Sequence-activity Relationships Research Articles

Design of Cytotoxic T Cell Epitopes by Machine Learning of Human Degrons.

Antigen processing is critical for therapeutic vaccines to generate epitopes for priming cytotoxic T cell responses against cancer and pathogens, but insufficient processing often limits the quantity of epitopes released. We address this challenge using machine learning to ascribe a proteasomal degradation score to epitope sequences. Epitopes with varying scores were translocated into cells using nontoxic anthrax proteins. Epitopes with a low score show pronounced immunogenicity due to antigen processing, but epitopes with a high score show limited immunogenicity. This work sheds light on the sequence-activity relationships between proteasomal degradation and epitope immunogenicity. We anticipate that future efforts to incorporate proteasomal degradation signals into vaccine designs will lead to enhanced cytotoxic T cell priming by these vaccines in clinical settings.

Base editor scanning charts the DNMT3A activity landscape.

DNA methylation is critical for regulating gene expression, necessitating its accurate placement by enzymes such as the DNA methyltransferase DNMT3A. Dysregulation of this process is known to cause aberrant development and oncogenesis, yet how DNMT3A is regulated holistically by its three domains remains challenging to study. Here, we integrate base editing with a DNA methylation reporter to perform in situ mutational scanning of DNMT3A in cells. We identify mutations throughout the protein that perturb function, including ones at an interdomain interface that block allosteric activation. Unexpectedly, we also find mutations in the PWWP domain, a histone reader, that modulate enzyme activity despite preserving histone recognition and protein stability. These effects arise from altered PWWP domain DNA affinity, which we show is a noncanonical function required for full activity in cells. Our findings highlight mechanisms of interdomain crosstalk and demonstrate a generalizable strategy to probe sequence-activity relationships of nonessential chromatin regulators.

Computational Insights into the Sequence-Activity Relationships of the NGF(1-14) Peptide by Molecular Dynamics Simulations.

The Nerve Growth Factor (NGF) belongs to the neurothrophins protein family involved in the survival of neurons in the nervous system. The interaction of NGF with its high-affinity receptor TrkA mediates different cellular pathways related to Alzheimer’s disease, pain, ocular dysfunction, and cancer. Therefore, targeting NGF-TrkA interaction represents a valuable strategy for the development of new therapeutic agents. In recent years, experimental studies have revealed that peptides belonging to the N-terminal domain of NGF are able to partly mimic the biological activity of the whole protein paving the way towards the development of small peptides that can selectively target specific signaling pathways. Hence, understanding the molecular basis of the interaction between the N-terminal segment of NGF and TrkA is fundamental for the rational design of new peptides mimicking the NGF N-terminal domain. In this study, molecular dynamics simulation, binding free energy calculations and per-residue energy decomposition analysis were combined in order to explore the molecular recognition pattern between the experimentally active NGF(1–14) peptide and TrkA. The results highlighted the importance of His4, Arg9 and Glu11 as crucial residues for the stabilization of NGF(1–14)-TrkA interaction, thus suggesting useful insights for the structure-based design of new therapeutic peptides able to modulate NGF-TrkA interaction.

Machine learning based predictive model for the analysis of sequence activity relationships using protein spectra and protein descriptors.

Accurately establishing the connection between a protein sequence and its function remains a focal point within the field of protein engineering, especially in the context of predicting the effects of mutations. From this, there has been a continued drive to build accurate and reliable predictive models via machine learning that allow for the virtual screening of many protein mutant sequences, measuring the relationship between sequence and 'fitness' or 'activity', commonly known as a Sequence-Activity-Relationship (SAR). An important preliminary stage in the building of these predictive models is the encoding of the chosen sequences. Evaluated in this work is a plethora of encoding strategies using the Amino Acid Index database, where the indices are transformed into their spectral form via Digital Signal Processing (DSP) techniques, as well as numerous protein structural and physiochemical descriptors. The encoding strategies are explored on a dataset curated to measure the thermostability of various mutants from a recombination library, designed from parental cytochrome P450s. In this work it was concluded that the implementation of protein spectra in concatenation with protein descriptors, together with the Partial Least Squares Regression (PLS) algorithm, gave the most noteworthy increase in the quality of the predictive models (as described in Encoding Strategy C), highlighting their utility in identifying an SAR. The accompanying software produced for this paper is termed pySAR (Python Sequence-Activity-Relationship), which allows for a user to find the optimal arrangement of structural and or physiochemical properties to encode their specific mutant library dataset; the source code is available at: https://github.com/amckenna41/pySAR.

