Cytochrome P450 sterol 14α-demethylase (CYP51) is an essential enzyme for sterol biosynthesis and a target for anti-parasitic drug design. However, the design of parasite-specific drugs that inhibit parasitic CYP51 without severe side effects remains challenging. The active site of CYP51 is situated in the interior of the protein. Here, we characterize the potential ligand egress routes and mechanisms in Trypanosoma brucei and human CYP51 enzymes.
We performed Random Acceleration Molecular Dynamics simulations of the egress of four different ligands from the active site of models of soluble and membrane-bound T. brucei CYP51 and of soluble human CYP51.
In the simulations, tunnel 2 f, which leads to the membrane, was found to be the predominant ligand egress tunnel for all the ligands studied. Tunnels S, 1 and W, which lead to the cytosol, were also used in T. brucei CYP51, whereas tunnel 1 was the only other tunnel used significantly in human CYP51. The common tunnels found previously in other CYPs were barely used. The ligand egress times were shorter for human than T. brucei CYP51, suggesting lower barriers to ligand passage. Two gating residues, F105 and M460, in T. brucei CYP51 that modulate the opening of tunnels 2 f and S were identified.
Although the main egress tunnel was the same, differences in the tunnel-lining residues, ligand passage and tunnel usage were found between T. brucei and human CYP51s.
The results provide a basis for the design of selective anti-parasitic agents targeting the ligand tunnels.
Sterol 14α-demethylase; CYP51; Cytochrome P450; Random acceleration molecular dynamics; Membrane-bound protein; Ligand access and egress
Linker histones are essential for DNA compaction in chromatin. They bind to nucleosomes in a 1:1 ratio forming chromatosomes. Alternative configurations have been proposed in which the globular domain of the linker histone H5 (gH5) is positioned either on- or off-dyad between the nucleosomal and linker DNAs. However, the dynamic pathways of chromatosome assembly remain elusive. Here, we studied the conformational plasticity of gH5 in unbound and off-dyad nucleosome-bound forms with classical and accelerated molecular dynamics simulations. We find that the unbound gH5 converts between open and closed conformations, preferring the closed form. However, the open gH5 contributes to a more rigid chromatosome and restricts the motion of the nearby linker DNA through hydrophobic interactions with thymidines. Moreover, the closed gH5 opens and reorients in accelerated simulations of the chromatosome. Brownian dynamics simulations of chromatosome assembly, accounting for a range of amplitudes of nucleosome opening and different nucleosome DNA sequences, support the existence of both on- and off-dyad binding modes of gH5 and reveal alternative, sequence and conformation-dependent chromatosome configurations. Taken together, these findings suggest that the conformational dynamics of linker histones and nucleosomes facilitate alternative chromatosome configurations through an interplay between induced fit and conformational selection.
2016;84(Suppl Suppl 1):323-348.
We present the results for CAPRI Round 30, the first joint CASP‐CAPRI experiment, which brought together experts from the protein structure prediction and protein–protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact‐sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology‐built subunit models and the smaller pair‐wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323–348. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.
CAPRI; CASP; oligomer state; blind prediction; protein interaction; protein docking
We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy.
CAPRI; CASP; Oligomer state; blind prediction; protein interaction; protein docking
Protein aggregates are the hallmark of stressed and ageing cells, and characterize several pathophysiological states1,2. Healthy metazoan cells effectively eliminate intracellular protein aggregates3,4, indicating that efficient disaggregation and/or degradation mechanisms exist. However, metazoans lack the key heat-shock protein disaggregase HSP100 of non-metazoan HSP70-dependent protein disaggregation systems5,6, and the human HSP70 system alone, even with the crucial HSP110 nucleotide exchange factor, has poor disaggregation activity in vitro4,7. This unresolved conundrum is central to protein quality control biology. Here we show that synergic cooperation between complexed J-protein co-chaperones of classes A and B unleashes highly efficient protein disaggregation activity in human and nematode HSP70 systems. Metazoan mixed-class J-protein complexes are transient, involve complementary charged regions conserved in the J-domains and carboxy-terminal domains of each J-protein class, and are flexible with respect to subunit composition. Complex formation allows J-proteins to initiate transient higher order chaperone structures involving HSP70 and interacting nucleotide exchange factors. A network of cooperative class A and B J-protein interactions therefore provides the metazoan HSP70 machinery with powerful, flexible, and finely regulatable disaggregase activity and a further level of regulation crucial for cellular protein quality control.
