Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy

Design of a light and Ca2+ switchable organic-peptide hybrid

The design of organic-peptide hybrids has the potential to combine our vast knowledge of protein design with small molecule engineering to create hybrid structures with complex functions. Here, we describe the computational design of a photoswitchable Ca2+-binding organic-peptide hybrid. The designed molecule, designated Ca2+-binding switch (CaBS), combines an EF-hand motif from classical Ca2+-binding proteins such as calmodulin with a photoswitchable group that can be reversibly isomerized between a spiropyran (SP) and merocyanine (MC) state in response to different wavelengths of light. The MC/SP group acts both as a photoswitch as well as an optical sensor of Ca2+ binding. Photoconversion of the SP to the corresponding MC unmasks an acidic phenol, which CaBS uses as an integral part of both its Ca2+-binding site as well as its tertiary and quaternary structure. By design, the SP state of CaBS is monomeric, while the Ca2+-bound form of the MC state is an obligate dimer, with two Ca2+-binding sites formed at the interface of a domain-swapped dimer. Thus, light and Ca2+ were expected to serve as an "AND gate" that powers a change in backbone structure/dynamics, oligomerization state, and fluorescence properties of the designed molecule. CaBS was designed using Rosetta and molecular dynamics simulations, and experimentally characterized by nuclear magnetic resonance, isothermal titration calorimetry, and optical titrations. These data illustrate the potential of combining small molecule engineering with de novo protein design to develop sensors whose conformation, association state, and optical properties respond to multiple environmental cues.

Machine Learning Guided Rational Design of a Non-Heme Iron-Based Lysine Dioxygenase Improves its Total Turnover Number

Highly selective C-H functionalization remains an ongoing challenge in organic synthetic methodologies. Biocatalysts are robust tools for achieving these difficult chemical transformations. Biocatalyst engineering has often required directed evolution or structure-based rational design campaigns to improve their activities. In recent years, machine learning has been integrated into these workflows to improve the discovery of beneficial enzyme variants. In this work, we combine a structure-based self-supervised machine learning framework, MutComputeX, with classical molecular dynamics simulations to down select mutations for rational design of a non-heme iron-dependent lysine dioxygenase, LDO. This approach consistently resulted in functional LDO mutants and circumvents the need for extensive study of mutational activity before-hand. Our rationally designed single mutants purified with up to 2-fold higher expression yields than WT and displayed higher total turnover numbers (TTN). Combining five such single mutations into a pentamutant variant, LPNYI LDO, leads to a 40 % improvement in the TTN (218±3) as compared to WT LDO (TTN=160±2). Overall, this work offers a low-barrier approach for those seeking to synergize machine learning algorithms with pre-existing protein engineering strategies.

Metals at the Helm: Revolutionizing Protein Assembly and Applications

Protein assembly is an essential process in biological systems, where proteins self-assemble into complex structures with diverse functions. Inspired by the exquisite control over protein assembly in nature, scientists have been exploring ways to design and assemble protein structures with precise control over their topologies and functions. One promising approach for achieving this goal is through metal coordination, which utilizes metal-binding motifs to mediate protein-protein interactions and assemble protein complexes with controlled stoichiometry and geometry. Metal coordination provides a modular and tunable approach for protein assembly and de novo structure design, where the metal ion acts as a molecular glue that holds the protein subunits together in a specific orientation. Metal-coordinated protein assemblies have shown great potential for developing functional metalloproteinase, novel biomaterials and integrated drug delivery systems. In this review, an overview of the recent advances in protein assemblies benefited from metal coordination is provided, focusing on various protein arrangements in different dimensions including protein oligomers, protein nanocage and higher-order protein architectures. Moreover, the key metal-binding motifs and strategies used to assemble protein structures with precise control over their properties are highlighted. The potential applications of metal-mediated protein assemblies in biotechnology and biomedicine are also discussed.

Expanding the Genetic Code of Bioelectrocatalysis and Biomaterials

Genetic code expansion is a promising genetic engineering technology that incorporates noncanonical amino acids into proteins alongside the natural set of 20 amino acids. This enables the precise encoding of non-natural chemical groups in proteins. This review focuses on the applications of genetic code expansion in bioelectrocatalysis and biomaterials. In bioelectrocatalysis, this technique enhances the efficiency and selectivity of bioelectrocatalysts for use in sensors, biofuel cells, and enzymatic electrodes. In biomaterials, incorporating non-natural chemical groups into protein-based polymers facilitates the modification, fine-tuning, or the engineering of new biomaterial properties. The review provides an overview of relevant technologies, discusses applications, and highlights achievements, challenges, and prospects in these fields.

Noncanonical Amino Acids: Bringing New-to-Nature Functionalities to Biocatalysis

Biocatalysis has become an important component of modern organic chemistry, presenting an efficient and environmentally friendly approach to synthetic transformations. Advances in molecular biology, computational modeling, and protein engineering have unlocked the full potential of enzymes in various industrial applications. However, the inherent limitations of the natural building blocks have sparked a revolutionary shift. In vivo genetic incorporation of noncanonical amino acids exceeds the conventional 20 amino acids, opening new avenues for innovation. This review provides a comprehensive overview of applications of noncanonical amino acids in biocatalysis. We aim to examine the field from multiple perspectives, ranging from their impact on enzymatic reactions to the creation of novel active sites, and subsequent catalysis of new-to-nature reactions. Finally, we discuss the challenges, limitations, and promising opportunities within this dynamic research domain.

