The design of functional proteins using tensorized energy calculations.

In protein design, the energy associated with a huge number of sequence-conformer perturbations has to be routinely estimated. Hence, enhancing the throughput and accuracy of these energy calculations can profoundly improve design success rates and enable tackling more complex design problems. In this work, we explore the possibility of tensorizing the energy calculations and apply them in a protein design framework. We use this framework to design enhanced proteins with anti-cancer and radio-tracing functions. Particularly, we designed multispecific binders against ligands of the epidermal growth factor receptor (EGFR), where the tested design could inhibit EGFR activity in vitro and in vivo. We also used this method to design high-affinity Cu2+ binders that were stable in serum and could be readily loaded with copper-64 radionuclide. The resulting molecules show superior functional properties for their respective applications and demonstrate the generalizable potential of the described protein design approach.

New protein families with hendecad coiled coils in the proteome of life.

Coiled coils are a widespread and well understood protein fold. Their short and simple repeats underpin considerable structural and functional diversity. The vast majority of coiled coils consist of 7-residue (heptad) sequence repeats, but in essence most combinations of 3- and 4-residue segments, each starting with a residue of the hydrophobic core, are compatible with coiled-coil structure. The most frequent among these other repeat patterns are 11-residue (hendecad, 3 + 4 + 4) repeats. Hendecads are frequently found in low copy number, interspersed between heptads, but some proteins consist largely or entirely of hendecad repeats. Here we describe the first large-scale survey of these proteins in the proteome of life. For this, we scanned the protein sequence database for sequences with 11-residue periodicity that lacked ß-strand prediction. We then clustered these by pairwise similarity to construct a map of potential hendecad coiled-coil families. Here we discuss these according to their structural properties, their potential cellular roles, and the evolutionary mechanisms shaping their diversity. We note in particular the continuous amplification of hendecads, both within existing proteins and de novo from previously non-coding sequence, as a powerful mechanism in the genesis of new coiled-coil forms.

A conserved motif suggests a common origin for a group of proteins involved in the cell division of Gram-positive bacteria.

DivIVA, GpsB, FilP, and Scy are all involved in bacterial cell division. They have been reported to interact with each other, and although they have been the subject of considerable research interest, not much is known about the molecular basis for their biological activity. Although they show great variability in taxonomic occurrence, phenotypic profile, and molecular properties, we find that they nevertheless share a conserved N-terminal sequence motif, which points to a common evolutionary origin. The motif always occurs N-terminally to a coiled-coil helix that mediates dimerization. We define the motif and coiled coil jointly as a new domain, which we name DivIVA-like. In a large-scale survey of this domain in the protein sequence database, we identify a new family of proteins potentially involved in cell division, whose members, unlike all other DivIVA-like proteins, have between 2 and 8 copies of the domain in tandem. AlphaFold models indicate that the domains in these proteins assemble within a single chain, therefore not mediating dimerization.

New ß-Propellers Are Continuously Amplified From Single Blades in all Major Lineages of the ß-Propeller Superfamily.

ß-Propellers are toroidal folds, in which consecutive supersecondary structure units of four anti-parallel ß-strands-called blades-are arranged radially around a central axis. Uniquely among toroidal folds, blades span the full range of sequence symmetry, from near identity to complete divergence, indicating an ongoing process of amplification and differentiation. We have proposed that the major lineages of ß-propellers arose through this mechanism and that therefore their last common ancestor was a single blade, not a fully formed ß-propeller. Here we show that this process of amplification and differentiation is also widespread within individual lineages, yielding ß-propellers with blades of more than 60% pairwise sequence identity in most major ß-propeller families. In some cases, the blades are nearly identical, indicating a very recent amplification event, but even in cases where such recently amplified ß-propellers have more than 80% overall sequence identity to each other, comparison of their DNA sequence shows that the amplification occurred independently.

A topological refactoring design strategy yields highly stable granulopoietic proteins.

