Unknown Three-dimensional Structure Research Articles

“Capillary” Structures in Transversely Trapped Nonlinear Optical Beams

A mathematical analogy between paraxial optics with two circular polarizations of light in a defocusing Kerr medium with positive dispersion, binary Bose–Einstein condensates of cold atoms in the phase separation regime, and hydrodynamics of two immiscible compressible liquids can help in theoretical search for unknown three-dimensional coherent optical structures. In this work, transversely trapped (by a smooth profile of the refractive index) light beams are considered and new numerical examples are presented, including a “floating drop,” a precessing longitudinal optical vortex with an inhomogeneous profile of filling with the second component, and the combination of a drop and a vortex filament. Filled vortices that are perpendicular to the beam axis and propagate at large distances have also been simulated.

Small-Angle X-ray Scattering Data in Combination with RosettaDock Improves the Docking Energy Landscape.

We have performed a benchmark to evaluate the relative success of using small-angle X-ray scattering (SAXS) data as constraints (hereafter termed SAXSconstrain) in the RosettaDock protocol (hereafter termed RosettaDockSAXS). For this purpose, we have chosen 38 protein complex structures, calculated the theoretical SAXS data for the protein complexes using the program CRYSOL, and then used the SAXS data as constraints. We further considered a few examples where crystal structures and experimental SAXS data are available. SAXSconstrain were added to the protocol in the initial, low-resolution docking step, allowing fast rejection of complexes that violate the shape restraints imposed by the SAXS data. Our results indicate that the implementation of SAXSconstrain in general reduces the sampling space of possible protein-protein complexes significantly and can indeed increase the probability of finding near-native protein complexes. The methodology used is based on rigid-body docking and works for cases where no or minor conformational changes occur upon binding of the docking partner. In a wider perspective, the strength of RosettaDockSAXS lies in the combination of low-resolution structural information on protein complexes in solution from SAXS experiments with protein-protein interaction energies obtained from RosettaDock, which will allow the prediction of unknown three-dimensional atomic structures of protein-protein complexes.

Biochemical Pharmacology of the Sigma-1 Receptor.

The sigma-1 receptor (S1R) is a 223 amino acid two transmembrane (TM) pass protein. It is a non-ATP-binding nonglycosylated ligand-regulated molecular chaperone of unknown three-dimensional structure. The S1R is resident to eukaryotic mitochondrial-associated endoplasmic reticulum and plasma membranes with broad functions that regulate cellular calcium homeostasis and reduce oxidative stress. Several multitasking functions of the S1R are underwritten by chaperone-mediated direct (and indirect) interactions with ion channels, G-protein coupled receptors and cell-signaling molecules involved in the regulation of cell growth. The S1R is a promising drug target for the treatment of several neurodegenerative diseases related to cellular stress. In vitro and in vivo functional and molecular characteristics of the S1R and its interactions with endogenous and synthetic small molecules have been discovered by the use of pharmacologic, biochemical, biophysical, and molecular biology approaches. The S1R exists in monomer, dimer, tetramer, hexamer/octamer, and higher oligomeric forms that may be important determinants in defining the pharmacology and mechanism(s) of action of the S1R. A canonical GXXXG in putative TM2 is important for S1R oligomerization. The ligand-binding regions of S1R have been identified and include portions of TM2 and the TM proximal regions of the C terminus. Some client protein chaperone functions and interactions with the cochaperone 78-kDa glucose-regulated protein (binding immunoglobulin protein) involve the C terminus. Based on its biochemical features and mechanisms of chaperone action the possibility that the S1R is a member of the small heat shock protein family is discussed.

Computer modelling of monoamine oxidases

The article summarized results of long-term studies on active site structures of monoamine oxidase (MAO) performed in the Institute of Biomedical Chemistry (Russia) by computer modeling approaches. In mammals MAO exists in two highly homologous forms, MAO A and MAO B, distinguished by substrate specificity, inhibitor selectivity, and other characteristics. The development of approaches for active site modeling of these enzymes (with unknown three-dimensional structures) was originally based on analysis of inhibitory activity of selective inhibitors. It started from the analysis of relationships between the geometrical sizes of conformationally rigid molecules and their inhibitory activity. These studies resulted in molding of the active site structures of MAO A and MAO B. These molds reflect the sizes and shapes of active sites of these enzymes. These mold models have been used for virtual screening of molecular databases for new selective and non-selective MAO inhibitors. The generated models have been compared with three-dimensional structures of MAO A and MAO B, which appeared later.

