Advances in Computational Approaches for Estimating Passive Permeability in Drug Discovery.

Passive permeation of cellular membranes is a key feature of many therapeutics. The relevance of passive permeability spans all biological systems as they all employ biomembranes for compartmentalization. A variety of computational techniques are currently utilized and under active development to facilitate the characterization of passive permeability. These methods include lipophilicity relations, molecular dynamics simulations, and machine learning, which vary in accuracy, complexity, and computational cost. This review briefly introduces the underlying theories, such as the prominent inhomogeneous solubility diffusion model, and covers a number of recent applications. Various machine-learning applications, which have demonstrated good potential for high-volume, data-driven permeability predictions, are also discussed. Due to the confluence of novel computational methods and next-generation exascale computers, we anticipate an exciting future for computationally driven permeability predictions.

Determining structure and action mechanism of LBF14 by molecular simulation.

The recently discovered, membrane-active peptide LBF14 contains several non-proteinogenic amino acids and is able to transform vesicles into tubule networks. The exact membrane interaction mechanism and detailed secondary structure are yet to be determined. We performed molecular dynamics simulations of LBF14 and let it fold de novo into its ensemble of native secondary structures. Histidine protonation state effects on secondary structure were investigated. An MD simulation of the peptide with a lipid bilayer was performed. Simulation results were compared to circular dichroism and electron paramagnetic resonance data of previous studies. LBF14 contains a conserved helical section in an otherwise random structure. Helical stability is influenced by histidine protonation. The peptide localized to the polar layer of the membrane, consistent with experimental results. While the overall secondary structure is unaffected by membrane interaction, Ramachandran plot analysis yielded two distinct peptide conformations during membrane interaction. This conformational change was accompanied by residue repositioning within the membrane. LBF14 only affected the local order in the membrane, and had no measurable effect on pressure. The simulation results are consistent with the previously proposed membrane interaction mechanism of LBF14 and can additionally explain the local interaction mechanism. Communicated by Ramaswamy H. Sarma.

CycFlowDec: A Python module for decomposing flow networks using simple cycles.

New algorithms for determining the expected flow through simple cycles in a closed network are presented. Current network analysis software do not implement algorithms for expected cyclic flow decomposition, despite its potential value. Decomposing networks into expected cycle flows provides a quantitative characterization of network cycles that can be further analyzed for sensitivity and correlative behavior. An efficient, general algorithm has been coded into CycFlowDec, an open source Python module available at https://github.com/austenb28/CycFlowDec.

Toward a Multipathway Perspective: pH-Dependent Kinetic Selection of Competing Pathways and the Role of the Internal Glutamate in Cl-/H+ Antiporters.

Canonical descriptions of multistep biomolecular transformations generally follow a single-pathway viewpoint, with a series of transitions through intermediates converting reactants to products or repeating a conformational cycle. However, mounting evidence suggests that more complexity and pathway heterogeneity are mechanistically relevant due to the statistical distribution of multiple interconnected rate processes. Making sense of such pathway complexity remains a significant challenge. To better understand the role and relevance of pathway heterogeneity, we herein probe the chemical reaction network of a Cl-/H+ antiporter, ClC-ec1, and analyze reaction pathways using multiscale kinetic modeling (MKM). This approach allows us to describe the nature of the competing pathways and how they change as a function of pH. We reveal that although pH-dependent Cl-/H+ transport rates are largely regulated by the charge state of amino acid E148, the charge state of E203 determines relative contributions from coexisting pathways and can shift the flux pH-dependence. The selection of pathways via E203 explains how ionizable mutations (D/H/K/R) would impact the ClC-ec1 bioactivity from a kinetic perspective and lends further support to the indispensability of an internal glutamate in ClC antiporters. Our results demonstrate how quantifying the kinetic selection of competing pathways under varying conditions leads to a deeper understanding of the Cl-/H+ exchange mechanism and can suggest new approaches for mechanistic control.

Development and simulation of fully glycosylated molecular models of ACE2-Fc fusion proteins and their interaction with the SARS-CoV-2 spike protein binding domain.

We develop fully glycosylated computational models of ACE2-Fc fusion proteins which are promising targets for a COVID-19 therapeutic. These models are tested in their interaction with a fragment of the receptor-binding domain (RBD) of the Spike Protein S of the SARS-CoV-2 virus, via atomistic molecular dynamics simulations. We see that some ACE2 glycans interact with the S fragments, and glycans are influencing the conformation of the ACE2 receptor. Additionally, we optimize algorithms for protein glycosylation modelling in order to expedite future model development. All models and algorithms are openly available.

Confining Liquids inside Carbon Nanotubes: Accelerated Molecular Dynamics with Spliced, Soft-Core Potentials and Simulated Annealing.

