Automatic identification and representation of protein binding sites for molecular docking.

Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.     

分子表面的计算机表示

提出了一种用于生成分子光滑表面的新算法.该算法从分布在一个包含整个分子表面的椭球上的三角网络开始,逐步收缩网络直到所有的三角形最佳贴近分子表面.所使用的收缩包络椭球的技术只要稍加修改就可用于蛋白质空腔的表示.     

Non‐interacting surface solvation and dynamics in protein–protein interactions

Protein–protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure‐based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein–protein binding, even for simple lock‐and‐key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein–protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein–protein surfaces. We compare properties of the interface, rim, and non‐interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non‐interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non‐interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein–protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein–protein complexes from unintended protein–protein interactions. Proteins 2015; 83:445–458. © 2014 Wiley Periodicals, Inc.     

Characterization of receptors with a new negative image: Use in molecular docking and lead optimization

The characterization of receptor binding sites is an important aspect of molecular docking, molecular recognition, and the structure-based design process. This characterization can take several forms: the receptor surface itself can be delineated or described, the space adjacent to the surface can be chemically mapped, or a negative image of the protein binding region can be generated. In this report, we describe a new method of constructing a negative image through generation of a set of spheres. These spheres lie along the receptor surface, and their centers represent possible ligand atom positions. By the method in which they are constructed, these spheres carry a limited amount of energetic and chemical information in addition to their primary geometric information. We test the accuracy of the image by comparing sphere positions to the positions of bound ligand atoms and propose a figure of merit for such tests. Then, we use the spheres to orient ligands in enzyme active sites and show how they can be used to generate low scoring configurations more efficiently than other approaches that search orientation space. In addition, two novel applications of these spheres are described: they are used to help identify structural differences among families of enzymes and to suggest points for ligand modification in analog design. Proteins 30:321–336, 1998. © 1998 Wiley-Liss, Inc.     

THz frequency spectrum of protein–solvent interaction energy using a recurrence plot‐based Wiener–Khinchin method

The dynamics of a protein and the water surrounding it are coupled via nonbonded energy interactions. This coupling can exhibit a complex, nonlinear, and nonstationary nature. The THz frequency spectrum for this interaction energy characterizes both the vibration spectrum of the water hydrogen bond network, and the frequency range of large amplitude modes of proteins. We use a Recurrence Plot based Wiener–Khinchin method RPWK to calculate this spectrum, and the results are compared to those determined using the classical auto‐covariance‐based Wiener–Khinchin method WK. The frequency spectra for the total nonbonded interaction energy extracted from molecular dynamics simulations between the β‐Lactamase Inhibitory Protein BLIP, and water molecules within a 10 Å distance from the protein surface, are calculated at 150, 200, 250, and 310 K, respectively. Similar calculations are also performed for the nonbonded interaction energy between the residues 49ASP, 53TYR, and 142PHE in BLIP, with water molecules within 10 Å from each residue respectively at 150, 200, 250, and 310 K. A comparison of the results shows that RPWK performs better than WK, and is able to detect some frequency data points that WK fails to detect. This points to the importance of using methods capable of taking the complex nature of the protein–solvent energy landscape into consideration, and not to rely on standard linear methods. In general, RPWK can be a valuable addition to the analysis tools for protein molecular dynamics simulations. Proteins 2016; 84:1549–1557. © 2016 Wiley Periodicals, Inc.     

Hydrophobic docking: A proposed enhancement to molecular recognition techniques

In the classical procedures for predicting the structure of protein complexes two molecules are brought in contact at multiple relative positions, the extent of complementarity (geometric and/or energy) at the surface of contact is assessed at each position, and the best fits are retrieved. In view of the higher occurrence of hydrophobic groups at contact sites, their contribution results in more intermolecular atom–atom contacts per unit area for correct matches than for false positive fits. The hydrophobic groups are also potentially less flexible at the surface. Thus, from a practical point of view, a partial representation of the molecules based on hydrophobic groups should improve the quality of the results in finding molecular recognition sites, as compared to full representation. We tested this proposal by applying the idea to an existing geometric fit procedure and compared the results obtained with full vs. hydrophobic representations of molecules in known molecular complexes. The hydrophobic docking yielded distinctly higher signal-to-noise ratio so that the correct match is discriminated better from false positive fits. It appears that nonhydrophobic groups contribute more to false matches. The results are discussed in terms of their relevance to molecular recognition techniques as compared to energy calculations. © 1994 Wiley-Liss, Inc.     

