The document discusses using in silico molecular dynamics simulations to predict the 3D structures of proteins from their amino acid sequences in order to better understand protein folding. It provides background on proteins and the protein folding problem, and describes current models of protein folding as well as molecular dynamics and replica exchange molecular dynamics simulation techniques for studying protein folding at an atomistic level in silico.

1. Insights into All-Atom Protein Structure
Prediction via in silico Simulations
2013 Sigma Xi Student Research Showcase
Daniel Wang

2. RESEARCH GOALS
To utilize in silico methods to perform de
novo simulations of protein folding
pathways and predict the functional
structures of proteins.

3. BACKGROUND
 Proteins – Biological Workhorses
The central dogma of biology A map of 3200 protein interactions between 1700 proteins
(Image from http://www.nyu.edu/ (Image from http://www.mdc-berlin.de/en/news/archive/2008/20080910-erwin_schr_dinger_prize_2008_goes_to_resea/index.html)
projects/vogel/Pics/centraldogma_2
 Proteins serve a plethora of vital functions: growth and repair, cell-to-cell signaling,
defense against pathogens, movement, catalyzing reactions
 Protein function is determined by specific 3-dimensional structure
 ~130,000 binary protein-protein interactions in a human cell at any given time

4.  Protein Folding Problem
Random Coil 3-dimensional
(Image from http://www.ks.uiuc.edu/villin-folding-process)
Structure native structure
 Protein folding is the process of molecular self-assembly during which an extended
chain of amino acids collapses to form a compact and specific three-
dimensional structure
 A protein becomes functional when it folds into a 3-dimensional structure.
 Misfolded proteins can aggregate and lead to a range of diseases, such as Alzheimer’s
and Parkinson’s
 No current method exists to predict the functional structure of a protein from its
amino acid sequence

5.  Folding Funnel Model
 Modern folding model = energy
of a protein with respect to
systemic changes in geometry and
is represented by funnel-shaped
energy landscapes
 Protein chain must negotiate
multiple folding pathways with
valley traps and mountain barriers
 Conformational entropy that is
lost during the folding process is
compensated by an increase in
free energy as the global
minimum is approached
Thermodynamic protein folding funnel
(Image from http://www.learner.org/courses/physics/visual/visual.html?shortname=funnel)

6.  Molecular Dynamics Simulations
Schematic of molecular dynamics steps Implicit molecular dynamics environment
(Image from http://www.yasara.org/benchmarks.htm)
 MD simulations calculate the physical movements of atoms in a system over a
period of time, known as a trajectory.
 Timesteps in the femtosecond (10-15 of a second) scale, MD simulations offer
insight into intra- and inter-molecular interactions at an atomistic level

7.  Replica Exchange MD
Schematic of replica exchange molecular dynamics
 Allows for larger conformational searches by utilizing independent realizations of a
system, known as replicas.
 Each replica is coupled to a different thermostat temperature. Replicas are exchanged
at regular time intervals, effectively allowing conformations to escape low temperature
kinetic traps by “jumping” to alternate minima being sampled at higher temperatures

8. METHODOLOGY