Artificial neural networks in tandem with molecular descriptors as predictive tools for continuous liposome manufacturing.

The current study utilized an artificial neural network (ANN) to generate computational models to achieve process optimization for a previously developed continuous liposome manufacturing system. The liposome formation was based on a continuous manufacturing system with a co-axial turbulent jet in a co-flow technology. The ethanol phase with lipids and aqueous phase resulted in liposomes of homogeneous sizes. The input features of the ANN included critical material attributes (CMAs) (e.g., hydrocarbon tail length, cholesterol percent, and buffer type) and critical process parameters (CPPs) (e.g., solvent temperature and flow rate), while the ANN outputs included critical quality attributes (CQAs) of liposomes (i.e., particle size and polydispersity index (PDI)). Two common ANN architectures, multiple-input-multiple-output (MIMO) models and multiple-input-single-output (MISO) models, were evaluated in this study, where the MISO outperformed MIMO with improved accuracy. Molecular descriptors, obtained from PaDEL-Descriptor software, were used to capture the physicochemical properties of the lipids and used in training of the ANN. The combination of CMAs, CPPs, and molecular descriptors as inputs to the MISO ANN model reduced the training and testing mean relative error. Additionally, a graphic user interface (GUI) was successfully developed to assist the end-user in performing interactive simulated risk analysis and visualizing model predictions.

Liposome-based measurement of light-driven chloride transport kinetics of halorhodopsin.

We report a simple and direct fluorimetric vesicle-based method for measuring the transport rate of the light-driven ions pumps as specifically applied to the chloride pump, halorhodopsin, from Natronomonas pharaonis (pHR). Previous measurements were cell-based and methods to determine average single channel permeability challenging. We used a water-in-oil emulsion method for directional pHR reconstitution into two different types of vesicles: lipid vesicles and asymmetric lipid-block copolymer vesicles. We then used stopped-flow experiments combined with fluorescence correlation spectroscopy to determine per protein Cl- transport rates. We obtained a Cl- transport rate of 442 (±17.7) Cl-/protein/s in egg phosphatidyl choline (PC) lipid vesicles and 413 (±26) Cl-/protein/s in hybrid block copolymer/lipid (BCP/PC) vesicles with polybutadine-polyethylene oxide (PB12PEO8) on the outer leaflet and PC in the inner leaflet at a photon flux of 1450 photons/protein/s. Normalizing to a per photon basis, this corresponds to 0.30 (±0.07) Cl-/photon and 0.28 (±0.04) Cl-/photon for pure PC and BCP/PC hybrid vesicles respectively, both of which are in agreement with recently reported turnover of ~500 Cl-/protein/s from flash photolysis experiments and with voltage-clamp measurements of 0.35 (±0.16) Cl-/photon in pHR-expressing oocytes as well as with a pHR quantum efficiency of ~30%.

Molecular Dynamics Simulation to Uncover the Mechanisms of Protein Instability During Freezing.

Freezing is a common process applied in the pharmaceutical industry to store and transport biotherapeutics. Herewith, multi-scale molecular dynamics simulations of Lactate dehydrogenase (LDH) protein in phosphate buffer with/without ice formation performed to uncover the still poorly understood mechanisms and molecular details of protein destabilization upon freezing. Both fast and slow ice growing conditions were simulated at 243 K from one or two-side of the simulation box, respectively. The rate of ice formation at all-atom simulations was crucial to LDH stability, as faster freezing rates resulted in enhanced structural stability maintained by a higher number of intramolecular hydrogen bonds, less flexible protein's residues, lower solvent accessibility and greater structural compactness. Further, protein aggregation investigated by coarse-grained simulations was verified to be initiated by extended protein structures and retained by electrostatic interactions of the salt bridges between charged residues and hydrogen bonds between polar residues of the protein. Lastly, the study of free energy of dissociation through steered molecular dynamics simulation revealed LDH was destabilized by the solvation of the hydrophobic core and the loss of hydrophobic interactions. For the first time, experimentally validated molecular simulations revealed the detailed mechanisms of LDH destabilization upon ice formation and cryoconcentration of solutes.

Interplay of cysteine exposure and global protein dynamics in small-molecule recognition by a regulator of G-protein signaling protein.

Regulator of G protein signaling (RGS) proteins play a pivotal role in regulation of G protein-coupled receptor (GPCR) signaling and are therefore becoming an increasingly important therapeutic target. Recently discovered thiadiazolidinone (TDZD) compounds that target cysteine residues have shown different levels of specificities and potencies for the RGS4 protein, thereby suggesting intrinsic differences in dynamics of this protein upon binding of these compounds. In this work, we investigated using atomistic molecular dynamics (MD) simulations the effect of binding of several small-molecule inhibitors on perturbations and dynamical motions in RGS4. Specifically, we studied two conformational models of RGS4 in which a buried cysteine residue is solvent-exposed due to side-chain motions or due to flexibility in neighboring helices. We found that TDZD compounds with aromatic functional groups perturb the RGS4 structure more than compounds with aliphatic functional groups. Moreover, small-molecules with aromatic functional groups but lacking sulfur atoms only transiently reside within the protein and spontaneously dissociate to the solvent. We further measured inhibitory effects of TDZD compounds using a protein-protein interaction assay on a single-cysteine RGS4 protein showing trends in potencies of compounds consistent with our simulation studies. Thermodynamic analyses of RGS4 conformations in the apo-state and on binding to TDZD compounds revealed links between both conformational models of RGS4. The exposure of cysteine side-chains appears to facilitate initial binding of TDZD compounds followed by migration of the compound into a bundle of four helices, thereby causing allosteric perturbations in the RGS/Gα protein-protein interface.

