SlideShare une entreprise Scribd logo
1  sur  23
Télécharger pour lire hors ligne
Drugs and Electrons

     David C. Thompson
            March 2008
Overview
 A little bit about why we make drugs, and
  how computational chemistry is used (my
  day job)
 A little bit about confined electronic
  systems, informational entropy, and
  complexity (my evening job)
 A novel 3D QM based structural descriptor
  (my afternoon job?)
Drugs - why do we make them?
1. Money
2. And I guess you can help people too
3. But mainly for the money
Drugs - how do we make them?
 From a computational perspective I will
  limit myself to Structure-Based Drug
  Design (SBDD)
Drugs - how do we make them?
 What are we trying to do?

                              +            = ?


 In SBDD we use computational chemistry to capture some
  part of this incredibly complex interaction by modeling the
  protein-ligand binding event
 We typically ‘ignore’:
    Protein flexibility, polarization and other electronic factors,
     solvent, entropy . . .
And what have I been doing?
 Detailed analysis of the in-house high-throughput virtual
  screening protocol
    Accepted in J. Chem. Inf. Mod.


 Fragment-based de novo design
    CONFIRM
    Submitted to J. Comput.-Aided Mol. Design


 A large scale critical assessment of docking programs
    Binding mode prediction
    Enrichment rates in virtual screening
    Method development: Docking pose assessment tool
The Hospital that ate my Wife
 Given the tools of our trade:




 I can still work on problems in electronic structure
 Information theoretic properties of strongly
  correlated systems
    Prof. Kalidas D. Sen, University of Hyderabad
    Dr. Ali Alavi, University of Cambridge
Electrons and how they get along
 PhD in small model quantum systems
    Particles-in-a-box
    Exact solutions
 Archetypal systems for investigating electron
  correlation
 Electron correlation arises as a consequence of the
  simultaneous interactions of mutually repelling
  particles
    It is what makes QM a ‘tricky’ problem both
     conceptually, and practically
Basic physics of these systems
 Two regions of behaviour
   Small R - kinetic dominance
   Large R - Coulombic dominance


 E ~ A/R2 + B/R + …

 Wigner ‘crystal’ formation at large R
Properties of interest
                               r r
Eigenvalues and
eigenvectors:
                     E i , "i (x1...x N )
                        r               2    r       r
Density:             n (r1 ) = N ! | " | ds1dx 2 ...dx N
Second order              rr         N(N - 1)        2         r     r
density matrix:      n 2 (r , r ') =          ! |" | ds1ds 2dx 3 ...dx N
                                         2
Physical                   rr          2      rr          r
exchange-            n xc (r , r ') = r n 2 (r , r ')# n (r ')
correlation                          n (r )
hole:
                          r r               2 r        r
First order
density matrix:
                     $ 1 (x, x') = N ! | " | dx 2 ...dx N
 FCI, RHF, UHF, and LDA solutions for both the spherical
 (N=2, 3, 4, and 5) and cubic/planar (N=3, and 4) geometries
Spherical two electron system
Spherical two electron system
 RHF solution is surprisingly simple (S=0)
                   1        µ max
         " (r) =
                   4#
                        $   µ =1
                                    Cµ j 0 (% µ 0 r)

 And rapidly convergent for even large R
 ! max=7)
  (µ
Spherical two electron system:
RHF and informational entropy


              Sr = " $ # (r) ln[ #(r)]dr
              S p = " $ % (p) ln[% (p)]dp
              ST = Sr + S p



         !
Spherical two electron system:
     Complexity - RHF
Spherical two electron system:
   Complexity - Hylleraas
A novel descriptor?
 Doesn’t Sr look a little familiar?
 Continuous form of a measure used in molecular
  similarity:

                 S = "# pi ln[ pi ]
                         i
 Could we use Sr as a measure of similarity?
 Moreover, could Sr be a 3D QM-based structural
  descriptor?
   !
    Literature search has shown that this has not been
    considered before (I think)
A novel descriptor?
     We want to make this useful
        But we still have the problem of finding ρ in a timely fashion


     Why don’t we approximate ρ?
        We construct a pro-molecular density from a sum of fitted s-
         Gaussians
       "(r) # " Mol (r) = % "$ (r) = % % c$i exp(&'$i (r & R$ ) 2 )
                           $            $   i

     Turns out that this isn’t as bad as you might think

!
Homebrew quantum mechanics

       All of this has been done on my iMac at home

       Molecular integrations performed using the
        Becke/Lebedev grids in PyQuante[1]

       Co-opted James into doing MathCad checks for
        me. . .



