Water-mediated interaction at a protein–protein interface

Effect of Direct and Water-Mediated Interactions on the Identification of Hotspots in Biomolecular Complexes with Multiple Subsystems

Identification of important residues in biochemical complexes is often a crucial step for many problems in molecular biology and biochemistry. A method is proposed to identify hotspots in biomolecular complexes based on a new metric, derived from networks representing molecular subunits (residues, bridging solvent molecules, ligands etc.) connected by interactions. A singular value decomposition of the weighted adjacency matrix is used to construct a scalar rank for each subunit that reflects its importance in the residue interaction network. This metric is called the singular value centrality. In addition, a new formalism is proposed to account for water-mediated interactions in the ranking of residues. Interactions for a residue network can be provided by various computational methods. In this work interactions are obtained from full quantum-mechanical calculations of protein-protein complexes using the fragment molecular orbital method. The ranking results are shown to be in good agreement with earlier computational and experimental studies. The developed method can be used to gain a deeper insight into the role of subunits in complex biomolecular systems.

Exploring the uncharted territory of the potential protein-protein interactions of cytosolic malate dehydrogenase

In this review, we examine the protein-protein interactions of cytosolic malate dehydrogenase (MDH), an under-studied area in cellular metabolism. We provide a comprehensive overview of MDH involvement in metabolism, especially its interactions with metabolic partners and dynamics of changing metabolism. We present an analysis of the biophysical nature of these interactions and the current methods used to study them. Our review includes an assessment of computational docking studies, which offer initial hypotheses about potential MDH interaction partners. Furthermore, we provide a summary of the sparse yet insightful experimental evidence available, establishing a foundation for future research. By integrating biophysical analysis and methodological advancements, this paper aims to illuminate the intricate network of interactions involving cytosolic MDH and their metabolic implications. This work not only contributes to our understanding of MDH's role in metabolism but also highlights the potential impact of these interactions in metabolic disorders.

Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD

The dissociation rate, or its reciprocal, the residence time (τ), is a crucial parameter for understanding the duration and biological impact of biomolecular interactions. Accurate prediction of τ is essential for understanding protein-protein interactions (PPIs) and identifying potential drug targets or modulators for tackling diseases. Conventional molecular dynamics simulation techniques are inherently constrained by their limited timescales, making it challenging to estimate residence times, which typically range from minutes to hours. Building upon its successful application in protein-small molecule systems, τ-Random Acceleration Molecular Dynamics (τRAMD) is here investigated for estimating dissociation rates of protein-protein complexes. τRAMD enables the observation of unbinding events on the nanosecond timescale, facilitating rapid and efficient computation of relative residence times. We tested this methodology for three protein-protein complexes and their extensive mutant datasets, achieving good agreement between computed and experimental data. By combining τRAMD with MD-IFP (Interaction Fingerprint) analysis, dissociation mechanisms were characterized and their sensitivity to mutations investigated, enabling the identification of molecular hotspots for selective modulation of dissociation kinetics. In conclusion, our findings underscore the versatility of τRAMD as a simple and computationally efficient approach for computing relative protein-protein dissociation rates and investigating dissociation mechanisms, thereby aiding the design of PPI modulators.

HydraProt: A New Deep Learning Tool for Fast and Accurate Prediction of Water Molecule Positions for Protein Structures

Water molecules are integral to the structural stability of proteins and vital for facilitating molecular interactions. However, accurately predicting their precise position around protein structures remains a significant challenge, making it a vibrant research area. In this paper, we introduce HydraProt (deep Hydration of Proteins), a novel methodology for predicting precise positions of water molecule oxygen atoms around protein structures, leveraging two interconnected deep learning architectures: a 3D U-net and a Multi-Layer Perceptron (MLP). Our approach starts by introducing a coarse voxel-based representation of the protein, which allows for rapid sampling of candidate water positions via the 3D U-net. These water positions are then assessed by embedding the water-protein relationship in the Euclidean space by means of an MLP. Finally, a postprocessing step is applied to further refine the MLP predictions. HydraProt surpasses existing state-of-the-art approaches in terms of precision and recall and has been validated on large data sets of protein structures. Notably, our method offers rapid inference runtime and should constitute the method of choice for protein structure studies and drug discovery applications. Our pretrained models, data, and the source code required to reproduce these results are accessible at https://github.com/azamanos/HydraProt.

