Systematic solution to homo‐oligomeric structures determined by NMR

Protein structure determination by NMR has predominantly relied on simulated annealing‐based conformational search for a converged fold using primarily distance constraints, including constraints derived from nuclear Overhauser effects, paramagnetic relaxation enhancement, and cysteine crosslinkings. Although there is no guarantee that the converged fold represents the global minimum of the conformational space, it is generally accepted that good convergence is synonymous to the global minimum. Here, we show such a criterion breaks down in the presence of large numbers of ambiguous constraints from NMR experiments on homo‐oligomeric protein complexes. A systematic evaluation of the conformational solutions that satisfy the NMR constraints of a trimeric membrane protein, DAGK, reveals 9 distinct folds, including the reported NMR and crystal structures. This result highlights the fundamental limitation of global fold determination for homo‐oligomeric proteins using ambiguous distance constraints and provides a systematic solution for exhaustive enumeration of all satisfying solutions. Proteins 2015; 83:651–661. © 2015 Wiley Periodicals, Inc.     

Energetically unfavorable amide conformations for N6‐acetyllysine side chains in refined protein structures

The reversible acetylation of lysine to form N6‐acetyllysine in the regulation of protein function is a hallmark of epigenetics. Acetylation of the positively charged amino group of the lysine side chain generates a neutral N‐alkylacetamide moiety that serves as a molecular “switch” for the modulation of protein function and protein–protein interactions. We now report the analysis of 381 N6‐acetyllysine side chain amide conformations as found in 79 protein crystal structures and 11 protein NMR structures deposited in the Protein Data Bank (PDB) of the Research Collaboratory for Structural Bioinformatics. We find that only 74.3% of N6‐acetyllysine residues in protein crystal structures and 46.5% in protein NMR structures contain amide groups with energetically preferred trans or generously trans conformations. Surprisingly, 17.6% of N6‐acetyllysine residues in protein crystal structures and 5.3% in protein NMR structures contain amide groups with energetically unfavorable cis or generously cis conformations. Even more surprisingly, 8.1% of N6‐acetyllysine residues in protein crystal structures and 48.2% in NMR structures contain amide groups with energetically prohibitive twisted conformations that approach the transition state structure for cis‐trans isomerization. In contrast, 109 unique N‐alkylacetamide groups contained in 84 highly accurate small molecule crystal structures retrieved from the Cambridge Structural Database exclusively adopt energetically preferred trans conformations. Therefore, we conclude that cis and twisted N6‐acetyllysine amides in protein structures deposited in the PDB are erroneously modeled due to their energetically unfavorable or prohibitive conformations. Proteins 2013; © 2012 Wiley Periodicals, Inc.     

Multiple solvent crystal structures of ribonuclease A: An assessment of the method

The multiple solvent crystal structures (MSCS) method uses organic solvents to map the surfaces of proteins. It identifies binding sites and allows for a more thorough examination of protein plasticity and hydration than could be achieved by a single structure. The crystal structures of bovine pancreatic ribonuclease A (RNAse A) soaked in the following organic solvents are presented: 50% dioxane, 50% dimethylformamide, 70% dimethylsulfoxide, 70% 1,6‐hexanediol, 70% isopropanol, 50% R,S,R‐bisfuran alcohol, 70% t‐butanol, 50% trifluoroethanol, or 1.0M trimethylamine‐N‐oxide. This set of structures is compared with four sets of crystal structures of RNAse A from the protein data bank (PDB) and with the solution NMR structure to assess the validity of previously untested assumptions associated with MSCS analysis. Plasticity from MSCS is the same as from PDB structures obtained in the same crystal form and deviates only at crystal contacts when compared to structures from a diverse set of crystal environments. Furthermore, there is a good correlation between plasticity as observed by MSCS and the dynamic regions seen by NMR. Conserved water binding sites are identified by MSCS to be those that are conserved in the sets of structures taken from the PDB. Comparison of the MSCS structures with inhibitor‐bound crystal structures of RNAse A reveals that the organic solvent molecules identify key interactions made by inhibitor molecules, highlighting ligand binding hot‐spots in the active site. The present work firmly establishes the relevance of information obtained by MSCS. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Online homology modelling as a means of bridging the sequence-structure gap

