Daria B. Kokh

Docking of ubiquitin to gold nanoparticles.

Protein-nanoparticle associations have important applications in nanoscience and nanotechnology such as targeted drug delivery and theranostics. However, the mechanisms by which proteins recognize nanoparticles and the determinants of specificity are still poorly understood at the microscopic level. Gold is a promising material in nanoparticles for nanobiotechnology applications because of the ease of its functionalization and its tunable optical properties. Ubiquitin is a small, cysteine-free protein (ubiquitous in eukaryotes) whose binding to gold nanoparticles has been characterized recently by nuclear magnetic resonance (NMR). To reveal the molecular basis of these protein-nanoparticle interactions, we performed simulations at multiple levels (ab initio quantum mechanics, classical molecular dynamics and Brownian dynamics) and compared the results with experimental data (circular dichroism and NMR). The results provide a model of the ensemble of structures constituting the ubiquitin-gold surface complex, and insights into the driving forces for the binding of ubiquitin to gold nanoparticles, the role of nanoparticle surfactants (citrate) in the association process, and the origin of the perturbations in the NMR chemical shifts.

Protein–surface interactions: challenging experiments and computations

Protein–surface interactions are fundamental in natural processes, and have great potential for applications ranging from nanotechnology to medicine. A recent workshop highlighted the current achievements and the main challenges in the field. Copyright

On the ultraviolet photofragmentation of hydrogen iodide

An ab initio configuration interaction (CI) study including spin-orbit coupling is carried out for the ground and low-lying excited states of the HI molecule by employing a relativistic effective core potential for the iodine atom. The computed spectroscopic constants for the X 1Σ+ ground and b 3ΠΩ Rydberg states are in good agreement with available experimental data, as are the vertical excitation energies for the repulsive a 3Π1, a 3Π0+, and A 1Π1 states of the A band. The a 3Π0+ state is found to possess a shallow minimum of 600 cm−1 depth outside the Franck–Condon region, at ≈5.1 a0. The electric-dipole moments have also been calculated for transitions from the ground to the A band states. Contrary to what is usually assumed, the a 3Π1, A 1Π1←X0+ transition moments are found to depend strongly on internuclear distance. Employing the computed potential energy and transition moment data, partial and total absorption spectra for the A band are calculated and the I* quantum yields, ΦI*(ν), are determined ...

Flexible side chain models improve enrichment rates in in silico screening.

While modern docking methods often predict accurate binding modes, affinity calculations remain challenging and enrichment rates of in silico screening methods unsatisfactory. Inadequate treatment of induced fit effects is one major shortcoming of existing in silico screening methods. Here we investigate enrichment rates of rigid-, soft- and flexible-receptor models for 12 diverse receptors using libraries containing up to 13000 molecules. For the rigid-receptor model, we observed high enrichment (EF1 > 20) only for four target proteins. A soft-receptor model showed improved docking rates at the expense of reduced enrichment rates. A flexible side-chain model with flexible dihedral angles for up to 12 amino acids (3-8 flexible side chains) increased both binding propensity and enrichment rates: EF1 values increased by approximately 35% on average with respect to rigid docking. We find on average 4 known ligands in the top 10 molecules in the rank-ordered databases for the receptors investigated.

ProMetCS: An Atomistic Force Field for Modeling Protein-Metal Surface Interactions in a Continuum Aqueous Solvent.

In order to study protein-inorganic surface association processes, we have developed a physics-based energy model, the ProMetCS model, which describes protein-surface interactions at the atomistic level while treating the solvent as a continuum. Here, we present an approach to modeling the interaction of a protein with an atomically flat Au(111) surface in an aqueous solvent. Protein-gold interactions are modeled as the sum of van der Waals, weak chemisorption, and electrostatic interactions, as well as the change in free energy due to partial desolvation of the protein and the metal surface upon association. This desolvation energy includes the effects of water-protein, water-surface, and water-water interactions and has been parametrized using molecular dynamics (MD) simulations of water molecules and a test atom at a gold-water interface. The proposed procedure for computing the energy terms is mostly grid-based and is therefore efficient for application to long-time simulations of protein binding processes. The approach was tested for capped amino acid residues whose potentials of mean force for binding to a gold surface were computed and compared with those obtained previously in MD simulations with water treated explicitly. Calculations show good quantitative agreement with the results from MD simulations for all but one amino acid (Trp), as well as correspondence with available experimental data on the adhesion properties of amino acids.

