MICAN: a protein structure alignment algorithm that can handle Multiple-chains, Inverse alignments, C(α) only models, Alternative alignments, and Non-sequential alignments

Design of complicated all-α protein structures

A wide range of de novo protein structure designs have been achieved, but the complexity of naturally occurring protein structures is still far beyond these designs. Here, to expand the diversity and complexity of de novo designed protein structures, we sought to develop a method for designing 'difficult-to-describe' α-helical protein structures composed of irregularly aligned α-helices like globins. Backbone structure libraries consisting of a myriad of α-helical structures with five or six helices were generated by combining 18 helix-loop-helix motifs and canonical α-helices, and five distinct topologies were selected for de novo design. The designs were found to be monomeric with high thermal stability in solution and fold into the target topologies with atomic accuracy. This study demonstrated that complicated α-helical proteins are created using typical building blocks. The method we developed will enable us to explore the universe of protein structures for designing novel functional proteins.

Isolation and Characterization of Neutralizing Monoclonal Antibodies from a Large Panel of Murine Antibodies against RBD of the SARS-CoV-2 Spike Protein

The COVID-19 pandemic, once a global crisis, is now largely under control, a testament to the extraordinary global efforts involving vaccination and public health measures. However, the relentless evolution of SARS-CoV-2, leading to the emergence of new variants, continues to underscore the importance of remaining vigilant and adaptable. Monoclonal antibodies (mAbs) have stood out as a powerful and immediate therapeutic response to COVID-19. Despite the success of mAbs, the evolution of SARS-CoV-2 continues to pose challenges and the available antibodies are no longer effective. New variants require the ongoing development of effective antibodies. In the present study, we describe the generation and characterization of neutralizing mAbs against the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein by combining plasmid DNA and recombinant protein vaccination. By integrating genetic immunization for rapid antibody production and the potent immune stimulation enabled by protein vaccination, we produced a rich pool of antibodies, each with unique binding and neutralizing specificities, tested with the ELISA, BLI and FACS assays and the pseudovirus assay, respectively. Here, we present a panel of mAbs effective against the SARS-CoV-2 variants up to Omicron BA.1 and BA.5, with the flexibility to target emerging variants. This approach ensures the preparedness principle is in place to address SARS-CoV-2 actual and future infections.

Design of allosteric sites into rotary motor V1-ATPase by restoring lost function of pseudo-active sites

Allostery produces concerted functions of protein complexes by orchestrating the cooperative work between the constituent subunits. Here we describe an approach to create artificial allosteric sites in protein complexes. Certain protein complexes contain subunits with pseudo-active sites, which are believed to have lost functions during evolution. Our hypothesis is that allosteric sites in such protein complexes can be created by restoring the lost functions of pseudo-active sites. We used computational design to restore the lost ATP-binding ability of the pseudo-active site in the B subunit of a rotary molecular motor, V1-ATPase. Single-molecule experiments with X-ray crystallography analyses revealed that binding of ATP to the designed allosteric site boosts this V1's activity compared with the wild-type, and the rotation rate can be tuned by modulating ATP's binding affinity. Pseudo-active sites are widespread in nature, and our approach shows promise as a means of programming allosteric control over concerted functions of protein complexes.

Exploration of novel αβ-protein folds through de novo design

A fundamental question in protein evolution is whether nature has exhaustively sampled nearly all possible protein folds throughout evolution, or whether a large fraction of the possible folds remains unexplored. To address this question, we defined a set of rules for β-sheet topology to predict novel αβ-folds and carried out a systematic de novo protein design exploration of the novel αβ-folds predicted by the rules. The designs for all eight of the predicted novel αβ-folds with a four-stranded β-sheet, including a knot-forming one, folded into structures close to the design models. Further, the rules predicted more than 10,000 novel αβ-folds with five- to eight-stranded β-sheets; this number far exceeds the number of αβ-folds observed in nature so far. This result suggests that a vast number of αβ-folds are possible, but have not emerged or have become extinct due to evolutionary bias.

BeEM: fast and faithful conversion of mmCIF format structure files to PDB format

BACKGROUND

Although mmCIF is the current official format for deposition of protein and nucleic acid structures to the protein data bank (PDB) database, the legacy PDB format is still the primary supported format for many structural bioinformatics tools. Therefore, reliable software to convert mmCIF structure files to PDB files is needed. Unfortunately, existing conversion programs fail to correctly convert many mmCIF files, especially those with many atoms and/or long chain identifies.

RESULTS

This study proposed BeEM, which converts any mmCIF format structure files to PDB format. BeEM conversion faithfully retains all atomic and chain information, including chain IDs with more than 2 characters, which are not supported by any existing mmCIF to PDB converters. The conversion speed of BeEM is at least ten times faster than existing converters such as MAXIT and Phenix. Part of the reason for the speed improvement is the avoidance of conversion between numerical values and text strings.

CONCLUSION

BeEM is a fast and accurate tool for mmCIF-to-PDB format conversion, which is a common procedure in structural biology. The source code is available under the BSD licence at https://github.com/kad-ecoli/BeEM/ .

