Designing surface exposed sites on Bacillus subtilis lipase A for spin-labeling and hydration studies.

Spin-labeling with electron paramagnetic resonance spectroscopy (EPR) is a facile method for interrogating macromolecular flexibility, conformational changes, accessibility, and hydration. Within we present a computationally based approach for the rational selection of reporter sites in Bacillus subtilis lipase A (BSLA) for substitution to cysteine residues with subsequent modification with a spin-label that are expected to not significantly perturb the wild-type structure, dynamics, or enzymatic function. Experimental circular dichroism spectroscopy, Michaelis-Menten kinetic parameters and EPR spectroscopy data validate the success of this approach to computationally select reporter sites for future magnetic resonance investigations of hydration and hydration changes induced by polymer conjugation, tethering, immobilization, or amino acid substitution in BSLA. Analysis of molecular dynamic simulations of the impact of substitutions on the secondary structure agree well with experimental findings. We propose that this computationally guided approach for choosing spin-labeled EPR reporter sites, which evaluates relative surface accessibility coupled with hydrogen bonding occupancy of amino acids to the catalytic pocket via atomistic simulations, should be readily transferable to other macromolecular systems of interest including selecting sites for paramagnetic relaxation enhancement NMR studies, other spin-labeling EPR studies or any method requiring a tagging method where it is desirable to not alter enzyme stability or activity.

Two-Dimensional Energy Histograms as Features for Machine Learning to Predict Adsorption in Diverse Nanoporous Materials.

A major obstacle for machine learning (ML) in chemical science is the lack of physically informed feature representations that provide both accurate prediction and easy interpretability of the ML model. In this work, we describe adsorption systems using novel two-dimensional energy histogram (2D-EH) features, which are obtained from the probe-adsorbent energies and energy gradients at grid points located throughout the adsorbent. The 2D-EH features encode both energetic and structural information of the material and lead to highly accurate ML models (coefficient of determination R2 ∼ 0.94-0.99) for predicting single-component adsorption capacity in metal-organic frameworks (MOFs). We consider the adsorption of spherical molecules (Kr and Xe), linear alkanes with a wide range of aspect ratios (ethane, propane, n-butane, and n-hexane), and a branched alkane (2,2-dimethylbutane) over a wide range of temperatures and pressures. The interpretable 2D-EH features enable the ML model to learn the basic physics of adsorption in pores from the training data. We show that these MOF-data-trained ML models are transferrable to different families of amorphous nanoporous materials. We also identify several adsorption systems where capillary condensation occurs, and ML predictions are more challenging. Nevertheless, our 2D-EH features still outperform structural features including those derived from persistent homology. The novel 2D-EH features may help accelerate the discovery and design of advanced nanoporous materials using ML for gas storage and separation in the future.

Temperature Effects in Flexible Adsorption Processes for Amorphous Microporous Polymers.

A collection of atomistic molecular simulations is reported that illustrate the impact of adsorption temperature on species uptake and adsorbate-induced structural rearrangement for amorphous polymers of intrinsic microporosity. Temperature-sensitive structural rearrangement is evaluated by contrasting two methods: standard grand canonical Monte Carlo simulations using a rigid framework approximation and a combined Monte Carlo/molecular dynamics approach that fully incorporates framework flexibility. We report single-component gas phase adsorption isotherms for CH4, C2H4, C2H6, C3H6, C3H8, and CO2 across a temperature range of 250-400 K for models of an archetypal polymer of intrinsic microporosity, PIM-1. A quadratic model is presented that captures two main mechanisms of temperature-dependent adsorption-induced deformation of PIM-1 up to a relative swelling of 1.15: thermal expansion and an increased propensity to swell as a function of species uptake. Two case studies are reported that highlight the critical role of operating temperature in industrial storage and separation applications. The first study focuses on methane storage and delivery applications using a pressure-temperature swing adsorption application (PTSA). We demonstrate that larger working capacities are accompanied by increased volumetric strain between adsorption-desorption steps. The second case study considers PIM-1 as an adsorbent to separate an exemplar ternary syngas mixture at operating temperatures ranging 300-550 K. A temperature threshold of ∼400 K is identified, beyond which adsorption-induced PIM-1 swelling is negligible and the solubility selectivity-loading curve transitions to exhibiting a nearly linear relationship.

