC1 Activates Smoothened-Independent Hedgehog Signaling in Basal-like Breast Cancer

The mesoderm- and epithelial-mesenchymal transition-associated transcription factor FOXC1 is specifically overexpressed in basal-like breast cancer (BLBC), but its biochemical function is not understood. Here, we demonstrate that FOXC1 controls cancer stem cell (CSC) properties enriched in BLBC cells via activation of Smoothened (SMO)-independent Hedgehog (Hh) signaling. This non-canonical activation of Hh is specifically mediated by Gli2. Furthermore, we show that the N-terminal domain of FOXC1 (aa 1-68) binds directly to an internal region (aa 898-1168) of Gli2, enhancing the DNA-binding and transcription-activating capacity of Gli2. FOXC1 expression correlates with that of Gli2 and its targets in human breast cancers. Moreover, FOXC1 overexpression reduces sensitivity to anti-Hedgehog (Hh) inhibitors in BLBC cells and xenograft tumors. Together, these findings reveal FOXC1-mediated non-canonical Hh signaling that determines the BLBC stem-like phenotype and anti-Hh sensitivity, supporting inhibition of FOXC1 pathways as potential approaches for improving BLBC treatment.

BiHelix: Towards de novo structure prediction of an ensemble of G-protein coupled receptor conformations

G‐Protein Coupled Receptors (GPCRs) play a critical role in cellular signal transduction pathways and are prominent therapeutic targets. Recently there has been major progress in obtaining experimental structures for a few GPCRs. Each GPCR, however, exhibits multiple conformations that play a role in their function and we have been developing methods aimed at predicting structures for all these conformations. Analysis of available structures shows that these conformations differ in relative helix tilts and rotations. The essential issue is, determining how to orient each of the seven helices about its axis since this determines how it interacts with the other six helices. Considering all possible helix rotations to ensure that no important packings are overlooked, and using rotation angle increments of 30° about the helical axis would still lead to 127 or 35 million possible conformations each with optimal residue positions. We show in this paper how to accomplish this. The fundamental idea is to optimize the interactions between each pair of contacting helices while ignoring the other 5 and then to estimate the energies of all 35 million combinations using these pair‐wise interactions. This BiHelix approach dramatically reduces the effort to examine the complete set of conformations and correctly identifies the crystal packing for the experimental structures plus other near‐native packings we believe may play an important role in activation. This approach also enables a detailed structural analysis of functionally distinct conformations using helix‐helix interaction energy landscapes and should be useful for other helical transmembrane proteins as well. Proteins 2012.