Exploring solubility and energetics: Dissolution of biologically important l-threonine in diverse aqueous organic mixtures across the temperature range of 288.15 K to 308.15 K

This research provides a thorough investigation into the solubility behavior and solution thermodynamics of l-threonine in significant organic solvent systems. The work was done on measuring the actual solubility and subsequently calculating overall transfer solvation free energetics (∆Genergetic0i) and transfer entropies (∆St0i) at a temperature of 298.15 K. These measurements were performed as l-threonine transitioned from water to different water-organic mixed solvents systems. The saturated solubilities of l-threonine were determined using the 'gravimetric method' at five equidistant temperatures namely 288.15 K, 293.15 K, 298.15 K, 303.15 K and 308.15 K. By analyzing the data on solubility, we further obtained the different energies involved in solvation related issues. In the case of single solvents, the nature of solubility of l-threonine was observed like: dimethylsulfoxide (DMSO) < acetonitrile (ACN) < N, N-dimethylformamide (DMF) < ethylene glycol (EG) < water (H2O), irrespective of the experimental conditions. Specifically, at 298.15 K, the solubilities of l-threonine in single solvents were found to be as follows: 0.8220 mol per kg of water, 0.3101 mol per kg of EG, 0.1337 mol per kg of DMF, 0.1107 mol per kg DMSO and 0.1188 mol per kg of ACN. This research critically examines the relationship between the experimental saturated solubility of l-threonine and the complex properties influencing its solvation energy in diverse aqueous organic solvent systems.

Number of Hydrogen Bonds per Unit Solvent Accessible Surface Area: A Descriptor of Functional States of Proteins

Proteins function close to native and near-native conformations. These states are evolutionarily selected to ensure the effect of mutations is minimized. The structural organization of a protein is hierarchical and modular, which reduces the dimensionality of the configurational space of the native states. Thus, finding appropriate descriptors that define the native state among all possible states of a protein is a problem of immense interest. The present study explores the correlation between solvent accessible surface areas (SASAs) and different intraprotein as well as protein-water hydrogen bonds of 55 single-chain globular proteins from four different structural classes (all α, all β, α+β, and α/β), 16 multichain proteins, and 4 macromolecular complexes. A systematic analysis of the solvent accessible surface area and intraprotein and protein-water hydrogen bonds suggests a linear relationship between SASAs and hydrogen bonds. The number of protein-water hydrogen bonds per unit SASA ranges from 3 to 4 for all the different structural protein classes. In contrast, the number of intramolecular hydrogen bonds per unit SASA, including the mainchain-mainchain, mainchain-sidechain, and sidechain-sidechain, varies between 0.75 to 2. The solvation free energy of a protein linearly decreases with SASA. Our study also shows that the solvation free energy/SASA varies from -75 to -105 kJ mol^-1 nm^-2 across all the native states studied here. The number conservancy of intraprotein hydrogen bonds per unit SASA possibly imparts structural stability to the native structure. On the other hand, 3-4 protein-water hydrogen bonds per unit SASA are possibly required to maintain a balance between the solubility and functionality of the native states. This study provides a basis for synthetic biologists to design new folds with improved functionality.

Roles of interfacial water states on advanced biomedical material design

When biomedical materials come into contact with body fluids, the first reaction that occurs on the material surface is hydration; proteins are then adsorbed and denatured on the hydrated material surface. The amount and degree of denaturation of adsorbed proteins affect subsequent cell behavior, including cell adhesion, migration, proliferation, and differentiation. Biomolecules are important for understanding the interactions and biological reactions of biomedical materials to elucidate the role of hydration in biomedical materials and their interaction partners. Analysis of the water states of hydrated materials is complicated and remains controversial; however, knowledge about interfacial water is useful for the design and development of advanced biomaterials. Herein, we summarize recent findings on the hydration of synthetic polymers, supramolecular materials, inorganic materials, proteins, and lipid membranes. Furthermore, we present recent advances in our understanding of the classification of interfacial water and advanced polymer biomaterials, based on the intermediate water concept.

High-resolution crystal structure of LpqH, an immunomodulatory surface lipoprotein of Mycobacterium tuberculosis reveals a distinct fold and a conserved cleft on its surface

Tuberculosis, caused by Mycobacterium tuberculosis, is predominantly a disease of the lungs acquired by inhaling mycobacteria from infected individuals via airborne droplets. In order to facilitate their entry into the alveolar macrophages, mycobacteria have a collection of pathogen-associated molecular patterns (PAMPs) on their surface that are known to detect certain pattern recognition receptors present on the surface of host cells. A major group of these PAMPs includes mycobacterial lipoproteins, of which, the 19 kDa surface antigen LpqH, has been reported to play a critical role in both host-pathogen interactions as well as pleiotropic immune regulation. Despite its crucial involvement in tuberculosis, the detailed structure-function relationship of this protein remains to be explored. Here, we report the high-resolution crystal structure of the non-acylated LpqH (LpqH^48-159) at a resolution of 1.26 Å, which adopts a unique fold. Flow cytometry-based experiments show that the protein can bind and induce apoptosis in PMA-activated human monocytic cell line THP-1, indicative of the preservation of functionality of the protein. Furthermore, analysis of conservation of LpqH sequences from Mycobacterium species reveals a patch of conserved residues on the surface which may play a role in its binding partner recognition and hence in host-pathogen interaction.

