Alexei A. Podtelezhnikov

Curriculum Vitæ
622 6th St
Lake Linden MI 49945		 aapodtel­@­mtu­·­edu (906)296÷2017
(906)370÷8103

Research Interests: Structural Bioinformatics, Machine Learning and Data Mining, Proteomics, Multiscale Simulations of Proteins and DNA, Computational Biophysics and Biochemistry, Molecular Modeling, Drug Discovery

Teaching Interests: Numerical and Computational Methods in Biophysics and Biochemistry, Statistical Methods, Advanced Monte Carlo Methods, Bioinformatics, Proteomics

Research Experience:
Michigan Technological University

Houghton, MI
08/2007-present 		Visiting Assistant Professor — Department of Physics
  • Protein structure prediction using knowledge-based potentials
  • Machine learning of interactions in biological systems
  • Physical interpretation of biological data mining
  • Polymer conformation sampling with efficient Monte Carlo
Keck Graduate Institute of Applied Life Sciences

Claremont, CA
11/2003-06/2007 		Postdoctoral Fellow — Wild Research Group
  • Knowledge-based protein structure prediction
  • Machine learning of hydrogen bonding and other protein interactions
  • Data mining of domain sequences and their secondary structures
  • Efficient Monte Carlo sampling of peptide conformations
Howard Hughes Medical Institute (University of California, San Diego)

San Diego, CA
11/2000-11/2003 		Research Associate — McCammon Research Group
  • Modeling tetrameric HIV-1 integrase complex with DNA
  • Hydrodynamics and electrostatics of HIV-1 integrase
  • Docking of small ligands to smallpox topoisomerase
  • Brownian dynamics of ligand binding to acetylcholinesterase
New York University, Department of Chemistry

New York, NY
09/1995-10/2000 		Graduate Assistant — Vologodskii Research Group
  • Brownian dynamics simulations of polymer cyclization kinetics
  • Efficient Monte Carlo estimation of DNA cyclization probability
  • Supercoiling and knotting of long DNA molecules
  • Non-equilibrium DNA properties during transcription
Institute of Molecular Genetics of Russian Academy of Science

Moscow, Russia
09/1991-08/1995 		Intern — Frank-Kamenetskii Research Group
  • Brownian dynamics simulations of diffusional polymer cyclization
  • Alignment of DNA images for Electron Microscopy mapping
  • Electron microscopy of specific DNA-ligand binding
Education New York University
Ph.D. in Biomolecular Chemistry (2000),
Dissertation: Kinetics and thermodynamics of DNA cyclization.
Moscow Institute of Physics and Technology
M.S. in Molecular Biophysics (1994) and
B.S. in Applied Physics and Mathematics (1992),
Thesis: Testing the quality of electron microscope mapping data for DNA molecules with sequence-specific ligands.
Teaching
Experience 		Visiting Assistant Professor — Michigan Technological University (2007-present)
  • Teaching and grading Introduction to Solid State Physics, Statistical Mechanics
  • Supervising a senior project for a Physics-major student
Graduate Supervisor — University of California, San Diego (2002-2003)
  • Guided a graduate student project on solution and visualization of Poisson-Boltzmann equation for small molecule docking studies.
Teaching Assistant — New York University (1995-2000)
  • Instructed laboratory and recitation sessions for College Chemistry I and II. Graded exams, homeworks, and laboratory reports.
Awards
and Honors
  • Participant in the NSF-funded Proteomics program, IPAM UCLA (2004).
  • M.S. diploma with excellence, cum laude (1994).
Additional
Skills
  • Statistical methods and numerical methods
  • C/C++ and Fortran programming
  • Cluster parallel programming with MPI
  • Matlab, Insight II, VMD, APBS, OpenDX, SPSS SigmaPlot
  • Linux, UNIX, and Windows environment
References
  • David L. Wild, Ph.D., Molecular Biophysics, University of Oxford; Professor, Warwick Systems Biology Centre, University of Warwick.
  • J. Andrew McCammon, Ph.D., Chemical Physics, Harvard University; Investigator, Howard Hughes Medical Institute; Joseph E. Mayer Professor of Theoretical Chemistry, Professor of Pharmacology, UCSD.
  • Alexander V. Vologodskii, Ph.D., Moscow Institute of Physics and Technology, D.S., Moscow State University; Research Professor, Department of Chemistry, NYU.
  • Frederic D. Bushman, Ph.D., Cellular and Developmental Biology, Harvard University; Professor, Department of Microbiology, University of Pennsylvania School of Medicine.
  • Zoubin Ghahramani, Ph.D., Cognitive Neuroscience, Massachusetts Institute of Technology; Professor in Information Engineering, University of Cambridge.
(Contact information is available upon request)

Research Grant Proposals

  1. Multi-dimensional Monte Carlo approach to protein structure prediction. To be submitted to NSF.
  2. Development of alternative knowledge-based potentials for protein modeling and drug discovery using modern machine learning techniques. To be submitted to NIH.

In progress

  1. A. A. Podtelezhnikov and J. A. McCammon. Electrostatic properties of tetrameric HIV-1 integrase complex with DNA, in preparation (2008)
  2. A. A. Podtelezhnikov et al. Geometrically constrained sampling of protein conformations in the space of contact maps, in preparation (2008).
  3. A. A. Podtelezhnikov et al. Sequence foldability analysis in the space of geometrically constrained contact maps, in preparation (2007).
  4. A. A. Podtelezhnikov and D. L. Wild. Optimized computation of bond and dihedral angles, in preparation (2007).

