Finding Druggable Sites in Proteins Using TACTICS.

Structure-based drug discovery efforts require knowledge of where drug-binding sites are located on target proteins. To address the challenge of finding druggable sites, we developed a machine-learning algorithm called TACTICS (trajectory-based analysis of conformations to identify cryptic sites), which uses an ensemble of molecular structures (such as molecular dynamics simulation data) as input. First, TACTICS uses k-means clustering to select a small number of conformations that represent the overall conformational heterogeneity of the data. Then, TACTICS uses a random forest model to identify potentially bindable residues in each selected conformation, based on protein motion and geometry. Lastly, residues in possible binding pockets are scored using fragment docking. As proof-of-principle, TACTICS was applied to the analysis of simulations of the SARS-CoV-2 main protease and methyltransferase and the Yersinia pestis aryl carrier protein. Our approach recapitulates known small-molecule binding sites and predicts the locations of sites not previously observed in experimentally determined structures. The TACTICS code is available at https://github.com/Albert-Lau-Lab/tactics_protein_analysis.

Phosphorylation at Ser65 modulates ubiquitin conformational dynamics.

Ubiquitin phosphorylation at Ser65 increases the population of a rare C-terminally retracted (CR) conformation. Transition between the Major and CR ubiquitin conformations is critical for promoting mitochondrial degradation. The mechanisms by which the Major and CR conformations of Ser65-phosphorylated (pSer65) ubiquitin interconvert, however, remain unresolved. Here, we perform all-atom molecular dynamics simulations using the string method with swarms of trajectories to calculate the lowest free-energy path between these two conformers. Our analysis reveals the existence of a Bent intermediate in which the C-terminal residues of the ß5 strand shift to resemble the CR conformation, while pSer65 retains contacts resembling the Major conformation. This stable intermediate was reproduced in well-tempered metadynamics calculations but was less stable for a Gln2Ala mutant that disrupts contacts with pSer65. Lastly, dynamical network modeling reveals that the transition from the Major to CR conformations involves a decoupling of residues near pSer65 from the adjacent ß1 strand.

Conformational changes in the essential E. coli septal cell wall synthesis complex suggest an activation mechanism.

The bacterial divisome is a macromolecular machine composed of more than 30 proteins that controls cell wall constriction during division. Here, we present a model of the structure and dynamics of the core complex of the E. coli divisome, supported by a combination of structure prediction, molecular dynamics simulation, single-molecule imaging, and mutagenesis. We focus on the septal cell wall synthase complex formed by FtsW and FtsI, and its regulators FtsQ, FtsL, FtsB, and FtsN. The results indicate extensive interactions in four regions in the periplasmic domains of the complex. FtsQ, FtsL, and FtsB support FtsI in an extended conformation, with the FtsI transpeptidase domain lifted away from the membrane through interactions among the C-terminal domains. FtsN binds between FtsI and FtsL in a region rich in residues with superfission (activating) and dominant negative (inhibitory) mutations. Mutagenesis experiments and simulations suggest that the essential domain of FtsN links FtsI and FtsL together, potentially modulating interactions between the anchor-loop of FtsI and the putative catalytic cavity of FtsW, thus suggesting a mechanism of how FtsN activates the cell wall synthesis activities of FtsW and FtsI.

Excitatory and inhibitory D-serine binding to the NMDA receptor.

N-methyl-D-aspartate receptors (NMDARs) uniquely require binding of two different neurotransmitter agonists for synaptic transmission. D-serine and glycine bind to one subunit, GluN1, while glutamate binds to the other, GluN2. These agonists bind to the receptor's bi-lobed ligand-binding domains (LBDs), which close around the agonist during receptor activation. To better understand the unexplored mechanisms by which D-serine contributes to receptor activation, we performed multi-microsecond molecular dynamics simulations of the GluN1/GluN2A LBD dimer with free D-serine and glutamate agonists. Surprisingly, we observed D-serine binding to both GluN1 and GluN2A LBDs, suggesting that D-serine competes with glutamate for binding to GluN2A. This mechanism is confirmed by our electrophysiology experiments, which show that D-serine is indeed inhibitory at high concentrations. Although free energy calculations indicate that D-serine stabilizes the closed GluN2A LBD, its inhibitory behavior suggests that it either does not remain bound long enough or does not generate sufficient force for ion channel gating. We developed a workflow using pathway similarity analysis to identify groups of residues working together to promote binding. These conformation-dependent pathways were not significantly impacted by the presence of N-linked glycans, which act primarily by interacting with the LBD bottom lobe to stabilize the closed LBD.

Development and characterization of functional antibodies targeting NMDA receptors.

N-methyl-D-aspartate receptors (NMDARs) are critically involved in basic brain functions and neurodegeneration as well as tumor invasiveness. Targeting specific subtypes of NMDARs with distinct activities has been considered an effective therapeutic strategy for neurological disorders and diseases. However, complete elimination of off-target effects of small chemical compounds has been challenging and thus, there is a need to explore alternative strategies for targeting NMDAR subtypes. Here we report identification of a functional antibody that specifically targets the GluN1-GluN2B NMDAR subtype and allosterically down-regulates ion channel activity as assessed by electrophysiology. Through biochemical analysis, x-ray crystallography, single-particle electron cryomicroscopy, and molecular dynamics simulations, we show that this inhibitory antibody recognizes the amino terminal domain of the GluN2B subunit and increases the population of the non-active conformational state. The current study demonstrates that antibodies may serve as specific reagents to regulate NMDAR functions for basic research and therapeutic objectives.

D-Serine Potently Drives Ligand-Binding Domain Closure in the Ionotropic Glutamate Receptor GluD2.

Despite their classification as ionotropic glutamate receptors, GluD receptors are not functional ligand-gated ion channels and do not bind glutamate. GluD2 receptors bind D-serine and coordinate transsynaptic complexes that regulate synaptic plasticity. Instead of opening the ion channel pore, mechanical tension produced from closure of GluD2 ligand-binding domains (LBDs) drives conformational rearrangements for non-ionotropic signaling. We report computed conformational free energy landscapes for the GluD2 LBD in apo and D-serine-bound states. Unexpectedly, the conformational free energy associated with GluD2 LBD closure upon D-serine binding is greater than that for AMPA, NMDA, and kainate receptor LBDs upon agonist binding. This excludes insufficient force generation as an explanation for lack of ion channel activity in GluD2 receptors and suggests that non-ionotropic conformational rearrangements do more work than pore opening. We also report free energy landscapes for GluD2 LBD harboring a neurodegenerative mutation and demonstrate selective stabilization of closed conformations in the apo state.

Flexible Backbone Assembly and Refinement of Symmetrical Homomeric Complexes.

Symmetrical homomeric proteins are ubiquitous in every domain of life, and information about their structure is essential to decipher function. The size of these complexes often makes them intractable to high-resolution structure determination experiments. Computational docking algorithms offer a promising alternative for modeling large complexes with arbitrary symmetry. Accuracy of existing algorithms, however, is limited by backbone inaccuracies when using homology-modeled monomers. Here, we present Rosetta SymDock2 with a broad search of symmetrical conformational space using a six-dimensional coarse-grained score function followed by an all-atom flexible-backbone refinement, which we demonstrate to be essential for physically realistic modeling of tightly packed complexes. In global docking of a benchmark set of complexes of different point symmetries-starting from homology-modeled monomers-we successfully dock (defined as predicting three near-native structures in the five top-scoring models) 17 out of 31 cyclic complexes and 3 out of 12 dihedral complexes.