Structural genomics and the Protein Data Bank.

The field of Structural Genomics arose over the last 3 decades to address a large and rapidly growing divergence between microbial genomic, functional, and structural data. Several international programs took advantage of the vast genomic sequence information and evaluated the feasibility of structure determination for expanded and newly discovered protein families. As a consequence, structural genomics has developed structure-determination pipelines and applied them to a wide range of novel, uncharacterized proteins, often from "microbial dark matter," and later to proteins from human pathogens. Advances were especially needed in protein production and rapid de novo structure solution. The experimental three-dimensional models were promptly made public, facilitating structure determination of other members of the family and helping to understand their molecular and biochemical functions. Improvements in experimental methods and databases resulted in fast progress in molecular and structural biology. The Protein Data Bank structure repository played a central role in the coordination of structural genomics efforts and the structural biology community as a whole. It facilitated development of standards and validation tools essential for maintaining high quality of deposited structural data.

How the Protein Data Bank changed biology: An introduction to the JBC Reviews thematic series, part 2.

In part 1 of this remarkable collection, we told you the story of The Protein Data Bank (PDB) (1), which was founded 50 years ago, and we illustrated the breadth of the science contained within it with ten informative review articles. The second half of this collection is a continuation of our celebrations to mark this momentous anniversary. Part 2 provides eight more superb articles describing how the PDB has influenced biology over the course of the last half-century and how biology has fueled the deposition of impactful structures in the PDB. Here are some brief synopses of the articles you will enjoy in part 2!

A review on structural genomics approach applied for drug discovery against three vector-borne viral diseases: Dengue, Chikungunya and Zika.

Structural genomics involves the advent of three-dimensional structures of the genome encoded proteins through various techniques available. Numerous structural genomics research groups have been developed across the globe and they contribute enormously to the identification of three-dimensional structures of various proteins. In this review, we have discussed the applications of the structural genomics approach towards the discovery of potential lead-like molecules against the genomic drug targets of three vector-borne diseases, namely, Dengue, Chikungunya and Zika. Currently, all these three diseases are associated with the most important global public health problems and significant economic burden in tropical countries. Structural genomics has accelerated the identification of novel drug targets and inhibitors for the treatment of these diseases. We start with the current development status of the drug targets and antiviral drugs against these three diseases and conclude by describing challenges that need to be addressed to overcome the shortcomings in the process of drug discovery.

Computational modelling of flavivirus dynamics: The ins and outs.

Enveloped viruses such as the flaviviruses represent a significant burden to human health around the world, with hundreds of millions of people each year affected by dengue alone. In an effort to improve our understanding of the molecular basis for the infective mechanisms of these viruses, extensive computational modelling approaches have been applied to elucidate their conformational dynamics. Multiscale protocols have been developed to simulate flavivirus envelopes in close accordance with biophysical data, in particular derived from cryo-electron microscopy, enabling high-resolution refinement of their structures and elucidation of the conformational changes associated with adaptation both to host environments and to immunological factors such as antibodies. Likewise, integrative modelling efforts combining data from biophysical experiments and from genome sequencing with chemical modification are providing unparalleled insights into the architecture of the previously unresolved nucleocapsid complex. Collectively, this work provides the basis for the future rational design of new antiviral therapeutics and vaccine development strategies targeting enveloped viruses.

Computational Structural Genomics Unravels Common Folds and Novel Families in the Secretome of Fungal Phytopathogen Magnaporthe oryzae.

Structural biology has the potential to illuminate the evolution of pathogen effectors and their commonalities that cannot be readily detected at the primary sequence level. Recent breakthroughs in protein structure modeling have demonstrated the feasibility to predict the protein folds without depending on homologous templates. These advances enabled a genome-wide computational structural biology approach to help understand proteins based on their predicted folds. In this study, we employed structure prediction methods on the secretome of the destructive fungal pathogen Magnaporthe oryzae. Out of 1,854 secreted proteins, we predicted the folds of 1,295 proteins (70%). We showed that template-free modeling by TrRosetta captured 514 folds missed by homology modeling, including many known effectors and virulence factors, and that TrRosetta generally produced higher quality models for secreted proteins. Along with sensitive homology search, we employed structure-based clustering, defining not only homologous groups with divergent members but also sequence-unrelated structurally analogous groups. We demonstrate that this approach can reveal new putative members of structurally similar MAX effectors and novel analogous effector families present in M. oryzae and possibly in other phytopathogens. We also investigated the evolution of expanded putative ADP-ribose transferases with predicted structures. We suggest that the loss of catalytic activities of the enzymes might have led them to new evolutionary trajectories to be specialized as protein binders. Collectively, we propose that computational structural genomics approaches can be an integral part of studying effector biology and provide valuable resources that were inaccessible before the advent of machine learning-based structure prediction.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Impact of single amino acid substitution on the structure and function of TANK-binding kinase-1.

