Protein Functional Sites Research Articles

Insights on Diversity of Leucine-Rich Repeat (LRR) Domain among Major Blast Resistance Genes of Rice

Rice blast is a continuous threat in rice ecosystems across the globe; its dynamics is becoming complex in the changing climatic conditions. Host resistance is still a viable option; hence, the exploration of resistance genes and their novel alleles is indispensable. The majority of the blast resistance genes belong to nucleotide-binding site and leucine-rich repeat (LRR) domain. In the present study, diverse LRR alleles of five major blast resistance genes (Pi2, Pi9, Pib, Pita, and Pi37) were cloned from 13 different Oryza species to determine the nucleotide diversity as well as to identify the single nucleotide polymorphisms, InDels, conserved domains, and protein functional sites. Although Pi9 and Pi2 are homologous genes, significant nucleotide variations and variants in the motifs distribution were observed. Among the five genes, Pi37 showed the highest nucleotide diversity and Pita showed the least diversity. The phylogenetic groups of alleles were correlated with the identified haplotypes. The motif (xxLxLxx) was present among all the alleles of blast R gene sequences across various Oryza species, indicating its importance. The appearance of post-translational modification sites in the protein sequences of these alleles also indicates its nature of involvement in host–pathogen interactions. The present study offers clues in further understanding the molecular evolution of the LRR domain of resistance genes, which is a key determinant of host–pathogen interactions.

Incorporation of protein binding effects into likelihood ratio test for exome sequencing data.

Statistical association studies are an important tool in detecting novel disease genes. However, for sequencing data, association studies confront the challenge of low power because of relatively small data sample size and rare variants. Incorporating biological information that reflects disease mechanism is likely to strengthen the association evidence of disease genes, and thus increase the power of association studies. In this paper, we annotate non-synonymous single-nucleotide variants according to protein binding sites (BSs) by using a more accurate BS prediction method. We then incorporate this information into association study through a statistical framework of likelihood ratio test (LRT) based on weighted burden score of single-nucleotide variants (SNVs). The strategy is applied to Genetic Analysis Workshop 19 exome-sequencing data for detecting novel genes associated to hypotension. The SNV-weighting LRT idea is empirically verified by the simulated phenotypes (336 cases and 1607 controls), and the weights based on BS annotation are applied to the real phenotypes (394 cases and 1457 controls). Such strategy of weighting the prior information on protein functional sites is shown to be superior to the unweighted LRT and serves as a good complement to the existing association tests. Several putative genes are reported; some of them are functionally related to hypertension according to the previous evidence in the literature.

Improving the performance of the PLB index for ligand-binding site prediction using dihedral angles and the solvent-accessible surface area.

Protein ligand-binding site prediction is highly important for protein function determination and structure-based drug design. Over the past twenty years, dozens of computational methods have been developed to address this problem. Soga et al. identified ligand cavities based on the preferences of amino acids for the ligand-binding site (RA) and proposed the propensity for ligand binding (PLB) index to rank the cavities on the protein surface. However, we found that residues exhibit different RAs in response to changes in solvent exposure. Furthermore, previous studies have suggested that some dihedral angles of amino acids in specific regions of the Ramachandran plot are preferred at the functional sites of proteins. Based on these discoveries, the amino acid solvent-accessible surface area and dihedral angles were combined with the RA and PLB to obtain two new indexes, multi-factor RA (MF-RA) and multi-factor PLB (MF-PLB). MF-PLB, PLB and other methods were tested using two benchmark databases and two particular ligand-binding sites. The results show that MF-PLB can improve the success rate of PLB for both ligand-bound and ligand-unbound structures, particularly for top choice prediction.

Synthetic Peptides as Protein Mimics.

