Principles of nanostructure design with protein building blocks

Currently there is increasing interest in nanostructures and their design. Nanostructure design involves the ability to predictably manipulate the properties of the self-assembly of autonomous units. Autonomous units have preferred conformational states. The units can be synthetic material science-based or derived from functional biological macromolecules. Autonomous biological building blocks with available structures provide an extremely rich and useful resource for design. For proteins, the structural databases contain large libraries of protein molecules and their building blocks with a range of shapes, surfaces, and chemical properties. The introduction of engineered synthetic residues or short peptides into these can expand the available chemical space and enhance the desired properties. Here we focus on the principles of nanostructure design with protein building blocks.     

In silico design of potent EGFR kinase inhibitors using combinatorial libraries

This paper is an attempt to design 4-anilinoquinazoline compounds having promising anticancer activities against epidermal growth factor (EGFR) kinase inhibition, using virtual combinatorial library approach. Partial least squares method has been applied for the development of a quantitative structure–activity relationship (QSAR) model based on training and test set approaches. The partial least squares model showed some interesting results in terms of internal and external predictability against EGFR kinase inhibition for such type of anilinoquinazoline derivatives. In virtual screening study, out of 4860 compounds in chemical library, 158 compounds were screened and finally, 10 compounds were selected as promising EGFR kinase inhibitors based on their predicted activities from the QSAR model. These derivatives were subjected to molecular docking study to investigate the mode of binding with the EGFR kinase, and the two compounds (ID 3639 and 3399) showing similar type of docking score and binding patterns with that of the existing drug molecules like erlotinib were finally reported.     

基于结构的CRISPR蛋白xCas9的优化设计

酿脓链球菌(Streptococcus pyogenes Cas9,SpCas9)已成为强大的基因组编辑工具,但其可识别的前间隔序列临近基序(Protospacer adjacent motifs,PAMs)范围有限,且存在脱靶效应.为解决这些问题,文中提出一种对SpCas9的定向进化突变体xCas9进行优化的理性方法...     

Nanoscale elongating control of the self‐assembled protein filament with the cysteine‐introduced building blocks

Self‐assembly of artificially designed proteins is extremely desirable for nanomaterials. Here we show a novel strategy for the creation of self‐assembling proteins, named “Nanolego.” Nanolego consists of “structural elements” of a structurally stable symmetrical homo‐oligomeric protein and “binding elements,” which are multiple heterointeraction proteins with relatively weak affinity. We have established two key technologies for Nanolego, a stabilization method and a method for terminating the self‐assembly process. The stabilization method is mediated by disulfide bonds between Cysteine‐residues incorporated into the binding elements, and the termination method uses “capping Nanolegos,” in which some of the binding elements in the Nanolego are absent for the self‐assembled ends. With these technologies, we successfully constructed timing‐controlled and size‐regulated filament‐shape complexes via Nanolego self‐assembly. The Nanolego concept and these technologies should pave the way for regulated nanoarchitecture using designed proteins.     

In silico predictions of LH2 ring sizes from the crystal structure of a single subunit using molecular dynamics simulations

Most of the currently known light‐harvesting complexes 2 (LH2) rings are formed by 8 or 9 subunits. As of now, questions like “what factors govern the LH2 ring size?” and “are there other ring sizes possible?” remain largely unanswered. Here, we investigate by means of molecular dynamics (MD) simulations and stochastic modeling the possibility of predicting the size of an LH2 ring from the sole knowledge of the high resolution crystal structure of a single subunit. Starting with single subunits of two LH2 rings with known size, that is, an 8‐ring from Rs. moliscianum (MOLI) and a 9‐ring from Rps. acidophila (ACI), and one with unknown size (referred to as X), we build atomic models of subunit dimers corresponding to assumed 8‐, 9‐, and 10‐ring geometries. After inserting each of the dimers into a lipid‐water environment, we determine the preferred angle between the corresponding subunits by three methods: (1) energy minimization, (2) free MD simulations, and (3) potential of mean force calculations. We find that the results from all three methods are consistent with each other, and when taken together, it allows one to predict with reasonable level of confidence the sizes of the corresponding ring structures. One finds that X and ACI very likely form a 9‐ring, while MOLI is more likely to form an 8‐ring than a 9‐ring. Finally, we discuss both the merits and limitations of all three prediction methods. Proteins 2011; © 2011 Wiley‐Liss, Inc.     

