Kekenes-Huskey, Peter

Owned by UKY CCS RCD
Jun 09, 2024
6 min read


Research Introduction
Defects in the contraction of muscle cells are a hallmark of contractile disease. Underlying these pathologies is the compromised performance of myofilaments, which are the key contractile components of muscle cells (myocytes). Tuning levels of free cytosolic Ca2+ or Ca2+ binding to Troponin C (TnC), a contractile protein, are prime treatment strategies for Ca2+ mismanagement in contractile diseases of cardiac, skeletal or smooth muscle. The Ca2+-sensitivity of contraction can be modulated directly by targeting TnC or secondary proteins that impact that availability of free Ca2+ , such as parvalbumin and calmodulin, through protein or small-molecule design. The direct TnC mutation approach has been shown to modulate myofilament performance, while the indirect approach of transfecting cardiomyocytes with skeletal parvalbumin, a potent Ca2+ binding protein, shortened the duration of elevated cytosolic Ca2+ during diastole and thus diminished contraction. The relatively small size of TnC, parvalbumin and similar Ca2+ -selective EF-hand proteins suggest computational protein and drug design is tractable, yet the lack of coherent models for assessing their impact on whole-cell contractility limits is a missing link in the design process. My proposed research will address this shortcoming and will yield potential drug targets for treating contractile diseases.

The first three-year phase of my research relies heavily on long duration molecular dynamics simulations of enzymes that have important roles in cardiac physiology and are potential pharmaceutical targets. Molecular dynamics simulations provide detailed time-dependent descriptions of these enzymes’ function and involve numerically integrating equations of motion between thousands of atoms representing the enzyme and its environment. These simulations often require large supercomputers running for days to months and generating terabytes of data for a single experiment. To illustrate the computational expense for a typical case, I provide scaling estimates for a small protein (Troponin C). This protein consists of roughly 70,000 atoms (protein plus surrounding water molecules) and in previous studies we have shown that 150 nanosecond (ns) simulations provide useful quantitative insight into the protein's ability to bind its substrate (calcium). Benchmarks using facilities I regularly use that are comparable to the UK DLX cluster indicate 128 computer cores will yield 20 ns of simulation data per day. For one experiment that compares simulations of the calcium free and calcium bound enzyme, just under 50,000 supercomputing hours (SUs=number of cores * hours of use) are needed. My initial studies aim to understand functional differences across a class of enzymes and mutations, which I project will require more than 25 calcium bound/calcium free simulations at a cost of 1.25 million SUs. Based on the 512 core limit at DLX, completion of this experiment would require about 100 days of continuous operation, assuming no delays in execution due to crowded job queues or downtime due to maintenance.

Overall, my program of research will involve very extensive calculations such as those mentioned above, and I will apply to national supercomputer centers for support of the large calculations. But calculations of the scale of the troponin-C work are not considered large enough for national facilities; access to local facilities is essential for these calculations and for local analysis of data gathered from the national centers. Access to a minor allocation on DLX would be ideal this purpose and could further accelerate my research.

Simulations of calcium binding proteins

Understanding the kinetics, energetics and signaling of calcium binding proteins through simulation.

Personnel

PI: Pete Kekenes-Huskey

Students

Postdoc: Fumie Sunahori
Postdoc: Caitlin Scott
Undergraduate: Amir N Kucharski, Jr.
Postdoc: Selcuk Atalay

Graduate:Tom Pace

Software

Amber, NAMD, FEniCS_dolfin (open source)

