Finding and characterizing tunnels in macromolecules with application to ion channels and pores

Equilibrium landscape of ingress/egress channels and gating residues of the Cytochrome P450 3A4

The Cytochrome P450 (CYP) enzymes metabolize a variety of drugs, which may potentially lead to toxicity or reduced efficacy when drugs are co-administered. These drug-drug interactions are often manifested by CYP3A4, the most prevalent of all CYP isozymes. We carried out multiple MD simulations employing CAVER to quantify the channels, and Hidden Markov Models (HMM) to characterize the behavior of the gating residues. We discuss channel properties, bottleneck residues with respect to their likelihood to deem the respective channel ingress or egress, gating residues regarding their open or closed states, and channel location relative to the membrane. Channels do not display coordinated motion and randomly transition between different conformations. Gateway residues also behave in a random fashion. Our findings shed light on the equilibrium behavior of the gating residues and channels in the apo state.

CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm

Numerous computational methods, including evolutionary-based, energy-based, and geometrical-based methods, are utilized to identify cavities inside proteins. Cavity information aids protein function annotation, drug design, poly-pharmacology, and allosteric site investigation. This article introduces "flow transfer algorithm" for rapid and effective identification of diverse protein cavities through multidimensional cavity scan. Initially, it identifies delimiter and susceptible tetrahedra to establish boundary regions and provide seed tetrahedra. Seed tetrahedron faces are precisely scanned using the maximum circle radius to transfer seed flow to neighboring tetrahedra. Seed flow continues until terminated by boundaries or forbidden faces, where a face is forbidden if the estimated maximum circle radius is less or equal to the user-defined maximum circle radius. After a seed scanning, tetrahedra involved in the flow are clustered to locate the cavity. The CRAFT web interface integrates this algorithm for protein cavity identification with enhanced user control. It supports proteins with cofactors, hydrogens, and ligands and provides comprehensive features such as 3D visualization, cavity physicochemical properties, percentage contribution graphs, and highlighted residues for each cavity. CRAFT can be accessed through its web interface at http://pitools.niper.ac.in/CRAFT , complemented by the command version available at https://github.com/PGlab-NIPER/CRAFT/ .Scientific contribution: Flow transfer algorithm is a novel geometric approach for accurate and reliable prediction of diverse protein cavities. This algorithm employs a distinct concept involving maximum circle radius within the 3D Delaunay triangulation to address diverse van der Waals radii while existing methods overlook atom specific van der Waals radii or rely on complex weighted geometric techniques.

RPflex: A Coarse-Grained Network Model for RNA Pocket Flexibility Study

RNA regulates various biological processes, such as gene regulation, RNA splicing, and intracellular signal transduction. RNA’s conformational dynamics play crucial roles in performing its diverse functions. Thus, it is essential to explore the flexibility characteristics of RNA, especially pocket flexibility. Here, we propose a computational approach, RPflex, to analyze pocket flexibility using the coarse-grained network model. We first clustered 3154 pockets into 297 groups by similarity calculation based on the coarse-grained lattice model. Then, we introduced the flexibility score to quantify the flexibility by global pocket features. The results show strong correlations between the flexibility scores and root-mean-square fluctuation (RMSF) values, with Pearson correlation coefficients of 0.60, 0.76, and 0.53 in Testing Sets I–III. Considering both flexibility score and network calculations, the Pearson correlation coefficient was increased to 0.71 in flexible pockets on Testing Set IV. The network calculations reveal that the long-range interaction changes contributed most to flexibility. In addition, the hydrogen bonds in the base–base interactions greatly stabilize the RNA structure, while backbone interactions determine RNA folding. The computational analysis of pocket flexibility could facilitate RNA engineering for biological or medical applications.