Protein Binding Pocket Dynamics

The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular binding partners and facilitates the binding process. This implies the necessity to consider protein internal motion in determining and predicting binding properties and in designing new binders. Although accounting for protein dynamics presents a challenge for computational approaches, it expands the structural and physicochemical space for compound design and thus offers the prospect of improved binding specificity and selectivity. A cavity on the surface or in the interior of a protein that possesses suitable properties for binding a ligand is usually referred to as a binding pocket. The set of amino acid residues around a binding pocket determines its physicochemical characteristics and, together with its shape and location in a protein, defines its functionality. Residues outside the binding site can also have a long-range effect on the properties of the binding pocket. Cavities with similar functionalities are often conserved across protein families. For example, enzyme active sites are usually concave surfaces that present amino acid residues in a suitable configuration for binding low molecular weight compounds. Macromolecular binding pockets, on the other hand, are located on the protein surface and are often shallower. The mobility of proteins allows the opening, closing, and adaptation of binding pockets to regulate binding processes and specific protein functionalities. For example, channels and tunnels can exist permanently or transiently to transport compounds to and from a binding site. The influence of protein flexibility on binding pockets can vary from small changes to an already existent pocket to the formation of a completely new pocket. Here, we review recent developments in computational methods to detect and define binding pockets and to study pocket dynamics. We introduce five different classes of protein pocket dynamics: (1) appearance/disappearance of a subpocket in an existing pocket; (2) appearance/disappearance of an adjacent pocket on the protein surface in the direct vicinity of an already existing pocket; (3) pocket breathing, which may be caused by side-chain fluctuations or backbone or interdomain vibrational motion; (4) opening/closing of a channel or tunnel, connecting a pocket inside the protein with solvent, including lid motion; and (5) the appearance/disappearance of an allosteric pocket at a site on a protein distinct from an already existing pocket with binding of a ligand to the allosteric binding site affecting the original pocket. We suggest that the class of pocket dynamics, as well as the type and extent of protein motion affecting the binding pocket, should be factors considered in choosing the most appropriate computational approach to study a given binding pocket. Furthermore, we examine the relationship between pocket dynamics classes and induced fit, conformational selection, and gating models of ligand binding on binding kinetics and thermodynamics. We discuss the implications of protein binding pocket dynamics for drug design and conclude with potential future directions for computational analysis of protein binding pocket dynamics.

A Quantitative, Real-Time Assessment of Binding of Peptides and Proteins to Gold Surfaces

Interactions of peptides and proteins with inorganic surfaces are important to both natural and artificial systems; however, a detailed understanding of such interactions is lacking. In this study, we applied new approaches to quantitatively measure the binding of amino acids and proteins to gold surfaces. Real-time surface plasmon resonance (SPR) measurements showed that TEM1-β-lactamase inhibitor protein (BLIP) interacts only weakly with Au nanoparticles (NPs). However, fusion of three histidine residues to BLIP (3H-BLIP) resulted in a significant increase in the binding to the Au NPs, which further increased when the histidine tail was extended to six histidines (6H-BLIP). Further increasing the number of His residues had no effect on the binding. A parallel study using continuous (111)-textured Au surfaces and single-crystalline, (111)-oriented, Au islands by ellipsometry, FTIR, and localized surface plasmon resonance (LSPR) spectroscopy further confirmed the results, validating the broad applicability of Au NPs as model surfaces. Evaluating the binding of all other natural amino acid homotripeptides fused to BLIP (except Cys and Pro) showed that aromatic and positively-charged residues bind preferentially to Au with respect to small aliphatic and negatively charged residues, and that the rate of association is related to the potency of binding. The binding of all fusions was irreversible. These findings were substantiated by SPR measurements of synthesized, free, soluble tripeptides using Au-NP-modified SPR chips. Here, however, the binding was reversible allowing for determination of binding affinities that correlate with the binding potencies of the related BLIP fusions. Competition assays performed between 3H-BLIP and the histidine tripeptide (3 His) suggest that Au binding residues promote the adsorption of proteins on the surface, and by this facilitate the irreversible interaction of the polypeptide chain with Au. The binding of amino acids to Au was simulated by using a continuum solvent model, showing agreement with the experimental values. These results, together with the observed binding potencies and kinetics of the BLIP fusions and free peptides, suggest a binding mechanism that is markedly different from biological protein-protein interactions.