Capturing the Effects of Explicit Waters in Implicit Electrostatics Modeling: Qualitative Justification of Gaussian-Based Dielectric Models in DelPhi

Our group has implemented a smooth Gaussian-based dielectric function in DelPhi (J. Chem. Theory Comput. 2013, 9 (4), 2126-2136) which models the solute as an object with inhomogeneous dielectric permittivity and provides a smooth transition of dielectric permittivity from surface-bound water to bulk solvent. Although it is well-understood that the protein hydrophobic core is less polarizable than the hydrophilic protein surface, less attention is paid to the polarizability of water molecules inside the solute and on its surface. Here, we apply explicit water simulations to study the behavior of water molecules buried inside a protein and on the surface of that protein and contrast it with the behavior of the bulk water. We selected a protein that is experimentally shown to have five cavities, most of which are occupied by water molecules. We demonstrate through molecular dynamics (MD) simulations that the behavior of water in the cavity is drastically different from that in the bulk. These observations were made by comparing the mean residence times, dipole orientation relaxation times, and average dipole moment fluctuations. We also show that the bulk region has a nonuniform distribution of these tempo-spatial properties. From the perspective of continuum electrostatics, we argue that the dielectric "constant" in water-filled cavities of proteins and the space close to the molecular surface should differ from that assigned to the bulk water. This provides support for the Gaussian-based smooth dielectric model for solving electrostatics in the Poisson-Boltzmann equation framework. Furthermore, we demonstrate that using a well-parametrized Gaussian-based model with a single energy-minimized configuration of a protein can also reproduce its ensemble-averaged polar solvation energy. Thus, we argue that the Gaussian-based smooth dielectric model not only captures accurate physics but also provides an efficient way of computing ensemble-averaged quantities.

A Boundary-Integral Approach for the Poisson-Boltzmann Equation with Polarizable Force Fields

Implicit-solvent models are widely used to study the electrostatics in dissolved biomolecules, which are parameterized using force fields. Standard force fields treat the charge distribution with point charges; however, other force fields have emerged which offer a more realistic description by considering polarizability. In this work, we present the implementation of the polarizable and multipolar force field atomic multipole optimized energetics for biomolecular applications (AMOEBA), in the boundary integral Poisson-Boltzmann solver PyGBe. Previous work from other researchers coupled AMOEBA with the finite-difference solver APBS, and found difficulties to effectively transfer the multipolar charge description to the mesh. A boundary integral formulation treats the charge distribution analytically, overlooking such limitations. This becomes particularly important in simulations that need high accuracy, for example, when the quantity of interest is the difference between solvation energies obtained from separate calculations, like happens for binding energy. We present verification and validation results of our software, compare it with the implementation on APBS, and assess the efficiency of AMOEBA and classical point-charge force fields in a Poisson-Boltzmann solver. We found that a boundary integral approach performs similarly to a volumetric method on CPU. Also, we present a GPU implementation of our solver. Moreover, with a boundary element method, the mesh density to correctly resolve the electrostatic potential is the same for standard point-charge and multipolar force fields. Finally, we saw that for binding energy calculations, a boundary integral approach presents more consistent results than a finite difference approximation for multipolar force fields. © 2019 Wiley Periodicals, Inc.

A grid-based algorithm in conjunction with a gaussian-based model of atoms for describing molecular geometry

A novel grid-based method is presented, which in conjunction with a smooth Gaussian-based model of atoms, is used to compute molecular volume (MV) and surface area (MSA). The MV and MSA are essential for computing nonpolar component of free energies. The objective of our grid-based approach is to identify solute atom pairs that share overlapping volumes in space. Once completed, this information is used to construct a rooted tree using depth-first method to yield the final volume and SA by using the formulations of the Gaussian model described by Grant and Pickup (J. Phys Chem, 1995, 99, 3503). The method is designed to function uninterruptedly with the grid-based finite-difference method implemented in Delphi, a popular and open-source package used for solving the Poisson-Boltzmann equation (PBE). We demonstrate the time efficacy of the method while also validating its performance in terms of the effect of grid-resolution, positioning of the solute within the grid-map and accuracy in identification of overlapping atom pairs. We also explore and discuss different aspects of the Gaussian model with key emphasis on its physical meaningfulness. This development and its future release with the Delphi package are intended to provide a physically meaningful, fast, robust and comprehensive tool for MM/PBSA based free energy calculations. © 2019 Wiley Periodicals, Inc.

OSPREY 3.0: Open-source protein redesign for you, with powerful new features

We present osprey 3.0, a new and greatly improved release of the osprey protein design software. Osprey 3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions of osprey when running the same algorithms on the same hardware. Moreover, osprey 3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions of osprey, osprey 3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically that osprey 3.0 accurately predicts the effect of mutations on protein-protein binding. Osprey 3.0 is available at http://www.cs.duke.edu/donaldlab/osprey.php as free and open-source software. © 2018 Wiley Periodicals, Inc.

