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Jack Tuszynski
          Cross Cancer Institute
           Edmonton, Alberta



Mathematical Modelling and Pharmaceutical
              Development
*Rebuilding a Research Team*
             Torin Huzil, PhD
            Vahid Rezania, PhD
          Avner Priel, PhD-Israel
      Przemek Chelminiak, PhD-UK
             Linda Payet, PhD
        Rebeccah Marsh, M.Sc.-US
           Eric Carpenter, B.Sc.
           Melissa Gajewski, BSc
             Evan Kelly, BSc
           Travis Craddock, BSc
         Tyler Luchko, B.Sc. Hon.
          Kristy Beinert, student
          Joseph Hajduk, student
Standard Cancer Treatment Modalities:


         Radiation therapy
         Chemotherapy
         Surgery
         Gene Therapy
Our Premise:
computational modeling of cancer processes
and treatments can help find new
chemotherapy compounds and guide clinical
delivery of treatments to improve cure rates
Key Objectives:

 Develop large-scale computational modeling of
cancer processes and treatments

 Find effective chemotherapy compounds (new and
repurposed) and modalities of their clinical delivery to
improve cure rates

 Experiment with novel techniques of attacking
cancer cells
Microtubules and Cancer
One of the critical components of cell division are the
  microtubules. We selectively target microtubules,
 disrupting cell division, thereby killing dividing cells.

The presence of several
human tubulin isoforms
provides us with a unique
platform on which to
develop drugs that have
increased specificities for
those expressed in
cancerous cells.
Understanding Microtubules
Microtubules
Zeroing in on the target
Simulating Microtubules
Tubulin Structure
          basic unit is dimer, two
          protein chains
          each chain is linked
          amino acids
          chain has compact,
          folded form
          backbone shows chain
          structure
Protein Backbone Structure
Two common forms

• α-helix
  helical backbone

• β-sheet
  straight, parallel
  backbone sections
Different Sequences—
 Different Properties
           sequences differ in
             shape
           • chemistry
           • movement

           tubulins differ
           • human isotypes
           • between species
Spatial Fitting of Drugs

Utilizes the visual
inspection of a         Target
binding site within a
target, followed by
the modification of a
drug to produce
better binding to the
target.
Binding pockets for colchicine and
            taxanes



                      docetaxel


 colchicine
              paclitaxel
Paclitaxel from the Pacific Yew
Colchicine from Autumn Crocus
Vinca alkaloids from periwinkle
Known tubulin inhibitors are not
         isotype specific
     -hence side effects…but:
“Conceivably, if one knew the tubulin isotype and
  microtubule regulatory protein composition of a
  specific tumor cell, one could design or choose drugs to
  selectively target that tumor”

Jordan and Wilson, Nature Reviews Cancer, 2004
Tubulin Amino Acids Involved in
        Colchicine Binding
  class I       EPYNATLSVH QLVENTDETYCIDNEALYDICFRTLKLTTPTY G DLNHLVSATM S G VTTCL 240
  class II      EPYNATLSVH HLVENTDETYSIDNEALYDICFRTLKLTTPTY G DLNHLVSATM S G VTTCL 240
  class II
         I      EPYNATLSIHQLVENTDETYCIDNEALYDICFRTLKLATPTY G DLNHLVSATM S G VTTSL 240
   class VI      EPYNAVLSIHQLIENAD A CFCIDNEALYDICFRTLKLTTPTY G DLN HLVSLTM S GITTSL 240
                              * * * * : : : * * :* * * * * * * * * * * * * * * * : * *
                               * *.****: .* * * * * * *.* * * * * * :**.

 class I      RFPG Q LNA DLRKLAV N M VPFPRLHFF MP GFAPLTSRG S Q Q Y R ALTVPELTQ Q VFDA K N M M 300
 class II     RFPG Q LNA DLRKLAV N M VPFPRLHFF MP GFAPLTSRG S Q Q Y R ALTVPELTQ Q M F D SK N M M 300
class II
       I      RFPG Q LNA DLRKLAVN M VPFPRLHFF MP GFAPLTARG S Q Q Y R ALTVPELTQ Q MF D A K N M M 300
class VI      RFPGQL N A DLR KLAVNM V PFPRLHFF MPGF APLTA Q G S Q Q YR ALSVAELT Q Q M F D A R N T M 300
                                * * * * * * * * * * * * * * . * * : * * *.:. * * : *: *
                                 * * * * * * * * * * * * * ** * * : * * ** ** * * * : *

class I       AACDPR H G RYLTVA AVFRG R M S M K EVDE Q M LNV Q N K NSSYFVEWIPN NV K TAVC DIPPR G 360
class II      AACDPR H G RYLTVA AIFRG R M S M K EVDE Q M LNV Q N K NSSYFVEWIPN NV K TAVC DIPPR G 360
 class II
        I     AACDPR H G RYLTVATVFRG R M S M K EVDE Q M LAIQSK N SSYFVEWIPN NV K VAVC DIPPR G 360
 class VI      AACDLRR G RYLTVACIFR G K M STKEVD Q Q LLSV QTRNSSCFVEWIPNNVKVAVC DIPPR G 360
                                * * * * * * *: * * : * : : : : * *: : * * . * * * *
                                 * : * . * * . * * * : * * * .* * * * * * * *
The Colchicine Binding Site:
     βII and βIII Tubulin
            βII                               βIII




