Optimal simultaneous superpositioning of multiple structures with missing data

Explaining Conformational Diversity in Protein Families through Molecular Motions

Proteins play a central role in biological processes, and understanding their conformational variability is crucial for unraveling their functional mechanisms. Recent advancements in high-throughput technologies have enhanced our knowledge of protein structures, yet predicting their multiple conformational states and motions remains challenging. This study introduces Dimensionality Analysis for protein Conformational Exploration (DANCE) for a systematic and comprehensive description of protein families conformational variability. DANCE accommodates both experimental and predicted structures. It is suitable for analysing anything from single proteins to superfamilies. Employing it, we clustered all experimentally resolved protein structures available in the Protein Data Bank into conformational collections and characterized them as sets of linear motions. The resource facilitates access and exploitation of the multiple states adopted by a protein and its homologs. Beyond descriptive analysis, we assessed classical dimensionality reduction techniques for sampling unseen states on a representative benchmark. This work improves our understanding of how proteins deform to perform their functions and opens ways to a standardised evaluation of methods designed to sample and generate protein conformations.

Structural insight into the ZFAND1-p97 interaction involved in stress granule clearance

Arsenite-induced stress granule (SG) formation can be cleared by the ubiquitin-proteasome system aided by the ATP-dependent unfoldase p97. ZFAND1 participates in this pathway by recruiting p97 to trigger SG clearance. ZFAND1 contains two An1-type zinc finger domains (ZF1 and ZF2), followed by a ubiquitin-like domain (UBL); but their structures are not experimentally determined. To shed light on the structural basis of the ZFAND1-p97 interaction, we determined the atomic structures of the individual domains of ZFAND1 by solution-state NMR spectroscopy and X-ray crystallography. We further characterized the interaction between ZFAND1 and p97 by methyl NMR spectroscopy and cryo-EM. 15N spin relaxation dynamics analysis indicated independent domain motions for ZF1, ZF2, and UBL. The crystal structure and NMR structure of UBL showed a conserved β-grasp fold homologous to ubiquitin and other UBLs. Nevertheless, the UBL of ZFAND1 contains an additional N-terminal helix that adopts different conformations in the crystalline and solution states. ZFAND1 uses the C-terminal UBL to bind to p97, evidenced by the pronounced line-broadening of the UBL domain during the p97 titration monitored by methyl NMR spectroscopy. ZFAND1 binding induces pronounced conformational heterogeneity in the N-terminal domain of p97, leading to a partial loss of the cryo-EM density of the N-terminal domain of p97. In conclusion, this work paved the way for a better understanding of the interplay between p97 and ZFAND1 in the context of SG clearance.

Structure prediction of linear and cyclic peptides using CABS-flex

The structural modeling of peptides can be a useful aid in the discovery of new drugs and a deeper understanding of the molecular mechanisms of life. Here we present a novel multiscale protocol for the structure prediction of linear and cyclic peptides. The protocol combines two main stages: coarse-grained simulations using the CABS-flex standalone package and an all-atom reconstruction-optimization process using the Modeller program. We evaluated the protocol on a set of linear peptides and two sets of cyclic peptides, with cyclization through the backbone and disulfide bonds. A comparison with other state-of-the-art tools (APPTEST, PEP-FOLD, ESMFold and AlphaFold implementation in ColabFold) shows that for most cases, AlphaFold offers the highest resolution. However, CABS-flex is competitive, particularly when it comes to short linear peptides. As demonstrated, the protocol performance can be further improved by combination with the residue-residue contact prediction method or more efficient scoring. The protocol is included in the CABS-flex standalone package along with online documentation to aid users in predicting the structure of peptides and mini-proteins.

Statistical Learning of Protein Elastic Network from Positional Covariance Matrix

Positional fluctuation and covariance during protein dynamics are key observables for understanding the molecular origin of biological functions. A frequently employed potential energy function for describing protein structural variation at the coarse-gained level is elastic network model (ENM). A long-standing issue in biomolecular simulation is thus the parametrization of ENM spring constants from the components of positional covariance matrix (PCM). Based on sensitivity analysis of PCM, the direct-coupling statistics of each spring, which is a specific combination of position fluctuation and covariance, is found to exhibit prominent signal of parameter dependence. This finding provides the basis for devising the objective function and the scheme of running through the effective one-dimensional optimization of every spring by self-consistent iteration. Formal derivation of the positional covariance statistical learning (PCSL) method also motivates the necessary data regularization for stable calculations. Robust convergence of PCSL is achieved in taking an all-atom molecular dynamics trajectory or an ensemble of homologous structures as input data. The PCSL framework can also be generalized with mixed objective functions to capture specific property such as the residue flexibility profile. Such physical chemistry-based statistical learning thus provides a useful platform for integrating the mechanical information encoded in various experimental or computational data.

Structural and functional mapping of ars gene cluster in Deinococcus indicus DR1

Deinococcus indicus DR1 is a novel Gram-negative bacterium, isolated from the Dadri wetlands in Uttar Pradesh, India. In addition to being radiation-resistant, the rod-shaped, red-pigmented organism shows extraordinary resistance to arsenic. The proteins of the corresponding ars gene cluster involved in arsenic extrusion in D. indicus DR1 have not yet been characterized. Additionally, how these proteins regulate each other providing arsenic resistance is still unclear. Here, we present a computational model of the operonic structure and the corresponding characterization of the six proteins of the ars gene cluster in D. indicus DR1. Additionally, we show the expression of the genes in the presence of arsenic using qRT-PCR. The ars gene cluster consists of two transcriptional regulators (ArsR1, ArsR2), two arsenate reductases (ArsC2, ArsC3), one metallophosphatase family protein (MPase), and a transmembrane arsenite efflux pump (ArsB). The transcriptional regulators are trans-acting repressors, and the reductases reduce arsenate (As⁵⁺) ions to arsenite (As³⁺) ions for favourable extrusion. The proteins modelled using RoseTTAFold, and their conformationally stable coordinates obtained after MD simulation indicate their various functional roles with respect to arsenic. Excluding ArsB, all the proteins belong to the α + β class of proteins. ArsB, being a membrane protein, is fully α-helical, with 12 transmembrane helices. The results show the degree of similarity or divergence of the mechanism utilized by these proteins of ars gene cluster in D. indicus DR1 to confer high levels of arsenic tolerance. This structural characterization study of the ars genes will enable new and deeper insights of arsenic tolerance.