PEGDA hydrogel structure from semi-dilute concentrations: insights from experiments and molecular simulations.

The efficacy of hydrogel materials used in biomedical applications is dependent on polymer network topology and the structure of water-laden pore space. Hydrogel microstructure can be tuned by adjusting synthesis parameters such as macromer molar mass and concentration. Moreover, hydrogels beyond dilute conditions are needed to produce mechanically robust and dense networks for tissue engineering and/or drug delivery systems. Thus, this study utilizes a combined experimental and molecular simulation approach to characterize structural features for 4.8 and 10 kDa poly (ethylene glycol) diacrylate (PEGDA) hydrogels formed from a range of semi-dilute solution concentrations. The connection between chain-chain interactions in polymer solutions, hydrogel structure, and equilibrium swelling behavior is presented. Bulk rheology analysis revealed an entanglement concentration for PEGDA pre-gel solutions around 28 wt% for both macromers studied. A similar transition in swelling behavior was revealed around the same concentration where hydrogel capacity to retain water was drastically reduced. To understand this transition, the hydrogel structure was characterized using the swollen polymer network hypothesis and compared to pore size distributions from molecular dynamics simulations. We find in both approaches a structural transition concentration at the hydrogel swelling inflection point that is comparable to the entanglement concentration. Calculated mesh sizes from theory are compared with computationally determined average maximum pore diameters; mesh sizes from theory yielded greater feature sizes across all concentrations considered. Molecular simulations are further used to assess pore dynamics, which are shown to vary in distribution shape and number of modes compared to the time-averaged hydrogel pore features. Altogether, this work provides insights into hydrogel network features and their dynamic behavior at physiological conditions (37 °C) as a basis for hydrogel design beyond dilute conditions for biomedical applications.

Incorporating Flexibility Effects into Metal-Organic Framework Adsorption Simulations Using Different Models.

High-throughput calculations based on molecular simulations to predict the adsorption of molecules inside metal-organic frameworks (MOFs) have become a useful complement to experimental efforts to identify promising adsorbents for chemical separations and storage. For computational convenience, all existing efforts of this kind have relied on simulations in which the MOF is approximated as rigid. In this paper, we use extensive adsorption-relaxation simulations that fully include MOF flexibility effects to explore the validity of the rigid framework approximation. We also examine the accuracy of several approximate methods to incorporate framework flexibility that are more computationally efficient than adsorption-relaxation calculations. We first benchmark various models of MOF flexibility for four MOFs with well-established CO2 experimental consensus isotherms. We then consider a range of adsorption properties, including Henry's constants, nondilute loadings, and adsorption selectivity, for seven adsorbates in 15 MOFs randomly selected from the CoRE MOF database. Our results indicate that in many MOFs adsorption-relaxation simulations are necessary to make quantitative predictions of adsorption, particularly for adsorption at dilute concentrations, although more standard calculations based on rigid structures can provide useful information. Finally, we investigate whether a correlation exists between the elastic properties of empty MOFs and the importance of including framework flexibility in making accurate predictions of molecular adsorption. Our results did not identify a simple correlation of this type.

Fingerprinting diverse nanoporous materials for optimal hydrogen storage conditions using meta-learning.

Adsorptive hydrogen storage is a desirable technology for fuel cell vehicles, and efficiently identifying the optimal storage temperature requires modeling hydrogen loading as a continuous function of pressure and temperature. Using data obtained from high-throughput Monte Carlo simulations for zeolites, metal-organic frameworks, and hyper-cross-linked polymers, we develop a meta-learning model that jointly predicts the adsorption loading for multiple materials over wide ranges of pressure and temperature. Meta-learning gives higher accuracy and improved generalization compared to fitting a model separately to each material and allows us to identify the optimal hydrogen storage temperature with the highest working capacity for a given pressure difference. Materials with high optimal temperatures are found in close proximity in the fingerprint space and exhibit high isosteric heats of adsorption. Our method and results provide new guidelines toward the design of hydrogen storage materials and a new route to incorporate machine learning into high-throughput materials discovery.