Deep Learning Enables Discovery of a Short Nuclear Targeting Peptide for Efficient Delivery of Antisense Oligomers.

Therapeutic macromolecules such as proteins and oligonucleotides can be highly efficacious but are often limited to extracellular targets due to the cell’s impermeable membrane. Cell-penetrating peptides (CPPs) are able to deliver such macromolecules into cells, but limited structure–activity relationships and inconsistent literature reports make it difficult to design effective CPPs for a given cargo. For example, polyarginine motifs are common in CPPs, promoting cell uptake at the expense of systemic toxicity. Machine learning may be able to address this challenge by bridging gaps between experimental data in order to discern sequence–activity relationships that evade our intuition. Our earlier data set and deep learning model led to the design of miniproteins (>40 amino acids) for antisense delivery. Here, we leveraged and expanded our model with data augmentation in the short CPP sequence space of the data set to extrapolate and discover short, low-arginine-content CPPs that would be easier to synthesize and amenable to rapid conjugation to desired cargo, and with minimal in vivo toxicity. The lead predicted peptide, termed P6, is as active as a polyarginine CPP for the delivery of an antisense oligomer, while having only one arginine side chain and 18 total residues. We determined the pentalysine motif and the C-terminal cysteine of P6 to be the main drivers of activity. The antisense conjugate was able to enhance corrective splicing in an animal model to produce functional eGFP in heart tissue in vivo while remaining nontoxic up to a dose of 60 mg/kg. In addition, P6 was able to deliver an enzyme to the cytosol of cells. Our findings suggest that, given a data set of long CPPs, we can discover by extrapolation short, active sequences that deliver antisense oligomers.

Engineering of the thermophilic nitrile hydratase from Pseudonocardia thermophila JCM3095 for large-scale nicotinamide production based on sequence-activity relationships

The green biocatalyst nitrile hydratase (NHase) is able to bio-transform 3-cyanopyridine into nicotinamide. As the NHase reaction is exothermic, an enzyme with high activity and stability is needed for nicotinamide production. In this study, we used sequence analysis and site-directed mutagenesis to generate a mutant of thermophilic NHase from Pseudonocardia thermophila JCM3095 with substantially enhanced activity and developed a powerful process for nicotinamide bio-production. The specific activity of αF126Y/αF168Y mutant was successfully increased by 3.98-fold over that of the wild-type enzyme. The half-life of such mutant was longer than 2 h, which was comparable to its parent enzyme. The relative activity of the αF126Y/αF168Y mutant after treatment with 1 M 3-cyanopyridine and 2 M nicotinamide was 73.2% and 63.7%, respectively, showing minor loss of its original stability. Structural analysis demonstrated that hydrogen bonds at the active site and α-β subunit interface of the NHase contribute to the improved activity and the maintenance of stability. Escherichia coli transformant harboring the mutant NHase was used for nicotinamide bio-production, yielding a nicotinamide productivity of 251.1 g/(L·h), which is higher than the productivity obtained using other NHase-containing strains and transformants. The newly established variant is therefore a promising alternative for the industrial production of nicotinamides.

Sequence-Activity Relationships for the Snf7 Insecticidal dsRNA in Chrysomelidae.

