Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design

Use of solvent mapping, based on multiple-copy minimization (MCM) techniques, is common in structure-based drug discovery. The minima of small-molecule probes define locations for complementary interactions within a binding pocket. Here, we present improved methods for MCM. In particular, a Jarvis-Patrick (JP) method is outlined for grouping the final locations of minimized probes into physical clusters. This algorithm has been tested through a study of protein-protein interfaces, showing the process to be robust, deterministic, and fast in the mapping of protein "hot spots." Improvements in the initial placement of probe molecules are also described. A final application to HIV-1 protease shows how our automated technique can be used to partition data too complicated to analyze by hand. These new automated methods may be easily and quickly extended to other protein systems, and our clustering methodology may be readily incorporated into other clustering packages.     

Desmoplakin is important for proper cardiac cell-cell interactions

Normal cardiac function is maintained through dynamic interactions of cardiac cells with each other and with the extracellular matrix. These interactions are important for remodeling during cardiac growth and pathophysiological conditions. However, the precise mechanisms of these interactions remain unclear. In this study we examined the importance of desmoplakin (DSP) in cardiac cell-cell interactions. Cell-cell communication in the heart requires the formation and preservation of cell contacts by cell adhesion junctions called desmosome-like structures. A major protein component of this complex is DSP, which plays a role in linking the cytoskeletal network to the plasma membrane. Our laboratory previously generated a polyclonal antibody (1611) against the detergent soluble fraction of cardiac fibroblast plasma membrane. In attempting to define which proteins 1611 recognizes, we performed two-dimensional electrophoresis and identified DSP as one of the major proteins recognized by 1611. Immunoprecipitation studies demonstrated that 1611 was able to directly pulldown DSP. We also demonstrate that 1611 and anti-DSP antibodies co-localize in whole heart sections. Finally, using a three-dimensional in vitro cell-cell interaction assay, we demonstrate that 1611 can inhibit cell-cell interactions. These data indicate that DSP is an important protein for cell-cell interactions and affects a variety of cellular functions, including cytokine secretion.     

Hydrogen is essential for sustainability

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Full hemispherical photoelectron diffraction and Fermi surface mapping

The routine measurement of full hemispherical photoemission intensity maps gives us the possibility for the combined investigation of structural and electronic phenomena at surfaces. As an example the growth of ultrathin films of Co on Cu(111) is studied as a function of film thickness. While X-ray photoelectron diffraction (XPD) shows the early appearance of stacking faults as a precursor of the hcp structure, Fermi surface maps reveal the very fast evolution of the Co Fermi surface that can be compared to measurements on a clean Co(0001) crystal. For the system O/Rh(111), XPD brings up important structural clues, relating changes in surface reactivity to small amounts of subsurface oxygen, which forces adjacent oxygen atoms to occupy new and more reactive adsorption sites. In the course of this last study we observed for the first time the weak backscattering signals in the angular pattern of adsorbate emission. These cone-like features are extremely sensitive to the adsorbate–substrate bond length.     

Including ligand‐induced protein flexibility into protein tunnel prediction

In proteins with buried active sites, understanding how ligands migrate through the tunnels that connect the exterior of the protein to the active site can shed light on substrate specificity and enzyme function. A growing body of evidence highlights the importance of protein flexibility in the binding site on ligand binding; however, the influence of protein flexibility throughout the body of the protein during ligand entry and egress is much less characterized. We have developed a novel tunnel prediction and evaluation method named IterTunnel, which includes the influence of ligand‐induced protein flexibility, guarantees ligand egress, and provides detailed free energy information as the ligand proceeds along the egress route. IterTunnel combines geometric tunnel prediction with steered molecular dynamics in an iterative process to identify tunnels that open as a result of ligand migration and calculates the potential of mean force of ligand egress through a given tunnel. Applying this new method to cytochrome P450 2B6, we demonstrate the influence of protein flexibility on the shape and accessibility of tunnels. More importantly, we demonstrate that the ligand itself, while traversing through a tunnel, can reshape tunnels due to its interaction with the protein. This process results in the exposure of new tunnels and the closure of preexisting tunnels as the ligand migrates from the active site. © 2014 Wiley Periodicals, Inc.     

