Complexes In Protein Data Bank Research Articles

Identification of Intrinsic Disorder in Complexes from the Protein Data Bank.

Background: Intrinsically disordered proteins or regions (IDPs or IDRs) lack stable structures in solution, yet often fold upon binding with partners. IDPs or IDRs are highly abundant in all proteomes and represent a significant modification of sequence → structure → function paradigm. The Protein Data Bank (PDB) includes complexes containing disordered segments bound to globular proteins, but the molecular mechanisms of such binding interactions remain largely unknown. Results: In this study, we present the results of various disorder predictions on a nonredundant set of PDB complexes. In contrast to their structural appearances, many PDB proteins were predicted to be disordered when separated from their binding partners. These predicted-to-be-disordered proteins were observed to form structures depending upon various factors, including heterogroup binding, protein/DNA/RNA binding, disulfide bonds, and ion binding. Conclusions: This study collects many examples of disorder-to-order transition in IDP complex formation, thus revealing the unusual structure–function relationships of IDPs and providing an additional support for the newly proposed paradigm of the sequence → IDP/IDR ensemble → function.

Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions.

In structure-based drug design, scoring functions are widely used for fast evaluation of protein-ligand interactions. They are often applied in combination with molecular docking and de novo design methods. Since the early 1990s, a whole spectrum of protein-ligand interaction scoring functions have been developed. Regardless of their technical difference, scoring functions all need data sets combining protein-ligand complex structures and binding affinity data for parametrization and validation. However, data sets of this kind used to be rather limited in terms of size and quality. On the other hand, standard metrics for evaluating scoring function used to be ambiguous. Scoring functions are often tested in molecular docking or even virtual screening trials, which do not directly reflect the genuine quality of scoring functions. Collectively, these underlying obstacles have impeded the invention of more advanced scoring functions. In this Account, we describe our long-lasting efforts to overcome these obstacles, which involve two related projects. On the first project, we have created the PDBbind database. It is the first database that systematically annotates the protein-ligand complexes in the Protein Data Bank (PDB) with experimental binding data. This database has been updated annually since its first public release in 2004. The latest release (version 2016) provides binding data for 16 179 biomolecular complexes in PDB. Data sets provided by PDBbind have been applied to many computational and statistical studies on protein-ligand interaction and various subjects. In particular, it has become a major data resource for scoring function development. On the second project, we have established the Comparative Assessment of Scoring Functions (CASF) benchmark for scoring function evaluation. Our key idea is to decouple the "scoring" process from the "sampling" process, so scoring functions can be tested in a relatively pure context to reflect their quality. In our latest work on this track, i.e. CASF-2013, the performance of a scoring function was quantified in four aspects, including "scoring power", "ranking power", "docking power", and "screening power". All four performance tests were conducted on a test set containing 195 high-quality protein-ligand complexes selected from PDBbind. A panel of 20 standard scoring functions were tested as demonstration. Importantly, CASF is designed to be an open-access benchmark, with which scoring functions developed by different researchers can be compared on the same grounds. Indeed, it has become a popular choice for scoring function validation in recent years. Despite the considerable progress that has been made so far, the performance of today's scoring functions still does not meet people's expectations in many aspects. There is a constant demand for more advanced scoring functions. Our efforts have helped to overcome some obstacles underlying scoring function development so that the researchers in this field can move forward faster. We will continue to improve the PDBbind database and the CASF benchmark in the future to keep them as useful community resources.

PDB-wide collection of binding data: current status of the PDBbind database.

Molecular recognition between biological macromolecules and organic small molecules plays an important role in various life processes. Both structural information and binding data of biomolecular complexes are indispensable for depicting the underlying mechanism in such an event. The PDBbind database was created to collect experimentally measured binding data for the biomolecular complexes throughout the Protein Data Bank (PDB). It thus provides the linkage between structural information and energetic properties of biomolecular complexes, which is especially desirable for computational studies or statistical analyses. Since its first public release in 2004, the PDBbind database has been updated on an annual basis. The latest release (version 2013) provides experimental binding affinity data for 10,776 biomolecular complexes in PDB, including 8302 protein-ligand complexes and 2474 other types of complexes. In this article, we will describe the current methods used for compiling PDBbind and the updated status of this database. We will also review some typical applications of PDBbind published in the scientific literature. All contents of this database are freely accessible at the PDBbind-CN Web server at http://www.pdbbind-cn.org/. wangrx@mail.sioc.ac.cn. Supplementary data are available at Bioinformatics online.