Prediction of chaperonin GroE substrates using small structural patterns of proteins

Molecular chaperones are indispensable proteins that assist the folding of aggregation-prone proteins into their functional native states, thereby maintaining organized cellular systems. Two of the best-characterized chaperones are the Escherichia coli chaperonins GroEL and GroES (GroE), for which in vivo obligate substrates have been identified by proteome-wide experiments. These substrates comprise various proteins but exhibit remarkable structural features. They include a number of α/β proteins, particularly those adopting the TIM β/α barrel fold. This observation led us to speculate that GroE obligate substrates share a structural motif. Based on this hypothesis, we exhaustively compared substrate structures with the MICAN alignment tool, which detects common structural patterns while ignoring the connectivity or orientation of secondary structural elements. We selected four (or five) substructures with hydrophobic indices that were mostly included in substrates and excluded in others, and developed a GroE obligate substrate discriminator. The substructures are structurally similar and superimposable on the 2-layer 2α4β sandwich, the most popular protein substructure, implying that targeting this structural pattern is a useful strategy for GroE to assist numerous proteins. Seventeen false positives predicted by our methods were experimentally examined using GroE-depleted cells, and 9 proteins were confirmed to be novel GroE obligate substrates. Together, these results demonstrate the utility of our common substructure hypothesis and prediction method.

MeDBA: the Metalloenzyme Data Bank and Analysis platform

Metalloenzymes are attractive research targets in fields of chemistry, biology, and medicine. Given that metalloenzymes can manifest conservation of metal-coordination and ligand binding modes, the excavation and expansion of metalloenzyme-specific knowledge is of interest in bridging metalloenzyme-related fields. Building on our previous metalloenzyme-ligand association database, MeLAD, we have expanded the scope of metalloenzyme-specific knowledge and services, by forming a versatile platform, termed the Metalloenzyme Data Bank and Analysis (MeDBA). The MeDBA provides: (i) manual curation of metalloenzymes into different categories, that this M-I, M-II and M-III; (ii) comprehensive information on metalloenzyme activities, expression profiles, family and disease links; (iii) structural information on metalloenzymes, in particular metal binding modes; (iv) metalloenzyme substrates and bioactive molecules acting on metalloenzymes; (v) excavated metal-binding pharmacophores and (vi) analysis tools for structure/metal active site comparison and metalloenzyme profiling. The MeDBA is freely available at https://medba.ddtmlab.org.

US-align: universal structure alignments of proteins, nucleic acids, and macromolecular complexes

Structure comparison and alignment are of fundamental importance in structural biology studies. We developed the first universal platform, US-align, to uniformly align monomer and complex structures of different macromolecules-proteins, RNAs and DNAs. The pipeline is built on a uniform TM-score objective function coupled with a heuristic alignment searching algorithm. Large-scale benchmarks demonstrated consistent advantages of US-align over state-of-the-art methods in pairwise and multiple structure alignments of different molecules. Detailed analyses showed that the main advantage of US-align lies in the extensive optimization of the unified objective function powered by efficient heuristic search iterations, which substantially improve the accuracy and speed of the structural alignment process. Meanwhile, the universal protocol fusing different molecular and structural types helps facilitate the heterogeneous oligomer structure comparison and template-based protein-protein and protein-RNA/DNA docking.

An auto-inhibited state of protein kinase G and implications for selective activation

Cyclic GMP-dependent protein kinases (PKGs) are key mediators of the nitric oxide/cyclic guanosine monophosphate (cGMP) signaling pathway that regulates biological functions as diverse as smooth muscle contraction, cardiac function, and axon guidance. Understanding how cGMP differentially triggers mammalian PKG isoforms could lead to new therapeutics that inhibit or activate PKGs, complementing drugs that target nitric oxide synthases and cyclic nucleotide phosphodiesterases in this signaling axis. Alternate splicing of PRKG1 transcripts confers distinct leucine zippers, linkers, and auto-inhibitory (AI) pseudo-substrate sequences to PKG Iα and Iβ that result in isoform-specific activation properties, but the mechanism of enzyme auto-inhibition and its alleviation by cGMP is not well understood. Here, we present a crystal structure of PKG Iβ in which the AI sequence and the cyclic nucleotide-binding (CNB) domains are bound to the catalytic domain, providing a snapshot of the auto-inhibited state. Specific contacts between the PKG Iβ AI sequence and the enzyme active site help explain isoform-specific activation constants and the effects of phosphorylation in the linker. We also present a crystal structure of a PKG I CNB domain with an activating mutation linked to Thoracic Aortic Aneurysms and Dissections. Similarity of this structure to wildtype cGMP-bound domains and differences with the auto-inhibited enzyme provide a mechanistic basis for constitutive activation. We show that PKG Iβ auto-inhibition is mediated by contacts within each monomer of the native full-length dimeric protein, and using the available structural and biochemical data we develop a model for the regulation and cooperative activation of PKGs.