Dynamic Structural Biology Experiments at XFEL or Synchrotron Sources

Macromolecular crystallography (MX) leverages the methods of physics and the language of chemistry to reveal fundamental insights into biology. Often beautifully artistic images present MX results to support profound functional hypotheses that are vital to entire life science research community. Over the past several decades, synchrotrons around the world have been the workhorses for X-ray diffraction data collection at many highly automated beamlines. The newest tools include X-ray-free electron lasers (XFELs) located at facilities in the USA, Japan, Korea, Switzerland, and Germany that deliver about nine orders of magnitude higher brightness in discrete femtosecond long pulses. At each of these facilities, new serial femtosecond crystallography (SFX) strategies exploit slurries of micron-size crystals by rapidly delivering individual crystals into the XFEL X-ray interaction region, from which one diffraction pattern is collected per crystal before it is destroyed by the intense X-ray pulse. Relatively simple adaptions to SFX methods produce time-resolved data collection strategies wherein reactions are triggered by visible light illumination or by chemical diffusion/mixing. Thus, XFELs provide new opportunities for high temporal and spatial resolution studies of systems engaged in function at physiological temperature. In this chapter, we summarize various issues related to microcrystal slurry preparation, sample delivery into the X-ray interaction region, and some emerging strategies for time-resolved SFX data collection.

Recent results in time resolved serial femtosecond crystallography at XFELs

Time-resolved serial femtosecond crystallography (tr-SFX) methods exploit slurries of crystalline samples that range in size from hundreds of nanometers to a few tens of micrometers, at near-physiological temperature and pressure, to generate atomic resolution models and probe authentic function with the same experiment. 'Dynamic structural biology' is often used to encompass the research philosophy and techniques. Reaction cycles for tr-SFX studies are initiated by photons or ligand addition/mixing strategies, wherein the latter are potentially generalizable across enzymology. Thus, dynamic structural biology often creates stop-motion molecular movies of macromolecular function. In metal-dependent systems, complementary spectroscopic information can also be collected from the same samples and X-ray pulses, which provides even more detailed mechanistic insights. These types of experimental data also complement quantum mechanical and classical dynamics numerical calculations. Correlated structural-functional results will yield more detailed mechanistic insights and will likely translate into better drugs and treatments impacting human health, and better catalysis for clean energy and agriculture.

X-ray Crystal Structures of the Influenza M2 Proton Channel Drug-Resistant V27A Mutant Bound to a Spiro-Adamantyl Amine Inhibitor Reveal the Mechanism of Adamantane Resistance

The V27A mutation confers adamantane resistance on the influenza A matrix 2 (M2) proton channel and is becoming more prevalent in circulating populations of influenza A virus. We have used X-ray crystallography to determine structures of a spiro-adamantyl amine inhibitor bound to M2(22-46) V27A and also to M2(21-61) V27A in the Inwardclosed conformation. The spiro-adamantyl amine binding site is nearly identical for the two crystal structures. Compared to the M2 "wild type" (WT) with valine at position 27, we observe that the channel pore is wider at its N-terminus as a result of the V27A mutation and that this removes V27 side chain hydrophobic interactions that are important for binding of amantadine and rimantadine. The spiro-adamantyl amine inhibitor blocks proton conductance in the WT and V27A mutant channels by shifting its binding site in the pore depending on which residue is present at position 27. Additionally, in the structure of the M2(21-61) V27A construct, the C-terminus of the channel is tightly packed relative to that of the M2(22-46) construct. We observe that residues Asp44, Arg45, and Phe48 face the center of the channel pore and would be well-positioned to interact with protons exiting the M2 channel after passing through the His37 gate. A 300 ns molecular dynamics simulation of the M2(22-46) V27A-spiro-adamantyl amine complex predicts with accuracy the position of the ligands and waters inside the pore in the X-ray crystal structure of the M2(22-46) V27A complex.

