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There have recently been rapid advances in deep learning models for protein design. To demonstrate proof-of-concept, these advancements have focused on small proteins with lots of data for training. This means that they are often not suitable for generating proteins with the most potential for high clinical impact –due to the additional challenges of sparse data and large size many therapeutically relevant proteins have. One major application that fits this category is gene therapy delivery. Viral vectors such as Adenoviruses and AAVs are a common delivery vehicle for gene therapy. However, environmental exposure means that most people exhibit potent pre-existing immune responses to many serotypes. This response, primarily driven by neutralizing antibodies, also precludes repeated administration with the same serotype. Rare serotypes, serotypes targeting other species, and capsid engineering, have all been deployed in the service of reducing neutralization by pre-existing antibodies. However, progress has been very limited using conventional methods and a new approach is urgently needed. To address this, we developed a variational autoencoder that can generate synthetic viral vector serotypes without epitopes for pre-existing neutralizing antibodies. A compact generative computational model was constructed, with only 12.4 million parameters that could be efficiently trained on the limited natural sequences (e.g., 711 natural Adenovirus hexon sequences with average length of 938 amino acids). In contrast to the current state-of-the-art, the model was able to generate high-quality Adenovirus hexon sequences that were folded with high confidence by Alphafold2 to produce structures essentially identical to natural hexon structures. Molecular dynamics simulations confirmed that the structures are stable and protein–protein interfaces are intact. Local secondary structure and local mobility is also comparable with natural serotype behavior. Our model could be used to generate a broad range of synthetic adenovirus serotype sequences without epitopes for pre-existing neutralizing antibodies in the human population. It could be used more broadly to generate different types of viral vector, and any large, therapeutically valuable proteins, where available data is sparse.

Development of a repeatable method for delivering transgene payloads to human induced pluripotent stem cells (hiPSCs) without risking unintended off-target effects is not fully realized. Yet, such methods are indispensable to fully unlocking the potential for applying synthetic biological approaches to regenerative medicine, delivering quantum impacts to cell-based therapeutics development. Here we present a toolkit for engineering hiPSCs centred on the development of two core ‘landing-pad’ cell-lines, facilitating rapid high-efficiency delivery of transgenes to theAAVS1safe-harbour locus using the Bxb1 large-serine recombinase. We developed two landing-pad cell lines expressing green and red fluorescent reporters respectively, both retaining stemness whilst fully capable of differentiation into all three germ layers. A fully selected hiPSC population can be isolated within 1-2 weeks after landing-pad recombinase-mediated cassette exchange. We demonstrate the capability for investigator-controlled homozygous or heterozygous transgene configurations in these cells. As such, the toolkit of vectors and protocols associated with this landing-pad hiPSC system has the potential to accelerate engineering workflows for researchers in a variety of disciplines.

Defects in hydroxymethylbilane synthase (HMBS) can cause Acute Intermittent Porphyria (AIP), an acute neurological disease. Although sequencing-based diagnosis can be definitive, ~⅓ of clinical HMBS variants are missense variants, and most clinically-reported HMBS missense variants are designated as “variants of uncertain significance” (VUS). Using saturation mutagenesis,en masseselection, and sequencing, we applied a multiplexed validated assay to both the erythroid-specific and ubiquitous isoforms of HMBS, obtaining confident functional impact scores for >84% of all possible amino-acid substitutions. The resulting variant effect maps generally agreed with biochemical expectation. However, the maps showed variants at the dimerization interface to be unexpectedly well tolerated, and suggested residue roles in active site dynamics that were supported by molecular dynamics simulations. Most importantly, these HMBS variant effect maps can help discriminate pathogenic from benign variants, proactively providing evidence even for yet-to-be-observed clinical missense variants.

Summary Most rare clinical missense variants cannot currently be classified as pathogenic or benign. Deficiency in human 5,10-methylenetetrahydrofolate reductase (MTHFR), the most common inherited disorder of folate metabolism, is caused primarily by rare missense variants. Further complicating variant interpretation, variant impacts often depend on environment. An important example of this phenomenon is the MTHFR variant p.Ala222Val (c.665C>T), which is carried by half of all humans and has a phenotypic impact that depends on dietary folate. Here we describe the results of 98,336 variant functional-impact assays, covering nearly all possible MTHFR amino acid substitutions in four folinate environments, each in the presence and absence of p.Ala222Val. The resulting atlas of MTHFR variant effects reveals many complex dependencies on both folinate and p.Ala222Val. MTHFR atlas scores can distinguish pathogenic from benign variants and, among individuals with severe MTHFR deficiency, correlate with age of disease onset. Providing a powerful tool for understanding structure-function relationships, the atlas suggests a role for a disordered loop in retaining cofactor at the active site and identifies variants that enable escape of inhibition by S-adenosylmethionine. Thus, a model based on eight MTHFR variant effect maps illustrates how shifting landscapes of environment- and genetic-background-dependent missense variation can inform our clinical, structural, and functional understanding of MTHFR deficiency.

