CASE STUDY

Predictionof Moisture
Adsorption
and Effects onAmorphousAmylose Starch
Molecular Dynamics simulations accelerate
optimization of product quality and processing
for food and beverage, packaging, andpharmaceutical applications.

Executive Summary• Accurately predicted key physicalproperties such as glass transition
temperature (Tg) for both wet and dry
amorphous amylose polymers• Effectively modeled water uptake andtransport by investigating the effect ofmoisture content on Tg and water diffusion
in starch polymers• OPLS3e force field provided high accuracy
for amorphous starch models• Further studies proposed on in-depth
water-amylose interactions and the effects ofingredients on complex starch formulation

Challenges

Approach

As amorphous starch is highly attractive
for applications in thermoplastics and foodencapsulation, understanding its functionality
is a high priority for R&D scientists in severalindustries. Key to starch functionality is theinteraction between water and starch granules.
Numerous studies have focused on understanding
the microstructure and the underlying
nanostructure of starch, however a thoroughunderstanding of the molecular structures ofnative and amorphous granules is challenging tocharacterize experimentally. This results in:Scientists at Schrödinger aimed to solve thesechallenges by using molecular simulationtechniques, specifically molecular dynamics(MD) simulations.1 All models and simulations
were performed using the Schrödinger Materials
Science Suite. These methods predicted water
uptake at a given temperature and relative
humidity condition and also allowed for tracking ofwater transport in the starch polymer matrix.

• Lack of high resolution, atomic levelstructural characterizations• Lack of morphological or thermophysicalproperties of amorphous starch• Lack of dynamic properties of amorphousstarch in solvent

Seamless Workflow with Schrödinger’s Intuitive
Modeling Platform for Materials Science01

0203

Build model sytems

Run MD equilibrium

Solvate maltose molecules
and amylose polymers
with water, and build
independent amorphous
amylose systems with varied
degrees of polymerization

Equilibrate and relax maltose
and amylose polymersystems, followed by a short
set of simulations

Characterize
conformational preferences
Employ enhanced samplingtechniques that use
Desmond’s metadynamics
workflow to characterize theconformational preferencesof maltose and amylosemolecules

040506

Simulate moisture uptake

Calculate water transport

Penetrant loading simulations
were performed at different
relative humidities (RH) togenerate water absorption
isotherm and at different
temperatures to predictwater uptake

Water diffusion coefficientswere calculated inamorphous starch by the
Einstein relation and theaverage diffusion coefficient
was used to calculate theactivation energy (Ea)

Predict glass transition
temperature
Predict system density versus
temperature by simulated
annealing simulations at aconstant cooling rate. Auto-fit
density versus temperature toestimate Tg

2

Results
MD simulations have greatly improved ourunderstanding of amylose molecules in solution
and bulk phase and have led to rapid predictionof key physical properties such as Tg.
• The results illustrate the plasticization effectof moisture content on amorphous starch.
Predicted glass transition temperature (Tg)
depression as a function of moisture content
is in line with experimental trends and allows
prediction of the previously inaccessible dry
Tg of amorphous starch.

A)• Using combined grand canonical Monte Carlo(GCMC)/MD simulations, a moisture sorption
isotherm curve is predicted along withtemperature dependence. Concentrationdependent activation energies for watertransport agree quantitatively withprevious experiments.
• The modern OPLS3e force field and welltempered metadynamics provided highly
accurate prediction of dynamical properties
and conformations for amorphous starchpolymers in addition to solution behavior.

B)

Plasticization effects of water on amorphous DP31 amylose. A) Density versus temperature plots of dry and 11 % moisture content DP31 using a
0.67 ns/K cooling rate. B) Tg as a function of moisture content. Blue data points represent the average of five independent systems. Orange datapoints are experimental values reported in (Ai & Jane, 2018).*3

What’s Next?
• Further studies can explore in-depth water-amylose interactions
and the effects of other commonly used ingredients in starch
formulations, for example emulsifiers, which are known to bind toamylose molecules.
• Future work can be performed to understand the morphology ofcomplex amorphous and/or semi-crystalline starch formulations andhow morphology affects transport and thermomechanical properties.

References
1. Jeffrey M.Sanders, Mayank Misra, Thomas J.L.Mustard, DavidJ.Giesen, Teng Zhang, John Shelley, Mathew D.Halls, “Characterizing
moisture uptake and plasticization effects of water on amorphous
amylose starch models using molecular dynamics methods”,
Carbohydrate Polymers, 252, 2021, 117161.
*The figures were published in the referenced paper. Copyright Elsevier

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