Gaussian-Based Smooth Dielectric Function: A Surface-Free Approach for Modeling Macromolecular Binding in Solvents

Conventional modeling techniques to model macromolecular solvation and its effect on binding in the framework of Poisson-Boltzmann based implicit solvent models make use of a geometrically defined surface to depict the separation of macromolecular interior (low dielectric constant) from the solvent phase (high dielectric constant). Though this simplification saves time and computational resources without significantly compromising the accuracy of free energy calculations, it bypasses some of the key physio-chemical properties of the solute-solvent interface, e.g., the altered flexibility of water molecules and that of side chains at the interface, which results in dielectric properties different from both bulk water and macromolecular interior, respectively. Here we present a Gaussian-based smooth dielectric model, an inhomogeneous dielectric distribution model that mimics the effect of macromolecular flexibility and captures the altered properties of surface bound water molecules. Thus, the model delivers a smooth transition of dielectric properties from the macromolecular interior to the solvent phase, eliminating any unphysical surface separating the two phases. Using various examples of macromolecular binding, we demonstrate its utility and illustrate the comparison with the conventional 2-dielectric model. We also showcase some additional abilities of this model, viz. to account for the effect of electrolytes in the solution and to render the distribution profile of water across a lipid membrane.

Signatures of Solvation Thermodynamics in Spectra of Intermolecular Vibrations

This study explores the thermodynamic and vibrational properties of water in the three-dimensional environment of solvated ions and small molecules using molecular simulations. The spectrum of intermolecular vibrations in liquid solvents provides detailed information on the shape of the local potential energy surface, which in turn determines local thermodynamic properties such as the entropy. Here, we extract this information using a spatially resolved extension of the two-phase thermodynamics method to estimate hydration water entropies based on the local vibrational density of states (3D-2PT). Combined with an analysis of solute–water and water–water interaction energies, this allows us to resolve local contributions to the solvation enthalpy, entropy, and free energy. We use this approach to study effects of ions on their surrounding water hydrogen bond network, its spectrum of intermolecular vibrations, and resulting thermodynamic properties. In the three-dimensional environment of polar and nonpolar functional groups of molecular solutes, we identify distinct hydration water species and classify them by their characteristic vibrational density of states and molecular entropies. In each case, we are able to assign variations in local hydration water entropies to specific changes in the spectrum of intermolecular vibrations. This provides an important link for the thermodynamic interpretation of vibrational spectra that are accessible to far-infrared absorption and Raman spectroscopy experiments. Our analysis provides unique microscopic details regarding the hydration of hydrophobic and hydrophilic functional groups, which enable us to identify interactions and molecular degrees of freedom that determine relevant contributions to the solvation entropy and consequently the free energy.

Dynamics of Hydration Water Plays a Key Role in Determining the Binding Thermodynamics of Protein Complexes

Interfacial waters are considered to play a crucial role in protein–protein interactions, but in what sense and why are they important? Here, using molecular dynamics simulations and statistical thermodynamic analyses, we demonstrate distinctive dynamic characteristics of the interfacial water and investigate their implications for the binding thermodynamics. We identify the presence of extraordinarily slow (~1,000 times slower than in bulk water) hydrogen-bond rearrangements in interfacial water. We rationalize the slow rearrangements by introducing the “trapping” free energies, characterizing how strongly individual hydration waters are captured by the biomolecular surface, whose magnitude is then traced back to the number of water–protein hydrogen bonds and the strong electrostatic field produced at the binding interface. We also discuss the impact of the slow interfacial waters on the binding thermodynamics. We find that, as expected from their slow dynamics, the conventional approach to the water-mediated interaction, which assumes rapid equilibration of the waters’ degrees of freedom, is inadequate. We show instead that an explicit treatment of the extremely slow interfacial waters is critical. Our results shed new light on the role of water in protein–protein interactions, highlighting the need to consider its dynamics to improve our understanding of biomolecular bindings.

Accurate estimation of electrostatic binding energy with Poisson-Boltzmann equation solver DelPhi program

Poisson–Boltzmann (PB) model is a widely used implicit solvent approximation in biophysical modeling because of its ability to provide accurate and reliable PB electrostatic salvation free energies ([Formula: see text] as well as electrostatic binding free energy ([Formula: see text] estimations. However, a recent study has warned that the 0.5[Formula: see text]Å grid spacing which is normally adopted can produce unacceptable errors in [Formula: see text] estimation with the solvent excluded surface (SES) (Harris RC, Boschitsch AH and Fenley MO, Influence of grid spacing in Poisson–Boltzmann equation binding energy estimation, J Chem Theory Comput 19: 3677–3685, 2013). In this work, we investigate the grid dependence of the widely used PB solver DelPhi v6.2 with molecular surface (MS) for estimating both electrostatic solvation free energies and electrostatic binding free energies. Our results indicate that, for the molecular complex and components the absolute errors of [Formula: see text] are smaller than that of [Formula: see text], and grid spacing of 0.8[Formula: see text]Å with DelPhi program ensures the accuracy and reliability of [Formula: see text]; however, the accuracy of [Formula: see text] largely relies on the order of magnitude of [Formula: see text] itself rather than that of [Formula: see text] or [Formula: see text]. Our findings suggest that grid spacing of 0.5[Formula: see text]Å is enough to produce accurate [Formula: see text] for molecules whose [Formula: see text] are large, but finer grids are needed when [Formula: see text] is very small.

