Speeding up the drug discovery process: structural similarity searches using molecular surfaces

Antibodies as stratagems against cancer

Antibodies have been in the frontline of anticancer research during the last few decades, since a number of different ways have been discovered to utilize them as parts or main components of anticancer drugs. Antibodies are used as the only component of some anticancer drugs, but they can also be conjugated with a variety of substances. Antibody engineering methods such as humanization, chimerization and Fc engineering are applied in order to modify their properties according to the requirements of anticancer drug application. Given the continuous advances in biology and informatics, the role of antibodies in anticancer treatment is expected to be prominent.

Protein signatures using electrostatic molecular surfaces in harmonic space

We developed a novel method based on the Fourier analysis of protein molecular surfaces to speed up the analysis of the vast structural data generated in the post-genomic era. This method computes the power spectrum of surfaces of the molecular electrostatic potential, whose three-dimensional coordinates have been either experimentally or theoretically determined. Thus we achieve a reduction of the initial three-dimensional information on the molecular surface to the one-dimensional information on pairs of points at a fixed scale apart. Consequently, the similarity search in our method is computationally less demanding and significantly faster than shape comparison methods. As proof of principle, we applied our method to a training set of viral proteins that are involved in major diseases such as Hepatitis C, Dengue fever, Yellow fever, Bovine viral diarrhea and West Nile fever. The training set contains proteins of four different protein families, as well as a mammalian representative enzyme. We found that the power spectrum successfully assigns a unique signature to each protein included in our training set, thus providing a direct probe of functional similarity among proteins. The results agree with established biological data from conventional structural biochemistry analyses.