Assessment of the optimization of affinity and specificity at protein-DNA interfaces

Engineering of Zinc Finger Nucleases Through Structural Modeling Improves Genome Editing Efficiency in Cells

Genome Editing is widely used in biomedical research and medicine. Zinc finger nucleases (ZFNs) are smaller in size than transcription activator-like effector (TALE) nucleases (TALENs) and CRISPR-Cas9. Therefore, ZFN-encoding DNAs can be easily packaged into a viral vector with limited cargo space, such as adeno-associated virus (AAV) vectors, for in vivo and clinical applications. ZFNs have great potential for translational research and clinical use. However, constructing functional ZFNs and improving their genome editing efficiency is extremely difficult. Here, the efficient construction of functional ZFNs and the improvement of their genome editing efficiency using AlphaFold, Coot, and Rosetta are described. Plasmids encoding ZFNs consisting of six fingers using publicly available zinc-finger resources are assembled. Two functional ZFNs from the ten ZFNs tested are successfully obtained. Furthermore, the engineering of ZFNs using AlphaFold, Coot, or Rosetta increases the efficiency of genome editing by 5%, demonstrating the effectiveness of engineering ZFNs based on structural modeling.

Multiple adaptations underly co-option of a CRISPR surveillance complex for RNA-guided DNA transposition

CRISPR-associated transposons (CASTs) are natural RNA-directed transposition systems. We demonstrate that transposon protein TniQ plays a central role in promoting R-loop formation by RNA-guided DNA-targeting modules. TniQ residues, proximal to CRISPR RNA (crRNA), are required for recognizing different crRNA categories, revealing an unappreciated role of TniQ to direct transposition into different classes of crRNA targets. To investigate adaptations allowing CAST elements to utilize attachment sites inaccessible to CRISPR-Cas surveillance complexes, we compared and contrasted PAM sequence requirements in both I-F3b CAST and I-F1 CRISPR-Cas systems. We identify specific amino acids that enable a wider range of PAM sequences to be accommodated in I-F3b CAST elements compared with I-F1 CRISPR-Cas, enabling CAST elements to access attachment sites as sequences drift and evade host surveillance. Together, this evidence points to the central role of TniQ in facilitating the acquisition of CRISPR effector complexes for RNA-guided DNA transposition.

Active-Site Models of Streptococcus pyogenes Cas9 in DNA Cleavage State

CRISPR-Cas9 is a powerful tool for target genome editing in living cells. Significant advances have been made to understand how this system cleaves target DNA. HNH is a nuclease domain, which shares structural similarity with the HNH endonuclease characterzied by a beta-beta-alpha-metal fold. Therefore, based on one- and two-metal-ion mechanisms, homology modeling and molecular dynamics (MD) simulation are suitable tools for building an atomic model of Cas9 in the DNA cleavage state. Here, by modeling and MD, we presented an atomic model of SpCas9-sgRNA-DNA complex with the cleavage state. This model shows that the HNH and RuvC conformations resemble their DNA cleavage state where the active-sites in the complex coordinate with DNA, Mg²⁺ ions, and water. Among them, residues D10, E762, H983, and D986 locate at the first shell of the RuvC active-site and interact with the ions directly, residues H982 or/and H985 are general (Lewis) bases, and the coordinated water is located at the positions for nucleophilic attack of the scissile phosphate. Meanwhile, this catalytic model led us to engineer a new SpCas9 variant (SpCas9-H982A + H983D) with reduced off-target effects. Thus, our study provided new mechanistic insights into the CRISPR-Cas9 system in the DNA cleavage state and offered useful guidance for engineering new CRISPR-Cas9 editing systems with improved specificity.

