Electronically-active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence-structure-function relations remain poorly characterized. In this work, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically-active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylene vinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8,000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

α-Helical antimicrobial peptides (AMPs) generally have facially amphiphilic structures that may lead to undesired peptide interactions with blood proteins and self-aggregation due to exposed hydrophobic surfaces. Here we report the design of a class of cationic, helical homo-polypeptide antimicrobials with a hydrophobic internal helical core and a charged exterior shell, possessing unprecedented radial amphiphilicity. The radially amphiphilic structure enables the polypeptide to bind effectively to the negatively charged bacterial surface and exhibit high antimicrobial activity against both gram-positive and gram-negative bacteria. Moreover, the shielding of the hydrophobic core by the charged exterior shell decreases nonspecific interactions with eukaryotic cells, as evidenced by low hemolytic activity, and protects the polypeptide backbone from proteolytic degradation. The radially amphiphilic polypeptides can also be used as effective adjuvants, allowing improved permeation of commercial antibiotics in bacteria and enhanced antimicrobial activity by one to two orders of magnitude. Designing AMPs bearing this unprecedented, unique radially amphiphilic structure represents an alternative direction of AMP development; radially amphiphilic polypeptides may become a general platform for developing AMPs to treat drug-resistant bacteria.

SummaryThe COVID-19 pandemic underwent a rapid transition with the emergence of a SARS-CoV-2 variant that carried the amino acid substitution D614G in the Spike protein that became globally prevalent. The G-form is both more infectious in vitro and associated with increased viral loads in infected people. To gain insight into the mechanism underlying these distinctive characteristics, we employed multiple replicas of microsecond all-atom simulations to probe the molecular-level impact of this substitution on Spike’s closed and open states. The open state enables Spike interactions with its human cellular receptor, ACE2. Here we show that changes in the inter-protomer energetics due to the D614G substitution favor a higher population of infection-capable (open) states. The inter-protomer interactions between S1 and S2 subunits in the open state of the D-form are asymmetric. This asymmetry is resolved in the G-form due to the release of tensile hydrogen bonds resulting in an increased population of open conformations. Thus, the increased infectivity of the G-form is likely due to a higher rate of profitable binding encounters with the host receptor. It is also predicted to be more neutralization sensitive due to enhanced exposure of the receptor binding domain, a key target region for neutralizing antibodies.

The COVID-19 (coronavirus disease 2019) pandemic underwent a rapid transition with the emergence of a dominant viral variant (from the “D-form” to the “G-form”) that carried an amino acid substitution D614G in its “Spike” protein. The G-form is more infectious in vitro and is associated with increased viral loads in the upper airways. To gain insight into the molecular-level underpinnings of these characteristics, we used microsecond all-atom simulations. We show that changes in the protein energetics favor a higher population of infection-capable states in the G-form through release of asymmetry present in the D-form inter-protomer interactions. Thus, the increased infectivity of the G-form is likely due to a higher rate of profitable binding encounters with the host receptor. It is also predicted to be more neutralization sensitive owing to enhanced exposure of the receptor binding domain, a key target region for neutralizing antibodies. These results are critical for vaccine design.

Self-assembled aggregates of peptides containing aromatic groups possess optoelectronic properties that make them attractive targets for the fabrication of biocompatible electronics. Molecular-level understanding of the influence of microscopic peptide chemistry on the properties of the aggregates is vital for rational peptide design. In this study, we construct a coarse-grained model of Asp-Phe-Ala-Gly-OPV3-Gly-Ala-Phe-Asp (DFAG-OPV3-GAFD) peptides containing OPV3 (distyrylbenzene) π-conjugated cores explicitly parameterized against all-atom calculations and perform molecular dynamics simulations of the self-assembly of hundreds of molecules over hundreds of nanoseconds. We observe a hierarchical assembly mechanism, wherein approximately two to eight peptides assemble into stacks with aligned aromatic cores that subsequently form elliptical aggregates and ultimately a branched network with a fractal dimensionality of ∼1.5. The assembly dynamics are well described by a Smoluchowski coagulation process, for which we extract rate constants from the molecular simulations to both furnish insight into the microscopic assembly kinetics and extrapolate our aggregation predictions to time and length scales beyond the reach of molecular simulation. This study presents new molecular-level understanding of the morphology and dynamics of the spontaneous self-assembly of DFAG-OPV3-GAFD peptides and establishes a systematic protocol to develop coarse-grained models of optoelectronic peptides for the exploration and design of π-conjugated peptides with tunable optoelectronic properties.