Bayesian Inference of Initial Models in Cryo-Electron Microscopy Using Pseudo-atoms

Single-particle cryo-electron microscopy is widely used to study the structure of macromolecular assemblies. Tens of thousands of noisy two-dimensional images of the macromolecular assembly viewed from different directions are used to infer its three-dimensional structure. The first step is to estimate a low-resolution initial model and initial image orientations. This is a challenging global optimization problem with many unknowns, including an unknown orientation for each two-dimensional image. Obtaining a good initial model is crucial for the success of the subsequent refinement step. We introduce a probabilistic algorithm for estimating an initial model. The algorithm is fast, has very few algorithmic parameters, and yields information about the precision of estimated model parameters in addition to the parameters themselves. Our algorithm uses a pseudo-atomic model to represent the low-resolution three-dimensional structure, with isotropic Gaussian components as moveable pseudo-atoms. This leads to a significant reduction in the number of parameters needed to represent the three-dimensional structure, and a simplified way of computing two-dimensional projections. It also contributes to the speed of the algorithm. We combine the estimation of the unknown three-dimensional structure and image orientations in a Bayesian framework. This ensures that there are very few parameters to set, and specifies how to combine different types of prior information about the structure with the given data in a systematic way. To estimate the model parameters we use Markov chain Monte Carlo sampling. The advantage is that instead of just obtaining point estimates of model parameters, we obtain an ensemble of models revealing the precision of the estimated parameters. We demonstrate the algorithm on both simulated and real data.

Computer modelling of monoaminoxidases

The article summarized results of studies on active site structures of monoamine oxidases (MAO) performed in the Institute of Biomedical Chemistry (Russia) by computer modelling approaches. MAO, catalyzing the reaction of oxidative deamination of major neurotransmitter monoamines, exists in two highly homologous forms, MAO A and MAO B, distinguished by substrate specificity and inhibitor selectivity. The development of approaches for active site modelling of these enzymes (with unknown three-dimensional structures) started from analysis of relationship between the geometrical sizes of rigid indole and isatin derivatives and their inhibitory activity. These studies resulted in molding of the active site structures of MAO A and MAO B. These molds reflect the sizes and shapes of active sites of these enzymes. These mold models have been used for virtual screening of molecular databases for new inhibitors. The models obtained at different stages of MAO investigations have been compared with recently appeared three-dimensional structures of MAO A and MAO B.

MAGNETIC ENERGY AND HELICITY BUDGETS IN THE ACTIVE-REGION SOLAR CORONA. II. NONLINEAR FORCE-FREE APPROXIMATION

Expanding on an earlier work that relied on linear force-free magnetic fields, we self-consistently derive the instantaneous free magnetic energy and relative magnetic helicity budgets of an unknown three-dimensional nonlinear force-free magnetic structure extending above a single, known lower-boundary magnetic field vector. The proposed method does not rely on the detailed knowledge of the three-dimensional field configuration but is general enough to employ only a magnetic connectivity matrix on the lower boundary. The calculation yields a minimum free magnetic energy and a relative magnetic helicity consistent with this free magnetic energy. The method is directly applicable to photospheric or chromospheric vector magnetograms of solar active regions. Upon validation, it basically reproduces magnetic energies and helicities obtained by well-known, but computationally more intensive and non-unique, methods relying on the extrapolated three-dimensional magnetic field vector. We apply the method to three active regions, calculating the photospheric connectivity matrices by means of simulated annealing, rather than a model-dependent nonlinear force-free extrapolation. For two of these regions we correct for the inherent linear force-free overestimation in free energy and relative helicity that is larger for larger, more eruptive, active regions. In the third studied region, our calculation can lead to a physical interpretation of observed eruptive manifestations. We conclude that the proposed method, including the proposed inference of the magnetic connectivity matrix, is practical enough to contribute to a physical interpretation of the dynamical evolution of solar active regions.

PROCARB: A Database of Known and Modelled Carbohydrate-Binding Protein Structures with Sequence-Based Prediction Tools

Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins) as well as noncovalently (protein-carbohydrate complexes) is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i) Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB), (ii) Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii) CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.

