Alexander E. Kister

Common features in structures and sequences of sandwich-like proteins

The goal of this work is to define the structural and sequence features common to sandwich-like proteins (SPs), a group of very different proteins now comprising 69 superfamilies in 38 protein folds. Analysis of the arrangements of strands within main sandwich sheets revealed a rigorously defined constraint on the supersecondary substructure that holds true for 94% of known SP structures. The invariant substructure consists of two interlocked pairs of neighboring β-strands. It is even more typical for centers of SP than the well-known “Greek key” strands arrangement for their edges. As homology among these proteins is not usually detectable even with the most powerful sequence-comparing algorithms, we employed a structure-based approach to sequence alignment. Within the interlocked strands we found 12 positions with fixed structural roles in SP. A residue at any of these positions possesses similar structural properties with residues in the same position of other SPs. The 12 positions lie at the center of the interface between the β-sheets and form the common geometrical core of SPs. Of the 12 positions, 8 are occupied by only four hydrophobic residues in 80% of all SPs.

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.

A stringent test for hydrophobicity scales: Two proteins with 88% sequence identity but different structure and function

Protein–protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein–protein interfaces. In their classic article, Kyte and Doolittle (KD) concluded that the “simplicity and graphic nature of hydrophobicity scales make them very useful tools for the evaluation of protein structures.” In practice, however, attempts to develop hydrophobicity scales (for example, compatible with classical force fields (CFF) in calculating the energetics of protein folding) have encountered many difficulties. Here, we suggest an entirely different approach based on the idea that proteins are self-organized networks, subject to evolving finite-scale criticality (like some network glasses). We test this proposal against two small proteins that are delicately balanced between α and α/β structures, with different functions encoded with only 12% of their amino acids. This example explains why protein structure prediction is so challenging, and it provides a severe test for the accuracy and content of hydrophobicity scales. This method confirms KDs evaluation and at the same time suggests that protein structure, dynamics, and function can be best discussed without using CFF.

Finding of residues crucial for supersecondary structure formation

This work evaluates the hypothesis that proteins with an identical supersecondary structure (SSS) share a unique set of residues—SSS-determining residues—even though they may belong to different protein families and have very low sequence similarities. This hypothesis was tested on two groups of sandwich-like proteins (SPs). Proteins in each group have an identical SSS, but their sequence similarity is below the “twilight zone.” To find the SSS-determining residues specific to each group, a unique structure-based algorithm of multiple sequences alignment was developed. The units of alignment are individual strands and loops rather than whole sequences. The algorithm is based on the alignment of residues that form hydrogen bonds between corresponding strands. Structure-based alignment revealed that 30–35% of the positions in the sequences in each group of proteins are “conserved positions” occupied either by hydrophobic-only or hydrophilic-only residues. Moreover, each group of SPs is characterized by a unique set of SSS-determining residues found at the conserved positions. The set of SSS-determining residues has very high sensitivity and specificity for identifying proteins with a corresponding SSS: It is an “amino acid tag” that brands a sequence as having a particular SSS. Thus, the sets of SSS-determining residues can be used to classify proteins and to predict the SSS of a query amino acid sequence.

Geometric invariant core for the CL and CH1 domains of immunoglobulin molecules.

A previously developed algorithmic method for identifying a geometric invariant of protein structures, termed geometrical core, is extended to the C(L) and C(H1) domains of immunoglobulin molecules. The method uses the matrix of C(alpha) - C(alpha) distances and does not require the usual superposition of structures. The result of applying the algorithm to 53 Immunoglobulin structures led to the identification of two geometrical core sets of C(alpha) atom positions for the C(L) and C(H1) domains.

Algorithmic determination of core positions in the VL and VH domains of immunoglobulin molecules.

We introduce a new algorithmic method for identifying the geometrical core of proteins that does not require the usual superposition of structures. A geometrical core is defined as the set of residues such that the C alpha (I) - C alpha (J) atom distances are identical in all structures of the protein family under study, where I and J are secondary structure positions in the structural units--strands, loops, or parts of them. The result of applying the algorithm to 53 Ig structures leads to the identification of two geometrical core sets of C alpha atom positions for the VL and VH domains. Applications of the core sets are described.

Algorithmic determination of core positions in the V L and V H domains of immunoglobulin molecules

We introduce a new algorithmic method for identifying the geometrical core of proteins that does not require the usual superposition of structures. A geometrical core is defined as the set of residues such that the C alpha (I) - C alpha (J) atom distances are identical in all structures of the protein family under study, where I and J are secondary structure positions in the structural units--strands, loops, or parts of them. The result of applying the algorithm to 53 Ig structures leads to the identification of two geometrical core sets of C alpha atom positions for the VL and VH domains. Applications of the core sets are described.