Peptide-based therapeutics are an alternative to small molecule drugs as they offer superior specificity, lower toxicity, and easy synthesis. Here we present an approach that leverages the dramatic performance increase afforded by the recent arrival of GPU accelerated thermodynamic integration (TI). GPU TI facilitates very fast, highly accurate binding affinity optimization of peptides against therapeutic targets. We benchmarked TI predictions using published peptide binding optimization studies. Prediction of mutations involving charged side-chains was found to be less accurate than for non-charged, and use of a more complex 3-step TI protocol was found to boost accuracy in these cases. Using the 3-step protocol for non-charged side-chains either had no effect or was detrimental. We use the benchmarked pipeline to optimize a peptide binding to our recently discovered cancer target: EME1. TI calculations predict beneficial mutations using both canonical and non-canonical amino acids. We validate these predictions using fluorescence polarization and confirm that binding affinity is increased. We further demonstrate that this increase translates to a significant reduction in pancreatic cancer cell viability.

Significance Using D-amino acids as the building blocks for bioactive peptides can dramatically increase their potency. However, simply swapping regular levorotary amino acids for dextrorotary (D)-amino acids alters the peptide surface topology and function is lost. Current methods to overcome this are not generally applicable and exclude the majority of therapeutic targets. By creating a mirror image of all 111,867 protein structures in the Protein Data Bank (PDB), we convert this repository into a D-peptide database with 2.8 million D-peptide structures. This D-PDB can be searched to find therapeutically active topologies, demonstrated here by the discovery of D-peptide GLP1R and PTH1R agonists. Evaluation of D-PDB coverage suggests that it holds candidates for most therapeutic targets and, thus, potentially contains hundreds of potent drug leads., Biologics are a rapidly growing class of therapeutics with many advantages over traditional small molecule drugs. A major obstacle to their development is that proteins and peptides are easily destroyed by proteases and, thus, typically have prohibitively short half-lives in human gut, plasma, and cells. One of the most effective ways to prevent degradation is to engineer analogs from dextrorotary (D)-amino acids, with up to 105-fold improvements in potency reported. We here propose a general peptide-engineering platform that overcomes limitations of previous methods. By creating a mirror image of every structure in the Protein Data Bank (PDB), we generate a database of ∼2.8 million D-peptides. To obtain a D-analog of a given peptide, we search the (D)-PDB for similar configurations of its critical—“hotspot”—residues. As a proof of concept, we apply our method to two peptides that are Food and Drug Administration approved as therapeutics for diabetes and osteoporosis, respectively. We obtain D-analogs that activate the GLP1 and PTH1 receptors with the same efficacy as their natural counterparts and show greatly increased half-life.

Protein-protein interactions are fundamental for virtually all functions of the cell. A large fraction of these interactions involve short peptide motifs, and there has been increased interest in targeting them using peptide-based therapeutics. Peptides benefit from being specific, relatively safe, and easy to produce. They are also easy to modify using chemical synthesis and molecular biology techniques. However, significant challenges remain regarding the use of peptides as therapeutic agents. Identification of peptide motifs is difficult, and peptides typically display low cell permeability and sensitivity to enzymatic degradation. In this review, we outline the principal high-throughput methodologies for motif discovery and describe current methods for overcoming pharmacokinetic and bioavailability limitations.

Many functional roles have been attributed to homodimers, the most common mode of protein self-association, notably in the regulation of enzymes, ion channels, transporters and transcription factors. Here we review findings that offer new insights into the different roles conformational flexibility plays in regulating homodimer function. Intertwined homodimers of two-domain proteins and their related family members display significant conformational flexibility, which translates into concerted motion between structural domains. This flexibility enables the corresponding proteins to regulate function across family members by modulating the spatial positions of key recognition surfaces of individual domains, to either maintain subunit interfaces, alter them or break them altogether, leading to a variety of functional consequences. Many proteins may exist as monomers but carry out their biological function as homodimers or higher-order oligomers. We present early evidence that in such systems homodimer formation primes the protein for its functional role. It does so by inducing elevated mobility in protein regions corresponding to the binding epitopes of functionally important ligands. In some systems this process acts as an allosteric response elicited by the self-association reaction itself. Our analysis furthermore suggests that the induced extra mobility likely facilitates ligand binding through the mechanism of conformational selection. This article is part of a discussion meeting issue ‘Allostery and molecular machines’.