Differences in the path to exit the ribosome across the three domains of life

The ribosome exit tunnel is an important structure involved in the regulation of translation and other essential functions such as protein folding. By comparing 20 recently obtained cryo-EM and X-ray crystallography structures of the ribosome from all three domains of life, we here characterize the key similarities and differences of the tunnel across species. We first show that a hierarchical clustering of tunnel shapes closely reflects the species phylogeny. Then, by analyzing the ribosomal RNAs and proteins, we explain the observed geometric variations and show direct association between the conservations of the geometry, structure and sequence. We find that the tunnel is more conserved in the upper part close to the polypeptide transferase center, while in the lower part, it is substantially narrower in eukaryotes than in bacteria. Furthermore, we provide evidence for the existence of a second constriction site in eukaryotic exit tunnels. Overall, these results have several evolutionary and functional implications, which explain certain differences between eukaryotes and prokaryotes in their translation mechanisms. In particular, they suggest that major co-translational functions of bacterial tunnels were externalized in eukaryotes, while reducing the tunnel size provided some other advantages, such as facilitating the nascent chain elongation and enabling antibiotic resistance.

CavVis-A Field-of-View Geometric Algorithm for Protein Cavity Detection

Several geometric-based methods have been developed for the last two to three decades to detect and identify cavities (i.e., putative binding sites) on proteins, as needed to study protein-ligand interactions and protein docking. This paper introduces a new protein cavity method, called CavVis, which combines voxelization (i.e., a grid of voxels) and an analytic formulation of Gaussian surfaces that approximates the solvent-excluded surface. This method builds upon visibility of points on protein surface to find its cavities. Specifically, the visibility criterion combines three concepts we borrow from computer graphics, the field-of-view of each surface point, voxel ray casting, and back-face culling.

Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey

Detecting and analyzing protein cavities provides significant information about active sites for biological processes (e.g., protein-protein or protein-ligand binding) in molecular graphics and modeling. Using the three-dimensional structure of a given protein (i.e., atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels, and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution-based, energy-based, and geometry-based. Our survey focuses on geometric algorithms, whose taxonomy is extended to include not only sphere-, grid-, and tessellation-based methods, but also surface-based, hybrid geometric, consensus, and time-varying methods. Finally, we detail those techniques that have been customized for GPU (Graphics Processing Unit) computing.

CAVER: Algorithms for Analyzing Dynamics of Tunnels in Macromolecules

The biological function of a macromolecule often requires that a small molecule or ion is transported through its structure. The transport pathway often leads through void spaces in the structure. The properties of transport pathways change significantly in time; therefore, the analysis of a trajectory from molecular dynamics rather than of a single static structure is needed for understanding the function of pathways. The identification and analysis of transport pathways are challenging because of the high complexity and diversity of macromolecular shapes, the thermal motion of their atoms, and the large amount of conformations needed to properly describe conformational space of protein structure. In this paper, we describe the principles of the CAVER 3.0 algorithms for the identification and analysis of properties of transport pathways both in static and dynamic structures. Moreover, we introduce the improved clustering solution for finding tunnels in macromolecules, which is included in the latest CAVER 3.02 version. Voronoi diagrams are used to identify potential pathways in each snapshot of a molecular dynamics trajectory and clustering is then used to find the correspondence between tunnels from different snapshots. Furthermore, the geometrical properties of pathways and their evolution in time are computed and visualized.

PrinCCes: Continuity-based geometric decomposition and systematic visualization of the void repertoire of proteins

Grooves and pockets on the surface, channels through the protein, the chambers or cavities, and the tunnels connecting the internal points to each other or to the external fluid environment are fundamental determinants of a wide range of biological functions. PrinCCes (Protein internal Channel & Cavity estimation) is a computer program supporting the visualization of voids. It includes a novel algorithm for the decomposition of the entire void volume of the protein or protein complex to individual entities. The decomposition is based on continuity. An individual void is defined by uninterrupted extension in space: a spherical probe can freely move between any two internal locations of a continuous void. Continuous voids are detected irrespective of their topological complexity, they may contain any number of holes and bifurcations. The voids of a protein can be visualized one by one or in combinations as triangulated surfaces. The output is automatically exported to free VMD (Visual Molecular Dynamics) or Chimera software, allowing the 3D rotation of the surfaces and the production of publication quality images. PrinCCes with graphic user interface and command line versions are available for MS Windows and Linux. The source code and executable can be downloaded at any of the following links: http://scholar.semmelweis.hu/czirjakgabor/s/princces/#t1 https://github.com/CzirjakGabor/PrinCCes http://1drv.ms/1bP9iJ3.

