蛋白质－DNA相互作用与真核基因转录

结合最近几年对真核转录调节因子和DNA的结构与机能研究,概述了蛋白质-蛋白质及蛋白质-DNA相互作用方式以及介导相互作用的分子结构基础,论述了转录因于之间、转录因子与DNA之间相互作用过程中的协同与拮抗作用、发生机制及其在真核基因转录调节中的普遍性和重要意义.     

蛋白质－DNA相互作用与真核基因转录

结合最近几年对真核转录调节因子和ＤＮＡ的结构与机能研究,概述了蛋白质－蛋白质及蛋白质－ＤＮＡ相互作用方式以及介导相互作用的分子结构基础,论述了转录因子之间,转录因子与ＤＮＡ之间相互作用过程中的同与拮抗作用,发生机制及其在真核基因转录调节中的遍性和重要意义。     

Efficient prediction of nucleic acid binding function from low-resolution protein structures

Structural genomics projects as well as ab initio protein structure prediction methods provide structures of proteins with no sequence or fold similarity to proteins with known functions. These are often low-resolution structures that may only include the positions of C alpha atoms. We present a fast and efficient method to predict DNA-binding proteins from just the amino acid sequences and low-resolution, C alpha-only protein models. The method uses the relative proportions of certain amino acids in the protein sequence, the asymmetry of the spatial distribution of certain other amino acids as well as the dipole moment of the molecule. These quantities are used in a linear formula, with coefficients derived from logistic regression performed on a training set, and DNA-binding is predicted based on whether the result is above a certain threshold. We show that the method is insensitive to errors in the atomic coordinates and provides correct predictions even on inaccurate protein models. We demonstrate that the method is capable of predicting proteins with novel binding site motifs and structures solved in an unbound state. The accuracy of our method is close to another, published method that uses all-atom structures, time-consuming calculations and information on conserved residues.     

Two’s company,three’s a crowd: Exploring how host–parasite–microbiota interactions may influence disease susceptibility and conservation of wildlife

A large body of research has demonstrated that host‐associated microbiota—the archaeal, bacterial, fungal and viral communities residing on and inside organisms—are critical to host health (Cho & Blaser, 2012). Although the vast majority of these studies focus on humans or model organisms in laboratory settings (Pascoe, Hauffe, Marchesi, & Perkins, 2017), they nevertheless provide important conceptual evidence that the disruption of host‐associated microbial communities (termed “dysbiosis”) among wild animals may reduce host fitness and survival under natural environmental conditions. Among the myriad of environmental factors capable of inducing dysbiosis among wild animals (Trevelline, Fontaine, Hartup, & Kohl, 2019), parasitic infections represent a potentially potent, yet poorly understood, factor influencing microbial community dynamics and animal health. The study by DeCandia et al. in this issue of Molecular Ecology is a rare example of a host–parasite–microbiota interaction that impacts the health, survival and conservation of a threatened wild animal in its natural habitat. Using culture‐independent techniques, DeCandia et al. found that the presence of an ectoparasitic mite (Otodectes cynotis) in the ear canal of the Santa Catalina Island fox (Urocyon littoralis catalinae) was associated with significantly reduced ear canal microbial diversity, with the opportunistic pathogen Staphylococcus pseudintermedius dominating the community. These findings suggest that parasite‐induced inflammation may contribute to the formation of ceruminous gland tumours in this subspecies of Channel Island fox. As a rare example of a host–parasite–microbiota interaction that may mediate a lethal disease in a population of threatened animals, their study provides an excellent example of how aspects of disease ecology can be integrated into studies of host‐associated microbiota to advance conservation science and practice.     