Restricted mobility of side chains on concave surfaces of solenoid proteins may impart heightened potential for intermolecular interactions

Significant progress has been made in the determination of the protein structures with their number today passing over a hundred thousand structures. The next challenge is the understanding and prediction of protein–protein and protein–ligand interactions. In this work we address this problem by analyzing curved solenoid proteins. Many of these proteins are considered as “hub molecules” for their high potential to interact with many different molecules and to be a scaffold for multisubunit protein machineries. Our analysis of these structures through molecular dynamics simulations reveals that the mobility of the side‐chains on the concave surfaces of the solenoids is lower than on the convex ones. This result provides an explanation to the observed preferential binding of the ligands, including small and flexible ligands, to the concave surface of the curved solenoid proteins. The relationship between the landscapes and dynamic properties of the protein surfaces can be further generalized to the other types of protein structures and eventually used in the computer algorithms, allowing prediction of protein–ligand interactions by analysis of protein surfaces . Proteins 2015; 83:1654–1664. © 2015 Wiley Periodicals, Inc.     

Molecular modeling and SPRi investigations of interleukin 6 (IL6) protein and DNA aptamers

Interleukin 6 (IL6), an inflammatory response protein has major implications in immune-related inflammatory diseases. Identification of aptamers for the IL6 protein aids in diagnostic, therapeutic, and theranostic applications. Three different DNA aptamers and their interactions with IL6 protein were extensively investigated in a phosphate buffed saline (PBS) solution. Molecular-level modeling through molecular dynamics provided insights of structural, conformational changes and specific binding domains of these protein–aptamer complexes. Multiple simulations reveal consistent binding region for all protein–aptamer complexes. Conformational changes coupled with quantitative analysis of center of mass (COM) distance, radius of gyration (R_g), and number of intermolecular hydrogen bonds in each IL6 protein–aptamer complex was used to determine their binding performance strength and obtain molecular configurations with strong binding. A similarity comparison of the molecular configurations with strong binding from molecular-level modeling concurred with Surface Plasmon Resonance imaging (SPRi) for these three aptamer complexes, thus corroborating molecular modeling analysis findings. Insights from the natural progression of IL6 protein–aptamer binding modeled in this work has identified key features such as the orientation and location of the aptamer in the binding event. These key features are not readily feasible from wet lab experiments and impact the efficacy of the aptamers in diagnostic and theranostic applications.     

Molecular recognition via face center representation of a molecular surface

While docking methodologies are now frequently being developed, a careful examination of the molecular surface representation, which necessarily is employed by them, is largely overlooked. There are two important aspects here that need to be addressed: how the surface representation quantifies surface complementarity, and whether a minimal representation is employed. Although complementarity is an accepted concept regarding molecular recognition, its quantification for computation is not trivial, and requires verification. A minimal representation is important because docking searches a conformational space whose extent and/ or dimensionality grows quickly with the size of surface representation, making it especially costly with big molecules, imperfect interfaces, and changes of conformation that occur in binding. It is essential for a docking methodology to establish that it employs an accurate, concise molecular surface representation.Here we employ the face center representation of molecular surface, developed by Lin et al.,¹ to investigate the complementarity of molecular interface. We study a wide variety of complexes: protein/small ligand, oligomeric chain-chain interfaces, proteinase/protein inhibitors, antibody/antigen, NMR structures, and complexes built from unbound, separately solved structures. The complementarity is examined at different levels of reduction, and hence roughness, of the surface representation, from one that describes subatomic details to a very sparse one that captures only the prominent features on the surface. Our simulation of molecular recognition indicates that in all cases, quality interface complementarity is obtained. We show that the representation is powerful in monitoring the complementarity either in its entirety, or in selected subsets that maintain a fraction of the face centers, and is capable of supporting molecular docking at high fidelity and efficiency. Furthermore, we also demonstrate that the presence of explicit hydrogens in molecular structures may not benefit docking, and that the different classes of protein complexes and may hold slightly different degrees of interface complementarity.     