NeMeHg, genetically encoded indicator for mercury ions based on mNeonGreen green fluorescent protein and merP protein from Shigella flexneri

The detection of mercury ions is an important task in both environmental monitoring and cell biology research. However, existing genetically encoded sensors for mercury ions have certain limitations, such as negative fluorescence response, narrow dynamic range, or the need for cofactor supplementation. To address these limitations, we have developed novel sensors by fusing a circularly permutated version of the mNeonGreen green fluorescent protein with the merP mercury-binding protein from Gram-negative bacteria Shigella flexneri. The developed NeMeHg and iNeMeHg sensors responded to mercury ions with positive and negative fluorescence changes, respectively. We characterized their properties in vitro. Using the developed biosensors, we were able to successfully visualize changes in mercury ion concentration in mammalian cultured cells.

Machine learning guided rational design of a non-heme iron-based lysine dioxygenase improves its total turnover number

Highly selective C-H functionalization remains an ongoing challenge in organic synthetic methodologies. Biocatalysts are robust tools for achieving these difficult chemical transformations. Biocatalyst engineering has often required directed evolution or structure-based rational design campaigns to improve their activities. In recent years, machine learning has been integrated into these workflows to improve the discovery of beneficial enzyme variants. In this work, we combine a structure-based machine-learning algorithm with classical molecular dynamics simulations to down select mutations for rational design of a non-heme iron-dependent lysine dioxygenase, LDO. This approach consistently resulted in functional LDO mutants and circumvents the need for extensive study of mutational activity before-hand. Our rationally designed single mutants purified with up to 2-fold higher yields than WT and displayed higher total turnover numbers (TTN). Combining five such single mutations into a pentamutant variant, LPNYI LDO, leads to a 40% improvement in the TTN (218±3) as compared to WT LDO (TTN = 160±2). Overall, this work offers a low-barrier approach for those seeking to synergize machine learning algorithms with pre-existing protein engineering strategies.

Atomically Accurate Design of Metalloproteins with Predefined Coordination Geometries

We report a new computational protein design method for the construction of oligomeric protein assemblies around metal centers with predefined coordination geometries. We apply this method to design two homotrimeric assemblies, Tet4 and TP1, with tetrahedral and trigonal-pyramidal tris(histidine) metal coordination geometries, respectively, and demonstrate that both assemblies form the targeted metal centers with ≤0.2 Å accuracy. Although Tet4 and TP1 are constructed from the same parent protein building block, they are distinct in terms of their overall architectures, the environment surrounding the metal centers, and their metal-based reactivities, illustrating the versatility of our approach.

Nature-inspired Enzyme engineering and sustainable catalysis: biochemical clues from the world of plants and extremophiles

The use of enzymes to accelerate chemical reactions for the synthesis of industrially important products is rapidly gaining popularity. Biocatalysis is an environment-friendly approach as it not only uses non-toxic, biodegradable, and renewable raw materials but also helps to reduce waste generation. In this context, enzymes from organisms living in extreme conditions (extremozymes) have been studied extensively and used in industries (food and pharmaceutical), agriculture, and molecular biology, as they are adapted to catalyze reactions withstanding harsh environmental conditions. Enzyme engineering plays a key role in integrating the structure-function insights from reference enzymes and their utilization for developing improvised catalysts. It helps to transform the enzymes to enhance their activity, stability, substrates-specificity, and substrate-versatility by suitably modifying enzyme structure, thereby creating new variants of the enzyme with improved physical and chemical properties. Here, we have illustrated the relatively less-tapped potentials of plant enzymes in general and their sub-class of extremozymes for industrial applications. Plants are exposed to a wide range of abiotic and biotic stresses due to their sessile nature, for which they have developed various mechanisms, including the production of stress-response enzymes. While extremozymes from microorganisms have been extensively studied, there are clear indications that plants and algae also produce extremophilic enzymes as their survival strategy, which may find industrial applications. Typical plant enzymes, such as ascorbate peroxidase, papain, carbonic anhydrase, glycoside hydrolases and others have been examined in this review with respect to their stress-tolerant features and further improvement via enzyme engineering. Some rare instances of plant-derived enzymes that point to greater exploration for industrial use have also been presented here. The overall implication is to utilize biochemical clues from the plant-based enzymes for robust, efficient, and substrate/reaction conditions-versatile scaffolds or reference leads for enzyme engineering.

