Comparative molecular field analysis and comparative molecular similarity indices analysis of human thymidine kinase 1 substrates

Thymidine kinase 1 (TK1) is a key target for antiviral and anticancer chemotherapy. Three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques was applied to analyze the phosphorylation capacity of a series of 31 TK1 substrates. The optimal predictive CoMFA model with 26 molecules provided the following values: cross-validated r(2) (q(2))=0.651, non-cross-validated r(2)=0.980, standard error of estimate (s)=0.207, F=129.3. For the optimal CoMSIA model the following values were found: q(2)=0.619, r(2)=0.994, s=0.104, F=372.2. The CoMSIA model includes steric, electrostatic, and hydrogen bond donor fields. The predictive capacity of both models was successfully validated by calculating known phosphorylation rates of five TK1 substrates that were not included in the training set. Contour maps obtained from CoMFA and CoMSIA models correlated with the experimentally developed SAR.     

Blue copper proteins: a comparative analysis of their molecular interaction properties

Blue copper proteins are type-I copper-containing redox proteins whose role is to shuttle electrons from an electron donor to an electron acceptor in bacteria and plants. A large amount of experimental data is available on blue copper proteins; however, their functional characterization is hindered by the complexity of redox processes in biological systems. We describe here the application of a semiquantitative method based on a comparative analysis of molecular interaction fields to gain insights into the recognition properties of blue copper proteins. Molecular electrostatic and hydrophobic potentials were computed and compared for a set of 33 experimentally-determined structures of proteins from seven blue copper subfamilies, and the results were quantified by means of similarity indices. The analysis provides a classification of the blue copper proteins and shows that (I) comparison of the molecular electrostatic potentials provides useful information complementary to that highlighted by sequence analysis; (2) similarities in recognition properties can be detected for proteins belonging to different subfamilies, such as amicyanins and pseudoazurins, that may be isofunctional proteins; (3) dissimilarities in interaction properties, consistent with experimentally different binding specificities, may be observed between proteins belonging to the same subfamily, such as cyanobacterial and eukaryotic plastocyanins; (4) proteins with low sequence identity, such as azurins and pseudoazurins, can have sufficient similarity to bind to similar electron donors and acceptors while having different binding specificity profiles.     

SPR for molecular interaction analysis: a review of emerging application areas

PubMed searches identified four emerging application areas for surface plasmon resonance systems. Food analysis, proteomics, immunogenicity and drug discovery. These application areas are reviewed. In connection with the review of drug discovery applications a case study is presented. This study demonstrates the value of combining results from drug-target and ADME predictive assays for compound selection.     

Protein-protein interaction based on pairwise similarity

Background  

Protein-protein interaction (PPI) is essential to most biological processes. Abnormal interactions may have implications in a number of neurological syndromes. Given that the association and dissociation of protein molecules is crucial, computational tools capable of effectively identifying PPI are desirable. In this paper, we propose a simple yet effective method to detect PPI based on pairwise similarity and using only the primary structure of the protein. The PPI based on Pairwise Similarity (PPI-PS) method consists of a representation of each protein sequence by a vector of pairwise similarities against large subsequences of amino acids created by a shifting window which passes over concatenated protein training sequences. Each coordinate of this vector is typically the E-value of the Smith-Waterman score. These vectors are then used to compute the kernel matrix which will be exploited in conjunction with support vector machines.     

Structural similarity enhances interaction propensity of proteins

We study statistical properties of interacting protein-like surfaces and predict two strong, related effects: (i) statistically enhanced self-attraction of proteins; (ii) statistically enhanced attraction of proteins with similar structures. The effects originate in the fact that the probability to find a pattern self-match between two identical, even randomly organized interacting protein surfaces is always higher compared with the probability for a pattern match between two different, promiscuous protein surfaces. This theoretical finding explains statistical prevalence of homodimers in protein-protein interaction networks reported earlier. Further, our findings are confirmed by the analysis of curated database of protein complexes that showed highly statistically significant overrepresentation of dimers formed by structurally similar proteins with highly divergent sequences ("superfamily heterodimers"). We suggest that promiscuous homodimeric interactions pose strong competitive interactions for heterodimers evolved from homodimers. Such evolutionary bottleneck is overcome using the negative design evolutionary pressure applied against promiscuous homodimer formation. This is achieved through the formation of highly specific contacts formed by charged residues as demonstrated both in model and real superfamily heterodimers.     