Proton Coupling and the Multiscale Kinetic Mechanism of a Peptide Transporter

Proton coupled peptide transporters (POTs) are crucial for the uptake of di- and tri-peptides as well as drug and pro-drug molecules in prokaryotes and eukaryotic cells. We illustrate from multiscale modeling how transmembrane proton flux couples within a POT protein to drive essential steps of the full functional cycle: 1) protonation of a glutamate on transmembrane helix (TM) 7 opens the extracellular gate, allowing ligand entry; 2) inward proton flow induces the cytosolic release of ligand by varying the protonation state of a second conserved glutamate on TM10; 3) proton movement between TM7 and TM10 is thermodynamically driven and kinetically permissible via water proton shuttling without the participation of ligand. Our results, for the first time, give direct computational confirmation for the alternating access model of POTs, and point to a quantitative multiscale kinetic picture of the functioning protein mechanism.

Molecular insights into RNA recognition and gene regulation by the TRIM-NHL protein Mei-P26

The TRIM-NHL protein Meiotic P26 (Mei-P26) acts as a regulator of cell fate in Drosophila Its activity is critical for ovarian germline stem cell maintenance, differentiation of oocytes, and spermatogenesis. Mei-P26 functions as a post-transcriptional regulator of gene expression; however, the molecular details of how its NHL domain selectively recognizes and regulates its mRNA targets have remained elusive. Here, we present the crystal structure of the Mei-P26 NHL domain at 1.6 Å resolution and identify key amino acids that confer substrate specificity and distinguish Mei-P26 from closely related TRIM-NHL proteins. Furthermore, we identify mRNA targets of Mei-P26 in cultured Drosophila cells and show that Mei-P26 can act as either a repressor or activator of gene expression on different RNA targets. Our work reveals the molecular basis of RNA recognition by Mei-P26 and the fundamental functional differences between otherwise very similar TRIM-NHL proteins.

Wavelet invariants for statistically robust multi-reference alignment

We propose a nonlinear, wavelet-based signal representation that is translation invariant and robust to both additive noise and random dilations. Motivated by the multi-reference alignment problem and generalizations thereof, we analyze the statistical properties of this representation given a large number of independent corruptions of a target signal. We prove the nonlinear wavelet-based representation uniquely defines the power spectrum but allows for an unbiasing procedure that cannot be directly applied to the power spectrum. After unbiasing the representation to remove the effects of the additive noise and random dilations, we recover an approximation of the power spectrum by solving a convex optimization problem, and thus reduce to a phase retrieval problem. Extensive numerical experiments demonstrate the statistical robustness of this approximation procedure.

Dataset and analysis of molecular dynamics simulation of EpCAM ectodomain dimer

The data provided and described here give insight into the solution dynamics of the dimer of human EpCAM ectodomain (EpEX). As the starting point, crystal structure of EpEX non-covalent dimer was used (PDB ID 4MZV). The coordinates of solvent-embedded dimer were used to generate a topology file, which was in turn used for all-atom molecular dynamics (MD) simulation run of 20 ns length using full-system periodic electrostatics at a constant temperature of 310 K and a constant pressure of 1 atm. The MD trajectory file (part of this dataset) contains 4000 frames corresponding to recording/sampling atom positions every 5 ps. The simulation run was then analyzed in terms of root mean square deviations (RMSD) of protein atoms, and non-covalent inter-subunit interactions. The MD trajectory and analyzed data enable-in contrast to the static crystal structure-detailed analysis of solution-like protein structural dynamics and support design of EpCAM-targetting binders and structure-based analysis of EpCAM interactome.

A potent peptide-steroid conjugate accumulates in cartilage and reverses arthritis without evidence of systemic corticosteroid exposure

On-target, off-tissue toxicity limits the systemic use of drugs that would otherwise reduce symptoms or reverse the damage of arthritic diseases, leaving millions of patients in pain and with limited physical mobility. We identified cystine-dense peptides (CDPs) that rapidly accumulate in cartilage of the knees, ankles, hips, shoulders, and intervertebral discs after systemic administration. These CDPs could be used to concentrate arthritis drugs in joints. A cartilage-accumulating peptide, CDP-11R, reached peak concentration in cartilage within 30 min after administration and remained detectable for more than 4 days. Structural analysis of the peptides by crystallography revealed that the distribution of positive charge may be a distinguishing feature of joint-accumulating CDPs. In addition, quantitative whole-body autoradiography showed that the disulfide-bonded tertiary structure is critical for cartilage accumulation and retention. CDP-11R distributed to joints while carrying a fluorophore imaging agent or one of two different steroid payloads, dexamethasone (dex) and triamcinolone acetonide (TAA). Of the two payloads, the dex conjugate did not advance because the free drug released into circulation was sufficient to cause on-target toxicity. In contrast, the CDP-11R-TAA conjugate alleviated joint inflammation in the rat collagen-induced model of rheumatoid arthritis while avoiding toxicities that occurred with nontargeted steroid treatment at the same molar dose. This conjugate shows promise for clinical development and establishes proof of concept for multijoint targeting of disease-modifying therapeutic payloads.

Discovery of a hidden transient state in all bromodomain families

Bromodomains (BDs) are small protein modules that interact with acetylated marks in histones. These posttranslational modifications are pivotal to regulate gene expression, making BDs promising targets to treat several diseases. While the general structure of BDs is well known, their dynamical features and their interplay with other macromolecules are poorly understood, hampering the rational design of potent and selective inhibitors. Here, we combine extensive molecular dynamics simulations, Markov state modeling, and available structural data to reveal a transiently formed state that is conserved across all BD families. It involves the breaking of two backbone hydrogen bonds that anchor the ZA-loop with the αA helix, opening a cryptic pocket that partially occludes the one associated to histone binding. By analyzing more than 1,900 experimental structures, we unveil just two adopting the hidden state, explaining why it has been previously unnoticed and providing direct structural evidence for its existence. Our results suggest that this state is an allosteric regulatory switch for BDs, potentially related to a recently unveiled BD-DNA-binding mode.

How directed evolution reshapes the energy landscape in an enzyme to boost catalysis

The advent of biocatalysts designed computationally and optimized by laboratory evolution provides an opportunity to explore molecular strategies for augmenting catalytic function. Applying a suite of nuclear magnetic resonance, crystallography, and stopped-flow techniques to an enzyme designed for an elementary proton transfer reaction, we show how directed evolution gradually altered the conformational ensemble of the protein scaffold to populate a narrow, highly active conformational ensemble and accelerate this transformation by nearly nine orders of magnitude. Mutations acquired during optimization enabled global conformational changes, including high-energy backbone rearrangements, that cooperatively organized the catalytic base and oxyanion stabilizer, thus perfecting transition-state stabilization. The development of protein catalysts for many chemical transformations could be facilitated by explicitly sampling conformational substates during design and specifically stabilizing productive substates over all unproductive conformations.