Molecular Complementarity of Proteomimetic Materials for Target-Specific Recognition and Recognition-Mediated Complex Functions

As biomolecules essential for sustaining life, proteins are generated from long chains of 20 different α-amino acids that are folded into unique 3D structures. In particular, many proteins have molecular recognition functions owing to their binding pockets, which have complementary shapes, charges, and polarities for specific targets, making these biopolymers unique and highly valuable for biomedical and biocatalytic applications. Based on the understanding of protein structures and microenvironments, molecular complementarity can be exhibited by synthesizable and modifiable materials. This has prompted researchers to explore the proteomimetic potentials of a diverse range of materials, including biologically available peptides and oligonucleotides, synthetic supramolecules, inorganic molecules, and related coordination networks. To fully resemble a protein, proteomimetic materials perform the molecular recognition to mediate complex molecular functions, such as allosteric regulation, signal transduction, enzymatic reactions, and stimuli-responsive motions; this can also expand the landscape of their potential bio-applications. This review focuses on the recognitive aspects of proteomimetic designs derived for individual materials and their conformations. Recent progress provides insights to help guide the development of advanced protein mimicry with material heterogeneity, design modularity, and tailored functionality. The perspectives and challenges of current proteomimetic designs and tools are also discussed in relation to future applications.

Using the Noncanonical Metallo-Amino Acid [Cu(II)(2,2'-Bipyridin-5-yl)]-alanine to Study the Structures of Proteins

Genetic code expansion allows modification of the physical and chemical properties of proteins by the site-directed insertion of noncanonical amino acids. Here we exploit this technology for measuring nanometer-scale distances in proteins. (2,2'-Bipyridin-5-yl)alanine was incorporated into the green fluorescent protein (GFP) and used as an anchoring point for Cu(II) to create a spin-label. The incorporation of (2,2'-bipyridin-5-yl)alanine directly into the protein resulted in a high-affinity binding site for Cu(II) capable of outcompeting other binding positions in the protein. The resulting Cu(II)-spin label is very compact and not larger than a conventional amino acid. By using 94 GHz electron paramagnetic resonance (EPR) pulse dipolar spectroscopy we have been able to determine accurately the distance between two such spin-labels. Our measurements revealed that GFP dimers can adopt different quaternary conformations. The combination of spin-labeling using a paramagnetic nonconventional amino acid with high-frequency EPR techniques resulted in a sensitive method for studying the structures of proteins.

Design of Artificial Enzymes: Insights into Protein Scaffolds

The design of artificial enzymes has emerged as a promising tool for the generation of potent biocatalysts able to promote new-to-nature reactions with improved catalytic performances, providing a powerful platform for wide-ranging applications and a better understanding of protein functions and structures. The selection of an appropriate protein scaffold plays a key role in the design process. This review aims to give a general overview of the most common protein scaffolds that can be exploited for the generation of artificial enzymes. Several examples are discussed and categorized according to the strategy used for the design of the artificial biocatalyst, namely the functionalization of natural enzymes, the creation of a new catalytic site in a protein scaffold bearing a wide hydrophobic pocket and de novo protein design. The review is concluded by a comparison of these different methods and by our perspective on the topic.

Enzyme redesign and genetic code expansion

Enzyme design is an important application of computational protein design (CPD). It can benefit enormously from the additional chemistries provided by noncanonical amino acids (ncAAs). These can be incorporated into an 'expanded' genetic code, and introduced in vivo into target proteins. The key step for genetic code expansion is to engineer an aminoacyl-transfer RNA (tRNA) synthetase (aaRS) and an associated tRNA that handles the ncAA. Experimental directed evolution has been successfully used to engineer aaRSs and incorporate over 200 ncAAs into expanded codes. But directed evolution has severe limits, and is not yet applicable to noncanonical AA backbones. CPD can help address several of its limitations, and has begun to be applied to this problem. We review efforts to redesign aaRSs, studies that designed new proteins and functionalities with the help of ncAAs, and some of the method developments that have been used, such as adaptive landscape flattening Monte Carlo, which allows an enzyme to be redesigned with substrate or transition state binding as the design target.

Rational design of photosynthetic reaction center protein maquettes

New technologies for efficient solar-to-fuel energy conversion will help facilitate a global shift from dependence on fossil fuels to renewable energy. Nature uses photosynthetic reaction centers to convert photon energy into a cascade of electron-transfer reactions that eventually produce chemical fuel. The design of new reaction centers de novo deepens our understanding of photosynthetic charge separation and may one day allow production of biofuels with higher thermodynamic efficiency than natural photosystems. Recently, we described the multi-step electron-transfer activity of a designed reaction center maquette protein (the RC maquette), which can assemble metal ions, tyrosine, a Zn tetrapyrrole, and heme into an electron-transport chain. Here, we detail our modular strategy for rational protein design and show that the intended RC maquette design agrees with crystal structures in various states of assembly. A flexible, dynamic apo-state collapses by design into a more ordered holo-state upon cofactor binding. Crystal structures illustrate the structural transitions upon binding of different cofactors. Spectroscopic assays demonstrate that the RC maquette binds various electron donors, pigments, and electron acceptors with high affinity. We close with a critique of the present RC maquette design and use electron-tunneling theory to envision a path toward a designed RC with a substantially higher thermodynamic efficiency than natural photosystems.

Engineering of enzymes using non-natural amino acids

In enzyme engineering, the main targets for enhancing properties are enzyme activity, stereoselective specificity, stability, substrate range, and the development of unique functions. With the advent of genetic code extension technology, non-natural amino acids (nnAAs) are able to be incorporated into proteins in a site-specific or residue-specific manner, which breaks the limit of 20 natural amino acids for protein engineering. Benefitting from this approach, numerous enzymes have been engineered with nnAAs for improved properties or extended functionality. In this review, we focus on applications and strategies for using nnAAs in enzyme engineering. Notably, approaches to computational modelling of enzymes with nnAAs are also addressed. Finally, we discuss the bottlenecks that currently need to be addressed in order to realise the broader prospects of this genetic code extension technique.