CHEXVIS: a tool for molecular channel extraction and visualization

Background

Understanding channel structures that lead to active sites or traverse the molecule is important in the study of molecular functions such as ion, ligand, and small molecule transport. Efficient methods for extracting, storing, and analyzing protein channels are required to support such studies. Further, there is a need for an integrated framework that supports computation of the channels, interactive exploration of their structure, and detailed visual analysis of their properties.

Results

We describe a method for molecular channel extraction based on the alpha complex representation. The method computes geometrically feasible channels, stores both the volume occupied by the channel and its centerline in a unified representation, and reports significant channels. The representation also supports efficient computation of channel profiles that help understand channel properties. We describe methods for effective visualization of the channels and their profiles. These methods and the visual analysis framework are implemented in a software tool, ChExVis. We apply the method on a number of known channel containing proteins to extract pore features. Results from these experiments on several proteins show that ChExVis performance is comparable to, and in some cases, better than existing channel extraction techniques. Using several case studies, we demonstrate how ChExVis can be used to study channels, extract their properties and gain insights into molecular function.

Conclusion

ChExVis supports the visual exploration of multiple channels together with their geometric and physico-chemical properties thereby enabling the understanding of the basic biology of transport through protein channels. The ChExVis web-server is freely available at http://vgl.serc.iisc.ernet.in/chexvis/. The web-server is supported on all modern browsers with latest Java plug-in.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0545-9) contains supplementary material, which is available to authorized users.

Visual cavity analysis in molecular simulations

Molecular surfaces provide a useful mean for analyzing interactions between biomolecules; such as identification and characterization of ligand binding sites to a host macromolecule. We present a novel technique, which extracts potential binding sites, represented by cavities, and characterize them by 3D graphs and by amino acids. The binding sites are extracted using an implicit function sampling and graph algorithms. We propose an advanced cavity exploration technique based on the graph parameters and associated amino acids. Additionally, we interactively visualize the graphs in the context of the molecular surface. We apply our method to the analysis of MD simulations of Proteinase 3, where we verify the previously described cavities and suggest a new potential cavity to be studied.

MOLE 2.0: advanced approach for analysis of biomacromolecular channels

BACKGROUND

Channels and pores in biomacromolecules (proteins, nucleic acids and their complexes) play significant biological roles, e.g., in molecular recognition and enzyme substrate specificity.

RESULTS

We present an advanced software tool entitled MOLE 2.0, which has been designed to analyze molecular channels and pores. Benchmark tests against other available software tools showed that MOLE 2.0 is by comparison quicker, more robust and more versatile. As a new feature, MOLE 2.0 estimates physicochemical properties of the identified channels, i.e., hydropathy, hydrophobicity, polarity, charge, and mutability. We also assessed the variability in physicochemical properties of eighty X-ray structures of two members of the cytochrome P450 superfamily.

CONCLUSION

Estimated physicochemical properties of the identified channels in the selected biomacromolecules corresponded well with the known functions of the respective channels. Thus, the predicted physicochemical properties may provide useful information about the potential functions of identified channels. The MOLE 2.0 software is available at http://mole.chemi.muni.cz.

CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures

Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

MOLEonline 2.0: interactive web-based analysis of biomacromolecular channels

Biomolecular channels play important roles in many biological systems, e.g. enzymes, ribosomes and ion channels. This article introduces a web-based interactive MOLEonline 2.0 application for the analysis of access/egress paths to interior molecular voids. MOLEonline 2.0 enables platform-independent, easy-to-use and interactive analyses of (bio)macromolecular channels, tunnels and pores. Results are presented in a clear manner, making their interpretation easy. For each channel, MOLEonline displays a 3D graphical representation of the channel, its profile accompanied by a list of lining residues and also its basic physicochemical properties. The users can tune advanced parameters when performing a channel search to direct the search according to their needs. The MOLEonline 2.0 application is freely available via the Internet at http://ncbr.muni.cz/mole or http://mole.upol.cz.

Use of spectroscopic, zeta potential and molecular dynamic techniques to study the interaction between human holo-transferrin and two antagonist drugs: comparison of binary and ternary systems

For the first time, the binding of ropinirole hydrochloride (ROP) and aspirin (ASA) to human holo-transferrin (hTf) has been investigated by spectroscopic approaches (fluorescence quenching, synchronous fluorescence, time-resolved fluorescence, three-dimensional fluorescence, UV-vis absorption, circular dichroism, resonance light scattering), as well as zeta potential and molecular modeling techniques, under simulated physiological conditions. Fluorescence analysis was used to estimate the effect of the ROP and ASA drugs on the fluorescence of hTf as well as to define the binding and quenching properties of binary and ternary complexes. The synchronized fluorescence and three-dimensional fluorescence spectra demonstrated some micro-environmental and conformational changes around the Trp and Tyr residues with a faint red shift. Thermodynamic analysis displayed the van der Waals forces and hydrogen bonds interactions are the major acting forces in stabilizing the complexes. Steady-state and time-resolved fluorescence data revealed that the fluorescence quenching of complexes are static mechanism. The effect of the drugs aggregating on the hTf resulted in an enhancement of the resonance light scattering (RLS) intensity. The average binding distance between were computed according to the forster non-radiation energy transfer theory. The circular dichroism (CD) spectral examinations indicated that the binding of the drugs induced a conformational change of hTf. Measurements of the zeta potential indicated that the combination of electrostatic and hydrophobic interactions between ROP, ASA and hTf formed micelle-like clusters. The molecular modeling confirmed the experimental results. This study is expected to provide important insight into the interaction of hTf with ROP and ASA to use in various toxicological and therapeutic processes.

Software tools for identification, visualization and analysis of protein tunnels and channels

Protein structures contain highly complex systems of voids, making up specific features such as surface clefts or grooves, pockets, protrusions, cavities, pores or channels, and tunnels. Many of them are essential for the migration of solvents, ions and small molecules through proteins, and their binding to the functional sites. Analysis of these structural features is very important for understanding of structure-function relationships, for the design of potential inhibitors or proteins with improved functional properties. Here we critically review existing software tools specialized in rapid identification, visualization, analysis and design of protein tunnels and channels. The strengths and weaknesses of individual tools are reported together with examples of their applications for the analysis and engineering of various biological systems. This review can assist users with selecting a proper software tool for study of their biological problem as well as highlighting possible avenues for further development of existing tools. Development of novel descriptors representing not only geometry, but also electrostatics, hydrophobicity or dynamics, is needed for reliable identification of biologically relevant tunnels and channels.

Identifying continuous pores in protein structures with PROPORES by computational repositioning of gating residues

Proteins containing concavities such as pockets, cavities, and tunnels or pores perform important functions in ligand-induced signal transduction, enzymatic catalysis, and in facilitating the permeation of small molecules through membranes. Computational algorithms for identifying such shapes are therefore of great use for studying the mechanisms of these reactions. We developed the novel toolkit PROPORES for pore identification and applied our program to the systems aquaporin, tryptophan synthase, leucine transporter, and acetylcholinesterase. As a novel feature, the program checks whether access to occluded ligand binding pockets or blocked channels can be achieved by systematically rotating side chains of the gating residues. In this way, we obtain a more flexible view of the putative structural adaptability of protein structures. For the four systems mentioned, the new method was able to identify connections between pores that are separated in the X-ray structures or to connect internal pores with the protein surrounding. The software is available from http://gepard.bioinformatik.uni-saarland.de/software/propores/.