Abstract 2681: EWS-FLI1 as a molecular target: Small molecule inhibitors for a disordered protein

Abstract Ewing's sarcoma family of tumors are characterized by the EWS-FLI1 oncogenic fusion protein. Our previous studies show that RNA Helicase A (RHA) enhances EWS-FLI1 driven oncogenesis, and interruption of this protein-protein complex by small molecule inhibitors validate this interaction as a unique therapeutic target (NatMed 2009 Jul;15(7):750-6). EWS-FLI1 is a significantly hydrophobic disordered protein with unknown three-dimensional structure, which therefore precludes standard structure-based small molecule design. Given the challenges of drug design targeted to EWS-FLI1, we hypothesize that the optimization of a peptide displacement assay using small molecules can predict and direct the design of more potent analogs. Fluorescence polarization (FP) was originally used to measure RHA peptide displacement from EWS-FLI1, but is time consuming and reagent limiting. To identify new strategies for higher-throughput screening, a TECAN ULTRA 384 was used for assay detection in a 96-well plate format. However, this resulted in high background and low signal. A second approach, AlphaScreen (amplified luminescent proximity homogenous assay, PerkinElmer), uses a bead-based interaction system based on energy conversion and generation of chemiluminescence when acceptor and donor beads are brought together during binding. Results show a 6-fold dynamic range between bound and quenched beads, in comparison to just 2.5-fold for FP and less than two-fold for TECAN. Our small molecule, YK-4-279, is able to reduce the signal down to baseline, indicating that YK-4-279 dissociates the RHA peptide and EWS-FLI1. Key negative controls support specific binding between EWS-FLI1 and the RHA peptide. In addition, YK-4-279 was unable to quench the signal from a positive control using immunoglobulin, supporting the conclusion that YK-4-279 disrupts the specific protein-peptide binding rather than directly extinguishing the chemiluminescence. Data from the AlphaScreen will be used as input to a quantitative-structure activity relationship (QSAR) method. This QSAR method will predict biological activity from chemical structure and the knowledge gained from AlphaScreen will aid in the optimization and design of future analogs. In our initial work, we used the Free-Wilson QSAR method, converting the structure of the small molecules into a numerical format allowing for a mathematical comparison between structures, to populate a table with 32 small molecule analogs of YK-4-279. The AlphaScreen data may also be used with other QSAR methods, to which we may transition in later work. AlphaScreen technology provides a method to quantitatively compare binding of small molecules in a high-throughput screening system, yields a greater dynamic range with more specificity, and provides data that will help to predict the binding of other analogs with similar chemical structures. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2681.

Atom-by-atom structural and chemical analysis by annular dark-field electron microscopy

Direct imaging and chemical identification of all the atoms in a material with unknown three-dimensional structure would constitute a very powerful general analysis tool. Transmission electron microscopy should in principle be able to fulfil this role, as many scientists including Feynman realized early on. It images matter with electrons that scatter strongly from individual atoms and whose wavelengths are about 50 times smaller than an atom. Recently the technique has advanced greatly owing to the introduction of aberration-corrected optics. However, neither electron microscopy nor any other experimental technique has yet been able to resolve and identify all the atoms in a non-periodic material consisting of several atomic species. Here we show that annular dark-field imaging in an aberration-corrected scanning transmission electron microscope optimized for low voltage operation can resolve and identify the chemical type of every atom in monolayer hexagonal boron nitride that contains substitutional defects. Three types of atomic substitutions were found and identified: carbon substituting for boron, carbon substituting for nitrogen, and oxygen substituting for nitrogen. The substitutions caused in-plane distortions in the boron nitride monolayer of about 0.1 A magnitude, which were directly resolved, and verified by density functional theory calculations. The results demonstrate that atom-by-atom structural and chemical analysis of all radiation-damage-resistant atoms present in, and on top of, ultra-thin sheets has now become possible.