Interaction between bound water molecules and local protein structures: A statistical analysis of the hydrogen bond structures around bound water molecules

Water molecules play an important role in protein folding and protein interactions through their structural association with proteins. Examples of such structural association can be found in protein crystal structures, and can often explain protein functionality in the context of structure. We herein report the systematic analysis of the local structures of proteins interacting with water molecules, and the characterization of their geometric features. We first examined the interaction of water molecules with a large local interaction environment by comparing the preference of water molecules in three regions, namely, the protein-protein interaction (PPI) interfaces, the crystal contact (CC) interfaces, and the non-interfacial regions. High preference of water molecules to the PPI and CC interfaces was found. In addition, the bound water on the PPI interface was more favorably associated with the complex interaction structure, implying that such water-mediated structures may participate in the shaping of the PPI interface. The pairwise water-mediated interaction was then investigated, and the water-mediated residue-residue interaction potential was derived. Subsequently, the types of polar atoms surrounding the water molecules were analyzed, and the preference of the hydrogen bond acceptor was observed. Furthermore, the geometries of the structures interacting with water were analyzed, and it was found that the major structure on the protein surface exhibited planar geometry rather than tetrahedral geometry. Several previously undiscovered characteristics of water-protein interactions were unfolded in this study, and are expected to lead to a better understanding of protein structure and function.

IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking

Background

Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones.

In this paper, we propose a new re-ranking technique using a new energy-based scoring function, namely IFACEwat - a combined Interface Atomic Contact Energy (IFACE) and water effect. The IFACEwat aims to further improve the discrimination of the near-native structures of the initial rigid docking algorithm ZDOCK3.0.2. Unlike other re-ranking techniques, the IFACEwat explicitly implements interfacial water into the protein interfaces to account for the water-mediated contacts during the protein interactions.

Results

Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F²Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes.

Conclusions

With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near native structures found. As our implementation so far targeted to improve the results of ZDOCK3.0.2, and particularly for the Antigen/Antibody complexes, it is expected in the near future that more implementations will be conducted to be applicable for other initial rigid docking algorithms.

Quinary protein structure and the consequences of crowding in living cells: leaving the test-tube behind

Although the importance of weak protein-protein interactions has been understood since the 1980s, scant attention has been paid to this "quinary structure". The transient nature of quinary structure facilitates dynamic sub-cellular organization through loose grouping of proteins with multiple binding partners. Despite our growing appreciation of the quinary structure paradigm in cell biology, we do not yet understand how the many forces inside the cell--the excluded volume effect, the "stickiness" of the cytoplasm, and hydrodynamic interactions--perturb the weakest functional protein interactions. We discuss the unresolved problem of how the forces in the cell modulate quinary structure, and to what extent the cell has evolved to exert control over the weakest biomolecular interactions. We conclude by highlighting the new experimental and computational tools coming on-line for in vivo studies, which are a critical next step if we are to understand quinary structure in its native environment.

Efficient determination of protein-protein standard binding free energies from first principles

Characterizing protein-protein association quantitatively has been a longstanding challenge for computer simulations. Here, a theoretical framework is put forth that addresses this challenge on the basis of detailed all-atom molecular dynamics simulations with explicit solvent. The proposed methodology relies upon independent potential of mean force (PMF) free-energy calculations carried out sequentially, wherein the biological objects are restrained in the conformation, position and orientation of the bound state, using adequately chosen biasing potentials. These restraints systematically narrow down the configurational entropy available to the system and effectively guarantee that the relevant network of interactions is properly sampled as the two proteins reversibly associate. Decomposition of the binding process into consecutive, well-delineated stages, for both the protein complex and the individual, unbound partners, offers a rigorous definition of the standard state, from which the absolute binding free energy can be determined. The method is applied to the difficult case of the extracellular ribonuclease barnase binding to its intracellular inhibitor barstar. The calculated binding free energy is -21.0 ± 1.4 kcal/mol, which compares well with the experimental value of -19.0 ± 0.2 kcal/mol. The relatively small statistical error reflects the precision and convergence afforded by the PMF-based simulation methodology. In addition to providing an accurate reproduction of the standard binding free energy, the proposed strategy offers a detailed picture of the protein-protein interface, illuminating the thermodynamic forces that underlie reversible association. The application of the present formal framework to barnase:barstar binding provides a foundation for tackling nearly any protein-protein complex.