Thr 353
          Cys 239             Val 353   Ser 239

                    Tyr 200

                                                  Arg 200
Colchicine Bound to
βII and βIII Tubulin
βII               βIII
Colchicine Derivatives that may
    Differentiate Isoforms

6 membered                              extended
aromatic ring                            methyl




                5 membered   extended
                   ring      hydroxyl
Colchicine Derivatives Bound
    to Tubulin Isoforms
    βII               βIII




          Void
Quantum Mechanical Method

A method that is applicable for calculating atomic and molecular
properties of any system without the need for parameterization

An approach that describes the dynamic distribution of electrons in
the system

Can calculate molecular geometries, transition states, spectra, etc.

A powerful method for predicting stability of molecules and
energetics of chemical reactions
Quantum Mechanical Optimization
        (An example)




Before                   After
Comparison of Molecular Mechanics and Quantum
        Mechanical Approach for Molecular Dynamics

Classical MD                                     Quantum Mechanical MD
•   Simplified description of the atomic         •   Atomic / molecular interactions are
    configurations and interactions in               calculated directly from first principles
    the system
•   Forces acting on the system are defined      •   Forces acting on the system are directly
    using fixed sets of parameters (i.e. force       calculated
    fields)
•   Computationally fast:                        •   Computationally expensive:
        thousand-million atoms                          < 500 atoms
•   Dynamic distribution of electrons in the     •   Dynamic distribution of electrons in the
    system is NOT described                          system is described

•   Difficult to model chemical bond             •   Easily handles bond making / bond
    making / bond breaking processes                 breaking
Hybrid QM/MM MD simulation



                QM
    MM
Coupling of QM and MM modeling
  QM - an active site;
       a reaction center;        Tubulin-colchicine
       solute
  MM - enzyme structure;
       explicit solvent
Our strategy:
Exquisite design of drugs for patient-specific
protein expression using clues from Mother
Nature
Chemical Synthesis
In Vitro and In Vivo Testing
Further Improvement and Refinement
Our other projects:

Ultrasound resonance
Electroporation
Magnetic field guided drug delivery
Laser-induced activation of conjugated
compounds
Microtubule hybridization
Taxane pharmacokinetics

