A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign and Its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme

Abstract

Realization of novel molecular function requires the ability to alter molecular complex formation. Enzymatic function can be altered by changing enzyme-substrate interactions via modification of an enzyme's active site. A redesigned enzyme may either perform a novel reaction on its native substrates or its native reaction on novel substrates. A number of computational approaches have been developed to address the combinatorial nature of the protein redesign problem. These approaches typically search for the global minimum energy conformation among an exponential number of protein conformations. We present a novel algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding constant with the speed and completeness of a branch-and-bound pruning algorithm. In addition, we developed an efficient deterministic approximation algorithm, capable of approximating our scoring function to arbitrary precision. In practice, the approximation algorithm decreases the execution time of the mutation search by a factor of ten. To test our method, we examined the Phe-specific adenylation domain of the nonribosomal peptide synthetase gramicidin synthetase A (GrsA-PheA). Ensemble scoring, using a rotameric approximation to the partition functions of the bound and unbound states for GrsA-PheA, is first used to predict binding of the wildtype protein and a previously described mutant (selective for leucine), and second, to switch the enzyme specificity toward leucine, using two novel active site sequences computationally predicted by searching through the space of possible active site mutations. The top scoring in silico mutants were created in the wetlab and dissociation/binding constants were determined by fluorescence quenching. These tested mutations exhibit the desired change in specificity from Phe to Leu. Our ensemble-based algorithm, which flexibly models both protein and ligand using rotamer-based partition functions, has application in enzyme redesign, the prediction of protein-ligand binding, and computer-aided drug design.

Protein Interfacial Pocket Engineering via Coupled Computational Filtering and Biological Focusing Criterion

“…26,27 In similar fashion, partitioning and docking can narrow the possibilities for R 4 . 25 A collection of IP conformations can be generated that each present a different VDW, electrostatic profile, or desolvation cost. By docking this collection of IP conformations to the proper substrate, the affinity features of those subpartition of IPs that dock more readily can be gleaned.…”

Algorithmic Challenges in Structural Molecular Biology and Proteomics

“…Our work spans a number of projects in computational structural biology, including algorithms for automated assignment and structure determination in NMR structural biology [3,9,6,19,10,5,7,18,4], protein redesign [13], computer-aided drug design [1,15,13], computational molecular replacement in X-ray crystallography [14,17,16], and other related projects [2,11,8]. To pursue research in the field of structural genomics is to study the geometric structures of proteins.…”

“…However, the techniques we develop can also be applied to synthetic problems such as a protein engineering. For example, in collaboration with Prof. Amy Anderson, we recently developed a novel ensemble-based scoring and search algorithm for protein redesign, and applied it to modify the substrate specificity of an antibioticproducing enzyme in the non-ribosomal peptide synthetase (NRPS) path-way [13]. Realization of novel molecular function requires the ability to alter molecular complex formation.…”

“…We believe these algorithms may be generally useful to the structural biology community, for studies of protein-ligand binding and protein redesign. Our provable approximation algorithm represents a new technique for computer-assisted drug design, and a novel approach for docking flexible ligands to flexible active sites [13]. In the future, we will extend and apply our algorithms to the redesign of other enzymes, including polyketide synthase (PKS) systems, which synthesize polyketide products such as erythromycin, rapamycin and tetracycline.…”

“…I'll briefly discuss some recent results from my lab, including new algorithms for interpreting X-ray crystallography [14,17,16] and NMR (nuclear magnetic resonance) data [3,9,6,19,10,5,7,18,4], disease classification using mass spectrometry of human serum [12], and protein redesign [13]. Our algorithms have recently been used, respectively, to reveal the enzymatic architecture of organisms high on the CDC bioterrorism watch-list [17,16], for probabilistic cancer classification from human peripheral blood [12], and to redesign an antibioticproducing enzyme to bind a novel substrate [13]. I'll overview these projects, and highlight some of the algorithmic and computational challenges.…”