An ability to develop sequence-defined synthetic polymers that both mimic lipid amphiphilicity for self-assembly of highly stable membrane-mimetic 2D nanomaterials and exhibit protein-like functionality would revolutionize the development of biomimetic membranes. Here we report the assembly of lipid-like peptoids into highly stable, crystalline, free-standing and self-repairing membrane-mimetic 2D nanomaterials through a facile crystallization process. Both experimental and molecular dynamics simulation results show that peptoids assemble into membranes through an anisotropic formation process. We further demonstrated the use of peptoid membranes as a robust platform to incorporate and pattern functional objects through large side-chain diversity and/or co-crystallization approaches. Similar to lipid membranes, peptoid membranes exhibit changes in thickness upon exposure to external stimuli; they can coat surfaces in single layers and self-repair. We anticipate that this new class of membrane-mimetic 2D nanomaterials will provide a robust matrix for development of biomimetic membranes tailored to specific applications.

Conformational transitions are functionally important in many proteins. In the enzyme adenylate kinase (AK), two small domains (LID and NMP) close over the larger CORE domain; the reverse (opening) motion limits the rate of catalytic turnover. Here, using double-well Gō simulations of E. coli AK, we elaborate on previous investigations of the AK transition mechanism by characterizing the contributions of rigid-body (Cartesian), backbone dihedral, and contact motions to the transition state (TS) properties. In addition, we compare an apo simulation to a pseudoligand-bound simulation to reveal insight into allostery. In Cartesian space, LID closure precedes NMP closure in the bound simulation, consistent with prior coarse-grained models of the AK transition. However, NMP-first closure is preferred in the apo simulation. In backbone dihedral space, we find that as expected, backbone fluctuations are reduced in the O to C transition in parts of all three domains. Among these "quenching" residues, most in the CORE, especially residues 11-13, are rigidified in the TS of the bound simulation, while residues 42-44 in the NMP are flexible in the TS. In contact space, in both apo and bound simulations, one nucleus of closed state contacts includes parts of the NMP and CORE; CORE-LID contacts are absent in the TS of the apo simulation but formed in the TS of the bound simulation. From these results, we predict mutations that will perturb the opening and/or closing transition rates by changing the entropy of dihedrals and/or the enthalpy of contacts. Furthermore, regarding allostery, the fully closed structure is populated in the apo simulation, but our contact results imply that ligand binding shifts the preferred O/C transition pathway, thus precluding a simple conformational selection mechanism. Finally, the analytical approach and the insights derived from this work may inform the rational design of flexibility and allostery in proteins.

Allosteric proteins have been studied extensively in the last 40 years, but so far, no systematic analysis of conformational changes between allosteric structures has been carried out. Here, we compile a set of 51 pairs of known inactive and active allosteric protein structures from the Protein Data Bank. We calculate local conformational differences between the two structures of each protein using simple metrics, such as backbone and side-chain Cartesian displacement, and torsion angle change and rearrangement in residue-residue contacts. Thresholds for each metric arise from distributions of motions in two control sets of pairs of protein structures in the same biochemical state. Statistical analysis of motions in allosteric proteins quantifies the magnitude of allosteric effects and reveals simple structural principles about allostery. For example, allosteric proteins exhibit substantial conformational changes comprising about 20% of the residues. In addition, motions in allosteric proteins show strong bias toward weakly constrained regions such as loops and the protein surface. Correlation functions show that motions communicate through protein structures over distances averaging 10-20 residues in sequence space and 10-20 A in Cartesian space. Comparison of motions in the allosteric set and a set of 21 nonallosteric ligand-binding proteins shows that nonallosteric proteins also exhibit bias of motion toward weakly constrained regions and local correlation of motion. However, allosteric proteins exhibit twice as much percent motion on average as nonallosteric proteins with ligand-induced motion. These observations may guide efforts to design flexibility and allostery into proteins.

Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that networks of contacts altered, formed, or broken are a significant contributor to allosteric communication in proteins. In this work, we identify which interactions change significantly between the residue-residue contact networks of two allosteric structures and then organize these changes into graphs. We perform the analysis on 15 pairs of allosteric structures with effector and substrate each present in at least one of the two structures. Most proteins exhibit large, dense regions of contact rearrangement, and the graphs form connected paths between allosteric effector and substrate sites in five of these proteins. In the remaining ten proteins, large-scale conformational changes such as rigid-body motions are likely required in addition to contact rearrangement networks to account for substrate-effector communication. On average, clusters which contain at least one substrate or effector molecule comprise 20% of the protein. These allosteric graphs are small worlds; that is, they typically have mean shortest path lengths comparable to those of corresponding random graphs and average clustering coefficients enhanced relative to those of random graphs. The networks capture 60 to 80% of known allosteryperturbing mutants in three proteins, and the metrics degree and closeness are statistically good discriminators of mutant residues from non-mutant residues within the networks in two of these three proteins. For two proteins, coevolving clusters of residues which have been hypothesized to be allosterically important differ from the regions with the most contact rearrangement. Residues and contacts which modulate normal mode fluctuations also often participate in the contact rearrangement networks. In summary, residue-residue contact rearrangement networks provide useful representations of the portions of allosteric pathways resulting from coupled local motions.