The register shift rules for βαβ-motifs for de novo protein design

A wide range of de novo design of αβ-proteins has been achieved based on the design rules, which describe secondary structure lengths and loop torsion patterns favorable for design target topologies. This paper proposes design rules for register shifts in βαβ-motifs, which have not been reported previously, but are necessary for determining a target structure of de novo design of αβ-proteins. By analyzing naturally occurring protein structures in a database, we found preferences for register shifts in βαβ-motifs, and derived the following empirical rules: (1) register shifts must not be negative regardless of torsion types for a constituent loop in βαβ-motifs; (2) preferred register shifts strongly depend on the loop torsion types. To explain these empirical rules by physical interactions, we conducted physics-based simulations for systems mimicking a βαβ-motif that contains the most frequently observed loop type in the database. We performed an exhaustive conformational sampling of the loop region, imposing the exclusion volume and hydrogen bond satisfaction condition. The distributions of register shifts obtained from the simulations agreed well with those of the database analysis, indicating that the empirical rules are a consequence of physical interactions, rather than an evolutionary sampling bias. Our proposed design rules will serve as a guide to making appropriate target structures for the de novo design of αβ-proteins.

Distinct mutations in importin-β family nucleocytoplasmic transport receptors transportin-SR and importin-13 affect specific cargo binding

Importin-(Imp)β family nucleocytoplasmic transport receptors (NTRs) are supposed to bind to their cargoes through interaction between a confined interface on an NTR and a nuclear localization or export signal (NLS/NES) on a cargo. Although consensus NLS/NES sequence motifs have been defined for cargoes of some NTRs, many experimentally identified cargoes of those NTRs lack those motifs, and consensus NLSs/NESs have been reported for only a few NTRs. Crystal structures of NTR-cargo complexes have exemplified 3D structure-dependent binding of cargoes lacking a consensus NLS/NES to different sites on an NTR. Since only a limited number of NTR-cargo interactions have been studied, whether most cargoes lacking a consensus NLS/NES bind to the same confined interface or to various sites on an NTR is still unclear. Addressing this issue, we generated four mutants of transportin-(Trn)SR, of which many cargoes lack a consensus NLS, and eight mutants of Imp13, where no consensus NLS has been defined, and we analyzed their binding to as many as 40 cargo candidates that we previously identified by a nuclear import reaction-based method. The cargoes bind differently to the NTR mutants, suggesting that positions on an NTR contribute differently to the binding of respective cargoes.

AncPhore: A versatile tool for anchor pharmacophore steered drug discovery with applications in discovery of new inhibitors targeting metallo-β-lactamases and indoleamine/tryptophan 2,3-dioxygenases

We herein describe AncPhore, a versatile tool for drug discovery, which is characterized by pharmacophore feature analysis and anchor pharmacophore (i.e., most important pharmacophore features) steered molecular fitting and virtual screening. Comparative analyses of numerous protein–ligand complexes using AncPhore revealed that anchor pharmacophore features are biologically important, commonly associated with protein conservative characteristics, and have significant contributions to the binding affinity. Performance evaluation of AncPhore showed that it had substantially improved prediction ability on different types of target proteins including metalloenzymes by considering the specific contributions and diversity of anchor pharmacophore features. To demonstrate the practicability of AncPhore, we screened commercially available chemical compounds and discovered a set of structurally diverse inhibitors for clinically relevant metallo-β-lactamases (MBLs); of them, 4 and 6 manifested potent inhibitory activity to VIM-2, NDM-1 and IMP-1 MBLs. Crystallographic analyses of VIM-2:4 complex revealed the precise inhibition mode of 4 with VIM-2, highly consistent with the defined anchor pharmacophore features. Besides, we also identified new hit compounds by using AncPhore for indoleamine/tryptophan 2,3-dioxygenases (IDO/TDO), another class of clinically relevant metalloenzymes. This work reveals anchor pharmacophore as a valuable concept for target-centered drug discovery and illustrates the potential of AncPhore to efficiently identify new inhibitors for different types of protein targets.

De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2

We developed a de novo protein design strategy to swiftly engineer decoys for neutralizing pathogens that exploit extracellular host proteins to infect the cell. Our pipeline allowed the design, validation, and optimization of de novo human angiotensin-converting enzyme 2 (hACE2) decoys to neutralize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The best monovalent decoy, CTC-445.2, bound with low nanomolar affinity and high specificity to the receptor-binding domain (RBD) of the spike protein. Cryo-electron microscopy (cryo-EM) showed that the design is accurate and can simultaneously bind to all three RBDs of a single spike protein. Because the decoy replicates the spike protein target interface in hACE2, it is intrinsically resilient to viral mutational escape. A bivalent decoy, CTC-445.2d, showed ~10-fold improvement in binding. CTC-445.2d potently neutralized SARS-CoV-2 infection of cells in vitro, and a single intranasal prophylactic dose of decoy protected Syrian hamsters from a subsequent lethal SARS-CoV-2 challenge.

