Ribosome assembly in eukaryotes requires approximately 200 essential assembly factors (AFs), and occurs via ordered events that initiate in the nucleolus and culminate in the cytoplasm. Here we present the cryo-electron microscopy (cryo-EM) structure of a late cytoplasmic 40S ribosome assembly intermediate from Saccharomyces cerevisiae. The positions of bound AFs were defined using cryo-EM reconstructions of pre-ribosomal complexes lacking individual components. All seven AFs are positioned to prevent each step in the translation initiation pathway by obstructing the binding sites for initiation factors, by preventing the opening of the mRNA channel, by blocking 60S subunit joining, and by disrupting the decoding site. We suggest that these highly redundant mechanisms ensure that pre-40S particles do not enter the translation pathway, which would result in their rapid degradation. Implications for the regulation of 40S maturation are also discussed.

Synthetic polymer membranes, critical to diverse energy-efficient separations, are subject to permeability-selectivity trade-offs that decrease their overall efficacy. These trade-offs are due to structural variations (e.g., broad pore size distributions) in both nonporous membranes used for Angstrom-scale separations and porous membranes used for nano to micron-scale separations. Biological membranes utilize well-defined Angstrom-scale pores to provide exceptional transport properties and can be used as inspiration to overcome this trade-off. Here, we present a comprehensive demonstration of such a bioinspired approach based on pillar[5]arene artificial water channels, resulting in artificial water channel-based block copolymer membranes. These membranes have a sharp selectivity profile with a molecular weight cutoff of ~ 500 Da, a size range challenging to achieve with current membranes, while achieving a large improvement in permeability (~65 L m−2 h−1 bar−1 compared with 4–7 L m−2 h−1 bar−1) over similarly rated commercial membranes.

Cooperative binding of phenolic species to insulin hexamers is known to stabilize pharmaceutical preparations of the hormone. Phenol dissociation is rapid on hexamer dissolution timescales, and phenol unbinding upon dilution is likely the first step in the conversion of (pharmaceutical) hexameric insulin to the active monomeric form upon injection. However, a clear understanding of the determinants of the rates of phenol unbinding remains obscure, chiefly because residues implicated in phenol exchange as determined by NMR are not all associated with likely unbinding routes suggested by the best-resolved hexamer structures. We apply random acceleration molecular dynamics simulation to identify potential escape routes of phenol from hydrophobic cavities in the hexameric insulin-phenol complex. We find three major pathways, which provide new insights into (un)binding mechanisms for phenol. We identify several residues directly participating in escape events that serve to resolve ambiguities from recent NMR experiments. Reaction coordinates for dissociation of phenol are developed based on these exit pathways. Potentials of mean force along the reaction coordinate for each pathway are resolved using multiple independent steered molecular dynamics simulations with second-order cumulant expansion of Jarzynski's equality. Our results for DeltaF agree reasonably well within the range of known experimental and previous simulation magnitudes of this quantity. Based on structural analysis and energetic barriers for each pathway, we suggest a plausible preferred mechanism of phenolic exchange that differs from previous mechanisms. Several weakly-bound metastable states are also observed for the first time in the phenol dissociation reaction.

We have characterized a large-scale inactive-to-active conformational change in the activation-loop of the insulin receptor kinase domain at the atomistic level via untargeted temperature-accelerated molecular dynamics (TAMD) and free-energy calculations using the string method. TAMD simulations consistently show folding of the A-loop into a helical conformation followed by unfolding to an active conformation, causing the highly conserved DFG-motif (Asp(1150), Phe(1151), and Gly(1152)) to switch from the inactive "D-out/F-in" to the nucleotide-binding-competent "D-in/F-out" conformation. The minimum free-energy path computed from the string method preserves these helical intermediates along the inactive-to-active path, and the thermodynamic free-energy differences are consistent with previous work on various other kinases. The mechanisms revealed by TAMD also suggest that the regulatory spine can be dynamically assembled/disassembled either by DFG-flip or by movement of the αC-helix. Together, these findings both broaden our understanding of kinase activation and point to intermediates as specific therapeutic targets.