For even the best-studied species, there is a large gap in their representation in the protein databank (PDB) compared to within sequence databases. Typically, less than 2% of sequences are represented in the PDB. This is partly due to the considerable experimental challenge and manual inputs required to solve three dimensional structures by methods such as X-ray diffraction and multi-dimensional nuclear magnetic resonance (NMR) spectroscopy in comparison to high-throughput sequencing. This gap is made even wider by the high level of redundancy within the PDB and under-representation of some protein categories such as membrane-associated proteins which comprise approximately 25% of proteins encoded in genomes. A traditional route to closing the sequence-structure gap is offered by homology modelling whereby the sequence of a target protein is modelled on a template represented in the PDB using in silico energy minimisation approaches. More recently, online homology servers have become available which automatically generate models from proffered sequences. However, many online servers give little indication of the structural plausibility of the generated model. In this paper, the online homology server Geno3D will be described. This server uses similar software to that used in modelling structures during structure determination and thus generates data allowing determination of the structural plausibility of models. For illustration, modelling of a chemotaxis protein (CheY) from Pseudomononas entomophila L48 (accession YP_609298) on a template (PDB id. 1mvo), the phosphorylation domain of an outer membrane protein PhoP from Bacillus subtilis, will be described.     

A hybrid NMR/SAXS‐based approach for discriminating oligomeric protein interfaces using Rosetta

Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology‐based methods, protein–protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet‐V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution. Proteins 2015; 83:309–317. © 2014 Wiley Periodicals, Inc.     

Prediction of protein loop geometries in solution

The ability to determine the structure of a protein in solution is a critical tool for structural biology, as proteins in their native state are found in aqueous environments. Using a physical chemistry based prediction protocol, we demonstrate the ability to reproduce protein loop geometries in experimentally derived solution structures. Predictions were run on loops drawn from (1)NMR entries in the Protein Databank (PDB), and from (2) the RECOORD database in which NMR entries from the PDB have been standardized and re-refined in explicit solvent. The predicted structures are validated by comparison with experimental distance restraints, a test of structural quality as defined by the WHAT IF structure validation program, root mean square deviation (RMSD) of the predicted loops to the original structural models, and comparison of precision of the original and predicted ensembles. Results show that for the RECOORD ensembles, the predicted loops are consistent with an average of 95%, 91%, and 87% of experimental restraints for the short, medium and long loops respectively. Prediction accuracy is strongly affected by the quality of the original models, with increases in the percentage of experimental restraints violated of 2% for the short loops, and 9% for both the medium and long loops in the PDB derived ensembles. We anticipate the application of our protocol to theoretical modeling of protein structures, such as fold recognition methods; as well as to experimental determination of protein structures, or segments, for which only sparse NMR restraint data is available.     

MOTOR: Model assisted software for NMR structure determination

Eukaryotic proteins with important biological function can be partially unstructured, conformational flexible, or heterogenic. Crystallization trials often fail for such proteins. In NMR spectroscopy, parts of the polypeptide chain undergoing dynamics in unfavorable time regimes cannot be observed. De novo NMR structure determination is seriously hampered when missing signals lead to an incomplete chemical shift assignment resulting in an information content of the NOE data insufficient to determine the structure ab initio. We developed a new protein structure determination strategy for such cases based on a novel NOE assignment strategy utilizing a number of model structures but no explicit reference structure as it is used for bootstrapping like algorithms. The software distinguishes in detail between consistent and mutually exclusive pairs of possible NOE assignments on the basis of different precision levels of measured chemical shifts searching for a set of maximum number of consistent NOE assignments in agreement with 3D space. Validation of the method using the structure of the low molecular‐weight‐protein tyrosine phosphatase A (MptpA) showed robust results utilizing protein structures with 30–45% sequence identity and 70% of the chemical shift assignments. About 60% of the resonance assignments are sufficient to identify those structural models with highest conformational similarity to the real structure. The software was benchmarked by de novo solution structures of fibroblast growth factor 21 (FGF21) and the extracellular fibroblast growth factor receptor domain FGFR4 D2, which both failed in crystallization trials and in classical NMR structure determination. Proteins 2013; 81:2007–2022. © 2013 Wiley Periodicals, Inc.     

