Biomolecular Surface Research Articles

Pseudo‐time‐coupled nonlinear models for biomolecular surface representation and solvation analysis

SUMMARYThis paper presents an improved mathematical model for biomolecular surface representation and solvation analysis. Based on the Eulerian formulation, the polar and nonpolar contributions to the solvation process can be equally accounted for via a unified free energy functional. Using the variational analysis, two nonlinear partial differential equations, that is, one Poisson–Boltzmann (PB) type equation for electrostatic potential and one geometric flow type equation defining the solute–solvent interface, can be derived. To achieve a more efficient and stable coupling, we propose a time‐dependent PB equation by introducing a pseudo‐time. The system of nonlinear partial differential equations can then be coupled via the standard time integration. Furthermore, the numerical treatment of nonlinear terms becomes easier in the present model. Based on a hypersurface function, the biomolecular surface is represented as a smooth interface. However, for the nonlinear PB equation, such a smooth interface may cause unphysical blowup because of the existence of nonvanishing values within the solute domain. A filtering process is proposed to circumvent this problem. Example solvation analysis of various compounds and proteins was carried out to validate the proposed model. The contributions of electrostatic interactions to the protein–protein binding affinity are studied for selected protein complexes. Copyright © 2011 John Wiley & Sons, Ltd.

On the Role of Flexibility in Protein-Ligand Interactions: the Example of p53 Tetramerization Domain

The recognition of protein surfaces by designed ligands has become an attractive approach in drug discovery. However, the variable nature and irregular behavior of protein surfaces defy this new area of research. The easy to understand "lock-and-key" model is far from being the ideal paradigm in biomolecular interactions and, hence, any new finding on how proteins and ligands behave in recognition events paves a step of the way. Herein, we illustrate a clear example on how an increase in flexibility of both protein and ligand can result in an increase in the stability of the macromolecular complex. The biophysical study of the interaction between a designed flexible tetraguanidinium-calix[4]arene and the tetramerization domain of protein p53 (p53TD) and its natural mutant p53TD-R337H shows how the floppy mutant domain interacts more tightly with the ligand than the well-packed wild-type protein. Moreover, the flexible calixarene ligand interacts with higher affinity to both wild-type and mutated protein domains than a conformationally rigid calixarene analog previously reported. These findings underscore the crucial role of flexibility in molecular recognition processes, for both small ligands and large biomolecular surfaces.

A statistical nanomechanism of biomolecular patterning actuated by surface potential

Biomolecular patterning on a nanoscale/microscale on chip surfaces is one of the most important techniques used in vitro biochip technologies. Here, we report upon a stochastic mechanics model we have developed for biomolecular patterning controlled by surface potential. The probabilistic biomolecular surface adsorption behavior can be modeled by considering the potential difference between the binding and nonbinding states. To verify our model, we experimentally implemented a method of electroactivated biomolecular patterning technology and the resulting fluorescence intensity matched the prediction of the developed model quite well. Based on this result, we also experimentally demonstrated the creation of a bovine serum albumin pattern with a width of 200 nm in 5 min operations. This submicron noncovalent-binding biomolecular pattern can be maintained for hours after removing the applied electrical voltage. These stochastic understandings and experimental results not only prove the feasibility of submicron biomolecular patterns on chips but also pave the way for nanoscale interfacial-bioelectrical engineering.

Differential geometry based solvation model II: Lagrangian formulation.

Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation models. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The optimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and PB equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of computation, thanks to the equivalence of the Laplace-Beltrami operator in the two representations. The coupled partial differential equations (PDEs) are solved with an iterative procedure to reach a steady state, which delivers desired solvent-solute interface and electrostatic potential for problems of interest. These quantities are utilized to evaluate the solvation free energies and protein-protein binding affinities. A number of computational methods and algorithms are described for the interconversion of Lagrangian and Eulerian representations, and for the solution of the coupled PDE system. The proposed approaches have been extensively validated. We also verify that the mean curvature flow indeed gives rise to the minimal molecular surface and the proposed variational procedure indeed offers minimal total free energy. Solvation analysis and applications are considered for a set of 17 small compounds and a set of 23 proteins. The salt effect on protein-protein binding affinity is investigated with two protein complexes by using the present model. Numerical results are compared to the experimental measurements and to those obtained by using other theoretical methods in the literature.