The high-mobility group box 1 (HMGB1) protein has a central role in immunological antitumour defense. Here we show that natural killer cell-derived HMGB1 directly eliminates cancer cells by triggering metabolic cell death. HMGB1 allosterically inhibits the tetrameric pyruvate kinase isoform M2, thus blocking glucose-driven aerobic respiration. This results in a rapid metabolic shift forcing cells to rely solely on glycolysis for the maintenance of energy production. Cancer cells can acquire resistance to HMGB1 by increasing glycolysis using the dimeric form of PKM2, and employing glutaminolysis. Consistently, we observe an increase in the expression of a key enzyme of glutaminolysis, malic enzyme 1, in advanced colon cancer. Moreover, pharmaceutical inhibition of glutaminolysis sensitizes tumour cells to HMGB1 providing a basis for a therapeutic strategy for treating cancer.
HMBG1 is a protein expressed in natural killer cells and is important in immunosurveillance. In this study, the authors show that HMGB1 binds to and inhibits PKM2, resulting in a block in aerobic glycolysis and ultimately cell death.
The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein–protein association rate constants, it has since been extended to study electron transfer rates, to predict the structures of biomacromolecular complexes, to investigate the adsorption of proteins to inorganic surfaces, and to simulate the dynamics of large systems containing many biomacromolecular solutes, allowing the study of concentration‐dependent effects. These extensions have led to a number of divergent versions of the software. In this article, we report the development of the latest version of the software (SDA 7). This release was developed to consolidate the existing codes into a single framework, while improving the parallelization of the code to better exploit modern multicore shared memory computer architectures. It is built using a modular object‐oriented programming scheme, to allow for easy maintenance and extension of the software, and includes new features, such as adding flexible solute representations. We discuss a number of application examples, which describe some of the methods available in the release, and provide benchmarking data to demonstrate the parallel performance. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.
Brownian dynamics; protein flexibility; macromolecular association; biomacromolecular diffusion; parallelization; protein‐solid state interactions; protein adsorption
Sterol 14α-demethylase (cytochrome P450 family 51 (CYP51)) is an essential enzyme occurring in all biological kingdoms. In eukaryotes, it is located in the membrane of the endoplasmic reticulum. Selective inhibitors of trypanosomal CYP51s that do not affect the human CYP51 have been discovered in vitro and found to cure acute and chronic mouse Chagas disease without severe side effects in vivo. Crystal structures indicate that CYP51 may be more rigid than most CYPs, and it has been proposed that this property may facilitate antiparasitic drug design. Therefore, to investigate the dynamics of trypanosomal CYP51, we built a model of membrane-bound Trypanosoma brucei CYP51 and then performed molecular dynamics simulations of T. brucei CYP51 in membrane-bound and soluble forms. We compared the dynamics of T. brucei CYP51 with those of human CYP51, CYP2C9, and CYP2E1. In the simulations, the CYP51s display low mobility in the buried active site although overall mobility is similar in all the CYPs studied. The simulations suggest that in CYP51, pathway 2f serves as the major ligand access tunnel, and both pathways 2f (leading to membrane) and S (leading to solvent) can serve as ligand egress tunnels. Compared with the other CYPs, the residues at the entrance of the ligand access tunnels in CYP51 have higher mobility that may be necessary to facilitate the passage of its large sterol ligands. The water (W) tunnel is accessible to solvent during most of the simulations of CYP51, but its width is affected by the conformations of the heme's two propionate groups. These differ from those observed in the other CYPs studied because of differences in their hydrogen-bonding network. Our simulations give insights into the dynamics of CYP51 that complement the available experimental data and have implications for drug design against CYP51 enzymes.
sterol 14α-demethylase; CYP51; cytochrome P450; molecular dynamics simulation; membrane-bound protein; protein dynamics; ligand tunnel; heme propionate groups
Kar1 interacts with the C-terminal (CT) region of Sfi1 to tether the yeast centrosome’s bridge to the nuclear envelope; Sfi1-CT and C-terminal Cdc31-binding regions form the antiparallel Sfi1 overlap in the bridge.
