Biomedical subjects

Shannon A Marshall

Publications and source records attributed to Shannon A Marshall.

7 recordsLinked to original sources

PubMed2006

Simple electrostatic model improves designed protein sequences.

Electrostatic interactions are important for both protein stability and function, including binding and catalysis. As protein design moves into these areas, an accurate description of electrostatic energy becomes necessary. Here, we show that a simple distance-dependent Coulombic function parameterized by a comparison to Poisson-Boltzmann calculations is able to capture some of these electrostatic interactions. Specifically, all three helix N-capping interactions in the engrailed homeodomain fold are recovered using the newly parameterized model. The stability of this designed protein is similar to a protein forced by sequence restriction to have beneficial electrostatic interactions.

Amino Acid Sequence↗

PubMed2005

One- and two-body decomposable Poisson-Boltzmann methods for protein design calculations.

Successfully modeling electrostatic interactions is one of the key factors required for the computational design of proteins with desired physical, chemical, and biological properties. In this paper, we present formulations of the finite difference Poisson-Boltzmann (FDPB) model that are pairwise decomposable by side chain. These methods use reduced representations of the protein structure based on the backbone and one or two side chains in order to approximate the dielectric environment in and around the protein. For the desolvation of polar side chains, the two-body model has a 0.64 kcal/mol RMSD compared to FDPB calculations performed using the full representation of the protein structure. Screened Coulombic interaction energies between side chains are approximated with an RMSD of 0.13 kcal/mol. The methods presented here are compatible with the computational demands of protein design calculations and produce energies that are very similar to the results of traditional FDPB calculations.

Poisson Distribution↗

PubMed2004

Minimizing the immunogenicity of protein therapeutics.

As is cautioned in many package inserts, 'with all therapeutic proteins, there is a potential for immunogenicity'. Immunogenicity problems in humans, which currently can be detected only in clinical trials or after product launch, pose a significant barrier to the development and acceptance of protein drugs. Recent and ongoing research, presented in this review, seeks to address the challenge of protein therapeutic immunogenicity by elucidating the mechanisms underlying immune recognition of protein therapeutics, establishing preclinical methods for assessing immunogenicity and developing strategies for minimizing immune responses.

Animals↗

PubMed2003

NMR and temperature-jump measurements of de novo designed proteins demonstrate rapid folding in the absence of explicit selection for kinetics.

We address the importance of natural selection in the origin and maintenance of rapid protein folding by experimentally characterizing the folding kinetics of two de novo designed proteins, NC3-NCAP and ENH-FSM1. These 51 residue proteins, which adopt the helix-turn-helix homeodomain fold, share as few as 12 residues in common with their most closely related natural analog. Despite the replacement of up to 3/4 of their residues by a computer algorithm optimizing only thermodynamic properties, the designed proteins fold as fast or faster than the 35,000 s(-1) observed for the closest natural analog. Thus these de novo designed proteins, which were produced in the complete absence of selective pressures or design constraints explicitly aimed at ensuring rapid folding, are among the most rapidly folding proteins reported to date.

Algorithms↗

PubMed2003

Rational design and engineering of therapeutic proteins.

An increasing number of engineered protein therapeutics are currently being developed, tested in clinical trials and marketed for use. Many of these proteins arose out of hit-and-miss efforts to discover specific mutations, fusion partners or chemical modifications that confer desired properties. Through these efforts, several useful strategies have emerged for rational optimization of therapeutic candidates. The controlled manipulation of the physical, chemical and biological properties of proteins enabled by structure-based simulation is now being used to refine established rational engineering approaches and to advance new strategies. These methods provide clear, hypothesis-driven routes to solve problems that plague many proteins and to create novel mechanisms of action. We anticipate that rational protein engineering will shape the field of protein therapeutics dramatically by improving existing products and enabling the development of novel therapeutic agents.

Animals↗

PubMed2003

Designing proteins for therapeutic applications.

Protein design is becoming an increasingly useful tool for optimizing protein drugs and creating novel biotherapeutics. Recent progress includes the engineering of monoclonal antibodies, cytokines, enzymes and viral fusion inhibitors.

Animals↗

PubMed2002

Electrostatics significantly affect the stability of designed homeodomain variants.

The role of electrostatic interactions in determining the stability of designed proteins was studied by constructing and analyzing a set of designed variants of the Drosophila engrailed homeodomain. Computational redesign of 29 surface positions results in a 25-fold mutant with moderate stability, similar to the wild-type protein. Incorporating helix dipole and N-capping considerations into the design algorithm by restricting amino acid composition at the helix termini and N-capping positions yields a ninefold mutant of the initial design (a 23-fold mutant of wild-type) that is over 3 kcal mol(-1) more stable than the protein resulting from the unbiased design. Four additional proteins were constructed and analyzed to isolate the effects of helix dipole and N-capping interactions in each helix. Based on the results of urea-denaturation experiments and calculations using the finite difference Poisson-Boltzmann method, both classes of interaction are found to increase the stability of the designed proteins significantly. The simple electrostatic model used in the optimization of rotamers by iterative techniques (ORBIT) force-field, which is similar to the electrostatic models used in other protein design force-fields, is unable to predict the experimentally determined stabilities of the designed variants. The helix dipole and N-capping restrictions provide a simple but effective method to incorporate two types of electrostatic interactions that impact protein stability significantly.

Algorithms↗