Abstract B181: EWS-FLI1 as a molecular target: Identification of inhibitors for a disordered protein

Abstract Ewing's sarcoma family of tumors (ESFT) are characterized by the EWS-FLI1 oncogenic fusion protein which results from a t(11;22) chromosomal translocation. Our previous studies show that RNA Helicase A (RHA) enhances EWS-FLI1 driven oncogenesis, and interruption of this protein-protein complex by small molecule inhibitors validate this interaction as a unique therapeutic target (NatMed 2009 Jul;15(7):750-6). EWS-FLI1 is a significantly hydrophobic disordered protein with unknown three-dimensional structure, which therefore precludes standard structure-based small molecule design. Fortunately, disordered proteins have a greater potential for binding with small molecule inhibitors due to structural flexibility. Given the challenges of drug design targeted to EWS-FLI1, we hypothesize that the optimization of a peptide displacement assay using small molecules can predict and direct the design of more potent analogs. Our methods originally used fluorescence polarization (FP) to measure RHA peptide displacement from EWS-FLI1. FP is a time consuming and reagent-limiting assay, so we evaluated new strategies using a 96-well plate format with the goal of high-throughput data collection. The first approach used a TECAN ULTRA 384 for assay detection and resulted in readings with high background noise and low signal. A second approach, AlphaScreen (amplified luminescent proximity homogenous assay, PerkinElmer), uses a bead-based interaction system based on energy conversion and generation of chemiluminescence when acceptor and donor beads are brought together during binding. The AlphaScreen assay uses approximately 3 ug of EWS-FLI1 protein per assay well and binds the 6-histadine tagged protein to the nickel-chelated donor beads while anti-FITC acceptor beads detect the flouresceintagged peptide. Our results show a 6-fold dynamic range between bound and quenched beads, in comparison to just 2.5-fold for FP and less than two-fold for the TECAN platform. Our small molecule YK-4-279 is able to reduce the signal back down to baseline, indicating that YK-4-279 dissociates the RHA peptide and EWS-FLI1. Key negative controls support specific binding between EWS-FLI1 and the RHA peptide. In addition, YK-4-279 was unable to quench the signal from a positive control using immunoglobulin, supporting the conclusion that YK-4-279 does indeed disrupt the specific protein-peptide binding rather than directly extinguishing the chemiluminescence. Data from the AlphaScreen will be used as input to a quantitative-structure activity relationship (QSAR) method. This QSAR method will predict biological activity from chemical structure and the knowledge gained from AlphaScreen will aid in the optimization and design of future analogs. In our initial work, we used the Free-Wilson QSAR method, converting the structure of the small molecules into a numerical format which allows for a mathematical comparison between structures, to populate a table with 32 small molecule analogs of YK-4-279. The AlphaScreen data may also be used with other QSAR methods, to which we may transition in later work. The AlphaScreen technology provides a method to quantitatively compare binding of small molecules in a high-throughput screening system, yields a greater dynamic range with more specificity, and provides data that will help to predict the binding of other analogs with similar chemical structures. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):B181.

Solution NMR structures of proteins VPA0419 from Vibrio parahaemolyticus and yiiS from Shigella flexneri provide structural coverage for protein domain family PFAM 04175

Protein with 83 residues, VPA0419 (residues 17–99, numbered 1–83) (gi|81726230, SwissProt/TrEMBL ID Q87J34_VIBPA, accession number {"type":"entrez-protein","attrs":{"text":"Q87J34","term_id":"81726230","term_text":"Q87J34"}}Q87J34)1 from Vibrio parahaemolyticus and 99-residue protein yiiS (gi|81722782, SwissProt/TrEMBL ID Q83IT9_SHIFL, accession number {"type":"entrez-protein","attrs":{"text":"Q83IT9","term_id":"81722782","term_text":"Q83IT9"}}Q83IT9)2, 3 from Shigella flexneri were selected as targets for the Protein Structure Initiative-2 and assigned to the Northeast Structural Genomics Consortium (NESG) for structure determination (NESG target ID VpR68 for VPA0419 and SfR90 for yiiS). VPA0419 and yiiS share 36% sequence identity, but show no significant sequence identity with any protein with known three-dimensional structure in the Protein Data Bank (PDB4). The two proteins belong to Pfam5 domain family PF04175 which currently contains 123 members with unknown three-dimensional structures and functional annotation, all of which appear to be found in gamma proteobacteria (for a sequence alignment, see Fig. S1 in Supporting Information). The NMR structures of VPA0419 and yiiS were solved using a protocol for high-throughput protein structure determination6 and represent the first ones for protein family PF04175. As these structures are the first for PF04175, “high leverage”7 of the experimental structures can be expected for calculating homology models.8, 9