Development of an accurate protein-DNA recognition code that can predict DNA specificity from protein sequence is a central problem in biology. C2H2 zinc fingers constitute by far the largest family of DNA binding domains and their binding specificity has been studied intensively. However, despite decades of research, accurate prediction of DNA specificity remains elusive. A major obstacle is thought to be the inability of current methods to account for the influence of neighbouring domains. Here we show that this problem can be addressed using a structural approach: we build structural models for all C2H2-ZF-DNA complexes with known binding motifs and find six distinct binding modes. Each mode changes the orientation of specificity residues with respect to the DNA, thereby modulating base preference. Most importantly, the structural analysis shows that residues at the domain interface strongly and predictably influence the binding mode, and hence specificity. Accounting for predicted binding mode significantly improves prediction accuracy of predicted motifs. This new insight into the fundamental behaviour of C2H2-ZFs has implications for both improving the prediction of natural zinc finger-binding sites, and for prioritizing further experiments to complete the code. It also provides a new design feature for zinc finger engineering.

Cys2-His2 zinc finger (C2H2-ZF) proteins represent the largest class of putative human transcription factors. However, for most C2H2-ZF proteins it is unknown whether they even bind DNA or, if they do, to which sequences. Here, by combining data from a modified bacterial one-hybrid system with protein-binding microarray and chromatin immunoprecipitation analyses, we show that natural C2H2-ZFs encoded in the human genome bind DNA both in vitro and in vivo, and we infer the DNA recognition code using DNA-binding data for thousands of natural C2H2-ZF domains. In vivo binding data are generally consistent with our recognition code and indicate that C2H2-ZF proteins recognize more motifs than all other human transcription factors combined. We provide direct evidence that most KRAB-containing C2H2-ZF proteins bind specific endogenous retroelements (EREs), ranging from currently active to ancient families. The majority of C2H2-ZF proteins, including KRAB proteins, also show widespread binding to regulatory regions, indicating that the human genome contains an extensive and largely unstudied adaptive C2H2-ZF regulatory network that targets a diverse range of genes and pathways.

Background The C2H2 zinc finger (C2H2-ZF) is the most numerous protein domain in many metazoans, but is not as frequent or diverse in other eukaryotes. The biochemical and evolutionary mechanisms that underlie the diversity of this DNA-binding domain exclusively in metazoans are, however, mostly unknown. Results Here, we show that the C2H2-ZF expansion in metazoans is facilitated by contribution of non-base-contacting residues to DNA binding energy, allowing base-contacting specificity residues to mutate without catastrophic loss of DNA binding. In contrast, C2H2-ZF DNA binding in fungi, plants, and other lineages is constrained by reliance on base-contacting residues for DNA-binding functionality. Reconstructions indicate that virtually every DNA triplet was recognized by at least one C2H2-ZF domain in the common progenitor of placental mammals, but that extant C2H2-ZF domains typically bind different sequences from these ancestral domains, with changes facilitated by non-base-contacting residues. Conclusions Our results suggest that the evolution of C2H2-ZFs in metazoans was expedited by the interaction of non-base-contacting residues with the DNA backbone. We term this phenomenon “kaleidoscopic evolution,” to reflect the diversity of both binding motifs and binding motif transitions and the facilitation of their diversification. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1287-y) contains supplementary material, which is available to authorized users.

Eukaryotic chromosomes are capped by telomeres, nucleoprotein complexes that prevent chromosome end-to-end fusions and control cell ageing. Two proteins in this complex, telomere repeat binding factors (TRF1 and TRF2), specifically recognise the double-stranded TTAGGG tandem repeat sequence. TRF1 is a homodimer with roles governing DNA architecture and negatively regulating telomere length. We explore the conformational space of this protein–DNA complex using molecular dynamics and, for the first time, generate a complete model of TRF1–DNA recognition that has not been possible on the basis of crystallographic and NMR data alone. The results reconcile previous conflicting experimental models for the sequence selectivity of the recognition process, by confirming many of the findings while identifying important new interactions and behaviour. This improved characterisation also reveals extensive indirect readout, which suggests that recognition will be affected by changes to DNA helical parameters such as bending., Graphical abstract, Highlights • X-ray and NMR data on TRF1–DNA fail to fully explain sequence-dependent recognition. • Molecular dynamics simulations reveal a much richer array of dynamic interactions. • The effects of changes in the DNA sequence on binding affinity are explained.