Molecular Dynamics-Guided Design of a Functional Protein-ATRP Conjugate That Eliminates Protein-Protein Interactions.

Even the most advanced protein-polymer conjugate therapeutics do not eliminate antibody-protein and receptor-protein recognition. Next-generation bioconjugate drugs will need to replace stochastic selection with rational design to select desirable levels of protein-protein interaction while retaining function. The "Holy Grail" for rational design would be to generate functional enzymes that are fully catalytic with small molecule substrates while eliminating interaction between the protein surface and larger molecules. Using chymotrypsin, an important enzyme that is used to treat pancreatic insufficiency, we have designed a series of molecular chimeras with varied grafting densities and shapes. Guided by molecular dynamic simulations and next-generation molecular chimera characterization with asymmetric flow field-flow fractionation chromatography, we grew linear, branched, and comb-shaped architectures from the surface of the protein by atom-transfer radical polymerization. Comb-shaped polymers, grafted from the surface of chymotrypsin, completely prevented enzyme inhibition with protein inhibitors without sacrificing the ability of the enzyme to catalyze the hydrolysis of a peptide substrate. Asymmetric flow field-flow fractionation coupled with multiangle laser light scattering including dynamic light scattering showed that nanoarmor designed with comb-shaped polymers was particularly compact and spherical. The polymer structure significantly increased protein stability and reduced protein-protein interactions. Atomistic molecular dynamic simulations predicted that a dense nanoarmor with long-armed comb-shaped polymer would act as an almost perfect molecular sieve to filter large ligands from substrates. Surprisingly, a conjugate that was composed of 99% polymer was needed before the elimination of protein-protein interactions.

Atomistic insight towards the impact of polymer architecture and grafting density on structure-dynamics of PEGylated bovine serum albumin and their applications.

Macromolecules such as proteins conjugated to polyethylene glycol (PEG) have been employed in therapeutic drug applications, and recent research has emphasized the potential of varying polymer architectures and conjugation strategies to achieve improved efficacy. In this study, we performed atomistic molecular dynamics simulations of bovine serum albumin (BSA) conjugated to 5 kDa PEG polymers in an array of schemes, including varied numbers of attached chains, grafting density, and nonlinear architectures. Nonlinear architectures included U-shaped PEG, Y-shaped PEG, and poly(oligoethylene glycol methacrylate) (POEGMA). Buried surface area calculations and polymer volume map analyses revealed that volume exclusion behaviors of the high grafting density conjugate promoted additional protein-polymer interactions when compared to simply increasing numbers of conjugated chains uniformly across the protein surface. Investigation of nonlinear polymer architectures showed that stable polymer-lysine loop-like conformations seen in previous conjugate designs were more variable in prevalence, especially in POEGMA, which contained short oligomer PEG chains. The findings of this comprehensive study of alternate PEGylation schemes of BSA provide critical insight into molecular patterns of interaction within bioconjugates and highlight their importance in the future of controlled modification of conjugate system parameters.

Structure-function-dynamics of α-chymotrypsin based conjugates as a function of polymer charge.

The field of protein-polymer conjugates has suffered from a lack of predictive tools and design guidelines to synthesize highly active and stable conjugates. In order to develop this type of information, structure-function-dynamics relationships must be understood. These relationships depend strongly on protein-polymer interactions and how these influence protein dynamics and conformations. Probing nanoscale interactions is experimentally difficult, but computational tools, such as molecular dynamics simulations, can easily obtain atomic resolution. Atomistic molecular dynamics simulations were used to study α-chymotrypsin (CT) densely conjugated with either zwitterionic, positively charged, or negatively charged polymers. Charged polymers interacted with the protein surface to varying degrees and in different regions of the polymer, depending on their flexibilities. Specific interactions of the negatively charged polymer with CT caused structural deformations in CT's substrate binding pocket and active site while no deformations were observed for zwitterionic and positively charged polymers. Attachment of polymers displaced water molecules from CT's surface into the polymer phase and polymer hydration correlated with the Hofmeister series.

PEGylation within a confined hydrophobic cavity of a protein.