The yeast spindle pole body (SPB) is the functional equivalent of the mammalian centrosome. The half bridge is a SPB substructure on the nuclear envelope (NE), playing a key role in SPB duplication. Its cytoplasmic components are the membrane-anchored Kar1, the yeast centrin Cdc31, and the Cdc31-binding protein Sfi1. In G1, the half bridge expands into the bridge through Sfi1 C-terminal (Sfi1-CT) dimerization, the licensing step for SPB duplication. We exploited photo-activated localization microscopy (PALM) to show that Kar1 localizes in the bridge center. Binding assays revealed direct interaction between Kar1 and C-terminal Sfi1 fragments. kar1Δ cells whose viability was maintained by the dominant CDC31-16 showed an arched bridge, indicating Kar1’s function in tethering Sfi1 to the NE. Cdc31-16 enhanced Cdc31–Cdc31 interactions between Sfi1–Cdc31 layers, as suggested by binding free energy calculations. In our model, Kar1 binding is restricted to Sfi1-CT and Sfi1 C-terminal centrin-binding repeats, and centrin and Kar1 provide cross-links, while Sfi1-CT stabilizes the bridge and ensures timely SPB separation.
Conservation of function across families of orthologous enzymes is generally accompanied by conservation of their active site electrostatic potentials. To study the electrostatic conservation in the highly conserved essential enzyme, thymidylate synthase (TS), we conducted a systematic species-based comparison of the electrostatic potential in the vicinity of its active site. Whereas the electrostatics of the active site of TS are generally well conserved, the TSs from minimal organisms do not conform to the overall trend. Since the genomes of minimal organisms have a high thymidine content compared to other organisms, the observation of non-conserved electrostatics was surprising. Analysis of the symbiotic relationship between minimal organisms and their hosts, and the genetic completeness of the thymidine synthesis pathway suggested that TS from the minimal organism Wigglesworthia glossinidia (W.g.b.) must be active. Four residues in the vicinity of the active site of Escherichia coli TS were mutated individually and simultaneously to mimic the electrostatics of W.g.b TS. The measured activities of the E. coli TS mutants imply that conservation of electrostatics in the region of the active site is important for the activity of TS, and suggest that the W.g.b. TS has the minimal activity necessary to support replication of its reduced genome.
Human thymidylate synthase (hTS), a target for antiproliferative drugs, is an obligate homodimer. Single-point mutations to alanine at the monomer–monomer interface may enable the identification of specific residues that delineate sites for drugs aimed at perturbing the protein–protein interactions critical for activity. We computationally identified putative hotspot residues at the interface and designed mutants to perturb the intersubunit interaction. Dimer dissociation constants measured by a FRET-based assay range from 60 nM for wild-type hTS up to about 1 mM for single-point mutants and agree with computational predictions of the effects of these mutations. Mutations that are remote from the active site retain full or partial activity, although the substrate KM values were generally higher and the dimer was less stable. The lower dimer stability of the mutants can facilitate access to the dimer interface by small molecules and thereby aid the design of inhibitors that bind at the dimer interface.
Several different models of the linker histone (LH)–nucleosome complex have been proposed, but none of them has unambiguously revealed the position and binding sites of the LH on the nucleosome. Using Brownian dynamics-based docking together with normal mode analysis of the nucleosome to account for the flexibility of two flanking 10 bp long linker DNAs (L-DNA), we identified binding modes of the H5-LH globular domain (GH5) to the nucleosome. For a wide range of nucleosomal conformations with the L-DNA ends less than 65 Å apart, one dominant binding mode was identified for GH5 and found to be consistent with fluorescence recovery after photobleaching (FRAP) experiments. GH5 binds asymmetrically with respect to the nucleosomal dyad axis, fitting between the nucleosomal DNA and one of the L-DNAs. For greater distances between L-DNA ends, docking of GH5 to the L-DNA that is more restrained and less open becomes favored. These results suggest a selection mechanism by which GH5 preferentially binds one of the L-DNAs and thereby affects DNA dynamics and accessibility and contributes to formation of a particular chromatin fiber structure. The two binding modes identified would, respectively, favor a tight zigzag chromatin structure or a loose solenoid chromatin fiber.
