Oleg Obolensky
Research Specialist (Contractor)
National Center for Biotechnology Information (NCBI)
National Library of Medicine (NLM)
National Institutes of Health (NIH)
Bldg. 38A, Room 6N611A
9000 Rockville Pike, MSC 3829
Bethesda, MD 20894, USA
Tel: (301) 402-3010
Fax: (301) 480-2288
e-mail:
obolensk <at> ncbi.nlm.nih.gov
CV
Publications
Current Research Projects
Molecular Interactions:
Energy minimization formulation of electrostatics suitable to biomolecular systems
The cell is a crowded environment in which proteins and other large molecules constantly collide,
interact and drift away unless they meet a very specific, complementary partner.
In order to understand, describe and eventually predict the dynamics and kinetics of the
formation of molecular complexes, one needs to be able to calculate the forces between
large biomolecules in a fast but accurate way.
We have developed a novel formulation of electrostatics specifically suited for applications
to biomolecular systems.
The formulation allows one to correctly account for the effects arising due to the presence of water,
while remaining computationally efficient.
Representative publications
1. Obolensky OI, Doerr TP, Ray R, Yu YK (2009) Rigorous treatment of electrostatics for spatially varying dielectrics based on energy minimization.
Physical Review E,
79: 041907-(1-15).
DOI: 10.1103/PhysRevE.79.041907
Mass Spectrometry (MS):
Fundamental physics for protein identification in biomedical research
In biomedical research it is often necessary to identify proteins present in a sample.
Tandem mass spectrometry (MS/MS) techniques are routinely used for this purpose.
The protein in question is digested into smaller pieces (peptides) and then these pieces
are further fragmented in mass spectrometers.
Currently, MS-based peptide identification methods rely mostly on analysis of the
positions and intensities of the peaks in mass spectra while information
about correlations between intensities of various peaks has not yet been utilized.
We expect that careful and theoretically sound analysis of the intensity profiles
will result in significant improvement in terms of robustness of computational tools
for protein/peptide identification.