Topology-independent and global protein structure alignment through an FFT-based algorithm

MOTIVATION

Protein structure alignment is one of the fundamental problems in computational structure biology. A variety of algorithms have been developed to address this important issue in the past decade. However, due to their heuristic nature, current structure alignment methods may suffer from suboptimal alignment and/or over-fragmentation and thus lead to a biologically wrong alignment in some cases. To overcome these limitations, we have developed an accurate topology-independent and global structure alignment method through an FFT-based exhaustive search algorithm, which is referred to as FTAlign.

RESULTS

Our FTAlign algorithm was extensively tested on six commonly used datasets and compared with seven state-of-the-art structure alignment approaches, TMalign, DeepAlign, Kpax, 3DCOMB, MICAN, SPalignNS and CLICK. It was shown that FTAlign outperformed the other methods in reproducing manually curated alignments and obtained a high success rate of 96.7 and 90.0% on two gold-standard benchmarks, MALIDUP and MALISAM, respectively. Moreover, FTAlign also achieved the overall best performance in terms of biologically meaningful structure overlap (SO) and TMscore on both the sequential alignment test sets including MALIDUP, MALISAM and 64 difficult cases from HOMSTRAD, and the non-sequential sets including MALIDUP-NS, MALISAM-NS, 199 topology-different cases, where FTAlign especially showed more advantage for non-sequential alignment. Despite its global search feature, FTAlign is also computationally efficient and can normally complete a pairwise alignment within one second.

AVAILABILITY AND IMPLEMENTATION

http://huanglab.phys.hust.edu.cn/ftalign/.

An ancient evolutionary connection between Ribonuclease A and EndoU families

The ribonuclease A family of proteins is well studied from the biochemical and biophysical points of view, but its evolutionary origins are obscure, as no sequences homologous to this family have been reported outside of vertebrates. Recently, the spatial structure of the ribonuclease domain from a bacterial polymorphic toxin was shown to be closely similar to the structure of vertebrate ribonuclease A. The absence of sequence similarity between the two structures prompted a speculation of convergent evolution of bacterial and vertebrate ribonuclease A-like enzymes. We show that bacterial and homologous archaeal polymorphic toxin ribonucleases with a known or predicted ribonuclease A-like fold are distant homologs of the ribonucleases from the EndoU family, found in all domains of cellular life and in viruses. We also detected a homolog of vertebrate ribonucleases A in the transcriptome assembly of the sea urchin Mesocentrotus franciscanus These observations argue for the common ancestry of prokaryotic ribonuclease A-like and ubiquitous EndoU-like ribonucleases, and suggest a better-grounded scenario for the origin of animal ribonucleases A, which could have emerged in the deuterostome lineage, either by an extensive modification of a copy of an EndoU gene, or, more likely, by a horizontal acquisition of a prokaryotic immunity-mediating ribonuclease gene.

MeLAD: an integrated resource for metalloenzyme-ligand associations

MOTIVATION

Metalloenzymes are attractive targets for therapeutic intervention owing to their central roles in various biological processes and pathological situations. The fast-growing body of structural data on metalloenzyme-ligand interactions is facilitating efficient drug discovery targeting metalloenzymes. However, there remains a shortage of specific databases that can provide centralized, interconnected information exclusive to metalloenzyme-ligand associations.

RESULTS

We created a Metalloenzyme-Ligand Association Database (MeLAD), which is designed to provide curated structural data and information exclusive to metalloenzyme-ligand interactions, and more uniquely, present expanded associations that are represented by metal-binding pharmacophores (MBPs), metalloenzyme structural similarity (MeSIM) and ligand chemical similarity (LigSIM). MeLAD currently contains 6086 structurally resolved interactions of 1416 metalloenzymes with 3564 ligands, of which classical metal-binding, non-classical metal-binding, non-metal-binding and metal water-bridging interactions account for 63.0%, 2.3%, 34.4% and 0.3%, respectively. A total of 263 monodentate, 191 bidentate and 15 tridentate MBP chemotypes were included in MeLAD, which are linked to different active site metal ions and coordination modes. 3726 and 52 740 deductive metalloenzyme-ligand associations by MeSIM and LigSIM analyses, respectively, were included in MeLAD. An online server is provided for users to conduct metalloenzyme profiling prediction for small molecules of interest. MeLAD is searchable by multiple criteria, e.g. metalloenzyme name, ligand identifier, functional class, bioinorganic class, metal ion and metal-containing cofactor, which will serve as a valuable, integrative data source to foster metalloenzyme related research, particularly involved in drug discovery targeting metalloenzymes.

AVAILABILITY AND IMPLEMENTATION

MeLAD is accessible at https://melad.ddtmlab.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Topology independent structural matching discovers novel templates for protein interfaces

Motivation

Protein-protein interactions (PPI) are essential for the function of the cellular machinery. The rapid growth of protein-protein complexes with known 3D structures offers a unique opportunity to study PPI to gain crucial insights into protein function and the causes of many diseases. In particular, it would be extremely useful to compare interaction surfaces of monomers, as this would enable the pinpointing of potential interaction surfaces based solely on the monomer structure, without the need to predict the complete complex structure. While there are many structural alignment algorithms for individual proteins, very few have been developed for protein interfaces, and none that can align only the interface residues to other interfaces or surfaces of interacting monomer subunits in a topology independent (non-sequential) manner.