The meticulous study of ichnofabrics and palaeobiological interpretation of behaviour are challenges that lie at the heart of rigorous ichnological analysis. Recent study of Cambrian Skolithos ichnofabrics from the north-west Scottish Highlands has attempted to shed light on the palaeoecology and evolution of the early Cambrian endo-benthos (Davies et al. 2009). The work presented herein highlights some of the difficulties in attempting nearest neighbour analysis on ancient bedding surfaces, and provides some suggestions for how palaeoecological analyses might be approached in pipe-rock facies in future. The greatest challenge to serious study of ichnofabrics in the Eriboll Formation is the lack of lithological contrast between the burrows and host sediment (Fig. 1A). This is less pronounced in the ‘trumpet pipe’ (Monocraterion-rich) interval due to diagenetic enhancement of the fabric (Fig. 1B). At most stratigraphic levels in the Eriboll Formation, pervasive quartz cementation requires that special techniques be employed to study ichnofabric in detail (Garton & McIlroy 2006; Fig. 1D, E). The recognition of the upper burrow terminations that could be considered colonization surfaces is, in our experience, complicated by the observed tendency of some Skolithos in the Eriboll Formation to deviate from the vertical through short oblique kinks (cf. Fig. 1C), and for outcrop surfaces to be variably and irregularly oblique to the vertical plane (see Davies et al. 2009, fig. 3C). In our experience, upper and lower terminations of burrows within pipe-rock ichnofabrics are difficult to determine in the field (cf. Davies et al. 2009, fig. 3A, C) but may be determined with careful observation (Bromley 1996) and can be demonstrated in the laboratory through creation of large thin slices (Garton & McIlroy 2006; Fig. 1F). At sites with net deposition, the Skolithos trace makers are forced to extend their burrow upward to compensate for aggradation of the sediment–water interface. Lower Palaeozoic pipe-rock ichnofabrics have been studied by a number of authors (e.g. Pemberton & Frey 1984; Droser & Bottjer 1989; Droser 1991; McIlroy 2004; McIlroy & Garton 2004). These studies include discussion of bioturbation intensity and its estimation in Skolithos ichnofabrics using flashcards (Droser & Bottjer 1986, 1989). The importance of Skolithos pipe-rock stems from: (1) its potential to provide evidence for the early colonization of marginal marine settings; but also (2) the presence of significant hydrocarbon reserves in such facies throughout northern Africa, the Middle East and in other peri-Gondwanan regions (McIlroy & Garton 2004). Conceptual models for the interpretation of piperock ichnofabrics have been proposed to focus observations of ichnofabric development with respect to colonization, sedimentation rate and changing palaeoenvironmental stress and model ichnofabrics (McIlroy 2004; McIlroy & Garton 2004; Figs 2, 3). These models can be used to augment descriptions of bioturbation intensity (cf. Droser & Bottjer 1989). Application of these ichnofabric-based models to the Eriboll Formation requires careful documentation of ichnofauna and sedimentary facies over large lateral distances, and is a work in progress.

This paper outlines a new method for the study of sedimentary fabrics in well-lithified facies. The technique involves the cutting of large, thin slices of rock that can then be viewed in transmitted light. The utility of this methodology is demonstrated in sandstone, soft siltstone, and even schist. The technique is particularly pertinent to sedimentary geologists studying lithologically homogeneous sediments in which physical and biogenic sedimentary fabrics are difficult to discern due to a lack of contrast.

Local backbone flexibility along the chain was analyzed in pairs of monomer and homodimeric protein structures with identical sequence. We identified pairs, where highly flexible regions (corresponding to prominent peaks in rmsd’s or crystallographic B-factor values) clearly ‘migrate’ to a new location along the polypeptide in the homodimer. We present several systems, where the new flexible region can be linked to the recruitment of a 3rd binding partner, and where this recruitment is not reported for the corresponding monomer. Conformational sampling of these systems over microsecond timescales further confirms the flexibility migration phenomenon. Compelling evidence is provided that altered backbone flexibility in the homodimer state enables specific recruitment of the heterologous binding partner through the process of conformational selection. Our findings lend support to conformational selection as a general mechanism for protein–ligand binding and highlight the regulatory allosteric role played by...