Homology‐based hydrogen bond information improves crystallographic structures in the PDB

The Protein Data Bank (PDB) is the global archive for structural information on macromolecules, and a popular resource for researchers, teachers, and students, amassing more than one million unique users each year. Crystallographic structure models in the PDB (more than 100,000 entries) are optimized against the crystal diffraction data and geometrical restraints. This process of crystallographic refinement typically ignored hydrogen bond (H‐bond) distances as a source of information. However, H‐bond restraints can improve structures at low resolution where diffraction data are limited. To improve low‐resolution structure refinement, we present methods for deriving H‐bond information either globally from well‐refined high‐resolution structures from the PDB‐REDO databank, or specifically from on‐the‐fly constructed sets of homologous high‐resolution structures. Refinement incorporating HOmology DErived Restraints (HODER), improves geometrical quality and the fit to the diffraction data for many low‐resolution structures. To make these improvements readily available to the general public, we applied our new algorithms to all crystallographic structures in the PDB: using massively parallel computing, we constructed a new instance of the PDB‐REDO databank ( https://pdb-redo.eu ). This resource is useful for researchers to gain insight on individual structures, on specific protein families (as we demonstrate with examples), and on general features of protein structure using data mining approaches on a uniformly treated dataset.     

Synthesis of 6‐[4‐(4‐Propoxyphenyl)piperazin‐1‐yl]‐9H‐purine Derivatives as Antimycobacterial and Antifungal Agents: In Vitro Evaluation and In Silico Study

A series of novel alkyl substituted purines were synthesized. 6‐[4‐(4‐Propoxyphenyl)piperazin‐1‐yl]‐9H‐purine was used as the key starting material, which was synthesized via a multistep protocol and finally subjected for N‐alkylation with various alkyl halides with an aim to get prospective antimicrobial agents. The structures of the novel compounds were established by substantiating them through spectral techniques like ¹H‐NMR, ¹³C‐NMR, FT‐IR and EI‐MS. They were explored for antitubercular activity against Mycobacterium tuberculosis H37RV. Furthermore, they were checked for their antimicrobial activity concerning bacterial and fungal strains. The title compounds exhibited considerable antimicrobial activity without any significant toxicity. In silico studies depicted their good binding profile against Mycobacterium tuberculosis enoyl reductase (InhA; PDB ID: 4TZK) and Candida albicans dihydrofolate reductase (PDB ID: 1AI9). The title compounds obeyed Lipinski's parameters and have exhibited good drug‐like properties.     

Multiple helical conformations of the helix‐turn‐helix region revealed by NOE‐restrained MD simulations of tryptophan aporepressor,TrpR

The nature of flexibility in the helix‐turn‐helix region of E. coli trp aporepressor has been unexplained for many years. The original ensemble of nuclear magnetic resonance (NMR structures showed apparent disorder, but chemical shift and relaxation measurements indicated a helical region. Nuclear Overhauser effect (NOE) data for a temperature‐sensitive mutant showed more helical character in its helix‐turn‐helix region, but nevertheless also led to an apparently disordered ensemble. However, conventional NMR structure determination methods require all structures in the ensemble to be consistent with every NOE simultaneously. This work uses an alternative approach in which some structures of the ensemble are allowed to violate some NOEs to permit modeling of multiple conformational states that are in dynamic equilibrium. Newly measured NOE data for wild‐type aporepressor are used as time‐averaged distance restraints in molecular dynamics simulations to generate an ensemble of helical conformations that is more consistent with the observed NMR data than the apparent disorder in the previously reported NMR structures. The results indicate the presence of alternating helical conformations that provide a better explanation for the flexibility of the helix‐turn‐helix region of trp aporepressor. Structures representing these conformations have been deposited with PDB ID: 5TM0. Proteins 2017; 85:731–740. © 2016 Wiley Periodicals, Inc.     