Interpreting Hydrogen-Deuterium Exchange Events in Proteins Using Atomistic Simulations: Case Studies on Regulators of G-Protein Signaling Proteins.

Hydrogen-deuterium exchange (HDX) experiments are widely used in studies of protein dynamics. To predict the propensity of amide hydrogens for exchange with deuterium, several models have been reported in which computations of amide-hydrogen protection factors are carried out using molecular dynamics (MD) simulations. Given significant variation in the criteria used in different models, the robustness and broader applicability of these models to other proteins, especially homologous proteins showing distinct amide-exchange patterns, remains unknown. The sensitivity of the predictions when MD simulations are conducted with different force-fields is yet to tested and quantified. Using MD simulations and experimental HDX data on three homologous signaling proteins, we report detailed studies quantifying the performance of seven previously reported models (M1-M7) of two general types: empirical and fractional-population models. We find that the empirical models show inconsistent predictions but predictions of the fractional population models are robust. Contrary to previously reported work, we find that the solvent-accessible surface area of amide hydrogens is a useful metric when combined with a new metric defining the distances of amide hydrogens from the first polar atoms in proteins. On the basis of this, we report two new models, one empirical (M8) and one population-based (M9). We find strong protection of amide hydrogens from solvent exchange both within the stable helical motifs and also in the interhelical loops. We further observe that the exchange-competent states of amide hydrogens occur on the sub 100 ps time-scale via localized fluctuations, and such states among amides of a given protein do not appear to show any cooperativity or allosteric coupling.

Differential Protein Dynamics of Regulators of G-Protein Signaling: Role in Specificity of Small-Molecule Inhibitors.

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.

Insulin mimetic peptide S371 folds into a helical structure.

Insulin plays a crucial physiological role in glucose control by initiating a number of signaling events on binding and activating its cell surface receptor. Insulin mimics have, therefore, become promising agents for treating diabetes and to probe the mechanism of interaction of insulin with its receptor. Specifically, many insulin-mimetic peptide sequences have been discovered and found to selectively function as agonists and antagonists, but their structures and the mechanistic details of their interactions with the receptor remain challenging to characterize. In this work, we have studied the folding properties and structure of a Site 1 insulin mimetic peptide S371 that has sequence similarities with the insulin B-chain as well as with a critical hormone-binding element of the receptor known as the C-terminal (CT) peptide. We first validated our simulation approaches by predicting the known solution structure of the insulin B-chain helix and then applied them to study the folding of the mimetic peptide S371. Our data predict a helical fold for the first 16 residues of S371 that has a resemblance to the helical motifs in the insulin B-chain and CT. We also propose receptor-bound models of S371 that provide mechanistic explanations for competing binding properties of S371 and CT to the Site 1 of IR. © 2017 Wiley Periodicals, Inc.

All-Atom Structural Models of the Transmembrane Domains of Insulin and Type 1 Insulin-Like Growth Factor Receptors.

The receptor tyrosine kinase superfamily comprises many cell-surface receptors including the insulin receptor (IR) and type 1 insulin-like growth factor receptor (IGF1R) that are constitutively homodimeric transmembrane glycoproteins. Therefore, these receptors require ligand-triggered domain rearrangements rather than receptor dimerization for activation. Specifically, binding of peptide ligands to receptor ectodomains transduces signals across the transmembrane domains for trans-autophosphorylation in cytoplasmic kinase domains. The molecular details of these processes are poorly understood in part due to the absence of structures of full-length receptors. Using MD simulations and enhanced conformational sampling algorithms, we present all-atom structural models of peptides containing 51 residues from the transmembrane and juxtamembrane regions of IR and IGF1R. In our models, the transmembrane regions of both receptors adopt helical conformations with kinks at Pro961 (IR) and Pro941 (IGF1R), but the C-terminal residues corresponding to the juxtamembrane region of each receptor adopt unfolded and flexible conformations in IR as opposed to a helix in IGF1R. We also observe that the N-terminal residues in IR form a kinked-helix sitting at the membrane-solvent interface, while homologous residues in IGF1R are unfolded and flexible. These conformational differences result in a larger tilt-angle of the membrane-embedded helix in IGF1R in comparison to IR to compensate for interactions with water molecules at the membrane-solvent interfaces. Our metastable/stable states for the transmembrane domain of IR, observed in a lipid bilayer, are consistent with a known NMR structure of this domain determined in detergent micelles, and similar states in IGF1R are consistent with a previously reported model of the dimerized transmembrane domains of IGF1R. Our all-atom structural models suggest potentially unique structural organization of kinase domains in each receptor.