The responsiveness of insects to oral delivery of insecticidal dsRNA has been shown to be dependent on dsRNA length and sequence match. Previous work with the western corn rootworm (WCR, Diabrotica virgifera virgifera; Coleoptera: Chrysomelidae) demonstrated that at least one ≥21 nt match must be present in the DvSnf7 dsRNA of approximately ≥60 base-pairs (bp) for activity. Further data is needed on the activity of <21 nt matches along with characterization of relationship between activity and the number of ≥21 nt matches. To characterize the sequence–activity relationship for insecticidal dsRNA further, the activity of orthologous Snf7 dsRNAs with 19, 20, and 21 nt contiguous matches against WCR was compared. Neither 19 nor 20 nt sequence matches were active, supporting that a ≥21 nt sequence match is required for activity. The relationship between the number of 21 nt matches with activity of Snf7 dsRNA orthologs from several Chrysomelid species was characterized using WCR and Colorado potato beetle (CPB, Leptinotarsa decemlineata; Coleoptera Chrysomelidae). For WCR, there was a strong relationship between an increasing number of 21 nt matches and increased activity (i.e., lower LC50 values). A similar relationship was observed for CPB with an exception for a single ortholog, which may be related to the exceptionally high rate of polymorphisms in CPB. Overall, these results demonstrate a general relationship between the number of 21 nt matches and activity, and this relationship could be used to inform a testing and assessment plan for an ecological risk assessment for an insecticidal dsRNA.

Determinants of Base Editing Outcomes from Target Library Analysis and Machine Learning

Although base editors are widely used to install targeted point mutations, the factors that determine base editing outcomes are not well understood. We characterized sequence-activity relationships of 11 cytosine and adenine base editors (CBEs and ABEs) on 38,538 genomically integrated targets in mammalian cells and used the resulting outcomes to train BE-Hive, a machine learning model that accurately predicts base editing genotypic outcomes (R ≈ 0.9) and efficiency (R ≈ 0.7). We corrected 3,388 disease-associated SNVs with ≥90% precision, including 675 alleles with bystander nucleotides that BE-Hive correctly predicted would not be edited. We discovered determinants of previously unpredictable C-to-G, or C-to-A editing and used these discoveries to correct coding sequences of 174 pathogenic transversion SNVs with ≥90% precision. Finally, we used insights from BE-Hive to engineer novel CBE variants that modulate editing outcomes. These discoveries illuminate base editing, enable editing at previously intractable targets, and provide new base editors with improved editing capabilities.

Characterization of imine reductases in reductive amination for the exploration of structure-activity relationships.

Imine reductases (IREDs) have shown great potential as catalysts for the asymmetric synthesis of industrially relevant chiral amines, but a limited understanding of sequence activity relationships makes rational engineering challenging. Here, we describe the characterization of 80 putative and 15 previously described IREDs across 10 different transformations and confirm that reductive amination catalysis is not limited to any particular subgroup or sequence motif. Furthermore, we have identified another dehydrogenase subgroup with chemoselectivity for imine reduction. Enantioselectivities were determined for the reduction of the model substrate 2-phenylpiperideine, and the effect of changing the reaction conditions was also studied for the reductive aminations of 1-indanone, acetophenone, and 4-methoxyphenylacetone. We have performed sequence-structure analysis to help explain clusters in activity across a phylogenetic tree and to inform rational engineering, which, in one case, has conferred a change in chemoselectivity that had not been previously observed.

Engineering the 5' UTR-Mediated Regulation of Protein Abundance in Yeast Using Nucleotide Sequence Activity Relationships.

The 5' untranslated region (5'UTR) plays a key role in post-transcriptional regulation, but interaction between nucleotides and directed evolution of 5'UTRs as synthetic regulatory elements remain unclear. By constructing a library of synthesized random 5'UTRs of 24 nucleotides in Saccharomyces cerevisiae, we observed strong epistatic interactions among bases from different positions in the 5'UTR. Taking into account these base interactions, we constructed a mathematical model to predict protein abundance with a precision of R2 = 0.60. On the basis of this model, we developed an approach to engineer 5'UTRs according to nucleotide sequence activity relationships (NuSAR), in which 5'UTRs were engineered stepwise through repeated cycles of backbone design, directed screening, and model reconstruction. After three rounds of NuSAR, the predictive accuracy of our model was improved to R2 = 0.71, and a strong 5'UTR was obtained with 5-fold higher protein abundance than the starting 5'UTR. Our findings provide new insights into the mechanism of 5'UTR regulation and contribute to a new translational elements engineering approach in synthetic biology.