Results

We present InterComp, a method for topology and sequence-order independent structural comparisons. The method is general and can be applied to various structural comparison applications. By representing residues as independent points in space rather than as a sequence of residues, InterComp can be applied to a wide range of problems including interface-surface comparisons and interface-interface comparisons. We demonstrate a use-case by applying InterComp to find similar protein interfaces on the surface of proteins. We show that InterComp pinpoints the correct interface for almost half of the targets (283 of 586) when considering the top 10 hits, and for 24% of the top 1, even when no templates can be found with regular sequence-order dependent structural alignment methods.

Availability and implementation

The source code and the datasets are available at: http://wallnerlab.org/InterComp.

Supplementary information

Supplementary data are available at Bioinformatics online.

Graph Splitting: A Graph-Based Approach for Superfamily-Scale Phylogenetic Tree Reconstruction

A protein superfamily contains distantly related proteins that have acquired diverse biological functions through a long evolutionary history. Phylogenetic analysis of the early evolution of protein superfamilies is a key challenge because existing phylogenetic methods show poor performance when protein sequences are too diverged to construct an informative multiple sequence alignment (MSA). Here, we propose the Graph Splitting (GS) method, which rapidly reconstructs a protein superfamily-scale phylogenetic tree using a graph-based approach. Evolutionary simulation showed that the GS method can accurately reconstruct phylogenetic trees and be robust to major problems in phylogenetic estimation, such as biased taxon sampling, heterogeneous evolutionary rates, and long-branch attraction when sequences are substantially diverge. Its application to an empirical data set of the triosephosphate isomerase (TIM)-barrel superfamily suggests rapid evolution of protein-mediated pyrimidine biosynthesis, likely taking place after the RNA world. Furthermore, the GS method can also substantially improve performance of widely used MSA methods by providing accurate guide trees.

Non-sequential protein structure alignment by conformational space annealing and local refinement

Protein structure alignment is an important tool for studying evolutionary biology and protein modeling. A tool which intensively searches for the globally optimal non-sequential alignments is rarely found. We propose ALIGN-CSA which shows improvement in scores, such as DALI-score, SP-score, SO-score and TM-score over the benchmark set including 286 cases. We performed benchmarking of existing popular alignment scoring functions, where the dependence of the search algorithm was effectively eliminated by using ALIGN-CSA. For the benchmarking, we set the minimum block size to 4 to prevent much fragmented alignments where the biological relevance of small alignment blocks is hard to interpret. With this condition, globally optimal alignments were searched by ALIGN-CSA using the four scoring functions listed above, and TM-score is found to be the most effective in generating alignments with longer match lengths and smaller RMSD values. However, DALI-score is the most effective in generating alignments similar to the manually curated reference alignments, which implies that DALI-score is more biologically relevant score. Due to the high demand on computational resources of ALIGN-CSA, we also propose a relatively fast local refinement method, which can control the minimum block size and whether to allow the reverse alignment. ALIGN-CSA can be used to obtain much improved alignment at the cost of relatively more extensive computation. For faster alignment, we propose a refinement protocol that improves the score of a given alignment obtained by various external tools. All programs are available from http://lee.kias.re.kr.

De novo design of potent and selective mimics of IL-2 and IL-15

We describe a de novo computational approach for designing proteins that recapitulate the binding sites of natural cytokines, but are otherwise unrelated in topology or amino acid sequence. We use this strategy to design mimics of the central immune cytokine interleukin-2 (IL-2) that bind to the IL-2 receptor βγc heterodimer (IL-2Rβγc) but have no binding site for IL-2Rα (also called CD25) or IL-15Rα (also known as CD215). The designs are hyper-stable, bind human and mouse IL-2Rβγc with higher affinity than the natural cytokines, and elicit downstream cell signalling independently of IL-2Rα and IL-15Rα. Crystal structures of the optimized design neoleukin-2/15 (Neo-2/15), both alone and in complex with IL-2Rβγc, are very similar to the designed model. Neo-2/15 has superior therapeutic activity to IL-2 in mouse models of melanoma and colon cancer, with reduced toxicity and undetectable immunogenicity. Our strategy for building hyper-stable de novo mimetics could be applied generally to signalling proteins, enabling the creation of superior therapeutic candidates.

An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes

We propose a new iterative screening contest method to identify target protein inhibitors. After conducting a compound screening contest in 2014, we report results acquired from a contest held in 2015 in this study. Our aims were to identify target enzyme inhibitors and to benchmark a variety of computer-aided drug discovery methods under identical experimental conditions. In both contests, we employed the tyrosine-protein kinase Yes as an example target protein. Participating groups virtually screened possible inhibitors from a library containing 2.4 million compounds. Compounds were ranked based on functional scores obtained using their respective methods, and the top 181 compounds from each group were selected. Our results from the 2015 contest show an improved hit rate when compared to results from the 2014 contest. In addition, we have successfully identified a statistically-warranted method for identifying target inhibitors. Quantitative analysis of the most successful method gave additional insights into important characteristics of the method used.

