Understanding and Controlling Protein Stability from Coarse-Grained
Marco A. Blanco
National Institute of
Standards and Technology, Gaithersburg, MD 20899
Bioscience and Biotechnology Research, University of Maryland, Rockville, MD
Protein-based therapeutics represents one of the fastest
growing markets in pharmaceutical industry. The high efficacy and specificity
of biotherapeutics make them valuable for targeting
different type of illnesses. Nonetheless, most, if not all, proteins present a very wide range of
behaviors that limit the development of commercially viable products. Small
changes in the protein sequence and formulation conditions may cause conformational
and physical instabilities that lead to the self-assembly of proteins (e.g., fluid
phase separation, oligomerization, and irreversible
aggregation). These stability concerns constitute the primary route for the
formation of impurities in biotherapeutics, as well
as may induce unfavorable immunologic responses in patients. The ability to
accurately and unambiguously predict the behavior of proteins in solution will
help control instability problems via an adequate design of proteins and
selection of formulation conditions.
research work has focused on understanding the stability of proteins in
solution via simple but realistic coarse-grained computational models, which
are combined with biomolecular and biophysical
experiments (e.g., mutagenesis, chromatography, calorimetry,
scattering) to provide both refinement and validation. By implementing advanced
Monte Carlo and Molecular Dynamics techniques, these models allow one to
evaluate the thermodynamic pathways by which proteins are destabilized, which
might be otherwise challenging to probe due to the generally short-living
nature of most of the key species in those processes. Thus, the resulting
models provide powerful, physics-based tools to assess how different factors
(e.g., pH, excipients, protein structure) affect those phenomena that cause
instability in proteins such as phase separation, protein unfolding, and
nonnative aggregation; moreover, they offer guidelines for rationally designing/selecting proteins with higher physical stability.
Blanco laboratory will built on the use of both computational and experimental methods
applied to topics within the general theme of protein stability, engineering,
and self-assembly. A specific emphasis will be placed on developing new and improved
theoretical models and experimental techniques to predict the conformational
and solution stability of proteins and peptides, and thus to gain insights
regarding how the local structure and surrounding molecular environment influence
the underlying mechanisms associated to physical degradation of proteins. Such
predicting methods will have direct application in fields such as biomedicine
(e.g., elucidating critical stages during amyloidosis), drug discovery (e.g.,
rational design of high-affinity peptide-based drugs), drug development (e.g.,
identifying optimal formulation and manufacturing conditions for biopharmaceutics), and biomaterials (e.g., developing
“smart” protein-based materials with controllable self-assembly properties).
Since research in these fields encompasses various disciplines, there will be
strong collaborations from both academy and pharmaceutical industry.
addition to my research career, I have also gained significant teaching
experience. I lectured an undergraduate course at the Industrial University of Santander
in Colombia about the implementation of statistical and quantum mechanical
computational methods to thermodynamics and transport phenomena problems related
to Chemical Engineering. I also TAed thermodynamics
courses at both undergraduate and graduate level, as well as mentored
undergraduate students and visiting scholars about application of molecular
simulations to protein systems.
background in protein science and chemical engineering, my teaching interests
extend in undergraduate core chemical engineering courses that include
thermodynamics, heat and mass transfer, chemical kinetics, and applied math. Furthermore,
I would also like to develop and teach undergraduate- and graduate-level
courses in topics such as protein engineering, statistical thermodynamics
applied to chemical engineering, and computational and experimental methods for
Protein-Protein interaction via Scattering Experiments from Low to High Protein
the Effect of Solution Conditions and Protein Sequence on the Cluster Formation
Algorithm for Predicting Amyloidosis and Protein β-Aggregation”
Behavior and Aggregation Propensity of Peptide-Polyacrylic
Supervised by Christopher J. Roberts, Department of Chemical
and Biomolecular Engineering, University of Delaware.
Specific Interactions on the Fluid Phase Behavior and Self-Assembly of Proteins
of the Solution Structure and Phase Behavior of Monoclonal Antibodies via
Electrostatic Interactions on the Oligomerization and
Amyloid Formation of the Cardiomyopathy-Related Protein Transthyretin”
Supervised by Vincent K. Shen and Zvi Kelman, National Institute of
Standards and Technology and Institute for Bioscience and Biotechnology Research,
University of Maryland.
Blanco, Erinc Sahin,
Anne S. Robinson, and Christopher J. Roberts. “Coarse-grained model for colloidal protein interactions, B22,
and protein cluster formation”. J. Phys. Chem. B, 117, 16013 (2013).
2. Marco A. Blanco, Tatiana Perevozchikova, Vincenzo Martorana,
Mauro Manno, and Christopher J. Roberts. “Protein-protein interactions in dilute to
concentrated solutions: a-Chymotrypsinogen
in acidic conditions”. J. Phys. Chem. B, 118, 5817 (2014).
Paik, Marco A. Blanco, Xinqiao Jia, Christopher J.
Roberts, and Kristi Kiick. “Aggregation of poly(acrylic acid)-containing
elastin-mimetic copolymers”. Soft Matter, 11, 1839 (2015).
Blanco and Vincent K. Shen. “Effect of the surface charge distribution on the fluid phase behavior
of charged colloids and proteins”. J. Chem. Phys. [submitted].