DNA immobilization, delivery and cleavage on solid supports

Progress in bio-molecular chemistry, nanotechnology, and surface engineering resulted in the fabrication of nanoscale bio-systems with advanced functionalities. These systems and the related methodologies offer new perspectives for the development of novel bio-related diagnostic tools and gene and/or photodynamic therapy. A key issue in this context is the design and fabrication of “smart surfaces” able to immobilize functional biomolecules and DNA in particular, which can perform a certain function (e.g. hybridize with the target DNA strand) or be delivered or cleaved under the input of external stimuli (chemical, electrochemical, thermal, photochemical, etc.). This review addresses the above points dealing first with immobilization of DNA on various solid substrates using a bottom-up approach and describing later subsequent transport and/or cleavage of DNA using various routes.

Interaction of the disaccharides trehalose and gentiobiose with lipid bilayers: A comparative molecular dynamics study

Abstract The disaccharide α, α-trehalose (TRH) is known for its bioprotective action in organisms subject to stressful environmental conditions. However, the mechanisms whereby TRH stabilizes biomolecules remains matter of debate, the five main hypotheses being the water replacement (WRH), headgroup bridging (HBH), vitrification (VIH), water entrapment (WEH) and hydration forces (HFH) hypotheses. Four hypotheses (all except HFH) are in principle compatible with a preferential affinity of the sugar molecules (compared to water) for the biomolecular surface. According to the recently proposed sugar-like mechanism (Pereira and Hünenberger [29]), preferential affinity would result from the entropy gain upon releasing many water molecules from the surface region to the bulk, at the cost of immobilizing and rigidifying fewer sugar molecules. Thus, a more flexible disaccharide such as gentiobiose (GNT) should evidence a weaker preferential affinity, limiting its bioprotective ability. In this work, molecular dynamics (MD) simulations of a dipalmitoyl-phosphatidylcholine (DPPC) bilayer patch in the presence of either pure water or aqueous solutions of GNT or TRH are performed in order to assess the validity of this suggestion. At 475 K and 1.6 m (molal), TRH indeed preserves the bilayer structure to a larger extent compared to GNT. However, the present investigation does not unambiguously indicate which of the above mechanism takes place, since the simulations reveal characteristic features of all of them. This suggests either that multiple mechanisms may be simultaneously active or that their definitions are not precise enough.

Characterization of molecular interactions of an immobilized biotinylated monolayer and streptavidin-coated microspheres by bond-rupture scanning

Bond-rupture approach has been used in the understanding of biomolecular interactions of highly specific recognition, e.g., an antibody and its antigen, by a functionalized and self-assembled monolayer (SAM). One of the most challenging issues of diagnostics is to distinguish between true binding and the ever-present non-specific binding in which a species gives false results in conventional affinity methods. In this study, bond-rupture scanning was proposed to characterize bindings by introducing energy mechanically through displacement of a resonant quartz crystal. This system was able to measure the resonant frequency difference, due to mass changes and bond breakages between supramolecular interaction of biotinylated SAM and streptavidin-coated polystyrene microsphere (SCPM). Both 2-μm and 4-μm of SCPMs revealed two recognized desorption patterns at 4 V and 2 V amplitudes respectively. It rapidly provided confirmation of the presence of a target analyte. From this study, it can be shown that an established approach of dynamic bond-rupture scanning can be adopted as a promising diagnostic tool for investigating various interactions of bacteria or virus on an immobilized biomolecular surface by measuring the characteristic level of mechanical energy required to break bonds.

Site-Specific Patterning of Highly Ordered Nanocrystal Superlattices through Biomolecular Surface Confinement

With the increasing demand in recent years for high-performance devices for both energy and health applications, there has been extensive research to direct the assembly of nanoparticles into meso- or macroscale single two- and three-dimensional crystals of arbitrary configuration or orientation. Inorganic nanoparticle arrays can have intriguing physical properties that differ from either individual nanoparticles or bulk materials. For most device applications, it is necessary to fabricate two-dimensional nanoparticle superlattices at programmed sites on a surface. However, it has remained a significant challenge to generate patterned arrays with long-range positional order because most highly ordered close-packed nanocrystal arrays are typically obtained by kinetically driven evaporation processes. In this report, we demonstrate a method to generate patterned nanocrystal superlattices by confining nanoparticles to geometrically defined 2-D DNA sites on a surface and using associative biomolecular interparticle interactions to produce thermodynamically stable arrays of hexagonally packed nanocrystals with significant long-range order observed over 1-2 μm. We also demonstrate the role of chemical and geometrical confinement on particle packing and obtaining long-range order. Finally, we also demonstrate that the formation of DNA-mediated nanocrystal superlattices requires both interparticle DNA hybridization and solvent-less thermal annealing.