A Combined Metadynamics and Umbrella Sampling Method for the Calculation of Ion Permeation Free Energy Profiles

Free energy calculations are one of the most useful methods for the study of ion transport mechanisms through confined spaces such as protein ion channels. Their reliability depends on a correctly defined reaction coordinate (RC). A straight line is usually not a proper RC for such complicated processes so in this work a combined metadynamics/umbrella sampling (MTD/US) method is proposed. In the combined method, the ion transport pathway is first identified by the MTD method and then the free energy profile or potential of mean force (PMF) along the path is calculated using umbrella sampling. This combined method avoids the discontinuity problem often associated with normal umbrella sampling calculations that assume a straight line RC and it provides a more physically accurate PMF for such processes. The method is demonstrated for the proton transport process through the protein channel of aquaporin-1.

Effect of the F610A mutation on substrate extrusion in the AcrB transporter: explanation and rationale by molecular dynamics simulations

The tripartite efflux pump AcrAB-TolC is responsible for the intrinsic and acquired multidrug resistance in Escherichia coli. Its active part, the homotrimeric transporter AcrB, is in charge of the selective binding of substrates and energy transduction. The mutation F610A has been shown to significantly reduce the minimum inhibitory concentration of doxorubicin and many other substrates, although F610 does not appear to interact strongly with them. Biochemical study of transport kinetics in AcrB is not yet possible, except for some β-lactams, and other techniques should supply this important information. Therefore, in this work, we assess the impact of the F610A mutation on the functionality of AcrB by means of computational techniques, using doxorubicin as substrate. We found that the compound slides deeply inside the binding pocket after mutation, increasing the strength of the interaction. During subsequent conformational alterations of the transporter, doxorubicin was either not extruded from the binding site or displaced along a direction other than the one associated with extrusion. Our study indicates how subtle interactions determine the functionality of multidrug transporters, since decreased transport might not be simplistically correlated to decreased substrate binding affinity.

dxTuber: detecting protein cavities, tunnels and clefts based on protein and solvent dynamics

Empty space in a protein structure can provide valuable insight into protein properties such as internal hydration, structure stabilization, substrate translocation, storage compartments or binding sites. This information can be visualized by means of cavity analysis. Numerous tools are available depicting cavities directly or identifying lining residues. So far, all available techniques base on a single conformation neglecting any form of protein and cavity dynamics. Here we report a novel, grid-based cavity detection method that uses protein and solvent residence probabilities derived from molecular dynamics simulations to identify (I) internal cavities, (II) tunnels or (III) clefts on the protein surface. Driven by a graphical user interface, output can be exported in PDB format where cavities are described as individually selectable groups of adjacent voxels representing regions of high solvent residence probability. Cavities can be analyzed in terms of solvent density, cavity volume and cross-sectional area along a principal axis. To assess dxTuber performance we performed test runs on a set of six example proteins representing the three main classes of protein cavities and compared our findings to results obtained with SURFNET, CAVER and PyMol.

Structural and dynamic mechanisms for the function and inhibition of the M2 proton channel from influenza A virus

The M2 proton channel from influenza A virus, a prototype for a class of viral ion channels known as viroporins, conducts protons along a chain of water molecules and ionizable sidechains, including His37. Recent studies highlight a delicate interplay between protein folding, proton binding, and proton conduction through the channel. Drugs inhibit proton conduction by binding to an aqueous cavity adjacent to M2's proton-selective filter, thereby blocking access of proton to the filter, and altering the energetic landscape of the channel and the energetics of proton-binding to His37.