MotifAnalyzer‐PDZ: A computational program to investigate the evolution of PDZ‐binding target specificity

Recognition of short linear motifs (SLiMs) or peptides by proteins is an important component of many cellular processes. However, due to limited and degenerate binding motifs, prediction of cellular targets is challenging. In addition, many of these interactions are transient and of relatively low affinity. Here, we focus on one of the largest families of SLiM‐binding domains in the human proteome, the PDZ domain. These domains bind the extreme C‐terminus of target proteins, and are involved in many signaling and trafficking pathways. To predict endogenous targets of PDZ domains, we developed MotifAnalyzer‐PDZ, a program that filters and compares all motif‐satisfying sequences in any publicly available proteome. This approach enables us to determine possible PDZ binding targets in humans and other organisms. Using this program, we predicted and biochemically tested novel human PDZ targets by looking for strong sequence conservation in evolution. We also identified three C‐terminal sequences in choanoflagellates that bind a choanoflagellate PDZ domain, the Monsiga brevicollis SHANK1 PDZ domain (mbSHANK1), with endogenously‐relevant affinities, despite a lack of conservation with the targets of a homologous human PDZ domain, SHANK1. All three are predicted to be signaling proteins, with strong sequence homology to cytosolic and receptor tyrosine kinases. Finally, we analyzed and compared the positional amino acid enrichments in PDZ motif‐satisfying sequences from over a dozen organisms. Overall, MotifAnalyzer‐PDZ is a versatile program to investigate potential PDZ interactions. This proof‐of‐concept work is poised to enable similar types of analyses for other SLiM‐binding domains (e.g., MotifAnalyzer‐Kinase). MotifAnalyzer‐PDZ is available at http://motifAnalyzerPDZ.cs.wwu.edu .     

Energetics of galactose- and glucose-aromatic amino acid interactions: implications for binding in galactose-specific proteins

An aromatic amino acid is present in the binding site of a number of sugar binding proteins. The interaction of the saccharide with the aromatic residue is determined by their relative position as well as orientation. The position-orientation of the saccharide relative to the aromatic residue was found to vary in different sugar-binding proteins. In the present study, interaction energies of the complexes of galactose (Gal) and of glucose (Glc) with aromatic residue analogs have been calculated by ab initio density functional (U-B3LYP/ 6-31G**) theory. The position-orientations of the saccharide with respect to the aromatic residue observed in various Gal-, Glc-, and mannose-protein complexes were chosen for the interaction energy calculations. The results of these calculations show that galactose can interact with the aromatic residue with similar interaction energies in a number of position-orientations. The interaction energy of Gal-aromatic residue analog complex in position-orientations observed for the bound saccharide in Glc/Man-protein complexes is comparable to the Glc-aromatic residue analog complex in the same position-orientation. In contrast, there is a large variation in interaction energies of complexes of Glc- and of Gal- with the aromatic residue analog in position-orientations observed in Gal-protein complexes. Furthermore, the conformation wherein the O6 atom is away from the aromatic residue is preferred for the exocyclic -CH2OH group in Gal-aromatic residue analog complexes. The implications of these results for saccharide binding in Gal-specific proteins and the possible role of the aromatic amino acid to ensure proper positioning and orientation of galactose in the binding site have been discussed.     

Interference interactions, co-existence and conservation of mammalian carnivores

Abstract.  The shift in emphasis from single species to ecosystem conservation is revealing how community interactions can potentially influence single species viability and conservation. Although there is much theory and empirical data concerning the dynamic consequences of exploitative interactions, there is still a very poor understanding of the effects of interference interactions. Recent studies, as shown in this review, have documented widespread effects of such interactions among mammalian carnivores. Harassment, loss of kills and intraguild predation have been documented in a wide range of species. The demonstrated effects also include avoidance of larger carnivores in both time and space and reductions in one species density or even total exclusion from certain habitats or regions. Our review of the literature thus provides a range of empirical examples that together demonstrate that these interactions have very important implications on carnivore demography. We believe that the effects of interference might differ strongly from the effects of exploitative competition. This is because interference might have the potential to affect population growth in an inverse density-dependent manner and thereby also reduce population growth at low densities, therefore increasing extinction probabilities. These factors need to be considered when planning future multi-species conservation. Further research into the temporal and spatial aspects of co-existence are required if diverse guilds and communities are to be conserved.     