[1] Python Quantum Chemistry - http://pyquante.sourceforge.net/
Homebrew quantum mechanics




        H1   Rz   H2
Homebrew quantum mechanics

  Molecule                 Sr
       H2O               -7.42
       H2S               3.94
     Benzene            -27.09
Cyclohexane (chair)     -35.94


                 Perhaps Sr isn’t that discriminatory?
                 Plan B - Sr (r) = " #(r)ln[ # (r)]
And that might look like. . .
Conclusions and outlook
 Hopefully you have a feel for what I have been
  working on, and why it might be interesting/useful

 Work with Prof. Sen is being written up
    Extend to planes - see if signature holds for N>2


 At BI incorporate descriptor into a QSAR model
    Is it of any use at all - what about Sp?
Acknowledgments
 Wyeth Research
 Prof. Sen and Dr. Alavi
 You all

Contenu connexe

Tendances

Tendances (8)

Spacey random walks from Householder Symposium XX 2017
Spacey random walks from Householder Symposium XX 2017Spacey random walks from Householder Symposium XX 2017
Spacey random walks from Householder Symposium XX 2017
 
K means Clustering Algorithm
K means Clustering AlgorithmK means Clustering Algorithm
K means Clustering Algorithm
 
K means
K meansK means
K means
 
Higher-order clustering coefficients
Higher-order clustering coefficientsHigher-order clustering coefficients
Higher-order clustering coefficients
 
Steven Duplij - Generalized duality, Hamiltonian formalism and new brackets
Steven Duplij - Generalized duality, Hamiltonian formalism and new bracketsSteven Duplij - Generalized duality, Hamiltonian formalism and new brackets
Steven Duplij - Generalized duality, Hamiltonian formalism and new brackets
 
K means clustering
K means clusteringK means clustering
K means clustering
 
Data miningpresentation
Data miningpresentationData miningpresentation
Data miningpresentation
 
Fractional pseudo-Newton method and its use in the solution of a nonlinear sy...
Fractional pseudo-Newton method and its use in the solution of a nonlinear sy...Fractional pseudo-Newton method and its use in the solution of a nonlinear sy...
Fractional pseudo-Newton method and its use in the solution of a nonlinear sy...
 

Similaire à Drugs and Electrons

20070823
2007082320070823
20070823
neostar
 
Modeling the dynamics of molecular concentration during the diffusion procedure
Modeling the dynamics of molecular concentration during the  diffusion procedureModeling the dynamics of molecular concentration during the  diffusion procedure
Modeling the dynamics of molecular concentration during the diffusion procedure
International Journal of Engineering Inventions www.ijeijournal.com
 
Paper computer
Paper computerPaper computer
Paper computer
bikram ...
 
Paper computer
Paper computerPaper computer
Paper computer
bikram ...
 
Discrete Signal Processing
Discrete Signal ProcessingDiscrete Signal Processing
Discrete Signal Processing
margretrosy
 

Similaire à Drugs and Electrons (20)

Nelly Litvak – Asymptotic behaviour of ranking algorithms in directed random ...
Nelly Litvak – Asymptotic behaviour of ranking algorithms in directed random ...Nelly Litvak – Asymptotic behaviour of ranking algorithms in directed random ...
Nelly Litvak – Asymptotic behaviour of ranking algorithms in directed random ...
 
Report on Efficient Estimation for High Similarities using Odd Sketches
Report on Efficient Estimation for High Similarities using Odd Sketches  Report on Efficient Estimation for High Similarities using Odd Sketches
Report on Efficient Estimation for High Similarities using Odd Sketches
 
Dumitru Vulcanov - Numerical simulations with Ricci flow, an overview and cos...
Dumitru Vulcanov - Numerical simulations with Ricci flow, an overview and cos...Dumitru Vulcanov - Numerical simulations with Ricci flow, an overview and cos...
Dumitru Vulcanov - Numerical simulations with Ricci flow, an overview and cos...
 