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

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

Discovery of Human Signaling Systems: Pairing Peptides to G Protein-Coupled Receptors

The peptidergic system is the most abundant network of ligand-receptor-mediated signaling in humans. However, the physiological roles remain elusive for numerous peptides and more than 100 G protein-coupled receptors (GPCRs). Here we report the pairing of cognate peptides and receptors. Integrating comparative genomics across 313 species and bioinformatics on all protein sequences and structures of human class A GPCRs, we identify universal characteristics that uncover additional potential peptidergic signaling systems. Using three orthogonal biochemical assays, we pair 17 proposed endogenous ligands with five orphan GPCRs that are associated with diseases, including genetic, neoplastic, nervous and reproductive system disorders. We also identify additional peptides for nine receptors with recognized ligands and pathophysiological roles. This integrated computational and multifaceted experimental approach expands the peptide-GPCR network and opens the way for studies to elucidate the roles of these signaling systems in human physiology and disease.

Video Abstract

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Universal characteristics enabled prediction of peptide ligands and receptors

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Multifaceted screening enabled detection of pathway- and assay-dependent responses

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Peptide ligands discovered for BB₃, GPR1, GPR15, GPR55, and GPR68

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Each signaling system is a link to human physiology and is associated with disease

Structural evidence for a latch mechanism regulating access to the active site of SufS-family cysteine desulfurases

Cysteine serves as the sulfur source for the biosynthesis of Fe-S clusters and thio-cofactors, molecules that are required for core metabolic processes in all organisms. Therefore, cysteine desulfurases, which mobilize sulfur for its incorporation into thio-cofactors by cleaving the Cα-S bond of cysteine, are ubiquitous in nature. SufS, a type 2 cysteine desulfurase that is present in plants and microorganisms, mobilizes sulfur from cysteine to the transpersulfurase SufE to initiate Fe-S biosynthesis. Here, a 1.5 Å resolution X-ray crystal structure of the Escherichia coli SufS homodimer is reported which adopts a state in which the two monomers are rotated relative to their resting state, displacing a β-hairpin from its typical position blocking transpersulfurase access to the SufS active site. A global structure and sequence analysis of SufS family members indicates that the active-site β-hairpin is likely to require adjacent structural elements to function as a β-latch regulating access to the SufS active site.

Cinnamate-CoA ligase is involved in biosynthesis of benzoate-derived biphenyl phytoalexin in Malus × domestica 'Golden Delicious' cell cultures

Apple (Malus sp.) and other genera belonging to the sub-tribe Malinae of the Rosaceae family produce unique benzoic acid-derived biphenyl phytoalexins. Cell cultures of Malus domestica cv. 'Golden Delicious' accumulate two biphenyl phytoalexins, aucuparin and noraucuparin, in response to the addition of a Venturia inaequalis elicitor (VIE). In this study, we isolated and expressed a cinnamate-CoA ligase (CNL)-encoding sequence from VIE-treated cell cultures of cv. 'Golden Delicious' (M. domestica CNL; MdCNL). MdCNL catalyses the conversion of cinnamic acid into cinnamoyl-CoA, which is subsequently converted to biphenyls. MdCNL failed to accept benzoic acid as a substrate. When scab-resistant (cv. 'Shireen') and moderately scab-susceptible (cv. 'Golden Delicious') apple cultivars were challenged with the V. inaequalis scab fungus, an increase in MdCNL transcript levels was observed in internodal regions. The increase in MdCNL transcript levels could conceivably correlate with the pattern of accumulation of biphenyls. The C-terminal signal in the MdCNL protein directed its N-terminal reporter fusion to peroxisomes in Nicotiana benthamiana leaves. Thus, this report records the cloning and characterisation of a cinnamoyl-CoA-forming enzyme from apple via a series of in vivo and in vitro studies. Defining the key step of phytoalexin formation in apple provides a biotechnological tool for engineering elite cultivars with improved resistance.

A Comprehensive Superposition of Viral Polymerase Structures

Nucleic acid polymerases are essential enzymes that replicate the genomes of both RNA and DNA viruses. These enzymes are generally encoded by viruses themselves so as to provide biochemical functions and control elements that differ from those of the host cell polymerases. The core active site structure used by all replicative polymerases is highly conserved and composed of two key aspartate residues from the conserved motifs A and C, but beyond this there is significant divergence among structures. These differences can make it difficult to select which portions of structures to align for comparisons, yet there are extended structural similarities within different groups of viral polymerases that should clearly be considered to generate optimal alignments. This manuscript describes a comprehensive structure-based superposition of every viral polymerase structure solved thus far based on an alignment-tree approach wherein aligned regions grow in complexity as similarity among polymerases increases. The result is a set of 646 structures that have been aligned into a single common orientation. This provides a convenient resource for directly comparing viral polymerases and illustrating structural conservation among them. It also sets the stage for detailed bioinformatics analysis to further assess common structural features. The full set of protein data bank (PDB) formatted files is publicly available at http://www.zenodo.org/communities/pols/.

The archaeal LDH-like malate dehydrogenase from Ignicoccus islandicus displays dual substrate recognition, hidden allostery and a non-canonical tetrameric oligomeric organization

The NAD(P)-dependent malate dehydrogenases (MalDHs) and NAD-dependent lactate dehydrogenases (LDHs) are homologous enzymes involved in central metabolism. They display a common protein fold and the same catalytic mechanism, yet have a stringent capacity to discriminate between their respective substrates. The MalDH/LDH superfamily is divided into several phylogenetically related groups. It has been shown that the canonical LDHs and LDH-like group of MalDHs are primarily tetrameric enzymes that diverged from a common ancestor. In order to gain understanding of the evolutionary history of the LDHs and MalDHs, the biochemical properties and crystallographic structure of the LDH-like MalDH from the hyperthermophilic archaeon Ignicoccus islandicus (I. isl) were determined. I. isl MalDH recognizes oxaloacetate as main substrate, but it is also able to use pyruvate. Surprisingly, with pyruvate, the enzymatic activity profile looks like that of allosteric LDHs, suggesting a hidden allosteric capacity in a MalDH. The I. isl MalDH tetrameric structure in the apo state is considerably different from those of canonical LDH-like MalDHs and LDHs, representing an alternative oligomeric organization. A comparison with MalDH and LDH counterparts provides strong evidence that the divergence between allosteric and non-allosteric members of the superfamily involves homologs with intermediate, atypical properties.