A comparison of techniques for calculating protein essential dynamics

Recently the basic theory of essential dynamics, a method for extracting large concerted motions from protein molecular dynamics trajectories, was described. Here, we introduce and test new aspects. A method for diagonalizing large covariance matrices is presented. We show that it is possible to perform essential dynamics using different subsets of atoms and compare these to the basic C-α analysis. Essential dynamics analyses are also compared to the normal modes method. The stability of the essential space during a simulation is investigated by comparing the two halves of a trajectory. Apart from the analyses in Cartesian space, the essential dynamics in ϕ/ψ torsion angle space is discussed. © 1997 by John Wiley & Sons, Inc.     

Exploring hierarchical refinement techniques for induced fit docking with protein and ligand flexibility

We present a series of molecular‐mechanics‐based protein refinement methods, including two novel ones, applied as part of an induced fit docking procedure. The methods used include minimization; protein and ligand sidechain prediction; a hierarchical ligand placement procedure similar to a‐priori protein loop predictions; and a minimized Monte Carlo approach using normal mode analysis as a move step. The results clearly indicate the importance of a proper opening of the active site backbone, which might not be accomplished when the ligand degrees of freedom are prioritized. The most accurate method consisted of the minimized Monte Carlo procedure designed to open the active site followed by a hierarchical optimization of the sidechain packing around a mobile flexible ligand. The methods have been used on a series of 88 protein‐ligand complexes including both cross‐docking and apo‐docking members resulting in complex conformations determined to within 2.0 Å heavy‐atom RMSD in 75% of cases where the protein backbone rearrangement upon binding is less than 1.0 Å α‐carbon RMSD. We also demonstrate that physics‐based all‐atom potentials can be more accurate than docking‐style potentials when complexes are sufficiently refined. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

Assessing protein loop flexibility by hierarchical Monte Carlo sampling

Loop flexibility is often crucial to protein biological function in solution. We report a new Monte Carlo method for generating conformational ensembles for protein loops and cyclic peptides. The approach incorporates the triaxial loop closure method which addresses the inverse kinematic problem for generating backbone move sets that do not break the loop. Sidechains are sampled together with the backbone in a hierarchical way, making it possible to make large moves that cross energy barriers. As an initial application, we apply the method to the flexible loop in triosephosphate isomerase that caps the active site, and demonstrate that the resulting loop ensembles agree well with key observations from previous structural studies. We also demonstrate, with 3 other test cases, the ability to distinguish relatively flexible and rigid loops within the same protein.     

Improved mapping of protein binding sites

Computational mapping methods place molecular probes – small molecules or functional groups – on a protein surface in order to identify the most favorable binding positions by calculating an interaction potential. Mapping is an important step in a number of flexible docking and drug design algorithms. We have developed improved algorithms for mapping protein surfaces using small organic molecules as molecular probes. The calculations reproduce the binding of eight organic solvents to lysozyme as observed by NMR, as well as the binding of four solvents to thermolysin, in good agreement with x-ray data. Application to protein tyrosine phosphatase 1B shows that the information provided by the mapping can be very useful for drug design. We also studied why the organic solvents bind in the active site of proteins, in spite of the availability of alternative pockets that can very tightly accommodate some of the probes. A possible explanation is that the binding in the relatively large active site retains a number of rotational states, and hence leads to smaller entropy loss than the binding elsewhere else. Indeed, the mapping reveals that the clusters of the ligand molecules in the protein's active site contain different rotational-translational conformers, which represent different local minima of the free energy surface. In order to study the transitions between different conformers, reaction path and molecular dynamics calculations were performed. Results show that most of the rotational states are separated by low free energy barriers at the experimental temperature, and hence the entropy of binding in the active site is expected to be high.     

Biomedical relevance of two-dimensional protein mapping

State-of-the-art and future perspectives are discussed for the application of two-dimensional protein maps to basic medical research and routine clinical chemistry problems. Despite the technical advances that allow effective processing of a large number of samples and the refinement of devices and procedures for image analysis, at present two-dimensional maps are mostly confined to research purposes, i.e. to the inventory of normal constituents of body fluids and tissues on the one hand, and to qualitative-quantitative alterations of some protein spots in a number of instances (genetic, degenerative, infectious or xenobiotic diseases) on the other. It is hoped that in some instances a single primarily affected component will be able to be identified and then specifically tested (for instance by immunological means) as a diagnostic marker, but complex pathological patterns would still require the analysis of a large number of peptides at the resolution level only afforded by two dimensions. Further simplification of the protocols, for example with ready-made gels, and data reduction systems might then allow the application of the technique to be extended to general clinical laboratories.     