Protein therapeutics frequently face major challenges, including complicated production, instability, poor solubility, and aggregation. De novo protein design can readily address these challenges. Here, we demonstrate the utility of a topological refactoring strategy to design novel granulopoietic proteins starting from the granulocyte-colony stimulating factor (G-CSF) structure. We change a protein fold by rearranging the sequence and optimising it towards the new fold. Testing four designs, we obtain two that possess nanomolar activity, the most active of which is highly thermostable and protease-resistant, and matches its designed structure to atomic accuracy. While the designs possess starkly different sequence and structure from the native G-CSF, they show specific activity in differentiating primary human haematopoietic stem cells into mature neutrophils. The designs also show significant and specific activity in vivo. Our topological refactoring approach is largely independent of sequence or structural context, and is therefore applicable to a wide range of protein targets.

RpuS/R Is a Novel Two-Component Signal Transduction System That Regulates the Expression of the Pyruvate Symporter MctP in Sinorhizobium fredii NGR234.

The SLC5/STAC histidine kinases comprise a recently identified family of sensor proteins in two-component signal transduction systems (TCSTS), in which the signaling domain is fused to an SLC5 solute symporter domain through a STAC domain. Only two members of this family have been characterized experimentally, the CrbS/R system that regulates acetate utilization in Vibrio and Pseudomonas, and the CbrA/B system that regulates the utilization of histidine in Pseudomonas and glucose in Azotobacter. In an attempt to expand the characterized members of this family beyond the Gammaproteobacteria, we identified two putative TCSTS in the Alphaproteobacterium Sinorhizobium fredii NGR234 whose sensor histidine kinases belong to the SLC5/STAC family. Using reverse genetics, we were able to identify the first TCSTS as a CrbS/R homolog that is also needed for growth on acetate, while the second TCSTS, RpuS/R, is a novel system required for optimal growth on pyruvate. Using RNAseq and transcriptional fusions, we determined that in S. fredii the RpuS/R system upregulates the expression of an operon coding for the pyruvate symporter MctP when pyruvate is the sole carbon source. In addition, we identified a conserved DNA sequence motif in the putative promoter region of the mctP operon that is essential for the RpuR-mediated transcriptional activation of genes under pyruvate-utilizing conditions. Finally, we show that S. fredii mutants lacking these TCSTS are affected in nodulation, producing fewer nodules than the parent strain and at a slower rate.

Exploring protein-protein interactions at the proteome level.

Proteins are central to all of the processes of life. For their activity, they almost invariably need to interact with other macromolecules, be they nucleic acids, membranes, glycans, or other proteins. The interaction between proteins is indeed the most common mode of macromolecular interaction underpinning living systems. To understand these systems at a molecular level, it is therefore essential to identify and characterize their constituent protein-protein interactions. Despite an unprecedented growth in our knowledge of complete proteomes across all domains of life, both at the sequence level and increasingly at the structure level, the inherently low accuracy and molecular resolution of many techniques have made the characterization of protein-protein interactions one of the grand challenges of molecular biology. In this review, we survey both computational and experimental techniques for the medium- to high-throughput characterization of protein-protein interactions and discuss the potential of integrative approaches, given recent advances in sequence analysis and structure prediction.

Identification of the adhesive domain of AtaA from Acinetobacter sp. Tol 5 and its application in immobilizing Escherichia coli.