Collaborators

None

Publications

https://www.ncbi.nlm.nih.gov/pubmed

  1. Increasing Salt Rejection of Polybenzimidazole Nanofiltration Membranes via the Addition of Immobilized and Aligned Aquaporins. Wagh P, Zhang X, Blood R, Kekenes-Huskey PM, Rajapaksha P, Wei Y, Escobar IC. Processes (Basel). 2019 Feb;7(2). pii: 76. doi: 10.3390/pr7020076. Epub 2019 Feb 3.
  2. A Matched-Filter-Based Algorithm for Subcellular Classification of T-System in Cardiac Tissues. Colli DF, Blood SR, Sankarankutty AC, Sachse FB, Frisk M, Louch WE, Kekenes-Huskey PM. Biophys J. 2019 Apr 23;116(8):1386-1393. doi: 10.1016/j.bpj.2019.03.010. Epub 2019 Mar 22.
  3. Thermodynamics of Cation Binding to the Sarcoendoplasmic Reticulum Calcium ATPase Pump and Impacts on Enzyme Function. Sun B, Stewart BD, Kucharski AN, Kekenes-Huskey PM. J Chem Theory Comput. 2019 Apr 9;15(4):2692-2705. doi: 10.1021/acs.jctc.8b01312. Epub 2019 Mar 13.
  4. Simulation of P2X-mediated calcium signalling in microglia. Chun BJ, Stewart BD, Vaughan DD, Bachstetter AD, Kekenes-Huskey PM. J Physiol. 2019 Feb;597(3):799-818. doi: 10.1113/JP277377. Epub 2018 Dec 17. 
  5. 3D dSTORM imaging reveals novel detail of ryanodine receptor localization in rat cardiac myocytes. Shen X, van den Brink J, Hou Y, Colli D, Le C, Kolstad TR, MacQuaide N, Carlson CR, Kekenes-Huskey PM, Edwards AG, Soeller C, Louch WE. J Physiol. 2019 Jan;597(2):399-418. doi: 10.1113/JP277360. Epub 2018 Nov 28. 
  6. Electrostatic control of calcineurin's intrinsically-disordered regulatory domain binding to calmodulin. Sun B, Cook EC, Creamer TP, Kekenes-Huskey PM. Biochim Biophys Acta Gen Subj. 2018 Dec;1862(12):2651-2659. doi: 10.1016/j.bbagen.2018.07.027. Epub 2018 Jul 31. 
  7. Computational modeling of amylin-induced calcium dysregulation in rat ventricular cardiomyocytes. Stewart BD, Scott CE, McCoy TP, Yin G, Despa F, Despa S, Kekenes-Huskey PM. Cell Calcium. 2018 May;71:65-74. doi: 10.1016/j.ceca.2017.11.006. Epub 2017 Dec 8. 
  8. Myofilament Calcium Sensitivity: Consequences of the Effective Concentration of Troponin I. Siddiqui JK, Tikunova SB, Walton SD, Liu B, Meyer M, de Tombe PP, Neilson N, Kekenes-Huskey PM, Salhi HE, Janssen PM, Biesiadecki BJ, Davis JP. Front Physiol. 2016 Dec 21;7:632. doi: 10.3389/fphys.2016.00632. eCollection 2016. 
  9. Quantifying the Influence of the Crowded Cytoplasm on Small Molecule Diffusion. Kekenes-Huskey PM, Scott CE, Atalay S. J Phys Chem B. 2016 Aug 25;120(33):8696-706. doi: 10.1021/acs.jpcb.6b03887. Epub 2016 Jul 7. 
  10. Understanding Ion Binding Affinity and Selectivity in β-Parvalbumin Using Molecular Dynamics and Mean Spherical Approximation Theory. Kucharski AN, Scott CE, Davis JP, Kekenes-Huskey PM. J Phys Chem B. 2016 Aug 25;120(33):8617-30. doi: 10.1021/acs.jpcb.6b02666. Epub 2016 Jul. 
  11. Molecular Basis of S100A1 Activation at Saturating and Subsaturating Calcium Concentrations. Scott CE, Kekenes-Huskey PM. Biophys J. 2016 Apr 26;110(8):1907. doi: 10.1016/j.bpj.2016.03.032. Epub 2016 Apr 26. No abstract available. 
  12. Molecular Basis of S100A1 Activation at Saturating and Subsaturating Calcium Concentrations. Scott CE, Kekenes-Huskey PM. Biophys J. 2016 Mar 8;110(5):1052-63. doi: 10.1016/j.bpj.2015.12.040. Erratum in: Biophys J. 2016 Apr 26;110(8):1907. 
  13. Computational modeling of subcellular transport and signaling. Hake J, Kekenes-Huskey PM, McCulloch AD. Curr Opin Struct Biol. 2014 Apr;25:92-7. doi: 10.1016/j.sbi.2014.01.006. Epub 2014 Feb 7. Review. PMID: 24509246 Free PMC Article
  14. Multi-core CPU or GPU-accelerated Multiscale Modeling for Biomolecular Complexes. Liao T, Zhang Y, Kekenes-Huskey PM, Cheng Y, Michailova A, McCulloch AD, Holst M, McCammon JA. Mol Based Math Biol. 2013 Jul;1. doi: 10.2478/mlbmb-2013-0009.