Molecular dynamics simulations of the interaction between polyhydroxylated compounds and Lennard-Jones walls: preferential affinity/exclusion effects and their relevance for bioprotection

Molecular dynamics simulation is used to investigate the interaction of methanol (MET) and the polyhydroxylated cosolutes (CSLs) ethylene glycol (ETG), glycerol (GLY), glucose (GLU) and trehalose (TRH) in aqueous solution with the surface of rigid Lennard-Jones walls. The walls are designed to represent simplified models for biomolecular (membrane, protein) surfaces and include three functionalisation variants: (i) non-polar (NP, no functionalisation); (ii) semi-polar (SP, surface hydroxyl groups); and (iii) highly polar (HP, positive and negative surface charges). The simulations are performed to investigate, in a simplified context, the preferential affinity/exclusion properties of the different CSLs (compared to water), which are relevant for the phenomenon of bioprotection by polyhydroxylated compounds. The simulations are carried out at three different temperatures (300, 475 and 600 K), and a comparison with simulations involving pure water or the pure liquid CSLs MET, ETG and GLY is also undertaken. In aqueous solution, all CSLs considered evidence preferential affinity (compared to water) for the NP and SP walls. This effect increases in magnitude with increasing CSL size, and is due to the favourable driving force associated with the replacement of multiple water molecules at the wall surface by a single polyhydroxylated CSL molecule (the partial substitution occurring without a significant change in the number of wall-solution hydrogen bonds). The preferential affinity is significantly reduced for the HP wall (for MET, ETG and GLY, preferential exclusion is actually observed). This change is probably related to the higher efficiency of water (compared to the CSLs) in terms of electrostatic solvation (higher dielectric permittivity), and provides an interpretation for the observation that polyhydroxylated CSLs appear to show preferential affinity for the surface of membranes, but preferential exclusion for the surface of proteins.

Visualizing water molecule distribution by atomic force microscopy

Hydration structures at biomolecular surfaces are essential for understanding the mechanisms of the various biofunctions and stability of biomolecules. Here, we demonstrate the measurement of local hydration structures using an atomic force microscopy system equipped with a low-noise deflection sensor. We applied this method to the analysis of the muscovite mica/water interface and succeeded in visualizing a hydration structure that is site-specific on a crystal. Furthermore, at the biomolecule/buffer solution interface, we found surface hydration layers that are more packed than those at the muscovite mica/water interface.

Accelerating electrostatic surface potential calculation with multi-scale approximation on graphics processing units.

Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed-up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson-Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multi-scale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone.

Dynamical Transition of Protein-Hydration Water

Thin layers of water on biomolecular and other nanostructured surfaces can be supercooled to temperatures not accessible with bulk water. Chen et al. [Proc. Natl. Acad. Sci. U.S.A. 103, 9012 (2006)]10.1073/pnas.0602474103 suggested that anomalies near 220 K observed by quasielastic neutron scattering can be explained by a hidden critical point of bulk water. Based on more sensitive measurements of water on perdeuterated phycocyanin, using the new neutron backscattering spectrometer SPHERES, and an improved data analysis, we present results that show no sign of such a fragile-to-strong transition. The inflection of the elastic intensity at 220 K has a dynamic origin that is compatible with a calorimetric glass transition at 170 K. The temperature dependence of the relaxation times is highly sensitive to data evaluation; it can be brought into perfect agreement with the results of other techniques, without any anomaly.

Preferential Interactions between Small Solutes and the Protein Backbone: A Computational Analysis

To improve our understanding of the effects of small solutes on protein stability, we conducted atomistic simulations to quantitatively characterize the interactions between two broadly used small solutes, urea and glycine betaine (GB), and a triglycine peptide, which is a good model for a protein backbone. Multiple solute concentrations were analyzed, and each solute-peptide-water ternary system was studied with approximately 200-300 ns of molecular dynamics simulations with the CHARMM force field. The comparison between calculated preferential interaction coefficients (Gamma(23)) and experimentally measured values suggests that semiquantitative agreement with experiments can be obtained if care is exercised to balance interactions among the solute, protein, and water. On the other hand, qualitatively incorrect (i.e., wrong sign in Gamma(23)) results can be obtained if a solute model is constructed by directly taking parameters for chemically similar groups from an existing force field. Such sensitivity suggests that small solute thermodynamic data can be valuable in the development of accurate force field models of biomolecules. Further decomposition of Gamma(23) into group contributions leads to additional insights regarding the effects of small solutes on protein stability. For example, use of the CHARMM force field predicts that urea preferentially interacts with not only amide groups in the peptide backbone but also aliphatic groups, suggesting a role for these interactions in urea-induced protein denaturation; quantitatively, however, it is likely that the CHARMM force field overestimates the interaction between urea and aliphatic groups. The results with GB support a simple thermodynamic model that assumes additivity of preferential interaction between GB and various biomolecular surfaces.

