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PubMed1998

Modelling repressor proteins docking to DNA.

The docking of repressor proteins to DNA starting from the unbound protein and model-built DNA coordinates is modeled computationally. The approach was evaluated on eight repressor/DNA complexes that employed different modes for protein/ DNA recognition. The global search is based on a protein-protein docking algorithm that evaluates shape and electrostatic complementarity, which was modified to consider the importance of electrostatic features in DNA-protein recognition. Complexes were then ranked by an empirical score for the observed amino acid /nucleotide pairings (i.e., protein-DNA pair potentials) derived from a database of 20 protein/ DNA complexes. A good prediction had at least 65% of the correct contacts modeled. This approach was able to identify a good solution at rank four or better for three out of the eight complexes. Predicted complexes were filtered by a distance constraint based on experimental data defining the DNA footprint. This improved coverage to four out of eight complexes having a good model at rank four or better. The additional use of amino acid mutagenesis and phylogenetic data defining residues on the repressor resulted in between 2 and 27 models that would have to be examined to find a good solution for seven of the eight test systems. This study shows that starting with unbound coordinates one can predict three-dimensional models for protein/DNA complexes that do not involve gross conformational changes on association.

Algorithms↗
PubMed2000

Homology models of mu-opioid receptor with organic and inorganic cations at conserved aspartates in the second and third transmembrane domains.

Metal ions affect ligand binding to G-protein-coupled receptors by as yet unknown mechanisms. In particular, Na(+) increases the affinity for antagonists but decreases it for agonists. We had modeled the mu-opioid receptor (muR) based on the low-resolution structure of rhodopsin by G. F. X. Schertler, C. Villa, and R. Henderson (1993, Nature 362, 770-772) and proposed that metal ions may be directly involved in the binding of ligands and receptor activation (B. S. Zhorov and V. S. Ananthanarayanan, 1998, J. Biomol. Struct. Dyn. 15, 631-637). Developing this concept further, we present here homology models of muR using as templates the structure of rhodopsin elaborated by I. D. Pogozheva, A. L. Lomize, and H. I. Mosberg (1997, Biophys. J. 70, 1963-1985) and J. M. Baldwin, G. F. X. Schertler, and V. M. Unger (1997, J. Mol. Biol., 272, 144-164). Using the Monte Carlo minimization (MCM) method, we docked the Na(+)-bound forms of muR ligands: naloxone, bremazocine, and carfentanyl. The resultant low-energy complexes showed that the two positive charges in the protonated metal-bound ligands interact with the two negative charges at Asp(3.32) and Asp(2.50) (for notations, see J. A. Ballesteros and H. Weinstein, 1995, Methods Neurosci. 25, 366-426). MCM computation on morphine docked inside the model of muR by I. D. Pogozheva, A. L. Lomize, and H. I. Mosberg (1998, Biophys. J. 75, 612-634) yielded two binding modes with the ligand's ammonium group salt-bridged either to Asp(3.32) (generally regarded as the ligand recognition site) or to Asp(2.50). The latter is the presumed site for Na(+) ion, which is known to modulate ligand binding. Assuming that in the low-dielectric transmembrane region of muR, organic and inorganic cations would compete for Asp(3.32) and Asp(2.50), we propose that ligand binding, as visualized in the above models, would first displace Na(+) from Asp(3.32). A subsequent progress of the ligand toward Asp(2.50) would result in either the retention of Na(+) at Asp(2.50) in the case of antagonists or the displacement of Na(+) from Asp(2.50) in the case of agonists. The displaced Na(+) would move toward the salt-bridged Asp(3.49)-Arg(3.50) and disengage the salt bridge. This, in turn, would result in conformational changes at the cytoplasmic face of the receptor that facilitate the interaction with the G-protein.

Amino Acid Sequence↗
PubMed2006

FK506-binding protein ligands: structure-based design, synthesis, and neurotrophic/neuroprotective properties of substituted 5,5-dimethyl-2-(4-thiazolidine)carboxylates.