Rintact: enabling computational analysis of molecular interaction data from the IntAct repository

MOTIVATION: The IntAct repository is one of the largest and most widely used databases for the curation and storage of molecular interaction data. These datasets need to be analyzed by computational methods. Software packages in the statistical environment R provide powerful tools for conducting such analyses. RESULTS: We introduce Rintact, a Bioconductor package that allows users to transform PSI-MI XML2.5 interaction data files from IntAct into R graph objects. On these, they can use methods from R and Bioconductor for a variety of tasks: determining cohesive subgraphs, computing summary statistics, fitting mathematical models to the data or rendering graphical layouts. Rintact provides a programmatic interface to the IntAct repository and allows the use of the analytic methods provided by R and Bioconductor. AVAILABILITY: Rintact is freely available at http://bioconductor.org     

Structural similarity and classification of protein interaction interfaces

Interactions between proteins play a key role in many cellular processes. Studying protein-protein interactions that share similar interaction interfaces may shed light on their evolution and could be helpful in elucidating the mechanisms behind stability and dynamics of the protein complexes. When two complexes share structurally similar subunits, the similarity of the interaction interfaces can be found through a structural superposition of the subunits. However, an accurate detection of similarity between the protein complexes containing subunits of unrelated structure remains an open problem. Here, we present an alignment-free machine learning approach to measure interface similarity. The approach relies on the feature-based representation of protein interfaces and does not depend on the superposition of the interacting subunit pairs. Specifically, we develop an SVM classifier of similar and dissimilar interfaces and derive a feature-based interface similarity measure. Next, the similarity measure is applied to a set of 2,806×2,806 binary complex pairs to build a hierarchical classification of protein-protein interactions. Finally, we explore case studies of similar interfaces from each level of the hierarchy, considering cases when the subunits forming interactions are either homologous or structurally unrelated. The analysis has suggested that the positions of charged residues in the homologous interfaces are not necessarily conserved and may exhibit more complex conservation patterns.     

Cytological and molecular analysis of the Hordeum vulgare-Puccinia triticina nonhost interaction

Cultivated barley, Hordeum vulgare L., is considered to be a nonhost or intermediate host species for the wheat leaf rust fungus Puccinia triticina. Here, we have investigated, at the microscopic and molecular levels, the reaction of barley cultivars to wheat leaf rust infection. In the nonhost resistant cultivar Cebada Capa, abortion of fungal growth occurred at both pre- and posthaustorial stages, suggesting that defense genes are expressed throughout the development of the inappropriate fungus during the nonhost resistance reaction. In the two barley lines L94 and Bowman, a low level of prehaustorial resistance to P. triticina was observed and susceptibility was comparable to that of wheat control plants. Suppression subtractive hybridization was used to identify genes that are differentially expressed during the nonhost resistance reaction in Cebada Capa as well as during the successful establishment of the inappropriate wheat leaf rust fungus in L94. Northern analysis indicated that two candidate genes, including a barley ortholog of the rice resistance gene Xa21, are putatively involved in nonhost and non-race-specific resistance reactions. In addition, a new gene that is specifically induced during the successful development of the inappropriate fungus P. triticina in barley has been identified.     

Knowledge-based interaction potentials for proteins.

We discuss the derivation of atomic-level potentials of mean force from the known protein structures and their applicability for structural evaluation applications. In the derivation process, rigorous density estimation methodology is used to estimate the probability density functions (PDFs) for the distributions of interatomic distances in the protein structures. Potentials of mean force are then derived from these density functions using simple Boltzmann's relation. We also test the potentials against pairs of current and superseded protein structures in the Protein Data Bank. Using PDF potentials to evaluate each structure pair, we are able to identify, with high accuracy, which of the two structures is of higher resolution or better quality. This result shows that the PDF potentials are sensitive to details in protein structures as the current and superseded atomic coordinates generally do not differ by more than 1 A in root-mean-square deviation, and that the PDF potentials could potentially be used for X-ray structure refinement and protein structure prediction.     

Quantitative analysis of molecular surfaces: areas, volumes, electrostatic potentials and average local ionization energies

We describe a procedure for performing quantitative analyses of fields f(r) on molecular surfaces, including statistical quantities and locating and evaluating their local extrema. Our approach avoids the need for explicit mathematical representation of the surface and can be implemented easily in existing graphical software, as it is based on the very popular representation of a surface as collection of polygons. We discuss applications involving the volumes, surface areas and molecular surface electrostatic potentials, and local ionization energies of a group of 11 molecules.