Tank-binding kinase 1 (TBK1) is a serine/threonine protein kinase involved in various signaling pathways and subsequently regulates cell proliferation, apoptosis, autophagy, antiviral and antitumor immunity. Dysfunction of TBK1 can cause many complex diseases, including autoimmunity, neurodegeneration, and cancer. This dysfunction of TBK1 may result from single amino acid substitutions and subsequent structural alterations. This study analyzed the effect of substituting amino acids on TBK1 structure, function, and subsequent disease using advanced computational methods and various tools. In the initial assessment, a total of 467 mutations were found to be deleterious. After that, in detailed structural and sequential analyses, 13 mutations were found to be pathogenic. Finally, based on the functional importance, two variants (K38D and S172A) of the TBK1 kinase domain were selected and studied in detail by utilizing all-atom molecular dynamics (MD) simulation for 200 ns. MD simulation, including correlation matrix and principal component analysis, helps to get deeper insights into the TBK1 structure at the atomic level. We observed a substantial change in variants' conformation, which may be possible for structural alteration and subsequent TBK1 dysfunction. However, substitution S172A shows a significant conformational change in TBK1 structure as compared to K38D. Thus, this study provides a structural basis to understand the effect of mutations on the kinase domain of TBK1 and its function associated with disease progression.

Structural-genetic insight and optimization of protease production from a novel strain of Aeromonas veronii CMF, a gut isolate of Chrysomya megacephala.

Structural-genetic characterization of protease producing genes and enzymes from microbial sources are seldom appreciated despite having its substantial utilization in protein engineering or genetic manipulation for biotechnological applications. Aeromonas veronii CMF, a mesophilic bacterium isolated from the gut of Chrysomya megacephala, was found to exhibited significant level of protease activity. For the revelation of genetic potential in relation to protease production, whole genome of this organism was sequenced and analysed while structure-function of different protease enzyme was predicated using various in silico analysis. The 4.5 mb CMF genome was found to encompass various types of protease and mostly they are neutral in nature. Enzyme production was highest in an optimum pH and temperature of 6.0 (32.09 ± 1.015 U/ml) and 35ºC (41.65 ± 1.152 U/ml), respectively. Other culture parameters for optimum production of protease were determined to be inoculum size (1%), incubation period (72 h), shaking condition (125 rpm), carbon and nitrogen source [2% lactose (92.21 ± 3.16 U/ml) and 0.5% urea (163.62 ± 4.31 U/ml), respectively] and effect of surfactants [0.02 mg/ml Tween 80 (174.72 ± 4.48 U/ml)]. Furthermore, A. veronii CMF exhibited significant enzyme production like serine protease (15.22 ± 0.563 U/ml), aspartate protease (33.16 ± 0.762 U/ml) and collagenase (17.26 ± 0.626 U/ml). Genomic information and results of physio-biochemical assays indicate its cost-effective potential use in different enzyme-industry.

Anticipating innovations in structural biology.

In this review, we describe how the interplay among science, technology and community interests contributed to the evolution of four structural biology data resources. We present the method by which data deposited by scientists are prepared for worldwide distribution, and argue that data archiving in a trusted repository must be an integral part of any scientific investigation.

A Tale of Two Families: Whole Genome and Segmental Duplications Underlie Glutamine Synthetase and Phosphoenolpyruvate Carboxylase Diversity in Narrow-Leafed Lupin (Lupinus angustifolius L.).

Narrow-leafed lupin (Lupinus angustifolius L.) has recently been supplied with advanced genomic resources and, as such, has become a well-known model for molecular evolutionary studies within the legume family-a group of plants able to fix nitrogen from the atmosphere. The phylogenetic position of lupins in Papilionoideae and their evolutionary distance to other higher plants facilitates the use of this model species to improve our knowledge on genes involved in nitrogen assimilation and primary metabolism, providing novel contributions to our understanding of the evolutionary history of legumes. In this study, we present a complex characterization of two narrow-leafed lupin gene families-glutamine synthetase (GS) and phosphoenolpyruvate carboxylase (PEPC). We combine a comparative analysis of gene structures and a synteny-based approach with phylogenetic reconstruction and reconciliation of the gene family and species history in order to examine events underlying the extant diversity of both families. Employing the available evidence, we show the impact of duplications on the initial complement of the analyzed gene families within the genistoid clade and posit that the function of duplicates has been largely retained. In terms of a broader perspective, our results concerning GS and PEPC gene families corroborate earlier findings pointing to key whole genome duplication/triplication event(s) affecting the genistoid lineage.

