Dahlia R. Weiss

Structure-based ligand discovery for the protein–protein interface of chemokine receptor CXCR4

G-protein–coupled receptors (GPCRs) are key signaling molecules and are intensely studied. Whereas GPCRs recognizing small-molecules have been successfully targeted for drug discovery, protein-recognizing GPCRs, such as the chemokine receptors, claim few drugs or even useful small molecule reagents. This reflects both the difficulties that attend protein–protein interface inhibitor discovery, and the lack of structures for these targets. Imminent structure determination of chemokine receptor CXCR4 motivated docking screens for new ligands against a homology model and subsequently the crystal structure. More than 3 million molecules were docked against the model and then against the crystal structure; 24 and 23 high-scoring compounds from the respective screens were tested experimentally. Docking against the model yielded only one antagonist, which resembled known ligands and lacked specificity, whereas the crystal structure docking yielded four that were dissimilar to previously known scaffolds and apparently specific. Intriguingly, several were potent and relatively small, with IC50 values as low as 306 nM, ligand efficiencies as high as 0.36, and with efficacy in cellular chemotaxis. The potency and efficiency of these molecules has few precedents among protein–protein interface inhibitors, and supports structure-based efforts to discover leads for chemokine GPCRs.

Conformation guides molecular efficacy in docking screens of activated β-2 adrenergic G protein coupled receptor

A prospective, large library virtual screen against an activated β2-adrenergic receptor (β2AR) structure returned potent agonists to the exclusion of inverse-agonists, providing the first complement to the previous virtual screening campaigns against inverse-agonist-bound G protein coupled receptor (GPCR) structures, which predicted only inverse-agonists. In addition, two hits recapitulated the signaling profile of the co-crystal ligand with respect to the G protein and arrestin mediated signaling. This functional fidelity has important implications in drug design, as the ability to predict ligands with predefined signaling properties is highly desirable. However, the agonist-bound state provides an uncertain template for modeling the activated conformation of other GPCRs, as a dopamine D2 receptor (DRD2) activated model templated on the activated β2AR structure returned few hits of only marginal potency.

Millisecond dynamics of RNA polymerase II translocation at atomic resolution

Significance In this study, by using molecular dynamics simulations and Markov state models, we reveal that RNA polymerase II translocation is driven purely by thermal energy and does not require the input of any additional chemical energy. Our simulations show an important role for the bridge helix: Large thermal oscillations of this structural element facilitate the translocation by specific interactions that lower the free-energy barriers between four metastable states. Among these states, we identify two previously unidentified intermediates that have not been previously captured by crystallography. The dynamic view of translocation presented in our study represents a substantial advance over the current understanding based on the static snapshots provided by X-ray structures of transcribing complexes. Transcription is a central step in gene expression, in which the DNA template is processively read by RNA polymerase II (Pol II), synthesizing a complementary messenger RNA transcript. At each cycle, Pol II moves exactly one register along the DNA, a process known as translocation. Although X-ray crystal structures have greatly enhanced our understanding of the transcription process, the underlying molecular mechanisms of translocation remain unclear. Here we use sophisticated simulation techniques to observe Pol II translocation on a millisecond timescale and at atomistic resolution. We observe multiple cycles of forward and backward translocation and identify two previously unidentified intermediate states. We show that the bridge helix (BH) plays a key role accelerating the translocation of both the RNA:DNA hybrid and transition nucleotide by directly interacting with them. The conserved BH residues, Thr831 and Tyr836, mediate these interactions. To date, this study delivers the most detailed picture of the mechanism of Pol II translocation at atomic level.

