Protein Engineering

Peters Research Group


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College of Engineering Faculty Profile

Affiliated Centers
Massey Cancer Center
Center for the Study of Biological Complexity

 

 

 

 

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Our research spans from detailed biomolecular computations and mathematical methods to experimental studies, including preclinical and laboratory experiments.  Our goals are to apply fundamental concepts in science, engineering, and mathematics to solve contemporary problems across the physical and life sciences. 

Our overall research topics fall into several main categories

1. Protein-Protein Interactions

We have developed an all-atom energy landscape mapping tool for protein-protein interactions, which we called OpenContact.  This open-source computational tool allows the determination of the most dominant atom-atom interactions among the residues of protein-protein binding partners.  It has been successfully used to determine druggable "hot spots" and to design peptide biomimetics aimed at disrupting aberrant interactions.  Recently, it has been used to study the fundamental binding behavior of amyloid beta fibrils present in Alzheimer's disease, and it is currently being used to design small molecule inhibitors to the fibril formation process.  The OpenContact computational package is compiled and wrapped in a Python GUI making it a user friendly open-source tool with no user knowledge required of the details of the all-atom biomolecular computations.

The OpenContact page for downloads and information on use is given below.  OpenContact is also available world-wide through the Protein Data Bank (PDB) under their third party software tools repository and, as a fully compiled code under Windows O.S., it runs locally on any PC desktop.   The current open source license for OpenContact is the popular Sleepy Cat license.  The site link below includes a READ ME file for its use as well as all source codes and force field data parameter files for the interested user. We also added plotting and spread sheet features to aid the user in interpretation and further analysis of output results.  The plotting feature, which uses the open source Matplotlib, generates "heat" maps that "light up" the dominant interaction sites.  The user can also "lower the energetic ceiling" in order to hone in on dominant interactions, such as hydrogen bonding sites.

Download OpenContact.zip By downloading this software you are agreeing to the license condition OpenContact_License Citation for OpenContact Krall A, Brunn J, Kankanala S, Peters MH. 2014. A simple contact mapping algorithm for identifying potential peptide mimetics in protein-protein interaction partners. Proteins: Structure, Function, and Bioinformatics 82(9):2253-62. Article first published online: 14 MAY 2014 | DOI: 10.1002/prot.24592 This article is OpenAccess at http://onlinelibrary.wiley.com/enhanced/doi/10.1002/prot.24592/

Beta-Release of OpenContact V3.0, which includes DNA-Protein Interactions, is scheduled for this Fall 2020

Bastidas,O.H., Green, B., Sprague, M., and Peters, M.H, Few  Ramachandran Angle Changes Provide Interaction Strength Increase in Aβ42 versus Aβ40 Amyloid Fibrils, Sci. Rep., 6, 36499 (2016). DOI: 10.1038/srep36499.

 

Krall,A., Brunn, J., Kankanala, S., and Peters, M.H. (2014). A Simple Contact Mapping Algorithm for   Indentifying Peptide Mimetics in Protein-Protein Interaction Partners. Proteins. Structure, Function, and Bioinformatics, 82, 2253-2262.

 

Other research areas of Protein-Protein Interactions by our group include:

dynamics of PPI’s via implicit solvent methods

The study of protein flexibility or dynamic protein conformational changes is critically important to the understanding of protein function including, for example, folding/misfolding, ligand-receptor signaling, enzymatic reactions, and protein-DNA interactions, to name a few.

We have developed an Implicit Solvent method for the study of biological molecular flexibility and conformational changes.  Briefly, the implicit solvent method is based on an all-atom approach that utilizes three important elements: 1) the physical and electrostatic effects of water molecules are averaged and thus not treated explicitly, 2) inter-atomic interaction forces associated with the protein are based on established force field models, and 3) protein atomic displacement trajectories are calculated based on integration of the Langevin equation that rigorously follow from the N-body Liouville equation noted above.  The first element involves a short-time averaging of the host solvent dynamics leading to implicit solvent functions such as position dependent dielectric constant, apolar implicit solvent forces and diffusion tensors for the protein ligands or subunits (Fig. 2).  The second element is accomplished via all atom force-field which accounts for the charge and polar (Coulombic) and non-polar (Lennard-Jones or LJ) atom-atom interactions.  The third element involves considering both deterministic and stochastic effects of Brownian motion of the solute or ligand induced by the presence of the solvent as they are prescribed in the Langevin equation. 