The crystal structure of Rv2991 from Mycobacterium tuberculosis: An F420 binding protein with unknown function.

The crystal structure of the conserved hypothetical protein Rv2991 from Mycobacterium tuberculosis has been solved by SAD using seleno-methionine substituted protein. The dimeric biological assembly and the sequence and fold conservation are typical of F420 cofactor binding enzymes. Despite Rv2991 still being of unknown function, sequence and structural comparison with similar proteins enable a role to be proposed for its C-terminal stretch of residues in recognizing and orienting the substrate. In addition, the C-terminus is involved in both protein folding and determining the size of the active site cavity.

Effects of Pro1266Leu mutation on structure and function of glycoprotein Ib binding domain of von Willebrand factor.

Glycoprotein Ibα (GpIbα) binding ability of A1 domain of von Willebrand factor (vWF) facilitates platelet adhesion that plays a crucial role in maintaining hemostasis and thrombosis at the site of vascular damage. There are both "loss as well as gain of function" mutations observed in this domain. Naturally occurring "gain of function" mutations leave self-activating impacts on the A1 domain which turns the normal binding to characteristic constitutive binding with GPIbα. These "gain of function" mutations are associated with the von Willebrand disease type 2B. In recent years, studies focused on understanding the mechanism and conformational patterns attached to these phenomena have been conducted, but the conformational pathways leading to such binding patterns are poorly understood as of now. To obtain a microscopic picture of such events for the better understanding of pathways, we used molecular dynamics (MD) simulations along with principal component analysis and normal mode analysis to study the effects of Pro1266Leu (Pro503Leu in structural context) mutation on the structure and function of A1 domain of vWF. MD simulations have provided atomic-level details of intermolecular motions as a function of time to understand the dynamic behavior of A1 domain of vWF. Comparative analysis of the trajectories obtained from MD simulations of both the wild type and Pro503Leu mutant suggesting appreciable conformational changes in the structure of mutant which might provide a basis for assuming the "gain of function" effects of these mutations on the A1 domain of vWF, resulting in the constitutive binding with GpIbα.

Investigation of deleterious effects of nsSNPs in the POT1 gene: a structural genomics-based approach to understand the mechanism of cancer development.

Protection of telomere 1 (POT1) is one of the key components of shelterin complex, implicated in maintaining the telomere homeostasis, and thus stability of the eukaryotic genome. A large number of non-synonymous single nucleotide polymorphisms (nsSNPs) in the POT1 gene have been reported to cause varieties of human diseases, including cancer. In recent years, a number of mutations in POT1 has been markedly increased, and interpreting the effect of these large numbers of mutations to understand the mechanism of associated diseases seems impossible using experimental approaches. Herein, we employ varieties of computational methods such as PROVEAN, PolyPhen-2, SIFT, PoPMuSiC, SDM2, STRUM, and MAESTRO to identify the effects of 387 nsSNPs on the structure and function of POT1 protein. We have identified about 183 nsSNPs as deleterious and termed them as "high-confidence nsSNPs." Distribution of these high-confidence nsSNPs demonstrates that the mutation in oligonucleotide binding domain 1 is highly deleterious (one in every three nsSNPs), and high-confidence nsSNPs show a strong correlation with residue conservation. The structure analysis provides a detailed insights into the structural changes occurred in consequence of conserved mutations which lead to the cancer progression. This study, for the first time, offers a newer prospective on the role of POT1 mutations on the structure, function, and their relation to associated diseases.

fDETECT webserver: fast predictor of propensity for protein production, purification, and crystallization.

