Assistant Professor of Chemical Engineering
809 SW Mudd, Mail Code: 4721
Phone: +1 212 854 7260
Fax: +1 212-854-3054
Ph.D., Chemical and Biomolecular Engineering, University of Pennsylvania, 2007.
B.S.E, Chemical Engineering, University of Puerto Rico, Mayagüez Campus, 2002.
Our primary research interests reside in the development and application of advanced multi-scale computational modeling techniques for the study of biological macromolecules. The goal is to provide insight into the mechanisms by which macromolecules communicate with each other to drive assembly and signal propagation through the cell. This type of information can provide guidance for development of better and more efficient biomedical therapies and sensing technologies.
A multi-scale computational approach for the study of nucleic-acid-based systems
The use of nucleic acids for templating directed organization of nanomaterials, including biomolecules, templating of inorganics, and approaches combining preformed and template materials has placed nucleic acids in a starring role in the areas of nanotechnology and materials. These new technologies have great potential to solve many problems that we currently face in areas as diverse as biology and medicine and materials science but, for some of them, development is hindered by a lack of understanding of the molecular level interactions that drive the required organization and assembly. In addition, when modeling DNA, one faces the issue that length-scales can vary immensely depending on the type of interactions considered. For example, DNA-nanotube systems can be in the Angstrom-to-nanometer scale when studying the interactions between nucleic–acid bases and carbon rings, and in the micrometer range when studying the wrapping of DNA around the nanotube. We use a multi-scale hierarchical modeling approach, rooted in the use of advanced, state-of-the-art sampling methods, to investigate the behavior of nucleic acids in solution and when in contact with other macromolecules (proteins, nanotubes), surfaces or assemblies (membranes). Results from these studies will address a range of problems that these technologies face, and predict and suggest ways to improve and make them more efficient.
Quantifying Signal Propagation and Conformational Changes in Allosteric Proteins
Allostery connects subtle changes in a protein's potential energy surface to significant changes in its function. Understanding this phenomenon and predicting its occurrence are major goals of current research in biophysics and molecular biology, and particularly in drug discovery. At the microscopic level, protein energetics is characterized by a balance between different inter-atomic interactions, with small perturbations at specific sites potentially leading to major changes in conformational distributions. Therefore, a thorough characterization of allostery requires understanding of two aspects: (1) how signals propagates through the protein structure, and (2) which regions of the protein are likely to suffer structural deformations as a response to the applied perturbation. On the first aspect, we have developed a new energy-based network analysis method, which allows characterization of signaling pathways in proteins. The method assumes that signals travel more efficiently through residues that have strong inter-atomic interactions, and is able to correctly identify important residues for allosteric signal propagation in several proteins. On the second aspect, we currently work on developing methods that calculate and analyze protein maps of atomic elastic constants to highlight regions that are particularly prone to suffer structural deformation, and are experimentally linked to allosteric function. The combined information from these methods will allow predictions of a protein’s response to a stimulus such as drug binding.
Ribeiro AAST and Ortiz V, “A Chemical Perspective on Allostery”, Chem. Rev., (2016), doi: 10.1021/acs.chemrev.5b00543
Ribeiro AAST and Ortiz V, “MDN: A Web Portal for Network Analysis of Molecular Dynamics Simulations”, Biophys. J., 109, 1 (2015), doi:10.1016/j.bpj.2015.06.013
Ribeiro AAST and Ortiz V, “Local Elastic Constants of LacI and Implications for Allostery”, J. Mol. Graph., 57, 106 (2015), doi:10.1016/j.jmgm.2015.01.013
Ribeiro AAST and Ortiz V, “Energy Propagation and Network Energetic Coupling in Proteins”, J. Phys. Chem. B, 119, 1835 (2015), doi:10.1021/jp509906m
Ribeiro AAST and Ortiz V, “Determination of signaling pathways in proteins through network theory: importance of the topology”, J. Chem. Theory Comput., 10 1762 (2014), doi:10.1021/ct400977r
Collier G and Ortiz V, “Emerging Computational Approaches for the Study of Protein Allostery”, Arch. Biochem. Biophys., 538 6 (2013), doi:10.1016/j.abb.2013.07.025
Ortiz V and de Pablo JJ, “Molecular origins of DNA flexibility: Sequence effects on conformational and mechanical properties”, Phys. Rev. Lett., 106 238107 (2011), doi:10.1103/PhysRevLett.106.238107
Ortiz V, Nielsen SO, Discher DE, and Klein ML, Lipowsky R, and Shillcock J, "Dissipative particle dynamics simulations of polymersomes", J. Phys. Chem. B, 109 17708 (2005), doi:10.1021/jp0512762
Ortiz V, Nielsen SO, Klein ML, and Discher DE, "Unfolding a linker between helical repeats", J. Mol. Biol., 349 638 (2005), doi:10.1016/j.jmb.2005.03.086