Biomolecular surface engineering of pancreatic islets with thrombomodulin

Islet transplantation has emerged as a promising treatment for Type 1 diabetes, but its clinical impact remains limited by early islet destruction mediated by prothrombotic and innate inflammatory responses elicited upon transplantation. Thrombomodulin (TM) acts as an important regulator of thrombosis and inflammation through its capacity to channel the catalytic activity of thrombin towards generation of activated protein C (APC), a potent anticoagulant and anti-inflammatory agent. We herein describe a novel biomolecular strategy for re-engineering the surface of pancreatic islets with TM. A biosynthetic approach was employed to generate recombinant human TM (rTM) bearing a C-terminal azide group, which facilitated site-specific biotinylation of rTM through Staudinger ligation. Murine pancreatic islets were covalently biotinylated through targeting of cell surface amines and aldehydes and both islet viability and the surface density of streptavidin were maximized through optimization of biotinylation conditions. rTM was immobilized on islet surfaces through streptavidin–biotin interactions, resulting in a nearly threefold increase in the catalytic capacity of islets to generate APC.

Synthesis of Alkyne-Terminated PCDA Linker for Applying Click Chemistry on PDA Layers

An alkyne-terminated PCDA (10,12-pentacosadiynoic acid) linker, which can undergo a simple click reaction with azide compounds, was synthesized for the purpose of immobilizing various kinds of biomolecular surface ligands on PDA (polydiacetylene) layers. In order to confirm the ability of the linker compound to anchor azide-modified surface ligands, we carried out a model reaction with benzyl azide under typical click-reaction conditions. We were able to confirm that the model reaction proceeded smoothly by observing the color change of PDA, including its thermochromic reversibility.

Mathematical Methods for Images and Surfaces

The last two decades have witnessed a greatly increasing interest in mathematical methods for images and surfaces that are originated from biomedical and biological applications. The research problems have necessitated the development of mathematical theories of wavelets, frames, harmonic analysis, geometric flows, differential geometry, topology statistical methods, machine learning, and so forth. This theoretical development is enhanced by the related numerical algorithm development and modeling development. Currently, mean curvature flow, Willmore flow, level set, generalized Laplace-Beltrami operator are commonly used mathematical techniques for the analysis of biomedical images and for the generation of biomolecular surfaces. Additionally, wavelets, frames, compressive sensing, and harmonic analysis are popular tools for biomedical visualization and image processing. Moreover, differential geometry, topology, and geometric measure theory are powerful approaches for the multiscale modeling of biomolecular structure, dynamics, and transport. Finally, persistently stable manifold, topological invariant, Euler characteristic, Frenet frame, and machine learning are vital to the dimensionality reduction of extremely massive biomedical and biomolecular data. These ideas have been successfully paired with current investigation and discovery in biomedical and biological systems. However, many mathematical challenges remain in image and surface analysis, such as the well-posedness of mathematical models under physical and biological constraints, maximum-minimum principle for high-order geometric evolution equations, numerical analysis of multiply coupled partial differential equations, effectiveness of approximation theory, and the modeling of complex biomolecular phenomena. This special issue was called to address mathematical difficulties and challenges in image and surface analysis. It consists of seventeen research papers.

Biomolecular Surfaces for the Capture and Reprogramming of Circulating Tumor Cells