Structure-based design and discovery of novel neuroimmunophilin FK506-binding protein (FKBP) ligands were pursued in the present study. The binding mode of the known FKBP ligand 1 (3-(3-pyridyl)-1-propyl (2S)-1-(3,3-dimethyl-1,2-dioxopentyl)-2-pyrrolidinecarboxylate) in complex with FKBP12 was investigated using LUDI simulation and upon which a novel scaffold structure predicted to possess improved binding affinity was designed. A virtual combinatorial library composed of diverse combinations of two substituted groups was constructed using Project Library, followed by an automated screening of the library against the ligand binding site on FKBP52 using DOCK. Forty-three candidate compounds that displayed favorable binding with the receptor were identified and synthesized. The neurotrophic activity of the candidate compounds was evaluated on chick dorsal root ganglion cultures in vitro. As a result, 15 compounds exhibited positive effects on ganglion neurite outgrowth in the presence of 0.15 ng/mL NGF, among which 7 compounds at testing concentrations of 1 pM and 100 pM showed greater efficacy than 1 at 100 pM. Compound 18 (3-(3-pyridyl)-1-propyl (2S)-5,5-dimethyl-1-(3,3-dimethyl-1,2-dioxobutyl)-2-(4-thiazolidine)carboxylate) afforded the most potent effect in promoting the processes of neurite outgrowth and which was in a concentration-dependent manner from 1 pM to 100 pM. Half-maximal effect occurred at about 10 pM. Moreover, 18 at a dosage of 10 mg/kg was found to be significantly neuroprotective in a mouse peripheral sympathetic nerve injury model induced by 8 mg/kg 6-hydroxydopamine. This study further suggests the clinical potential of novel FKBP ligands as a new therapeutic approach in the treatment of neurodegenerative disorders, such as Parkinson's disease.

Animals↗
PubMed2006

Docking studies of agonists and antagonists suggest an activation pathway of the A3 adenosine receptor.

Structural determinants of ligand efficacy in the human A(3) adenosine receptor (AR) were studied using pharmacophore and docking analyses of various categories of A(3) selective ligands: inverse agonist, neutral antagonist (nonnucleoside and nucleoside), and agonist (partial and full). The homology modeling of GPCRs was adapted to provide two templates: the rhodopsin-based resting state for antagonist binding and a putative Meta I state, conformationally altered at a key residue (W6.48), for agonist binding. The preferential binding domains and/or local conformational changes associated with docking of three high affinity A(3)AR ligands were compared: inverse agonist PSB-11 1 ((R)-8-ethyl-4-methyl-2-phenyl-imidazo[2,1-i]purin-5-one); neutral antagonist MRE-3008F20 7 (5-[[(4-methoxyphenyl)amino]carbonyl]amino-8-methyl-2-(2-furyl)pyra-zolo[4,3-e]1,2,4-triazolo[1,5-c]pyrimidine), and full agonist Cl-IB-MECA 21 (2-chloro-N(6)-(3-iodobenzyl)-5'-N-methylcarboxamidoadenosine) to define a distinct recognition mode for each. Ribose-containing agonists were more hydrophilic than nonnucleoside antagonists, and H-bonding ability at the ribose 3'- and 5'-positions was required for agonism. From the receptor perspective, common requirements for activation included the destabilization of H-bond networks at W6.48 and H7.43, the specific interactions of the ribose moiety in its putative hydrophilic pocket at T3.36, S7.42, and H7.43, the stabilization of the complex by inward movement of F5.43, and the characteristic rotation of W6.48. By analogy, outward rotation of the W6.48 side-chain upon activation of an internally-crosslinking mutant M(3) muscarinic receptor was indicated by constrained molecular dynamics (MD). Our results are consistent with an anti-clockwise rotation (from the extracellular view) of transmembrane domains 3, 5, 6, and 7, as proposed for other Family A GPCRs. Thus, the putative conformational changes associated with A(3)AR activation indicate a shared mechanism of GPCR activation similar to rhodopsin.

Adenosine↗
PubMed2004

Distance-restrained docking of rifampicin and rifamycin SV to RNA polymerase using systematic FRET measurements: developing benchmarks of model quality and reliability.