The design and generation of molecules capable of mimicking the binding and/or functional sites of proteins represents a promising strategy for the exploration and modulation of protein function through controlled interference with the underlying molecular interactions. Synthetic peptides have proven an excellent type of molecule for the mimicry of protein sites because such peptides can be generated as exact copies of protein fragments, as well as in diverse chemical modifications, which includes the incorporation of a large range of non-proteinogenic amino acids as well as the modification of the peptide backbone. Apart from extending the chemical and structural diversity presented by peptides, such modifications also increase the proteolytic stability of the molecules, enhancing their utility for biological applications. This article reviews recent advances by this and other laboratories in the use of synthetic protein mimics to modulate protein function, as well as to provide building blocks for synthetic biology.

Analysis of regulatory mechanism after ErbB4 gene mutation based on local modeling methodology.

ErbB4 is an oncogene belonging to the epidermal growth factor receptor family and contributes to the occurrence and development of multiple cancers, such as gastric, breast, and colorectal cancers. Therefore, studies of the regulation of ErbB4 in cancerigenic pathway will advance molecular targeted therapy. Advanced bioinformatic analysis softwares, such as ExPASy, Predictprotei, QUARK, and I-TASSER, were used to analyze the regulatory mechanism after ErbB4 gene mutation in terms of amino acid sequence, primary, secondary, and tertiary structure of the protein and upstream-downstream receptor/ligands. Mutation of the 19th and 113th amino acids at the carboxyl terminus of ErbB4 protein did not affect its biological nature, but its secondary structure changed and protein binding sites were near 2 mutational sites; moreover, after mutation introduction, additional binding sites were observed. Tertiary structure modeling indicated that local structure of ErbB4 was changed from an α helical conformation into a β chain folding structure; the α helical conformation is the functional site of protein, while active sites are typically near junctions between helical regions, thus the helical structures are easily destroyed and change into folding structures or other structures after stretching. Mutable sites of ErbB4 is exact binding sites where dimer formed with other epidermal growth factor family proteins; mutation enabled the ErbB4 receptor to bind to neuregulin 1 ligand without dimer formation, disrupting the signal transduction pathway and affecting ErbB4 function.

Structural characterization of single nucleotide variants at ligand binding sites and enzyme active sites of human proteins.

Functional sites on proteins play an important role in various molecular interactions and reactions between proteins and other molecules. Thus, mutations in functional sites can severely affect the overall phenotype. Progress of genome sequencing projects has yielded a wealth of information on single nucleotide variants (SNVs), especially those with less than 1% minor allele frequency (rare variants). To understand the functional influence of genetic variants at a protein level, we investigated the relationship between SNVs and protein functional sites in terms of minor allele frequency and the structural position of variants. As a result, we observed that SNVs were less abundant at ligand binding sites, which is consistent with a previous study on SNVs and protein interaction sites. Additionally, we found that non-rare variants tended to be located slightly apart from enzyme active sites. Examination of non-rare variants revealed that most of the mutations resulted in moderate changes of the physico-chemical properties of amino acids, suggesting the existence of functional constraints. In conclusion, this study shows that the mapping of genetic variants on protein structures could be a powerful approach to evaluate the functional impact of rare genetic variations.

Study of Functional and Allosteric Sites in Protein Superfamilies

The interaction of proteins (enzymes) with a variety of low-molecular-weight compounds, as well as protein-protein interactions, is the most important factor in the regulation of their functional properties. To date, research effort has routinely focused on studying ligand binding to the functional sites of proteins (active sites of enzymes), whereas the molecular mechanisms of allosteric regulation, as well as binding to other pockets and cavities in protein structures, remained poorly understood. Recent studies have shown that allostery may be an intrinsic property of virtually all proteins. Novel approaches are needed to systematically analyze the architecture and role of various binding sites and establish the relationship between structure, function, and regulation. Computational biology, bioinformatics, and molecular modeling can be used to search for new regulatory centers, characterize their structural peculiarities, as well as compare different pockets in homologous proteins, study the molecular mechanisms of allostery, and understand the communication between topologically independent binding sites in protein structures. The establishment of an evolutionary relationship between different binding centers within protein superfamilies and the discovery of new functional and allosteric (regulatory) sites using computational approaches can improve our understanding of the structure-function relationship in proteins and provide new opportunities for drug design and enzyme engineering.