A Probabilistic Programming Approach to Protein Structure Superposition

Optimal superposition of protein structures or other biological molecules is crucial for understanding their structure, function, dynamics and evolution. Here, we investigate the use of probabilistic programming to superimpose protein structures guided by a Bayesian model. Our model THESEUS-PP is based on the THESEUS model, a probabilistic model of protein superposition based on rotation, translation and perturbation of an underlying, latent mean structure. The model was implemented in the probabilistic programming language Pyro. Unlike conventional methods that minimize the sum of the squared distances, THESEUS takes into account correlated atom positions and heteroscedasticity (ie. atom positions can feature different variances). THESEUS performs maximum likelihood estimation using iterative expectation-maximization. In contrast, THESEUS-PP allows automated maximum a-posteriori (MAP) estimation using suitable priors over rotation, translation, variances and latent mean structure. The results indicate that probabilistic programming is a powerful new paradigm for the formulation of Bayesian probabilistic models concerning biomolecular structure. Specifically, we envision the use of the THESEUS-PP model as a suitable error model or likelihood in Bayesian protein structure prediction using deep probabilistic programming.

Enspara: Modeling molecular ensembles with scalable data structures and parallel computing

Markov state models (MSMs) are quantitative models of protein dynamics that are useful for uncovering the structural fluctuations that proteins undergo, as well as the mechanisms of these conformational changes. Given the enormity of conformational space, there has been ongoing interest in identifying a small number of states that capture the essential features of a protein. Generally, this is achieved by making assumptions about the properties of relevant features-for example, that the most important features are those that change slowly. An alternative strategy is to keep as many degrees of freedom as possible and subsequently learn from the model which of the features are most important. In these larger models, however, traditional approaches quickly become computationally intractable. In this paper, we present enspara, a library for working with MSMs that provides several novel algorithms and specialized data structures that dramatically improve the scalability of traditional MSM methods. This includes ragged arrays for minimizing memory requirements, message passing interface-parallelized implementations of compute-intensive operations, and a flexible framework for model construction and analysis.

Atomic-Level Description of Protein Folding inside the GroEL Cavity

Chaperonins (ubiquitous facilitators of protein folding) sequester misfolded proteins within an internal cavity, thus preventing protein aggregation during the process of refolding. GroEL, a tetradecameric bacterial chaperonin, is one of the most studied chaperonins, but the role of the internal cavity in the refolding process is still unclear. It has been suggested that rather than simply isolating proteins while they refold, the GroEL cavity actively promotes protein folding. A detailed characterization of the folding dynamics and thermodynamics of protein substrates encapsulated within the cavity, however, has been difficult to obtain by experimental means, due to the system's complexity and the many steps in the folding cycle. Here, we examine the influence of the GroEL cavity on protein folding based on the results of unbiased, atomistic molecular dynamics simulations. We first verified that the computational setup, which uses a recently developed state-of-the-art force field that more accurately reproduces the aggregation propensity of unfolded states, could recapitulate the essential structural dynamics of GroEL. In these simulations, the GroEL tetradecamer was highly dynamic, transitioning among states corresponding to most of the structures that have been observed experimentally. We then simulated a small, unfolded protein both in the GroEL cavity and in bulk solution and compared the protein's folding process within these two environments. Inside the GroEL cavity, the unfolded protein interacted strongly with the disordered residues in GroEL's C-terminal tails. These interactions stabilized the protein's unfolded states relative to its compact states and increased the roughness of its folding free-energy surface, resulting in slower folding compared to the rate in solution. For larger proteins, which are more typical GroEL substrates, we speculate that these interactions may allow substrates to more quickly escape kinetic traps associated with compact, misfolded states, thereby actively promoting folding.

Molecular dynamics ensemble refinement of the heterogeneous native state of NCBD using chemical shifts and NOEs

Many proteins display complex dynamical properties that are often intimately linked to their biological functions. As the native state of a protein is best described as an ensemble of conformations, it is important to be able to generate models of native state ensembles with high accuracy. Due to limitations in sampling efficiency and force field accuracy it is, however, challenging to obtain accurate ensembles of protein conformations by the use of molecular simulations alone. Here we show that dynamic ensemble refinement, which combines an accurate atomistic force field with commonly available nuclear magnetic resonance (NMR) chemical shifts and NOEs, can provide a detailed and accurate description of the conformational ensemble of the native state of a highly dynamic protein. As both NOEs and chemical shifts are averaged on timescales up to milliseconds, the resulting ensembles reflect the structural heterogeneity that goes beyond that probed, e.g., by NMR relaxation order parameters. We selected the small protein domain NCBD as object of our study since this protein, which has been characterized experimentally in substantial detail, displays a rich and complex dynamical behaviour. In particular, the protein has been described as having a molten-globule like structure, but with a relatively rigid core. Our approach allowed us to describe the conformational dynamics of NCBD in solution, and to probe the structural heterogeneity resulting from both short- and long-timescale dynamics by the calculation of order parameters on different time scales. These results illustrate the usefulness of our approach since they show that NCBD is rather rigid on the nanosecond timescale, but interconverts within a broader ensemble on longer timescales, thus enabling the derivation of a coherent set of conclusions from various NMR experiments on this protein, which could otherwise appear in contradiction with each other.

Screening, large-scale production and structure-based classification of cystine-dense peptides

Peptides folded through interwoven disulfides display extreme biochemical properties and unique medicinal potential. However, their exploitation has been hampered by the limited amounts isolatable from natural sources and the expense of chemical synthesis. We developed reliable biological methods for high-throughput expression, screening and large-scale production of these peptides: 46 were successfully produced in multimilligram quantities, and >600 more were deemed expressible through stringent screening criteria. Many showed extreme resistance to temperature, proteolysis and/or reduction, and all displayed inhibitory activity against at least 1 of 20 ion channels tested, thus confirming their biological functionality. Crystal structures of 12 confirmed proper cystine topology and the utility of crystallography to study these molecules but also highlighted the need for rational classification. Previous categorization attempts have focused on limited subsets featuring distinct motifs. Here we present a global definition, classification and analysis of >700 structures of cystine-dense peptides, providing a unifying framework for these molecules.

