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Computational Science: Computational Chemistry in the FAMU Chemistry Department. Jesse Edwards Associate Professor Chemistry Florida A&M University Tallahassee, FL 32307 June 15, 2010 MSEIP C-STEM Workshop. Computational Science. http://www.shodor.org/chemviz/overview/compsci.html.

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Computational science computational chemistry in the famu chemistry department

Computational Science: Computational Chemistry in the FAMU Chemistry Department

Jesse Edwards

Associate Professor Chemistry

Florida A&M University

Tallahassee, FL 32307

June 15, 2010

MSEIP C-STEM Workshop


Computational science
Computational Science Chemistry Department

http://www.shodor.org/chemviz/overview/compsci.html


Computer science and chemistry

Computer Science and Chemistry Chemistry Department

Instrumentation/Computer Interface

Visualization

Computational Chemistry

Computer Aided Instruction


Computational Chemistry Chemistry Department

Mathematics , Physics, Chemistry Theories

Algorithms

More Theories

Properties

Structures


Computational chemistry
Computational Chemistry Chemistry Department

  • Use of computers and algorithms based on chemistry and physics to predict structures, and properties of chemical systems

    • Properties Include:

      • electronic structure determinations

      • geometry optimizations

      • frequency calculations

      • transition structures

      • protein calculations, i.e. docking

      • electron and charge distributions

      • potential energy surfaces (PES)

      • rate constants for chemical reactions (kinetics)

      • thermodynamic calculations- heat of reactions, energy of activation

      • Molecular dynamics

      • Conformational Energies

      • Binding Energies

      • Protein Folding



Mesoscale modeling

Mesoscale Chemistry Department Modeling

Large scale

Coarse Grain Modeling

Engineering Applications


Edwards group research projects
Edwards Group Research Projects Chemistry Department

Drug Delivery Systems

Tissue Engineering Scaffolding

<-Synthetic Wet Lab->

Estrogen Receptor LBD

SERM’s

HIV -1 Protease

Drug Discovery and Protein Folding


Molecular Mechanics Chemistry Department

And

Molecular Dynamics



P= - (A/r Chemistry Department6) + (B/r12)

Ecol = E1E2

r

P

E

r

1/r

Coulombic Interaction

van der Waals

Non-bondedInteractions


Molecular dynamic simulations of the estrogen receptor a lbd

Molecular Dynamic Simulations of the Estrogen Receptor Chemistry Departmenta LBD

T. Dwight McGee Jr.1, Jesse Edwards1, Adrian E. Roitberg21Department of Chemistry, Florida A & M University, Tallahassee, FL, 32307.2Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL 32608


Her mechanism
hER Chemistry Department Mechanism


Estradiol Chemistry Department



Overlay structure copeptide helix 12 portion with lxxll motif
Overlay Structure Copeptide Helix 12 portion with LXXLL motif.

LXXLL/Copeptide Motif

Red Simulation Average Structure

Blue Antagonist Starting Structure


Summary of dynamics
Summary of Dynamics motif.

  • Residue chain at the head of H12 begins an almost immediate translation >10ns after the removal of the 4-hydoxytamoxifen.

  • Residue chain at the end of H12 migrate towards the top of Helices 3 and 4 and remain there.

  • Residue chain at the beginning of H12 oscillates between the antagonist (initial position) and the antagonist conformation throughout the entire 121ns simulation.


Molecular dynamic study on the conformational dynamics of hiv 1 protease subtype b vs c

Molecular Dynamic Study on the Conformational Dynamics of HIV-1 Protease Subtype B vs. C

T. Dwight McGee Jr.

Florida A&M University


Global effect of aids
Global Effect of AIDS HIV-1 Protease Subtype B vs. C

Map shows HIV-1 subtype prevalence in 2002 based on Osmanov S, Pattou C, Walker N, Schwardlander B, Esparza J; WHO-UNAIDS Network for HIV Isolation and Characterization. (2002) Estimated global distribution and regional spread of HIV-1 genetic subtypes in the year 2000. J Acquir Immune Defic Syndr. 29(2):184-90.


Purpose
Purpose HIV-1 Protease Subtype B vs. C

The results gained from this project could help expand the limited knowledge on the effects of PR C and aid the improvement or the cultivation of new drugs.

Questions of Interest

  • How do these differences affect the size binding cavity?