TRAPP: A Tool for Analysis of Transient Binding Pockets in Proteins

We present TRAPP (TRAnsient Pockets in Proteins), a new automated software platform for tracking, analysis, and visualization of binding pocket variations along a protein motion trajectory or within an ensemble of protein structures that may encompass conformational changes ranging from local side chain fluctuations to global backbone motions. TRAPP performs accurate grid-based calculations of the shape and physicochemical characteristics of a binding pocket for each structure and detects the conserved and transient regions of the pocket in an ensemble of protein conformations. It also provides tools for tracing the opening of a particular subpocket and residues that contribute to the binding site. TRAPP thus enables an assessment of the druggability of a disease-related target protein taking its flexibility into account.

Receptor flexibility in small-molecule docking calculations

Protein structural flexibility plays a critical role in receptor–ligand binding processes and should be considered in computational drug design. However, the treatment of protein conformational changes is still a major challenge because it is associated with a large increase in the conformational space that needs to be sampled and requires highly accurate scoring functions that incorporate the receptor reorganization energy. A number of different approaches have been proposed recently to address this problem. Most of them have been shown to be successful in reproducing the correct docking pose of known ligands, but their benefit regarding enrichment, affinity prediction, and screening of large molecular libraries is less clear. Here, we review current methodologies to treat receptor conformational changes in structure‐based docking procedures, and show their impact on the accuracy of docking and scoring. We also discuss pitfalls and limitations of state‐of‐the‐art flexible‐receptor docking strategies and perspectives for their improvement.

Modeling and simulation of protein–surface interactions: achievements and challenges

Understanding protein-inorganic surface interactions is central to the rational design of new tools in biomaterial sciences, nanobiotechnology and nanomedicine. Although a significant amount of experimental research on protein adsorption onto solid substrates has been reported, many aspects of the recognition and interaction mechanisms of biomolecules and inorganic surfaces are still unclear. Theoretical modeling and simulations provide complementary approaches for experimental studies, and they have been applied for exploring protein-surface binding mechanisms, the determinants of binding specificity towards different surfaces, as well as the thermodynamics and kinetics of adsorption. Although the general computational approaches employed to study the dynamics of proteins and materials are similar, the models and force-fields (FFs) used for describing the physical properties and interactions of material surfaces and biological molecules differ. In particular, FF and water models designed for use in biomolecular simulations are often not directly transferable to surface simulations and vice versa. The adsorption events span a wide range of time- and length-scales that vary from nanoseconds to days, and from nanometers to micrometers, respectively, rendering the use of multi-scale approaches unavoidable. Further, changes in the atomic structure of material surfaces that can lead to surface reconstruction, and in the structure of proteins that can result in complete denaturation of the adsorbed molecules, can create many intermediate structural and energetic states that complicate sampling. In this review, we address the challenges posed to theoretical and computational methods in achieving accurate descriptions of the physical, chemical and mechanical properties of protein-surface systems. In this context, we discuss the applicability of different modeling and simulation techniques ranging from quantum mechanics through all-atom molecular mechanics to coarse-grained approaches. We examine uses of different sampling methods, as well as free energy calculations. Furthermore, we review computational studies of protein-surface interactions and discuss the successes and limitations of current approaches.