Understanding the structural details of APOBEC3-DNA interactions using graph-based representations

Human APOBEC3 (A3; apolipoprotein B mRNA editing catalytic polypeptide-like 3) is a family of seven enzymes involved in generating mutations in nascent reverse transcripts of many retroviruses, as well as the human genome in a range of cancer types. The structural details of the interaction between A3 proteins and DNA molecules are only available for a few family members. Here we use homology modelling techniques to address the difference in structural coverage of human A3 enzymes interacting with different DNA substrates. A3-DNA interfaces are represented as residue networks ("graphs"), based on which features at these interfaces are compared and quantified. We demonstrate that graph-based representations are effective in highlighting structural features of A3-DNA interfaces. By large-scale in silico mutagenesis of the bound DNA chain, we predicted the preference of substrate DNA sequence for multiple A3 domains. These data suggested that computational modelling approaches could contribute in the exploration of the structural basis for sequence specificity in A3 substrate selection, and demonstrated the utility of graph-based approaches in evaluating a large number of structural models generated in silico.

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APOBEC3(A3)-DNA structures have been resolved with modified deaminase domains.

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Structural modelling of interaction between wild-type A3 domains and DNA substrates.

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Graph-based representations reveal structural differences across A3-DNA interfaces.

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Using in silico mutagenesis we compared substrate preference of multiple A3 domains.

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Graph-based approaches can efficiently compare a large number of structural models.

Optimizing the Specificity Window of Biomolecular Receptors Using Structure-Switching and Allostery

To ensure maximum specificity (i.e., minimize cross-reactivity with structurally similar analogues of the desired target), most bioassays invoke "stringency", the careful tuning of the conditions employed (e.g., pH, ionic strength, or temperature). Willingness to control assay conditions will fall, however, as quantitative, single-step biosensors begin to replace multistep analytical processes. This is especially true for sensors deployed in vivo, where the tuning of such parameters is not just inconvenient but impossible. In response, we describe here the rational adaptation of two strategies employed by nature to tune the affinity of biomolecular receptors so as to optimize the placement of their specificity "windows" without the need to alter measurement conditions: structure-switching and allosteric control. We quantitatively validate these approaches using two distinct, DNA-based receptors: a simple, linear-chain DNA suitable for detecting a complementary DNA strand and a structurally complex DNA aptamer used for the detection of a small-molecule drug. Using these models, we show that, without altering assay conditions, structure-switching and allostery can tune the concentration range over which a receptor achieves optimal specificity over orders of magnitude, thus optimally matching the specificity window with the range of target concentrations expected to be seen in a given application.

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.

Better together: Elements of successful scientific software development in a distributed collaborative community

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities.

An Easy and Efficient Strategy for the Enhancement of Epothilone Production Mediated by TALE-TF and CRISPR/dcas9 Systems in Sorangium cellulosum

Epothilones are a kind of macrolides with strong cytotoxicity toward cancer cells and relatively lower side effects compared with taxol. Epothilone B derivate ixabepilone has been used for the clinical treatment of advanced breast cancer. However, the low yield of epothilones and the difficulty in the genetic manipulation of Sorangium cellulosum limited their wider application. Transcription activator-like effectors-Trancriptional factor (TALE-TF)-VP64 and clustered regularly interspaced short palindromic repeats (CRISPR)/dCas9-VP64 have been demonstrated as effective systems for the transcriptional improvement. In this study, a promoter for the epothilone biosynthesis cluster was obtained and the function has been verified. The TALE-TF-VP64 and CRISPR/dcas9-VP64 target P3 promoter were electroporated into S. cellulosum strain So ce M4, and the transcriptional levels of epothilone biosynthesis-related genes were significantly upregulated. The yield of epothilone B was improved by 2.89- and 1.53-fold by the introduction of recombinant TALE-TF-VP64-P3 and dCas9-VP64-P3 elements into So ce M4, respectively. The epothilone D yield was also improved by 1.12- and 2.18-fold in recombinant dCas9-So ce M4 and TALE-VP64 strains, respectively. The transcriptional regulation mechanism of TALE-TF-VP64 and the competition mechanism with endogenous transcriptional factor were investigated by electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP), demonstrating the combination of the P3 promoter and TALE-TF element and the competition between TALE-TF and endogenous transcriptional protein. This is the first report on the transcriptional regulation of the epothilone biosynthetic gene cluster in S. cellulosum using the TALE-TF and dCas9-VP64 systems, and the regulatory mechanism of the TALE-TF system for epothilone biosynthesis in S. cellulosum was also firstly revealed, thus shedding light on the metabolic engineering of S. cellulosum to improve epothilone yields substantially and promoting the application of epothilones in the biomedical industry.