  • How do these differences affect the flap orientation?


HIV Life Cycle HIV-1 Protease Subtype B vs. C

http://pathmicro.med.sc.edu/lecture/hivstage.gif


Semiopen HIV-1 Protease Subtype B vs. C

Closed

Open


Subtype b vs c
Subtype B vs. C HIV-1 Protease Subtype B vs. C

T12S

I15V

L19I

M36I

S37A

H69K

L89M

I93L

X-ray Crystal Structure provided by Dunn et al.


Histogram of ILE50-ILE50 HIV-1 Protease Subtype B vs. C

PR C- RED

PR B- BLACK


Histogram ASP25-ILE50 HIV-1 Protease Subtype B vs. C

PR C- RED

PR B- BLACK


Molecular Modeling Studies of the Binding Characteristics of Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

R. Parkera, J. Edwardsb, A. A. Odukalec, C. Batichc, E. Rossc

a Department of Industrial and Manufacturing Engineering FAMU/FSU College of Engineering

b Department of Chemistry Florida A&M University

c Department of Materials Engineering University of Florida


Our approach
Our approach Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

  • Sevelamar hydrochloride is used in Renagel® to reduce the level of phosphates in the body.

  • A Sevelamar hydrochloride-pyrrole composite can be formed to build a self-monitoring phosphate contamination system and removal system

  • Molecular dynamics and monte carlo methods will be used to determine key design parameters for the composite system


Sevelamar hydrochloride
Sevelamar hydrochloride Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

  • a crosslinked poly(allylamine hydrochloride)

  • binds phosphates by ionic interactions between protonated amide groups along the polymer backbone.

Structure;

a, b = number of primary amine groups a+b =9;

c = number of cross-linking groups) c= 1;

n = fraction of protonated amines) n = 0.4;

m = large number to indicate extended polymer network

m

R. A. Swearingen, X. Chen, J. S. Petersen, K. S. Riley, D. Wang, E. Zhorov, Determination of the Binding Parameter Constants of Renagel® Capsules and Tablets Utilizing the Langmuir Approximation at Various pH by Ion Chromatograhpy, Journal of Pharmaceutical and Biomedical Analysis, 2002, 29, 195-201


Objectives
Objectives Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

  • Build a system with high Phosphate binding efficiency

  • Understand how uptake and binding are affected by pH, swelling, swelling & concentration of Phosphate groups

  • Understand binding efficiency and mechanism of Phosphates with Sevelamer Hydrochloride


Observed swelling due to ph
Observed Swelling due to pH Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

Observed swelling of dry particles…

…exposed to an acidic solution at pH = 1…

…followed by additional exposure to a pH = 7 solution

Swelling of 50-70% at 1-hr exposure to a pH solution of 1 to 7.


Modeling methods
Modeling Methods Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

Molecular Dynamics

  • Used to determine average structure

  • Means of capturing phosphates

    Monte Carlo Simulations

  • Determine the overall volume of model system

  • Compare results with swelling data


Modeled system 4 po4
Modeled System Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination4 PO4


25 swelling observed within a single molecule
25% swelling observed within a single molecule Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination


Computational studies of anti tumor agents drug discovery

Computational Studies of Anti-Tumor Agents Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination(Drug Discovery)

J. Edwards

J. Cooperwood

J. Robinson

Mindi L. Buckles


Serm s bond rotational barriers
SERM’s Bond Rotational Barriers Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination


Cnt epoxy resin composites materials
CNT-Epoxy Resin Composites Materials Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

  • D. Thomas, FAMU, Chemistry

  • R. Parker, 510nano Inc. Baltimore, MD

  • J. Edwards, FAMU, Chemistry

  • C. Liu, FAMU/FSU Engineering


Comparing exp to simulation

500 ps Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination

Comparing Exp. To Simulation

Experiment (SEM Image CNT-Epoxy Composite)

Small Model Simulation

Large Model Simulation


Coarse grain modeling of micelle formation drug delivery

Coarse-Grain Modeling of Micelle Formation Phosphates to Sevelamar Hydrochloride – Assessing a Novel Technique to Reduce Phosphates Contamination(Drug Delivery)

Scott Shell, UCSB, Chemical Engineering

J. Edwards, FAMU, Chemistry

Craig Hawker, UCSB, Chemisrty/MRL


Polymeric micelle systems for delivery of steroidal derivatives

Polymeric Micelle Systems for Delivery of Steroidal Derivatives

Antoinette Addison2, Jos M.J. Paulusse1,Roey Amir1 Jesse Edwards2,Craig J. Hawker1

1Univeristy of California at Santa Barbara, Materials Research Laboratory, Santa Barbara CA93106

2 Florida A&M University, College of Arts and Science, Tallahassee, Florida 32307


Synthetic strategy
Synthetic Strategy Derivatives

  • The reaction of poly (ethylene glycol) with various cyclic anhydrides

n

n

R = CH2, CH2-CH2, CH2-C-(CH3)2 .......