Rules for connectivity of secondary structure elements in protein: Two-layer αβ sandwiches

In protein structures, the fold is described according to the spatial arrangement of secondary structure elements (SSEs: α-helices and β-strands) and their connectivity. The connectivity or the pattern of links among SSEs is one of the most important factors for understanding the variety of protein folds. In this study, we introduced the connectivity strings that encode the connectivities by using the types, positions, and connections of SSEs, and computationally enumerated all the connectivities of two-layer αβ sandwiches. The calculated connectivities were compared with those in natural proteins determined using MICAN, a nonsequential structure comparison method. For 2α-4β, among 23,000 of all connectivities, only 48 were free from irregular connectivities such as loop crossing. Of these, only 20 were found in natural proteins and the superfamilies were biased toward certain types of connectivities. A similar disproportional distribution was confirmed for most of other spatial arrangements of SSEs in the two-layer αβ sandwiches. We found two connectivity rules that explain the bias well: the abundances of interlayer connecting loops that bridge SSEs in the distinct layers; and nonlocal β-strand pairs, two spatially adjacent β-strands located at discontinuous positions in the amino acid sequence. A two-dimensional plot of these two properties indicated that the two connectivity rules are not independent, which may be interpreted as a rule for the cooperativity of proteins.

Cooperativity and modularity in protein folding

A simple statistical mechanical model proposed by Wako and Saitô has explained the aspects of protein folding surprisingly well. This model was systematically applied to multiple proteins by Muñoz and Eaton and has since been referred to as the Wako-Saitô-Muñoz-Eaton (WSME) model. The success of the WSME model in explaining the folding of many proteins has verified the hypothesis that the folding is dominated by native interactions, which makes the energy landscape globally biased toward native conformation. Using the WSME and other related models, Saitô emphasized the importance of the hierarchical pathway in protein folding; folding starts with the creation of contiguous segments having a native-like configuration and proceeds as growth and coalescence of these segments. The Φ-values calculated for barnase with the WSME model suggested that segments contributing to the folding nucleus are similar to the structural modules defined by the pattern of native atomic contacts. The WSME model was extended to explain folding of multi-domain proteins having a complex topology, which opened the way to comprehensively understanding the folding process of multi-domain proteins. The WSME model was also extended to describe allosteric transitions, indicating that the allosteric structural movement does not occur as a deterministic sequential change between two conformations but as a stochastic diffusive motion over the dynamically changing energy landscape. Statistical mechanical viewpoint on folding, as highlighted by the WSME model, has been renovated in the context of modern methods and ideas, and will continue to provide insights on equilibrium and dynamical features of proteins.

Landscape of protein-small ligand binding modes

Elucidating the mechanisms of specific small-molecule (ligand) recognition by proteins is a long-standing conundrum. While the structures of these molecules, proteins and ligands, have been extensively studied, protein-ligand interactions, or binding modes, have not been comprehensively analyzed. Although methods for assessing similarities of binding site structures have been extensively developed, the methods for the computational treatment of binding modes have not been well established. Here, we developed a computational method for encoding the information about binding modes as graphs, and assessing their similarities. An all-against-all comparison of 20,040 protein-ligand complexes provided the landscape of the protein-ligand binding modes and its relationships with protein- and chemical spaces. While similar proteins in the same SCOP Family tend to bind relatively similar ligands with similar binding modes, the correlation between ligand and binding similarities was not very high (R(2)  = 0.443). We found many pairs with novel relationships, in which two evolutionally distant proteins recognize dissimilar ligands by similar binding modes (757,474 pairs out of 200,790,780 pairs were categorized into this relationship, in our dataset). In addition, there were an abundance of pairs of homologous proteins binding to similar ligands with different binding modes (68,217 pairs). Our results showed that many interesting relationships between protein-ligand complexes are still hidden in the structure database, and our new method for assessing binding mode similarities is effective to find them.

Importance of consensus region of multiple-ligand templates in a virtual screening method

We discuss methods and ideas of virtual screening (VS) for drug discovery by examining the performance of VS-APPLE, a recently developed VS method, which extensively utilizes the tendency of single binding pockets to bind diversely different ligands, i.e. promiscuity of binding pockets. In VS-APPLE, multiple ligands bound to a pocket are spatially arranged by maximizing structural overlap of the protein while keeping their relative position and orientation with respect to the pocket surface, which are then combined into a multiple-ligand template for screening test compounds. To greatly reduce the computational cost, comparison of test compound structures are made only with limited regions of the multiple-ligand template. Even when we use the narrow regions with most densely populated atoms for the comparison, VSAPPLE outperforms other conventional VS methods in terms of Area Under the Curve (AUC) measure. This region with densely populated atoms corresponds to the consensus region among multiple ligands. It is typically observed that expansion of the sampled region including more atoms improves screening efficiency. However, for some target proteins, considering only a small consensus region is enough for the effective screening of test compounds. These results suggest that the performance test of VS methods sheds light on the mechanisms of protein-ligand interactions, and elucidation of the protein-ligand interactions should further help improvement of VS methods.