We are developing distance-restrained docking strategies for modeling macromolecular complexes that combine available high-resolution structures of the components and intercomponent distance restraints derived from systematic fluorescence resonance energy transfer (FRET) measurements. In this article, we consider the problem of docking small-molecule ligands within macromolecular complexes. Using simulated FRET data, we have generated a series of benchmarks that permit estimation of model accuracy based on the quantity and quality of FRET-derived distance restraints, including the number, random error, systematic error, distance distribution, and radial distribution of FRET-derived distance restraints. We find that expected model accuracy is 10 A or better for models based on: i), > or =20 restraints with up to 15% random error and no systematic error, or ii), > or =20 restraints with up to 15% random error, up to 10% systematic error, and a symmetric radial distribution of restraints. Model accuracies can be improved to 5 A or better by increasing the number of restraints to > or =40 and/or by optimizing the distance distribution of restraints. Using experimental FRET data, we have defined the positions of the binding sites within bacterial RNA polymerase of the small-molecule inhibitors rifampicin (Rif) and rifamycin SV (Rif SV). The inferred binding sites for Rif and Rif SV were located with accuracies of, respectively, 7 and 10 A relative to the crystallographically defined binding site for Rif. These accuracies agree with expectations from the benchmark simulations and suffice to indicate that the binding sites for Rif and Rif SV are located within the RNA polymerase active-center cleft, overlapping the binding site for the RNA-DNA hybrid.

Binding Sites↗
PubMed2000

Structural investigations of the CuA centre of nitrous oxide reductase from Pseudomonas stutzeri by site-directed mutagenesis and X-ray absorption spectroscopy.

Nitrous oxide reductase is the terminal component of a respiratory chain that utilizes N2O in lieu of oxygen. It is a homodimer carrying in each subunit the electron transfer site, CuA, and the substrate-reducing catalytic centre, CuZ. Spectroscopic data have provided robust evidence for CuA as a binuclear, mixed-valence metal site. To provide further structural information on the CuA centre of N2O reductase, site directed mutagenesis and Cu K-edge X-ray absorption spectroscopic investigation have been undertaken. Candidate amino acids as ligands for the CuA centre of the enzyme from Pseudomonas stutzeri ATCC14405 were substituted by evolutionary conserved residues or amino acids similar to the wild-type residues. The mutations identified the amino acids His583, Cys618, Cys622 and Met629 as ligands of Cu1, and Cys618, Cys622 and His626 as the minimal set of ligands for Cu2 of the CuA centre. Other amino acid substitutions indicated His494 as a likely ligand of CuZ, and an indirect role for Asp580, compatible with a docking function for the electron donor. Cu binding and spectroscopic properties of recombinant N2O reductase proteins point at intersubunit or interdomain interaction of CuA and CuZ. Cu K-edge X-ray absorption spectra have been recorded to investigate the local environment of the Cu centres in N2O reductase. Cu K-edge Extended X-ray Absorption Fine Structure (EXAFS) for binuclear Cu chemical systems show clear evidence for Cu backscattering at approximately 2.5 A. The Cu K-edge EXAFS of the CuA centre of N2O reductase is very similar to that of the CuA centre of cytochrome c oxidase and the optimum simulation of the experimental data involves backscattering from a histidine group with Cu-N of 1.92 A, two sulfur atoms at 2.24 A and a Cu atom at 2. 43 A, and allows for the presence of a further light atom (oxygen or nitrogen) at 2.05 A. The interpretation of the CuA EXAFS is in line with ligands assigned by site-directed mutagenesis. By a difference spectrum approach, using the Cu K-edge EXAFS of the holoenzyme and that of the CuA-only form, histidine was identified as a major contributor to the backscattering. A structural model for the CuA centre of N2O reductase has been generated on the basis of the atomic coordinates for the homologous domain of cytochrome c oxidase and incorporating our current results and previous spectroscopic data.

Amino Acid Sequence↗
PubMed2005

Molecular modeling of cardiac glycoside binding by the human sequence monoclonal antibody 1B3.