Structural analysis reveals a "molecular calipers" mechanism for a LATERAL ORGAN BOUNDARIES DOMAIN transcription factor protein from wheat

LATERAL ORGAN BOUNDARIES DOMAIN (LBD) proteins, a family of plant-specific transcription factors harboring a conserved Lateral Organ Boundaries (LOB) domain, are regulators of plant organ development. Recent studies have unraveled additional pivotal roles of the LBD protein family beyond defining lateral organ boundaries, such as pollen development and nitrogen metabolism. The structural basis for the molecular network of LBD-dependent processes remains to be deciphered. Here, we solved the first structure of the homodimeric LOB domain of Ramosa2 from wheat (TtRa2LD) to 1.9 Å resolution. Our crystal structure reveals structural features shared with other zinc-finger transcriptional factors, as well as some features unique to LBD proteins. Formation of the TtRa2LD homodimer relied on hydrophobic interactions of its coiled-coil motifs. Several specific motifs/domains of the LBD protein were also involved in maintaining its overall conformation. The intricate assembly within and between the monomers determined the precise spatial configuration of the two zinc fingers that recognize palindromic DNA sequences. Biochemical, molecular modeling, and small-angle X-ray scattering experiments indicated that dimerization is important for cooperative DNA binding and discrimination of palindromic DNA through a molecular calipers mechanism. Along with previously published data, this study enables us to establish an atomic-scale mechanistic model for LBD proteins as transcriptional regulators in plants.

Structural insights into DNA cleavage activation of CRISPR-Cas9 system

CRISPR-Cas9 technology has been widely used for genome engineering. Its RNA-guided endonuclease Cas9 binds specifically to target DNA and then cleaves the two DNA strands with HNH and RuvC nuclease domains. However, structural information regarding the DNA cleavage-activating state of two nuclease domains remains sparse. Here, we report a 5.2 Å cryo-EM structure of Cas9 in complex with sgRNA and target DNA. This structure reveals a conformational state of Cas9 in which the HNH domain is closest to the DNA cleavage site. Compared with two known HNH states, our structure shows that the HNH active site moves toward the cleavage site by about 25 and 13 Å, respectively. In combination with EM-based molecular dynamics simulations, we show that residues of the nuclease domains in our structure could form cleavage-compatible conformations with the target DNA. Together, these results strongly suggest that our cryo-EM structure resembles a DNA cleavage-activating architecture of Cas9.

Statistical analysis of structural determinants for protein-DNA-binding specificity

DNA-binding proteins play critical roles in biological processes including gene expression, DNA packaging and DNA repair. They bind to DNA target sequences with different degrees of binding specificity, ranging from highly specific (HS) to nonspecific (NS). Alterations of DNA-binding specificity, due to either genetic variation or somatic mutations, can lead to various diseases. In this study, a comparative analysis of protein-DNA complex structures was carried out to investigate the structural features that contribute to binding specificity. Protein-DNA complexes were grouped into three general classes based on degrees of binding specificity: HS, multispecific (MS), and NS. Our results show a clear trend of structural features among the three classes, including amino acid binding propensities, simple and complex hydrogen bonds, major/minor groove and base contacts, and DNA shape. We found that aspartate is enriched in HS DNA binding proteins and predominately binds to a cytosine through a single hydrogen bond or two consecutive cytosines through bidentate hydrogen bonds. Aromatic residues, histidine and tyrosine, are highly enriched in the HS and MS groups and may contribute to specific binding through different mechanisms. To further investigate the role of protein flexibility in specific protein-DNA recognition, we analyzed the conformational changes between the bound and unbound states of DNA-binding proteins and structural variations. The results indicate that HS and MS DNA-binding domains have larger conformational changes upon DNA-binding and larger degree of flexibility in both bound and unbound states. Proteins 2016; 84:1147-1161. © 2016 Wiley Periodicals, Inc.