20070823
2007082320070823
20070823
 
Master Thesis on the Mathematial Analysis of Neural Networks
Master Thesis on the Mathematial Analysis of Neural NetworksMaster Thesis on the Mathematial Analysis of Neural Networks
Master Thesis on the Mathematial Analysis of Neural Networks
 
Comparative Study of the Effect of Different Collocation Points on Legendre-C...
Comparative Study of the Effect of Different Collocation Points on Legendre-C...Comparative Study of the Effect of Different Collocation Points on Legendre-C...
Comparative Study of the Effect of Different Collocation Points on Legendre-C...
 
Modeling the dynamics of molecular concentration during the diffusion procedure
Modeling the dynamics of molecular concentration during the  diffusion procedureModeling the dynamics of molecular concentration during the  diffusion procedure
Modeling the dynamics of molecular concentration during the diffusion procedure
 
Mtc ssample05
Mtc ssample05Mtc ssample05
Mtc ssample05
 
Mtc ssample05
Mtc ssample05Mtc ssample05
Mtc ssample05
 
Paper computer
Paper computerPaper computer
Paper computer
 
Paper computer
Paper computerPaper computer
Paper computer
 
Discrete Signal Processing
Discrete Signal ProcessingDiscrete Signal Processing
Discrete Signal Processing
 
Metodo Monte Carlo -Wang Landau
Metodo Monte Carlo -Wang LandauMetodo Monte Carlo -Wang Landau
Metodo Monte Carlo -Wang Landau
 
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
Manifold Blurring Mean Shift algorithms for manifold denoising, presentation,...
 
NANO266 - Lecture 4 - Introduction to DFT
NANO266 - Lecture 4 - Introduction to DFTNANO266 - Lecture 4 - Introduction to DFT
NANO266 - Lecture 4 - Introduction to DFT
 
Introduction to recommender systems
Introduction to recommender systemsIntroduction to recommender systems
Introduction to recommender systems
 
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
 
AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...
AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...
AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...
 
AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...
AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...
AN EFFICIENT PARALLEL ALGORITHM FOR COMPUTING DETERMINANT OF NON-SQUARE MATRI...
 
Knn solution
Knn solutionKnn solution
Knn solution
 

Plus de David Thompson

Plus de David Thompson (20)

Connect With STEM Learning Report (2015-2016)
Connect With STEM Learning Report (2015-2016)Connect With STEM Learning Report (2015-2016)
Connect With STEM Learning Report (2015-2016)
 
Five Things to Know about Networks Within Firms
Five Things to Know about Networks Within FirmsFive Things to Know about Networks Within Firms
Five Things to Know about Networks Within Firms
 
Connect With STEM - See It, Be It
Connect With STEM - See It, Be ItConnect With STEM - See It, Be It
Connect With STEM - See It, Be It
 
The context of crowdsourcing: A driver of organizational openness?
The context of crowdsourcing: A driver of organizational openness?The context of crowdsourcing: A driver of organizational openness?
The context of crowdsourcing: A driver of organizational openness?
 
Data Driven Change
Data Driven ChangeData Driven Change
Data Driven Change
 
Crowdsourcing: Bringing Outside, In
Crowdsourcing: Bringing Outside, InCrowdsourcing: Bringing Outside, In
Crowdsourcing: Bringing Outside, In
 
Grand Theft Engagement
Grand Theft EngagementGrand Theft Engagement
Grand Theft Engagement
 
Social: A Network Leader's Perfect Diversity Platform
Social: A Network Leader's Perfect Diversity PlatformSocial: A Network Leader's Perfect Diversity Platform
Social: A Network Leader's Perfect Diversity Platform
 
Redressing the Baseline: Exploit vs. Explore
Redressing the Baseline: Exploit vs. ExploreRedressing the Baseline: Exploit vs. Explore
Redressing the Baseline: Exploit vs. Explore
 
Change Management 2.0
Change Management 2.0Change Management 2.0
Change Management 2.0
 
Social is Dead. Long Live Social.
Social is Dead. Long Live Social.Social is Dead. Long Live Social.
Social is Dead. Long Live Social.
 
Welcome To My Brain
Welcome To My BrainWelcome To My Brain
Welcome To My Brain
 
Thinking inside the box - What is the role of digital within the four walls o...
Thinking inside the box - What is the role of digital within the four walls o...Thinking inside the box - What is the role of digital within the four walls o...
Thinking inside the box - What is the role of digital within the four walls o...
 
