Ramu Anandakrishnan

Postdoctoral Research Associate, Department of Computer Science, Virginia Tech, Blacksburg, VA
E-mail: ramu@vt.edu

EDUCATION

Ph.D., Computer Science, Virginia Tech, Blacksburg, VA, 2011
M.B.A., Finance, University of Maryland, College Park, MD, 1979
B.Tech, Mechanical Engineering, Indian Institute of Technology, Kanpur, India, 1977

EXPERIENCE

Postdoctoral Research Associate, Virginia Tech, 2012-present
Research Assistant, Virginia Tech, 2006-2011
Partner, Accenture, 1997-2006
Director, Computer Sciences Corp., 1988-1997
Software Consultant/Partner, Meta Systems, 1982-1987
Systems Programmer, U.S. Chamber of Commerce, 1979-1982

RESEARCH INTEREST

Biomolecular electrostatics
Long range electrostatic interactions determine the structure, function and activity of biological molecules -- proteins, DNA and RNA. Molecular dynamics simulations are routinely used to study biological molecules. However, due to the computational cost of calculating electrostatic interactions, O(N²), it is not possible to simulate realistic biomolecular systems (tens to hundreds of thousand atoms) at the atomic level for useful timescales (microseconds to seconds), even with today's fastest supercomputers. My research goal is to develop methods for speeding up the computation of electrostatic interactions without significantly sacrificing accuracy, and applying these methods to practical biological problems.

One such method is the O(N log N) hierarchical charge partitioning (HCP) approximation, that is based on the natural organization of biomolecules into multiple hierarchical levels of components as shown below. The HCP approximates the charge distribution of these components with a small number of point charges which are then used in the computation of long range electrostatic interactions.

PUBLICATIONS

Ramu Anandakrishnan, Alex Drozdetski, Ross C Walker and Alexey V. Onufriev. Speed of conformational change: comparing explicit and implicit solvent molecular dynamics.
Biophysical Journal, 108(5), 1153-1164, 2015.

Saeed Izadi, Ramu Anandakrishnan and Alexey V. Onufriev. Building water models: a different approach.
Journal of Physical Chemistry Letters, 5(21), 3863-3871, 2014.

Ramu Anandakrishnan, Charles Baker, Saeed Izadi and Alexey V. Onufriev. Point Charges Optimally Placed to Represent the Multipole Expansion of Charge Distributions.
PLoS ONE, 8(7), e67715, 2013.

Ramu Anandakrishnan. A Partition Function Approximation Using Elementary Symmetric Functions.
PLoS ONE, 7(12), e51352, 2012.

Ramu Anandakrishnan, Boris Aguilar and Alexey V. Onufriev. H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulation.
Nucleic Acids Research, 40(W1), W537-W541, 2012.

Ramu Anandakrishnan, Mayank Daga and Alexey V. Onufriev. An n log n Generalized Born Approximation.
Journal of Chemical Theory and Computation, 7(3), 544-559, 2011.

Ramu Anandakrishnan, Tom Scogland, Andrew Fenley, John Gordon, Wu Feng and Alexey V. Onufriev. Accelerating Electrostatic Surface Potential Calculation with Multiscale Approximation on Graphics Processing Units.
Journal of Molecular Graphics and Modelling, 28(8), 904-910, 2010.

Andrew S Warren, Ramu Anandakrishnan and Liqing Zhang. Functional bias in molecular evolution rate of Arabidopsis thaliana.
BMC Evolutionary Biology, 10:125, 2010.

Boris Aguilar, Ramu Anandakrishnan, Jory Z. Ruscio, and Alexey V. Onufriev. Statistics and Physical Origins of pK and Ionization State Changes upon Protein-Ligand Binding.
Biophysical journal, 98(5), 872-880, 2010.

Ramu Anandakrishnan and Alexey V. Onufriev. An N log N approximation based on the natural organization of biomolecules for speeding up the computation of long range interactions.
Journal of Computational Chemistry, 31(4), 691–706, 2010.

Ramu Anandakrishnan and Alexey V. Onufriev. Analysis of basic clustering algorithms for numerical estimation of statistical averages in biomolecules.
Journal of Computational Biology, 15, 165-184, 2008.