Designing peptide sequences in flexible chain conformations to bind RNA: a search algorithm combining Monte Carlo, self-consistent mean field and concerted rotation techniques

A search algorithm combining Monte Carlo, self-consistent mean field, and concerted rotation techniques was developed to discover peptide sequences that are reasonable HIV drug candidates due to their exceptional binding to human tRNAUUU(Lys3), the primer of HIV replication. The search algorithm allows for iteration between sequence mutations and conformation changes during sequence evolution. Searches conducted for different classes of peptides identified several potential peptide candidates. Analysis of the energy revealed that the asparagine and cysteine at residues 11 and 12 play important roles in "recognizing" tRNA(Lys3) via van der Waals interactions, contributing to binding specificity. Arginines preferentially attract the phosphate linkage via charge-charge interaction, contributing to binding affinity. Evaluation of the RNA/peptide complex's structure revealed that adding conformation changes to the search algorithm yields peptides with better binding affinity and specificity to tRNA(Lys3) than a previous mutation-only algorithm.

Specific disulfide cross-linking to constrict the mobile carrier domain of nonribosomal peptide synthetases

Nonribosomal peptide synthetases are large, multi-domain enzymes that produce peptide molecules with important biological activity such as antibiotic, antiviral, anti-tumor, siderophore and immunosuppressant action. The adenylation (A) domain catalyzes two reactions in the biosynthetic pathway. In the first reaction, it activates the substrate amino acid by adenylation and in the second reaction it transfers the amino acid onto the phosphopantetheine arm of the adjacent peptide carrier protein (PCP) domain. The conformation of the A domain differs significantly depending on which of these two reactions it is catalyzing. Recently, several structures of A-PCP di-domains have been solved using mechanism-based inhibitors to trap the PCP domain in the A domain active site. Here, we present an alternative strategy to stall the A-PCP di-domain, by engineering a disulfide bond between the native amino acid substrate and the A domain. Size exclusion studies showed a significant shift in apparent size when the mutant A-PCP was provided with cross-linking reagents, and this shift was reversible in the presence of high concentrations of reducing agent. The cross-linked protein crystallized readily in several of the conditions screened and the best crystals diffracted to ≈8 Å.

Structure-based predictions broadly link transcription factor mutations to gene expression changes in cancers

Thousands of unique mutations in transcription factors (TFs) arise in cancers, and the functional and biological roles of relatively few of these have been characterized. Here, we used structure-based methods developed specifically for DNA-binding proteins to systematically predict the consequences of mutations in several TFs that are frequently mutated in cancers. The explicit consideration of protein-DNA interactions was crucial to explain the roles and prevalence of mutations in TP53 and RUNX1 in cancers, and resulted in a higher specificity of detection for known p53-regulated genes among genetic associations between TP53 genotypes and genome-wide expression in The Cancer Genome Atlas, compared to existing methods of mutation assessment. Biophysical predictions also indicated that the relative prevalence of TP53 missense mutations in cancer is proportional to their thermodynamic impacts on protein stability and DNA binding, which is consistent with the selection for the loss of p53 transcriptional function in cancers. Structure and thermodynamics-based predictions of the impacts of missense mutations that focus on specific molecular functions may be increasingly useful for the precise and large-scale inference of aberrant molecular phenotypes in cancer and other complex diseases.

Quantitative analysis of the interaction between l-methionine derivative and oligonucleotides

This study explores the use of l-methionine derivative as a potential affinity ligand for nucleic acids purification. The l-methionine derivative is synthesized by activation of the carboxylic acid group with 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-hydroxysuccinimide follow by immobilization on amine sensor surface, previously activated and treated with ethylenediamine. Their affinity towards oligonucleotides has been determined by surface plasmon resonance biosensor. The highest affinity is found for cytosine and thymine, followed by adenine, whereas the lowest affinity is found for guanine. For hetero-oligonucleotides the affinity order is CCCTTT > CCCAAA ≈ AAATTT > GGGTTT, showing that nucleotides with cytosine have the highest affinity, and the presence of guanine reduces the affinity, corroborating with the results obtained with homo-oligonucleotides.