De novo design of protein homo-oligomers with modular hydrogen-bond network-mediated specificity

In nature, structural specificity in DNA and proteins is encoded differently: In DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here, we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen-bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen-bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen-bond networks with atomic accuracy enables the programming of protein interaction specificity for a broad range of synthetic biology applications; more generally, our results demonstrate that, even with the tremendous diversity observed in nature, there are fundamentally new modes of interaction to be discovered in proteins.

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of four-fold symmetrical (β/α)8 barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of side chain-backbone hydrogen bonds for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical to that of the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has sampled only a subset of the sequence space available to the TIM-barrel fold. The ability to design TIM barrels de novo opens new possibilities for custom-made enzymes.

Fast and accurate non-sequential protein structure alignment using a new asymmetric linear sum assignment heuristic

MOTIVATION

The three dimensional tertiary structure of a protein at near atomic level resolution provides insight alluding to its function and evolution. As protein structure decides its functionality, similarity in structure usually implies similarity in function. As such, structure alignment techniques are often useful in the classifications of protein function. Given the rapidly growing rate of new, experimentally determined structures being made available from repositories such as the Protein Data Bank, fast and accurate computational structure comparison tools are required. This paper presents SPalignNS, a non-sequential protein structure alignment tool using a novel asymmetrical greedy search technique.

RESULTS

The performance of SPalignNS was evaluated against existing sequential and non-sequential structure alignment methods by performing trials with commonly used datasets. These benchmark datasets used to gauge alignment accuracy include (i) 9538 pairwise alignments implied by the HOMSTRAD database of homologous proteins; (ii) a subset of 64 difficult alignments from set (i) that have low structure similarity; (iii) 199 pairwise alignments of proteins with similar structure but different topology; and (iv) a subset of 20 pairwise alignments from the RIPC set. SPalignNS is shown to achieve greater alignment accuracy (lower or comparable root-mean squared distance with increased structure overlap coverage) for all datasets, and the highest agreement with reference alignments from the challenging dataset (iv) above, when compared with both sequentially constrained alignments and other non-sequential alignments.

AVAILABILITY AND IMPLEMENTATION

SPalignNS was implemented in C++. The source code, binary executable, and a web server version is freely available at: http://sparks-lab.org

CONTACT

yaoqi.zhou@griffith.edu.au.

Amplitude spectrum distance: measuring the global shape divergence of protein fragments

Background

In structural bioinformatics, there is an increasing interest in identifying and understanding the evolution of local protein structures regarded as key structural or functional protein building blocks. A central need is then to compare these, possibly short, fragments by measuring efficiently and accurately their (dis)similarity. Progress towards this goal has given rise to scores enabling to assess the strong similarity of fragments. Yet, there is still a lack of more progressive scores, with meaningful intermediate values, for the comparison, retrieval or clustering of distantly related fragments.

Results

We introduce here the Amplitude Spectrum Distance (ASD), a novel way of comparing protein fragments based on the discrete Fourier transform of their C_α distance matrix. Defined as the distance between their amplitude spectra, ASD can be computed efficiently and provides a parameter-free measure of the global shape dissimilarity of two fragments. ASD inherits from nice theoretical properties, making it tolerant to shifts, insertions, deletions, circular permutations or sequence reversals while satisfying the triangle inequality. The practical interest of ASD with respect to RMSD, RMSD_d, BC and TM scores is illustrated through zinc finger retrieval experiments and concrete structure examples. The benefits of ASD are also illustrated by two additional clustering experiments: domain linkers fragments and complementarity-determining regions of antibodies.

Conclusions

Taking advantage of the Fourier transform to compare fragments at a global shape level, ASD is an objective and progressive measure taking into account the whole fragments. Its practical computation time and its properties make ASD particularly relevant for applications requiring meaningful measures on distantly related protein fragments, such as similar fragments retrieval asking for high recalls as shown in the experiments, or for any application taking also advantage of triangle inequality, such as fragments clustering.

ASD program and source code are freely available at: http://www.irisa.fr/dyliss/public/ASD/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0693-y) contains supplementary material, which is available to authorized users.

The Representation and Parametrization of Orthogonal Matrices

Four representations and parametrizations of orthogonal matrices Q ∈ R(m×n) in terms of the minimal number of essential parameters {φ} are discussed: the exponential representation, the Householder reflector representation, the Givens rotation representation, and the rational Cayley transform representation. Both square n = m and rectangular n < m situations are considered. Two separate kinds of parametrizations are considered: one in which the individual columns of Q are distinct, the Stiefel manifold, and the other in which only span(Q) is significant, the Grassmann manifold. The practical issues of numerical stability, continuity, and uniqueness are discussed. The computation of Q in terms of the essential parameters {φ}, and also the extraction of {φ} for a given Q are considered for all of the parametrizations. The transformation of gradient arrays between the Q and {φ} variables is discussed for all representations. It is our hope that developers of new methods will benefit from this comparative presentation of an important but rarely analyzed subject.

PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs

PoSSuM (http://possum.cbrc.jp/PoSSuM/) is a database for detecting similar small-molecule binding sites on proteins. Since its initial release in 2011, PoSSuM has grown to provide information related to 49 million pairs of similar binding sites discovered among 5.5 million known and putative binding sites. This enlargement of the database is expected to enhance opportunities for biological and pharmaceutical applications, such as predictions of new functions and drug discovery. In this release, we have provided a new service named PoSSuM drug search (PoSSuMds) at http://possum.cbrc.jp/PoSSuM/drug_search/, in which we selected 194 approved drug compounds retrieved from ChEMBL, and detected their known binding pockets and pockets that are similar to them. Users can access and download all of the search results via a new web interface, which is useful for finding ligand analogs as well as potential target proteins. Furthermore, PoSSuMds enables users to explore the binding pocket universe within PoSSuM. Additionally, we have improved the web interface with new functions, including sortable tables and a viewer for visualizing and downloading superimposed pockets.

How a spatial arrangement of secondary structure elements is dispersed in the universe of protein folds

It has been known that topologically different proteins of the same class sometimes share the same spatial arrangement of secondary structure elements (SSEs). However, the frequency by which topologically different structures share the same spatial arrangement of SSEs is unclear. It is important to estimate this frequency because it provides both a deeper understanding of the geometry of protein folds and a valuable suggestion for predicting protein structures with novel folds. Here we clarified the frequency with which protein folds share the same SSE packing arrangement with other folds, the types of spatial arrangement of SSEs that are frequently observed across different folds, and the diversity of protein folds that share the same spatial arrangement of SSEs with a given fold, using a protein structure alignment program MICAN, which we have been developing. By performing comprehensive structural comparison of SCOP fold representatives, we found that approximately 80% of protein folds share the same spatial arrangement of SSEs with other folds. We also observed that many protein pairs that share the same spatial arrangement of SSEs belong to the different classes, often with an opposing N- to C-terminal direction of the polypeptide chain. The most frequently observed spatial arrangement of SSEs was the 2-layer α/β packing arrangement and it was dispersed among as many as 27% of SCOP fold representatives. These results suggest that the same spatial arrangements of SSEs are adopted by a wide variety of different folds and that the spatial arrangement of SSEs is highly robust against the N- to C-terminal direction of the polypeptide chain.

Exploring protein domain organization by recognition of secondary structure packing interfaces

MOTIVATION

Protein domains are fundamental units of protein structure, function and evolution; thus, it is critical to gain a deep understanding of protein domain organization. Previous works have attempted to identify key residues involved in organization of domain architecture. Because one of the most important characteristics of domain architecture is the arrangement of secondary structure elements (SSEs), here we present a picture of domain organization through an integrated consideration of SSE arrangements and residue contact networks.

RESULTS

In this work, by representing SSEs as main-chain scaffolds and side-chain interfaces and through construction of residue contact networks, we have identified the SSE interfaces well packed within protein domains as SSE packing clusters. In total, 17 334 SSE packing clusters were recognized from 9015 Structural Classification of Proteins domains of <40% sequence identity. The similar SSE packing clusters were observed not only among domains of the same folds, but also among domains of different folds, indicating their roles as common scaffolds for organization of protein domains. Further analysis of 14 small single-domain proteins reveals a high correlation between the SSE packing clusters and the folding nuclei. Consistent with their important roles in domain organization, SSE packing clusters were found to be more conserved than other regions within the same proteins.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA

Searching for similar 3D protein structures is one of the primary processes employed in the field of structural bioinformatics. However, the computational complexity of this process means that it is constantly necessary to search for new methods that can perform such a process faster and more efficiently. Finding molecular substructures that complex protein structures have in common is still a challenging task, especially when entire databases containing tens or even hundreds of thousands of protein structures must be scanned. Graphics processing units (GPUs) and general purpose graphics processing units (GPGPUs) can perform many time-consuming and computationally demanding processes much more quickly than a classical CPU can. In this paper, we describe the GPU-based implementation of the CASSERT algorithm for 3D protein structure similarity searching. This algorithm is based on the two-phase alignment of protein structures when matching fragments of the compared proteins. The GPU (GeForce GTX 560Ti: 384 cores, 2GB RAM) implementation of CASSERT (“GPU-CASSERT”) parallelizes both alignment phases and yields an average 180-fold increase in speed over its CPU-based, single-core implementation on an Intel Xeon E5620 (2.40GHz, 4 cores). In this paper, we show that massive parallelization of the 3D structure similarity search process on many-core GPU devices can reduce the execution time of the process, allowing it to be performed in real time. GPU-CASSERT is available at: http://zti.polsl.pl/dmrozek/science/gpucassert/cassert.htm.