Circulating Tumor Cells (CTC) have the potential to be used clinically as a diagnostic tool and a treatment tool in the field of oncology. As a diagnostic tool, CTC may be used to indicate the presence of a tumor before it is large enough to cause noticeable symptoms. As a treatment tool, CTC isolated from patients may be used to test the efficacy of chemotherapy options to personalize patient treatment. One way for tumors to spread is through metastasis via the circulatory system. CTC are able to exploit the natural leukocyte recruitment process that is initially mediated by rolling on transient selectin bonds. Our capture devices take advantage of this naturally occurring recruitment step to isolate CTC from whole blood by flowing samples through selectin and antibody-coated microtubes. Whole blood was spiked with a known concentration of labeled cancer cells and then perfused through pre-coated microtubes. Microtubes were then rinsed to remove unbound cells and the number of labeled cells captured on the lumen was assessed. CTC were successfully captured from whole blood at a clinically relevant level on the order of 10 cells per mL. Combination tubes with selectin and antibody coated surface exhibited higher capture rate than tubes coated with selectin alone or antibody alone. Additionally, CTC capture was demonstrated with the KG1a hematopoietic cell line and the DU145 epithelial cell line. Thus, the in vivo process of selectin-mediated CTC recruitment to distant vessel walls can be used in vitro to target CTC to a tube lumen. The biomolecular coatings can also be used to capture CTC of hematopoietic and epithelial tumor origin and is demonstrated to sensitivities down to the order of 10 CTC per mL. In a related study aimed at reducing the blood borne metastatic cancer load, we have shown that cells captured to a surface can be neutralized by a receptor-mediated biochemical signal. In the proposed method we have shown that using a combined selectin and TRAIL (TNF Related Apoptosis Inducing Ligand or Apo 2L) functionalized surface we are able to kill about 30% of the captured cells in a short duration of one hour whereas it took about 4 hours to kill the same proportion of cells without flow on a similarly functionalized surface. Here we have taken the approach a step further by showing that with very small doses of chemotherapeutic agents like bortezomib, we can increase the kill rate of CTC, thus allowing the device to function in scenarios where the patient is undergoing treatment. We show here that, with leukemic cells treated with bortezomib we are able to kill about 41% of the captured cells.

Interacting with the biomolecular solvent accessible surface via a haptic feedback device

BackgroundFrom the 1950s computer based renderings of molecules have been produced to aid researchers in their understanding of biomolecular structure and function. A major consideration for any molecular graphics software is the ability to visualise the three dimensional structure of the molecule. Traditionally, this was accomplished via stereoscopic pairs of images and later realised with three dimensional display technologies. Using a haptic feedback device in combination with molecular graphics has the potential to enhance three dimensional visualisation. Although haptic feedback devices have been used to feel the interaction forces during molecular docking they have not been used explicitly as an aid to visualisation.ResultsA haptic rendering application for biomolecular visualisation has been developed that allows the user to gain three-dimensional awareness of the shape of a biomolecule. By using a water molecule as the probe, modelled as an oxygen atom having hard-sphere interactions with the biomolecule, the process of exploration has the further benefit of being able to determine regions on the molecular surface that are accessible to the solvent. This gives insight into how awkward it is for a water molecule to gain access to or escape from channels and cavities, indicating possible entropic bottlenecks. In the case of liver alcohol dehydrogenase bound to the inhibitor SAD, it was found that there is a channel just wide enough for a single water molecule to pass through. Placing the probe coincident with crystallographic water molecules suggests that they are sometimes located within small pockets that provide a sterically stable environment irrespective of hydrogen bonding considerations.ConclusionBy using the software, named HaptiMol ISAS (available from ), one can explore the accessible surface of biomolecules using a three-dimensional input device to gain insights into the shape and water accessibility of the biomolecular surface that cannot be so easily attained using conventional molecular graphics software.

Detection of biomolecular surface interactions by transit time measurements with a coplanar transmission line probe

Changes in the transit time of a short electrical pulse propagating through a coplanar transmission line (CTL) are used to sense protein interactions at an aqueous–solid interface. The effective permittivity of the CTL is lowered as a result of protein binding at the interface. This decrease is sensed by the relative decrease in propagation transit time of a baseband picosecond electrical pulse through the probe. It is shown that the microwave probe is sensitive to protein binding at a liquid–solid interface and can be used for measuring dissociation constants in the nM range. In comparison with previous microwave sensors, this sensor is relatively insensitive to temperature fluctuations. It has the capability of operating in non-optical environments such as porous capillaries, capillaries filled with separation media, or opaque substrates.

Quantitative Biological Surface Science: Challenges and Recent Advances

Biological surface science is a broad, interdisciplinary subfield of surface science, where properties and processes at biological and synthetic surfaces and interfaces are investigated, and where biofunctional surfaces are fabricated. The need to study and to understand biological surfaces and interfaces in liquid environments provides sizable challenges as well as fascinating opportunities. Here, we report on recent progress in biological surface science that was described within the program assembled by the Biomaterial Interface Division of the Science and Technology of Materials, Interfaces and Processes (www.avs.org) during their 55th International Symposium and Exhibition held in Boston, October 19-24, 2008. The selected examples show that the rapid progress in nanoscience and nanotechnology, hand-in-hand with theory and simulation, provides increasingly sophisticated methods and tools to unravel the mechanisms and details of complex processes at biological surfaces and in-depth understanding of biomolecular surface interactions.