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J Med Oncl Ther 2017 Volume 2 | Issue 3
International Conference on
Oncology and Cancer Therapeutics
October 30- November 01, 2017 | Chicago, USA
Hidden correlations and symmetries determine per-residue interaction free energy contributions of
protein: Small molecule/biomolecule binding
Lawrence J Williams
Rutgers University, USA
P rotein interaction free energy is the lynchpin to
understanding, identifying, and targeting cancer. Despite
the common practice of describing key interactions in terms
of ionic, polar, hydrogen bonding, and hydrophobic contacts,
the interactions are too numerous, varied, weak and delicately
balanced to allow meaningful prediction of per-residue
contributions to interaction free energy. All-atom physics-
based (molecular dynamics and free energy perturbation)
simulations have struggled to provide per-residue
contributions as well. The ideas presented here constitute
an alternative physics-based approach to describe protein
interaction energies without resorting to atomistic methods
or rationales. Dilation symmetry, simple accommodations of
protein backbone fluctuations and renormalization-based
approaches provide a straight forward description of the
individual and correlated effects of per-residue contributions
to interaction free energy. This approach enables protein
residues to be mapped according to how ‘hot’ or ‘sticky’ each
residue is. Protein interiors are dominated by hot residues
and exteriors are dominated by cool residues. Hot patches on
protein surfaces correspond to the substrate binding surfaces
of enzymes (Bcl kinase), protein-protein interfaces (Mcl-1/
Bim), and protein-peptide interfaces (MHCs). Additionally,
the model can be used to classify mutations as primarily
impacting ground state conformations (Class I mutation) or
ground and/or excited state conformations (Class II mutation)
and to compute protein stability (ddG, lysozyme). The data
suggest that sequence space – so abundant in the wake of
the genomic revolution – can be converted into energy space
and that it may be possible to navigate and interpret genomic
and protein structure data directly in terms of interaction
energy signatures.
Speaker Biography
Lawrence J Williams completed his PhD at the University of Arizona and held Post-
doctoral fellowships at MIT and Memorial Sloan-Kettering where he studied molecular
structure and synthesis of natural and engineered peptides and tumor-associated
glycopeptides for immune activation. His independent research has focused on
developing synthetic methods and strategies to understand structure, reactivity,
materials and biological function of complex organic molecules, especially natural
products, peptides and proteins. Recently, he has worked in the fields of antibody drug
conjugates, biomarker diagnostics and protein biophysics.
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