Abstract 5620: Multispecific antibodies targeting CD38 and PD-L1 show potent tumor cytotoxicity

Abstract Multivalent antibodies targeting either CD38 alone or CD38 in conjunction with PD-L1 may yield therapeutics with superior biologic activities and provide benefit for treating malignancies expressing low levels of CD38 (DLCBL, daratumumab refractory MM, and NSCLC). Multivalent, multispecific antibodies kill CD38low cells through a variety of mechanisms including stronger and more specific engagement of CD38. Potent and directed immune checkpoint inhibition is realized by adding an anti-PD-L1 binding domain. Teneobio's discovery platform utilizes VH domains (UniDabs) of fully human heavy chain antibodies (UniAbs) to develop bi-, tri-, and tetravalent antibodies. Individual UniDabs targeting CD38 and PDL1 were identified using our unique sequence-based discovery platform and high-throughput lead evaluation pipeline (TeneoSeek). This robust screening workflow enables evaluation of a large diversity of natural fully human antibodies, targeting multiple epitopes on a single antigen and uncovering important sequence activity relationships. We have identified UniDabs that bind five different functional epitopes on human, cynomolgus and mouse CD38 including potent inhibitors of hydrolase and cyclase enzymatic functions. In addition, we generated a large panel of PD-L1 inhibitors that bind with high affinities human and cynomolgus PD-L1. Using different combinations and arrangements of UniDabs, a variety of multivalent antibodies were constructed and evaluated in in vitro models. Data from a range of assay types show that multivalent UniAbs targeting CD38 can be engineered to display superior tumor cell cytotoxicity through multiple mechanisms of action. Summary: Teneobio's discovery platform utilizes VH domains (UniDabs) of fully human heavy chain antibodies (UniAbs) to develop bi-, tri-, and tetravalent antibodies. Multivalent UniAbs targeting CD38 and PD-L1 can be engineered to display superior tumor cell cytotoxicity through multiple mechanisms of action. Citation Format: Wim van Schooten. Multispecific antibodies targeting CD38 and PD-L1 show potent tumor cytotoxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5620.

Multispecific antibodies targeting CD38 show potent tumor-specific cytotoxicity.

57 Background: Multivalent antibodies targeting either CD38 alone or CD38 in conjunction with PD-L1 may yield therapeutics with superior biological activities and provide benefit for treating malignancies expressing low levels of CD38 (MCL, NHL, T cell lymphomas and Daratumumab refractory MM). Multivalent, multispecific antibodies kill CD38low cells through a variety of mechanisms including stronger and more specific engagement of CD38. Potent and directed immune checkpoint inhibition is realized by adding an anti-PD-L1 binding domain. Teneobio’s discovery platform utilizes VH domains (UniDabs) of fully human heavy chain antibodies (UniAbs) to develop bi-, tri-, and tetravalent antibodies. Methods: Individual UniDabs targeting CD38 and PDL1 were identified using our unique sequence-based discovery platform and high-throughput lead evaluation pipeline (TeneoSeek). This robust screening workflow enables evaluation of a large diversity of natural fully human antibodies, targeting multiple epitopes on a single antigen and uncovering important sequence activity relationships. UniDabs from transgenic rats are ideal building blocks for the generation of potent and highly manufacturable multivalent antibody therapeutics. Results: We have identified UniDabs that efficiently block PD-1/PD-L1 interaction as well as additional UniDabs that bind to five different functional epitopes on human CD38. Using different combinations and arrangements of UniDabs, a variety of multivalent antibodies were constructed and evaluated in in vitro models. Specific combinations of UniDabs show more potent cytotoxic effects than Daratumumab for multiple mechanisms including CDC and direct apoptosis. Conclusions: Data from a range of assay types show that multivalent UniAbs targeting CD38 can be engineered to display superior tumor cell cytotoxicity through multiple mechanisms of action.

Exploring sequence-function space of a poplar glutathione transferase using designed information-rich gene variants.