Derivation of protein-specific pair potentials based on weak sequence fragment similarity

A method is presented for the derivation of knowledge-based pair potentials that corrects for the various compositions of different proteins. The resulting statistical pair potential is more specific than that derived from previous approaches as assessed by gapless threading results. Additionally, a methodology is presented that interpolates between statistical potentials when no homologous examples to the protein of interest are in the structural database used to derive the potential, to a Go-like potential (in which native interactions are favorable and all nonnative interactions are not) when homologous proteins are present. For cases in which no protein exceeds 30% sequence identity, pairs of weakly homologous interacting fragments are employed to enhance the specificity of the potential. In gapless threading, the mean z score increases from -10.4 for the best statistical pair potential to -12.8 when the local sequence similarity, fragment-based pair potentials are used. Examination of the ab initio structure prediction of four representative globular proteins consistently reveals a qualitative improvement in the yield of structures in the 4 to 6 A rmsd from native range when the fragment-based pair potential is used relative to that when the quasichemical pair potential is employed. This suggests that such protein-specific potentials provide a significant advantage relative to generic quasichemical potentials.     

Subunit interaction: A molecular basis of heterosis

Acid phosphatase, a dimeric enzyme, in Drosophila malerkotliana was studied in isogenic flies to explore the molecular basis of heterosis. As the enzyme activity in heterozygotes is 34% more than that in the better parent (S/S), heterosis is indicated. Vmax, Km, and Ki values are 14.60, 3.6 X 10(-4) M, and 0.45 X 10(-4) M, respectively, for the enzyme from F/S flies and 11.80, 4.0 X 10(-4) M, and 0.37 X 10(-4) M, respectively, for the enzyme from S/S flies. Thus heterosis for enzyme activity results from a better enzyme in F/S flies. The higher efficiency and better quality of the enzyme in F/S flies were traced to the heterodimeric allozyme, present only in heterozygotes. Enzyme activity, Vmax, Km, and Ki values are 0.739, 42.1; 3.6 X 10(-4) M, and 0.50 X 10(-4) M, respectively, for the heterodimeric and 0.513, 36.8; 4.1 X 10(-4) M, and 0.37 X 10(-4) M, respectively, for the better parental homodimeric allozyme. On an equimolar basis the enzyme activity of the heterodimer is 44% higher than that of the better homodimer. The better performance of the heterodimer is probably a reflection of superior conformation resulting from interaction between component subunits (F and S polypeptides).     

Bilateral similarity function: A novel and universal method for similarity analysis of biological sequences

Bilateral similarity function is designed for analyzing the similarities of biological sequences such as DNA, RNA secondary structure or protein in this paper. The defined function can perform comprehensive comparison between sequences remarkably well, both in terms of the Hamming distance of two compared sequences and the corresponding location difference. Compared with the existing methods for similarity analysis, the examination of similarities/dissimilarities illustrates that the proposed method with the computational complexity of O(N) is effective for these three kinds of biological sequences, and bears the universality for them.     

Assessing sedimentation equilibrium profiles in analytical ultracentrifugation experiments on macromolecules: from simple average molecular weight analysis to molecular weight distribution and interaction analysis

Molecular weights (molar masses), molecular weight distributions, dissociation constants and other interaction parameters are fundamental characteristics of proteins, nucleic acids, polysaccharides and glycoconjugates in solution. Sedimentation equilibrium analytical ultracentrifugation provides a powerful method with no supplementary immobilization, columns or membranes required. It is a particularly powerful tool when used in conjunction with its sister technique, namely sedimentation velocity. Here, we describe key approaches now available and their application to the characterization of antibodies, polysaccharides and glycoconjugates. We indicate how major complications, such as thermodynamic non-ideality, can now be routinely dealt with, thanks to a great extent to the extensive contribution of Professor Don Winzor over several decades of research.     

A principle of maximum topological similarity in molecular systematics

The paper deals with the problem of phylogenetic reconstruction on the basis of comparative analysis of features. Main attention is paid to comparison and classification of the biopolymer sequences. Different approaches to this task are critically reviewed. The novel principle of construction of tree-like classification schemes permitting subsequent evolutionary analysis is proposed. It concentrates on reconstruction of the tree with a topologic structure that is most close to topologic features, imprinted in the source distance matrix. Realization of this approach was made possible by development of the special formalism, enabling evaluation and comparison of topologic features of distance matrices and trees.