LunchRoulette
LunchRouletteLunchRoulette
LunchRoulette
 
Crowd computing: All your base are belong to us
Crowd computing: All your base are belong to usCrowd computing: All your base are belong to us
Crowd computing: All your base are belong to us
 
Competitive data science: A tale of two web services
Competitive data science: A tale of two web servicesCompetitive data science: A tale of two web services
Competitive data science: A tale of two web services
 
Internal Social Media: The ties that bind
Internal Social Media: The ties that bindInternal Social Media: The ties that bind
Internal Social Media: The ties that bind
 
Tri-State SHRM Conference
Tri-State SHRM ConferenceTri-State SHRM Conference
Tri-State SHRM Conference
 
Diversity 2.0 - The Diversity and Inclusion Social Media Revolution
Diversity 2.0 - The Diversity and Inclusion Social Media RevolutionDiversity 2.0 - The Diversity and Inclusion Social Media Revolution
Diversity 2.0 - The Diversity and Inclusion Social Media Revolution
 
Internal Social Media: Weaving the threads together
Internal Social Media: Weaving the threads togetherInternal Social Media: Weaving the threads together
Internal Social Media: Weaving the threads together
 

Dernier

Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
ZurliaSoop
 

Dernier (20)

Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
Jual Obat Aborsi Hongkong ( Asli No.1 ) 085657271886 Obat Penggugur Kandungan...
 
Fostering Friendships - Enhancing Social Bonds in the Classroom
Fostering Friendships - Enhancing Social Bonds  in the ClassroomFostering Friendships - Enhancing Social Bonds  in the Classroom
Fostering Friendships - Enhancing Social Bonds in the Classroom
 
How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17How to Create and Manage Wizard in Odoo 17
How to Create and Manage Wizard in Odoo 17
 
Google Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptxGoogle Gemini An AI Revolution in Education.pptx
Google Gemini An AI Revolution in Education.pptx
 
Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024Mehran University Newsletter Vol-X, Issue-I, 2024
Mehran University Newsletter Vol-X, Issue-I, 2024
 
ICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptxICT Role in 21st Century Education & its Challenges.pptx
ICT Role in 21st Century Education & its Challenges.pptx
 
Sociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning ExhibitSociology 101 Demonstration of Learning Exhibit
Sociology 101 Demonstration of Learning Exhibit
 
REMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptxREMIFENTANIL: An Ultra short acting opioid.pptx
REMIFENTANIL: An Ultra short acting opioid.pptx
 
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
TỔNG ÔN TẬP THI VÀO LỚP 10 MÔN TIẾNG ANH NĂM HỌC 2023 - 2024 CÓ ĐÁP ÁN (NGỮ Â...
 
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdfUGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
80 ĐỀ THI THỬ TUYỂN SINH TIẾNG ANH VÀO 10 SỞ GD – ĐT THÀNH PHỐ HỒ CHÍ MINH NĂ...
 
How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17How to Give a Domain for a Field in Odoo 17
How to Give a Domain for a Field in Odoo 17
 
Food safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdfFood safety_Challenges food safety laboratories_.pdf
Food safety_Challenges food safety laboratories_.pdf
 
Wellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptxWellbeing inclusion and digital dystopias.pptx
Wellbeing inclusion and digital dystopias.pptx
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024FSB Advising Checklist - Orientation 2024
FSB Advising Checklist - Orientation 2024
 
Spatium Project Simulation student brief
Spatium Project Simulation student briefSpatium Project Simulation student brief
Spatium Project Simulation student brief
 
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
 
ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.ICT role in 21st century education and it's challenges.
ICT role in 21st century education and it's challenges.
 