Exploring the vicinity around a locus of a protein in sequence space may identify homologs with enhanced properties, which could become valuable in biotechnical and other applications. A rational approach to this pursuit is the use of ‘infologs’, i.e. synthetic sequences with specific substitutions capturing maximal sequence information derived from the evolutionary history of the protein family. Ninety-five such infolog genes of poplar glutathione transferase were synthesized and expressed in Escherichia coli, and the catalytic activities of the proteins determined with alternative substrates. Sequence–activity relationships derived from the infologs were used to design a second set of 47 infologs in which 90% of the members exceeded wild-type properties. Two mutants, C2 (V55I/E95D/D108E/A160V) and G5 (F13L/C70A/G122E), were further functionally characterized. The activities of the infologs with the alternative substrates 1-chloro-2,4-dinitrobenzene and phenethyl isothiocyanate, subject to different chemistries, were positively correlated, indicating that the examined mutations were affecting the overall catalytic competence without major shift in substrate discrimination. By contrast, the enhanced protein expressivity observed in many of the mutants were not similarly correlated with the activities. In conclusion, small libraries of well-defined infologs can be used to systematically explore sequence space to optimize proteins in multidimensional functional space.

456. Transgene Bioengineering Through Ancestral Protein Reconstruction

Bioengineering of the transgene often is a critical component of preclinical gene therapy R&D. Transgenes and their products represent the active agent in nucleic acid pharmaceuticals and similar to small molecule pharmaceuticals, they can be modified to possess improved pharmacological properties. However as they are significantly more complex than small molecules, the available strategies for bioengineering, such as in silico rational design, directed evolution and homolog/ortholog-scanning mutagenesis, are less robust. Herein, we propose combined ancestral sequence and protein reconstruction (ASR and APR, respectively) as newly accessible approaches to transgene/transgene product bioengineering. ASR is the prediction of ancient sequences from extant ones and well developed ASR methods and tools now exist. Furthermore, the availability of de novo custom DNA synthesis and recombinant protein expression systems now facilitates APR to complement and extend ASR findings. Previously through the study of extant FVIII orthologs, we discovered that differential molecular, biochemical and immunological properties with exist and could have a positive pharmacological impact upon engineering into human FVIII. For example, porcine FVIII was shown to display 10-100-fold more efficient biosynthesis than human FVIII in vitro and in vivo, while murine FVIII displays 5 - 10-fold greater stability following thrombin activation. Ovine FVIII displays intermediate biosynthesis and stability, but strikingly reduced cross-reactivity to anti-human FVIII inhibitory antibodies. APR provides a high-resolution mapping solution to these ortholog sequence-activity relationships and also takes advantage of the observation that ancient proteins often have unpredicted and/or expanded functionalities that can be efficiently mapped to specific amino acid residues through comparisons of ancestral proteins and genes within an evolutionary lineage. Therefore, we sought to validate APR as a FVIII discovery/bioengineering platform with the expectation that this approach can be successfully applied to essentially all hemostatic, as well as non-hemostatic, gene therapies. Initially, we employed ASR/APR to resurrect 14 ancestral (An) FVIII molecules. Each An-FVIII was shown to be active in standard coagulation assays using human plasma demonstrating evolutionary compatibility. To study biosynthetic efficiency, secreted An-FVIII activity and mRNA transcript levels were analyzed from stably transfected cells demonstrating that, An-53, an ancestral primate sequence with 95% identity to extant human FVIII, displayed the greatest biosynthetic efficiency equivalent to porcine FVIII and our lead bioengineered high expression FVIII, ET3. As a proxy for AAV gene therapy, hemophilia A mice were administered several doses of a liver-directed An-53 AAV plasmid DNA cassette via hydrodynamic injection resulting in peak plasma FVIII activity levels ≥12-fold higher than observed with the ET3 transgene. In addition to superior biosynthetic efficiency, we have identified An-FVIII variants with 2 - 3 fold improved specific activity and stability greater or equal to murine FVIII. Furthermore, we have identified An-FVIII molecules that display reduced immune reactivity and have used these constructs to define functional epitopes to the single amino acid level. Currently, we are refining this approach to identify the key functional residues responsible for each property with the goal of improving the pharmacology of the human FVIII transgenes.

