ABSTRACT: Ten protein kinase C (PKC) isozymes play divergent roles in signal transduction. Because of sequence similarities, it is particularly difficult to generate isozyme-selective small molecule inhibitors. In order to identify such a selective binder, we derived a pharmacophore model from the peptide EAVSLKPT, a fragment of PKCε that inhibits the interaction of PKCε and receptor for activated C-kinase 2 (RACK2). A database of 330 000 molecules was screened in silico, leading to the discovery of a series of thienoquinolines that disrupt the interaction of PKCε with RACK2 in vitro. The most active molecule, N-(3-acetylphenyl)-9- amino-2,3-dihydro-1,4-dioxino[2,3-g]thieno[2,3-b]quinoline-8-carboxamide (8), inhibited this interaction with a measured IC50 of 5.9 μM and the phosphorylation of downstream target Elk-1 in HeLa cells with an IC50 of 11.2 μM. Compound 8 interfered with MARCKS phosphorylation and TPA-induced translocation of PKCε (but not that of PKCδ) from the cytosol to the membrane. The compound reduced the migration of HeLa cells into a gap, reduced invasion through a reconstituted basement membrane matrix, and inhibited angiogenesis in a chicken egg assay.
J Med Chem. 2014 Apr 24;57(8):3235-46.

Globular proteins themselves form compact molecular structures, the packing density of the atoms in which is close to the density of packing of atoms in crystals. We suppose that for the existence of such properties in natural polypeptide chains, there must exist both the areas in which local interactions mainly take place, and the areas in which the interaction between remote chain residues mainly takes place. To test this prediction, we developed a program for analyzing contacts between residues in the polypeptide chain, depending on the local density of structural information. To estimate the density of the structural information, the earlier proposed in [1] method of analysis of the information structure of protein sequences was used. The developed program uses a set of files in PDB for input, which initially pass through a correction stage (insertions and deletions are corrected, the non-canonical residues names are restored, etc.) and then information structure of the regarded protein is calculated, and a matrix of contacts for residues belonging to the sections of the polypeptide with a different density of structural information is built. The program is able to build a matrix of contacts for residues of various information type, i.e. located at different distances from the local extremes in the information structure of the protein under study. This paper discusses in detail the contacts between residues located in the vicinity of the extremes of the information structure, i.e. residues of different information types. The developed program allows exploring the contacts between amino acid residues depending on their information types. It is shown that the information type of residue is an important factor in determining the amino acid residue ability to interact effectively with other amino acid residues of the polypeptide chain. The matrices of contacts were shown for residues of various information types, what confirms the hypothesis of the existence of the regions of the polypeptide chain implementing mainly short- or long-distance interactions within the protein molecule. The results obtained can be widely used in protein computer modeling works and in the design of natural protein molecules. 1. A. N. Nekrasov et al. (2004) Analysis of the information structure of protein sequences: a new method for analyzing the domain organization of proteins, J. Biomol. Struct. Dyn. 2004, 21(5), pp. 615-624. A. N. Nekrasov, A. A. Zinchenko (2010) Structural features of the interfaces in enzyme-inhibitor complexes. J Biomol Struct Dyn. 2010, 28(1), pp. 85-96.
Moscow Conference on Computational Molecular Biology (MCCMB'13) Moscow, Russia July 25–28, 2013

Background: The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published in silico method PAAS was applied for prediction of interactions between protein kinases and their substrates. Results: We used the method for recognition of the protein classes defined by the interaction with the same protein partners. 1021 protein kinase substrates classified by 45 kinases were extracted from the Phospho.ELM database and used as a training set. The reasonable accuracy of prediction calculated by leave-one-out cross validation procedure was observed in the majority of kinase-specificity classes. The random multiple splitting of the studied set onto the test and training set had also led to satisfactory results. The kinase substrate specificity for 186 proteins extracted from TRANSPATH® database was predicted by PAAS method. Several kinase-substrate interactions described in this database were correctly predicted. Using the previously developed ExPlain™ system for the reconstruction of signal transduction pathways, we showed that addition of the newly predicted interactions enabled us to find the possible path between signal trigger, TNF-alpha, and its target genes in the cell. Conclusions: It was shown that the predictions of protein kinase substrates by PAAS were suitable for the enrichment of signaling pathway networks and identification of the novel signaling pathways. The on-line version of PAAS for prediction of protein kinase substrates is freely available at http://www.ibmc.msk.ru/PAAS/.
BMC Bioinformatics, 2010, 11: 313.

In our previous report we first described a complex between lactoferrin (Lf) and ceruloplasmin (Cp) with K (d) ~ 1.8 muM. The presence of this complex in colostrum that never contains more than 0.3 muM Cp questions the reliability of K (d) value. We carefully studied Lf binding to Cp and investigated the enzymatic activity of the latter in the presence of Lf, which allowed obtaining a new value for K (d) of Cp-Lf complex. Lf interacting with Cp changes its oxidizing activity with various substrates, such as Fe(2+), o-dianisidine (o-DA), p-phenylenediamine (p-PD) and dihydroxyphenylalanine (DOPA). The presence of at least two binding sites for Lf in Cp molecule is deduced from comparison of substrates' oxidation kinetics with and without Lf. When Lf binds to the first site affinity of Cp to Fe(2+) and to o-DA increases, but it decreases towards DOPA and remains unchanged towards p-PD. Oxidation rate of Fe(2+) grows, while that of o-DA, p-PD and DOPA goes down. Subsequent Lf binding to the second center has no effect on iron oxidation, hampers DOPA and o-DA oxidation, and reduces affinity towards p-PD. Scatchard plot for Lf sorbing to Cp-Sepharose allowed estimating K (d) for Lf binding to high-affinity (~13.4 nM) and low-affinity (~211 nM) sites. The observed effect of Lf on ferroxidase activity of Cp is likely to have physiological implications.
Sokolov AV, Ageeva KV, Pulina MO, Zakharova ET, Vasilyev VB. (2009) Effect of lactoferrin on oxidative features of ceruloplasmin.// Biometals, V. 22, P. 521-529.