Theoretical and Computational Protein Design

Samish, Ilan; MacDermaid, Christopher M.; Pérez-Aguilar, José Manuel; Saven, Jeffery G.

doi:10.1146/annurev-physchem-032210-103509

Cited by 128 publications

(155 citation statements)

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“…In many applications of protein design, designability of a structure is made accessible by using structures from naturally occurring proteins (24,27,32,33), but here both the structure of the protein as well as its crystalline ordering are specified de novo. A trimeric coiled-coil protein is designed to fold into a stable unit that then further assembles into a crystalline structure.…”

Section: Resultsmentioning

confidence: 99%

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Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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Protein crystals have catalytic and materials applications and are central to efforts in structural biology and therapeutic development. Designing predetermined crystal structures can be subtle given the complexity of proteins and the noncovalent interactions that govern crystallization. De novo protein design provides an approach to engineer highly complex nanoscale molecular structures, and often the positions of atoms can be programmed with sub-Å precision. Herein, a computational approach is presented for the design of proteins that self-assemble in three dimensions to yield macroscopic crystals. A three-helix coiled-coil protein is designed de novo to form a polar, layered, three-dimensional crystal having the P6 space group, which has a "honeycomb-like" structure and hexameric channels that span the crystal. The approach involves: (i) creating an ensemble of crystalline structures consistent with the targeted symmetry; (ii) characterizing this ensemble to identify "designable" structures from minima in the sequencestructure energy landscape and designing sequences for these structures; (iii) experimentally characterizing candidate proteins. A 2.1 Å resolution X-ray crystal structure of one such designed protein exhibits sub-Å agreement [backbone root mean square deviation (rmsd)] with the computational model of the crystal. This approach to crystal design has potential applications to the de novo design of nanostructured materials and to the modification of natural proteins to facilitate X-ray crystallographic analysis.M olecular design provides powerful tools for exploring how molecular properties dictate macroscopic structure and function. One of the most precise forms of self-organization, crystallization achieves orientation and symmetry across many length scales and can be leveraged to engineer materials with well-defined molecular order (1). In addition to their central role in structure determination, molecular crystals have many applications, including nanoparticle templating (2, 3), nonlinear optical devices (4), molecular scaffolding (5), and porous frameworks (6). A predictive understanding of how to achieve self-assembled macroscale structure and desired properties remains challenging, however, particularly when large, conformationally flexible molecules are employed.Small synthetic molecules have been designed that display complementary functional groups in a manner consistent with a chosen crystal structure. Intermolecular contacts are often patterned using strong, directional interactions (e.g., hydrogen bonding, metalcoordination, and electrostatic interactions) (7). The constituent molecules, however, are typically small and synthetic, thus limiting size, shape, and functionality. Hence, simultaneously achieving functional properties and the presentation of complementary intermolecular interactions that confer a targeted crystal structure can be difficult. Commonly, weak intermolecular forces stabilize crystalline ordering, and as a result, quantitative, predictive approaches to crystal de...

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Section: Resultsmentioning

confidence: 99%

“…Computational protein design continues to advance (22)(23)(24)(25)(26)(27)(28)(29)(30)(31), and herein a strategy for designing a predetermined protein crystal structure is presented. A three-helix coiled-coil protein was designed de novo to form a polar, layered three-dimensional crystal having the P6 space group.…”

mentioning

confidence: 99%

Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

158

165

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“…This is again in contrast to heterotropic allostery, in which each binding site is chemically distinct, allowing each to be independently optimized. Given these difficulties, and given the relative infancy of biomolecular design efforts (20)(21)(22), the ability to perform the structure-based design of cooperativity appears beyond current capabilities except for the simplest, most well-understood receptors (9)(10)(11)(12). Here, however, we use an approach to the rational engineering of allosterically cooperative receptors that does not require detailed, structure-based design.…”

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confidence: 99%

Intrinsic disorder as a generalizable strategy for the rational design of highly responsive, allosterically cooperative receptors

