Creating protein biocatalysts as tools for future industrial applications

Application of conventional molecular dynamics simulation in evaluating the stability of apomyoglobin in urea solution

In this study, we had exploited the advancement in computer technology to determine the stability of four apomyoglobin variants namely wild type, E109A, E109G and G65A/G73A by conducting conventional molecular dynamics simulations in explicit urea solution. Variations in RMSD, native contacts and solvent accessible surface area of the apomyoglobin variants during the simulation were calculated to probe the effect of mutation on the overall conformation of the protein. Subsequently, the mechanism leading to the destabilization of the apoMb variants was studied through the calculation of correlation matrix, principal component analyses, hydrogen bond analyses and RMSF. The results obtained here correlate well with the study conducted by Baldwin and Luo which showed improved stability of apomyoglobin with E109A mutation and contrariwise for E109G and G65A/G73A mutation. These positive observations showcase the feasibility of exploiting MD simulation in determining protein stability prior to protein expression.

The unexpected structure of the designed protein Octarellin V.1 forms a challenge for protein structure prediction tools

Despite impressive successes in protein design, designing a well-folded protein of more 100 amino acids de novo remains a formidable challenge. Exploiting the promising biophysical features of the artificial protein Octarellin V, we improved this protein by directed evolution, thus creating a more stable and soluble protein: Octarellin V.1. Next, we obtained crystals of Octarellin V.1 in complex with crystallization chaperons and determined the tertiary structure. The experimental structure of Octarellin V.1 differs from its in silico design: the (αβα) sandwich architecture bears some resemblance to a Rossman-like fold instead of the intended TIM-barrel fold. This surprising result gave us a unique and attractive opportunity to test the state of the art in protein structure prediction, using this artificial protein free of any natural selection. We tested 13 automated webservers for protein structure prediction and found none of them to predict the actual structure. More than 50% of them predicted a TIM-barrel fold, i.e. the structure we set out to design more than 10years ago. In addition, local software runs that are human operated can sample a structure similar to the experimental one but fail in selecting it, suggesting that the scoring and ranking functions should be improved. We propose that artificial proteins could be used as tools to test the accuracy of protein structure prediction algorithms, because their lack of evolutionary pressure and unique sequences features.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

Protein engineering of enzymes for process applications

Scientific progress in the field of enzyme modification today enables the opportunity to tune a given biocatalyst for a specific industrial application. Much work has been focused on extending the substrate repertoire and altering selectivity. Nevertheless, it is clear that many new forthcoming opportunities will be targeted on modification to enable process application. This article discusses the challenges involved in enzyme modification focused on process requirements, such as the need to fulfill reaction thermodynamics, specific activity under the required conditions, kinetics at required concentrations, and stability. Finally, future research directions are discussed, including the integration of biocatalysis with neighboring chemical steps.

Pre-existing anti-adeno-associated virus antibodies as a challenge in AAV gene therapy

Adeno-associated virus (AAV)-based vectors are promising tools for gene therapeutic applications, in part because AAVs are nonpathogenic viruses, and vectors derived from them can drive long-term transgene expression without integration of the vector DNA into the host genome. AAVs are not strongly immunogenic, but they can, nonetheless, give rise to both a cellular and humoral immune response. As a result, a significant fraction of potential patients for AAV-based gene therapy harbors pre-existing antibodies against AAV. Because even very low levels of antibodies can prevent successful transduction, antecedent anti-AAV antibodies pose a serious obstacle to the universal application of AAV gene therapy. In this review, we discuss the current knowledge of the role of anti-AAV antibodies in AAV-based gene therapy with a particular emphasis on approaches to overcome the hurdle that they pose.

Ultrahigh-throughput FACS-based screening for directed enzyme evolution

Directed enzyme evolution has proven to be a powerful tool for improving a range of properties of enzymes through consecutive rounds of diversification and selection. However, its success depends heavily on the efficiency of the screening strategy employed. Fluorescence-activated cell sorting (FACS) has recently emerged as a powerful tool for screening enzyme libraries due to its high sensitivity and its ability to analyze as many as 10(8) mutants per day. Applications of FACS screening have allowed the isolation of enzyme variants with significantly improved activities, altered substrate specificities, or even novel functions. This review discusses FACS-based screening for enzymatic activity and its potential application for the directed evolution of enzymes, ribozymes, and catalytic antibodies.

Random mutagenesis by error-prone PCR

In vitro selection coupled with directed evolution represents a powerful method for generating nucleic acids and proteins with desired functional properties. Creating high-quality libraries of random sequences is an important step in this process as it allows variants of individual molecules to be generated from a single-parent sequence. These libraries are then screened for individual molecules with interesting, and sometimes very rare, phenotypes. Here, we describe a general method to introduce random nucleotide mutations into a parent sequence that takes advantage of the polymerase chain reaction (PCR). This protocol reduces mutational bias often associated with error-prone PCR methods and allows the experimenter to control the degree of mutagenesis by controlling the number of gene-doubling events that occur in the PCR reaction. The error-prone PCR method described here was used to optimize a de novo evolved protein for improved folding stability, solubility, and ligand-binding affinity.

A man-made ATP-binding protein evolved independent of nature causes abnormal growth in bacterial cells

Recent advances in de novo protein evolution have made it possible to create synthetic proteins from unbiased libraries that fold into stable tertiary structures with predefined functions. However, it is not known whether such proteins will be functional when expressed inside living cells or how a host organism would respond to an encounter with a non-biological protein. Here, we examine the physiology and morphology of Escherichia coli cells engineered to express a synthetic ATP-binding protein evolved entirely from non-biological origins. We show that this man-made protein disrupts the normal energetic balance of the cell by altering the levels of intracellular ATP. This disruption cascades into a series of events that ultimately limit reproductive competency by inhibiting cell division. We now describe a detailed investigation into the synthetic biology of this man-made protein in a living bacterial organism, and the effect that this protein has on normal cell physiology.

A synthetic protein selected for ligand binding affinity mediates ATP hydrolysis

How primitive enzymes emerged from a primordial pool remains a fundamental unanswered question with important practical implications in synthetic biology. Here we show that a de novo evolved ATP binding protein, selected solely on the basis of its ability to bind ATP, mediates the regiospecific hydrolysis of ATP to ADP when crystallized with 1 equiv of ATP. Structural insights into this reaction were obtained by growing protein crystals under saturating ATP conditions. The resulting crystal structure refined to 1.8 A resolution reveals that this man-made protein binds ATP in an unusual bent conformation that is metal-independent and held in place by a key bridging water molecule. Removal of this interaction using a null mutant results in a variant that binds ATP in a normal linear geometry and is incapable of ATP hydrolysis. Biochemical analysis, including high-resolution mass spectrometry performed on dissolved protein crystals, confirms that the reaction is accelerated in the crystalline environment. This observation suggests that proteins with weak chemical reactivity can emerge from high affinity ligand binding sites and that constrained ligand-binding geometries could have helped to facilitate the emergence of early protein enzymes.