The conjugation of polyethylene glycol (PEG) to proteins, known as PEGylation, has increasingly been employed to expand the efficacy of therapeutic drugs. Recently, research has emphasized the effect of the conjugation site on protein-polymer interactions. In this study, we performed atomistic molecular dynamics (MD) simulations of lysine 116 PEGylated bovine serum albumin (BSA) to illustrate how conjugation near a hydrophobic pocket affects the conjugate's dynamics and observed altered low mode vibrations in the protein. MD simulations were performed for a total of 1.5 µs for each PEG chain molecular mass from 2 to 20 kDa. Analysis of preferential PEG-BSA interactions showed that polymer behavior was also affected as proximity to the attractive protein surface patches promoted interactions in small (2 kDa) PEG chains, while the confined environment of the conjugation site reduced the expected BSA surface coverage when the polymer molecular mass increased to 10 kDa. This thorough analysis of PEG-BSA interactions and polymer dynamics increases the molecular understanding of site-specific PEGylation and enhances the use of protein-polymer conjugates as therapeutics.

Transforming protein-polymer conjugate purification by tuning protein solubility.

Almost all commercial proteins are purified using ammonium sulfate precipitation. Protein-polymer conjugates are synthesized from pure starting materials, and the struggle to separate conjugates from polymer, native protein, and from isomers has vexed scientists for decades. We have discovered that covalent polymer attachment has a transformational effect on protein solubility in salt solutions. Here, protein-polymer conjugates with a variety of polymers, grafting densities, and polymer lengths are generated using atom transfer radical polymerization. Charged polymers increase conjugate solubility in ammonium sulfate and completely prevent precipitation even at 100% saturation. Atomistic molecular dynamic simulations show the impact is driven by an anti-polyelectrolyte effect from zwitterionic polymers. Uncharged polymers exhibit polymer length-dependent decreased solubility. The differences in salting-out are then used to simply purify mixtures of conjugates and native proteins into single species. Increasing protein solubility in salt solutions through polymer conjugation could lead to many new applications of protein-polymer conjugates.

Molecular Modeling of Complex Cross-Linked Networks of PEGDA Nanogels.

Poly(ethylene glycol) (PEG)-based nanogels are attractive for biomedical applications due to their biocompatibility, versatile end group chemistry, and ability to sterically shield encapsulated drug molecules. The characteristics of a hydrogel network govern the encapsulation and efficient delivery of drug molecules for a target application. A molecular-level description of network topology can complement experimental investigations to understand its effects on the structural properties of these nanogels. In this work, atomistic molecular simulations of heterogeneous, nonideal PEG-diacrylate (PEGDA) nanogels are presented. The effects of cross-linking density and topological features on the structural properties of PEGDA nanogels were studied. The average functionality was controlled to systematically study the effect of cross-linking density on the radius of gyration, shape, and mesh size of the nanogels. For a given average functionality, the impact of distinct network topologies on the structural properties was also studied. The aspect ratios, based on the gyration tensor, were calculated to characterize the shapes of these nanogels for different topologies. Nanogel structures with higher cross-linking densities showed a globular shape, while structures with lower cross-linking density showed shape anisotropy. The distribution and connectivity of the cross-linked junctions played a key role in determining the size and shape anisotropy of PEGDA nanogels; the number of unreacted chain ends and their connectivity directly affected the anisotropy. The mesh size, denoted by the limiting "free volume element" present in the nanogel samples, does not show a significant change with increasing average functionality. This work provides insight into the structural properties of heterogeneous hydrogels that aid the design of nonideal nanogel networks for a targeted drug delivery application.

Molecular Insight into the Protein?Polymer Interactions in N-Terminal PEGylated Bovine Serum Albumin.

Therapeutic proteins have increasingly been used in modern medical applications, but their effectiveness is limited by factors such as stability and blood circulation time. Recently, there has been significant research into covalently linking polyethylene glycol polymer chains (PEG) to proteins, known as PEGylation, to mitigate these issues. In this work, an atomistic molecular dynamics study of N-terminal conjugated PEG-BSA (bovine serum albumin) was conducted with varying PEG molecular weights (2, 5, 10, and 20 kDa) to probe PEG-BSA interactions and evaluate the effect of polymer length on dynamics. It was found that the affinity of PEG toward the protein surface increased as a function of PEG molecular weight and that a certain weight (around 10 kDa) was required to promote protein?polymer interactions. Additionally, preferential interactions were monitored through formed contacts and hotspots were identified. PEG chains coordinating in looplike conformations were found near lysine residues. Also, it was found that hydrophobic interactions played an important role in promoting PEG-BSA interactions as the PEG molecular weight increased. The results provide insight into underlying mechanisms behind transitions in PEG conformations and will aid in future design of effective PEGylated drug molecules.