Re-visiting protein-centric two-tier classification of existing DNA-protein complexes

BackgroundPrecise DNA-protein interactions play most important and vital role in maintaining the normal physiological functioning of the cell, as it controls many high fidelity cellular processes. Detailed study of the nature of these interactions has paved the way for understanding the mechanisms behind the biological processes in which they are involved. Earlier in 2000, a systematic classification of DNA-protein complexes based on the structural analysis of the proteins was proposed at two tiers, namely groups and families. With the advancement in the number and resolution of structures of DNA-protein complexes deposited in the Protein Data Bank, it is important to revisit the existing classification.ResultsOn the basis of the sequence analysis of DNA binding proteins, we have built upon the protein centric, two-tier classification of DNA-protein complexes by adding new members to existing families and making new families and groups. While classifying the new complexes, we also realised the emergence of new groups and families. The new group observed was where β-propeller was seen to interact with DNA. There were 34 SCOP folds which were observed to be present in the complexes of both old and new classifications, whereas 28 folds are present exclusively in the new complexes. Some new families noticed were NarL transcription factor, Z-α DNA binding proteins, Forkhead transcription factor, AP2 protein, Methyl CpG binding protein etc.ConclusionsOur results suggest that with the increasing number of availability of DNA-protein complexes in Protein Data Bank, the number of families in the classification increased by approximately three fold. The folds present exclusively in newly classified complexes is suggestive of inclusion of proteins with new function in new classification, the most populated of which are the folds responsible for DNA damage repair. The proposed re-visited classification can be used to perform genome-wide surveys in the genomes of interest for the presence of DNA-binding proteins. Further analysis of these complexes can aid in developing algorithms for identifying DNA-binding proteins and their family members from mere sequence information.

New angle‐dependent potential energy function for backbone–backbone hydrogen bond in protein–protein interactions

Backbone-backbone hydrogen bonds (BBHBs) are one of the most abundant interactions at the interface of protein-protein complex. Here, we propose an angle-dependent potential energy function for BBHB based on density functional theory (DFT) calculations and the operation of a genetic algorithm to find the optimal parameters in the potential energy function. The angular part of the energy function is assumed to be the product of the power series of sine and cosine functions with respect to the two angles associated with BBHB. Two radial functions are taken into account in this study: Morse and Leonard-Jones 12-10 potential functions. Of these two functions under consideration, the former is found to be more accurate than the latter in terms of predicting the binding energies obtained from DFT calculations. The new HB potential function also compares well with the knowledge-based potential derived by applying Boltzmann statistics for a variety of protein-protein complexes in protein data bank.

A tool for calculating binding-site residues on proteins from PDB structures

BackgroundIn the research on protein functional sites, researchers often need to identify binding-site residues on a protein. A commonly used strategy is to find a complex structure from the Protein Data Bank (PDB) that consists of the protein of interest and its interacting partner(s) and calculate binding-site residues based on the complex structure. However, since a protein may participate in multiple interactions, the binding-site residues calculated based on one complex structure usually do not reveal all binding sites on a protein. Thus, this requires researchers to find all PDB complexes that contain the protein of interest and combine the binding-site information gleaned from them. This process is very time-consuming. Especially, combing binding-site information obtained from different PDB structures requires tedious work to align protein sequences. The process becomes overwhelmingly difficult when researchers have a large set of proteins to analyze, which is usually the case in practice.ResultsIn this study, we have developed a tool for calculating binding-site residues on proteins, TCBRP . For an input protein, TCBRP can quickly find all binding-site residues on the protein by automatically combining the information obtained from all PDB structures that consist of the protein of interest. Additionally, TCBRP presents the binding-site residues in different categories according to the interaction type. TCBRP also allows researchers to set the definition of binding-site residues.ConclusionThe developed tool is very useful for the research on protein binding site analysis and prediction.