The amino acid sequences of the heavy- and light-chain variable regions of the high-affinity human sequence antidigoxin monoclonal antibody 1B3 (mAb 1B3) were determined, and a structural model for the mAb's variable region was developed by homology modeling techniques. The structural model provided the basis for computationally docking digoxin and eight related cardiac glycosides into the putative binding site of mAb 1B3. Analysis of the consensus binding mode obtained for digoxin showed that the cardenolide moiety of digoxin is deeply embedded in a predominantly hydrophobic, narrow cavity, whereas the terminal, gamma-carbohydrate group is solvent-exposed. The docking results indicated that the primary driving forces for digoxin binding by mAb 1B3 are hydrophobic interactions with the digoxin steroid ring system and hydrogen bonds with the digitoxose groups. The binding model accounts for the experimentally observed variations in mAb 1B3 binding affinity for various structural analogs of digoxin used previously to develop a 3D structure-activity relationship model of drug binding (Farr CD, Tabet MR, Ball WJ Jr, Fishwild DM, Wang X, Nair AC, Welsh WJ. Three-dimensional quantitative structure-activity relationship analysis of ligand binding to human sequence antidigoxin monoclonal antibodies using comparative molecular field analysis. J Med Chem 2002;45:3257-3270). In particular, the hydrogen bond pattern is consistent with the unique sensitivity of mAb 1B3's binding affinity to the number of sugar residues present in a cardiac glycoside. The hydrophobic environment about the steroid moiety of digoxin is compatible with the mAb's reduced affinity for ligands that possess hydrophilic hydroxyl and acetyl group modifications in this region. The model also indicated that most of the amino acid residues in contact with the ligand reside in or about the three complementarity determining regions (CDRs) of the heavy chain and the third CDR of the light chain. A comparison of the 1B3 binding model with the crystal structures of two murine antidigoxin mAbs revealed similar binding patterns used by the three mAbs, such as a high frequency of occurrence of aromatic, hydrophobic residues in the CDRs and a dominant role of the heavy chain CDR3 in antigen binding.

Amino Acid Sequence↗
PubMedDate not supplied

SitePrint: three-dimensional pharmacophore descriptors derived from protein binding sites for family based active site analysis, classification, and drug design.

Integrating biological and chemical information is one key task in drug discovery, and one approach to attaining this goal is via three-dimensional pharmacophore descriptors derived from protein binding sites. The SitePrint program generates, aligns, scores, and classifies three-dimensional pharmacophore descriptors, active site grids, and ligand surfaces. The descriptors are formed from molecular fragments that have been docked, minimized, filtered, and clustered in protein active sites. The descriptors have geometric coordinates derived from the fragment positions, and they capture the shape, electrostatics, locations, and angles of entry into pockets of the recognition sites: they also provide a direct link to databases of organic molecules. The descriptors have been shown to be robust with respect to small changes in protein structure observed when multiple compounds are cocrystallized in a protein. Five aligned thrombin cocrystals with an average core alpha-carbon RMSD of 0.7 A gave three-dimensional pharmacophore descriptors with an average RMSD of 1.1 A. On a larger test set, alignment and scoring of the descriptors using clique-based alignment, and a best first search strategy with an adapted forward-looking Ullmann heuristic was able to select the global minimum three-dimensional alignment in twenty-nine out of thirty cases in less than one CPU second on a workstation. A protein family based analysis was then performed to demonstrate the usefulness of the method in producing a correlation of active site pharmacophore descriptors to protein function. Each protein in a test set of thirty was assigned membership to a family based on computed active site similarity to the following families: kinases, nuclear receptors, the aspartyl, cysteine, serine, and metallo proteases. This method of classifying proteins is complementary to approaches based on sequence or fold homology. The values within protein families for correctly assigning membership of a protein to a family ranged from 25% to 80%.

Algorithms↗
PubMed2007

Ensemble docking of multiple protein structures: considering protein structural variations in molecular docking.

One approach to incorporate protein flexibility in molecular docking is the use of an ensemble consisting of multiple protein structures. Sequentially docking each ligand into a large number of protein structures is computationally too expensive to allow large-scale database screening. It is challenging to achieve a good balance between docking accuracy and computational efficiency. In this work, we have developed a fast, novel docking algorithm utilizing multiple protein structures, referred to as ensemble docking, to account for protein structural variations. The algorithm can simultaneously dock a ligand into an ensemble of protein structures and automatically select an optimal protein structure that best fits the ligand by optimizing both ligand coordinates and the conformational variable m, where m represents the m-th structure in the protein ensemble. The docking algorithm was validated on 10 protein ensembles containing 105 crystal structures and 87 ligands in terms of binding mode and energy score predictions. A success rate of 93% was obtained with the criterion of root-mean-square deviation <2.5 A if the top five orientations for each ligand were considered, comparable to that of sequential docking in which scores for individual docking are merged into one list by re-ranking, and significantly better than that of single rigid-receptor docking (75% on average). Similar trends were also observed in binding score predictions and enrichment tests of virtual database screening. The ensemble docking algorithm is computationally efficient, with a computational time comparable to that for docking a ligand into a single protein structure. In contrast, the computational time for the sequential docking method increases linearly with the number of protein structures in the ensemble. The algorithm was further evaluated using a more realistic ensemble in which the corresponding bound protein structures of inhibitors were excluded. The results show that ensemble docking successfully predicts the binding modes of the inhibitors, and discriminates the inhibitors from a set of noninhibitors with similar chemical properties. Although multiple experimental structures were used in the present work, our algorithm can be easily applied to multiple protein conformations generated by computational methods, and helps improve the efficiency of other existing multiple protein structure(MPS)-based methods to accommodate protein flexibility.