Designing Artificial Metalloenzymes by Tuning of the Environment beyond the Primary Coordination Sphere

Metalloenzymes catalyze a variety of reactions using a limited number of natural amino acids and metallocofactors. Therefore, the environment beyond the primary coordination sphere must play an important role in both conferring and tuning their phenomenal catalytic properties, enabling active sites with otherwise similar primary coordination environments to perform a diverse array of biological functions. However, since the interactions beyond the primary coordination sphere are numerous and weak, it has been difficult to pinpoint structural features responsible for the tuning of activities of native enzymes. Designing artificial metalloenzymes (ArMs) offers an excellent basis to elucidate the roles of these interactions and to further develop practical biological catalysts. In this review, we highlight how the secondary coordination spheres of ArMs influence metal binding and catalysis, with particular focus on the use of native protein scaffolds as templates for the design of ArMs by either rational design aided by computational modeling, directed evolution, or a combination of both approaches. In describing successes in designing heme, nonheme Fe, and Cu metalloenzymes, heteronuclear metalloenzymes containing heme, and those ArMs containing other metal centers (including those with non-native metal ions and metallocofactors), we have summarized insights gained on how careful controls of the interactions in the secondary coordination sphere, including hydrophobic and hydrogen bonding interactions, allow the generation and tuning of these respective systems to approach, rival, and, in a few cases, exceed those of native enzymes. We have also provided an outlook on the remaining challenges in the field and future directions that will allow for a deeper understanding of the secondary coordination sphere a deeper understanding of the secondary coordintion sphere to be gained, and in turn to guide the design of a broader and more efficient variety of ArMs.

Key aspects of the past 30 years of protein design

Proteins are the workhorse of life. They are the building infrastructure of living systems; they are the most efficient molecular machines known, and their enzymatic activity is still unmatched in versatility by any artificial system. Perhaps proteins' most remarkable feature is their modularity. The large amount of information required to specify each protein's function is analogically encoded with an alphabet of just ∼20 letters. The protein folding problem is how to encode all such information in a sequence of 20 letters. In this review, we go through the last 30 years of research to summarize the state of the art and highlight some applications related to fundamental problems of protein evolution.

Expanding the functionality of proteins with genetically encoded dibenzo[b,f][1,4,5]thiadiazepine: a photo-transducer for photo-click decoration

Genetic incorporation of novel noncanonical amino acids (ncAAs) that are specialized for the photo-click reaction allows the precisely orthogonal and site-specific functionalization of proteins in living cells under photo-control. However, the development of a r̲ing-strain i̲n situ l̲oadable d̲ipolarophile (RILD) as a genetically encodable reporter for photo-click bioconjugation with spatiotemporal controllability is quite rare. Herein, we report the design and synthesis of a photo-switchable d̲ib̲enzo[b,f][1,4,5]t̲hiad̲iazepine-based a̲lanine (DBTDA) ncAA, together with the directed evolution of a pyrrolysyl-tRNA synthetase/tRNACUA pair (PylRS/tRNACUA), to encode the DBTDA into recombinant proteins as a RILD in living E. coli cells. The fast-responsive photo-isomerization of the DBTDA residue can be utilized as a converter of photon energy into ring-strain energy to oscillate the conformational changes of the parent proteins. Due to the photo-activation of RILD, the photo-switching of the DBTDA residue on sfGFP and OmpC is capable of promoting the photo-click ligation with diarylsydnone (DASyd) derived probes with high efficiency and selectivity. We demonstrate that the genetic code expansion (GCE) with DBTDA benefits the studies on the distribution of decorated OmpC-DBTD on specific E. coli cells under a spatiotemporal resolved photo-stimulation. The GCE for encoding DBTDA enables further functional diversity of artificial proteins in living systems.

Bioconjugation strategies and clinical implications of Interferon-bioconjugates

Interferons (IFN) are immunomodulating, antiviral and antiproliferative cytokines for treatment of multiple indications, including cancer, hepatitis, and autoimmune disease. The first IFNs were discovered in 1957, first approved in 1986, and are nowadays listed in the WHO model list of essential Medicines. Three classes of IFNs are known; IFN-α2a and IFN-β belonging to type-I IFNs, IFN-γ a type-II IFN approved for some hereditary diseases and IFN-λs, which form the newest class of type-III IFNs. IFN-λs were discovered in the last decade with fascinating yet under discovered pharmaceutical potential. This article reviews available IFN drugs, their field and route of application, while also outlining available and future strategies for bioconjugation to further optimize pharmaceutical and clinical performances of all three available IFN classes.