Understanding emergent phenomena of fluids under physical confinement requires the development of advanced tools for rapid and accurate simulation of their physiochemical properties. Simulating liquid molecules commensurate in size with the nanoscale enclosures that confine them is a key challenge. We demonstrate an accelerated molecular dynamics simulation technique that combines soft-core potentials (SCP) and simulated annealing (SA) to analyze confined liquids. This integrated SCP/SA method relies on a new spliced soft-core potential (SSCP), which enables tunable accuracy with respect to the target hard-core potential (HCP). SCP/SA enables the packing of enclosures with bulk material in a controlled, thermodynamically consistent manner. The enhanced SSCP accuracy is a critical feature of SCP/SA, enabling a smooth transition between the SCP and the HCP at a desired SCP hardness. We applied SCP/SA to the problem of filling a carbon nanotube (CNT) in periodic boundary conditions with a popular ionic liquid (IL), 1-butyl-3-methylimidazolium hexafluorophosphate [BMIM+][PF6-]. We performed a series of triplicate simulations on systems with varying CNT diameter and charge to demonstrate SCP/SA's versatility. Beyond this IL/CNT system, the SCP/SA simulation framework has a broad range of potential applications, not limited to nanoscale enclosures and interfaces, including both solid-state and biological systems.

Effects of N-Glycosylation on the Structure, Function, and Stability of a Plant-Made Fc-Fusion Anthrax Decoy Protein.

Protein N-glycosylation is an important post-translational modification and has influences on a variety of biological processes at the cellular and molecular level, making glycosylation a major study aspect for glycoprotein-based therapeutics. To achieve a comprehensive understanding on how N-glycosylation impacts protein properties, an Fc-fusion anthrax decoy protein, viz rCMG2-Fc, was expressed in Nicotiana benthamiana plant with three types of N-glycosylation profiles. Three variants were produced by targeting protein to plant apoplast (APO), endoplasmic reticulum (ER) or removing the N-glycosylation site by a point mutation (Agly). Both the APO and ER variants had a complex-type N-glycan (GnGnXF) as their predominant glycans. In addition, ER variant had a higher concentration of mannose-type N-glycans (50%). The decoy protein binds to the protective antigen (PA) of anthrax through its CMG2 domain and inhibits toxin endocytosis. The protein expression, sequence, N-glycosylation profile, binding kinetics to PA, toxin neutralization efficiency, and thermostability were determined experimentally. In parallel, we performed molecular dynamics (MD) simulations of the predominant full-length rCMG2-Fc glycoform for each of the three N-glycosylation profiles to understand the effects of glycosylation at the molecular level. The MAN8 glycoform from the ER variant was additionally simulated to resolve differences between the APO and ER variants. Glycosylation showed strong stabilizing effects on rCMG2-Fc during in planta accumulation, evidenced by the over 2-fold higher expression and less protein degradation observed for glycosylated variants compared to the Agly variant. Protein function was confirmed by toxin neutralization assay (TNA), with effective concentration (EC50) rankings from low to high of 67.6 ng/ml (APO), 83.15 ng/ml (Agly), and 128.9 ng/ml (ER). The binding kinetics between rCMG2-Fc and PA were measured with bio-layer interferometry (BLI), giving sub-nanomolar affinities regardless of protein glycosylation and temperatures (25 and 37°C). The protein thermostability was examined utilizing the PA binding ELISA to provide information on EC50 differences. The fraction of functional ER variant decayed after overnight incubation at 37°C, and no significant change was observed for APO or Agly variants. In MD simulations, the MAN8 glycoform exhibits quantitatively higher distance between the CMG2 and Fc domains, as well as higher hydrophobic solvent accessible surface areas (SASA), indicating a possibly higher aggregation tendency of the ER variant. This study highlights the impacts of N-glycosylation on protein properties and provides insight into the effects of glycosylation on protein molecular dynamics.

Structural analysis of human glycoprotein butyrylcholinesterase using atomistic molecular dynamics: The importance of glycosylation site ASN241.

Human butyrylcholinesterase (BChE) is a glycoprotein capable of bioscavenging toxic compounds such as organophosphorus (OP) nerve agents. For commercial production of BChE, it is practical to synthesize BChE in non-human expression systems, such as plants or animals. However, the glycosylation profile in these systems is significantly different from the human glycosylation profile, which could result in changes in BChE's structure and function. From our investigation, we found that the glycan attached to ASN241 is both structurally and functionally important due to its close proximity to the BChE tetramerization domain and the active site gorge. To investigate the effects of populating glycosylation site ASN241, monomeric human BChE glycoforms were simulated with and without site ASN241 glycosylated. Our simulations indicate that the structure and function of human BChE are significantly affected by the absence of glycan 241.