Optimal protein library design using recombination or point mutations based on sequence-based scoring functions.

In this paper, we introduce and test two new sequence-based protein scoring systems (i.e. S1, S2) for assessing the likelihood that a given protein hybrid will be functional. By binning together amino acids with similar properties (i.e. volume, hydrophobicity and charge) the scoring systems S1 and S2 allow for the quantification of the severity of mismatched interactions in the hybrids. The S2 scoring system is found to be able to significantly functionally enrich a cytochrome P450 library over other scoring methods. Given this scoring base, we subsequently constructed two separate optimization formulations (i.e. OPTCOMB and OPTOLIGO) for optimally designing protein combinatorial libraries involving recombination or mutations, respectively. Notably, two separate versions of OPTCOMB are generated (i.e. model M1, M2) with the latter allowing for position-dependent parental fragment skipping. Computational benchmarking results demonstrate the efficacy of models OPTCOMB and OPTOLIGO to generate high scoring libraries of a prespecified size.

IPRO: an iterative computational protein library redesign and optimization procedure.

A number of computational approaches have been developed to reengineer promising chimeric proteins one at a time through targeted point mutations. In this article, we introduce the computational procedure IPRO (iterative protein redesign and optimization procedure) for the redesign of an entire combinatorial protein library in one step using energy-based scoring functions. IPRO relies on identifying mutations in the parental sequences, which when propagated downstream in the combinatorial library, improve the average quality of the library (e.g., stability, binding affinity, specific activity, etc.). Residue and rotamer design choices are driven by a globally convergent mixed-integer linear programming formulation. Unlike many of the available computational approaches, the procedure allows for backbone movement as well as redocking of the associated ligands after a prespecified number of design iterations. IPRO can also be used, as a limiting case, for the redesign of a single or handful of individual sequences. The application of IPRO is highlighted through the redesign of a 16-member library of Escherichia coli/Bacillus subtilis dihydrofolate reductase hybrids, both individually and through upstream parental sequence redesign, for improving the average binding energy. Computational results demonstrate that it is indeed feasible to improve the overall library quality as exemplified by binding energy scores through targeted mutations in the parental sequences.

Design of combinatorial protein libraries of optimal size.

In this article we introduce a computational procedure, OPTCOMB (Optimal Pattern of Tiling for COMBinatorial library design), for designing protein hybrid libraries that optimally balance library size with quality. The proposed procedure is directly applicable to oligonucleotide ligation-based protocols such as GeneReassembly, DHR, SISDC, and many more. Given a set of parental sequences and the size ranges of the parental sequence fragments, OPTCOMB determines the optimal junction points (i.e., crossover positions) and the fragment contributing parental sequences at each one of the junction points. By rationally selecting the junction points and the contributing parental sequences, the number of clashes (i.e., unfavorable interactions) in the library is systematically minimized with the aim of improving the overall library quality. Using OPTCOMB, hybrid libraries containing fragments from three different dihydrofolate reductase sequences (Escherichia coli, Bacillus subtilis, and Lactobacillus casei) are computationally designed. Notably, we find that there exists an optimal library size when both the number of clashes between the fragments composing the library and the average number of clashes per hybrid in the library are minimized. Results reveal that the best library designs typically involve complex tiling patterns of parental segments of unequal size hard to infer without relying on computational means.

FamClash: a method for ranking the activity of engineered enzymes.

This article introduces the computational procedure FamClash for analyzing incompatibilities in engineered protein hybrids by using protein family sequence data. All pairs of residue positions in the sequence alignment that conserve the property triplet of charge, volume, and hydrophobicity are first identified, and significant deviations are denoted as residue-residue clashes. This approach moves beyond earlier efforts aimed at solely classifying hybrids as functional or nonfunctional by correlating the rank ordering of these hybrids based on their activity levels. Experimental testing of this approach was performed in parallel to assess the predictive ability of FamClash. As a model system, single-crossover ITCHY (incremental truncation for the creation of hybrid enzymes) libraries were prepared from the Escherichia coli and Bacillus subtilis dihydrofolate reductases, and the activities of functional hybrids were determined. Comparisons of the predicted clash map as a function of crossover position revealed good agreement with activity data, reproducing the observed V shape and matching the location of a local peak in activity.

Using multiple sequence correlation analysis to characterize functionally important protein regions.

Protein co-evolution under structural and functional constraints necessitates the preservation of important interactions. Identifying functionally important regions poses many obstacles in protein engineering efforts. In this paper, we present a bioinformatics-inspired approach (residue correlation analysis, RCA) for predicting functionally important domains from protein family sequence data. RCA is comprised of two major steps: (i) identifying pairs of residue positions that mutate in a coordinated manner, and (ii) using these results to identify protein regions that interact with an uncommonly high number of other residues. We hypothesize that strongly correlated pairs result not only from contacting pairs, but also from residues that participate in conformational changes involved during catalysis or important interactions necessary for retaining functionality. The results show that highly mobile loops that assist in ligand association/dissociation tend to exhibit high correlation. RCA results exhibit good agreement with the findings of experimental and molecular dynamics studies for the three protein families that are analyzed: (i) DHFR (dihydrofolate reductase), (ii) cyclophilin, and (iii) formyl-transferase. Specifically, the specificity (percentage of correct predictions) in all three cases is substantially higher than those obtained by entropic measures or contacting residue pairs. In addition, we use our approach in a predictive fashion to identify important regions of a transmembrane amino acid transporter protein for which there is limited structural and functional information available.

Using a residue clash map to functionally characterize protein recombination hybrids.

In this article, we introduce a rapid, protein sequence database-driven approach to characterize all contacting residue pairs present in protein hybrids for inconsistency with protein family structural features. This approach is based on examining contacting residue pairs with different parental origins for different types of potentially unfavorable interactions (i.e. electrostatic repulsion, steric hindrance, cavity formation and hydrogen bond disruption). The identified clashing residue pairs between members of a protein family are then contrasted against functionally characterized hybrid libraries. Comparisons for five different protein recombination studies available in the literature: (i) glycinamide ribonucleotide transformylase (GART) from Escherichia coli (purN) and human (hGART), (ii) human Mu class glutathione S-transferase (GST) M1-1 and M2-2, (iii) beta-lactamase TEM-1 and PSE-4, (iv) catechol-2,3-oxygenase xylE and nahH, and (v) dioxygenases (toluene dioxygenase, tetrachlorobenzene dioxygenase and biphenyl dioxygenase) reveal that the patterns of identified clashing residue pairs are remarkably consistent with experimentally found patterns of functional crossover profiles. Specifically, we show that the proposed residue clash maps are on average 5.0 times more effective than randomly generated clashes and 1.6 times more effective than residue contact maps at explaining the observed crossover distributions among functional members of hybrid libraries. This suggests that residue clash maps can provide quantitative guidelines for the placement of crossovers in the design of protein recombination experiments.