Genetic Incorporation of Selenotyrosine Significantly Improves Enzymatic Activity of Agrobacterium radiobacter Phosphotriesterase

Tyrosine plays important roles in many enzymes. To facilitate enzyme design, mechanistic studies and minimize structural perturbation in the active site, here we report the genetic incorporation of a novel unnatural amino acid selenotyrosine (SeHF), which has single-atom replacement in comparison to tyrosine. The arPTE-(Agrobacterium radiobacter Phosphotriesterase) Tyr309SeHF mutant exhibits a significant 12-fold increase in kcat and 3.2-fold enhancement in kcat /KM at pH 7.0. Molecular dynamics simulations show that the SeHF309 mutation results in a conformational switch which opens up the product release pocket and increases the product release rate, thereby elevating the overall enzyme activity. Significant improvement of the catalytic efficiency at neutral pH by single unnatural amino acid (UAA) mutation broadens the application of this enzyme, and provides valuable insights to the mechanism. Our method represents a new approach for designing enzymes with enhanced activity.

Recent Advances in Biocatalysis with Chemical Modification and Expanded Amino Acid Alphabet

The two main strategies for enzyme engineering, directed evolution and rational design, have found widespread applications in improving the intrinsic activities of proteins. Although numerous advances have been achieved using these ground-breaking methods, the limited chemical diversity of the biopolymers, restricted to the 20 canonical amino acids, hampers creation of novel enzymes that Nature has never made thus far. To address this, much research has been devoted to expanding the protein sequence space via chemical modifications and/or incorporation of noncanonical amino acids (ncAAs). This review provides a balanced discussion and critical evaluation of the applications, recent advances, and technical breakthroughs in biocatalysis for three approaches: (i) chemical modification of cAAs, (ii) incorporation of ncAAs, and (iii) chemical modification of incorporated ncAAs. Furthermore, the applications of these approaches and the result on the functional properties and mechanistic study of the enzymes are extensively reviewed. We also discuss the design of artificial enzymes and directed evolution strategies for enzymes with ncAAs incorporated. Finally, we discuss the current challenges and future perspectives for biocatalysis using the expanded amino acid alphabet.

Metal-Binding Foldamers

Sequence-defined oligomeric molecules with discrete folding propensities, termed foldamers, are a versatile source of agents with tailored structure and function. An inspiration for the development of the foldamer paradigm are natural biomacromolecules, the sequence-encoded folding of which is the basis of life. Metal ions and clusters are common features in proteins, where the role of metal varies from supporting structure to enabling function. The ubiquity of metals in natural systems suggests promise for metals in the context of folded artificial backbones. In this Minireview, we highlight efforts to realize this potential through a survey of published work on the design, synthesis, and characterization of metal-binding foldamers.

A Hydroxyquinoline-Based Unnatural Amino Acid for the Design of Novel Artificial Metalloenzymes

We have examined the potential of the noncanonical amino acid (8-hydroxyquinolin-3-yl)alanine (HQAla) for the design of artificial metalloenzymes. HQAla, a versatile chelator of late transition metals, was introduced into the lactococcal multidrug-resistance regulator (LmrR) by stop codon suppression methodology. LmrR_HQAla was shown to complex efficiently with three different metal ions, CuII , ZnII and RhIII to form unique artificial metalloenzymes. The catalytic potential of the CuII -bound LmrR_HQAla enzyme was shown through its ability to catalyse asymmetric Friedel-Craft alkylation and water addition, whereas the ZnII -coupled enzyme was shown to mimic natural Zn hydrolase activity.

Structural Insights into How Protein Environments Tune the Spectroscopic Properties of a Noncanonical Amino Acid Fluorophore

Genetically encoded fluorescent noncanonical amino acids (fNCAAs) could be used to develop novel fluorescent sensors of protein function. Previous efforts toward this goal have been limited by the lack of extensive physicochemical and structural characterizations of protein-based sensors containing fNCAAs. Here, we report the steady-state spectroscopic properties and first structural analyses of an fNCAA-containing Fab fragment of the 5c8 antibody, which binds human CD40L. A previously reported 5c8 variant in which the light chain residue Ile^L98 is replaced with the fNCAA l-(7-hydroxycoumarin-4-yl)ethylglycine (7-HCAA) exhibits a 1.7-fold increase in fluorescence upon antigen binding. Determination and comparison of the apparent pK_as of 7-HCAA in the unbound and bound forms indicate that the observed increase in fluorescence is not the result of perturbations in pK_a. Crystal structures of the fNCAA-containing Fab in the apo and bound forms reveal interactions between the 7-HCAA side chain and surrounding residues that are disrupted upon antigen binding. This structural characterization not only provides insight into the manner in which protein environments can modulate the fluorescence properties of 7-HCAA but also could serve as a starting point for the rational design of new fluorescent protein-based reporters of protein function.

Macromolecular modeling and design in Rosetta: recent methods and frameworks

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at http://www.rosettacommons.org.

Enabling protein-hosted organocatalytic transformations

In this review, the development of organocatalytic artificial enzymes will be discussed. This area of protein engineering research has underlying importance, as it enhances the biocompatibility of organocatalysis for applications in chemical and synthetic biology research whilst expanding the catalytic repertoire of enzymes. The approaches towards the preparation of organocatalytic artificial enzymes, techniques used to improve their performance (selectivity and reactivity) as well as examples of their applications are presented. Challenges and opportunities are also discussed.

