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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


Computational Science

Computer Science and Chemistry

Instrumentation/Computer Interface


Computational Chemistry

Computer Aided Instruction

Computational Chemistry

Mathematics , Physics, Chemistry Theories


More Theories



Computational Chemistry

  • 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

Large scale

Coarse Grain Modeling

Engineering Applications

Edwards Group Research Projects

Drug Delivery Systems

Tissue Engineering Scaffolding

<-Synthetic Wet Lab->

Estrogen Receptor LBD


HIV -1 Protease

Drug Discovery and Protein Folding

Molecular Mechanics


Molecular Dynamics

Common Molecular Mechanics Forcefield Components

P= - (A/r6) + (B/r12)

Ecol = E1E2






Coulombic Interaction

van der Waals


Molecular Dynamic Simulations of the Estrogen Receptor a LBD

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

hER Mechanism


Simulation of the Estrogen Receptor Ligand Binding Domain

Overlay Structure Copeptide Helix 12 portion with LXXLL motif.

LXXLL/Copeptide Motif

Red Simulation Average Structure

Blue Antagonist Starting Structure

Summary of Dynamics

  • 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

T. Dwight McGee Jr.

Florida A&M University

Global Effect of AIDS

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.


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




Subtype B vs. C









X-ray Crystal Structure provided by Dunn et al.

Histogram of ILE50-ILE50



Histogram ASP25-ILE50



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

  • 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

  • a crosslinked poly(allylamine hydrochloride)

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


a, b = number of primary amine groupsa+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


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


  • 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 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

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 System4 PO4

25% swelling observed within a single molecule

Computational Studies of Anti-Tumor Agents(Drug Discovery)

J. Edwards

J. Cooperwood

J. Robinson

Mindi L. Buckles

SERMs Bond Rotational Barriers

CNT-Epoxy Resin Composites Materials

  • D. Thomas, FAMU, Chemistry

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

  • J. Edwards, FAMU, Chemistry

  • C. Liu, FAMU/FSU Engineering

500 ps

Comparing Exp. To Simulation

Experiment (SEM Image CNT-Epoxy Composite)

Small Model Simulation

Large Model Simulation

Coarse-Grain Modeling of Micelle Formation(Drug Delivery)

Scott Shell, UCSB, Chemical Engineering

J. Edwards, FAMU, Chemistry

Craig Hawker, UCSB, Chemisrty/MRL

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

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



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

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











Computation and Science Education Research

  • 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

Dr. Serena Roberts

Curriculum & Evidence Coordinator, Teachers for a New Era

Florida A&M University

Dr. Gita Wijesinghe Pitter

Associate Vice President, Institutional Effectiveness

Florida A&M University


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 Blooms 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

Ms. Christy Chatmon

Department of Computer and Information Systems

Florida A&M University

Dr. Mark Howse

Associate Dean, College of Education

Florida A&M University

Dr. Serena Roberts

Curriculum & Evidence Coordinator, Teachers for a New Era

Florida A&M University


  • 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

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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