  15. Molecular and subcellular-scale modeling of nucleotide diffusion in the cardiac myofilament lattice. Kekenes-Huskey PM, Liao T, Gillette AK, Hake JE, Zhang Y, Michailova AP, McCulloch AD, McCammon JA. Biophys J. 2013 Nov 5;105(9):2130-40. doi: 10.1016/j.bpj.2013.09.020.
  16. Influence of neighboring reactive particles on diffusion-limited reactions. Eun C, Kekenes-Huskey PM, McCammon JA. J Chem Phys. 2013 Jul 28;139(4):044117. doi: 10.1063/1.4816522.
  17. Multi-Scale Continuum Modeling of Biological Processes: From Molecular Electro-Diffusion to Sub-Cellular Signaling Transduction. Cheng Y, Kekenes-Huskey P, Hake J, Holst M, McCammon J, Michailova A. Comput Sci Discov. 2012 Mar 20;5(1). pii: 015002.
  18. Finite Element Estimation of Protein-Ligand Association Rates with Post-Encounter Effects: Applications to Calcium binding in Troponin C and SERCA. Kekenes-Huskey PM, Gillette A, Hake J, McCammon JA. Comput Sci Discov. 2012 Oct 31;5. pii: 014015.
  19. Molecular basis of calcium-sensitizing and desensitizing mutations of the human cardiac troponin C regulatory domain: a multi-scale simulation study. Kekenes-Huskey PM, Lindert S, McCammon JA. PLoS Comput Biol. 2012;8(11):e1002777. doi: 10.1371/journal.pcbi.1002777. Epub 2012 Nov 29.
  20. Long-timescale molecular dynamics simulations elucidate the dynamics and kinetics of exposure of the hydrophobic patch in troponin C. Lindert S, Kekenes-Huskey PM, McCammon JA. Biophys J. 2012 Oct 17;103(8):1784-9. doi: 10.1016/j.bpj.2012.08.058. Epub 2012 Oct 16.
  21. Modeling effects of L-type ca(2+) current and na(+)-ca(2+) exchanger on ca(2+) trigger flux in rabbit myocytes with realistic T-tubule geometries. Kekenes-Huskey PM, Cheng Y, Hake JE, Sachse FB, Bridge JH, Holst MJ, McCammon JA, McCulloch AD, Michailova AP. Front Physiol. 2012 Sep 10;3:351. doi: 10.3389/fphys.2012.00351. eCollection 2012.
  22. Calcium binding and allosteric signaling mechanisms for the sarcoplasmic reticulum Ca²+ ATPase. Kekenes-Huskey PM, Metzger VT, Grant BJ, Andrew McCammon J. Protein Sci. 2012 Oct;21(10):1429-43. doi: 10.1002/pro.2129.
  23. Modelling cardiac calcium sparks in a three-dimensional reconstruction of a calcium release unit. Hake J, Edwards AG, Yu Z, Kekenes-Huskey PM, Michailova AP, McCammon JA, Holst MJ, Hoshijima M, McCulloch AD. J Physiol. 2012 Sep 15;590(18):4403-22. doi: 0.1113/jphysiol.2012.227926. Epub 2012 Apr 10.
  24. Dynamics and calcium association to the N-terminal regulatory domain of human cardiac troponin C: a multiscale computational study. Lindert S, Kekenes-Huskey PM, Huber G, Pierce L, McCammon JA. J Phys Chem B. 2012 Jul 26;116(29):8449-59. doi: 10.1021/jp212173f. Epub 2012 Feb 14.
  25. Prediction of the 3D structure of FMRF-amide neuropeptides bound to the mouse MrgC11 GPCR and experimental validation. Heo J, Han SK, Vaidehi N, Wendel J, Kekenes-Huskey P, Goddard WA 3rd. Chembiochem. 2007 Sep 3;8(13):1527-39.
  26. Unimolecular rate constants for HX or DX elimination (X = F, Cl) from chemically activated CF3CH2CH2Cl, C2H5CH2Cl, and C2D5CH2Cl: threshold energies for HF and HCl elimination. Ferguson JD, Johnson NL, Kekenes-Huskey PM, Everett WC, Heard GL, Setser DW, Holmes BE. J Phys Chem A. 2005 May 26;109(20):4540-51.
  27. A molecular docking study of estrogenically active compounds with 1,2-diarylethane and 1,2-diarylethene pharmacophores. Kekenes-Huskey PM, Muegge I, von Rauch M, Gust R, Knapp EW. Bioorg Med Chem. 2004 Dec 15;12(24):6527-37.
  28. The MPSim-Dock hierarchical docking algorithm: application to the eight trypsin inhibitor cocrystals. Cho AE, Wendel JA, Vaidehi N, Kekenes-Huskey PM, Floriano WB, Maiti PK, Goddard WA 3rd. J Comput Chem. 2005 Jan 15;26(1):48-71.

Grants

Center for Computational Sciences