Thermal Tunneling of Homopolymers through Amphiphilic Membranes

Efficient enumeration-selection computational strategy for adaptive chemistry

Design problems of finding efficient patterns, adaptation of complex molecules to external environments, affinity of molecules to specific targets, dynamic adaptive behavior of chemical systems, reconstruction of 3D structures from diffraction data are examples of difficult to solve optimal design or inverse search problems. Nature inspires evolution strategies to solve design problems that are based on selection of successful adaptations and heritable traits over generations. To exploit this strategy in the creation of new materials, a concept of adaptive chemistry was proposed to provide a route for synthesis of self-adapting molecules that can fit to their environment. We propose a computational method of an efficient exhaustive search exploiting massive parallelization on modern GPUs, which finds a solution for an inverse problem by solving repetitively a direct problem in the mean field approximation. One example is the search for a composition of a copolymer that allows the polymer to translocate through a lipid membrane at a minimal time. Another example is a search of a copolymer sequence that maximizes the polymer load in the micelle defined by the radial core-shell potentials. The length and the composition of the sequence are adjusted to fit into the restricted environment. Hydrogen bonding is another pathway of adaptation to the environment through reversible links. A linear polymer that interacts with water through hydrogen bonds adjusts the position of hydrogen bonds along the chain as a function of the concentration field around monomers. In the last example, branching of the molecules is adjusted to external fields, providing molecules with annealed topology, that can be flexibly changed by changing external conditions. The method can be generalized and applied to a broad spectrum of design problems in chemistry and physics, where adaptive behavior in multi-parameter space in response to environmental conditions lead to non-trivial patterns or molecule architectures and compositions. It can further be combined with machine learning or other optimization techniques to explore more efficiently the parameter space.

Decoding Interaction Patterns from the Chemical Sequence of Polymers Using Neural Networks

The relation between chemical sequences and the properties of polymers is considered using artificial neural networks with a low-dimensional bottleneck layer of neurons. These encoder-decoder architectures may compress the input information into a meaningful set of physical variables that describe the correlation between distinct types of data. In this work, neural networks were trained to translate a sequence of hydrophilic and hydrophobic segments into the effective free energy landscape of a copolymer interacting with a lipid membrane. The training data were obtained by the sampling of coarse-grained polymer conformations in a given membrane density field. Neural networks that were split into separate channels have learned to decompose the free energy into independent components that are explainable by known concepts from polymer physics. The semantic information in the hidden layers was employed to predict polymer translocation events through a membrane for a more detailed dynamic model via a transfer learning procedure. The search for minimal translocation times in the compressed chemical space underlined that nontrivial sequence motifs may lead to optimal properties.

Phospholipid-mimicking cell-penetrating polymers: principles and applications

Understanding the interactions of eukaryotic cellular membranes with nanomaterials is required to construct efficient and safe nanomedicines and molecular bioengineering. Intracellular uptake of nanocarriers by active endocytosis limits the intracellular distribution to the endosomal compartment, impairing the intended biological actions of the cargo molecules. Nonendocytic intracellular migration is another route for nanomaterials with cationic or amphiphilic properties to evade the barrier function of the lipid bilayer plasma membranes. Direct transport of nanomaterials into cells is efficient, but this may cause cytotoxic or biocidal effects by temporarily disrupting the biological membrane barrier. We have recently discovered that nonendocytic internalization of synthetic amphipathic polymer-based nanoaggregates that mimic the structure of natural phospholipids can occur without inducing cytotoxicity. Analysis using a proton leakage assay indicated that the polymer enters cells by amphiphilicity-induced membrane fusion rather than by transmembrane pore formation. These noncytotoxic cell-penetrating polymers may find applications in drug delivery systems, gene transfection, cell therapies, and biomolecular engineering.

Translocation Mechanisms of Cell-Penetrating Polymers Identified by Induced Proton Dynamics

Unlike the majority of nanomaterials designed for cellular uptake via endocytic pathways, some of the functional nanoparticles and nanospheres directly enter the cytoplasm without overt biomembrane injuries. Previously, we have shown that a water-soluble nanoaggregate composed of amphiphilic random copolymer of 2-methacryloyloxyethyl phosphorylcholine (MPC) and n-butyl methacrylate (BMA), poly(MPC- random-BMA) (PMB), passes live cell membranes in an endocytosis-free manner. Yet, details in its translocation mechanism remain elusive due to the lack of proper analytical methods. To understand this phenomenon experimentally, we elaborated the original pH perturbation assay that is extremely sensitive to the pore formation on cell membranes. The ultimate sensitivity originates from the detection of the smallest indicator H⁺ (H₃O⁺) passed through the molecularly sized transmembrane pores upon challenge by exogenous reagents. We revealed that water-soluble PMB at the 30 mol % MPC unit (i.e., PMB30W) penetrated into the cytosol of model mammalian cells without any proton leaks, in contrast to conventional cell-penetrating peptides, TAT and R8 as well as the surfactant, Triton X-100. While exposure of PMB30W permeabilized cytoplasmic lactate dehydrogenase out of the cells, indicating the alteration of cell membrane polarity by partitioning of amphiphilic PMB30W into the lipid bilayers. Nevertheless, the biomembrane alterations by PMB30W did not exhibit cytotoxicity. In summary, elucidating translocation mechanisms by proton dynamics will guide the design of nanomaterials with controlled permeabilization to cell membranes for bioengineering applications.