Computer analysis of protein functional sites projection on exon structure of genes in Metazoa

BackgroundStudy of the relationship between the structural and functional organization of proteins and their coding genes is necessary for an understanding of the evolution of molecular systems and can provide new knowledge for many applications for designing proteins with improved medical and biological properties. It is well known that the functional properties of proteins are determined by their functional sites. Functional sites are usually represented by a small number of amino acid residues that are distantly located from each other in the amino acid sequence. They are highly conserved within their functional group and vary significantly in structure between such groups. According to this facts analysis of the general properties of the structural organization of the functional sites at the protein level and, at the level of exon-intron structure of the coding gene is still an actual problem.ResultsOne approach to this analysis is the projection of amino acid residue positions of the functional sites along with the exon boundaries to the gene structure. In this paper, we examined the discontinuity of the functional sites in the exon-intron structure of genes and the distribution of lengths and phases of the functional site encoding exons in vertebrate genes. We have shown that the DNA fragments coding the functional sites were in the same exons, or in close exons. The observed tendency to cluster the exons that code functional sites which could be considered as the unit of protein evolution. We studied the characteristics of the structure of the exon boundaries that code, and do not code, functional sites in 11 Metazoa species. This is accompanied by a reduced frequency of intercodon gaps (phase 0) in exons encoding the amino acid residue functional site, which may be evidence of the existence of evolutionary limitations to the exon shuffling.ConclusionsThese results characterize the features of the coding exon-intron structure that affect the functionality of the encoded protein and allow a better understanding of the emergence of biological diversity.

Protein Functional Site Prediction Using a Conservative Grade and a Proximate Grade

So far, in order to predict important sites of a protein, many computational methods have been developed. In the era of big-data, it is required for improvements and sophistication of existing methods by integrating sequence data in the structural data. In this paper, we aim at two things: improving sequence-based methods and developing a new method using both sequence and structural data. Therefore, we developed an originally modified evolutionary trace method, in which we defined conservative grades calculated from a given multiple sequence alignment and a proximate grade in order to evaluate predicted active sites from a viewpoint of protein-ion, protein-ligand, protein-nucleic acid, proteinprotein interaction by use of three-dimensional structures. In other words, the proximate grade also can evaluate an amino acid residue. When we applied our method to translation elongation factor Tu/1A proteins, it showed that the conservative grades are evaluated accurately by the proximate grade. Consequently, our idea indicated two advantages. One is that we can take into account various cocrystal structures for evaluation. Another one is that, by calculating the fitness between the given conservative grade and the proximate grade, we can select the best conservative grade.

Synthetic peptides mimicking the binding site of human acetylcholinesterase for its inhibitor fasciculin 2.

Molecules capable of mimicking protein binding and/or functional sites present useful tools for a range of biomedical applications, including the inhibition of protein-ligand interactions. Such mimics of protein binding sites can currently be generated through structure-based design and chemical synthesis. Computational protein design could be further used to optimize protein binding site mimetics through rationally designed mutations that improve intermolecular interactions or peptide stability. Here, as a model for the study, we chose an interaction between human acetylcholinesterase (hAChE) and its inhibitor fasciculin-2 (Fas) because the structure and function of this complex is well understood. Structure-based design of mimics of the hAChE binding site for Fas yielded a peptide that binds to Fas at micromolar concentrations. Replacement of hAChE residues known to be essential for its interaction with Fas with alanine, in this peptide, resulted in almost complete loss of binding to Fas. Computational optimization of the hAChE mimetic peptide yielded a variant with slightly improved affinity to Fas, indicating that more rounds of computational optimization will be required to obtain peptide variants with greatly improved affinity for Fas. CD spectra in the absence and presence of Fas point to conformational changes in the peptide upon binding to Fas. Furthermore, binding of the optimized hAChE mimetic peptide to Fas could be inhibited by hAChE, providing evidence for a hAChE-specific peptide-Fas interaction.