BACKGROUND: Development of predictors of propensity of protein sequences for successful crystallization has been actively pursued for over a decade. A few novel methods that expanded the scope of these predictions to address additional steps of protein production and structure determination pipelines were released in recent years. The predictive performance of the current methods is modest. This is because the only input that they use is the protein sequence and since the experimental annotations of these data might be inconsistent given that they were collected across many laboratories and centers. However, even these modest levels of predictive quality are still practical compared to the reported low success rates of crystallization, which are below 10%. We focus on another important aspect related to a high computational cost of running the predictors that offer the expanded scope. RESULTS: We introduce a novel fDETECT webserver that provides very fast and modestly accurate predictions of the success of protein production, purification, crystallization, and structure determination. Empirical tests on two datasets demonstrate that fDETECT is more accurate than the only other similarly fast method, and similarly accurate and three orders of magnitude faster than the currently most accurate predictors. Our method predicts a single protein in about 120 milliseconds and needs less than an hour to generate the four predictions for an entire human proteome. Moreover, we empirically show that fDETECT secures similar levels of predictive performance when compared with four representative methods that only predict success of crystallization, while it also provides the other three predictions. A webserver that implements fDETECT is available at http://biomine.cs.vcu.edu/servers/fDETECT/ . CONCLUSIONS: fDETECT is a computational tool that supports target selection for protein production and X-ray crystallography-based structure determination. It offers predictive quality that matches or exceeds other state-of-the-art tools and is especially suitable for the analysis of large protein sets.

Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes.

Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of >10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its advances is urgently needed. Here, we first summarize the main features of these methods and tools for whole-exome, whole-genome and whole-transcriptome sequencing data. Then, we discuss major challenges like tumor intra-heterogeneity, tumor sample saturation and functionality of synonymous mutations in cancer, all of which may result in false-positive discoveries. Finally, we highlight new directions in studying regulatory roles of noncoding somatic mutations and quantitatively measuring circulating tumor DNA in cancer. This review may help investigators find an appropriate tool for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine.

The NMR solution structure and function of RPA3313: a putative ribosomal transport protein from Rhodopseudomonas palustris.

Protein function elucidation often relies heavily on amino acid sequence analysis and other bioinformatics approaches. The reliance is extended to structure homology modeling for ligand docking and protein-protein interaction mapping. However, sequence analysis of RPA3313 exposes a large, unannotated class of hypothetical proteins mostly from the Rhizobiales order. In the absence of sequence and structure information, further functional elucidation of this class of proteins has been significantly hindered. A high quality NMR structure of RPA3313 reveals that the protein forms a novel split ßßαß fold with a conserved ligand binding pocket between the first ß-strand and the N-terminus of the α-helix. Conserved residue analysis and protein-protein interaction prediction analyses reveal multiple protein binding sites and conserved functional residues. Results of a mass spectrometry proteomic analysis strongly point toward interaction with the ribosome and its subunits. The combined structural and proteomic analyses suggest that RPA3313 by itself or in a larger complex may assist in the transportation of substrates to or from the ribosome for further processing. Proteins 2016; 85:93-102. © 2016 Wiley Periodicals, Inc.

The impact of structural genomics: the first quindecennial.

The period 2000-2015 brought the advent of high-throughput approaches to protein structure determination. With the overall funding on the order of $2 billion (in 2010 dollars), the structural genomics (SG) consortia established worldwide have developed pipelines for target selection, protein production, sample preparation, crystallization, and structure determination by X-ray crystallography and NMR. These efforts resulted in the determination of over 13,500 protein structures, mostly from unique protein families, and increased the structural coverage of the expanding protein universe. SG programs contributed over 4400 publications to the scientific literature. The NIH-funded Protein Structure Initiatives alone have produced over 2000 scientific publications, which to date have attracted more than 93,000 citations. Software and database developments that were necessary to handle high-throughput structure determination workflows have led to structures of better quality and improved integrity of the associated data. Organized and accessible data have a positive impact on the reproducibility of scientific experiments. Most of the experimental data generated by the SG centers are freely available to the community and has been utilized by scientists in various fields of research. SG projects have created, improved, streamlined, and validated many protocols for protein production and crystallization, data collection, and functional analysis, significantly benefiting biological and biomedical research.

Structure and functional characterization of a bile acid 7α dehydratase BaiE in secondary bile acid synthesis.

