Class-defining characteristics in the mouse heavy chains of variable domains

The 3D Invariant Positioning for Protein Molecules / Molecular Complexes with Matching Subunits

This chapter revisits the method to construct the 3D invariant positions (invariant system of coordinates) for a given protein molecule or molecular complex-its premises and purpose, algorithmic details, and opportunities for use. This chapter also proposes the generalized approach, good for any class of molecules or complexes that contain several spatially identical (or nearly identical) subunits.

Applying hybrid reasoning to mine for associative features in biological data

We develop the means to mine for associative features in biological data. The hybrid reasoning schema for deterministic machine learning and its implementation via logic programming is presented. The methodology of mining for correlation between features is illustrated by the prediction tasks for protein secondary structure and phylogenetic profiles. The suggested methodology leads to a clearer approach to hierarchical classification of proteins and a novel way to represent evolutionary relationships. Comparative analysis of Jasmine and other statistical and deterministic systems (including Explanation-Based Learning and Inductive Logic Programming) are outlined. Advantages of using deterministic versus statistical data mining approaches for high-level exploration of correlation structure are analyzed.

Correlated mutations: advances and limitations. A study on fusion proteins and on the Cohesin-Dockerin families

Correlated mutations have been repeatedly exploited for intramolecular contact map prediction. Over the last decade these efforts yielded several methods for measuring correlated mutations. Nevertheless, the application of correlated mutations for the prediction of intermolecular interactions has not yet been explored. This gap is due to several obstacles, such as 3D complexes availability, paralog discrimination, and the availability of sequence pairs that are required for inter- but not intramolecular analyses. Here we selected for analysis fusion protein families that bypass some of these obstacles. We find that several correlated mutation measurements yield reasonable accuracy for intramolecular contact map prediction on the fusion dataset. However, the accuracy level drops sharply in intermolecular contacts prediction. This drop in accuracy does not occur always. In the Cohesin-Dockerin family, reasonable accuracy is achieved in the prediction of both intra- and intermolecular contacts. The Cohesin-Dockerin family is well suited for correlated mutation analysis. Because, however, this family constitutes a special case (it has radical mutations, has domain repeats, within each species each Dockerin domain interacts with each Cohesin domain, see below), the successful prediction in this family does not point to a general potential in using correlated mutations for predicting intermolecular contacts. Overall, the results of our study indicate that current methodologies of correlated mutations analysis are not suitable for large-scale intermolecular contact prediction, and thus cannot assist in docking. With current measurements, sequence availability, sequence annotations, and underdeveloped sequence pairing methods, correlated mutations can yield reasonable accuracy only for a handful of families.

Determining the roles of different chain fragments in recognition of immunoglobulin fold

We examine sequence-to-structure specificity of beta-structural fragments of immunoglobulin domains. The structure specificity of separate chain fragments is estimated by computing the Z-score values in recognition of the native structure in gapless threading tests. To improve the accuracy of our calculations we use energy averaging over diverse homologs of immunoglobulin domains. We show that the interactions between residues of beta-structure are more determinant in recognition of the native structure than the interactions within the whole chain molecule. This result distinguishes immunoglobulins from more typical proteins where the interactions between residues of the whole chain normally recognize the native fold more accurately than interactions between the residues of the secondary structure residues alone [Reva,B. and Topiol,S. (2000) BIOCOMPUTING: Proceedings of the Pacific Symposium. World Scientific Publishing Co., pp. 168-178]. We also find that the predominant contributions of the secondary structure are produced by the four central beta-strands that form the core of the molecule. The results of this study allow us through quantitative means to understand the architecture of immunoglobulin molecules. Comparing the fold recognition data for different chain fragments one can say that beta-strands form a rigid frame for immunoglobulin molecules, whereas loops, with no structural role, can develop a broad variety of binding specificities. It is well known that protein function is determined by specific portions of a protein chain. This study suggests that the whole protein structure can be predominantly determined by a few fragments of chain which form the structural framework of the molecule. This idea may help in better understanding the mechanisms of protein evolution: strengthening a protein structure in the key framework-forming regions allows mutations and flexibility in other chain regions.

The sequence determinants of cadherin molecules

The sequence and structural analysis of cadherins allow us to find sequence determinants-a few positions in sequences whose residues are characteristic and specific for the structures of a given family. Comparison of the five extracellular domains of classic cadherins showed that they share the same sequence determinants despite only a nonsignificant sequence similarity between the N-terminal domain and other extracellular domains. This allowed us to predict secondary structures and propose three-dimensional structures for these domains that have not been structurally analyzed previously. A new method of assigning a sequence to its proper protein family is suggested: analysis of sequence determinants. The main advantage of this method is that it is not necessary to know all or almost all residues in a sequence as required for other traditional classification tools such as BLAST, FASTA, and HMM. Using the key positions only, that is, residues that serve as the sequence determinants, we found that all members of the classic cadherin family were unequivocally selected from among 80,000 examined proteins. In addition, we proposed a model for the secondary structure of the cytoplasmic domain of cadherins based on the principal relations between sequences and secondary structure multialignments. The patterns of the secondary structure of this domain can serve as the distinguishing characteristics of cadherins.