Recent developments in MrBUMP: better search-model preparation, graphical interaction with search models, and solution improvement and assessment

Increasing sophistication in molecular-replacement (MR) software and the rapid expansion of the PDB in recent years have allowed the technique to become the dominant method for determining the phases of a target structure in macromolecular X-ray crystallography. In addition, improvements in bioinformatic techniques for finding suitable homologous structures for use as MR search models, combined with developments in refinement and model-building techniques, have pushed the applicability of MR to lower sequence identities and made weak MR solutions more amenable to refinement and improvement. MrBUMP is a CCP4 pipeline which automates all stages of the MR procedure. Its scope covers everything from the sourcing and preparation of suitable search models right through to rebuilding of the positioned search model. Recent improvements to the pipeline include the adoption of more sensitive bioinformatic tools for sourcing search models, enhanced model-preparation techniques including better ensembling of homologues, and the use of phase improvement and model building on the resulting solution. The pipeline has also been deployed as an online service through CCP4 online, which allows its users to exploit large bioinformatic databases and coarse-grained parallelism to speed up the determination of a possible solution. Finally, the molecular-graphics application CCP4mg has been combined with MrBUMP to provide an interactive visual aid to the user during the process of selecting and manipulating search models for use in MR. Here, these developments in MrBUMP are described with a case study to explore how some of the enhancements to the pipeline and to CCP4mg can help to solve a difficult case.

Target highlights from the first post-PSI CASP experiment (CASP12, May-August 2016)

The functional and biological significance of the selected CASP12 targets are described by the authors of the structures. The crystallographers discuss the most interesting structural features of the target proteins and assess whether these features were correctly reproduced in the predictions submitted to the CASP12 experiment.

In silico and crystallographic studies identify key structural features of biliverdin IXβ reductase inhibitors having nanomolar potency

Heme cytotoxicity is minimized by a two-step catabolic reaction that generates biliverdin (BV) and bilirubin (BR) tetrapyrroles. The second step is regulated by two non-redundant biliverdin reductases (IXα (BLVRA) and IXβ (BLVRB)), which retain isomeric specificity and NAD(P)H-dependent redox coupling linked to BR's antioxidant function. Defective BLVRB enzymatic activity with antioxidant mishandling has been implicated in metabolic consequences of hematopoietic lineage fate and enhanced platelet counts in humans. We now outline an integrated platform of in silico and crystallographic studies for the identification of an initial class of compounds inhibiting BLVRB with potencies in the nanomolar range. We found that the most potent BLVRB inhibitors contain a tricyclic hydrocarbon core structure similar to the isoalloxazine ring of flavin mononucleotide and that both xanthene- and acridine-based compounds inhibit BLVRB's flavin and dichlorophenolindophenol (DCPIP) reductase functions. Crystallographic studies of ternary complexes with BLVRB-NADP⁺-xanthene-based compounds confirmed inhibitor binding adjacent to the cofactor nicotinamide and interactions with the Ser-111 side chain. This residue previously has been identified as critical for maintaining the enzymatic active site and cellular reductase functions in hematopoietic cells. Both acridine- and xanthene-based compounds caused selective and concentration-dependent loss of redox coupling in BLVRB-overexpressing promyelocytic HL-60 cells. These results provide promising chemical scaffolds for the development of enhanced BLVRB inhibitors and identify chemical probes to better dissect the role of biliverdins, alternative substrates, and BLVRB function in physiologically relevant cellular contexts.

Bispectrum Inversion with Application to Multireference Alignment

We consider the problem of estimating a signal from noisy circularly-translated versions of itself, called multireference alignment (MRA). One natural approach to MRA could be to estimate the shifts of the observations first, and infer the signal by aligning and averaging the data. In contrast, we consider a method based on estimating the signal directly, using features of the signal that are invariant under translations. Specifically, we estimate the power spectrum and the bispectrum of the signal from the observations. Under mild assumptions, these invariant features contain enough information to infer the signal. In particular, the bispectrum can be used to estimate the Fourier phases. To this end, we propose and analyze a few algorithms. Our main methods consist of non-convex optimization over the smooth manifold of phases. Empirically, in the absence of noise, these non-convex algorithms appear to converge to the target signal with random initialization. The algorithms are also robust to noise. We then suggest three additional methods. These methods are based on frequency marching, semidefinite relaxation and integer programming. The first two methods provably recover the phases exactly in the absence of noise. In the high noise level regime, the invariant features approach for MRA results in stable estimation if the number of measurements scales like the cube of the noise variance, which is the information-theoretic rate. Additionally, it requires only one pass over the data which is important at low signal-to-noise ratio when the number of observations must be large.

Structural basis of cholesterol binding by a novel clade of dendritic cell modulators from ticks

Two crystal structures of Japanin, an 18 kDa immune-modulatory lipocalin from the Brown Ear Tick (Rhipicephalus appendiculatus), have been determined at 2.2 and 2.4 Å resolution. In both crystal forms the protein is in complex with cholesterol, which sits in a closed pocket at the centre of the lipocalin barrel. Both crystal forms are dimers, which are also observed in solution. Molecular modelling suggests that previously-described members of a tick protein family bearing high sequence homology to Japanin are also likely to bind cholesterol or cholesterol derivatives.

Combined x-ray crystallography and computational modeling approach to investigate the Hsp90 C-terminal peptide binding to FKBP51

FK506 binding protein of 51 kDa (FKBP51) is a heat shock protein 90 (Hsp90) co-chaperone involved in the regulation of steroid hormone receptors activity. It is known for its role in various regulatory pathways implicated in mood and stress-related disorders, cancer, obesity, Alzheimer’s disease and corticosteroid resistant asthma. It consists of two FKBP12 like active peptidyl prolyl isomerase (PPIase) domains (an active FK1 and inactive FK2 domain) and one tetratricopeptide repeat (TPR) domain that mediates interaction with Hsp90 via its C-terminal MEEVD peptide. Here, we report a combined x-ray crystallography and molecular dynamics study to reveal the binding mechanism of Hsp90 MEEVD peptide to the TPR domain of FKBP51. The results demonstrated that the Hsp90 C-terminal peptide binds to the TPR domain of FKBP51 with the help of di-carboxylate clamp involving Lys272, Glu273, Lys352, Asn322, and Lys329 which are conserved throughout several di-carboxylate clamp TPR proteins. Interestingly, the results from molecular dynamics study are also in agreement to the complex structure where all the contacts between these two partners were consistent throughout the simulation period. In a nutshell, our findings provide new opportunity to engage this important protein-protein interaction target by small molecules designed by structure based drug design strategy.