Drugs and Electrons

  • 1. Drugs and Electrons David C. Thompson March 2008
  • 2. Overview  A little bit about why we make drugs, and how computational chemistry is used (my day job)  A little bit about confined electronic systems, informational entropy, and complexity (my evening job)  A novel 3D QM based structural descriptor (my afternoon job?)
  • 3. Drugs - why do we make them? 1. Money 2. And I guess you can help people too 3. But mainly for the money
  • 4. Drugs - how do we make them?  From a computational perspective I will limit myself to Structure-Based Drug Design (SBDD)
  • 5. Drugs - how do we make them?  What are we trying to do? + = ?  In SBDD we use computational chemistry to capture some part of this incredibly complex interaction by modeling the protein-ligand binding event  We typically ‘ignore’:  Protein flexibility, polarization and other electronic factors, solvent, entropy . . .
  • 6. And what have I been doing?  Detailed analysis of the in-house high-throughput virtual screening protocol  Accepted in J. Chem. Inf. Mod.  Fragment-based de novo design  CONFIRM  Submitted to J. Comput.-Aided Mol. Design  A large scale critical assessment of docking programs  Binding mode prediction  Enrichment rates in virtual screening  Method development: Docking pose assessment tool
  • 7. The Hospital that ate my Wife  Given the tools of our trade:  I can still work on problems in electronic structure  Information theoretic properties of strongly correlated systems  Prof. Kalidas D. Sen, University of Hyderabad  Dr. Ali Alavi, University of Cambridge
  • 8. Electrons and how they get along  PhD in small model quantum systems  Particles-in-a-box  Exact solutions  Archetypal systems for investigating electron correlation  Electron correlation arises as a consequence of the simultaneous interactions of mutually repelling particles  It is what makes QM a ‘tricky’ problem both conceptually, and practically
  • 9. Basic physics of these systems  Two regions of behaviour  Small R - kinetic dominance  Large R - Coulombic dominance  E ~ A/R2 + B/R + …  Wigner ‘crystal’ formation at large R
  • 10. Properties of interest r r Eigenvalues and eigenvectors: E i , "i (x1...x N ) r 2 r r Density: n (r1 ) = N ! | " | ds1dx 2 ...dx N Second order rr N(N - 1) 2 r r density matrix: n 2 (r , r ') = ! |" | ds1ds 2dx 3 ...dx N 2 Physical rr 2 rr r exchange- n xc (r , r ') = r n 2 (r , r ')# n (r ') correlation n (r ) hole: r r 2 r r First order density matrix: $ 1 (x, x') = N ! | " | dx 2 ...dx N FCI, RHF, UHF, and LDA solutions for both the spherical (N=2, 3, 4, and 5) and cubic/planar (N=3, and 4) geometries
  • 12. Spherical two electron system  RHF solution is surprisingly simple (S=0) 1 µ max " (r) = 4# $ µ =1 Cµ j 0 (% µ 0 r)  And rapidly convergent for even large R ! max=7) (µ
  • 13. Spherical two electron system: RHF and informational entropy Sr = " $ # (r) ln[ #(r)]dr S p = " $ % (p) ln[% (p)]dp ST = Sr + S p !
  • 14. Spherical two electron system: Complexity - RHF
  • 15. Spherical two electron system: Complexity - Hylleraas
  • 16. A novel descriptor?  Doesn’t Sr look a little familiar?  Continuous form of a measure used in molecular similarity: S = "# pi ln[ pi ] i  Could we use Sr as a measure of similarity?  Moreover, could Sr be a 3D QM-based structural descriptor? ! Literature search has shown that this has not been considered before (I think)
  • 17. A novel descriptor?  We want to make this useful  But we still have the problem of finding ρ in a timely fashion  Why don’t we approximate ρ?  We construct a pro-molecular density from a sum of fitted s- Gaussians "(r) # " Mol (r) = % "$ (r) = % % c$i exp(&'$i (r & R$ ) 2 ) $ $ i  Turns out that this isn’t as bad as you might think !
  • 18. Homebrew quantum mechanics  All of this has been done on my iMac at home  Molecular integrations performed using the Becke/Lebedev grids in PyQuante[1]  Co-opted James into doing MathCad checks for me. . . [1] Python Quantum Chemistry - http://pyquante.sourceforge.net/
  • 20. Homebrew quantum mechanics Molecule Sr H2O -7.42 H2S 3.94 Benzene -27.09 Cyclohexane (chair) -35.94 Perhaps Sr isn’t that discriminatory? Plan B - Sr (r) = " #(r)ln[ # (r)]
  • 21. And that might look like. . .
  • 22. Conclusions and outlook  Hopefully you have a feel for what I have been working on, and why it might be interesting/useful  Work with Prof. Sen is being written up  Extend to planes - see if signature holds for N>2  At BI incorporate descriptor into a QSAR model  Is it of any use at all - what about Sp?
  • 23. Acknowledgments  Wyeth Research  Prof. Sen and Dr. Alavi  You all