Cell immobilization is an important technique for efficiently utilizing whole-cell biocatalysts. We previously invented a method for bacterial cell immobilization using AtaA, a trimeric autotransporter adhesin from the highly sticky bacterium Acinetobacter sp. Tol 5. However, except for Acinetobacter species, only one bacterium has been successfully immobilized using AtaA. This is probably because the heterologous expression of large AtaA (1 MDa), that is a homotrimer of polypeptide chains composed of 3,630 amino acids, is difficult. In this study, we identified the adhesive domain of AtaA and constructed a miniaturized AtaA (mini-AtaA) to improve the heterologous expression of ataA. In-frame deletion mutants were used to perform functional mapping, revealing that the N-terminal head domain is essential for the adhesive feature of AtaA. The mini-AtaA, which contains a homotrimer of polypeptide chains from 775 amino acids and lacks the unnecessary part for its adhesion, was properly expressed in E. coli, and a larger amount of molecules was displayed on the cell surface than that of full-length AtaA (FL-AtaA). The immobilization ratio of E. coli cells expressing mini-AtaA on a polyurethane foam support was significantly higher compared to the cells with or without FL-AtaA expression, respectively. The expression of mini-AtaA in E. coli had little effect on the cell growth and the activity of another enzyme reflecting the production level, and the immobilized E. coli cells could be used for repetitive enzymatic reactions as a whole-cell catalyst.

Target highlights in CASP14: Analysis of models by structure providers.

The biological and functional significance of selected Critical Assessment of Techniques for Protein Structure Prediction 14 (CASP14) targets are described by the authors of the structures. The authors highlight the most relevant features of the target proteins and discuss how well these features were reproduced in the respective submitted predictions. The overall ability to predict three-dimensional structures of proteins has improved remarkably in CASP14, and many difficult targets were modeled with impressive accuracy. For the first time in the history of CASP, the experimentalists not only highlighted that computational models can accurately reproduce the most critical structural features observed in their targets, but also envisaged that models could serve as a guidance for further studies of biologically-relevant properties of proteins.

Assessing the utility of CASP14 models for molecular replacement.

The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real-world application. In CASP7, the metric for molecular replacement assessment involved full likelihood-based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood-based rigid-body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log-likelihood-gain (LLG) score. This enabled multi-copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative-expected-LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X-ray, NMR or cryo-EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

Computational models in the service of X-ray and cryo-electron microscopy structure determination.

Critical assessment of structure prediction (CASP) conducts community experiments to determine the state of the art in computing protein structure from amino acid sequence. The process relies on the experimental community providing information about not yet public or about to be solved structures, for use as targets. For some targets, the experimental structure is not solved in time for use in CASP. Calculated structure accuracy improved dramatically in this round, implying that models should now be much more useful for resolving many sorts of experimental difficulties. To test this, selected models for seven unsolved targets were provided to the experimental groups. These models were from the AlphaFold2 group, who overall submitted the most accurate predictions in CASP14. Four targets were solved with the aid of the models, and, additionally, the structure of an already solved target was improved. An a posteriori analysis showed that, in some cases, models from other groups would also be effective. This paper provides accounts of the successful application of models to structure determination, including molecular replacement for X-ray crystallography, backbone tracing and sequence positioning in a cryo-electron microscopy structure, and correction of local features. The results suggest that, in future, there will be greatly increased synergy between computational and experimental approaches to structure determination.

High-accuracy protein structure prediction in CASP14.

The application of state-of-the-art deep-learning approaches to the protein modeling problem has expanded the "high-accuracy" category in CASP14 to encompass all targets. Building on the metrics used for high-accuracy assessment in previous CASPs, we evaluated the performance of all groups that submitted models for at least 10 targets across all difficulty classes, and judged the usefulness of those produced by AlphaFold2 (AF2) as molecular replacement search models with AMPLE. Driven by the qualitative diversity of the targets submitted to CASP, we also introduce DipDiff as a new measure for the improvement in backbone geometry provided by a model versus available templates. Although a large leap in high-accuracy is seen due to AF2, the second-best method in CASP14 out-performed the best in CASP13, illustrating the role of community-based benchmarking in the development and evolution of the protein structure prediction field.

An astonishing wealth of new proteasome homologs.