Conjoined Use of EM and NMR in RNA Structure Refinement

More than 40% of the RNA structures have been determined using nuclear magnetic resonance (NMR) technique. NMR mainly provides local structural information of protons and works most effectively on relatively small biomacromolecules. Hence structural characterization of large RNAs can be difficult for NMR alone. Electron microscopy (EM) provides global shape information of macromolecules at nanometer resolution, which should be complementary to NMR for RNA structure determination. Here we developed a new energy term in Xplor-NIH against the density map obtained by EM. We conjointly used NMR and map restraints for the structure refinement of three RNA systems — U2/U6 small-nuclear RNA, genome-packing motif (Ψ^CD)₂ from Moloney murine leukemia virus, and ribosome-binding element from turnip crinkle virus. In all three systems, we showed that the incorporation of a map restraint, either experimental or generated from known PDB structure, greatly improves structural precision and accuracy. Importantly, our method does not rely on an initial model assembled from RNA duplexes, and allows full torsional freedom for each nucleotide in the torsion angle simulated annealing refinement. As increasing number of macromolecules can be characterized by both NMR and EM, the marriage between the two techniques would enable better characterization of RNA three-dimensional structures.     

Intrinsic nature of the three-dimensional structure of proteins as determined by distance geometry with good sampling properties

Summary A protocol for distance geometry calculation is shown to have excellent sampling properties in the determination of three-dimensional structures of proteins from nuclear magnetic resonance (NMR) data. This protocol uses a simulated annealing optimization employing mass-weighted molecular dynamics in four-dimensional space (Havel, T.F. (1991) Prog. Biophys. Mol. Biol., 56, 43–78). It attains an extremely large radius of convergence, allowing a random coil conformation to be used as the initial estimate for the succeeding optimization process. Computations are performed with four systems of simulated distance data as tests of the protocol, using an unconstrained l-alanine 30mer and three different types of proteins, bovine pancreatic trypsin inhibitor, the -amylase inhibitor Tendamistat, and the N-terminal domain of the 434-repressor. The test of the unconstrained polypeptide confirms that the sampled conformational space is that of the statistical random coil. In the larger and more complicated systems of the three proteins, the protocol gives complete convergence of the optimization without any trace of initial structure dependence. As a result of an exhaustive conformational sampling by the protocol, the intrinsic nature of the structures generated with distance restraints derived from NMR data has been revealed. When the sampled structures are compared with the corresponding X-ray structures, we find that the averages of the sampled structures always show a certain pattern of discrepancy from the X-ray structure. This discrepancy is due to the short distance nature of the distance restraints, and correlates with the characteristic shape of the protein molecule.Abbreviations r.m.s.d. root-mean-square deviation - MD molecular dynamics - NMR nuclear magnetic resonance - NOE nuclear Overhauser enhancement - BPTI bovine pancreatic trypsin inhibitor     

Evaluating protein structures determined by structural genomics consortia

Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X-ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects. The software integrates under a single interface analyses from several widely-used structure quality evaluation tools, including PROCHECK (Laskowski et al., J Appl Crystallog 1993;26:283-291), MolProbity (Lovell et al., Proteins 2003;50:437-450), Verify3D (Luthy et al., Nature 1992;356:83-85), ProsaII (Sippl, Proteins 1993;17: 355-362), the PDB validation software, and various structure-validation tools developed in our own laboratory. PSVS provides standard constraint analyses, statistics on goodness-of-fit between structures and experimental data, and knowledge-based structure quality scores in standardized format suitable for database integration. The analysis provides both global and site-specific measures of protein structure quality. Global quality measures are reported as Z scores, based on calibration with a set of high-resolution X-ray crystal structures. PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X-ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5-year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher-resolution X-ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this "structure quality score gap" between NMR and X-ray crystal structures are discussed.     