Predictions of Backbone Dynamics in Intrinsically Disordered Proteins Using De Novo Fragment-Based Protein Structure Predictions

Intrinsically disordaered proteins (IDPs) are a prevalent phenomenon with over 30% of human proteins estimated to have long disordered regions. Computational methods are widely used to study IDPs, however, nearly all treat disorder in a binary fashion, not accounting for the structural heterogeneity present in disordered regions. Here, we present a new de novo method, FRAGFOLD-IDP, which addresses this problem. Using 200 protein structural ensembles derived from NMR, we show that FRAGFOLD-IDP achieves superior results compared to methods which can predict related data (NMR order parameter, or crystallographic B-factor). FRAGFOLD-IDP produces very good predictions for 33.5% of cases and helps to get a better insight into the dynamics of the disordered ensembles. The results also show it is not necessary to predict the correct fold of the protein to reliably predict per-residue fluctuations. It implies that disorder is a local property and it does not depend on the fold. Our results are orthogonal to DynaMine, the only other method significantly better than the naïve prediction. We therefore combine these two using a neural network. FRAGFOLD-IDP enables better insight into backbone dynamics in IDPs and opens exciting possibilities for the design of disordered ensembles, disorder-to-order transitions, or design for protein dynamics.

Structurally Linked Dynamics in Lactate Dehydrogenases of Evolutionarily Distinct Species

We present new findings about how primary and secondary structure affects the role of fast protein motions in the reaction coordinates of enzymatic reactions. Using transition path sampling and committor distribution analysis, we examined the difference in the role of these fast protein motions in the reaction coordinate of lactate dehydrogenases (LDHs) of Apicomplexa organisms Plasmodium falciparum and Cryptosporidium parvum. Having evolved separately from a common malate dehydrogenase ancestor, the two enzymes exhibit several important structural differences, notably a five-amino acid insertion in the active site loop of P. falciparum LDH. We find that these active site differences between the two organisms' LDHs likely cause a decrease in the contribution of the previously determined LDH rate-promoting vibration to the reaction coordinate of P. falciparum LDH compared to that of C. parvum LDH, specifically in the coupling of the rate-promoting vibration and the hydride transfer. This effect, while subtle, directly shows how changes in structure near the active site of LDH alter catalytically important motions. Insights provided by studying these alterations would prove to be useful in identifying LDH inhibitors that specifically target the isozymes of these parasitic organisms.

Picornaviral polymerase structure, function, and fidelity modulation

Like all positive strand RNA viruses, the picornaviruses replicate their genomes using a virally encoded RNA-dependent RNA polymerase enzyme known as 3Dpol. Over the past decade we have made tremendous advances in our understanding of 3Dpol structure and function, including the discovery of a novel mechanism for closing the active site that allows these viruses to easily fine tune replication fidelity and quasispecies distributions. This review summarizes current knowledge of picornaviral polymerase structure and how the enzyme interacts with RNA and other viral proteins to form stable and processive elongation complexes. The picornaviral RdRPs are among the smallest viral polymerases, but their fundamental molecular mechanism for catalysis appears to be generally applicable as a common feature of all positive strand RNA virus polymerases.

Evolutionary drivers of thermoadaptation in enzyme catalysis

With early life likely to have existed in a hot environment, enzymes had to cope with an inherent drop in catalytic speed caused by lowered temperature. Here we characterize the molecular mechanisms underlying thermoadaptation of enzyme catalysis in adenylate kinase using ancestral sequence reconstruction spanning 3 billion years of evolution. We show that evolution solved the enzyme's key kinetic obstacle-how to maintain catalytic speed on a cooler Earth-by exploiting transition-state heat capacity. Tracing the evolution of enzyme activity and stability from the hot-start toward modern hyperthermophilic, mesophilic, and psychrophilic organisms illustrates active pressure versus passive drift in evolution on a molecular level, refutes the debated activity/stability trade-off, and suggests that the catalytic speed of adenylate kinase is an evolutionary driver for organismal fitness.

One-Dimensional Structural Properties of Proteins in the Coarse-Grained CABS Model

Despite the significant increase in computational power, molecular modeling of protein structure using classical all-atom approaches remains inefficient, at least for most of the protein targets in the focus of biomedical research. Perhaps the most successful strategy to overcome the inefficiency problem is multiscale modeling to merge all-atom and coarse-grained models. This chapter describes a well-established CABS coarse-grained protein model. The CABS (C-Alpha, C-Beta, and Side chains) model assumes a 2-4 united-atom representation of amino acids, knowledge-based force field (derived from the statistical regularities seen in known protein sequences and structures) and efficient Monte Carlo sampling schemes (MC dynamics, MC replica-exchange, and combinations). A particular emphasis is given to the unique design of the CABS force-field, which is largely defined using one-dimensional structural properties of proteins, including protein secondary structure. This chapter also presents CABS-based modeling methods, including multiscale tools for de novo structure prediction, modeling of protein dynamics and prediction of protein-peptide complexes. CABS-based tools are freely available at http://biocomp.chem.uw.edu.pl/tools.

Mutational analysis and interactions of HBV preS1 with asialoglycoprotein receptor

Background: The mutations in preS1 of a large envelop protein of HBV may have profound implications in HBV receptor binding to hepatocytes and subsequent entry of the virus into host cells. Aims: This study aimed to identify the mutations in preS1 region and the receptor binding interactions of preS1 with hepatocytes. Methods: The mutations were searched through direct sequencing of the preS1 region. Sequence analysis was done through ClustalX and Jalview. Ab initio modeling of preS1 was done through Rosetta and QUARK followed by glycosylation of best model of preS1. Finally the interactions of preS1 with ASGPR was studied using PatchDock and analysis was done using MOE and pyMol. Results: Sequence comparison revealed changes in the preS1 region. Ab initio modeling results showed that preS1 is an overall unstructured protein with the presence of three structural motifs. Docking of preS1 with asialoglycoprotein receptor showed mostly hydrophobic interactions. Conclusion: In conclusion, preS1 sequences from Pakistani isolates were found to be 90% conserved and the predicted structure of preS1 was near to native structure.