Evaluation of a sesquiterpene as possible drug lead against gelatinases via molecular dynamics simulations

Malignant tumors can be targeted by accounting for their metastatic capabilities. Matrix metalloproteinases (MMPs) are the key players in tumor metastasis facilitating through their proteolytic activities of angiogenesis and extracellular matrix components (ECM) degradation. MMP-2 and MMP-9 being the members of a distinguished class of MMPs more commonly known as gelatinases are the prominent enzymes which are involved in different cancer progression stages. Targeting these isoforms specifically has always been a challenging task due to highly similar structural and functional features among the other members of MMPs with well preserve active sites containing catalytic zinc atom that was the only reason that none of the MMP inhibitor has been successfully marketed for the tumor pathology up till now. Therefore, non-competitive inhibitors with different structural attributed are needed to be evaluated at the molecular level for further experiments. The present study deals with the application of molecular dynamics simulation for the investigation of an alternative pathway for the inhibition of MMP-2 and MMP-9 by a sesquiterpene isolated from Polygonum barbatum which demonstrates the characteristics binding to the S1' subsite of the enzymes followed by in vitro gene expression studies. The simulation results provide information on the possible binding profile producing inhibitory effects imposed by the inhibitor to these enzymes by acquiring different structural and dynamical features. Moreover, thermodynamic quantities based on the computationally intensive thermodynamic integration approach were also obtained in terms of inhibitor binding affinity computed for the inhibitor against MMP-2 and MMP-9 that completely augmented the experimental gene expression study.Communicated by Ramaswamy H. Sarma.

Noncoded Amino Acids in de Novo Metalloprotein Design: Controlling Coordination Number and Catalysis

The relationship between structure and function has long been one of the major points of investigation in Biophysics. Understanding how much, or how little, of a protein's often complicated structure is necessary for its function can lead to directed therapeutic strategies and would allow one to design proteins for specific desired functions. Studying protein function by de novo design builds the functionality from the ground up in a completely unrelated and noncoded protein scaffold. Our lab has used this strategy to study heavy and transition metal binding within the TRI family of three stranded coiled coil (3SCC) constructs to understand coordination geometry and metalloenzyme catalytic control within a protein environment. These peptides contain hydrophobic layers within the interior of the 3SCC, which one can mutate to metal binding residues to create a minimal metal binding site, while solid phase synthesis allows our lab to easily incorporate a number of noncoded amino acids including d enantiomers of binding or secondary coordination sphere amino acids, penicillamine, or methylated versions of histidine. Our studies of Cd(II) binding to Cys₃ environments have determined, largely through the use of ¹¹³Cd NMR and ^111mCd PAC, that the coordination environment around a heavy metal can be controlled by incorporating noncoded amino acids in either the primary or secondary coordination spheres. We found mutating the metal binding amino acids to l-Pen can enforce trigonal Cd(II)S₃ geometry exclusively compared to the mixed coordination determined for l-Cys coordination. The same result can be achieved with secondary sphere mutations as well by incorporating d-Leu above a Cys₃. We hypothesize this latter effect is due to the increased steric packing above the metal binding site that occurs when the l-Leu oriented toward the N-terminus of the scaffold is mutated to d-Leu and oriented toward the C-terminus. Mutating the layer below Cys₃ to d-Leu instead formed a mixed 4- and 5-coordinate Cd(II)S₃(H₂O) and Cd(II)S₃(H₂O)₂ construct as steric bulk was decreased below the metal binding site. We have also applied noncoded amino acids to metalloenzyme systems by incorporating His residues that are methylated at the δ- or ε-nitrogen to enforce Cu(I) ligation to the opposite open nitrogen of His and found a 2 orders of magnitude increased catalytic efficiency for nitrite reductase activity with ε-nitrogen coordination compared to δ-nitrogen. These results exemplify the ability to tune coordination environment and catalytic efficiency within a de novo scaffold as well as the utility of noncoded amino acids to increase the chemist's toolbox. By furthering our understanding of metalloprotein design one could envision, through our use of amino acids not normally available to nature, that protein design laboratories will soon be capable of outperforming the native systems previously used as their benchmark of successful design. The ability to design proteins at this level would have far reaching and exciting benefits within various fields including medical and industrial applications.

Electrical energy storage with engineered biological systems

The availability of renewable energy technologies is increasing dramatically across the globe thanks to their growing maturity. However, large scale electrical energy storage and retrieval will almost certainly be a required in order to raise the penetration of renewable sources into the grid. No present energy storage technology has the perfect combination of high power and energy density, low financial and environmental cost, lack of site restrictions, long cycle and calendar lifespan, easy materials availability, and fast response time. Engineered electroactive microbes could address many of the limitations of current energy storage technologies by enabling rewired carbon fixation, a process that spatially separates reactions that are normally carried out together in a photosynthetic cell and replaces the least efficient with non-biological equivalents. If successful, this could allow storage of renewable electricity through electrochemical or enzymatic fixation of carbon dioxide and subsequent storage as carbon-based energy storage molecules including hydrocarbons and non-volatile polymers at high efficiency. In this article we compile performance data on biological and non-biological component choices for rewired carbon fixation systems and identify pressing research and engineering challenges.