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Microtubules in 5 minutes

  • 1. Jack Tuszynski Cross Cancer Institute Edmonton, Alberta Mathematical Modelling and Pharmaceutical Development
  • 2. *Rebuilding a Research Team* Torin Huzil, PhD Vahid Rezania, PhD Avner Priel, PhD-Israel Przemek Chelminiak, PhD-UK Linda Payet, PhD Rebeccah Marsh, M.Sc.-US Eric Carpenter, B.Sc. Melissa Gajewski, BSc Evan Kelly, BSc Travis Craddock, BSc Tyler Luchko, B.Sc. Hon. Kristy Beinert, student Joseph Hajduk, student
  • 3. Standard Cancer Treatment Modalities: Radiation therapy Chemotherapy Surgery Gene Therapy
  • 4. Our Premise: computational modeling of cancer processes and treatments can help find new chemotherapy compounds and guide clinical delivery of treatments to improve cure rates
  • 5. Key Objectives: Develop large-scale computational modeling of cancer processes and treatments Find effective chemotherapy compounds (new and repurposed) and modalities of their clinical delivery to improve cure rates Experiment with novel techniques of attacking cancer cells
  • 6. Microtubules and Cancer One of the critical components of cell division are the microtubules. We selectively target microtubules, disrupting cell division, thereby killing dividing cells. The presence of several human tubulin isoforms provides us with a unique platform on which to develop drugs that have increased specificities for those expressed in cancerous cells.
  • 9. Zeroing in on the target
  • 11. Tubulin Structure basic unit is dimer, two protein chains each chain is linked amino acids chain has compact, folded form backbone shows chain structure
  • 12. Protein Backbone Structure Two common forms • α-helix helical backbone • β-sheet straight, parallel backbone sections
  • 13. Different Sequences— Different Properties sequences differ in shape • chemistry • movement tubulins differ • human isotypes • between species
  • 14. Spatial Fitting of Drugs Utilizes the visual inspection of a Target binding site within a target, followed by the modification of a drug to produce better binding to the target.
  • 15. Binding pockets for colchicine and taxanes docetaxel colchicine paclitaxel
  • 16. Paclitaxel from the Pacific Yew
  • 18. Vinca alkaloids from periwinkle
  • 19. Known tubulin inhibitors are not isotype specific -hence side effects…but: “Conceivably, if one knew the tubulin isotype and microtubule regulatory protein composition of a specific tumor cell, one could design or choose drugs to selectively target that tumor” Jordan and Wilson, Nature Reviews Cancer, 2004
  • 20. Tubulin Amino Acids Involved in Colchicine Binding class I EPYNATLSVH QLVENTDETYCIDNEALYDICFRTLKLTTPTY G DLNHLVSATM S G VTTCL 240 class II EPYNATLSVH HLVENTDETYSIDNEALYDICFRTLKLTTPTY G DLNHLVSATM S G VTTCL 240 class II I EPYNATLSIHQLVENTDETYCIDNEALYDICFRTLKLATPTY G DLNHLVSATM S G VTTSL 240 class VI EPYNAVLSIHQLIENAD A CFCIDNEALYDICFRTLKLTTPTY G DLN HLVSLTM S GITTSL 240 * * * * : : : * * :* * * * * * * * * * * * * * * * : * * * *.****: .* * * * * * *.* * * * * * :**. class I RFPG Q LNA DLRKLAV N M VPFPRLHFF MP GFAPLTSRG S Q Q Y R ALTVPELTQ Q VFDA K N M M 300 class II RFPG Q LNA DLRKLAV N M VPFPRLHFF MP GFAPLTSRG S Q Q Y R ALTVPELTQ Q M F D SK N M M 300 class II I RFPG Q LNA DLRKLAVN M VPFPRLHFF MP GFAPLTARG S Q Q Y R ALTVPELTQ Q MF D A K N M M 300 class VI RFPGQL N A DLR KLAVNM V PFPRLHFF MPGF APLTA Q G S Q Q YR ALSVAELT Q Q M F D A R N T M 300 * * * * * * * * * * * * * * . * * : * * *.:. * * : *: * * * * * * * * * * * * * * ** * * : * * ** ** * * * : * class I AACDPR H G RYLTVA AVFRG R M S M K EVDE Q M LNV Q N K NSSYFVEWIPN NV K TAVC DIPPR G 360 class II AACDPR H G RYLTVA AIFRG R M S M K EVDE Q M LNV Q N K NSSYFVEWIPN NV K TAVC DIPPR G 360 class II I AACDPR H G RYLTVATVFRG R M S M K EVDE Q M LAIQSK N SSYFVEWIPN NV K VAVC DIPPR G 360 class VI AACDLRR G RYLTVACIFR G K M STKEVD Q Q LLSV QTRNSSCFVEWIPNNVKVAVC DIPPR G 360 * * * * * * *: * * : * : : : : * *: : * * . * * * * * : * . * * . * * * : * * * .* * * * * * * *
  • 21. The Colchicine Binding Site: βII and βIII Tubulin βII βIII Thr 353 Cys 239 Val 353 Ser 239 Tyr 200 Arg 200
  • 22. Colchicine Bound to βII and βIII Tubulin βII βIII
  • 23. Colchicine Derivatives that may Differentiate Isoforms 6 membered extended aromatic ring methyl 5 membered extended ring hydroxyl
  • 24. Colchicine Derivatives Bound to Tubulin Isoforms βII βIII Void
  • 25. Quantum Mechanical Method A method that is applicable for calculating atomic and molecular properties of any system without the need for parameterization An approach that describes the dynamic distribution of electrons in the system Can calculate molecular geometries, transition states, spectra, etc. A powerful method for predicting stability of molecules and energetics of chemical reactions
  • 26. Quantum Mechanical Optimization (An example) Before After
  • 27. Comparison of Molecular Mechanics and Quantum Mechanical Approach for Molecular Dynamics Classical MD Quantum Mechanical MD • Simplified description of the atomic • Atomic / molecular interactions are configurations and interactions in calculated directly from first principles the system • Forces acting on the system are defined • Forces acting on the system are directly using fixed sets of parameters (i.e. force calculated fields) • Computationally fast: • Computationally expensive: thousand-million atoms < 500 atoms • Dynamic distribution of electrons in the • Dynamic distribution of electrons in the system is NOT described system is described • Difficult to model chemical bond • Easily handles bond making / bond making / bond breaking processes breaking
  • 28. Hybrid QM/MM MD simulation QM MM Coupling of QM and MM modeling QM - an active site; a reaction center; Tubulin-colchicine solute MM - enzyme structure; explicit solvent
  • 29. Our strategy: Exquisite design of drugs for patient-specific protein expression using clues from Mother Nature Chemical Synthesis In Vitro and In Vivo Testing Further Improvement and Refinement
  • 30. Our other projects: Ultrasound resonance Electroporation Magnetic field guided drug delivery Laser-induced activation of conjugated compounds Microtubule hybridization Taxane pharmacokinetics