Can morphing methods predict intermediate structures

Movement is crucial to the biological function of many proteins, yet crystallographic structures of proteins can give us only a static snapshot. The protein dynamics that are important to biological function often happen on a timescale that is unattainable through detailed simulation methods such as molecular dynamics as they often involve crossing high-energy barriers. To address this coarse-grained motion, several methods have been implemented as web servers in which a set of coordinates is usually linearly interpolated from an initial crystallographic structure to a final crystallographic structure. We present a new morphing method that does not extrapolate linearly and can therefore go around high-energy barriers and which can produce different trajectories between the same two starting points. In this work, we evaluate our method and other established coarse-grained methods according to an objective measure: how close a coarse-grained dynamics method comes to a crystallographically determined intermediate structure when calculating a trajectory between the initial and final crystal protein structure. We test this with a set of five proteins with at least three crystallographically determined on-pathway high-resolution intermediate structures from the Protein Data Bank. For simple hinging motions involving a small conformational change, segmentation of the protein into two rigid sections outperforms other more computationally involved methods. However, large-scale conformational change is best addressed using a nonlinear approach and we suggest that there is merit in further developing such methods.

How Hydrophobic Buckminsterfullerene Affects Surrounding Water Structure

The hydrophobic hydration of fullerenes in water is of significant interest as the most common Buckminsterfullerene (C60) is a mesoscale sphere; C60 also has potential in pharmaceutical and nanomaterial applications. We use an all-atom molecular dynamics simulation lasting hundreds of nanoseconds to determine the behavior of a single molecule of C60 in a periodic box of water, and compare this to methane. A C60 molecule does not induce drying at the surface; however, unlike a hard sphere methane, a hard sphere C60 solute does. This is due to a larger number of attractive Lennard-Jones interactions between the carbon atom centers in C60 and the surrounding waters. In these simulations, water is not uniformly arranged but rather adopts a range of orientations in the first hydration shell despite the spherical symmetry of both solutes. There is a clear effect of solute size on the orientation of the first hydration shell waters. There is a large increase in hydrogen-bonding contacts between waters in the C60 first hydration shell. There is also a disruption of hydrogen bonds between waters in the first and second hydration shells. Water molecules in the first hydration shell preferentially create triangular structures that minimize the net water dipole near the surface near both the methane and C60 surface, reducing the total energy of the system. Additionally, in the first and second hydration shells, the water dipoles are ordered to a distance of 8 A from the solute surface. We conclude that, with a diameter of approximately 1 nm, C60 behaves as a large hydrophobic solute.

RNA polymerase II trigger loop residues stabilize and position the incoming nucleotide triphosphate in transcription.

A structurally conserved element, the trigger loop, has been suggested to play a key role in substrate selection and catalysis of RNA polymerase II (pol II) transcription elongation. Recently resolved X-ray structures showed that the trigger loop forms direct interactions with the β-phosphate and base of the matched nucleotide triphosphate (NTP) through residues His1085 and Leu1081, respectively. In order to understand the role of these two critical residues in stabilizing active site conformation in the dynamic complex, we performed all-atom molecular dynamics simulations of the wild-type pol II elongation complex and its mutants in explicit solvent. In the wild-type complex, we found that the trigger loop is stabilized in the “closed” conformation, and His1085 forms a stable interaction with the NTP. Simulations of point mutations of His1085 are shown to affect this interaction; simulations of alternative protonation states, which are inaccessible through experiment, indicate that only the protonated form is able to stabilize the His1085-NTP interaction. Another trigger loop residue, Leu1081, stabilizes the incoming nucleotide position through interaction with the nucleotide base. Our simulations of this Leu mutant suggest a three-component mechanism for correctly positioning the incoming NTP in which (i) hydrophobic contact through Leu1081, (ii) base stacking, and (iii) base pairing work together to minimize the motion of the incoming NTP base. These results complement experimental observations and provide insight into the role of the trigger loop on transcription fidelity.