Predicting the distance between antibody’s interface residue and antigen to recognize antigen types by support vector machine

In this paper, a machine learning approach, known as support vector machine (SVM) is employed to predict the distance between antibody’s interface residue and antigen in antigen–antibody complex. The heavy chains, light chains and the corresponding antigens of 37 antibodies are extracted from the antibody–antigen complexes in protein data bank. According to different distance ranges, sequence patch sizes and antigen classes, a number of computational experiments are conducted to describe the distance between antibody’s interface residue and antigen with antibody sequence information. The high prediction accuracy of both self-consistent and cross-validation tests indicates that the sequential discovered information from antibody structure characterizes much in predicting the distance between antibody’s interface residue and antigen. Furthermore, the antigen class is predicted from residue composition information that belongs to different distance range by SVM, which shows some potential significance.

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BioTechniquesVol. 40, No. 2 WebWatchOpen AccessWebWatchKevin AhernKevin AhernSearch for more papers by this authorPublished Online:21 May 2018https://doi.org/10.2144/06402WW01AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail The Vision ThingYou may not realize it, but macular degeneration is the leading cause of blindness in people over the age of 55. That's a scary thought for a rapidly aging group of baby boomers. The Foundation Fighting Blindness is a charitable organization aimed at preventing, treating, and curing a broad spectrum of retinal diseases, including macular degeneration, retinitis pigmentosa (degeneration of photoreceptor cells), Stargardt disease (juvenile macular degeneration), and Usher syndrome (hearing impairment at birth followed by retinitis pigmentosa). The site abounds with educational content about each of these diseases, as well as clinical trial summaries, and descriptions of experimental therapies. A site with a mission to inform and serve.www.blindness.orgOrientation ExpressLook in the Protein Data Bank (PDB) and you'll find thousands of structures of proteins embedded in or associated with the cell's phospholipid bilayer. Search for information about how these proteins are oriented in the membrane, and you'll draw a blank. That didn't sit well with Andrei Lomize and coworkers, so they developed a computational approach to optimize the spatial arrangement of proteins in membranes and then applied it to all known transmembrane complexes in PDB. Abracadabra! Thus was the Orientations of Proteins in Membranes (OPM) database born. At the OPM site, you'll discover 162 proteins from over 60 species grouped according to type, class, family, superfamily, and localization site. Click on a desired protein, and you can view it in ribbon form or in 3-D relative to the membrane it resides in.opm.phar.umich.eduSearching SmartsTalk to Tom Sharpton, cofounder of the interesting Siphs site, and you'll discover a young scientist bursting with enthusiasm. It's no surprise that these qualities carry over entirely into the design of his web site. With a dogged determination to put scientists together to share important information, Siphs’ philosophy is rooted in sharing the expertise of its users. Towards this end, newcomers identify their areas of expertise on registration, and questions are posted to these areas. Siphs’ users answer each other's questions using a bulletin board style of format along with the assistance of a search engine. Bringing together a community of scholars in this way is a brilliant idea—who better knows the ins and outs of a problem than one working on it?www.siphs.com/ate/index.jspAnimal SentinelsFor detecting lethal, odorless gases like carbon monoxide in mines, a canary was a miner's best friend because if it died or got sick, it was time to make serious plans for exit. Besides canaries, other organisms also provide important information relating to human health. The Canary Database, currently in beta testing at Yale, is a great place to learn more about, for example, birds as an early warning system for an avian flu epidemic. From information on an animal's exposure to reagents to linkages between human and animal health outcomes, the Canary Database is chock full of data from over 1600 curated, peer-reviewed articles that will be welcomed by environmental health specialists.canarydatabase.orgGenome Du JourCan it possibly be 10 years since the complete sequence of the first organismal genome, that of Haemophilus influenzae, was determined? Since that momentous event, over 330 genomes have been completed and published, representing a new genome about every 11 days. One of the more interesting genomic projects currently underway (of approximately 1700 in progress) is the Salamander Genome Project, hosted at the University of Kentucky. Salamanders are model vertebrate organisms for vision, renal function, embryogenesis and, perhaps most interestingly, tissue/limb regeneration. At the site, visitors can follow the progress of this project, check out the expressed sequence tag (EST) database, access linkage map information, and much more. If one day we learn to regenerate human organs, it may come as a result of information from the salamander.salamander.uky.eduFiguresReferencesRelatedDetails Vol. 40, No. 2 Follow us on social media for the latest updates Metrics Downloaded 137 times History Published online 21 May 2018 Published in print February 2006 Information© 2006 Author(s)PDF download