Protein pockets: inventory, shape, and comparison

The shape of the protein surface dictates what interactions are possible with other macromolecules, but defining discrete pockets or possible interaction sites remains difficult. First, there is the problem of defining the extent of the pocket. Second, one has to characterize the shape of each pocket. Third, one needs to make quantitative comparisons between pockets on different proteins. An elegant solution to these problems is to sort all surface and solvent points by travel depth and then collect a hierarchical tree of pockets. The connectivity of the tree is determined via the deepest saddle points between each pair of neighboring pockets. The resulting pocket surfaces tessellate the entire protein surface, producing a complete inventory of pockets. This method of identifying pockets also allows one to easily compute important shape metrics, including the problematic pocket volume, surface area, and mouth size. Pockets are also annotated with their lining residue lists and polarity and with other residue-based properties. Using this tree and the various shape metrics pockets can be merged, grouped, or filtered for further analysis. Since this method includes the entire surface, it guarantees that any pocket of interest will be found among the output pockets, unlike all previous methods of pocket identification. The resulting hierarchy of pockets is easy to visualize and aids users in higher level analysis. Comparison of pockets is done by using the shape metrics, avoiding the complex shape alignment problem. Example applications show that the method facilitates pocket comparison along mutational or time-dependent series. Pockets from families of proteins can be examined using multiple pocket tree alignments to see how ligand binding sites or how other pockets have changed with evolution. Our method is called CLIPPERS for complete liberal inventory of protein pockets elucidating and reporting on shape.

3V: cavity, channel and cleft volume calculator and extractor

As larger macromolecular structures become available, there is a growing need to understand their ‘internal’ volumes—such as deep clefts, channels and cavities—as these often play critical roles in their function. The 3V web server can automatically extract and comprehensively analyze all the internal volumes from input RNA and protein structures. It rapidly finds internal volumes by taking the difference between two rolling-probe solvent-excluded surfaces, one with as large as possible a probe radius and the other with a solvent radius (typically 1.5 Å for water). The outputs are volumetric representations, both as images and downloadable files, which can be used for further analysis.

The 3V server and source code are available from http://3vee.molmovdb.org.

Shape and evolution of thermostable protein structure

Organisms evolved at high temperatures must maintain their proteins' structures in the face of increased thermal disorder. This challenge results in differences in residue utilization and overall structure. Focusing on thermostable/mesostable pairs of homologous structures, we have examined these differences using novel geometric measures: specifically burial depth (distance from the molecular surface to each atom) and travel depth (distance from the convex hull to the molecular surface that avoids the protein interior). These along with common metrics like packing and Wadell Sphericity are used to gain insight into the constraints experienced by thermophiles. Mean travel depth of hyperthermostable proteins is significantly less than that of their mesostable counterparts, indicating smaller, less numerous and less deep pockets. The mean burial depth of hyperthermostable proteins is significantly higher than that of mesostable proteins indicating that they bury more atoms further from the surface. The burial depth can also be tracked on the individual residue level, adding a finer level of detail to the standard exposed surface area analysis. Hyperthermostable proteins for the first time are shown to be more spherical than their mesostable homologues, regardless of when and how they adapted to extreme temperature. Additionally, residue specific burial depth examinations reveal that charged residues stay unburied, most other residues are slightly more buried and Alanine is more significantly buried in hyperthermostable proteins.

Computational tools for designing and engineering biocatalysts

Current computational tools to assist experimentalists for the design and engineering of proteins with desired catalytic properties are reviewed. The applications of these tools for de novo design of protein active sites, optimization of substrate access and product exit pathways, redesign of protein-protein interfaces, identification of neutral/advantageous/deleterious mutations in the libraries from directed evolution and stabilization of protein structures are described. Remarkable progress is seen in de novo design of enzymes catalyzing a chemical reaction for which a natural biocatalyst does not exist. Yet, constructed biocatalysts do not match natural enzymes in their efficiency, suggesting that more research is needed to capture all the important features of natural biocatalysts in theoretical designs.