Algorithms↗
PubMed1999

The particle concept: placing discrete water molecules during protein-ligand docking predictions.

Water is known to play a significant role in the formation of protein-ligand complexes. In this paper, we focus on the influence of water molecules on the structure of protein-ligand complexes. We present an algorithmic approach, called the particle concept, for integrating the placement of single water molecules in the docking algorithm of FLEXX. FLEXX is an incremental construction approach to ligand docking consisting of three phases: the selection of base fragments, the placement of the base fragments, and the incremental reconstruction of the ligand inside the active site of a protein. The goal of the extension is to find water molecules at favorable places in the protein-ligand interface which may guide the placement of the ligand. In a preprocessing phase, favorable positions of water molecules inside the active site are calculated and stored in a list of possible water positions. During the incremental construction phase, water molecules are placed at the precomputed positions if they can form additional hydrogen bonds to the ligand. Steric constraints resulting from the water molecules as well as the geometry of the hydrogen bonds are used to optimize the ligand orientation in the active site during the reconstruction process. We have tested the particle concept on a series of 200 protein-ligand complexes. Although the average improvement of the prediction results is minor, we were able to predict water molecules between the protein and the ligand correctly in several cases. For instance in the case of HIV-1 protease, where a single water molecule between the protein and the ligand is known to be of importance in complex formation, significant improvements can be achieved.

Algorithms↗
PubMed2003

Computational detection of the binding-site hot spot at the remodeled human growth hormone-receptor interface.

A hierarchical computational approach is used to identify the engineered binding-site cavity at the remodeled intermolecular interface between the mutants of human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp). Multiple docking simulations are conducted with the remodeled hGH-hGHbp complex for a panel of potent benzimidazole-containing inhibitors that can restore the binding affinity of the wild-type complex, and for a set of known nonactive small molecules that contain different heterocyclic motifs. Structural clustering of ligand-bound conformations and binding free-energy calculations, using the AMBER force field and a continuum solvation model, can rapidly locate and screen numerous ligand-binding modes on the protein surface and detect the binding-site hot spot at the intermolecular interface. Structural orientation of the benzimidazole motif in the binding-site cavity closely mimics the position of the hot spot residue W104 in the crystal structure of the wild-type complex, which is recognized as an important structural requirement for restoring binding affinity. Despite numerous pockets on the protein surface of the mutant hGH-hGHbp complex, the binding-site cavity presents the energetically favorable hot spot for the benzimidazole-containing inhibitors, whereas for a set of nonactive molecules, the lowest energy ligand conformations do not necessarily bind in the engineered cavity. The results reveal a dominant role of the intermolecular van der Waals interactions in providing favorable ligand-protein energetics in the redesigned interface, in agreement with the experimental and computational alanine scanning of the hGH-hGHbp complex.

Alanine↗
PubMed2005

Protein-protein docking using 3D-Dock in rounds 3, 4, and 5 of CAPRI.

In rounds 3-5 of CAPRI, the community-wide experiment on the comparative evaluation of protein-protein docking for structure prediction, we applied the 3D-Dock software package to predict the atomic structures of nine biophysical interactions. This approach starts with an initial grid-based shape complementarity search. The product of this is a large number of potential interacting conformations that are subsequently ranked by interface residue propensities and interaction energies. Refinement through detailed energetics and optimization of side-chain positions using a rotamer library is also performed. For rounds 3, 4, and 5 of the CAPRI evaluation, where possible, we clustered functional residues on the surfaces of the monomers as an indication of binding sites, using sequence based evolutionary conservations. In certain targets this provided a very useful tool for identifying the areas of interaction. During round 5, we also applied the techniques of side-chain trimming and geometrical clustering described in the literature. Of the nine target complexes in rounds 3-5, we predicted conformations that contained at least some correct contact residues for seven of these systems. For two of the targets, we submitted predictions that were considered as medium-quality. These were a nidogen-laminin complex for target 8 (T08) and a serine-threonine phosphatase bound to a targeting subunit (T14). For a further three target systems, we produced models that were rated as acceptable predictions.