Synthetic fusion protein design and applications

Synthetic fusion proteins can be designed to achieve improved properties or new functionality by synergistically incorporating multiple proteins into one complex. The fusion of two or more protein domains enhances bioactivities or generates novel functional combinations with a wide range of biotechnological and (bio)pharmaceutical applications. In this review, initially, we summarize the commonly used approaches for constructing fusion proteins. For each approach, the design strategy and desired properties are elaborated with examples of recent studies in the areas of biocatalysts, protein switches and bio-therapeutics. Subsequently, the progress in structural prediction of fusion proteins is presented, which can potentially facilitate the structure-based systematic design of fusion proteins toward identifying the best combinations of fusion partners. Finally, the current challenges and future directions in this field are discussed.

Inference of expanded Lrp-like feast/famine transcription factor targets in a non-model organism using protein structure-based prediction

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

Mutations in NOTCH1 cause Adams-Oliver syndrome

Notch signaling determines and reinforces cell fate in bilaterally symmetric multicellular eukaryotes. Despite the involvement of Notch in many key developmental systems, human mutations in Notch signaling components have mainly been described in disorders with vascular and bone effects. Here, we report five heterozygous NOTCH1 variants in unrelated individuals with Adams-Oliver syndrome (AOS), a rare disease with major features of aplasia cutis of the scalp and terminal transverse limb defects. Using whole-genome sequencing in a cohort of 11 families lacking mutations in the four genes with known roles in AOS pathology (ARHGAP31, RBPJ, DOCK6, and EOGT), we found a heterozygous de novo 85 kb deletion spanning the NOTCH1 5' region and three coding variants (c.1285T>C [p.Cys429Arg], c.4487G>A [p.Cys1496Tyr], and c.5965G>A [p.Asp1989Asn]), two of which are de novo, in four unrelated probands. In a fifth family, we identified a heterozygous canonical splice-site variant (c.743-1 G>T) in an affected father and daughter. These variants were not present in 5,077 in-house control genomes or in public databases. In keeping with the prominent developmental role described for Notch1 in mouse vasculature, we observed cardiac and multiple vascular defects in four of the five families. We propose that the limb and scalp defects might also be due to a vasculopathy in NOTCH1-related AOS. Our results suggest that mutations in NOTCH1 are the most common cause of AOS and add to a growing list of human diseases that have a vascular and/or bony component and are caused by alterations in the Notch signaling pathway.

Redesigning the specificity of protein-DNA interactions with Rosetta

Building protein tools that can selectively bind or cleave specific DNA sequences requires efficient technologies for modifying protein-DNA interactions. Computational design is one method for accomplishing this goal. In this chapter, we present the current state of protein-DNA interface design with the Rosetta macromolecular modeling program. The LAGLIDADG endonuclease family of DNA-cleaving enzymes, under study as potential gene therapy reagents, has been the main testing ground for these in silico protocols. At this time, the computational methods are most useful for designing endonuclease variants that can accommodate small numbers of target site substitutions. Attempts to engineer for more extensive interface changes will likely benefit from an approach that uses the computational design results in conjunction with a high-throughput directed evolution or screening procedure. The family of enzymes presents an engineering challenge because their interfaces are highly integrated and there is significant coordination between the binding and catalysis events. Future developments in the computational algorithms depend on experimental feedback to improve understanding and modeling of these complex enzymatic features. This chapter presents both the basic method of design that has been successfully used to modulate specificity and more advanced procedures that incorporate DNA flexibility and other properties that are likely necessary for reliable modeling of more extensive target site changes.