Muscarinic Receptors as Model Targets and Antitargets for Structure-Based Ligand Discovery

G protein–coupled receptors (GPCRs) regulate virtually all aspects of human physiology and represent an important class of therapeutic drug targets. Many GPCR-targeted drugs resemble endogenous agonists, often resulting in poor selectivity among receptor subtypes and restricted pharmacologic profiles. The muscarinic acetylcholine receptor family exemplifies these problems; thousands of ligands are known, but few are receptor subtype–selective and nearly all are cationic in nature. Using structure-based docking against the M2 and M3 muscarinic receptors, we screened 3.1 million molecules for ligands with new physical properties, chemotypes, and receptor subtype selectivities. Of 19 docking-prioritized molecules tested against the M2 subtype, 11 had substantial activity and 8 represented new chemotypes. Intriguingly, two were uncharged ligands with low micromolar to high nanomolar Ki values, an observation with few precedents among aminergic GPCRs. To exploit a single amino-acid substitution among the binding pockets between the M2 and M3 receptors, we selected molecules predicted by docking to bind to the M3 and but not the M2 receptor. Of 16 molecules tested, 8 bound to the M3 receptor. Whereas selectivity remained modest for most of these, one was a partial agonist at the M3 receptor without measurable M2 agonism. Consistent with this activity, this compound stimulated insulin release from a mouse β-cell line. These results support the ability of structure-based discovery to identify new ligands with unexplored chemotypes and physical properties, leading to new biologic functions, even in an area as heavily explored as muscarinic pharmacology.

SAMPL4 & DOCK3.7: lessons for automated docking procedures

The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.

Structure-based discovery of selective positive allosteric modulators of antagonists for the M2 muscarinic acetylcholine receptor

Significance The orthosteric binding sites of the five muscarinic acetylcholine receptor (mAChR) subtypes are highly conserved, making the development of selective antagonists challenging. The allosteric sites of these receptors are more variable, allowing one to imagine allosteric modulators that confer subtype selectivity, which would reduce the major off-target effects of muscarinic antagonists. Accordingly, a large library docking campaign was prosecuted seeking unique positive allosteric modulators (PAMs) for antagonists, ultimately revealing a PAM that substantially potentiates antagonist binding leading to subtype selectivity at the M2 mAChR. This study supports the feasibility of discovering PAMs that can convert an armamentarium of potent but nonselective G-protein–coupled receptor (GPCR) antagonist drugs into subtype-selective reagents. Subtype-selective antagonists for muscarinic acetylcholine receptors (mAChRs) have long been elusive, owing to the highly conserved orthosteric binding site. However, allosteric sites of these receptors are less conserved, motivating the search for allosteric ligands that modulate agonists or antagonists to confer subtype selectivity. Accordingly, a 4.6 million-molecule library was docked against the structure of the prototypical M2 mAChR, seeking molecules that specifically stabilized antagonist binding. This led us to identify a positive allosteric modulator (PAM) that potentiated the antagonist N-methyl scopolamine (NMS). Structure-based optimization led to compound ’628, which enhanced binding of NMS, and the drug scopolamine itself, with a cooperativity factor (α) of 5.5 and a KB of 1.1 μM, while sparing the endogenous agonist acetylcholine. NMR spectral changes determined for methionine residues reflected changes in the allosteric network. Moreover, ’628 slowed the dissociation rate of NMS from the M2 mAChR by 50-fold, an effect not observed at the other four mAChR subtypes. The specific PAM effect of ’628 on NMS antagonism was conserved in functional assays, including agonist stimulation of [35S]GTPγS binding and ERK 1/2 phosphorylation. Importantly, the selective allostery between ’628 and NMS was retained in membranes from adult rat hypothalamus and in neonatal rat cardiomyocytes, supporting the physiological relevance of this PAM/antagonist approach. This study supports the feasibility of discovering PAMs that confer subtype selectivity to antagonists; molecules like ’628 can convert an armamentarium of potent but nonselective GPCR antagonist drugs into subtype-selective reagents, thus reducing their off-target effects.

Morphing Methods to Visualize Coarse-Grained Protein Dynamics

Morphing was initially developed as a cinematic effect, where one image is seamlessly transformed into another image. The technique was widely adopted by biologists to visualize the transition between protein conformational states, generating an interpolated pathway from an initial to a final protein structure. Geometric morphing seeks to create visually suggestive movies that illustrate structural changes between conformations but do not necessarily represent a biologically relevant pathway, while minimum energy path (MEP) interpolations aim at describing the true transition state between the crystal structure minima in the energy landscape.