Conversion of the primary bile acids cholic acid (CA) and chenodeoxycholic acid (CDCA) to the secondary bile acids deoxycholic acid (DCA) and lithocholic acid (LCA) is performed by a few species of intestinal bacteria in the genus Clostridium through a multistep biochemical pathway that removes a 7α-hydroxyl group. The rate-determining enzyme in this pathway is bile acid 7α-dehydratase (baiE). In this study, crystal structures of apo-BaiE and its putative product-bound [3-oxo-Δ(4,6) -lithocholyl-Coenzyme A (CoA)] complex are reported. BaiE is a trimer with a twisted α + ß barrel fold with similarity to the Nuclear Transport Factor 2 (NTF2) superfamily. Tyr30, Asp35, and His83 form a catalytic triad that is conserved across this family. Site-directed mutagenesis of BaiE from Clostridium scindens VPI 12708 confirm that these residues are essential for catalysis and also the importance of other conserved residues, Tyr54 and Arg146, which are involved in substrate binding and affect catalytic turnover. Steady-state kinetic studies reveal that the BaiE homologs are able to turn over 3-oxo-Δ(4) -bile acid and CoA-conjugated 3-oxo-Δ(4) -bile acid substrates with comparable efficiency questioning the role of CoA-conjugation in the bile acid metabolism pathway.

Structural organization of fatty acid desaturase loci in linseed lines with contrasting linolenic acid contents.

Flax (Linum usitatissimum L.), the richest crop source of omega-3 fatty acids (FAs), is a diploid plant with an estimated genome size of ~370 Mb and is well suited for studying genomic organization of agronomically important traits. In this study, 12 bacterial artificial chromosome clones harbouring the six FA desaturase loci sad1, sad2, fad2a, fad2b, fad3a and fad3b from the conventional variety CDC Bethune and the high linolenic acid line M5791 were sequenced, analysed and compared to determine the structural organization of these loci and to gain insights into the genetic mechanisms underlying FA composition in flax. With one gene every 3.2-4.6 kb, the desaturase loci have a higher gene density than the genome's average of one gene per 7.8-8.2 kb. The gene order and orientation across the two genotypes were generally conserved with the exception of the sad1 locus that was predicted to have additional genes in CDC Bethune. High sequence conservation in both genic and intergenic regions of the sad and fad2b loci contrasted with the significant level of variation of the fad2a and fad3 loci, with SNPs being the most frequently observed mutation type. The fad2a locus had 297 SNPs and 36 indels over ~95 kb contrasting with the fad2b locus that had a mere seven SNPs and four indels in ~110 kb. Annotation of the gene-rich loci revealed other genes of known role in lipid or carbohydrate metabolic/catabolic pathways. The organization of the fad2b locus was particularly complex with seven copies of the fad2b gene in both genotypes. The presence of Gypsy, Copia, MITE, Mutator, hAT and other novel repeat elements at the desaturase loci was similar to that of the whole genome. This structural genomic analysis provided some insights into the genomic organization and composition of the main desaturase loci of linseed and of their complex evolution through both tandem and whole genome duplications.

Organophosphonate-degrading PhnZ reveals an emerging family of HD domain mixed-valent diiron oxygenases.

The founding members of the HD-domain protein superfamily are phosphohydrolases, and newly discovered members are generally annotated as such. However, myo-inositol oxygenase (MIOX) exemplifies a second, very different function that has evolved within the common scaffold of this superfamily. A recently discovered HD protein, PhnZ, catalyzes conversion of 2-amino-1-hydroxyethylphosphonate to glycine and phosphate, culminating a bacterial pathway for the utilization of environmentally abundant 2-aminoethylphosphonate. Using Mössbauer and EPR spectroscopies, X-ray crystallography, and activity measurements, we show here that, like MIOX, PhnZ employs a mixed-valent Fe(II)/Fe(III) cofactor for the O2-dependent oxidative cleavage of its substrate. Phylogenetic analysis suggests that many more HD proteins may catalyze yet-unknown oxygenation reactions using this hitherto exceptional Fe(II)/Fe(III) cofactor. The results demonstrate that the catalytic repertoire of the HD superfamily extends well beyond phosphohydrolysis and suggest that the mechanism used by MIOX and PhnZ may be a common strategy for oxidative C-X bond cleavage.

Structure of a cupin protein Plu4264 from Photorhabdus luminescens subsp. laumondii TTO1 at 1.35 Å resolution.

Proteins belonging to the cupin superfamily have a wide range of catalytic and noncatalytic functions. Cupin proteins commonly have the capacity to bind a metal ion with the metal frequently determining the function of the protein. We have been investigating the function of homologous cupin proteins that are conserved in more than 40 species of bacteria. To gain insights into the potential function of these proteins we have solved the structure of Plu4264 from Photorhabdus luminescens TTO1 at a resolution of 1.35 Å and identified manganese as the likely natural metal ligand of the protein.