242
P. Volarath et al.
and George Oster), Simcyp (provided by Simcyp Limited based in Sheffield, UK),
and GastroPlus (provided by Simulations Plus based in Lancaster, CA).
More recently, biological response has been incorporated into PBTK modeling,
which is referred to as biologically based dose response (BBDR) modeling. BBDR
modeling assumes that a toxic response is a function of the concentration of the
substance in the target tissue and describes a biological response or any mechanism
related to toxicity. A BBDR model was developed by McLanahan et al. (2008)
for dietary iodide and the hypothalamic–pituitary–thyroid (HPT) axis in adult rats.
The BDDR-HPT model [43] consisted of submodels for dietary iodide, thyroidstimulating hormone (TSH), and thyroid hormones T 3 and T 4 . The key biological
processes described in the model included the influence of T 4 on TSH production,
stimulation of thyroidal T 4 and T 3 production by TSH, TSH upregulation of the
thyroid sodium/iodide symporter, and recycling of iodide from metabolism of thyroid
hormones. This model predicted effects on the HPT axis caused by insufficient dietary
iodide intake and successfully simulated perturbations in serum T 4 when compared
with experimental results. This BDDR-HPT axis model [43] provides a strong basis
for use in conjunction with PBTK models for thyroid-active chemicals to evaluate
and predict dose-dependent HPT alterations based on modes of action [44, 45].
12.2.3 Bioinformatic Approaches for Analysis of Potential
Allergenicity of Proteins
The allergenicity potential is an essential aspect of assessing the safety of food ingredients that have protein components. Since most food allergies are mediated through
immunoglobulin E (IgE) which reacts with specific linear or conformational epitopes,
the degree of amino acid (AA) sequence similarities between the query protein and
known allergens could be used to predict the likelihood of the query protein to induce
a cross-reactivity through IgE binding [46]. OFAS refers to the guideline of Codex
Alimentarius (Codex) [47, 48] that describes the principles of AA sequence-based
bioinformatic analysis as one of the first steps in allergenicity risk assessment. Bioinformatic tools for AA sequence alignment and similarity comparisons are commonly
used in OFAS as one of the criteria to predict the potential allergenicity risk of food
ingredients with protein components, including direct additives such as phycocyanins
in the color additive spirulina extract, microbially derived food processing enzymes,
and food proteins from genetically engineered plants.
12.2.3.1 Allergenic Protein Database
As the first step in their allergenicity risk assessments, the Codex recommends that
the AA sequence of a query protein be compared against all scientifically known
allergens. Thus, the predictivity of the bioinformatic methods relies on the collec-
P. Volarath et al.
and George Oster), Simcyp (provided by Simcyp Limited based in Sheffield, UK),
and GastroPlus (provided by Simulations Plus based in Lancaster, CA).
More recently, biological response has been incorporated into PBTK modeling,
which is referred to as biologically based dose response (BBDR) modeling. BBDR
modeling assumes that a toxic response is a function of the concentration of the
substance in the target tissue and describes a biological response or any mechanism
related to toxicity. A BBDR model was developed by McLanahan et al. (2008)
for dietary iodide and the hypothalamic–pituitary–thyroid (HPT) axis in adult rats.
The BDDR-HPT model [43] consisted of submodels for dietary iodide, thyroidstimulating hormone (TSH), and thyroid hormones T 3 and T 4 . The key biological
processes described in the model included the influence of T 4 on TSH production,
stimulation of thyroidal T 4 and T 3 production by TSH, TSH upregulation of the
thyroid sodium/iodide symporter, and recycling of iodide from metabolism of thyroid
hormones. This model predicted effects on the HPT axis caused by insufficient dietary
iodide intake and successfully simulated perturbations in serum T 4 when compared
with experimental results. This BDDR-HPT axis model [43] provides a strong basis
for use in conjunction with PBTK models for thyroid-active chemicals to evaluate
and predict dose-dependent HPT alterations based on modes of action [44, 45].
12.2.3 Bioinformatic Approaches for Analysis of Potential
Allergenicity of Proteins
The allergenicity potential is an essential aspect of assessing the safety of food ingredients that have protein components. Since most food allergies are mediated through
immunoglobulin E (IgE) which reacts with specific linear or conformational epitopes,
the degree of amino acid (AA) sequence similarities between the query protein and
known allergens could be used to predict the likelihood of the query protein to induce
a cross-reactivity through IgE binding [46]. OFAS refers to the guideline of Codex
Alimentarius (Codex) [47, 48] that describes the principles of AA sequence-based
bioinformatic analysis as one of the first steps in allergenicity risk assessment. Bioinformatic tools for AA sequence alignment and similarity comparisons are commonly
used in OFAS as one of the criteria to predict the potential allergenicity risk of food
ingredients with protein components, including direct additives such as phycocyanins
in the color additive spirulina extract, microbially derived food processing enzymes,
and food proteins from genetically engineered plants.
12.2.3.1 Allergenic Protein Database
As the first step in their allergenicity risk assessments, the Codex recommends that
the AA sequence of a query protein be compared against all scientifically known
allergens. Thus, the predictivity of the bioinformatic methods relies on the collec-