MoonProt: A Database for Proteins That Are Known to Moonlight

Moonlighting proteins comprise a class of multifunctional proteins in which a single polypeptide chain performs multiple physiologically relevant biochemical or biophysical functions. Over 200 proteins have been found to moonlight, and it is possible that many other proteins also have additional functions that have not yet been found. The known moonlighting proteins include receptors, enzymes, transcription factors, adhesins and other types of proteins, and different combinations of functions are observed. Information about their structures and functions is scattered in many publications. We have constructed the manually curated, searchable, internet-based MoonProt Database (www.moonlightingproteins.org) with information about the proteins that have been experimentally verified to be moonlighting proteins. The availability of this organized information provides a more complete picture of what is currently known about moonlighting proteins. The database will also aid researchers in other fields, including determining the functions of genes identified in genome sequencing projects, interpreting data from proteomics projects, and annotating protein sequence and structural databases. In addition, information about the structures and functions of moonlighting proteins can be helpful in understanding how novel protein functional sites evolved on an ancient protein scaffold, which can also help in the design of proteins with novel functions.

Moonprot: A Database for Proteins that are Known to Moonlight

Moonlighting proteins comprise a class of multifunctional proteins in which a single polypeptide chain performs multiple biochemical functions that are not due to gene fusions, multiple RNA splice variants, or pleiotropic effects. The known moonlighting proteins perform a variety of diverse functions in many different cell types and species, and information about their structures and functions is scattered in many publications. We have constructed the manually curated, searchable, internet-based MoonProt Database (http://www.moonlightingproteins.org) with information about the over 200 proteins that have been experimentally verified to be moonlighting proteins. The availability of this organized information provides a more complete picture of what is currently known about moonlighting proteins. The database will also aid researchers in other fields, including determining the functions of genes identified in genome sequencing projects, interpreting data from proteomics projects, and annotating protein sequence and structural databases. In addition, information about the structures and functions of moonlighting proteins can be helpful in understanding how novel protein functional sites evolved on an ancient protein scaffold, which can also help in the design of proteins with novel functions.

Condensing position-specific scoring matrixs by the Kidera factors for ligand-binding site prediction.

Position-specific scoring matrix (PSSM) has been widely used for identifying protein functional sites. However, it is 20-dimentional and contains many redundant features. The Kidera factors were reported to contain information relating almost all physical properties of amino acids, but it requires appropriate weighting coefficients to express their properties. We developed a novel method, named as KSPSSMpred, which integrated PSSM and the Kidera Factors into a 10-dimensional matrix (KSPSSM) for ligand-binding site prediction. Flavin adenine dinucleotide (FAD) was chosen as a representative ligand for this study. When compared with five other feature-based methods on a benchmark dataset, KSPSSMpred performed the best. This study demonstrates that, KSPSSM is an effective feature extraction method which can enrich PSSM with information relating 188 physical properties of residues, and reduce 50% feature dimensions without losing information included in the PSSM.

An analysis approach to identify specific functional sites in orthologous proteins using sequence and structural information: application to neuroserpin reveals regions that differentially regulate inhibitory activity.

The analysis of sequence conservation is commonly used to predict functionally important sites in proteins. We have developed an approach that first identifies highly conserved sites in a set of orthologous sequences using a weighted substitution-matrix-based conservation score and then filters these conserved sites based on the pattern of conservation present in a wider alignment of sequences from the same family and structural information to identify surface-exposed sites. This allows us to detect specific functional sites in the target protein and exclude regions that are likely to be generally important for the structure or function of the wider protein family. We applied our method to two members of the serpin family of serine protease inhibitors. We first confirmed that our method successfully detected the known heparin binding site in antithrombin while excluding residues known to be generally important in the serpin family. We next applied our sequence analysis approach to neuroserpin and used our results to guide site-directed polyalanine mutagenesis experiments. The majority of the mutant neuroserpin proteins were found to fold correctly and could still form inhibitory complexes with tissue plasminogen activator (tPA). Kinetic analysis of tPA inhibition, however, revealed altered inhibitory kinetics in several of the mutant proteins, with some mutants showing decreased association with tPA and others showing more rapid dissociation of the covalent complex. Altogether, these results confirm that our sequence analysis approach is a useful tool that can be used to guide mutagenesis experiments for the detection of specific functional sites in proteins.