The Era of RNA Awakening: Structural biology of RNA in the early years

In the mid-1950s, RNA was a somewhat mysterious molecule with unknown three-dimensional structure and little hard evidence of biological function. Changes began with the 1956 discoveries of the RNA double helix and the phenomenon of nucleic acid hybridization. Discovery of the DNA-RNA hybrid helix in 1960 opened the door to understanding biological information transfer. Single-crystal X-ray diffraction analysis made it possible to precisely define the RNA double helix, discover the novel L-shaped fold of transfer RNA (tRNA), and finally reveal the complete three-dimensional tRNA structure by 1974. By then, a functional understanding of protein synthesis had developed with an appreciation of the various roles of different RNA species. This was the era of RNA awakening.

CSSP(Consensus Secondary Structure Prediction): a web-based server for structural biologists

Sequence–structure correlation studies are important in deciphering the relationships between various structural aspects, which may shed light on the protein-folding problem. The first step of this process is the prediction of secondary structure for a protein sequence of unknown three-dimensional structure. To this end, a web server has been created to predict the consensus secondary structure using well known algorithms from the literature. Furthermore, the server allows users to see the occurrence of predicted secondary structural elements in other structure and sequence databases and to visualize predicted helices as a helical wheel plot. The web server is accessible at http://bioserver1.physics.iisc.ernet.in/cssp/.

Protein contact order prediction from primary sequences

BackgroundContact order is a topological descriptor that has been shown to be correlated with several interesting protein properties such as protein folding rates and protein transition state placements. Contact order has also been used to select for viable protein folds from ab initio protein structure prediction programs. For proteins of known three-dimensional structure, their contact order can be calculated directly. However, for proteins with unknown three-dimensional structure, there is no effective prediction method currently available.ResultsIn this paper, we propose several simple yet very effective methods to predict contact order from the amino acid sequence only. One set of methods is based on a weighted linear combination of predicted secondary structure content and amino acid composition. Depending on the number of components used in these equations it is possible to achieve a correlation coefficient of 0.857–0.870 between the observed and predicted contact order. A second method, based on sequence similarity to known three-dimensional structures, is able to achieve a correlation coefficient of 0.977. We have also developed a much more robust implementation for calculating contact order directly from PDB coordinates that works for > 99% PDB files. All of these contact order predictors and calculators have been implemented as a web server (see Availability and requirements section for URL).ConclusionProtein contact order can be effectively predicted from the primary sequence, at the absence of three-dimensional structure. Three factors, percentage of residues in alpha helices, percentage of residues in beta strands, and sequence length, appear to be strongly correlated with the absolute contact order.

The Key Residue for Substrate Transport (Glu14) in the EmrE Dimer Is Asymmetric

Transport proteins exhibiting broad substrate specificities are major determinants for the phenomenon of multidrug resistance. The Escherichia coli multidrug transporter EmrE, a 4-transmembrane, helical 12-kDa membrane protein, forms a functional dimer to transport a diverse array of aromatic, positively charged substrates in a proton/drug antiport fashion. Here, we report (13)C chemical shifts of the essential residue Glu(14) within the binding pocket. To ensure a native environment, EmrE was reconstituted into E. coli lipids. Experiments were carried out using one- and two-dimensional double quantum filtered (13)C solid state NMR. For an unambiguous assignment of Glu(14), an E25A mutation was introduced to create a single glutamate mutant. Glu(14) was (13)C-labeled using cell-free expression. Purity, labeling, homogeneity, and functionality were probed by mass spectrometry, NMR spectroscopy, freeze fracture electron microscopy, and transport assays. For Glu(14), two distinct sets of chemical shifts were observed that indicates structural asymmetry in the binding pocket of homodimeric EmrE. Upon addition of ethidium bromide, chemical shift changes and altered line shapes were observed, demonstrating substrate coordination by both Glu(14) in the dimer.