Towards ligand docking including explicit interface water molecules

Small molecule docking predicts the interaction of a small molecule ligand with a protein at atomic-detail accuracy including position and conformation the ligand but also conformational changes of the protein upon ligand binding. While successful in the majority of cases, docking algorithms including RosettaLigand fail in some cases to predict the correct protein/ligand complex structure. In this study we show that simultaneous docking of explicit interface water molecules greatly improves Rosetta’s ability to distinguish correct from incorrect ligand poses. This result holds true for both protein-centric water docking wherein waters are located relative to the protein binding site and ligand-centric water docking wherein waters move with the ligand during docking. Protein-centric docking is used to model 99 HIV-1 protease/protease inhibitor structures. We find protease inhibitor placement improving at a ratio of 9∶1 when one critical interface water molecule is included in the docking simulation. Ligand-centric docking is applied to 341 structures from the CSAR benchmark of diverse protein/ligand complexes [1]. Across this diverse dataset we see up to 56% recovery of failed docking studies, when waters are included in the docking simulation.

Biomolecular electrostatics and solvation: a computational perspective

An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

Progressive dry-core-wet-rim hydration trend in a nested-ring topology of protein binding interfaces

BACKGROUND

Water is an integral part of protein complexes. It shapes protein binding sites by filling cavities and it bridges local contacts by hydrogen bonds. However, water molecules are usually not included in protein interface models in the past, and few distribution profiles of water molecules in protein binding interfaces are known.

RESULTS

In this work, we use a tripartite protein-water-protein interface model and a nested-ring atom re-organization method to detect hydration trends and patterns from an interface data set which involves immobilized interfacial water molecules. This data set consists of 206 obligate interfaces, 160 non-obligate interfaces, and 522 crystal packing contacts. The two types of biological interfaces are found to be drier than the crystal packing interfaces in our data, agreeable to a hydration pattern reported earlier although the previous definition of immobilized water is pure distance-based. The biological interfaces in our data set are also found to be subject to stronger water exclusion in their formation. To study the overall hydration trend in protein binding interfaces, atoms at the same burial level in each tripartite protein-water-protein interface are organized into a ring. The rings of an interface are then ordered with the core atoms placed at the middle of the structure to form a nested-ring topology. We find that water molecules on the rings of an interface are generally configured in a dry-core-wet-rim pattern with a progressive level-wise solvation towards to the rim of the interface. This solvation trend becomes even sharper when counterexamples are separated.

CONCLUSIONS

Immobilized water molecules are regularly organized in protein binding interfaces and they should be carefully considered in the studies of protein hydration mechanisms.

Structural insight into the kinetics and DeltaCp of interactions between TEM-1 beta-lactamase and beta-lactamase inhibitory protein (BLIP)

In a previous study, we examined thermodynamic parameters for 20 alanine mutants in beta-lactamase inhibitory protein (BLIP) for binding to TEM-1 beta-lactamase. Here we have determined the structures of two thermodynamically distinctive complexes of BLIP mutants with TEM-1 beta-lactamase. The complex BLIP Y51A-TEM-1 is a tight binding complex with the most negative binding heat capacity change (DeltaG = approximately -13 kcal mol(-1) and DeltaCp = approximately -0.8 kcal mol(-1) K(-1)) among all of the mutants, whereas BLIP W150A-TEM-1 is a weak complex with one of the least negative binding heat capacity changes (DeltaG = approximately -8.5 kcal mol(-1) and DeltaCp = approximately -0.27 kcal mol(-1) K(-1)). We previously determined that BLIP Tyr51 is a canonical and Trp150 an anti-canonical TEM-1-contact residue, where canonical refers to the alanine substitution resulting in a matched change in the hydrophobicity of binding free energy. Structure determination indicates a rearrangement of the interactions between Asp49 of the W150A BLIP mutant and the catalytic pocket of TEM-1. The Asp49 of W150A moves more than 4 angstroms to form two new hydrogen bonds while losing four original hydrogen bonds. This explains the anti-canonical nature of the Trp150 to alanine substitution, and also reveals a strong long distance coupling between Trp150 and Asp49 of BLIP, because these two residues are more than 25 angstroms apart. Kinetic measurements indicate that the mutations influence the dissociation rate but not the association rate. Further analysis of the structures indicates that an increased number of interface-trapped water molecules correlate with poor interface packing in a mutant. It appears that the increase of interface-trapped water molecules is inversely correlated with negative binding heat capacity changes.