Optimized distance‐dependent atom‐pair‐based potential DOOP for protein structure prediction

The DOcking decoy‐based Optimized Potential (DOOP) energy function for protein structure prediction is based on empirical distance‐dependent atom‐pair interactions. To optimize the atom‐pair interactions, native protein structures are decomposed into polypeptide chain segments that correspond to structural motives involving complete secondary structure elements. They constitute near native ligand–receptor systems (or just pairs). Thus, a total of 8609 ligand–receptor systems were prepared from 954 selected proteins. For each of these hypothetical ligand–receptor systems, 1000 evenly sampled docking decoys with 0–10 Å interface root‐mean‐square‐deviation (iRMSD) were generated with a method used before for protein–protein docking. A neural network‐based optimization method was applied to derive the optimized energy parameters using these decoys so that the energy function mimics the funnel‐like energy landscape for the interaction between these hypothetical ligand–receptor systems. Thus, our method hierarchically models the overall funnel‐like energy landscape of native protein structures. The resulting energy function was tested on several commonly used decoy sets for native protein structure recognition and compared with other statistical potentials. In combination with a torsion potential term which describes the local conformational preference, the atom‐pair‐based potential outperforms other reported statistical energy functions in correct ranking of native protein structures for a variety of decoy sets. This is especially the case for the most challenging ROSETTA decoy set, although it does not take into account side chain orientation‐dependence explicitly. The DOOP energy function for protein structure prediction, the underlying database of protein structures with hypothetical ligand–receptor systems and their decoys are freely available at http://agknapp.chemie.fu‐berlin.de/doop/ . Proteins 2015; 83:881–890. © 2015 Wiley Periodicals, Inc.     

RCSB Protein Data Bank: Enabling biomedical research and drug discovery

Analyses of publicly available structural data reveal interesting insights into the impact of the three‐dimensional (3D) structures of protein targets important for discovery of new drugs (e.g., G‐protein‐coupled receptors, voltage‐gated ion channels, ligand‐gated ion channels, transporters, and E3 ubiquitin ligases). The Protein Data Bank (PDB) archive currently holds > 155,000 atomic‐level 3D structures of biomolecules experimentally determined using crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy. The PDB was established in 1971 as the first open‐access, digital‐data resource in biology, and is now managed by the Worldwide PDB partnership (wwPDB; wwPDB.org ). US PDB operations are the responsibility of the Research Collaboratory for Structural Bioinformatics PDB (RCSB PDB). The RCSB PDB serves millions of RCSB.org users worldwide by delivering PDB data integrated with ～40 external biodata resources, providing rich structural views of fundamental biology, biomedicine, and energy sciences. Recently published work showed that the PDB archival holdings facilitated discovery of ～90% of the 210 new drugs approved by the US Food and Drug Administration 2010–2016. We review user‐driven development of RCSB PDB services, examine growth of the PDB archive in terms of size and complexity, and present examples and opportunities for structure‐guided drug discovery for challenging targets (e.g., integral membrane proteins).     

The structural genomics experimental pipeline: insights from global target lists

Structural genomics (SG) initiatives are currently attempting to achieve the high-throughput determination of protein structures on a genome-wide scale. Here we analyze the SG target data that have been publicly released over a period of 16 months to assess the potential of the SG initiatives. We use statistical techniques most commonly applied in epidemiology to describe the dynamics of targets through the experimental SG pipeline. There is no clear bottleneck among the key stages of cloning, expression, purification and crystallization. An SG target will progress through each of these steps with a probability of approximately 45%. Around 80% of targets with diffraction data will yield a crystal structure, and 20% of targets with HSQC spectra will yield an NMR structure. We also find the overlaps among SG targets: 61% of SG protein sequences share at least 30% sequence identity with one or more other SG targets. There is no significant difference in average structure quality among SG structures and other structures in the PDB determined by "traditional" methods, but on average SG structures are deposited to the PDB twice as quickly after X-ray data collection.     