蛋白质分子表面高质量网格构建技术的研究进展

分子表面即分子边界,在一定程度上蕴含了分子的生物化学属性信息,对分子表面进行分析将有助于理解分子对接、识别和相互作用等问题。由于蛋白质分子表面的构造相对复杂,尤其是分子表面的网格化,因此寻求高效的算法构建高质量的蛋白质分子表面网格对生成光滑的分子表面、分子可视化及分子模拟都有着重要的意义。本文主要根据现有定义的蛋白质分子表面,针对近年来几种高质量分子表面网格构建的新技术进行了阐述,同时介绍了几款蛋白质分子表面可视化软件,并对它们的性能进行了简单的分析。     

Theoretical Modeling of Surface Confined Chiral Nanoporous Networks: Cruciform Molecules as Versatile Building Blocks

Patterning of solid surfaces with functional organic molecules has been a convenient route to fabricate two‐dimensional materials with programmed architecture and activities. One example is the chiral nanoporous networks that can be created via controlled self‐assembly of star‐shaped molecules under 2D confinement. In this contribution we use computer modeling to predict the formation of molecular networks in adsorbed overlayers comprising cruciform molecular building blocks equipped with discrete interaction centers. To that end, we employ the Monte Carlo simulation method combined with a coarse‐grained representation of the adsorbed molecules which are treated as collections of interconnected segments. The interaction centers within the molecules are represented by active segments whose number and distribution are adjusted. Our particular focus is on those distributions that produce prochiral molecules able to occur in adsorbed configurations being mirror images of each other (surface enantiomers). We demonstrate that, depending on size, aspect ratio, and intramolecular distribution of active sites, the surface enantiomers can co‐crystallize or segregate into extended homochiral domains with largely diversified nanosized cavities. The insights from our theoretical studies can be helpful in designing 2D chiral porous networks with potential applications in enantioselective adsorption and asymmetric heterogeneous catalysis. Chirality 27:397–404, 2015. © 2015 Wiley Periodicals, Inc.     

Effect of glycerol–water binary mixtures on the structure and dynamics of protein solutions

We have performed 20?ns of fully atomistic molecular dynamics simulations of Hen Egg-White Lysozyme in 0, 10, 20, 30, and 100% by weight of glycerol in water to better understand the microscopic physics behind the bioprotection offered by glycerol to naturally occuring biological systems. The solvent exposure of protein surface residues changes when glycerol is introduced. The dynamic behavior of the protein, as quantified by the incoherent intermediate scattering function, shows a nonmonotonic dependence on glycerol content. The fluctuations of the protein residues with respect to each other were found to be similar in all water-containing solvents, but different from the pure glycerol case. The increase in the number of protein–glycerol hydrogen bonds in glycerol–water binary mixtures explains the slowing down of protein dynamics as the glycerol content increases. We also explored the dynamic behavior of the hydration layer. We show that the short length scale dynamics of this layer are insensitive to glycerol concentration. However, the long length scale behavior shows a significant dependence on glycerol content. We also provide insights into the behavior of bound and mobile water molecules.     

Analytical shape computation of macromolecules: I. molecular area and volume through alpha shape

The size and shape of macromolecules such as proteins and nucleic acids play an important role in their functions. Prior efforts to quantify these properties have been based on various discretization or tessellation procedures involving analytical or numerical computations. In this article, we present an analytically exact method for computing the metric properties of macromolecules based on the alpha shape theory. This method uses the duality between alpha complex and the weighted Voronoi decomposition of a molecule. We describe the intuitive ideas and concepts behind the alpha shape theory and the algorithm for computing areas and volumes of macromolecules. We apply our method to compute areas and volumes of a number of protein systems. We also discuss several difficulties commonly encountered in molecular shape computations and outline methods to overcome these problems. Proteins 33:1–17, 1998. © 1998 Wiley-Liss, Inc.     