Crystal structural analysis of protein-protein interactions drastically destabilized by a single mutation

The complex of barnase (bn) and barstar (bs), which has been widely studied as a model for quantitative analysis of protein-protein interactions, is significantly destabilized by a single mutation, namely, bs Asp39 --> Ala, which corresponds to a change of 7.7 kcal x mol(-1) in the free energy of binding. However, there has been no structural information available to explain such a drastic destabilization. In the present study, we determined the structure of the mutant complex at 1.58 A resolution by X-ray crystallography. The complex was similar to the wild-type complex in terms of overall and interface structures; however, the hydrogen bond network mediated by water molecules at the interface was significantly different. Several water molecules filled the cavity created by the mutation and consequently caused rearrangement of the hydrated water molecules at the interface. The water molecules were redistributed into a channel-like structure that penetrated into the complex. Furthermore, molecular dynamics simulations showed that the mutation increased the mobility of water molecules at the interface. Since such a drastic change in hydration was not observed in other mutant complexes of bn and bs, the significant destabilization of the interaction may be due to this channel-like structure of hydrated water molecules.

Solvent reaction field potential inside an uncharged globular protein: a bridge between implicit and explicit solvent models?

The solvent reaction field potential of an uncharged protein immersed in simple point charge/extended explicit solvent was computed over a series of molecular dynamics trajectories, in total 1560 ns of simulation time. A finite, positive potential of 13-24 kbTec(-1) (where T=300 K), dependent on the geometry of the solvent-accessible surface, was observed inside the biomolecule. The primary contribution to this potential arose from a layer of positive charge density 1.0 A from the solute surface, on average 0.008 ec/A3, which we found to be the product of a highly ordered first solvation shell. Significant second solvation shell effects, including additional layers of charge density and a slight decrease in the short-range solvent-solvent interaction strength, were also observed. The impact of these findings on implicit solvent models was assessed by running similar explicit solvent simulations on the fully charged protein system. When the energy due to the solvent reaction field in the uncharged system is accounted for, correlation between per-atom electrostatic energies for the explicit solvent model and a simple implicit (Poisson) calculation is 0.97, and correlation between per-atom energies for the explicit solvent model and a previously published, optimized Poisson model is 0.99.

Fluctuating hydration structure around nanometer-size hydrophobic solutes. I. Caging and drying around C60 and C60H60 spheres

The hydration structure around nanometer-size hydrophobic solutes is studied with molecular dynamics simulation by taking aqueous solutions of C60 and C60H60 as examples. In the hydration shell around a single C60 or C60H60, dipoles of simulated water molecules tend to be aligned to form the vortexlike coherent pattern which lasts for 100 ps, while individual water molecules stay within the hydration shell for about 10 ps. This structural pattern organized by fluctuating and diffusively moving molecules should be called a "fluctuating cage". In the narrow region between a pair of C60 molecules or a pair of C60H60 molecules, water density strongly fluctuates and is correlated to the mean force between solutes. The fluctuating caging and drying between solutes affect the hydrophobic interaction and dynamical behaviors of solutes.

In silico screening of mutational effects on enzyme-proteic inhibitor affinity: a docking-based approach

BACKGROUND

Molecular recognition between enzymes and proteic inhibitors is crucial for normal functioning of many biological pathways. Mutations in either the enzyme or the inhibitor protein often lead to a modulation of the binding affinity with no major alterations in the 3D structure of the complex.

RESULTS

In this study, a rigid body docking-based approach has been successfully probed in its ability to predict the effects of single and multiple point mutations on the binding energetics in three enzyme-proteic inhibitor systems. The only requirement of the approach is an accurate structural model of the complex between the wild type forms of the interacting proteins, with the assumption that the architecture of the mutated complexes is almost the same as that of the wild type and no major conformational changes occur upon binding. The method was applied to 23 variants of the ribonuclease inhibitor-angiogenin complex, to 15 variants of the barnase-barstar complex, and to 8 variants of the bovine pancreatic trypsin inhibitor-beta Trypsin system, leading to thermodynamic and kinetic estimates consistent with in vitro data. Furthermore, simulations with and without explicit water molecules at the protein-protein interface suggested that they should be included in the simulations only when their positions are well defined both in the wild type and in the mutants and they result to be relevant for the modulation of mutational effects on the association process.

CONCLUSION

The correlative models built in this study allow for predictions of mutational effects on the thermodynamics and kinetics of association of three substantially different systems, and represent important extensions of our computational approach to cases in which it is not possible to estimate the absolute free energies. Moreover, this study is the first example in the literature of an extensive evaluation of the correlative weights of the single components of the ZDOCK score on the thermodynamics and kinetics of binding of protein mutants compared to the native state.Finally, the results of this study corroborate and extend a previously developed quantitative model for in silico predictions of absolute protein-protein binding affinities spanning a wide range of values, i.e. from -10 up to -21 kcal/mol. The computational approach is simple and fast and can be used for structure-based design of protein-protein complexes and for in silico screening of mutational effects on protein-protein recognition.