Structural determinants of binding and specificity in transforming growth factor-receptor interactions.

Transforming growth factor (TGF-beta) protein families are cytokines that occur as a large number of homologous proteins. Three major subgroups of these proteins with marked specificities for their receptors have been found-TGF-beta, activin/inhibin, and bone morphogenic protein. Although structural information is available for some members of the TGF-beta family of ligands and receptors, very little is known about the way these growth factors interact with the extracellular domains of their cell surface receptors, especially the type II receptor. In addition, the elements that are the determinants of binding and specificity of the ligands are poorly understood. The structure of the extracellular domain of the receptor is a three-finger fold similar to some toxin structures. Amino acid exchanges between multiply aligned homologous sequences of type II receptors point to a residue at the surface, specifically finger 1, as the determinant of ligand specificity and complex formation. The "knuckle" epitope of ligands was predicted to be the surface that interacts with the type II receptor. The residues on strands beta2, beta3, beta7, beta8 and the loop region joining beta2 and beta3 and joining beta7 and beta8 of the ligands were identified as determinants of binding and specificity. These results are supported by studies on the docking of the type II receptor to the ligand dimer-type I receptor complex.     

qNABpredict: Quick,accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids

Protein sequence-based predictors of nucleic acid (NA)-binding include methods that predict NA-binding proteins and NA-binding residues. The residue-level tools produce more details but suffer high computational cost since they must predict every amino acid in the input sequence and rely on multiple sequence alignments. We propose an alternative approach that predicts content (fraction) of the NA-binding residues, offering more information than the protein-level prediction and much shorter runtime than the residue-level tools. Our first-of-its-kind content predictor, qNABpredict, relies on a small, rationally designed and fast-to-compute feature set that represents relevant characteristics extracted from the input sequence and a well-parametrized support vector regression model. We provide two versions of qNABpredict, a taxonomy-agnostic model that can be used for proteins of unknown taxonomic origin and more accurate taxonomy-aware models that are tailored to specific taxonomic kingdoms: archaea, bacteria, eukaryota, and viruses. Empirical tests on a low-similarity test dataset show that qNABpredict is 100 times faster and generates statistically more accurate content predictions when compared to the content extracted from results produced by the residue-level predictors. We also show that qNABpredict's content predictions can be used to improve results generated by the residue-level predictors. We release qNABpredict as a convenient webserver and source code at http://biomine.cs.vcu.edu/servers/qNABpredict/ . This new tool should be particularly useful to predict details of protein–NA interactions for large protein families and proteomes.     

Rat polymerase beta gapped DNA interactions: antagonistic effects of the 5' terminal PO4 - group and magnesium on the enzyme binding to the gapped DNAs with different ssDNA gaps

The role of the 5′ terminal phosphate group downstream from the primer and magnesium cations in the energetics and dynamics of the gapped DNA recognition by rat polymerase β have been examined, using the fluorescence titration and stopped-flow techniques. The analyses have been performed with the entire series of gapped DNA substrates differing in the size of the ssDNA gap. The 5′ terminal phosphate group and magnesium cations exert antagonistic effect on enzyme binding to gapped DNA that depends on the length of the ssDNA gap. The PO ₄ ⁻ group amplifies the differences between the substrates with different ssDNA gaps, while in the presence of magnesium, affinities and structural changes induced in the DNA are very similar among examined DNA substrates. Both, the phosphate group and Mg⁺² differ dramatically in affecting the thermodynamic response of the gapped DNA-rat pol β system to the salt concentration. The data indicate that these distinct effects result from affecting the structure of the DNA, in the case of the phosphate group, and from direct magnesium binding to the protein. The mechanism of rat enzyme binding depends on the length of the ssDNA gap and the presence of the 5′ terminal phosphate group. Complex formation with DNAs having three, four, and five residues in the gap occurs by a minimum three-step sequential mechanism. Depending on the presence of the 5′ terminal phosphate group and/or magnesium, binding of the enzyme to a DNA containing two residues in the ssDNA gap is described by the same three-step or by a simpler two-step mechanism. With the DNA containing only one residue in the gap, binding is always described by only a two-step mechanism. The PO ₄ ⁻ group and magnesium cations have opposite effects on internal stability of the complexes with different length of the ssDNA gap. While the PO ₄ ⁻ group increases the stability of internal intermediates with the increasing length of the gap, Mg⁺² decreases the stability of the intermediates with longer ssDNA gap. As a result, the combined favorable orientation effect of the phosphate group and the unfavorable Mg⁺² effect lead to the optimal docking of the ssDNA gaps with three and four residues by the enzyme. This work was supported by NIH Grant GM-58565 (to W. B.)     