Analytically defined surfaces to analyze molecular interaction properties

Molecular surfaces are widely used for characterizing molecules and displaying and quantifying their interaction properties. Here we consider molecular surfaces defined as isocontours of a function (a sum of exponential functions centered on each atom) that approximately represents electron density. The smoothness is advantageous for surface mapping of molecular properties (e.g., electrostatic potential). By varying parameters, these surfaces can be constructed to represent the van der Waals or solvent-accessible surface of a molecular with any accuracy. We describe numerical algorithms to operate on the analytically defined surfaces. Two applications are considered: (1) We define and locate extremal points of molecular properties on the surfaces. The extremal points provide a compact representation of a property on a surface, obviating the necessity to compute values of the property on an array of surface points as is usually done; (2) a molecular surface patch or interface is projected onto a flat surface (by introducing curvilinear coordinates) with approximate conservation of area for analysis purposes. Applications to studies of protein-protein interactions are described.     

Protein side chain conformation predictions with an MMGBSA energy function

The prediction of protein side chain conformations from backbone coordinates is an important task in structural biology, with applications in structure prediction and protein design. It is a difficult problem due to its combinatorial nature. We study the performance of an “MMGBSA” energy function, implemented in our protein design program Proteus, which combines molecular mechanics terms, a Generalized Born and Surface Area (GBSA) solvent model, with approximations that make the model pairwise additive. Proteus is not a competitor to specialized side chain prediction programs due to its cost, but it allows protein design applications, where side chain prediction is an important step and MMGBSA an effective energy model. We predict the side chain conformations for 18 proteins. The side chains are first predicted individually, with the rest of the protein in its crystallographic conformation. Next, all side chains are predicted together. The contributions of individual energy terms are evaluated and various parameterizations are compared. We find that the GB and SA terms, with an appropriate choice of the dielectric constant and surface energy coefficients, are beneficial for single side chain predictions. For the prediction of all side chains, however, errors due to the pairwise additive approximation overcome the improvement brought by these terms. We also show the crucial contribution of side chain minimization to alleviate the rigid rotamer approximation. Even without GB and SA terms, we obtain accuracies comparable to SCWRL4, a specialized side chain prediction program. In particular, we obtain a better RMSD than SCWRL4 for core residues (at a higher cost), despite our simpler rotamer library. Proteins 2016; 84:803–819. © 2016 Wiley Periodicals, Inc.     

Identification of protein biochemical functions by similarity search using the molecular surface database eF-site

The identification of protein biochemical functions based on their three-dimensional structures is strongly required in the post-genome-sequencing era. We have developed a new method to identify and predict protein biochemical functions using the similarity information of molecular surface geometries and electrostatic potentials on the surfaces. Our prediction system consists of a similarity search method based on a clique search algorithm and the molecular surface database eF-site (electrostatic surface of functional-site in proteins). Using this system, functional sites similar to those of phosphoenoylpyruvate carboxy kinase were detected in several mononucleotide-binding proteins, which have different folds. We also applied our method to a hypothetical protein, MJ0226 from Methanococcus jannaschii, and detected the mononucleotide binding site from the similarity to other proteins having different folds.     

Identification of protein functions from a molecular surface database,eF-site

A bioinformatics method was developed to identify the protein surface around the functional site and to estimate the biochemical function, using a newly constructed molecular surface database named the eF-site (electrostatic surface of Functional site. Molecular surfaces of protein molecules were computed based on the atom coordinates, and the eF-site database was prepared by adding the physical properties on the constructed molecular surfaces. The electrostatic potential on each molecular surface was individually calculated solving the Poisson–Boltzmann equation numerically for the precise continuum model, and the hydrophobicity information of each residue was also included. The eF-site database is accessed by the internet (http://pi.protein.osaka-u.ac.jp/eF-site/). We have prepared four different databases, eF-site/antibody, eF-site/prosite, eF-site/P-site, and eF-site/ActiveSite, corresponding to the antigen binding sites of antibodies with the same orientations, the molecular surfaces for the individual motifs in PROSITE database, the phosphate binding sites, and the active site surfaces for the representatives of the individual protein family, respectively. An algorithm using the clique detection method as an applied graph theory was developed to search of the eF-site database, so as to recognize and discriminate the characteristic molecular surfaces of the proteins. The method identifies the active site having the similar function to those of the known proteins.