Reprogramming homing endonuclease specificity through computational design and directed evolution

Homing endonucleases (HEs) can be used to induce targeted genome modification to reduce the fitness of pathogen vectors such as the malaria-transmitting Anopheles gambiae and to correct deleterious mutations in genetic diseases. We describe the creation of an extensive set of HE variants with novel DNA cleavage specificities using an integrated experimental and computational approach. Using computational modeling and an improved selection strategy, which optimizes specificity in addition to activity, we engineered an endonuclease to cleave in a gene associated with Anopheles sterility and another to cleave near a mutation that causes pyruvate kinase deficiency. In the course of this work we observed unanticipated context-dependence between bases which will need to be mechanistically understood for reprogramming of specificity to succeed more generally.

Strategy for naturelike designer transcription factors with reduced toxicity

For clinical applications, the biological functions of DNA-binding proteins require that they interact with their target binding site with high affinity and specificity. Advances in randomized production and target-oriented selection of engineered artificial DNA-binding domains incited a rapidly expanding field of designer transcription factors (TFs). Engineered transcription factors are used in zinc-finger nuclease (ZFN) technology that allows targeted genome editing. Zinc-finger-binding domains fabricated by modular assembly display an unexpectedly high failure rate having either a lack of activity as ZFNs in human cells or activity at "off-target” binding sites on the human genome causing cell death. To address these shortcomings, we created new binding domains using a targeted modification strategy. We produced two SP1 mutants by exchanging amino acid residues in the alpha-helical region of the transcription factor SP1. We identified their best target binding sites and searched the NCBI HuRef genome for matches of the nine-base-pair consensus binding site of SP1 and the best binding sites of its mutants. Our research concludes that we can alter the binding preference of existing zinc-finger domains without altering its biological functionalities.

PiDNA: Predicting protein-DNA interactions with structural models

Predicting binding sites of a transcription factor in the genome is an important, but challenging, issue in studying gene regulation. In the past decade, a large number of protein–DNA co-crystallized structures available in the Protein Data Bank have facilitated the understanding of interacting mechanisms between transcription factors and their binding sites. Recent studies have shown that both physics-based and knowledge-based potential functions can be applied to protein–DNA complex structures to deliver position weight matrices (PWMs) that are consistent with the experimental data. To further use the available structural models, the proposed Web server, PiDNA, aims at first constructing reliable PWMs by applying an atomic-level knowledge-based scoring function on numerous in silico mutated complex structures, and then using the PWM constructed by the structure models with small energy changes to predict the interaction between proteins and DNA sequences. With PiDNA, the users can easily predict the relative preference of all the DNA sequences with limited mutations from the native sequence co-crystallized in the model in a single run. More predictions on sequences with unlimited mutations can be realized by additional requests or file uploading. Three types of information can be downloaded after prediction: (i) the ranked list of mutated sequences, (ii) the PWM constructed by the favourable mutated structures, and (iii) any mutated protein–DNA complex structure models specified by the user. This study first shows that the constructed PWMs are similar to the annotated PWMs collected from databases or literature. Second, the prediction accuracy of PiDNA in detecting relatively high-specificity sites is evaluated by comparing the ranked lists against in vitro experiments from protein-binding microarrays. Finally, PiDNA is shown to be able to select the experimentally validated binding sites from 10 000 random sites with high accuracy. With PiDNA, the users can design biological experiments based on the predicted sequence specificity and/or request mutated structure models for further protein design. As well, it is expected that PiDNA can be incorporated with chromatin immunoprecipitation data to refine large-scale inference of in vivo protein–DNA interactions. PiDNA is available at: http://dna.bime.ntu.edu.tw/pidna.

SP transcription factor paralogs and DNA-binding sites coevolve and adaptively converge in mammals and birds