MOTIVATION: The proteasome is the main proteolytic machine for targeted protein degradation in archaea and eukaryotes. While some bacteria also possess the proteasome, most of them contain a simpler and more specialized homolog, the heat shock locus V protease. In recent years, three further homologs of the proteasome core subunits have been characterized in prokaryotes: Anbu, BPH and connectase. With the inclusion of these members, the family of proteasome-like proteins now exhibits a range of architectural and functional forms, from the canonical proteasome, a barrel-shaped protease without pronounced intrinsic substrate specificity, to the monomeric connectase, a highly specific protein ligase. RESULTS: We employed systematic sequence searches to show that we have only seen the tip of the iceberg so far and that beyond the hitherto known proteasome homologs lies a wealth of distantly related, uncharacterized homologs. We describe a total of 22 novel proteasome homologs in bacteria and archaea. Using sequence and structure analysis, we analyze their evolutionary history and assess structural differences that may modulate their function. With this initial description, we aim to stimulate the experimental investigation of these novel proteasome-like family members. AVAILABILITY AND IMPLEMENTATION: The protein sequences in this study are searchable in the MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) with ProtBLAST/PSI-BLAST and with HHpred (database 'proteasome_homologs'). The following data are available at https://data.mendeley.com/datasets/t48yhff7hs/3: (i) sequence alignments for each proteasome-like homolog, (ii) the coordinates for their structural models and (iii) a cluster-map file, which can be navigated interactively in CLANS and gives direct access to all the sequences in this study. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Gram-negative outer-membrane proteins with multiple ß-barrel domains.

Outer-membrane beta barrels (OMBBs) are found in the outer membrane of gram-negative bacteria and eukaryotic organelles. OMBBs fold as antiparallel ß-sheets that close onto themselves, forming pores that traverse the membrane. Currently known structures include only one barrel, of 8 to 36 strands, per chain. The lack of multi-OMBB chains is surprising, as most OMBBs form oligomers, and some function only in this state. Using a combination of sensitive sequence comparison methods and coevolutionary analysis tools, we identify many proteins combining multiple beta barrels within a single chain; combinations that include eight-stranded barrels prevail. These multibarrels seem to be the result of independent, lineage-specific fusion and amplification events. The absence of multibarrels that are universally conserved in bacteria with an outer membrane, coupled with their frequent de novo genesis, suggests that their functions are not essential but rather beneficial in specific environments. Adjacent barrels of complementary function within the same chain may allow for functions beyond those of the individual barrels.

The breakthrough in protein structure prediction.

Proteins are the essential agents of all living systems. Even though they are synthesized as linear chains of amino acids, they must assume specific three-dimensional structures in order to manifest their biological activity. These structures are fully specified in their amino acid sequences - and therefore in the nucleotide sequences of their genes. However, the relationship between sequence and structure, known as the protein folding problem, has remained elusive for half a century, despite sustained efforts. To measure progress on this problem, a series of doubly blind, biennial experiments called CASP (critical assessment of structure prediction) were established in 1994. We were part of the assessment team for the most recent CASP experiment, CASP14, where we witnessed an astonishing breakthrough by DeepMind, the leading artificial intelligence laboratory of Alphabet Inc. The models filed by DeepMind's structure prediction team using the program AlphaFold2 were often essentially indistinguishable from experimental structures, leading to a consensus in the community that the structure prediction problem for single protein chains has been solved. Here, we will review the path to CASP14, outline the method employed by AlphaFold2 to the extent revealed, and discuss the implications of this breakthrough for the life sciences.

Archaeal Connectase is a specific and efficient protein ligase related to proteasome ß subunits.