Intramolecular Interactions of Conjugated Polymers Mimic Molecular Chaperones to Stabilize Protein-Polymer Conjugates.

The power and elegance of protein-polymer conjugates has solved many vexing problems for society. Rational design of these complex covalent hybrids depends on a deep understanding of how polymer physicochemical properties impact the conjugate structure-function-dynamic relationships. We have generated a large family of chymotrypsin-polymer conjugates which differ in polymer length and charge, using grafting-from atom-transfer radical polymerization, to elucidate how the polymers influenced enzyme structure and function at pHs that would unfold and inactivate the enzyme. We also used molecular dynamics simulations to deepen our understanding of protein-polymer intramolecular interactions. Remarkably, the data revealed that, contrary to current thoughts on how polymers stabilize proteins, appropriately designed polymers actually stabilize partially unfolded intermediates and assist in refolding to an active conformation. Long, hydrophilic polymers minimized interfacial interactions in partially unfolded conjugates leading to increased stabilization. The design of covalently attached intramolecular biomimetic chaperones that drive protein refolding could have far reaching consequences.

Optimizing Protein-Polymer Interactions in a Poly(ethylene glycol) Coarse-Grained Model.

Increasing demand for hybrid materials that merge the synthetic and biological areas in drug industries requires in-depth knowledge of the individual components and their contributions to these complexes. Coarse-grained (CG) models developed for proteins and polymers exist, yet there is a lack of understanding of the cross interactions when these two groups of materials integrate to build a complex. In this work, we characterized the nonbonded interactions between poly(ethylene glycol) (PEG) and amino acids in a Martini CG model utilizing state-of-the-art quantum mechanics calculations of interaction energies. The parameter set proposed, was validated by assessing the polymer density in the vicinity of individual amino acids obtained from available all-atomistic molecular dynamic simulations of plasma proteins. Our results revealed the necessity of protein-polymer interaction parameterization at the CG level to avoid overestimation of polymer association when employing other PEG models within the Martini framework.

Modeling Amorphous Microporous Polymers for CO2 Capture and Separations.

This review concentrates on the advances of atomistic molecular simulations to design and evaluate amorphous microporous polymeric materials for CO2 capture and separations. A description of atomistic molecular simulations is provided, including simulation techniques, structural generation approaches, relaxation and equilibration methodologies, and considerations needed for validation of simulated samples. The review provides general guidelines and a comprehensive update of the recent literature (since 2007) to promote the acceleration of the discovery and screening of amorphous microporous polymers for CO2 capture and separation processes.

Ionic-Functionalized Polymers of Intrinsic Microporosity for Gas Separation Applications.

Ionic-functionalized microporous materials are attractive for energy-efficient gas adsorption and separation processes and have shown promising results in gas mixtures at pressure ranges and compositions that are relevant for industrial applications. In this work, we studied the influence of different counterions (Li+, Na+, K+, Rb+, and Mg2+) on the porosity, carbon dioxide (CO2) gas adsorption, and selectivity in ionic-functionalized PIM-1 (IonomIMs), a polymer belonging to the class of linear and amorphous microporous polymers known as polymers of intrinsic microporosity (PIMs). It was found that an increase in the concentration of ionic groups led to a decrease in the free volume, resulting in a less porous polymer framework, and Mg2+-functionalized IonomIMs exhibited a relatively larger porosity compared to other IonomIMs. The CO2 adsorption capacity was affected by the different counterions for IonomIM-1, and a higher loading capacity for pure CO2 was observed for Mg2+. Furthermore, the IonomIMs showed an enhanced CO2 selectivity in CO2/CH4 and CO2/N2 gas mixtures at conditions used in pressure swing adsorption and vacuum swing adsorption applications. It was also observed that the concentration of ionic groups plays a vital role in changing the CO2 gas adsorption and selectivity.