Functional modification of regulatory proteins can affect hundreds of genes throughout the genome, and is therefore thought to be almost universally deleterious. This belief, however, has recently been challenged. A potential example comes from transcription factor SP1, for which statistical evidence indicates that motif preferences were altered in eutherian mammals. Here, we set out to discover possible structural and theoretical explanations, evaluate the role of selection in SP1 evolution, and discover effects on coregulatory proteins. We show that SP1 motif preferences were convergently altered in birds as well as mammals, inducing coevolutionary changes in over 800 regulatory regions. Structural and phylogenic evidence implicates a single causative amino acid replacement at the same SP1 position along both lineages. Furthermore, paralogs SP3 and SP4, which coregulate SP1 target genes through competitive binding to the same sites, have accumulated convergent replacements at the homologous position multiple times during eutherian and bird evolution, presumably to preserve competitive binding. To determine plausibility, we developed and implemented a simple model of transcription factor and binding site coevolution. This model predicts that, in contrast to prevailing beliefs, even small selective benefits per locus can drive concurrent fixation of transcription factor and binding site mutants under a broad range of conditions. Novel binding sites tend to arise de novo, rather than by mutation from ancestral sites, a prediction substantiated by SP1-binding site alignments. Thus, multiple lines of evidence indicate that selection has driven convergent evolution of transcription factors along with their binding sites and coregulatory proteins.

TFinDit: transcription factor-DNA interaction data depository

Background

One of the crucial steps in regulation of gene expression is the binding of transcription factor(s) to specific DNA sequences. Knowledge of the binding affinity and specificity at a structural level between transcription factors and their target sites has important implications in our understanding of the mechanism of gene regulation. Due to their unique functions and binding specificity, there is a need for a transcription factor-specific, structure-based database and corresponding web service to facilitate structural bioinformatics studies of transcription factor-DNA interactions, such as development of knowledge-based interaction potential, transcription factor-DNA docking, binding induced conformational changes, and the thermodynamics of protein-DNA interactions.

Description

TFinDit is a relational database and a web search tool for studying transcription factor-DNA interactions. The database contains annotated transcription factor-DNA complex structures and related data, such as unbound protein structures, thermodynamic data, and binding sequences for the corresponding transcription factors in the complex structures. TFinDit also provides a user-friendly interface and allows users to either query individual entries or generate datasets through culling the database based on one or more search criteria.

Conclusions

TFinDit is a specialized structural database with annotated transcription factor-DNA complex structures and other preprocessed data. We believe that this database/web service can facilitate the development and testing of TF-DNA interaction potentials and TF-DNA docking algorithms, and the study of protein-DNA recognition mechanisms.

3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations

We present the webserver 3D transcription factor (3DTF) to compute position-specific weight matrices (PWMs) of transcription factors using a knowledge-based statistical potential derived from crystallographic data on protein–DNA complexes. Analysis of available structures that can be used to construct PWMs shows that there are hundreds of 3D structures from which PWMs could be derived, as well as thousands of proteins homologous to these. Therefore, we created 3DTF, which delivers binding matrices given the experimental or modeled protein–DNA complex. The webserver can be used by biologists to derive novel PWMs for transcription factors lacking known binding sites and is freely accessible at http://www.gene-regulation.com/pub/programs/3dtf/.

Improved modeling of side-chain--base interactions and plasticity in protein--DNA interface design

Combinatorial sequence optimization for protein design requires libraries of discrete side-chain conformations. The discreteness of these libraries is problematic, particularly for long, polar side chains, since favorable interactions can be missed. Previously, an approach to loop remodeling where protein backbone movement is directed by side-chain rotamers predicted to form interactions previously observed in native complexes (termed "motifs") was described. Here, we show how such motif libraries can be incorporated into combinatorial sequence optimization protocols and improve native complex recapitulation. Guided by the motif rotamer searches, we made improvements to the underlying energy function, increasing recapitulation of native interactions. To further test the methods, we carried out a comprehensive experimental scan of amino acid preferences in the I-AniI protein-DNA interface and found that many positions tolerated multiple amino acids. This sequence plasticity is not observed in the computational results because of the fixed-backbone approximation of the model. We improved modeling of this diversity by introducing DNA flexibility and reducing the convergence of the simulated annealing algorithm that drives the design process. In addition to serving as a benchmark, this extensive experimental data set provides insight into the types of interactions essential to maintain the function of this potential gene therapy reagent.

Benchmarks for flexible and rigid transcription factor-DNA docking

BACKGROUND

Structural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms.

RESULTS

We constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered.

CONCLUSIONS

We believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.

