Department of Biochemistry and Molecular Biology
RBHS, Robert Wood Johnson Medical School

Ph.D., 2001, Johns Hopkins University
Telephone: (848) 445-9810
Fax: (732) 235-4850

Molecular Bioscience Site
Personal Site

Computational protein design, biomaterials, molecular evolution

Our group is interested in constructing new proteins for applications in biomedical research, nanotechnology and as tools for understanding how proteins fold and evolve. Significant progress has been made in the last decade using sophisticated computer programs to design proteins with novel folds and functions. We maintain and develop software for protein design, structure prediction and docking of protein-ligand complexes. Several design projects our group pursues include the computational design of an extracellular matrix, thermostabilization of peptide therapeutics with D-amino acids and prediction of allergenicity of food proteins.

The extracellular matrix (ECM) is a complex network of collagens, laminins, fibronectins and proteoglycans that provides a surface upon which cells can adhere, differentiate and proliferate. Defects in the ECM are the underlying cause of a wide spectrum of diseases. The ECM mediates endothelial cell polarity and under normal conditions can suppress pre-oncogenic transitions to a neoplastic state. We are constructing artificial, de novo collagen-based matrices using a hierarchic computational approach. These matrices are physically characterized in the laboratory and used to probe the role of chemical and spatial organization in the ECM on the tumor forming potential of adhered cells.

Peptides are an emergent and important class of therapeutics with over forty compounds on the market and nearly 700 more in clinical or pre-clinical trials. During the development of peptide drugs, D-enantiomers of amino acids are frequently incorporated to improve pharmacokinetic and pharmacodynamic properties by lowering susceptibility to proteolysis. Typically, such modifications are introduced in lead compounds by trial-and-error or combinatorial approaches. Our laboratory is developing software to simulate the impact of non-natural amino acids on structure and stability. Using fundamental principles of protein design, we will pursue the computational, structure-based development of peptides with variable chirality, broadly extending our capacity to create safe and potent therapeutics.

A crucial and unanswered question in the field of food allergy research is why certain proteins elicit an IgE mediated immune response, while others are tolerated. One compelling hypothesis is that non-allergens are more digestible, resulting in sufficient protein degradation in the stomach and intestine to render the remaining fragments immunologically inert. Despite efforts to contrast the proteolytic stability of allergens and non-allergens, a clear link between digestibility and allergenicity has yet to be established. Confounding variables such as interactions with other components in the food matrix, cross-reactivity with other allergens, or the pathway of sensitization (e.g. alimentary canal versus respiratory tract) complicate the interpretation of experimental outcomes. We are developing a highly defined system for exploring the relationship between digestibility and allergenicity. We hypothesize that the digestibility of a protein is dependent on its stability under acidic (pH less than 3.0) conditions. Using shrimp tropomyosin as a model system, we will computationally design acid sensitive variants that are rapidly proteolyzed in gastric fluid. These mutants will provide optimal reagents for comparative studies relating pH-stability to digestibility and eventually to allergenicity.

Figure 1. Computational design of peptide drug stabilizing mutations. Starting with the three dimensional structure of the 20-residue mini-protein, the Trp Cage, a D-amino acid is inserted and conformationally sampled (left). The predicted conformation participates a network of stabilizing hydrogen bonds (middle) and favorable interactions with surrounding water (right). Computational design of D-amino acids is a promising strategy for enhancing pharmacological properties of peptide therapeutics.

Selected Publications

Parmar AS, James JK, Grisham DR, Pike DH, Nanda V. (2016) Dissecting electrostatic contributions to folding and self-assembly using designed multicomponent peptide systems. J Am Chem Soc 138:4362-7

Nanda V, Senn S, Pike DH, Rodriguez-Granillo A, Hansen WA, Khare SD, Noy D. (2016) Structural principles for computational and de novo design of 4Fe-4S metalloproteins. Biochim Biophys Acta 1857:531-8

Stapleton JA, Whitehead TA, Nanda V. (2015) Computational redesign of the lipid-facing surface of the outer membrane protein OmpA. Proc Natl Acad Sci USA 112:9632-7

Parmar AS, Xu F, Pike DH, Belure SV, Hasan NF, Drzewiecki KE, Shreiber DI, Nanda V. (2015) Metal stabilization of collagen and de novo designed mimetic peptides. Biochemistry 54:4987-97

McGuinness K, Khan IJ, Nanda V. (2014) Morphological diversity and polymorphism of self-assembling collagen peptides controlled by length of hydrophobic domains. ACS Nano 8:12514-23

Kim JD, Yee N, Nanda V, Falkowski PG. (2013) Anoxic photochemical oxidation of siderite generates molecular hydrogen and iron oxides. Proc Natl Acad Sci USA 110:10073-7

Xu F, Khan IJ, McGuinness K, Parmar AS, Silva T, Murthy NS, Nanda V. (2013) Self-assembly of left and right-handed molecular screws. J Am Chem Soc 135:18762-5

Xu F, Li J, Jain V, Tu RS, Huang Q, Nanda V. (2012) Compositional control of higher order assembly using synthetic collagen peptides. J Am Chem Soc 134:47-50

Kim JD, Rodriguez-Granillo A, Case DA, Nanda V, Falkowski PG. (2012) Energetic selection of topology in ferredoxins. PLoS Comput Biol 8:e1002463

Xu F, Zahid S, Silva T, Nanda V. (2011) Computational design of a collagen A:B:C-type heterotrimer. J Am Chem Soc 133:15260-3

Rodriguez-Granillo A, Annavarapu S, Zhang L, Koder RL, Nanda V. (2011) Computational design of thermostabilizing D-amino acid substitutions. J Am Chem Soc 133:18750-9

Nanda V, Koder RL. (2010) Designing artificial enzymes by intuition and computation. Nat Chem 2:15-24