Heavy Metal Removal by Bioaccumulation Using Genetically Engineered Microorganisms

Wastewater effluents from mines and metal refineries are often contaminated with heavy metal ions, so they pose hazards to human and environmental health. Conventional technologies to remove heavy metal ions are well-established, but the most popular methods have drawbacks: chemical precipitation generates sludge waste, and activated carbon and ion exchange resins are made from unsustainable non-renewable resources. Using microbial biomass as the platform for heavy metal ion removal is an alternative method. Specifically, bioaccumulation is a natural biological phenomenon where microorganisms use proteins to uptake and sequester metal ions in the intracellular space to utilize in cellular processes (e.g., enzyme catalysis, signaling, stabilizing charges on biomolecules). Recombinant expression of these import-storage systems in genetically engineered microorganisms allows for enhanced uptake and sequestration of heavy metal ions. This has been studied for over two decades for bioremediative applications, but successful translation to industrial-scale processes is virtually non-existent. Meanwhile, demands for metal resources are increasing while discovery rates to supply primary grade ores are not. This review re-thinks how bioaccumulation can be used and proposes that it can be developed for bioextractive applications-the removal and recovery of heavy metal ions for downstream purification and refining, rather than disposal. This review consolidates previously tested import-storage systems into a biochemical framework and highlights efforts to overcome obstacles that limit industrial feasibility, thereby identifying gaps in knowledge and potential avenues of research in bioaccumulation.

Rational design of a hexameric protein assembly stabilized by metal chelation

Protein-based self-assembled nanostructures hold tremendous promise as smart materials. One strategy to control the assembly of individual protein modules takes advantage of the directionality and high affinity bonding afforded by metal chelation. Here, we describe the use of 2,2'-bipyridine units (Bpy) as side chains to template the assembly of large structures (MW approx. 35 000 Da) in a metal-dependent manner. The structures are trimers of independently folded 3-helix bundles, and are held together by 2 Me(Bpy)₃ complexes. The assemblies are stable to thermal denaturation, and are more than 90% helical at 90°C. Circular dichroism spectroscopy shows that one of the 2 possible (Bpy)₃ enantiomers is favored over the other. Because of the sequence pliability of the starting peptides, these constructs could find use to organize functional groups at controlled positions within a supramolecular assembly.

Development of de Novo Copper Nitrite Reductases: Where We Are and Where We Need To Go

The development of redox-active metalloprotein catalysts is a challenging objective of de novo protein design. Within this Perspective we detail our efforts to create a redox-active Cu nitrite reductase (NiR) by incorporating Cu into the hydrophobic interior of well-defined three-stranded coiled coils (3SCCs). The scaffold contains three histidine residues that provide a layer of three nitrogen donors that mimic the type 2 catalytic site of NiR. We have found that this strategy successfully produces an active and stable CuNiR model that functions for over 1000 turnovers. Spectroscopic evidence indicates that the Cu(I) site has a lower coordination number in comparison to the enzyme, whereas the Cu(II) geometry may more faithfully reproduce the NiR type 2 center. Mutations at the helical interface successfully produce a hydrogen bond between an interfacial Glu residue and the Culigating His residue, which allows for the tuning of the redox potential over a 100 mV range. We successfully created constructs with as much as a 120-fold improvement from the original design by modifying the steric bulk above or below the Cu binding site. These systems are now the most active water-soluble and stable artificial NiR catalysts yet produced. Several avenues for improving the catalytic efficiency of later designs are detailed within this Perspective, including adjustment of their resting oxidation state, the use of asymmetric scaffolds to allow for single amino acid mutation within the second coordination sphere, and the design of hydrogen-bonding networks to tune residue orientation and electronics. Through these studies the TRI-H system has given insight into the difficulties that arise in creating a de novo redox active enzyme. Work to improve upon this model will provide strategies by which redox-active de novo enzymes may be tuned and detail how native enzymes accomplish catalytic efficiencies through proton gated redox catalysis.

Engineered Metalloenzymes with Non-Canonical Coordination Environments

Nature employs a limited number of genetically encoded, metal-coordinating residues to create metalloenzymes with diverse structures and functions. Engineered components of the cellular translation machinery can now be exploited to encode non-canonical ligands with user-defined electronic and structural properties. This ability to install "chemically programmed" ligands into proteins can provide powerful chemical probes of metalloenzyme mechanism and presents excellent opportunities to create metalloprotein catalysts with augmented properties and novel activities. In this Concept article, we provide an overview of several recent studies describing the creation of engineered metalloenzymes with interesting catalytic properties, and reveal how characterization of these systems has advanced our understanding of nature's bioinorganic mechanisms. We also highlight how powerful laboratory evolution protocols can be readily adapted to allow optimization of metalloenzymes with non-canonical ligands. This approach combines beneficial features of small molecule and protein catalysis by allowing the installation of a greater variety of local metal coordination environments into evolvable protein scaffolds, and holds great promise for the future creation of powerful metalloprotein catalysts for a host of synthetically valuable transformations.