The conformational states explored by polymers and proteins can be controlled by environmental conditions (e.g., temperature, pressure, and solvent) and molecular chemistry (e.g., molecular weight and side chain identity). We introduce an approach employing the diffusion map nonlinear machine learning technique to recover single molecule free energy landscapes from molecular simulations, quantify changes to the landscape as a function of external conditions and molecular chemistry, and relate these changes to modifications of molecular structure and dynamics. In an application to an n-eicosane chain, we quantify the thermally accessible chain configurations as a function of temperature and solvent conditions. In an application to a family of polyglutamate-derivative homopeptides, we quantify helical stability as a function of side chain length, resolve the critical side chain length for the helix-coil transition, and expose the molecular mechanisms underpinning side chain-mediated helix stability. By quantifying single molecule responses through perturbations to the underlying free energy surface, our approach provides a quantitative bridge between experimentally controllable variables and microscopic molecular behavior, guiding and informing rational engineering of desirable molecular structure and function.

Synthetic polypeptides have received increasing attention due to their ability to form higher ordered structures similar to proteins. The control over their secondary structures, which enables dynamic conformational changes, is primarily accomplished by tuning the side-chain hydrophobic or ionic interactions. Herein we report a strategy to modulate the conformation of polypeptides utilizing donor–acceptor interactions emanating from side-chain H-bonding ligands. Specifically, 1,2,3-triazole groups, when incorporated onto polypeptide side-chains, serve as both H-bond donors and acceptors at neutral pH and disrupt the α-helical conformation. When protonated, the resulting 1,2,3-triazolium ions lose the ability to act as H-bond acceptors, and the polypeptides regain their α-helical structure. The conformational change of triazole polypeptides in response to the donor-acceptor pattern was conclusively demonstrated using both experimental-based and simulation-based methods. We further showed the utility of this transition by designing smart, cell-penetrating polymers that undergo acid-activated endosomal escape in living cells.

Antibiotic-resistant bacteria rapidly spread in clinical and natural environments and challenge our modern lifestyle. A major component of defense against antibiotics in Gram-negative bacteria is a drug permeation barrier created by active efflux across the outer membrane. We identified molecular determinants defining the propensity of small peptidomimetic molecules to avoid and inhibit efflux pumps in Pseudomonas aeruginosa, a human pathogen notorious for its antibiotic resistance. Combining experimental and computational protocols, we mapped the fate of the compounds from structure-activity relationships through their dynamic behavior in solution, permeation across both the inner and outer membranes, and interaction with MexB, the major efflux transporter of P. aeruginosa. We identified predictors of efflux avoidance and inhibition and demonstrated their power by using a library of traditional antibiotics and compound series and by generating new inhibitors of MexB. The identified predictors will enable the discovery and optimization of antibacterial agents suitable for treatment of P. aeruginosa infections. IMPORTANCE Efflux pump avoidance and inhibition are desired properties for the optimization of antibacterial activities against Gram-negative bacteria. However, molecular and physicochemical interactions defining the interface between compounds and efflux pumps remain poorly understood. We identified properties that correlate with efflux avoidance and inhibition, are predictive of similar features in structurally diverse compounds, and allow researchers to distinguish between efflux substrates, inhibitors, and avoiders in P. aeruginosa. The developed predictive models are based on the descriptors representative of different clusters comprising a physically intuitive combination of properties. Molecular shape (represented by acylindricity), amphiphilicity (anisotropic polarizability), aromaticity (number of aromatic rings), and the partition coefficient (LogD) are physicochemical predictors of efflux inhibitors, whereas interactions with Pro668 and Leu674 residues of MexB distinguish between inhibitors/substrates and efflux avoiders. The predictive models and efflux rules are applicable to compounds with unrelated chemical scaffolds and pave the way for development of compounds with the desired efflux interface properties.