Hybrid Global Optimization Algorithms for Protein Structure Prediction: Alternating Hybrids

Hybrid global optimization methods attempt to combine the beneficial features of two or more algorithms, and can be powerful methods for solving challenging nonconvex optimization problems. In this paper, novel classes of hybrid global optimization methods, termed alternating hybrids, are introduced for application as a tool in treating the peptide and protein structure prediction problems. In particular, these new optimization methods take the form of hybrids between a deterministic global optimization algorithm, the αBB, and a stochastically based method, conformational space annealing (CSA). The αBB method, as a theoretically proven global optimization approach, exhibits consistency, as it guarantees convergence to the global minimum for twice-continuously differentiable constrained nonlinear programming problems, but can benefit from computationally related enhancements. On the other hand, the independent CSA algorithm is highly efficient, though the method lacks theoretical guarantees of convergence. Furthermore, both the αBB method and the CSA method are found to identify ensembles of low-energy conformers, an important feature for determining the true free energy minimum of the system. The proposed hybrid methods combine the desirable features of efficiency and consistency, thus enabling the accurate prediction of the structures of larger peptides. Computational studies for met-enkephalin and melittin, employing sequential and parallel computing frameworks, demonstrate the promise for these proposed hybrid methods.     

An overview of tools for the validation of protein NMR structures

Biomolecular structures at atomic resolution present a valuable resource for the understanding of biology. NMR spectroscopy accounts for 11 % of all structures in the PDB repository. In response to serious problems with the accuracy of some of the NMR-derived structures and in order to facilitate proper analysis of the experimental models, a number of program suites are available. We discuss nine of these tools in this review: PROCHECK-NMR, PSVS, GLM-RMSD, CING, Molprobity, Vivaldi, ResProx, NMR constraints analyzer and QMEAN. We evaluate these programs for their ability to assess the structural quality, restraints and their violations, chemical shifts, peaks and the handling of multi-model NMR ensembles. We document both the input required by the programs and output they generate. To discuss their relative merits we have applied the tools to two representative examples from the PDB: a small, globular monomeric protein (Staphylococcal nuclease from S. aureus, PDB entry 2kq3) and a small, symmetric homodimeric protein (a region of human myosin-X, PDB entry 2lw9).     

Computational modeling of membrane proteins

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1–2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug‐specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans‐membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α‐helical MPs as well as β‐barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge‐based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade. Proteins 2015; 83:1–24. © 2014 Wiley Periodicals, Inc.     

PDB-REPRDB: a database of representative protein chains from the Protein Data Bank (PDB) in 2003

PDB-REPRDB is a database of representative protein chains from the Protein Data Bank (PDB). Started at the Real World Computing Partnership (RWCP) in August 1997, it developed to the present system of PDB-REPRDB. In April 2001, the system was moved to the Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST) (http://www.cbrc.jp/); it is available at http://www.cbrc.jp/pdbreprdb/. The current database includes 33 368 protein chains from 16 682 PDB entries (1 September, 2002), from which are excluded (a) DNA and RNA data, (b) theoretically modeled data, (c) short chains (1<40 residues), or (d) data with non-standard amino acid residues at all residues. The number of entries including membrane protein structures in the PDB has increased rapidly with determination of numbers of membrane protein structures because of improved X-ray crystallography, NMR, and electron microscopic experimental techniques. Since many protein structure studies must address globular and membrane proteins separately, this new elimination factor, which excludes membrane protein chains, is introduced in the PDB-REPRDB system. Moreover, the PDB-REPRDB system for membrane protein chains begins at the same URL. The current membrane database includes 551 protein chains, including membrane domains in the SCOP database of release 1.59 (15 May, 2002).