Unraveling Binding Interactions between Human RANKL and Its Decoy Receptor Osteoprotegerin.

Recent studies have revealed the importance and the active contribution of the RANKL/OPG/RANK pathway in many bone diseases including different forms of common osteoporosis. In this study, we present an extensive atomistic molecular dynamic study of the OPG/RANKL system. Within the molecular models, we varied the number of OPG molecules bound to the RANKL trimer and carried out a study to determine how the binding affinity of the OPG/RANKL system changes as a function of OPG concentration. The molecular mechanics Poisson-Boltzmann surface area method was used to analyze binding free energies. It is shown that the binding affinity decreases with increasing numbers of OPG molecules. Additionally, conformational changes of RANKL, interactions between the N-terminus outlier module of OPG with RANKL, and residues that play an important role in the binding of OPG to RANKL trimer were investigated. A probable cause for unfavorable binding for a third OPG molecule was found. Along with the currently available experimental studies, this computational study will be valuable for the comprehensive understanding of OPG/RANKL at the atomistic level.

Polymer ultrapermeability from the inefficient packing of 2D chains.

The promise of ultrapermeable polymers, such as poly(trimethylsilylpropyne) (PTMSP), for reducing the size and increasing the efficiency of membranes for gas separations remains unfulfilled due to their poor selectivity. We report an ultrapermeable polymer of intrinsic microporosity (PIM-TMN-Trip) that is substantially more selective than PTMSP. From molecular simulations and experimental measurement we find that the inefficient packing of the two-dimensional (2D) chains of PIM-TMN-Trip generates a high concentration of both small (<0.7 nm) and large (0.7-1.0 nm) micropores, the former enhancing selectivity and the latter permeability. Gas permeability data for PIM-TMN-Trip surpass the 2008 Robeson upper bounds for O2/N2, H2/N2, CO2/N2, H2/CH4 and CO2/CH4, with the potential for biogas purification and carbon capture demonstrated for relevant gas mixtures. Comparisons between PIM-TMN-Trip and structurally similar polymers with three-dimensional (3D) contorted chains confirm that its additional intrinsic microporosity is generated from the awkward packing of its 2D polymer chains in a 3D amorphous solid. This strategy of shape-directed packing of chains of microporous polymers may be applied to other rigid polymers for gas separations.

NLDFT Pore Size Distribution in Amorphous Microporous Materials.

The pore size distribution (PSD) is one of the most important properties when characterizing and designing materials for gas storage and separation applications. Experimentally, one of the current standards for determining microscopic PSD is using indirect molecular adsorption methods such as nonlocal density functional theory (NLDFT) and N2 isotherms at 77 K. Because determining the PSD from NLDFT is an indirect method, the validation can be a nontrivial task for amorphous microporous materials. This is especially crucial since this method is known to produce artifacts. In this work, the accuracy of NLDFT PSD was compared against the exact geometric PSD for 11 different simulated amorphous microporous materials. The geometric surface area and micropore volumes of these materials were between 5 and 1698 m2/g and 0.039 and 0.55 cm3/g, respectively. N2 isotherms at 77 K were constructed using Gibbs ensemble Monte Carlo (GEMC) simulations. Our results show that the discrepancies between NLDFT and geometric PSD are significant. NLDFT PSD produced several artificial gaps and peaks that were further confirmed by the coordinates of inserted particles of a specific size. We found that dominant peaks from NLDFT typically reported in the literature do not necessarily represent the truly dominant pore size within the system. The confirmation provides concrete evidence for artifacts that arise from the NLDFT method. Furthermore, a sensitivity analysis was performed to show the high dependency of PSD as a function of the regularization parameter, λ. A higher value of λ produced a broader and smoother PSD that closely resembles geometric PSD. As an alternative, a new criterion for choosing λ, called here the smooth-shift method (SSNLDFT), is proposed that tuned the NLDFT PSD to better match the true geometric PSD. Using the geometric pore size distribution as our reference, the smooth-shift method reduced the root-mean-square deviation by ∼70% when the geometric surface area of the material is greater than 100 m2/g.