Structure determination of a protein assembly by amino acid selective cross-saturation

Amino acid selective cross-saturation (ASCS) method not only provides information about the interface of a protein assembly by the spin relaxation experiment, but also identifies the amino acid residues in the acceptor protein, which are located close to the selectively labeled amino acid residues in the donor protein. Here, a new method was developed to build a precise structural model of a protein assembly, which satisfies the experimental ASCS values, using simulated annealing computation. This method was applied to the ubiquitin-yeast ubiquitin hydrolase 1 (Ub-YUH1) complex to build a precise complex structure compatible with that determined by X-ray crystallography.     

Biologically inspired strategy for programmed assembly of viral building blocks with controlled dimensions

Facile fabrication of building blocks with precisely controlled dimensions is imperative in the development of functional devices and materials. We demonstrate the assembly of nanoscale viral building blocks of controlled lengths using a biologically motivated strategy. To achieve this we exploit the simple self-assembly mechanism of Tobacco mosaic virus (TMV), whose length is solely governed by the length of its genomic mRNA. We synthesize viral mRNA of desired lengths using simple molecular biology techniques, and in vitro assemble the mRNA with viral coat proteins to yield viral building blocks of controlled lengths. The results indicate that the assembly of the viral building blocks is consistent and reproducible, and can be readily extended to assemble building blocks with genetically modified coat proteins (TMV1cys). Additionally, we confirm the potential utility of the TMV1cys viral building blocks with controlled dimensions via covalent and quantitative conjugation of fluorescent markers. We envision that our biologically inspired assembly strategy to design and construct viral building blocks of controlled dimensions could be employed to fabricate well-controlled nanoarchitectures and hybrid nanomaterials for a wide variety of applications including nanoelectronics and nanocatalysis.     

Tertiary motifs as building blocks for the design of protein‐binding peptides

Despite advances in protein engineering, the de novo design of small proteins or peptides that bind to a desired target remains a difficult task. Most computational methods search for binder structures in a library of candidate scaffolds, which can lead to designs with poor target complementarity and low success rates. Instead of choosing from pre‐defined scaffolds, we propose that custom peptide structures can be constructed to complement a target surface. Our method mines tertiary motifs (TERMs) from known structures to identify surface‐complementing fragments or “seeds.” We combine seeds that satisfy geometric overlap criteria to generate peptide backbones and score the backbones to identify the most likely binding structures. We found that TERM‐based seeds can describe known binding structures with high resolution: the vast majority of peptide binders from 486 peptide‐protein complexes can be covered by seeds generated from single‐chain structures. Furthermore, we demonstrate that known peptide structures can be reconstructed with high accuracy from peptide‐covering seeds. As a proof of concept, we used our method to design 100 peptide binders of TRAF6, seven of which were predicted by Rosetta to form higher‐quality interfaces than a native binder. The designed peptides interact with distinct sites on TRAF6, including the native peptide‐binding site. These results demonstrate that known peptide‐binding structures can be constructed from TERMs in single‐chain structures and suggest that TERM information can be applied to efficiently design novel target‐complementing binders.     

In silico design of novel hERG-neutral sildenafil-like PDE5 inhibitors

Cyclic nucleotide phosphodiesterase enzymes (PDEs) have functions in regulating the levels of intracellular second messengers, 3′, 5′-cyclic adenosine monophosphate (cAMP) and 3′, 5′-cyclic guanosine monophosphate (cGMP), via hydrolysis and decomposing mechanisms in cells. They take essential roles in modulating various cellular activities such as memory and smooth muscle functions. PDE type 5 (PDE5) inhibitors enhance the vasodilatory effects of cGMP in the corpus cavernosum and they are used to treat erectile dysfunction. Patch clamp experiments showed that the IC₅₀ values of the human ether-à-go-go-related gene (hERG1) potassium (K) ion channel blocking affinity of PDE5 inhibitors sildenafil, vardenafil, and tadalafil as 33, 12, and 100 μM, respectively. hERG1 channel is responsible for the regulation of the action potential of human ventricular myocyte by contributing the rapid component of delayed rectifier K⁺ current (I_Kr) component of the cardiac action potential. In this work, interaction patterns and binding affinity predictions of selected PDE5 inhibitors against the hERG1 channel are studied. It is attempted to develop PDE5 inhibitor analogs with lower binding affinity to hERG1 ion channel while keeping their pharmacological activity against their principal target PDE5 using in silico methods. Based on detailed analyses of docking poses and predicted interaction energies, novel analogs of PDE5 inhibitors with lower predicted binding affinity to hERG1 channels without loosing their principal target activity were proposed. Moreover, molecular dynamics (MD) simulations and post-processing MD analyses (i.e. Molecular Mechanics/Generalized Born Surface Area calculations) were performed. Detailed analysis of molecular simulations helped us to better understand the PDE5 inhibitor–target binding interactions in the atomic level. Results of this study can be useful for designing of novel and safe PDE5 inhibitors with enhanced activity and other tailored properties.     