iWRAP: An interface threading approach with application to prediction of cancer-related protein-protein interactions

Current homology modeling methods for predicting protein-protein interactions (PPIs) have difficulty in the “twilight zone” (< 40%) of sequence identities. Threading methods extend coverage further into the twilight zone by aligning primary sequences for a pair of proteins to a best-fit template complex to predict an entire three-dimensional structure. We introduce a threading approach, iWRAP, which focuses only on the protein interface. Our approach combines a novel linear programming formulation for interface alignment with a boosting classifier for interaction prediction. We demonstrate its efficacy on SCOPPI, a classification of PPIs in the Protein Databank, and on the entire yeast genome. iWRAP provides significantly improved prediction of PPIs and their interfaces in stringent cross-validation on SCOPPI. Furthermore, by combining our predictions with a full-complex threader, we achieve a coverage of 13% for the yeast PPIs, which is close to a 50% increase over previous methods at a higher sensitivity. As an application, we effectively combine iWRAP with genomic data to identify novel cancer-related genes involved in chromatin remodeling, nucleosome organization, and ribonuclear complex assembly. iWRAP is available at http://iwrap.csail.mit.edu.     

A tri-functional amino acid enables mapping of binding sites for posttranslational-modification-mediated protein-protein interactions

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The interactions between humans and mammals in Africa in relation to conservation: a review

Most human-mammal interactions are detrimental to wild mammals. In Africa, mammalian population numbers and the geographical distribution of many species have been reduced due to hunting, pastoralism, habitat modification and disease control. The importance of each of these factors depends on the species, its location and habitat, and density of the human population. In contrast, some small- and medium-sized species have benefited from human activities, and there has been an increase in the population numbers of some species in well-managed and well-protected conservation areas. There appears to be a strong negative correlation (at least for some well-studied species) between density of humans and density of mammals. Recently, several African countries, notably in southern Africa, have developed the principle of integrated rural development in which local people are involved in the planning and administration of their traditional lands. Managed conservation areas are an integral part of good land-use policies. Surveys indicate that most Africans living close to conservation areas, especially those with a higher level of education, understand and support the ideals of conservation; nevertheless it is important that the benefits of conservation and integrated development (such as money, jobs, and food) directly benefit the local people. Conservation of mammals (and all other species) in Africa in the future will only succeed if there is participation at the grass roots level, better food production in designated agricultural areas, reduction in the rate of increase of human populations, stabilization of human densities, and active programmes of conservation education.     