Macromolecular interactions play a crucial role in biological systems. Simulation of diffusional association (SDA) is a software for carrying out Brownian dynamics simulations that can be used to study the interactions between two or more biological macromolecules. webSDA allows users to run Brownian dynamics simulations with SDA to study bimolecular association and encounter complex formation, to compute association rate constants, and to investigate macromolecular crowding using atomically detailed macromolecular structures. webSDA facilitates and automates the use of the SDA software, and offers user-friendly visualization of results. webSDA currently has three modules: ‘SDA docking’ to generate structures of the diffusional encounter complexes of two macromolecules, ‘SDA association’ to calculate bimolecular diffusional association rate constants, and ‘SDA multiple molecules’ to simulate the diffusive motion of hundreds of macromolecules. webSDA is freely available to all users and there is no login requirement. webSDA is available at http://mcm.h-its.org/webSDA/.
Summary: LigDig is a web server designed to answer questions that previously required several independent queries to diverse data sources. It also performs basic manipulations and analyses of the structures of protein–ligand complexes. The LigDig webserver is modular in design and consists of seven tools, which can be used separately, or via linking the output from one tool to the next, in order to answer more complex questions. Currently, the tools allow a user to: (i) perform a free-text compound search, (ii) search for suitable ligands, particularly inhibitors, of a protein and query their interaction network, (iii) search for the likely function of a ligand, (iv) perform a batch search for compound identifiers, (v) find structures of protein–ligand complexes, (vi) compare three-dimensional structures of ligand binding sites and (vii) prepare coordinate files of protein–ligand complexes for further calculations.
Availability and implementation: LigDig makes use of freely available databases, including ChEMBL, PubChem and SABIO-RK, and software programs, including cytoscape.js, PDB2PQR, ProBiS and Fconv. LigDig can be used by non-experts in bio- and chemoinformatics. LigDig is available at: http://mcm.h-its.org/ligdig.
Supplementary data are available at Bioinformatics online.
Many signaling events require the binding of cytoplasmic proteins to cell membranes by recognition of specific charged lipids, such as phosphoinositol-phosphates. As a model for a protein-membrane binding site, we consider one charged phosphoinositol phosphate (PtdIns(3)P) embedded in a phosphatidylcholine bilayer. As the protein-membrane binding is driven by electrostatic interactions, continuum solvent models require an accurate representation of the electrostatic potential of the phosphoinositol phosphate-containing membrane. We computed and analyzed the electrostatic potentials of snapshots taken at regular intervals from molecular dynamics simulations of the bilayer. We observe considerable variation in the electrostatic potential of the bilayer both along a single simulation and between simulations performed with the GAFF or CHARMM c36 force fields. However, we find that the choice of GAFF or CHARMM c36 parameters has little effect on the electrostatic potential of a given configuration of the bilayer with a PtdIns(3)P embedded in it. From our results, we propose a remedian averaging method for calculating the electrostatic potential of a membrane system that is suitable for simulations of protein-membrane binding with a continuum solvent model.
Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulate solutions of bovine serum albumin and of hen egg white lysozyme.
We found that the inclusion of the long-range electrostatic correction increased the accuracy of both the protein-protein interaction profiles and the protein diffusion coefficients at low ionic strength.
An advantage of this method is the low additional computational cost required to treat long-range electrostatic interactions in large biomacromolecular systems. Moreover, the implementation described here for BD simulations of protein solutions can also be applied in implicit solvent molecular dynamics simulations that make use of gridded interaction potentials.
Continuum solvent electrostatics; Ionic strength; Debye-Hückel; Poisson-Boltzmann equation; Brownian dynamics simulation; Protein diffusion; Discretization grid; Finite difference; Second virial coefficient; Small angle scattering intensity
Pyruvate kinase (PYK) is a critical allosterically regulated enzyme that links glycolysis, the primary energy metabolism, to cellular metabolism. Lactic acid bacteria rely almost exclusively on glycolysis for their energy production under anaerobic conditions, which reinforces the key role of PYK in their metabolism. These organisms are closely related, but have adapted to a huge variety of native environments. They include food-fermenting organisms, important symbionts in the human gut, and antibiotic-resistant pathogens. In contrast to the rather conserved inhibition of PYK by inorganic phosphate, the activation of PYK shows high variability in the type of activating compound between different lactic acid bacteria. System-wide comparative studies of the metabolism of lactic acid bacteria are required to understand the reasons for the diversity of these closely related microorganisms. These require knowledge of the identities of the enzyme modifiers. Here, we predict potential allosteric activators of PYKs from three lactic acid bacteria which are adapted to different native environments. We used protein structure-based molecular modeling and enzyme kinetic modeling to predict and validate potential activators of PYK. Specifically, we compared the electrostatic potential and the binding of phosphate moieties at the allosteric binding sites, and predicted potential allosteric activators by docking. We then made a kinetic model of Lactococcus lactis PYK to relate the activator predictions to the intracellular sugar-phosphate conditions in lactic acid bacteria. This strategy enabled us to predict fructose 1,6-bisphosphate as the sole activator of the Enterococcus faecalis PYK, and to predict that the PYKs from Streptococcus pyogenes and Lactobacillus plantarum show weaker specificity for their allosteric activators, while still having fructose 1,6-bisphosphate play the main activator role in vivo. These differences in the specificity of allosteric activation may reflect adaptation to different environments with different concentrations of activating compounds. The combined computational approach employed can readily be applied to other enzymes.