Docking validation resources: protein family and ligand flexibility experiments

A database consisting of 780 ligand-receptor complexes, termed SB2010, has been derived from the Protein Databank to evaluate the accuracy of docking protocols for regenerating bound ligand conformations. The goal is to provide easily accessible community resources for development of improved procedures to aid virtual screening for ligands with a wide range of flexibilities. Three core experiments using the program DOCK, which employ rigid (RGD), fixed anchor (FAD), and flexible (FLX) protocols, were used to gauge performance by several different metrics: (1) global results, (2) ligand flexibility, (3) protein family, and (4) cross-docking. Global spectrum plots of successes and failures vs rmsd reveal well-defined inflection regions, which suggest the commonly used 2 ? criteria is a reasonable choice for defining success. Across all 780 systems, success tracks with the relative difficulty of the calculations: RGD (82.3%) > FAD (78.1%) > FLX (63.8%). In general, failures due to scoring strongly outweigh those due to sampling. Subsets of SB2010 grouped by ligand flexibility (7-or-less, 8-to-15, and 15-plus rotatable bonds) reveal that success degrades linearly for FAD and FLX protocols, in contrast to RGD, which remains constant. Despite the challenges associated with FLX anchor orientation and on-the-fly flexible growth, success rates for the 7-or-less (74.5%) and, in particular, the 8-to-15 (55.2%) subset are encouraging. Poorer results for the very flexible 15-plus set (39.3%) indicate substantial room for improvement. Family-based success appears largely independent of ligand flexibility, suggesting a strong dependence on the binding site environment. For example, zinc-containing proteins are generally problematic, despite moderately flexible ligands. Finally, representative cross-docking examples, for carbonic anhydrase, thermolysin, and neuraminidase families, show the utility of family-based analysis for rapid identification of particularly good or bad docking trends, and the type of failures involved (scoring/sampling), which will likely be of interest to researchers making specific receptor choices for virtual screening. SB2010 is available for download at http://rizzolab.org .     

Quantifying the protein core flexibility through analysis of cavity formation

We present an extensive analysis of cavity statistics in the interior of three different proteins, in liquid n-hexane, and in water performed using molecular-dynamics simulations. The heterogeneity of packing density over atomic length scales in different parts of proteins is evident in the wide range of values observed for the average cavity size, the probability of cavity formation, and the corresponding free energy of hard-sphere insertion. More interestingly, however, the distribution of cavity sizes observed at various points in the protein interior is surprisingly homogeneous in width. That width is significantly smaller than that measured for similar distributions in liquid n-hexane or water, indicating that protein interior is much less flexible than liquid hexane. The width of the cavity size distribution correlates well with the experimental isothermal compressibility data for liquids and proteins. An analysis of cavity statistics thus provides an efficient method to quantify local properties, such as packing, stiffness, or compressibility in heterogeneous condensed media.     

Focused grid‐based resampling for protein docking and mapping

The fast Fourier transform (FFT) sampling algorithm has been used with success in application to protein‐protein docking and for protein mapping, the latter docking a variety of small organic molecules for the identification of binding hot spots on the target protein. Here we explore the local rather than global usage of the FFT sampling approach in docking applications. If the global FFT based search yields a near‐native cluster of docked structures for a protein complex, then focused resampling of the cluster generally leads to a substantial increase in the number of conformations close to the native structure. In protein mapping, focused resampling of the selected hot spot regions generally reveals further hot spots that, while not as strong as the primary hot spots, also contribute to ligand binding. The detection of additional ligand binding regions is shown by the improved overlap between hot spots and bound ligands. © 2016 Wiley Periodicals, Inc.     

A simple method to predict protein flexibility using secondary chemical shifts

Protein motions play a critical role in many biological processes, such as enzyme catalysis, allosteric regulation, antigen-antibody interactions, and protein-DNA binding. NMR spectroscopy occupies a unique place among methods for investigating protein dynamics due to its ability to provide site-specific information about protein motions over a large range of time scales. However, most NMR methods require a detailed knowledge of the 3D structure and/or the collection of additional experimental data (NOEs, T1, T2, etc.) to accurately measure protein dynamics. Here we present a simple method based on chemical shift data that allows accurate, quantitative, site-specific mapping of protein backbone mobility without the need of a three-dimensional structure or the collection and analysis of NMR relaxation data. Further, we show that this chemical shift method is able to quantitatively predict per-residue RMSD values (from both MD simulations and NMR structural ensembles) as well as model-free backbone order parameters.     