Computation of conformational entropy from protein sequences using the machine-learning method--application to the study of the relationship between structural conservation and local structural stability

A complete protein sequence can usually determine a unique conformation; however, the situation is different for shorter subsequences--some of them are able to adopt unique conformations, independent of context; while others assume diverse conformations in different contexts. The conformations of subsequences are determined by the interplay between local and nonlocal interactions. A quantitative measure of such structural conservation or variability will be useful in the understanding of the sequence-structure relationship. In this report, we developed an approach using the support vector machine method to compute the conformational variability directly from sequences, which is referred to as the sequence structural entropy. As a practical application, we studied the relationship between sequence structural entropy and the hydrogen exchange for a set of well-studied proteins. We found that the slowest exchange cores usually comprise amino acids of the lowest sequence structural entropy. Our results indicate that structural conservation is closely related to the local structural stability. This relationship may have interesting implications in the protein folding processes, and may be useful in the study of the sequence-structure relationship.     

Prediction of protein secondary structure content using amino acid composition and evolutionary information

Knowing protein structure and inferring its function from the structure are one of the main issues of computational structural biology, and often the first step is studying protein secondary structure. There have been many attempts to predict protein secondary structure contents. Previous attempts assumed that the content of protein secondary structure can be predicted successfully using the information on the amino acid composition of a protein. Recent methods achieved remarkable prediction accuracy by using the expanded composition information. The overall average error of the most successful method is 3.4%. Here, we demonstrate that even if we only use the simple amino acid composition information alone, it is possible to improve the prediction accuracy significantly if the evolutionary information is included. The idea is motivated by the observation that evolutionarily related proteins share the similar structure. After calculating the homolog-averaged amino acid composition of a protein, which can be easily obtained from the multiple sequence alignment by running PSI-BLAST, those 20 numbers are learned by a multiple linear regression, an artificial neural network and a support vector regression. The overall average error of method by a support vector regression is 3.3%. It is remarkable that we obtain the comparable accuracy without utilizing the expanded composition information such as pair-coupled amino acid composition. This work again demonstrates that the amino acid composition is a fundamental characteristic of a protein. It is anticipated that our novel idea can be applied to many areas of protein bioinformatics where the amino acid composition information is utilized, such as subcellular localization prediction, enzyme subclass prediction, domain boundary prediction, signal sequence prediction, and prediction of unfolded segment in a protein sequence, to name a few.     

Sequence specific DNA binding of Ets-1 transcription factor: molecular dynamics study on the Ets domain--DNA complexes

Molecular dynamics (MD) simulations for Ets-1 ETS domain-DNA complexes were performed to investigate the mechanism of sequence-specific recognition of the GGAA DNA core by the ETS domain. Employing the crystal structure of the Ets-1 ETS domain-DNA complex as a starting structure we carried out MD simulations of: (i). the complex between Ets-1 ETS domain and a 14 base-pair DNA containing GGAA core sequence (ETS-GGAA); (ii). the complex between the ETS domain and a DNA having single base-pair mutation, GGAG sequence (ETS-GGAG); and (iii). the 14 base-pair DNA alone (GGAA). Comparative analyses of the MD structures of ETS-GGAA and ETS-GGAG reveal that the DNA bending angles and the ETS domain-DNA phosphate interactions are similar in these complexes. These results support that the GGAA core sequence is distinguished from the mutated GGAG sequence by a direct readout mechanism in the Ets-1 ETS domain-DNA complex. Further analyses of the direct contacts in the interface between the helix-3 region of Ets-1 and the major groove of the core DNA sequence clearly show that the highly conserved arginine residues, Arg391 and Arg394, play a critical role in binding to the GGAA core sequence. These arginine residues make bidentate contacts with the nucleobases of GG dinucleotides in GGAA core sequence. In ETS-GGAA, the hydroxyl group of Tyr395 is hydrogen bonded to N7 nitrogen of A(3) (the third adenosine in the GGAA core), while the hydroxyl group makes a contact with N4 nitrogen of C(4') (the complementary nucleotide of the fourth guanosine G(4) in the GGAG sequence) in the ETS-GGAG complex. We have found that this difference in behavior of Tyr395 results in the relatively large motion of helix-3 in the ETS-GGAG complex, causing the collapse of bidentate contacts between Arg391/Arg394 and the GG dinucleotides in the GGAG sequence.