Fast gap‐free enumeration of conformations and sequences for protein design

Despite significant successes in structure‐based computational protein design in recent years, protein design algorithms must be improved to increase the biological accuracy of new designs. Protein design algorithms search through an exponential number of protein conformations, protein ensembles, and amino acid sequences in an attempt to find globally optimal structures with a desired biological function. To improve the biological accuracy of protein designs, it is necessary to increase both the amount of protein flexibility allowed during the search and the overall size of the design, while guaranteeing that the lowest‐energy structures and sequences are found. DEE/A*‐based algorithms are the most prevalent provable algorithms in the field of protein design and can provably enumerate a gap‐free list of low‐energy protein conformations, which is necessary for ensemble‐based algorithms that predict protein binding. We present two classes of algorithmic improvements to the A* algorithm that greatly increase the efficiency of A*. First, we analyze the effect of ordering the expansion of mutable residue positions within the A* tree and present a dynamic residue ordering that reduces the number of A* nodes that must be visited during the search. Second, we propose new methods to improve the conformational bounds used to estimate the energies of partial conformations during the A* search. The residue ordering techniques and improved bounds can be combined for additional increases in A* efficiency. Our enhancements enable all A*‐based methods to more fully search protein conformation space, which will ultimately improve the accuracy of complex biomedically relevant designs. Proteins 2015; 83:1859–1877. © 2015 Wiley Periodicals, Inc.     

Structure‐based design of combinatorial mutagenesis libraries

The development of protein variants with improved properties (thermostability, binding affinity, catalytic activity, etc.) has greatly benefited from the application of high‐throughput screens evaluating large, diverse combinatorial libraries. At the same time, since only a very limited portion of sequence space can be experimentally constructed and tested, an attractive possibility is to use computational protein design to focus libraries on a productive portion of the space. We present a general‐purpose method, called “Structure‐based Optimization of Combinatorial Mutagenesis ” (SOCoM ), which can optimize arbitrarily large combinatorial mutagenesis libraries directly based on structural energies of their constituents. SOCoM chooses both positions and substitutions, employing a combinatorial optimization framework based on library‐averaged energy potentials in order to avoid explicitly modeling every variant in every possible library. In case study applications to green fluorescent protein, β‐lactamase, and lipase A, SOCoM optimizes relatively small, focused libraries whose variants achieve energies comparable to or better than previous library design efforts, as well as larger libraries (previously not designable by structure‐based methods) whose variants cover greater diversity while still maintaining substantially better energies than would be achieved by representative random library approaches. By allowing the creation of large‐scale combinatorial libraries based on structural calculations, SOCoM promises to increase the scope of applicability of computational protein design and improve the hit rate of discovering beneficial variants. While designs presented here focus on variant stability (predicted by total energy), SOCoM can readily incorporate other structure‐based assessments, such as the energy gap between alternative conformational or bound states.     

Cyclopeptides design as blockers against HCV p7 channel in silico

ABSTRACT

The protein p7 in the hepatitis C virus (HCV) is a 63-residue transmembrane protein that oligomerizes to form an ion channel with cation selectivity. This protein is essential for the assembly and release of infectious viral particles. Structural analysis indicates that the bottleneck of the p7 hexamer channel is located on Asparagines at position 9 in the conical region with a pore radius of 3.9?Å, which is reduced to nearly 3.0?Å upon protonation. Amantadine and BIT225 binds in the hydrophobic pocket on the lipid-facing side of the p7 channel as allosteric inhibitors to stabilise the channel pore in a closed conformation. Here, we designed a series of cyclopeptides as inner channel blockers in the conical region based on chemical and physical characteristics of the channel bottleneck for the HCV p7 protein. As a result, cyclic-4-Asp is found to bind in the channel lumen between the gating residues Ile6 and Asn9 with a favourable binding affinity, perfectly fitting with the hydrophobic pocket in the conical region. Compared with amantadine and BIT225, we believe that the cylcopeptides have potential to be effective inhibitors against HCV p7 protein.     