Computational protein design-the next generation tool to expand synthetic biology applications

One powerful approach to engineer synthetic biology pathways is the assembly of proteins sourced from one or more natural organisms. However, synthetic pathways often require custom functions or biophysical properties not displayed by natural proteins, limitations that could be overcome through modern protein engineering techniques. Structure-based computational protein design is a powerful tool to engineer new functional capabilities in proteins, and it is beginning to have a profound impact in synthetic biology. Here, we review efforts to increase the capabilities of synthetic biology using computational protein design. We focus primarily on computationally designed proteins not only validated in vitro, but also shown to modulate different activities in living cells. Efforts made to validate computational designs in cells can illustrate both the challenges and opportunities in the intersection of protein design and synthetic biology. We also highlight protein design approaches, which although not validated as conveyors of new cellular function in situ, may have rapid and innovative applications in synthetic biology. We foresee that in the near-future, computational protein design will vastly expand the functional capabilities of synthetic cells.

Playing with the Molecules of Life

Our understanding of the complex molecular processes of living organisms at the molecular level is growing exponentially. This knowledge, together with a powerful arsenal of tools for manipulating the structures of macromolecules, is allowing chemists to to harness and reprogram the cellular machinery in ways previously unimaged. Here we review one example in which the genetic code itself has been expanded with new building blocks that allow us to probe and manipulate the structures and functions of proteins with unprecedented precision.

Rational and Semirational Protein Design

This mini review gives an overview over different design approaches and methodologies applied in rational and semirational enzyme engineering. The underlying principles for engineering novel activities, enantioselectivity, substrate specificity, stability, and pH optimum are summarized.

Genetically encoded fluorescent sensors for measuring transition and heavy metals in biological systems

Great progress has been made in expanding the repertoire of genetically encoded fluorescent sensors for monitoring intracellular transition metals (TMs). This powerful toolkit permits dynamic and non-invasive detection of TMs with high spatial-temporal resolution, which enables us to better understand the roles of TM homeostasis in both physiological and pathological settings. Here we summarize the recent development of genetically encoded fluorescent sensors for intracellular detection of TMs such as zinc and copper, as well as heavy metals including lead, cadmium, mercury, and arsenic.

Expanding and reprogramming the genetic code

Nature uses a limited, conservative set of amino acids to synthesize proteins. The ability to genetically encode an expanded set of building blocks with new chemical and physical properties is transforming the study, manipulation and evolution of proteins, and is enabling diverse applications, including approaches to probe, image and control protein function, and to precisely engineer therapeutics. Underpinning this transformation are strategies to engineer and rewire translation. Emerging strategies aim to reprogram the genetic code so that noncanonical biopolymers can be synthesized and evolved, and to test the limits of our ability to engineer the translational machinery and systematically recode genomes.

Design of an enantioselective artificial metallo-hydratase enzyme containing an unnatural metal-binding amino acid

The design of artificial metalloenzymes is a challenging, yet ultimately highly rewarding objective because of the potential for accessing new-to-nature reactions. One of the main challenges is identifying catalytically active substrate-metal cofactor-host geometries. The advent of expanded genetic code methods for the in vivo incorporation of non-canonical metal-binding amino acids into proteins allow to address an important aspect of this challenge: the creation of a stable, well-defined metal-binding site. Here, we report a designed artificial metallohydratase, based on the transcriptional repressor lactococcal multidrug resistance regulator (LmrR), in which the non-canonical amino acid (2,2'-bipyridin-5yl)alanine is used to bind the catalytic Cu(ii) ion. Starting from a set of empirical pre-conditions, a combination of cluster model calculations (QM), protein-ligand docking and molecular dynamics simulations was used to propose metallohydratase variants, that were experimentally verified. The agreement observed between the computationally predicted and experimentally observed catalysis results demonstrates the power of the artificial metalloenzyme design approach presented here.

Benchmarking a computational design method for the incorporation of metal ion-binding sites at symmetric protein interfaces

The design of novel metal-ion binding sites along symmetric axes in protein oligomers could provide new avenues for metalloenzyme design, construction of protein-based nanomaterials and novel ion transport systems. Here, we describe a computational design method, symmetric protein recursive ion-cofactor sampling (SyPRIS), for locating constellations of backbone positions within oligomeric protein structures that are capable of supporting desired symmetrically coordinated metal ion(s) chelated by sidechains (chelant model). Using SyPRIS on a curated benchmark set of protein structures with symmetric metal binding sites, we found high recovery of native metal coordinating rotamers: in 65 of the 67 (97.0%) cases, native rotamers featured in the best scoring model while in the remaining cases native rotamers were found within the top three scoring models. In a second test, chelant models were crossmatched against protein structures with identical cyclic symmetry. In addition to recovering all native placements, 10.4% (8939/86013) of the non-native placements, had acceptable geometric compatibility scores. Discrimination between native and non-native metal site placements was further enhanced upon constrained energy minimization using the Rosetta energy function. Upon sequence design of the surrounding first-shell residues, we found further stabilization of native placements and a small but significant (1.7%) number of non-native placement-based sites with favorable Rosetta energies, indicating their designability in existing protein interfaces. The generality of the SyPRIS approach allows design of novel symmetric metal sites including with non-natural amino acid sidechains, and should enable the predictive incorporation of a variety of metal-containing cofactors at symmetric protein interfaces.