Constrained proper sampling of conformations of transition state ensemble of protein folding

Characterizing the conformations of protein in the transition state ensemble (TSE) is important for studying protein folding. A promising approach pioneered by Vendruscolo et al. [Nature (London) 409, 641 (2001)] to study TSE is to generate conformations that satisfy all constraints imposed by the experimentally measured φ values that provide information about the native likeness of the transition states. Fai?sca et al. [J. Chem. Phys. 129, 095108 (2008)] generated conformations of TSE based on the criterion that, starting from a TS conformation, the probabilities of folding and unfolding are about equal through Markov Chain Monte Carlo (MCMC) simulations. In this study, we use the technique of constrained sequential Monte Carlo method [Lin et al., J. Chem. Phys. 129, 094101 (2008); Zhang et al. Proteins 66, 61 (2007)] to generate TSE conformations of acylphosphatase of 98 residues that satisfy the φ-value constraints, as well as the criterion that each conformation has a folding probability of 0.5 by Monte Carlo simulations. We adopt a two stage process and first generate 5000 contact maps satisfying the φ-value constraints. Each contact map is then used to generate 1000 properly weighted conformations. After clustering similar conformations, we obtain a set of properly weighted samples of 4185 candidate clusters. Representative conformation of each of these cluster is then selected and 50 runs of Markov chain Monte Carlo (MCMC) simulation are carried using a regrowth move set. We then select a subset of 1501 conformations that have equal probabilities to fold and to unfold as the set of TSE. These 1501 samples characterize well the distribution of transition state ensemble conformations of acylphosphatase. Compared with previous studies, our approach can access much wider conformational space and can objectively generate conformations that satisfy the φ-value constraints and the criterion of 0.5 folding probability without bias. In contrast to previous studies, our results show that transition state conformations are very diverse and are far from nativelike when measured in cartesian root-mean-square deviation (cRMSD): the average cRMSD between TSE conformations and the native structure is 9.4 A? for this short protein, instead of 6 A? reported in previous studies. In addition, we found that the average fraction of native contacts in the TSE is 0.37, with enrichment in native-like β-sheets and a shortage of long range contacts, suggesting such contacts form at a later stage of folding. We further calculate the first passage time of folding of TSE conformations through calculation of physical time associated with the regrowth moves in MCMC simulation through mapping such moves to a Markovian state model, whose transition time was obtained by Langevin dynamics simulations. Our results indicate that despite the large structural diversity of the TSE, they are characterized by similar folding time. Our approach is general and can be used to study TSE in other macromolecules.     

The role of conformational flexibility on protein supercharging in native electrospray ionization

Effects of covalent intramolecular bonds, either native disulfide bridges or chemical crosslinks, on ESI supercharging of proteins from aqueous solutions were investigated. Chemically modifying cytochrome c with up to seven crosslinks or ubiquitin with up to two crosslinks did not affect the average or maximum charge states of these proteins in the absence of m-nitrobenzyl alcohol (m-NBA), but the extent of supercharging induced by m-NBA increased with decreasing numbers of crosslinks. For the model random coil polypeptide reduced/alkylated RNase A, a decrease in charging with increasing m-NBA concentration attributable to reduced surface tension of the ESI droplet was observed, whereas native RNase A electrosprayed from these same solutions exhibited enhanced charging. The inverse relationship between the extent of supercharging and the number of intramolecular crosslinks for folded proteins, as well as the absence of supercharging for proteins that are random coils in aqueous solution, indicate that conformational restrictions induced by the crosslinks reduce the extent of supercharging. These results provide additional evidence that protein and protein complex supercharging from aqueous solution is primarily due to partial or significant unfolding that occurs as a result of chemical and/or thermal denaturation induced by the supercharging reagent late in the ESI droplet lifetime.     

Active site pressurization: a new tool for structure-guided drug design and other studies of protein flexibility

We present a new molecular dynamics methodology to assist in structure-based drug design and other studies that seek to predict protein deformability. Termed Active Site Pressurization (ASP), the new methodology simply injects a resin into the ligand binding-site of a protein during the course of a molecular dynamics simulation such that novel, energetically reasonable protein conformations are generated in an unbiased way that may be better representations of the ligand binding conformation than are currently available. Here we apply two different versions of the ASP methodology to three proteins, cytochrome P450cam, PcrA helicase, and glycogen synthase kinase 3beta (GSK3beta), and show that the method is capable of inducing significant conformational changes when compared to the X-ray crystal structures. Application of the ASP methodology therefore provides a view of binding site flexibility that is a rich source of data for inclusion in a variety of further investigations, including high-throughput virtual screening, lead hopping, revealing alternative modes of deformation, and revealing hidden exit and entrance tunnels.