In silico development of new acetylcholinesterase inhibitors

In this work, we made use of fragment-based drug design (FBDD) and de novo design to obtain more powerful acetylcholinesterase (AChE) inhibitors. AChE is associated with Alzheimer’s disease (AD). It was found that the cholinergic pathways in the cerebral cortex are compromised in AD and the accompanying cholinergic deficiency contributes to the cognitive deterioration of AD patients. In the FBDD approach, fragments are docked into the active site of the protein. As fragments are molecular groups with a low number of atoms, it is possible to study their interaction with localized amino acids. Once the interactions are measured, the fragments are organized by affinity and then linked together to form new molecules with a high degree of interaction with the active site. In the other approach, we used the de novo design technique starting from reference drugs used in the AD treatment. These drugs were broken into fragments (seeds). In the growing strategy, fragments were added to each seed, growing new molecules. In the linking strategy, two or more separated seeds were linked with different fragments. Both strategies combined produced a library of more than 2 million compounds. This library was filtered using absorption, distribution, metabolism, and excretion properties. The resulting library with around six thousand compounds was filtered again. In this case, structures with Tanimoto coefficients >.85 were discarded. The final library with 1500 compounds was submitted to docking studies. As a result, 10 compounds with better interaction energy than the reference drugs were obtained.     

Plasticity in eucaryotic 20S proteasome ring assembly revealed by a subunit deletion in yeast

The 20S proteasome is made up of four stacked heptameric rings, which in eucaryotes assemble from 14 different but related subunits. The rules governing subunit assembly and placement are not understood. We show that a different kind of proteasome forms in yeast when the Pre9/alpha3 subunit is deleted. Purified pre9Delta proteasomes show a two-fold enrichment for the Pre6/alpha4 subunit, consistent with the presence of an extra copy of Pre6 in each outer ring. Based on disulfide engineering and structure-guided suppressor analyses, Pre6 takes the position normally occupied by Pre9, a substitution that depends on a network of intersubunit salt bridges. When Arabidopsis PAD1/alpha4 is expressed in yeast, it complements not only pre6Delta but also pre6Delta pre9Delta mutants; therefore, the plant alpha4 subunit also can occupy multiple positions in a functional yeast proteasome. Importantly, biogenesis of proteasomes is delayed at an early stage in pre9Delta cells, suggesting an advantage for Pre9 over Pre6 incorporation at the alpha3 position that facilitates correct assembly.     

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.     

Computational protein design

The field of computational protein design is reaching its adolescence. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. Further developments of scoring functions, sampling strategies, and optimization methods will expand the range of applicability of computational protein design to larger and more varied systems, with greater incidence of success. Developments in this field are beginning to have significant impact on biotechnology and chemical biology.     

Improved energy bound accuracy enhances the efficiency of continuous protein design

Flexibility and dynamics are important for protein function and a protein's ability to accommodate amino acid substitutions. However, when computational protein design algorithms search over protein structures, the allowed flexibility is often reduced to a relatively small set of discrete side‐chain and backbone conformations. While simplifications in scoring functions and protein flexibility are currently necessary to computationally search the vast protein sequence and conformational space, a rigid representation of a protein causes the search to become brittle and miss low‐energy structures. Continuous rotamers more closely represent the allowed movement of a side chain within its torsional well and have been successfully incorporated into the protein design framework to design biomedically relevant protein systems. The use of continuous rotamers in protein design enables algorithms to search a larger conformational space than previously possible, but adds additional complexity to the design search. To design large, complex systems with continuous rotamers, new algorithms are needed to increase the efficiency of the search. We present two methods, PartCR and HOT, that greatly increase the speed and efficiency of protein design with continuous rotamers. These methods specifically target the large errors in energetic terms that are used to bound pairwise energies during the design search. By tightening the energy bounds, additional pruning of the conformation space can be achieved, and the number of conformations that must be enumerated to find the global minimum energy conformation is greatly reduced. Proteins 2015; 83:1151–1164. © 2015 Wiley Periodicals, Inc.