Algorithms↗
PubMed2000

Solution structure of ileal lipid binding protein in complex with glycocholate.

Ileal lipid binding protein (ILBP) is a cytosolic lipid-binding protein that binds both bile acids and fatty acids. We have determined the solution structure of porcine ILBP in complex with glycocholate by homonuclear and heteronuclear two-dimensional NMR spectroscopy. The conformation of the protein-ligand complex was determined by restrained energy minimization and simulated annealing calculations after docking the glycocholate ligand into the protein structure. The overall tertiary structure of ILBP is highly analogous to the three-dimensional structures of several other intracellular lipid binding proteins (LBPs). Like the apo-structure, the bile-acid complex of ILBP is composed of 10 anti-parallel beta-strands that form a water-filled clam-shell structure, and two short alpha-helices. Chemical shift data indicated that the bile acid ligand is bound inside the protein cavity. Furthermore, 13C-edited heteronuclear single-quantum correlation-NOESY experiments showed NOE contacts between several aromatic residues located in the proposed bile acid portal region and the 13C-labeled ligand. A single bile acid molecule is bound inside the protein, with the steroid moiety penetrating deep into the water-accessible internal cavity, such that ring A is located right above the plane of the Trp49 indole ring. The carboxylate tail of the ligand is protruding from the proposed bile acid portal into the surrounding aqueous solution. The body of the steroid moiety is oriented with the nonpolar face in contact with the mostly hydrophobic residues of beta-strands C, D and E, while the polar face shows contacts with the side-chains of Tyr97, His99, Glu110 and Arg121 in beta-strands H, I and J. Thus, the conformational arrangement of the ligand complex suggests that the binding affinity of ILBP for bile acid molecules is based mainly on strong hydrophobic interactions inside the protein cavity. Furthermore, this binding mode explains how ILBP can transport unconjugated and conjugated bile acids.

Animals↗
PubMed1997

Docking of verapamil in a synthetic Ca2+ channel: formation of a ternary complex involving Ca2+ ions.

The mechanism by which diverse drugs modulate voltage-dependent Ca2+ channels is ill-understood. We have approached this problem by examining the interaction of verapamil with a 97-residue synthetic channel peptide (SCP) that exhibits functional similarities to authentic L-type Ca2+ channels in terms of cation selectivity and permeation as well as interaction with channel-activating and blocking drugs (Grove et al. (1991) Proc. Natl. Acad. Sci. USA 88, 6418). Different possibilities of binding of verapamil inside the Ca(2+)-bound SCP were simulated using the Monte Carlo-with-energy-minimization method. In the optimal mode of the binding, verapamil adopted a folded conformation and fit snugly in the pore. The dimethoxyphenyl groups of the drug interacted with two Ca2+ ions coordinated to the acidic residues of SCP, thus forming a ternary complex of the drug, Ca2+, and channel. The isopropyl group of verapamil abetted a ring of four Ile residues constituting the putative SCP gate. The occlusion of this gate by verapamil in this manner was strikingly similar to that accomplished by the methyl group of dihydropyridine drugs. In conjunction with an earlier study on SCP bound to dihydropyridine drugs (Zhorov and Ananthanarayanan (1996) Biophys. J. 70, 22), our data suggest that, in general, drug modulation of SCP would involve the interaction of the ligands with the pore-bound Ca2+ and with the hydrophobic gate. In light of the functional similarity between SCP and L-type Ca2+ channel, it is likely that the latter would also interact with drugs in a similar fashion.

Amino Acid Sequence↗
PubMed2003

Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations.

Protein-protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. The method employs a low-resolution, rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 10(5) independent simulations are carried out, and the resulting "decoys" are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently determined coordinates of one or both monomers. Experimental binding affinities correlate with the calculated score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue-residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biologically important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein-protein interactions.

Algorithms↗
PubMedDate not supplied

Impact of conformational flexibility on three-dimensional similarity searching using correlation vectors.