  • Reacting the peg-acid with ethylcholorformate and attaching the cholesterol

)

(

n

n

)

(

n

(

)

n


Computation and science education research
Computation and Science Education Research Derivatives

  • Using computer software to do analysis on student performance

    • Data driven pedagogy

    • Data driven curriculum changes


A Formula for Success in General Chemistry: Increasing Student Performance in a Barrier Course

Dr. Jesse Edwards

Department of Chemistry

Florida A&M University

[email protected]

Dr. Serena Roberts

Curriculum & Evidence Coordinator, Teachers for a New Era

Florida A&M University

[email protected]

Dr. Gita Wijesinghe Pitter

Associate Vice President, Institutional Effectiveness

Florida A&M University

[email protected]


Introduction Student Performance in a Barrier

Florida A&M University is an 1890 land-grant HBCU with an enrollment of approximately 12,000 students. Many of the students are first generation in college and 66% are Pell grant recipients. The Chemistry Department at Florida A&M University has taken on the serious challenge of addressing poor performance in General Chemistry I (CHM 1045), a course for majors in Chemistry and a required prerequisite course for majors in other natural sciences, engineering, health professions, agriculture and science education. The class sizes range from 30 – 140 students and there is no teaching assistant support. An overwhelming majority of the students taking General Chemistry I and II are freshman; however, a significant number are more advanced students due to high repeat rates in the course. During fall 2005 and fall 2006, the pass rates for CHM 1045 were 32% and 30% respectively. In an intensive effort to improve the pass rates, the Department of Chemistry, in collaboration with the Teaching Learning Institute, founded in part through a Teachers for a New Era grant, a Carnegie Corporation of New York sponsored program, undertook a variety of strategies to improve student learning and studied the impact. The body of the paper describes the strategies which had a dramatic impact. The paper also describes recent efforts to increase the pass rates in General Chemistry II (CHM 1046), using study sessions that are based on Bloom’s Taxonomy.


An Ever Improving Formula for Success in General Chemistry: Increasing Student Performance in a Barrier Course

Dr. Jesse Edwards

Department of Chemistry

Florida A&M University

[email protected]

Ms. Christy Chatmon

Department of Computer and Information Systems

Florida A&M University

[email protected]

Dr. Mark Howse

Associate Dean, College of Education

Florida A&M University

[email protected]

Dr. Serena Roberts

Curriculum & Evidence Coordinator, Teachers for a New Era

Florida A&M University

[email protected]


Acknowledgments
Acknowledgments Increasing Student Performance in a Barrier Course

  • Roitberg Group

  • SEAGEP Program

  • NIH/RCMI Faculty Development Award Grant 2 G12 RR003020-19, RCMI

  • University of Florida Chemistry Department

  • Quantum Theory Project

  • Florida Supercomputer Center

  • NCSA University of Illinois Urbana-Champaigne

  • National Oceanic and Atmospheric Administration (NOAA) Climate and Global Change program, CFDA Number: 11.431


Additional acknowledgements

Additional Acknowledgements Increasing Student Performance in a Barrier Course

Student Participants

Antoinette Addison (M.S. Candidate FAMU, Chemistry)

T. Dwight McGee (PhD. Candidate U of F /QTP)

Jamar Robinson (Recently Rickards High School)

Dabrisha Thomas (Scientist, Dept. of Energy)

Dr. Craig Hawker (UCSB MRL/MRFN program NSF award # 0520415)

Dr. Adrian Roitberg (UF/QTP)

Dr. Scott Shell UCSB

Dr. John Cooperwood (FAMU)

Dr. Anne Donnelly (AGEP-SEAGEP)

FAMU Chemistry Department

MSEIP-CSTEM (Dr. Hongmei Chi Principal Investigator)


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