Structural characterization of the thermostable Bradyrhizobium japonicumD-sorbitol dehydrogenase

Bradyrhizobium japonicum sorbitol dehydrogenase is NADH-dependent and is active at elevated temperatures. The best substrate is D-glucitol (a synonym for D-sorbitol), although L-glucitol is also accepted, giving it particular potential in industrial applications. Crystallization led to a hexagonal crystal form, with crystals diffracting to 2.9 Å resolution. In attempts to phase the data, a molecular-replacement solution based upon PDB entry 4nbu (33% identical in sequence to the target) was found. The solution contained one molecule in the asymmetric unit, but a tetramer similar to that found in other short-chain dehydrogenases, including the search model, could be reconstructed by applying crystallographic symmetry operations. The active site contains electron density consistent with D-glucitol and phosphate, but there was not clear evidence for the binding of NADH. In a search for the features that determine the thermostability of the enzyme, the Tm for the orthologue from Rhodobacter sphaeroides, for which the structure was already known, was also determined, and this enzyme proved to be considerably less thermostable. A continuous β-sheet is formed between two monomers in the tetramer of the B. japonicum enzyme, a feature not generally shared by short-chain dehydrogenases, and which may contribute to thermostability, as may an increased Pro/Gly ratio.

Vibrational entropy of a protein: large differences between distinct conformations

In this article, it is investigated whether vibrational entropy (VE) is an important contribution to the free energy of globular proteins at ambient conditions. VE represents the major configurational-entropy contribution of these proteins. By definition, it is an average of the configurational entropies of the protein within single minima of the energy landscape, weighted by their occupation probabilities. Its large part originates from thermal motion of flexible torsion angles giving rise to the finite peak widths observed in torsion angle distributions. While VE may affect the equilibrium properties of proteins, it is usually neglected in numerical calculations as its consideration is difficult. Moreover, it is sometimes believed that all well-packed conformations of a globular protein have similar VE anyway. Here, we measure explicitly the VE for six different conformations from simulation data of a test protein. Estimates are obtained using the quasi-harmonic approximation for three coordinate sets, Cartesian, bond-angle-torsion (BAT), and a new set termed rotamer-degeneracy lifted BAT coordinates by us. The new set gives improved estimates as it overcomes a known shortcoming of the quasi-harmonic approximation caused by multiply populated rotamer states, and it may serve for VE estimation of macromolecules in a very general context. The obtained VE values depend considerably on the type of coordinates used. However, for all coordinate sets we find large entropy differences between the conformations, of the order of the overall stability of the protein. This result may have important implications on the choice of free energy expressions used in software for protein structure prediction, protein design, and NMR refinement.

The Structure of the Plakin Domain of Plectin Reveals an Extended Rod-like Shape

Plakins are large multi-domain proteins that interconnect cytoskeletal structures. Plectin is a prototypical plakin that tethers intermediate filaments to membrane-associated complexes. Most plakins contain a plakin domain formed by up to nine spectrin repeats (SR1-SR9) and an SH3 domain. The plakin domains of plectin and other plakins harbor binding sites for junctional proteins. We have combined x-ray crystallography with small angle x-ray scattering (SAXS) to elucidate the structure of the plakin domain of plectin, extending our previous analysis of the SR1 to SR5 region. Two crystal structures of the SR5-SR6 region allowed us to characterize its uniquely wide inter-repeat conformational variability. We also report the crystal structures of the SR7-SR8 region, refined to 1.8 Å, and the SR7-SR9 at lower resolution. The SR7-SR9 region, which is conserved in all other plakin domains, forms a rigid segment stabilized by uniquely extensive inter-repeat contacts mediated by unusually long helices in SR8 and SR9. Using SAXS we show that in solution the SR3-SR6 and SR7-SR9 regions are rod-like segments and that SR3-SR9 of plectin has an extended shape with a small central kink. Other plakins, such as bullous pemphigoid antigen 1 and microtubule and actin cross-linking factor 1, are likely to have similar extended plakin domains. In contrast, desmoplakin has a two-segment structure with a central flexible hinge. The continuous versus segmented structures of the plakin domains of plectin and desmoplakin give insight into how different plakins might respond to tension and transmit mechanical signals.

An effective sequence-alignment-free superpositioning of pairwise or multiple structures with missing data

BACKGROUND

Superpositioning is an important problem in structural biology. Determining an optimal superposition requires a one-to-one correspondence between the atoms of two proteins structures. However, in practice, some atoms are missing from their original structures. Current superposition implementations address the missing data crudely by ignoring such atoms from their structures.

RESULTS

In this paper, we propose an effective method for superpositioning pairwise and multiple structures without sequence alignment. It is a two-stage procedure including data reduction and data registration.

CONCLUSIONS

Numerical experiments demonstrated that our method is effective and efficient. The code package of protein structure superposition method for addressing the cases with missing data is implemented by MATLAB, and it is freely available from: http://sourceforge.net/projects/pssm123/files/?source=navbar.

Biological function derived from predicted structures in CASP11

In CASP11, the organizers sought to bring the biological inferences from predicted structures to the fore. To accomplish this, we assessed the models for their ability to perform quantifiable tasks related to biological function. First, for 10 targets that were probable homodimers, we measured the accuracy of docking the models into homodimers as a function of GDT-TS of the monomers, which produced characteristic L-shaped plots. At low GDT-TS, none of the models could be docked correctly as homodimers. Above GDT-TS of ∼60%, some models formed correct homodimers in one of the largest docked clusters, while many other models at the same values of GDT-TS did not. Docking was more successful when many of the templates shared the same homodimer. Second, we docked a ligand from an experimental structure into each of the models of one of the targets. Docking to the models with two different programs produced poor ligand RMSDs with the experimental structure. Measures that evaluated similarity of contacts were reasonable for some of the models, although there was not a significant correlation with model accuracy. Finally, we assessed whether models would be useful in predicting the phenotypes of missense mutations in three human targets by comparing features calculated from the models with those calculated from the experimental structures. The models were successful in reproducing accessible surface areas but there was little correlation of model accuracy with calculation of FoldX evaluation of the change in free energy between the wild-type and the mutant. Proteins 2016; 84(Suppl 1):370-391. © 2016 Wiley Periodicals, Inc.