Many three-dimensional (3D) virtual screening concepts, like automated docking or pharmacophore searching, rely on the calculation of a "bioactive" or "receptor-relevant" conformation of a molecule to assess its biological activity. We investigated the dependence of the presence of conformations near the "bioactive" conformation on three-dimensional similarity searching with pharmacophore-based correlation vectors (CATS3D approach). Cocrystal structures of 11 target classes served as queries for virtual screening of a database of annotated ligands. Different numbers of conformations were calculated. Single 3D structures were obtained using the 3D structure generator CORINA and conformational ensembles by the conformation generation program ROTATE. This approach was able to reproduce conformations for high resolution cocrystal structures. For virtual screening we found that using only the CORINA-generated single conformation already resulted in a significant enrichment of isofunctional molecules having the same biological property profile. This observation was also made for ligand classes with many rotatable bonds. Although more similar conformations were considered to be more similar in the CATS3D description, the impact of using multiple conformations on the enrichment of actives was not as high as expected. CATS3D provides an alignment-free three-dimensional virtual screening approach that is less dependent on the presence of conformations which are close to the "bioactive" conformation of a molecule compared to methods that rely on an explicit three-dimensional alignment of molecules.

Algorithms↗
PubMed1996

A dataset of protein-protein interfaces generated with a sequence-order-independent comparison technique.

While there are a number of structurally non-redundant datasets of protein monomers, there is none of protein-protein interfaces. Yet, the availability of such a dataset is expected to provide an added insight into a number of investigations. First and foremost among these is analyzing the interfaces to obtain their prevailing architectures, the forces that account for the protein-protein associations and their packing considerations. Their comparisons with those of the monomers are likely to shed additional light on protein-protein recognition on the one hand and on the folding of the polypeptide chain on the other. Docking simulations are also expected to benefit from the existence of such a dataset. A major stumbling block to the generation of a dataset of interfaces has been that the interface is composed of at least two chains. Furthermore, in the interfaces, each of the chains might be represented by non-contiguous pieces. Their order in the interfaces being compared might be different as well. This discontinuity stems from the definition of an interface. An interface consists of interacting residues between the chains, and those that are in their vicinity in the supporting scaffold, within a certain distance threshold. This necessarily yields unordered fragments, as well as isolated residues. Our novel, efficient, sequence-order-independent structural comparison technique is ideally suited to handle the task of the generation of a library of structurally non-redundant protein-protein interfaces. As it is computer-vision based, it views atoms as collections of points in space, disregarding their chain connectivity. In this work, 351 interface-families are created. Comparisons of the interfaces, and separately, of the chains which contribute to them, yield some interesting cases. In one of the cases, while two interfaces are similar, the structure of only one of the two chains is similar between the two complexes. The structure of the second chain of the first complex differs from that of the second chain of the second complex. Here the structure of the cleft in the first chain dictates the specific binding interactions. In another case, while the interfaces in the two complexes are similar, both chains composing them differ between the complexes. Lastly, the chains composing the complexes are similar, but the interfaces are dissimilar, providing a set of data for investigations of the favorable orientations of protein-protein associations.

Algorithms↗
PubMed2004

Study of the functional interaction of the 900 Tetraloop of 16S ribosomal RNA with helix 24 within the bacterial ribosome.

The 900 tetraloop that caps helix 27 of 16S ribosomal RNA (rRNA) is amongst the most conserved regions of rRNA. This tetraloop forms a GNRA motif that docks into the minor groove of three base-pairs at the bottom of helix 24 of 16S rRNA in the 30S subunit. Both the tetraloop and its receptor in helix 24 contact the 23S rRNA, forming the intersubunit bridge B2c. Here, we investigated the interaction between the 900 tetraloop and its receptor by genetic complementation. We used a specialized ribosome system in combination with an in vivo instant evolution approach to select mutations in helix 24 compensating for a mutation in the 900 tetraloop (A900G) that severely decreases ribosomal activity, impairing subunit association and translational fidelity. We selected two mutants where the G769-C810 base-pair of helix 24 was substituted with either U-A or C x A. When these mutations in helix 24 were investigated in the context of a wild-type 900 tetraloop, the C x A but not the U-A mutation severely impaired ribosome activity, interfering with subunit association and decreasing translational fidelity. In the presence of the A900G mutation, both mutations in helix 24 increased the ribosome activity to the same extent. Subunit association and translational fidelity were increased to the same level. Computer modeling was used to analyze the effect of the mutations in helix 24 on the interaction between the tetraloop and its receptor. This study demonstrates the functional importance of the interaction between the 900 tetraloop and helix 24.

Base Sequence↗