MoonProt: a database for proteins that are known to moonlight

Moonlighting proteins comprise a class of multifunctional proteins in which a single polypeptide chain performs multiple biochemical functions that are not due to gene fusions, multiple RNA splice variants or pleiotropic effects. The known moonlighting proteins perform a variety of diverse functions in many different cell types and species, and information about their structures and functions is scattered in many publications. We have constructed the manually curated, searchable, internet-based MoonProt Database (http://www.moonlightingproteins.org) with information about the over 200 proteins that have been experimentally verified to be moonlighting proteins. The availability of this organized information provides a more complete picture of what is currently known about moonlighting proteins. The database will also aid researchers in other fields, including determining the functions of genes identified in genome sequencing projects, interpreting data from proteomics projects and annotating protein sequence and structural databases. In addition, information about the structures and functions of moonlighting proteins can be helpful in understanding how novel protein functional sites evolved on an ancient protein scaffold, which can also help in the design of proteins with novel functions.

Analysis of evolutionary conservation patterns and their influence on identifying protein functional sites.

Evolutionary conservation information included in position-specific scoring matrix (PSSM) has been widely adopted by sequence-based methods for identifying protein functional sites, because all functional sites, whether in ordered or disordered proteins, are found to be conserved at some extent. However, different functional sites have different conservation patterns, some of them are linear contextual, some of them are mingled with highly variable residues, and some others seem to be conserved independently. Every value in PSSMs is calculated independently of each other, without carrying the contextual information of residues in the sequence. Therefore, adopting the direct output of PSSM for prediction fails to consider the relationship between conservation patterns of residues and the distribution of conservation scores in PSSMs. In order to demonstrate the importance of combining PSSMs with the specific conservation patterns of functional sites for prediction, three different PSSM-based methods for identifying three kinds of functional sites have been analyzed. Results suggest that, different PSSM-based methods differ in their capability to identify different patterns of functional sites, and better combining PSSMs with the specific conservation patterns of residues would largely facilitate the prediction.

New insights into the role of water in biological function: studying solvated biomolecules using terahertz absorption spectroscopy in conjunction with molecular dynamics simulations.

In life science, water is the ubiquitous solvent, sometimes even called the "matrix of life". There is increasing experimental and theoretical evidence that solvation water is not a passive spectator in biomolecular processes. New experimental techniques can quantify how water interacts with biomolecules and, in doing so, differs from "bulk" water. Terahertz (THz) absorption spectroscopy has turned out to be a powerful tool to study (bio)molecular hydration. The main concepts that have been developed in the recent years to describe the underlying solute-induced sub-picosecond dynamics of the hydration shell are discussed herein. Moreover, we highlight recent findings that show the significance of hydrogen bond dynamics for the function of antifreeze proteins and for molecular recognition. In all of these examples, a gradient of water motion toward functional sites of proteins is observed, the so-called "hydration funnel". By means of molecular dynamics simulations, we provide new evidence for a specific water-protein coupling as the cause of the observed dynamical heterogeneity. The efficiency of the coupling at THz frequencies is explained in terms of a two-tier (short- and long-range) solute-solvent interaction.

The HIVToolbox 2 web system integrates sequence, structure, function and mutation analysis.