Some lactic acid bacteria are antibiotic resistant pathogens causing severe diseases whereas others are healthy probiotics used in the food industry. What makes an LAB a friend or a foe and how do they adapt to survive in such different environments? Here, we addressed this problem by focusing on the enzyme pyruvate kinase, which plays a central role in the metabolism of lactic acid bacteria. This enzyme needs to react quickly to changes in the environment and, therefore, its activity is strictly regulated. In this study, we used computational techniques to predict the cellular substances, called allosteric activators that are responsible for the quick and effective activation of pyruvate kinase. We modeled the three dimensional structures of pyruvate kinases from different bacteria and computed interactions with possible activators. We simulated the dynamic behavior of the pyruvate kinase activity and, considering the cellular concentrations of metabolites in the different organisms, predicted the activators. We found that different lactic acid bacteria have different preferences for activators and that the level of activator specificity can be related to the environment in which the bacteria live.
Resistance to drugs targeting human thymidylate synthase (TS) poses a major challenge in the field of anti-cancer therapeutics. Overexpression of the TS protein has been implicated as one of the factors leading to the development of resistance. Therefore, repressing translation by targeting the TS mRNA could help to overcome this problem. In this study, we report that the compound Hoechst 33258 (HT) can reduce cellular TS protein levels without altering TS mRNA levels, suggesting that it modulates TS expression at the translation level. We have combined nuclear magnetic resonance, UV-visible and fluorescence spectroscopy methods with docking and molecular dynamics simulations to study the interaction of HT with a region in the TS mRNA. The interaction predominantly involves intercalation of HT at a CC mismatch in the region near the translational initiation site. Our results support the use of HT-like compounds to guide the design of therapeutic agents targeting TS mRNA.
Rab GTPases constitute the largest subfamily of the Ras protein superfamily. Rab proteins regulate organelle biogenesis and transport, and display distinct binding preferences for effector and activator proteins, many of which have not been elucidated yet. The underlying molecular recognition motifs, binding partner preferences and selectivities are not well understood.
Comparative analysis of the amino acid sequences and the three-dimensional electrostatic and hydrophobic molecular interaction fields of 62 human Rab proteins revealed a wide range of binding properties with large differences between some Rab proteins. This analysis assists the functional annotation of Rab proteins 12, 14, 26, 37 and 41 and provided an explanation for the shared function of Rab3 and 27. Rab7a and 7b have very different electrostatic potentials, indicating that they may bind to different effector proteins and thus, exert different functions. The subfamily V Rab GTPases which are associated with endosome differ subtly in the interaction properties of their switch regions, and this may explain exchange factor specificity and exchange kinetics.
We have analysed conservation of sequence and of molecular interaction fields to cluster and annotate the human Rab proteins. The analysis of three dimensional molecular interaction fields provides detailed insight that is not available from a sequence-based approach alone. Based on our results, we predict novel functions for some Rab proteins and provide insights into their divergent functions and the determinants of their binding partner selectivity.