Regulators of G protein signaling (RGS) proteins are key players in regulating signaling via G protein-coupled receptors. RGS proteins directly bind to the Gα-subunits of activated heterotrimeric G-proteins, and accelerate the rate of GTP hydrolysis, thereby rapidly deactivating G-proteins. Using atomistic simulations and NMR spectroscopy, we have studied in molecular detail the mechanism of action of CCG-50014, a potent small molecule inhibitor of RGS4 which covalently binds to cysteine residues on RGS4. We apply temperature-accelerated molecular dynamics (TAMD) to carry out enhanced conformational sampling of apo RGS4 structures, and consistently find that the α5-α6 helix pair of RGS4 can spontaneously span open-like conformations, allowing binding of CCG-50014 to the buried side-chain of Cys95. Both NMR experiments and MD simulations reveal chemical shift perturbations in residues in the vicinity of inhibitor binding site as well as in the RGS4-Gα binding interface. Consistent with a loss of G-protein binding, GAP activity, and allosteric mechanism of action of CCG-50014, our simulations of the RGS4-Gα complex in the presence of inhibitor suggest a relatively unstable protein-protein interaction. These results have potential implications for understanding how the conformational dynamics among RGS proteins may play a key role in the sensitivity of inhibitors.

Insulin regulates blood glucose levels in higher organisms by binding to and activating insulin receptor (IR), a constitutively homodimeric glycoprotein of the receptor tyrosine kinase (RTK) superfamily. Therapeutic efforts in treating diabetes have been significantly impeded by the absence of structural information on the activated form of the insulin/IR complex. Mutagenesis and photo-crosslinking experiments and structural information on insulin and apo-IR strongly suggest that the dual-chain insulin molecule, unlike the related single-chain insulin-like growth factors, binds to IR in a very different conformation than what is displayed in storage forms of the hormone. In particular, hydrophobic residues buried in the core of the folded insulin molecule engage the receptor. There is also the possibility of plasticity in the receptor structure based on these data, which may in part be due to rearrangement of the so-called CT-peptide, a tandem hormone-binding element of IR. These possibilities provide opportunity for large-scale molecular modeling to contribute to our understanding of this system. Using various atomistic simulation approaches, we have constructed all-atom structural models of hormone/receptor complexes in the presence of CT in its crystallographic position and a thermodynamically favorable displaced position. In the "displaced-CT" complex, many more insulin-receptor contacts suggested by experiments are satisfied, and our simulations also suggest that R-insulin potentially represents the receptor-bound form of hormone. The results presented in this work have further implications for the design of receptor-specific agonists/antagonists.

Small-molecule inhibitor selectivity may be influenced by variation in dynamics among members of a protein family. Regulator of G-protein Signaling (RGS) proteins are a family that plays a key role in G-Protein Coupled Receptor (GPCR) signaling by binding to active Gα subunits and accelerating GTP hydrolysis, thereby terminating activity. Thiadiazolidinones (TDZDs) inhibit the RGS-Gα interaction by covalent modification of cysteine residues in RGS proteins. Some differences in specificity may be explained by differences in the complement of cysteines among RGS proteins. However, key cysteines shared by RGS proteins inhibited by TDZDs are not exposed on the protein surface, and differences in potency exist among RGS proteins containing only buried cysteines. We hypothesize that differential exposure of buried cysteine residues among RGS proteins partially drives TDZD selectivity. Hydrogen-deuterium exchange (HDX) studies and molecular dynamics (MD) simulations were used to probe the dynamics of RGS4, RGS8, and RGS19, three RGS proteins inhibited at a range of potencies by TDZDs. When these proteins were mutated to contain a single, shared cysteine, RGS19 was found to be most potently inhibited. HDX studies revealed differences in α4 and α6 helix flexibility among RGS isoforms, with particularly high flexibility in RGS19. This could cause differences in cysteine exposure and lead to differences in potency of TDZD inhibition. MD simulations of RGS proteins revealed motions that correspond to solvent exposure observed in HDX, providing further evidence for a role of protein dynamics in TDZD selectivity.

Ligand residence times and binding rates have been found to be useful quantities to consider during drug design. The underlying structural and dynamic determinants of these kinetic quantities are difficult to discern. Driven by developments in computational hardware and simulation methodologies, molecular dynamics (MD) studies on full binding and unbinding pathways have emerged recently, showing these structural and dynamic determinants in atomic detail. However, the long timescales related to drug binding and release are still prohibitive to conventional MD simulation. Here we discuss a suite of enhanced sampling methods that have been applied to the study of full ligand binding or unbinding pathways, and reveal the kinetics of drug binding and/or release. We divide these sampling methods into three families (trajectory parallelization, metadynamics, and temperature- based methods), and discuss recent applications of each, as well as their basic theoretical underpinnings including how kinetic information is extracted. We then present an outlook for how the field could evolve, and how the rich variety of sampling methods discussed here can be leveraged in the future for computationally driven drug design.