Peters, M.H.  (2011). Langevin Dynamics for the Transport of Flexible Biological Macromolecules in Confined Geometries, J. Chem. Phys., 134, 025105 (1-11).

 

fragment discovery algorithms

Infectious disease from viral agents continues to represent one of the most significant health threats to society. The ability of these agents to mutate, transform, and develop across species makes them a formidable opponent to the development of therapeutics, diagnostics, and vaccines aimed at their debilitation. The development of vaccines to emerging forms of viral agents represents a methodical and coordinated response to reduce outbreaks and pandemics.  However, the speed at which vaccines can be developed and produced on a large, global scale across a spectrum of ever-changing pathogens is a significant drawback to their use.  Here we take a radically different large-scale, multiprocessor computational approach based on a fragment discovery and annealing algorithm to generate small molecule, designer peptide candidates for specific antigen recognition.  In turn, promising computationally designed peptide candidates can be further studied experimentally and potentially produced on a large scale through modern, relatively low-cost recombinant and ex-vivo peptide production methods.

 

Peters, M.H., Targeting HIV-1 Envelop Proteins Using a Fragment discovery All-Atom Computational Algorithm, Current Enzyme Inhibition, 13, 1-7 (2017).  DOI: 10.2174/1573408012666160725095854.

protein folding

When nascent proteins are manufactured in cellular ribosomes, they quickly “fold” or collapse into structures that are responsible for their particular function.  For example, the protein may fold to expose a particular segment or set of residues to the “outside world” that leads to its function or role as a self-recognition element.  Folding must be precise even though the overall structure appears highly chaotic (twisted like a telephone cord).  We are using IS methods to attempt to tackle the protein folding problem and sort out the essential dynamic elements that are necessary to accomplish this “order out of chaos” state.

2.  Drug Development:  Alzheimer’s Disease and Inhibiting Apoptotic Pathways in Cancer

a-beta amyloid plaque inhibitors

We have used our detailed energy mappings to develop small molecular weight peptides that both disrupt the oligomer/fibril formation process by binding to key adhesive contact points in the Aβ42 monomers but also have the potential to cross the so-called blood brain barrier (BBB).  We have carried out numerous in-vitro studies that demonstrate the potential of these inhibitors at treating AD, and we have furthered our mechanistic understandings of amyloid fibril formation through dynamic biomolecular computational studies.

anti-apoptotic inhibitors in cancer

World-wide, an estimated 500,000 women die each year from breast cancer.  Chemotherapeutic agents in the treatment of breast cancer are based on the particular cancer cell type, such as drugs that specifically target the HER2 protein for HER2-positive breast cancers.  Breast cancers can develop chemo-resistance through the blocking of cell death pathways, such as the blocking of apoptotic pathways (anti-apoptotic behavior).

We have developed a potential, novel peptide inhibitor to Bcl-2 Associated Anthanogen (BAG-1) which is associated with anti-apoptotic pathways prevalent in a variety of cancer cell types including, most notably, breast cancers.  An all-atom, dominant energy landscape mapping of BAG-1 to its HSP-70/HSC-70 (Heat Shock Protein 70 and its conjugate) binding partner identified a helical peptide segment from the binding domain of HSC-70.  Experimental kinetic binding studies demonstrated that this peptide binds to BAG-1 in the pico-molar range.  Subsequently, we augmented the helical peptide with a poly-arginine CPP (cell penetrating peptide) and demonstrated dose-dependent increases in apoptosis in a number of hematological cancer cell lines and primary patient AML cells. 

BAG-1 could be a critical target in multimode chemotherapeutic approaches aimed at breast cancer.  In fact, BAG-1 inhibition via knockdown studies was recently demonstrated to synergistically enhance the effects of Trastuzumab in HER2 positive breast cancer cell lines

3.  Statistical Mechanics and Foundations of the Second Law

We also work in fundamental areas of science and mathematics in addition to the applied areas described above.  Our fundamental research includes the molecular foundations of the Second Law of Thermodynamics (entropy) and fundamental aspects of statistical mechanics (perturbation theory).

Peters, M.H., Generalized Entropy Generation Expressions in Gases Entropy 2019, 21, 330; doi:10.3390/e21040330

 

Peters, M. H., Molecular Thermodynamics and Transport Phenomena.  Complexities of Scales in Space and Time, McGraw-Hill, NY, 2005.



Contact: mpeters@vcu.edu

601 West Main Street
Department of Chemical
and Life Science Engineering
Virginia Commonwealth University, Richmond, VA 23284
804-828-7790