The microsomal, membrane-bound, human cytochrome P450 (CYP) 2C9 is a liver-specific monooxygenase essential for drug metabolism. CYPs require electron transfer from the membrane-bound CYP reductase (CPR) for catalysis. The structural details and functional relevance of the CYP-membrane interaction are not understood. From multiple coarse grained molecular simulations started with arbitrary configurations of protein-membrane complexes, we found two predominant orientations of CYP2C9 in the membrane, both consistent with experiments and conserved in atomic-resolution simulations. The dynamics of membrane-bound and soluble CYP2C9 revealed correlations between opening and closing of different tunnels from the enzyme's buried active site. The membrane facilitated the opening of a tunnel leading into it by stabilizing the open state of an internal aromatic gate. Other tunnels opened selectively in the simulations of product-bound CYP2C9. We propose that the membrane promotes binding of liposoluble substrates by stabilizing protein conformations with an open access tunnel and provide evidence for selective substrate access and product release routes in mammalian CYPs. The models derived here are suitable for extension to incorporate other CYPs for oligomerization studies or the CYP reductase for studies of the electron transfer mechanism, whereas the modeling procedure is generally applicable to study proteins anchored in the bilayer by a single transmembrane helix.
We describe the first atomic-detail models and simulations of a full-length, membrane-bound mammalian cytochrome P450. To date, all the structural studies of microsomal, drug-metabolizing cytochrome P450s have been performed using engineered, solubilized forms of the enzymes and it is not yet understood how the membrane influences their structure, dynamics, and ability to bind substrates. We focused on CYP2C9, the second most abundant cytochrome P450 in the human liver which oxidizes 20% of all marketed drugs. Here, we have derived models of CYP2C9-membrane complexes with a modeling procedure based on molecular dynamics simulations started with arbitrary configurations of the protein in the membrane and performed using both coarse grained and atomic-detail molecular representations. This procedure is expected to be generally applicable to proteins that are anchored in the membrane with a single transmembrane helix. The models and simulations provide evidence for selective substrate access and product release routes in membrane-bound CYPs. This observation may contribute to new strategies to manipulate the activity of CYPs and other enzymes with buried active sites. We anticipate that this study will bring about a paradigm shift towards studying microsomal CYPs as dynamic structures in their natural, lipid environment rather than in artificially solubilized forms.
Hydrophobins are small proteins produced by filamentous fungi that have a variety of biological functions including coating of spores and surface adhesion. To accomplish these functions, they rely on unique interface-binding properties. Using atomic-detail implicit solvent rigid-body Brownian dynamics simulations, we studied the diffusion of HFBI, a class II hydrophobin from Trichoderma reesei, in aqueous solution in the presence and absence of a graphite surface.
In the simulations, HFBI exists in solution as a mixture of monomers in equilibrium with different types of oligomers. The oligomerization state depends on the conformation of HFBI. When a Highly Ordered Pyrolytic Graphite (HOPG) layer is present in the simulated system, HFBI tends to interact with the HOPG layer through a hydrophobic patch on the protein.
From the simulations of HFBI solutions, we identify a tetrameric encounter complex stabilized by non-polar interactions between the aliphatic residues in the hydrophobic patch on HFBI. After the formation of the encounter complex, a local structural rearrangement at the protein interfaces is required to obtain the tetrameric arrangement seen in HFBI crystals. Simulations performed with the graphite surface show that, due to a combination of a geometric hindrance and the interaction of the aliphatic sidechains with the graphite layer, HFBI proteins tend to accumulate close to the hydrophobic surface.
Macromolecular diffusion plays a fundamental role in biological processes. Here, we give an overview of recent methodological advances and some of the challenges for understanding how molecular diffusional properties influence biological function that were highlighted at a recent workshop, BDBDB2, the second Biological Diffusion and Brownian Dynamics Brainstorm.
Protein molecular interaction fields are key determinants of protein functionality. PIPSA (Protein Interaction Property Similarity Analysis) is a procedure to compare and analyze protein molecular interaction fields, such as the electrostatic potential. PIPSA may assist in protein functional assignment, classification of proteins, the comparison of binding properties and the estimation of enzyme kinetic parameters. webPIPSA is a web server that enables the use of PIPSA to compare and analyze protein electrostatic potentials. While PIPSA can be run with downloadable software (see http://projects.eml.org/mcm/software/pipsa), webPIPSA extends and simplifies a PIPSA run. This allows non-expert users to perform PIPSA for their protein datasets. With input protein coordinates, the superposition of protein structures, as well as the computation and analysis of electrostatic potentials, is automated. The results are provided as electrostatic similarity matrices from an all-pairwise comparison of the proteins which can be subjected to clustering and visualized as epograms (tree-like diagrams showing electrostatic potential differences) or heat maps. webPIPSA is freely available at: http://pipsa.eml.org.