Simon

Vallée‐Bélisle

Ricci

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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Control over the sensitivity with which biomolecular receptors respond to small changes in the concentration of their target ligand is critical for the proper function of many cellular processes. Such control could likewise be of utility in artificial biotechnologies, such as biosensors, genetic logic gates, and "smart" materials, in which highly responsive behavior is of value. In nature, the control of molecular responsiveness is often achieved using "Hilltype" cooperativity, a mechanism in which sequential binding events on a multivalent receptor are coupled such that the first enhances the affinity of the next, producing a steep, higher-order dependence on target concentration. Here, we use an intrinsicdisorder-based mechanism that can be implemented without requiring detailed structural knowledge to rationally introduce this potentially useful property into several normally noncooperative biomolecules. To do so, we fabricate a tandem repeat of the receptor that is destabilized (unfolded) via the introduction of a long, unstructured loop. The first binding event requires the energetically unfavorable closing of this loop, reducing its affinity relative to that of the second binding event, which, in contrast occurs at a preformed site. Using this approach, we have rationally introduced cooperativity into three unrelated DNA aptamers, achieving in the best of these a Hill coefficient experimentally indistinguishable from the theoretically expected maximum. The extent of cooperativity and thus the steepness of the binding transition are, moreover, well modeled as simple functions of the energetic cost of binding-induced folding, speaking to the quantitative nature of this design strategy. ultrasensitivity | intrinsically disordered proteins | biosensors | synthetic biology | ribozymes

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“…As in most simulation fields, a compromise between sampling quality and quantity is necessary. Sampling quality involves construction of the models together with the energy and scoring functions necessary to rank them and evaluate molecular interactions, topics extensively reviewed previously [63,[79][80][81][82][83][84][85][86][87][88][89][90][91][92]]. An energy function describes the internal energy of the protein and its interactions with the environment such as other proteins, substrates and solvent, aiming at reproducing the features of the folded protein [34,84,93].…”

mentioning

confidence: 99%

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

Monza

Acebes

Lucas

et al. 2017

Directed Enzyme Evolution: Advances and Applications

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Directed evolution creates diversity in subsequent rounds of mutagenesis in the quest of increased protein stability, substrate binding and catalysis. Although this technique does not require any structural/mechanistic knowledge of the system, the frequency of improved mutations is usually low. For this reason, computational tools are increasingly used to focus the search in sequence space, enhancing the efficiency of laboratory evolution. In particular, molecular modeling methods provide a unique tool to grasp the sequence/structure/function relationship The final publication is available at Springer via https://link.springer.com/chapter/10.1007/978-3-319-50413-1_10/fulltext.html of the protein to evolve, with the only condition that a structural model is provided. With this book chapter, we tried to guide the reader through the state of art of molecular modeling, discussing their strengths, limitations and directions. In addition, we suggest a possible future template for in silico directed evolution where we underline two main points: a hierarchical computational protocol combining several different techniques, and a synergic effort between simulations and experimental validation. IntroductionBiotechnology needs catalysts that can work under harsh conditions, catalyze a broad range of substrates, generate maximum amount of product, and tolerate changes in the environment. Enzymes, which are biodegradable and reusable catalysts [1], in addition to remarkable reaction rates, can work in environmentally friendly pH and temperature ranges, and display control over stereochemistry and regioselectivity which makes them ideal for many applications [2,3]. When thinking about enzymes, people normally associate them to expressions such as "perfect catalysts" or "outstanding reaction rate". In fact, there are examples of enzymes that catalyze reactions at extremely high rates such as triose phosphate isomerase, superoxide dismutase or carbonic anhydrase [4]. These are often limited only by the rate of ligand diffusion into the active site (diffusion-controlled rate). Nevertheless, an extensive analysis by Bar-Even et al., of nearly 2000 enzymes, showed that the median maximal turnover rate value over all measured enzymes is about 10 s −1 nowhere close to the values of 10 5 or 10 6 normally associated with catalysts [5,6].So, it would appear that natural enzymes are "just good enough" for the function they must perform in a given organism [7]. One might conclude that if they had evolved to their optimum performance then trying to improve them (from a kinetic point of view) would be attempting the impossible. On the contrary, as seen by the distribution of reaction rates, k cat , most enzymes function at a lower rate than the diffusion-limit and thus, there is space to further increase their kinetic properties to meet industrial needs. Additionally, we need enzymes capable of catalyzing reactions for which no known enzymes exist, to work with different substrates and for particular conditions that are industrially...

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Theoretical and Computational Protein Design

Cited by 128 publications

References 148 publications

Computational design of a protein crystal

Computational design of a protein crystal

Intrinsic disorder as a generalizable strategy for the rational design of highly responsive, allosterically cooperative receptors

Molecular Modeling in Enzyme Design, Toward In Silico Guided Directed Evolution

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