Attractors in Sequence Space: Peptide Morphing by Directed Simulated Evolution.

Certain antimicrobial peptides (AMPs) and mitochondrial targeting peptides (mTPs) share common features such as a positive net charge, helical propensity, and the ability to interact with lipid membranes[1]. While a primary function of AMPs is to disrupt membrane integrity, many mTPs interact with the mitochondrial membranes and the translocator complex, leaving the membranes intact when proteolytically degraded by matrix-located protease(s)[2]. We present a computational approach that may help rationalize the delicate balance of these effects and other sequence-activity relationships. We implemented and applied a directed evolutionary strategy for stepwise peptide morphing of one peptide into another (MoPED, Morphing of Peptides by Evolutionary Design). For the prospective application, we chose cationic peptides as representatives of both peptide classes and converted an AMP (Protonectin, start sequence)[3] into an mTP (target or “attractor” sequence). Novel peptides were generated based on a chemical similarity index (Grantham substitution matrix).[4] The target sequence served as an attractor point for evolutionary exploration of sequence space. We synthesized and tested the individual peptides that were generated during the morphing process. The designed peptides showed systematic loss of membranolytic potential with increasing distance from the start sequence. The results of biophysical and bacterial growth experiments confirmed the applicability of MoPED to designing chemically motivated peptide derivatives. Receiver operating characteristic (ROC) analysis advocates the inducible peptide α-helicity as a semi-quantitative indicator of membranolytic antimicrobial activity.

Comprehensive mutational scanning of a kinase in vivo reveals substrate-dependent fitness landscapes.

Deep mutational scanning has emerged as a promising tool for mapping sequence–activity relationships in proteins, ribonucleic acid and deoxyribonucleic acid. In this approach, diverse variants of a sequence of interest are first ranked according to their activities in a relevant assay, and this ranking is then used to infer the shape of the fitness landscape around the wild-type sequence. Little is currently known, however, about the degree to which such fitness landscapes are dependent on the specific assay conditions from which they are inferred. To explore this issue, we performed comprehensive single-substitution mutational scanning of APH(3′)II, a Tn5 transposon-derived kinase that confers resistance to aminoglycoside antibiotics, in Escherichia coli under selection with each of six structurally diverse antibiotics at a range of inhibitory concentrations. We found that the resulting local fitness landscapes showed significant dependence on both antibiotic structure and concentration, and that this dependence can be exploited to guide protein engineering. Specifically, we found that differential analysis of fitness landscapes allowed us to generate synthetic APH(3′)II variants with orthogonal substrate specificities.

The structure and function of the glucagon‐like peptide‐1 receptor and its ligands

Glucagon-like peptide-1(7-36)amide (GLP-1) is a 30-residue peptide hormone released from intestinal L cells following nutrient consumption. It potentiates the glucose-induced secretion of insulin from pancreatic beta cells, increases insulin expression, inhibits beta-cell apoptosis, promotes beta-cell neogenesis, reduces glucagon secretion, delays gastric emptying, promotes satiety and increases peripheral glucose disposal. These multiple effects have generated a great deal of interest in the discovery of long-lasting agonists of the GLP-1 receptor (GLP-1R) in order to treat type 2 diabetes. This review article summarizes the literature regarding the discovery of GLP-1 and its physiological functions. The structure, function and sequence-activity relationships of the hormone and its natural analogue exendin-4 (Ex4) are reviewed in detail. The current knowledge of the structure of GLP-1R, a Family B GPCR, is summarized and discussed, before its known interactions with the principle peptide ligands are described and summarized. Finally, progress in discovering non-peptide ligands of GLP-1R is reviewed. GLP-1 is clearly an important hormone linking nutrient consumption with blood sugar control, and therefore knowledge of its structure, function and mechanism of action is of great importance.