Publications

  1. A. A. Podtelezhnikov and D. L. Wild. CRANKITE : A Fast Polypeptide Backbone Conformation Sampler, submitted to SCFBM (2008).
  2. A. A. Podtelezhnikov, N. T. Amin, R. B. Freedman, D. L. Wild. Reconstruction of All-Atom Protein Backbone Conformation from Regularized Contact Maps, submitted to Proteins (2008).
  3. A. A. Podtelezhnikov, Z. Ghahramani, D. L. Wild. Learning about protein hydrogen bonding by minimizing contrastive divergence, Proteins 66, 588-599 (2007).
  4. W. Chu, Z. Ghahramani, A. Podtelezhnikov, D. L. Wild. Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction, IEEE/ACM Trans. Comp. Biol. Bioinformatics 3, 98-113 (2006).
  5. A. A. Podtelezhnikov and D. L. Wild. Exhaustive Metropolis Monte Carlo sampling and analysis of polyalanine conformations adopted under the influence of hydrogen bonds, Proteins 61, 94-104 (2005).
  6. A. A. Podtelezhnikov, K. Gao, F. D. Bushman and J. A. McCammon. Modeling HIV-1 integrase complexes based on their hydrodynamic properties, Biopolymers 68, 110-120 (2003).
  7. A. V. Vologodskii, W. T. Zhang, V. V. Rybenkov, A. A. Podtelezhnikov, D. Subramanian, J. D. Griffith, N. R. Cozzarelli. Mechanism of topology simplification by type II DNA topoisomerases, Proc. Natl. Acad. Sci. U.S.A. 98, 3045-3049 (2001).
  8. A. A. Podtelezhnikov, C. Mao, N. C. Seeman and A. V. Vologodskii. Multimerization-cyclization of DNA fragments as a method of conformational analysis, Biophysical Journal 79, 2692-2704 (2000).
  9. A. A. Podtelezhnikov and A. V. Vologodskii. Dynamics of small loops in DNA molecules, Macromolecules 33, 2767-2771 (2000).
  10. A. A. Podtelezhnikov, N. R. Cozzarelli and A. V. Vologodskii. Equilibrium distributions of topological states in circular DNA: interplay of supercoiling and knotting, Proc. Natl. Acad. Sci. U.S.A. 96, 12974-12979 (1999).
  11. A. S. Krasilnikov, A. Podtelezhnikov, A. Vologodskii and S. M. Mirkin. Large-scale effects of transcriptional DNA supercoiling in vivo, J. Mol. Biol. 292, 1149-1160 (1999).
  12. A. A. Podtelezhnikov and A. V. Vologodskii. Simulations of polymer cyclization by Brownian Dynamics, Macromolecules 30, 6668-6673 (1997).
  13. A. A. Podtelezhnikov, A. V. Kurakin, A. V. Vologodskii and D. I. Cherny. Testing the quality of electron microscope mapping data for DNA molecules with sequence-specific ligands, Micron 25, 439-446 (1994).

Invited Presentations

  1. A. A. Podtelezhnikov. Learning about Protein Energetics by Minimizing Contrastive Divergence. Machine learning in Structural Bioinformatics, Copenhagen Denmark, April 2008.
  2. A. A. Podtelezhnikov. Polypeptide sampling, protein structure prediction, and contrastive divergence, presented at Proteomics Reunion Conference IPAM, Lake Arrowhead CA, December 2005.
  3. A. A. Podtelezhnikov. Polypeptide sampling, knowledge-based potentials, and protein structure prediction, presented at Gatsby Computational Neuroscience Unit UCL, London UK, October 2005.
  4. A. A. Podtelezhnikov. Molecular dynamics vs Brownian dynamics vs Monte Carlo methods: pros and cons, presented at Proteomics Culminating Conference IPAM, Lake Arrowhead CA, June 2004.

Conference Abstracts

  1. A. A. Podtelezhnikov, Z. Ghahramani, D. L. Wild. Learning about hydrogen bonding by minimizing contrastive divergence. An Isaac Newton Institute Workshop, Camdridge UK, October 30 - November 3, 2006.
  2. A. A. Podtelezhnikov, Z. Ghahramani, D. L. Wild. Contrastive divergence learning of hydrogen bonding and side-chain interactions in proteins using Metropolis Monte Carlo. An Isaac Newton Institute Workshop, Camdridge UK, December 11 - December 15, 2006.
  3. A. A. Podtelezhnikov, K. Gui, F. Bushman, J. A. McCammon. Modeling HIV-1 integrase complexes based on their electrostatic and hydrodynamic properties. Protein Science 11 (Suppl. 1): A541-A541 (2002) — 16th Symposium of the Protein Society, San Diego CA, August 17-21, 2002.
  4. A. Podtelezhnikov and A. Vologodskii. Thermodynamics and kinetics of DNA loop formation studied by computer simulations. Biophysical Journal 76 (1): A316-A316 Part 2 (1999) — 43rd Annual Biophysical Society Meeting, Baltimore MD, February 13-17, 1999.
  5. A. A. Podtelezhnikov and A. V. Vologodskii. Analysis of multimerization-cyclization of short bent DNA fragments. Efficient method of calculation of J-factors. — Gordon Research Conference on Biopolymers, Newport RI, June 14-19, 1998.
  6. A. A. Podtelezhnikov and A. V. Vologodskii. Structural interpretation of the cyclization kinetics of bent DNA fragments. 1. Extraction of the J-factor. Biophysical Journal 74 (2): A287-A287 Part 2 (1998) — 42nd Annual Biophysical Society Meeting, Kansas City MO, February 22-26, 1998.
  7. A. Podtelezhnikov and A. Vologodskii. Simulations of DNA Cyclization by Brownian Dynamics. J. Biomol Struct. Dyn. (1997) — 10th Conversation in the Discipline Biomolecular Stereodynamics, Albany NY, June 17-21, 1997.