PREDICCIÓN DE ESTRUCTURAS DE CRISTALES CON MOLÉCULAS FLEXIBES EN SU CELDA
Download
1 / 24

MGAC Crystal Structure Prediction Capabilities - PowerPoint PPT Presentation


  • 336 Views
  • Uploaded on

PREDICCIÓN DE ESTRUCTURAS DE CRISTALES CON MOLÉCULAS FLEXIBES EN SU CELDA. V. Bazterra, M. B. Ferraro, J. C. Facelli. Departamento de Física Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires. 2007. AIM OF THE APPLICATION. Crystal engeneering. Pharmaceutical design.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'MGAC Crystal Structure Prediction Capabilities' - Gideon


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Slide1 l.jpg

PREDICCIÓN DE ESTRUCTURAS DE CRISTALES CON MOLÉCULAS FLEXIBES EN SU CELDA

V. Bazterra, M. B. Ferraro,

J. C. Facelli

Departamento de Física

Facultad de Ciencias Exactas y Naturales

Universidad de Buenos Aires

2007


Slide2 l.jpg

AIM OF THE APPLICATION FLEXIBES EN SU CELDA

  • Crystal engeneering

  • Pharmaceutical design

  • Polymorphism

  • Application in materials.


Slide3 l.jpg

Why GENETIC ALGORITHMS? FLEXIBES EN SU CELDA

  • Difficult crystal prediction from first principles.

  • Polymorphic forms in organic crystals

  • Useful to model atomic and molecular clusters.


Slide4 l.jpg

MGAC Crystal Structure Prediction Capabilities FLEXIBES EN SU CELDAVictor E. Bazterra, Matthew Thorley, Marta B. Ferraro, and Julio C. FacelliJ. Chem. Theory Comput. 2007, 3, 201-209

  • Search for crystal structures within any symmetry group and with an arbitrary number of molecules and molecular types per asymmetric unit.

  • Search structures using either the rigid or flexible molecule models.

  • Automatically generate the molecule’s force field using existing force field libraries.

  • Increase the sampling power and the complexity of molecules amenable to CSP studies using the parallel and distributed computing capabilities of the system.

  • Automatically compare, sort and archive the most relevant structures in a user database.


Genetic coding l.jpg

Molecular center of mass FLEXIBES EN SU CELDA {R1, R2,…Rn} 

Its orientations  {1 , 2 ,…\n }

Relevant dihedral angles  {1 , 2 , …..n }

Space group and lattice parameters  {a,b,c,,,}

GENETIC CODING

(Rigid bodies)


Genetic algorithms application l.jpg
Genetic Algorithms Application FLEXIBES EN SU CELDA


Semi rigid approximation l.jpg
SEMI-RIGID APPROXIMATION FLEXIBES EN SU CELDA

-Crystallographic group

DATA

-Number of molecules in the cell

MOLECULES:

-center of mass positions

-relative orientations

PARAMETERS

-Lattice axis a, b, c

-Lattice angles, , , 

-AMBER FORCE FIELD

-CHARMm FORCE FIELD

in CHARMM code

APTITUDE FUNCTION


Semirigid approximation l.jpg
SEMIRIGID APPROXIMATION FLEXIBES EN SU CELDA

-crystallographic cell axes and angles.

-positions of the center of masss of each molecule.

-Euler angles respect to the unit cell.

-Ndihe molecular angles.

Rigid bodies with flexible chains

K=6+Z(6+Ndihed.)

Parameters to be optimized


Interface with charm module l.jpg
Interface with CHARM Module FLEXIBES EN SU CELDA


Population analysis l.jpg
Population analysis FLEXIBES EN SU CELDA

Evolution of the

population energy

Hystogram of the evolution


Comparison between crystals l.jpg
Comparison between crystals FLEXIBES EN SU CELDA


Fragment matching l.jpg
Fragment matching FLEXIBES EN SU CELDA


Csp2007 methodology l.jpg
CSP2007 Methodology FLEXIBES EN SU CELDA

  • Local optimization using CHARMM 6, 7 with the GAFF 14 parameters. cutoff of 14 Å, and the electrostatic interactions were calculated using the Ewald technique.

  • Atomic charges, , using the restrained electrostatic potential approach implemented on the RESP program. Gaussian03 32 package at HF/6-31G* level.

  • Restricted searches using 30 individuals in the population for up to 130 generations, for the 14 most common symmetry groups for organic molecules, P1, P-1, P21, C2, Pc, Cc, P21/c, C2/c, P212121, Pca21, Pna21, Pbcn, Pbca and Pnma.

  • For each molecule we performed between 150 and 200 runs leading to at least 100 complete runs with 130 generations.

  • From these short lists we manually detected clearly unphysical structures and duplicated ones that were not eliminated in the previous step that were identified by comparison of their XRPD spectra


Molecule i l.jpg
Molecule I FLEXIBES EN SU CELDA


Molecule i16 l.jpg
Molecule I FLEXIBES EN SU CELDA


Molecule iii l.jpg
Molecule III FLEXIBES EN SU CELDA


Molecule xii l.jpg
Molecule XII FLEXIBES EN SU CELDA

ACRY02

Space group: Pbca


Molecule xii20 l.jpg
Molecule XII FLEXIBES EN SU CELDA


Molecule xiv l.jpg
Molecule XIV FLEXIBES EN SU CELDA

P21/c


Molecule xiv22 l.jpg
Molecule XIV FLEXIBES EN SU CELDA


Slide23 l.jpg
?????? FLEXIBES EN SU CELDA

  • Test predictions of benchmark crystals

  • Prediction of experimental data

  • Incorporation of additional pseudopotentials

  • Cosmetics and website.


Slide24 l.jpg

Marta Ferraro FLEXIBES EN SU CELDA

Víctor Bazterra

Departamento de Física

University of Buenos Aires

Argentina

Center for High

Performance Computing

University of Utah

Julio C. Facelli

Martin Cuma


ad