There is enormous interest in studying HIV pathogenesis for improving the treatment of patients with HIV infection. HIV infection has become one of the best-studied systems for understanding how a virus can hijack a cell. To help facilitate discovery, we previously built HIVToolbox, a web system for visual data mining. The original HIVToolbox integrated information for HIV protein sequence, structure, functional sites, and sequence conservation. This web system has been used for almost 40,000 searches. We report improvements to HIVToolbox including new functions and workflows, data updates, and updates for ease of use. HIVToolbox2, is an improvement over HIVToolbox with new functions. HIVToolbox2 has new functionalities focused on HIV pathogenesis including drug-binding sites, drug-resistance mutations, and immune epitopes. The integrated, interactive view enables visual mining to generate hypotheses that are not readily revealed by other approaches. Most HIV proteins form multimers, and there are posttranslational modification and protein-protein interaction sites at many of these multimerization interfaces. Analysis of protease drug binding sites reveals an anatomy of drug resistance with different types of drug-resistance mutations regionally localized on the surface of protease. Some of these drug-resistance mutations have a high prevalence in specific HIV-1 M subtypes. Finally, consolidation of Tat functional sites reveals a hotspot region where there appear to be 30 interactions or posttranslational modifications. A cursory analysis with HIVToolbox2 has helped to identify several global patterns for HIV proteins. An initial analysis with this tool identifies homomultimerization of almost all HIV proteins, functional sites that overlap with multimerization sites, a global drug resistance anatomy for HIV protease, and specific distributions of some DRMs in specific HIV M subtypes. HIVToolbox2 is an open-access web application available at [http://hivtoolbox2.bio-toolkit.com].

Attractor Structures of Signaling Networks: Consequences of Different Conformational Barcode Dynamics and Their Relations to Network-Based Drug Design.

Conformational barcodes tag functional sites of proteins and are decoded by interacting molecules transmitting the incoming signal. Conformational barcodes are modified by all co-occurring allosteric events induced by post-translational modifications, pathogen, drug binding, etc. We argue that fuzziness (plasticity) of conformational barcodes may be increased by disordered protein structures, by integrative plasticity of multi-phosphorylation events, by increased intracellular water content (decreased molecular crowding) and by increased action of molecular chaperones. This leads to increased plasticity of signaling and cellular networks. Increased plasticity is both substantiated by and inducing an increased noise level. Using the versatile network dynamics tool, Turbine (www.turbine.linkgroup.hu), here we show that the 10 % noise level expected in cellular systems shifts a cancer-related signaling network of human cells from its proliferative attractors to its largest, apoptotic attractor representing their health-preserving response in the carcinogen containing and tumor suppressor deficient environment modeled in our study. Thus, fuzzy conformational barcodes may not only make the cellular system more plastic, and therefore more adaptable, but may also stabilize the complex system allowing better access to its largest attractor.

Simplified sequence-based method for ATP-binding prediction using contextual local evolutionary conservation

BackgroundIdentifying ligand-binding sites is a key step to annotate the protein functions and to find applications in drug design. Now, many sequence-based methods adopted various predicted results from other classifiers, such as predicted secondary structure, predicted solvent accessibility and predicted disorder probabilities, to combine with position-specific scoring matrix (PSSM) as input for binding sites prediction. These predicted features not only easily result in high-dimensional feature space, but also greatly increased the complexity of algorithms. Moreover, the performances of these predictors are also largely influenced by the other classifiers.ResultsIn order to verify that conservation is the most powerful attribute in identifying ligand-binding sites, and to show the importance of revising PSSM to match the detailed conservation pattern of functional site in prediction, we have analyzed the Adenosine-5'-triphosphate (ATP) ligand as an example, and proposed a simple method for ATP-binding sites prediction, named as CLCLpred (Contextual Local evolutionary Conservation-based method for Ligand-binding prediction). Our method employed no predicted results from other classifiers as input; all used features were extracted from PSSM only. We tested our method on 2 separate data sets. Experimental results showed that, comparing with other 9 existing methods on the same data sets, our method achieved the best performance.ConclusionsThis study demonstrates that: 1) exploiting the signal from the detailed conservation pattern of residues will largely facilitate the prediction of protein functional sites; and 2) the local evolutionary conservation enables accurate prediction of ATP-binding sites directly from protein sequence.