Comprehensive computational design of mCreI homing endonuclease cleavage specificity for genome engineering

Homing endonucleases (HEs) cleave long (∼ 20 bp) DNA target sites with high site specificity to catalyze the lateral transfer of parasitic DNA elements. In order to determine whether comprehensive computational design could be used as a general strategy to engineer new HE target site specificities, we used RosettaDesign (RD) to generate 3200 different variants of the mCreI LAGLIDADG HE towards 16 different base pair positions in the 22 bp mCreI target site. Experimental verification of a range of these designs demonstrated that over 2/3 (24 of 35 designs, 69%) had the intended new site specificity, and that 14 of the 15 attempted specificity shifts (93%) were achieved. These results demonstrate the feasibility of using structure-based computational design to engineer HE variants with novel target site specificities to facilitate genome engineering.

RosettaBackrub--a web server for flexible backbone protein structure modeling and design

The RosettaBackrub server (http://kortemmelab.ucsf.edu/backrub) implements the Backrub method, derived from observations of alternative conformations in high-resolution protein crystal structures, for flexible backbone protein modeling. Backrub modeling is applied to three related applications using the Rosetta program for structure prediction and design: (I) modeling of structures of point mutations, (II) generating protein conformational ensembles and designing sequences consistent with these conformations and (III) predicting tolerated sequences at protein–protein interfaces. The three protocols have been validated on experimental data. Starting from a user-provided single input protein structure in PDB format, the server generates near-native conformational ensembles. The predicted conformations and sequences can be used for different applications, such as to guide mutagenesis experiments, for ensemble-docking approaches or to generate sequence libraries for protein design.

Computational reprogramming of homing endonuclease specificity at multiple adjacent base pairs

Site-specific homing endonucleases are capable of inducing gene conversion via homologous recombination. Reprogramming their cleavage specificities allows the targeting of specific biological sites for gene correction or conversion. We used computational protein design to alter the cleavage specificity of I-MsoI for three contiguous base pair substitutions, resulting in an endonuclease whose activity and specificity for its new site rival that of wild-type I-MsoI for the original site. Concerted design for all simultaneous substitutions was more successful than a modular approach against individual substitutions, highlighting the importance of context-dependent redesign and optimization of protein–DNA interactions. We then used computational design based on the crystal structure of the designed complex, which revealed significant unanticipated shifts in DNA conformation, to create an endonuclease that specifically cleaves a site with four contiguous base pair substitutions. Our results demonstrate that specificity switches for multiple concerted base pair substitutions can be computationally designed, and that iteration between design and structure determination provides a route to large scale reprogramming of specificity.

Exploitation of binding energy for catalysis and design

Enzymes utilize substrate binding energy both to promote ground state association and to selectively lower the energy of the reaction transition state.i The monomeric homing endonuclease I-AniI cleaves with high sequence specificity in the center of a 20 base-pair DNA target site, with the N-terminal domain of the enzyme making extensive binding interactions with the left (−) side of the target site and the similarly structured C-terminal domain interacting with the right (+) side.ii Despite the approximate two-fold symmetry of the enzyme-DNA complex, we find that there is almost complete segregation of interactions responsible for substrate binding to the (−) side of the interface and interactions responsible for transition state stabilization to the (+) side. While single base-pair substitutions throughout the entire DNA target site reduce catalytic efficiency, mutations in the (−) DNA half-site almost exclusively increase K_D and K_M*, and those in the (+) half-site primarily decrease k_cat*. The reduction of activity produced by mutations on the (−) side, but not mutations on the (+) side, can be suppressed by tethering the substrate to the endonuclease displayed on the surface of yeast. This dramatic asymmetry in the utilization of enzyme-substrate binding energy for catalysis has direct relevance to the redesign of endonucleases to cleave genomic target sites for gene therapy and other applications. Computationally redesigned enzymes that achieve new specificities on the (−) side do so by modulating K_M*, while redesigns with altered specificities on the (+) side modulate k_cat*. Our results illustrate how classical enzymology and modern protein design can each inform the other.