Spatially addressed combinatorial protein libraries for recombinant antibody discovery and optimization

Antibody discovery typically uses hybridoma- or display-based selection approaches, which lack the advantages of directly screening spatially addressed compound libraries as in small-molecule discovery. Here we apply the latter strategy to antibody discovery, using a library of ∼10,000 human germline antibody Fabs created by de novo DNA synthesis and automated protein expression and purification. In multiplexed screening assays, we obtained specific hits against seven of nine antigens. Using sequence-activity relationships and iterative mutagenesis, we optimized the binding affinities of two hits to the low nanomolar range. The matured Fabs showed full and partial antagonism activities in cell-based assays. Thus, protein drug leads can be discovered using surprisingly small libraries of proteins with known sequences, questioning the requirement for billions of members in an antibody discovery library. This methodology also provides sequence, expression and specificity information at the first step of the discovery process, and could enable novel antibody discovery in functional screens.

Classification, Prediction, and Verification of the Regioselectivity of Fungal Polyketide Synthase Product Template Domains

The fungal iterative nonreducing polyketide synthases (NRPKSs) synthesize aromatic polyketides, many of which have important biological activities. The product template domains (PT) embedded in the multidomain NRPKSs mediate the regioselective cyclization of the highly reactive polyketide backbones and dictate the final structures of the products. Understanding the sequence-activity relationships of different PT domains is therefore an important step toward the prediction of polyketide structures from NRPKS sequences and can enable the genome mining of hundreds of cryptic NRPKSs uncovered via genome sequencing. In this work, we first performed phylogenetic analysis of PT domains from NRPKSs of known functions and showed that the PT domains can be classified into five groups, with each group corresponding to a unique product size or cyclization regioselectivity. Group V contains the formerly unverified PT domains that were identified as C6-C11 aldol cyclases. The regioselectivity of PTs from this group were verified by product-based assays using the PT domain excised from the asperthecin AptA NRPKS. When combined with dissociated PKS4 minimal PKS, or replaced the endogenous PKS4 C2-C7 PT domain in a hybrid NRPKS, AptA-PT directed the C6-C11 cyclization of the nonaketide backbone to yield a tetracyclic pyranoanthraquinone 4. Extensive NMR analysis verified that the backbone of 4 was indeed cyclized with the expected regioselectivity. The PT phylogenetic analysis was then expanded to include approximately 100 PT sequences from unverified NRPKSs. Using the assays developed for AptA-PT, the regioselectivities of additional PT domains were investigated and matched to those predicted by the phylogenetic classifications.

Comparable stabilisation, structural changes and activities can be induced in FGF by a variety of HS and non-GAG analogues: implications for sequence-activity relationships

The activities of heparan sulfate (HS) and heparin do not correlate simply with sulfation levels or sequence. The alternative hypothesis, that appropriate charge and conformational characteristics for protein binding and activity can be provided by other sequences in heparan sulfate and, possibly, also in unrelated sulfated polysaccharides, is explored. Differential scanning fluorimetry was used to measure the thermostabilisation bestowed by modified heparin polysaccharides (proxies for heparan sulfate) on fibroblast growth factor-1 (FGF-1) and fibroblast growth factor-2 (FGF-2), prototypical heparan sulfate-binding proteins, revealing varied abilities and primary sequence-activity redundancy. The effect of substitution pattern on the heparin/heparan sulfate backbone was explored using principal component analysis of (13)C NMR chemical shift data for homogeneously modified heparin polysaccharides revealing complex conformational effects. No simple relationship emerged between these polysaccharides, with their distinct charge distributions and geometries, and their ability to signal. Other, structurally unrelated sulfated polysaccharides were also able to support signalling. These influenced FGF stabilisation in a similar manner to the HS analogues and provided analogous cell signalling activity. For FGF-1, but not FGF-2, signaling correlated strongly with protein stabilisation and circular dichroism spectroscopy demonstrated that some non-HS polysaccharides invoked comparable secondary structural changes to those induced by heparin. Active conformations can readily be found in several heparin derivatives, as well as among non-HS polysaccharides, which comprise unrelated primary sequences, confirming the hypothesis and implying that the level of unique information contained in HS sequences may be much lower than previously thought.