Background:

• Research Associate, Massachusetts Institute of Technology, 1970-75
• Alfred P. Sloan Research Fellow, 1980-82
• NATO Fellow, 1982
• Guggenheim Fellow, 1990

At The Center for Cell and Virus Theory mathematical and computational models of physical and chemical processes underlying cell and virus behavior are being developed. The challenge of understanding the workings of life on multi-, single- and sub-cellular scales is being addressed. The interdisciplinary approach integrates methods from biochemistry, bioinformatics, bionanotechnology, chemical kinetics, computational sciences, mathematics, physics, quantum chemistry, statistical mechanics, and systems biology. Research is carried out collaboratively with bacteriaologists, cancer biologists, geoscientists, nanotechnologists, and virologists at Indiana University and other institutions. For more information please visit our Web site at http://sysbio.indiana.edu/.

Karyote®: a genomic, proteomic, metabolic cell simulator
A quantitative model, Karyote, of the behavior of a cell and its response to chemical disturbances in the extra-cellular medium, gene deletion/mutation, and the presence of other cells, is being developed. Karyote is based on the numerical solution of a set of reaction and transport ordinary differential equations. Karyote predictions reflect the nonlinear dynamics of the cell reaction-transport system. Karyote is being integrated with genomic, proteomic, metabolic and other experimental data through our novel information theory approach. The result will be an automated procedure for tailoring Karyote to a given cell type. Karyote has great potential for accelerating drug discovery, optimizing treatment regimes, testing concepts in cloning and designing microbes for biotechnical and environmental remediation activities. Please visit our Karyote Web site at http://sysbio.indiana.edu/karyote/.

Cell3-D: a multi-dimensional simulator
The simulator, Cell3-D, predicts the spatio-temporal dynamics of a cell, capturing the evolving gradients of molecular species within each of its compartments. Cell3-D is based on the numerical solution of equations of reaction and transport in the cell interior and along its membrane. The distinction between bulk species and those adsorbed at membranes or on fibrils is accounted for by solving equations in 1- or 2- dimensions. This multiple spatial dimensional character of Cell3-D allows it to capture the complexity of intra-cellular structure. Cell3-D has been applied to the oscillatory dynamics of Min proteins in E. coli and the segregation of daughter chromosomes following bacterial division.

NanoX ®: a multiscale bionanosystem simulator
A quantitative model of the structure and dynamics of a bionanosystem (BNS) is being developed for fundamental and health sciences research. All-atom simulations have played an important role in molecular research. However, the large number of atoms in a BNS and its immediate surroundings render these approaches unfeasible. We have developed and implemented all-atom multiscale techniques that start with a multiscale analysis of the Liouville equation and yield stochastic equations for the order parameters describing overall features of the bionanosystem. In this way, NanoX simultaneously accounts for atomic-scale processes and self-assembly or overall structural transitions to simulate these many-atom systems (Fig.1). NanoX is being used to study the assembly and stability of partial and whole viruses, the design of nanocapsules for delivery of therapeutic agents, the design of nanotechnical devices, and the computer-aided design of antiviral vaccines and drugs. Please visit our NanoX Web site at http://sysbio.indiana.edu/nanox/.

Fig. 1 (a) Crystal structure of a CCMV protomer with its three quasi-threefold related
subunits colored in blue (A), red (B) and green (C). (b) Native CCMV capsid organized
in 12 pentameric and 20 hexameric capsomers with 5 blue (A) subunits in each pentamer and 3 red (B) and 3 green (C) subunits in each hexamer. (c) The swollen CCMV capsid generated computationally by rigid-body translations and rotations of the pentamers and hexamers.

 

Selected Publications:

Ortoleva, P. 1992. Nonlinear Chemical Waves. Chichester : John Wiley and Sons, 1992, 302 pp.

Ortoleva, P. 1994. Geochemical Self-Organization. Oxford University Press, 1994, 411 pp.

Tuncay, K. and P. Ortoleva. 2004. Quantitative basin modeling: present state and developments toward predictability, Geofluids, Volume 4, Number 1, 23-39.

Jaqaman, K., K. Tuncay and P. Ortoleva. 2004. Classical density functional theory of orientation order at interfaces: Application to water, J. Chem. Phys. Vol. 120 (2): 926-938.

Navid, A. and P. Ortoleva. 2004. Simulated complex dynamics of glycolysis in the protozoan parasite Trypanosoma brucei . J. Theor. Biol. 228(4), 449-458.

Jarymowycz, L. and P. Ortoleva. 2006. Involatile nanodroplets:  An asymptotic analysis. J. Chem. Phys. Vol. 124: 234705. 4 pp.

Miao, Y. and P. Ortoleva. 2006b. Viral structural transitions: An all-atom multiscale theory. J. Chem. Phys . 125, 214901.

Sheen, D-H., K. Tuncay, C-E. Bang, and P. Ortoleva. 2006. Parallel implementation of a velocity-stress staggered-grid finite-difference method for 2-D poroelastic wave propagation. Computers and Geosciences , Vol. 32, iss. 8, p. 1182-1191.

Sayyed-Ahmad, A., K. Tuncay and P. Ortoleva. 2007. Transcriptional Regulatory Network Refinement and Quantification Through Kinetic Modeling, Gene Expression Microarray Data and Information Theory. BMC Bioinformatics, 8:20, doi:10.1186/1471-2105-8-20.

Qu, K., A.E. Abi Haidar, J. Fan, D. Basu, G. Lin, L. Ensman, M. Jolly, P. Ortoleva. 2007. Cancer Onset and Progression: A Genome-Wide, Nonlinear Dynamical Systems Perspective on Onconetworks. J. Theoret. Bio.   May 21;246(2):234

Comer, J. and P. Ortoleva. 2007. Coexistence of Twisted and Untwisted Crystals : An Impurity/Structural Order Model with Implications for Agate Patterns. American Mineralogist .  Vol. 92, p. 1952–1957.

Fan, J., K. Tuncay and P. Ortoleva. 2007. Chromosome Segregation in E. coli Division: A Free Energy-Driven String Model . J. Comp. Bio. and Chem. 31:257-264

Qu, K., and P. Ortoleva. 2007. Understanding Stem Cell Differentiation through Self-Organization Theory. J. Theoret. Bio. (in press).

Sayyed-Ahmad, A., Y. Miao, and P. Ortoleva. 2008. Poisson-Boltzmann Theory of Bionanosystems. Commun. Comp. Phys . , 3, pp. 1100-1116.

Iyengar, S. S. and P. Ortoleva. 2007. Multiscale Theory of Collective and Single-Particle Modes in Quantum Nanosystem. J. Chem. Phys. (in press).

Miao, Y. and P. Ortoleva (2008). Molecular Dynamics/Order Parameter eXtrapolation (MD/OPX) for Bionanosystem Simulations. J. Comp. Chem. (in press).

Pankavich, S., Y. Miao, J. Ortoleva, Z. Shreif, and P. Ortoleva. 2008. Stochastic dynamics of bionanosystems: Multi-scale analysis and specialized ensembles. J. Chem. Phys. (in press).

Shreif, Z. and P. Ortoleva. 2008. Computer-Aided Design of Nanocapsules for Therapeutic Delivery. Comp. Math. Methods in Med. (accepted).