Magnetic Energy and Helicity Budgets in the Active Region Solar Corona. I. Linear Force‐Free Approximation

Expanding on an earlier work that relied on linear force-free magnetic fields, we self-consistently derive the instantaneous free magnetic energy and relative magnetic helicity budgets of an unknown three-dimensional nonlinear force-free magnetic structure extending above a single, known lower-boundary magnetic field vector. The proposed method does not rely on the detailed knowledge of the three-dimensional field configuration but is general enough to employ only a magnetic connectivity matrix on the lower boundary. The calculation yields a minimum free magnetic energy and a relative magnetic helicity consistent with this free magnetic energy. The method is directly applicable to photospheric or chromospheric vector magnetograms of solar active regions. Upon validation, it basically reproduces magnetic energies and helicities obtained by well-known, but computationally more intensive and non-unique, methods relying on the extrapolated three-dimensional magnetic field vector. We apply the method to three active regions, calculating the photospheric connectivity matrices by means of simulated annealing, rather than a model-dependent nonlinear force-free extrapolation. For two of these regions we correct for the inherent linear force-free overestimation in free energy and relative helicity that is larger for larger, more eruptive, active regions. In the third studied region, our calculation can lead to a physical interpretation of observed eruptive manifestations. We conclude that the proposed method, including the proposed inference of the magnetic connectivity matrix, is practical enough to contribute to a physical interpretation of the dynamical evolution of solar active regions.

Molecular Basis for the Aromatization Reaction and Exemestane-Mediated Irreversible Inhibition of Human Aromatase

Aromatase converts androgens to aromatic estrogens. Aromatase inhibitors have been used as first-line drugs in the treatment of hormone-dependent breast cancer. Structural basis of the aromatization reaction and drug recognition by aromatase has remained elusive because of its unknown three-dimensional structure. In this study, recombinant human aromatase was expressed and purified from Escherichia coli. Using this purified and active preparation, the three-dimensional folding of aromatase was revealed by proteomic analysis. Combined with site-directed mutagenesis, several critical residues involved in enzyme catalysis and suicide inhibition by exemestane were evaluated. Based on our results, a new clamping mechanism of substrate/exemestane binding to the active site is proposed. These structure-function studies of aromatase would provide useful information to design more effective aromatase inhibitors for the prevention and the treatment of hormone-dependent breast cancer.

Generalized modeling of enzyme–ligand interactions using proteochemometrics and local protein substructures

Modeling and understanding protein-ligand interactions is one of the most important goals in computational drug discovery. To this end, proteochemometrics uses structural and chemical descriptors from several proteins and several ligands to induce interaction-models. Here, we present a new and generalized approach in which proteins varying greatly in terms of sequence and structure are represented by a library of local substructures. Using linear regression and rule-based learning, we combine such local substructures with chemical descriptors from the ligands to model binding affinity for a training set of hydrolase and lyase enzymes. We evaluate the predictive performance of these models using cross validation and sets of unseen ligand with unknown three-dimensional structure. The models are shown to generalize by outperforming models using descriptors from only proteins or only ligands, or models using global structure similarities rather than local similarities. Thus, we demonstrate that this approach is capable of describing dependencies between local structural properties and ligands in otherwise dissimilar protein structures. These dependencies are often, but not always, associated with local substructures that are in contact with the ligands. Finally, we show that strongly bound enzyme-ligand complexes require the presence of particular local substructures, while weakly bound complexes may be described by the absence of certain properties. The results demonstrate that the alignment-independent approach using local substructures is capable of describing protein-ligand interaction for largely different proteins and hence opens up for proteochemometrics-analysis of the interaction-space of entire proteomes. Current approaches are limited to families of closely related proteins. families of closely related proteins.

Prediction of protein domain boundaries from statistics of appearance of amino acid residues

We have created a database of two-domain proteins with homology less than 25% (452 proteins). Based on one half of this set of proteins statistics of appearance of amino acid residues on the domain boundaries of multiple domain proteins has been obtained. Small and hydrophilic amino acids (proline, glycine, asparagine, glutamic acid, arginine and others) appear on the domain boundaries more often than in the whole protein. Opposite, hydrophobic amino acid residues (tryptophane, methionine, phenylalanine and others) appear on the domain boundaries more rarely. The obtained scales of the appearance of amino acid residues on the boundary regions from the statistics have been used for calculation of domain boundaries in the proteins of the second half of the database. The probability scale obtained by averaging the appearance of amino acid residues on the domain boundary region including 8 residues (+/-4 residues from the real domain boundary) gives the best result: for 57% of proteins the predicted boundary was closer than 40 residues to the boundary assigned from three-dimensional structures, for 41% it was closer than 20 residues from the real boundary. The probability scale was used to predict domain boundaries for proteins with unknown three-dimensional structure (international competition CASP6).