A water mediated electrostatic interaction gives thermal stability to the "tail" region of the GrpE protein from E. coli

The GrpE protein from E. coli is a homodimer with an unusual structure of two long paired alpha-helices from each monomer interacting in a parallel arrangement to form a "tail" at the N-terminal end. Using site-directed mutagenesis, we show that there is a key electrostatic interaction involving R57 (mediated by a water molecule) that provides thermal stability to this "tail" region. The R57A mutant showed a drop in T (m) of 8.5 degrees C and a smaller DeltaH (u) (unfolding) compared to wild-type for the first unfolding transition, but no significant decrease in dimer stability as shown through equilibrium analytical ultracentrifugation studies. Another mutant (E94A) at the dimer interface showed a decrease in DeltaH (u )but no drop in T (m) for the second unfolding transition and a slight increase in dimer stability.

CIRSE: a solvation energy estimator compatible with flexible protein docking and design applications

We present the Coordinate Internal Representation of Solvation Energy (CIRSE) for computing the solvation energy of protein configurations in terms of pairwise interactions between their atoms with analytic derivatives. Currently, CIRSE is trained to a Poisson/surface-area benchmark, but CIRSE is not meant to fit this benchmark exclusively. CIRSE predicts the overall solvation energy of protein structures from 331 NMR ensembles with 0.951+/-0.047 correlation and predicts relative solvation energy changes between members of individual ensembles with an accuracy of 15.8+/-9.6 kcal/mol. The energy of individual atoms in any of CIRSE's 17 types is predicted with at least 0.98 correlation. We apply the model in energy minimization, rotamer optimization, protein design, and protein docking applications. The CIRSE model shows some propensity to accumulate errors in energy minimization as well as rotamer optimization, but these errors are consistent enough that CIRSE correctly identifies the relative solvation energies of designed sequences as well as putative docked complexes. We analyze the errors accumulated by the CIRSE model during each type of simulation and suggest means of improving the model to be generally useful for all-atom simulations.

Mapping the energetics of water-protein and water-ligand interactions with the "natural" HINT forcefield: predictive tools for characterizing the roles of water in biomolecules

The energetics and hydrogen bonding pattern of water molecules bound to proteins were mapped by analyzing structural data (resolution better than 2.3A) for sets of uncomplexed and ligand-complexed proteins. Water-protein and water-ligand interactions were evaluated using hydropatic interactions (HINT), a non-Newtonian forcefield based on experimentally determined logP(octanol/water) values. Potential water hydrogen bonding ability was assessed by a new Rank algorithm. The HINT-derived binding energies and Ranks for second shell water molecules were -0.04 kcal mol(-1) and 0.0, respectively, for first shell water molecules -0.38 kcal mol(-1) and 1.6, for active site water molecules -0.45 kcal mol(-1) and 2.3, for cavity water molecules -0.55 kcal mol(-1) and 3.3, and for buried water molecules -0.56 kcal mol(-1) and 4.4. For the last four classes, similar energies indicate that internal and external water molecules interact with protein almost equally, despite different degrees of hydrogen bonding. The binding energies and Ranks for water molecules bridging ligand-protein were -1.13 kcal mol(-1) and 4.5, respectively. This energetic contribution is shared equally between protein and ligand, whereas Rank favors the protein. Lastly, by comparing the uncomplexed and complexed forms of proteins, guidelines were developed for prediction of the roles played by active site water molecules in ligand binding. A water molecule with high Rank and HINT score is unlikely to make further interactions with the ligand and is largely irrelevant to the binding process, while a water molecule with moderate Rank and high HINT score is available for ligand interaction. Water molecule displaced for steric reasons were characterized by lower Rank and HINT score. These guidelines, tested by calculating HINT score and Rank for 50 water molecules bound in the active site of four uncomplexed proteins (for which the structures of the liganded forms were also available), correctly predicted the ultimate roles (in the complex) for 76% of water molecules. Some failures were likely due to ambiguities in the structural data.

Survey of the year 2004 commercial optical biosensor literature

The year 2004 represents a milestone for the biosensor research community: in this year, over 1000 articles were published describing experiments performed using commercially available systems. The 1038 papers we found represent an approximately 10% increase over the past year and demonstrate that the implementation of biosensors continues to expand at a healthy pace. We evaluated the data presented in each paper and compiled a 'top 10' list. These 10 articles, which we recommend every biosensor user reads, describe well-performed kinetic, equilibrium and qualitative/screening studies, provide comparisons between binding parameters obtained from different biosensor users, as well as from biosensor- and solution-based interaction analyses, and summarize the cutting-edge applications of the technology. We also re-iterate some of the experimental pitfalls that lead to sub-optimal data and over-interpreted results. We are hopeful that the biosensor community, by applying the hints we outline, will obtain data on a par with that presented in the 10 spotlighted articles. This will ensure that the scientific community at large can be confident in the data we report from optical biosensors.