Sequence-specific protein ligations are widely used to produce customized proteins "on demand." Such chimeric, immobilized, fluorophore-conjugated or segmentally labeled proteins are generated using a range of chemical, (split) intein, split domain, or enzymatic methods. Where short ligation motifs and good chemoselectivity are required, ligase enzymes are often chosen, although they have a number of disadvantages, for example poor catalytic efficiency, low substrate specificity, and side reactions. Here, we describe a sequence-specific protein ligase with more favorable characteristics. This ligase, Connectase, is a monomeric homolog of 20S proteasome subunits in methanogenic archaea. In pulldown experiments with Methanosarcina mazei cell extract, we identify a physiological substrate in methyltransferase A (MtrA), a key enzyme of archaeal methanogenesis. Using microscale thermophoresis and X-ray crystallography, we show that only a short sequence of about 20 residues derived from MtrA and containing a highly conserved KDPGA motif is required for this high-affinity interaction. Finally, in quantitative activity assays, we demonstrate that this recognition tag can be repurposed to allow the ligation of two unrelated proteins. Connectase catalyzes such ligations at substantially higher rates, with higher yields, but without detectable side reactions when compared with a reference enzyme. It thus presents an attractive tool for the development of new methods, for example in the preparation of selectively labeled proteins for NMR, the covalent and geometrically defined attachment of proteins on surfaces for cryo-electron microscopy, or the generation of multispecific antibodies.

The VCBS superfamily forms a third supercluster of ß-propellers that includes tachylectin and integrins.

MOTIVATION: ß-Propellers are found in great variety across all kingdoms of life. They assume many cellular roles, primarily as scaffolds for macromolecular interactions and catalysis. Despite their diversity, most ß-propeller families clearly originated by amplification from the same ancient peptide-the 'blade'. In cluster analyses, ß-propellers of the WD40 superfamily always formed the largest group, to which some important families, such as the α-integrin, Asp-box and glycoside hydrolase ß-propellers connected weakly. Motivated by the dramatic growth of sequence databases we revisited these connections, with a special focus on VCBS-like ß-propellers, which have not been analysed for their evolutionary relationships so far. RESULTS: We found that VCBS-like form a supercluster with integrin-like ß-propellers and tachylectins, clearly delimited from the superclusters formed by WD40 and Asp-Box ß-propellers. Connections between the three superclusters are made mainly through PQQ-like ß-propeller. Our results present a new, greatly expanded view of the ß-propeller classification landscape. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Design of novel granulopoietic proteins by topological rescaffolding.

Computational protein design is rapidly becoming more powerful, and improving the accuracy of computational methods would greatly streamline protein engineering by eliminating the need for empirical optimization in the laboratory. In this work, we set out to design novel granulopoietic agents using a rescaffolding strategy with the goal of achieving simpler and more stable proteins. All of the 4 experimentally tested designs were folded, monomeric, and stable, while the 2 determined structures agreed with the design models within less than 2.5 Å. Despite the lack of significant topological or sequence similarity to their natural granulopoietic counterpart, 2 designs bound to the granulocyte colony-stimulating factor (G-CSF) receptor and exhibited potent, but delayed, in vitro proliferative activity in a G-CSF-dependent cell line. Interestingly, the designs also induced proliferation and differentiation of primary human hematopoietic stem cells into mature granulocytes, highlighting the utility of our approach to develop highly active therapeutic leads purely based on computational design.

Protein Sequence Analysis Using the MPI Bioinformatics Toolkit.

The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) provides interactive access to a wide range of the best-performing bioinformatics tools and databases, including the state-of-the-art protein sequence comparison methods HHblits and HHpred. The Toolkit currently includes 35 external and in-house tools, covering functionalities such as sequence similarity searching, prediction of sequence features, and sequence classification. Due to this breadth of functionality, the tight interconnection of its constituent tools, and its ease of use, the Toolkit has become an important resource for biomedical research and for teaching protein sequence analysis to students in the life sciences. In this article, we provide detailed information on utilizing the three most widely accessed tools within the Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets. © 2020 The Authors. Basic Protocol 1: Sequence similarity searching using HHpred Alternate Protocol: Pairwise sequence comparison using HHpred Support Protocol: Building a custom multiple sequence alignment using PSI-BLAST and forwarding it as input to HHpred Basic Protocol 2: Calculation of homology models using HHpred and MODELLER Basic Protocol 3: Cluster analysis using CLANS.