Assessment of template-based modeling of protein structure in CASP11

We present the assessment of predictions submitted in the template-based modeling (TBM) category of CASP11 (Critical Assessment of Protein Structure Prediction). Model quality was judged on the basis of global and local measures of accuracy on all atoms including side chains. The top groups on 39 human-server targets based on model 1 predictions were LEER, Zhang, LEE, MULTICOM, and Zhang-Server. The top groups on 81 targets by server groups based on model 1 predictions were Zhang-Server, nns, BAKER-ROSETTASERVER, QUARK, and myprotein-me. In CASP11, the best models for most targets were equal to or better than the best template available in the Protein Data Bank, even for targets with poor templates. The overall performance in CASP11 is similar to the performance of predictors in CASP10 with slightly better performance on the hardest targets. For most targets, assessment measures exhibited bimodal probability density distributions. Multi-dimensional scaling of an RMSD matrix for each target typically revealed a single cluster with models similar to the target structure, with a mode in the GDT-TS density between 40 and 90, and a wide distribution of models highly divergent from each other and from the experimental structure, with density mode at a GDT-TS value of ∼20. The models in this peak in the density were either compact models with entirely the wrong fold, or highly non-compact models. The results argue for a density-driven approach in future CASP TBM assessments that accounts for the bimodal nature of these distributions instead of Z scores, which assume a unimodal, Gaussian distribution. Proteins 2016; 84(Suppl 1):200-220. © 2016 Wiley Periodicals, Inc.

Gradual neofunctionalization in the convergent evolution of trichomonad lactate and malate dehydrogenases

Lactate and malate dehydrogenases (LDH and MDH) are homologous, core metabolic enzymes common to nearly all living organisms. LDHs have evolved convergently from MDHs at least four times, achieving altered substrate specificity by a different mechanism each time. For instance, the LDH of anaerobic trichomonad parasites recently evolved independently from an ancestral trichomonad MDH by gene duplication. LDH plays a central role in trichomonad metabolism by catalyzing the reduction of pyruvate to lactate, thereby regenerating the NAD+ required for glycolysis. Using ancestral reconstruction methods, we identified the biochemical and evolutionary mechanisms responsible for this convergent event. The last common ancestor of these enzymes was a highly specific MDH, similar to modern trichomonad MDHs. In contrast, the LDH lineage evolved promiscuous activity by relaxing specificity in a gradual process of neofunctionalization involving one highly detrimental substitution at the “specificity residue” (R91L) and many additional mutations of small effect. L91 has different functional consequences in LDHs and in MDHs, indicating a prominent role for epistasis. Crystal structures of modern‐day and ancestral enzymes show that the evolution of substrate specificity paralleled structural changes in dimerization and α‐helix orientation. The relatively small “specificity residue” of the trichomonad LDHs can accommodate a range of substrate sizes and may permit solvent to access the active site, both of which promote substrate promiscuity. The trichomonad LDHs present a multi‐faceted counterpoint to the independent evolution of LDHs in other organisms and illustrate the diverse mechanisms by which protein function, structure, and stability coevolve.

PDB Code(s): 4UUL; 4UUM; 4UUN; 4UUO; 4UUP; 5A1T

New insights into the mechanism of substrates trafficking in Glyoxylate/Hydroxypyruvate reductases

Glyoxylate accumulation within cells is highly toxic. In humans, it is associated with hyperoxaluria type 2 (PH2) leading to renal failure. The glyoxylate content within cells is regulated by the NADPH/NADH dependent glyoxylate/hydroxypyruvate reductases (GRHPR). These are highly conserved enzymes with a dual activity as they are able to reduce glyoxylate to glycolate and to convert hydroxypyruvate into D-glycerate. Despite the determination of high-resolution X-ray structures, the substrate recognition mode of this class of enzymes remains unclear. We determined the structure at 2.0 Å resolution of a thermostable GRHPR from Archaea as a ternary complex in the presence of D-glycerate and NADPH. This shows a binding mode conserved between human and archeal enzymes. We also determined the first structure of GRHPR in presence of glyoxylate at 1.40 Å resolution. This revealed the pivotal role of Leu53 and Trp138 in substrate trafficking. These residues act as gatekeepers at the entrance of a tunnel connecting the active site to protein surface. Taken together, these results allowed us to propose a general model for GRHPR mode of action.

The Combination of X-Ray Crystallography and Cryo-Electron Microscopy Provides Insight into the Overall Architecture of the Dodecameric Rvb1/Rvb2 Complex

The Rvb1/Rvb2 complex is an essential component of many cellular pathways. The Rvb1/Rvb2 complex forms a dodecameric assembly where six copies of each subunit form two heterohexameric rings. However, due to conformational variability, the way the two rings pack together is still not fully understood. Here, we present the crystal structure and two cryo-electron microscopy reconstructions of the dodecameric, full-length Rvb1/Rvb2 complex, all showing that the interaction between the two heterohexameric rings is mediated through the Rvb1/Rvb2-specific domain II. Two conformations of the Rvb1/Rvb2 dodecamer are present in solution: a stretched conformation also present in the crystal, and a compact conformation. Novel asymmetric features observed in the reconstruction of the compact conformation provide additional insight into the plasticity of the Rvb1/Rvb2 complex.

Predicted structures of new Vitamin D Receptor agonists based on available X-ray structures

Current efforts in the field of vitamin D are to develop 1,25(OH)2D3 analogs that exhibit equal or even increased anti-proliferative activity while possessing a reduced tendency to cause hypercalcemia. The study proposes a new, rational design of vitamin D analogs based on data available in the Protein Data Bank. Undertaken approach was to minimize the electrostatic interaction energies available after the reconstruction of charge density with the aid of the pseudoatom databank, namely the University at Buffalo Pseudoatom Databank (UBDB). Analysis of 24 vitamin D analogs, bearing similar molecular structures complexed with Vitamin D Receptor enabled the design of new agonists forming all advantageous interaction to the receptor, coded TB1, TB2, TB3 and TB4.

Combination of X-ray crystallography, SAXS and DEER to obtain the structure of the FnIII-3,4 domains of integrin α6β4

Integrin α6β4 is a major component of hemidesmosomes that mediate the stable anchorage of epithelial cells to the underlying basement membrane. Integrin α6β4 has also been implicated in cell proliferation and migration and in carcinoma progression. The third and fourth fibronectin type III domains (FnIII-3,4) of integrin β4 mediate binding to the hemidesmosomal proteins BPAG1e and BPAG2, and participate in signalling. Here, it is demonstrated that X-ray crystallography, small-angle X-ray scattering and double electron-electron resonance (DEER) complement each other to solve the structure of the FnIII-3,4 region. The crystal structures of the individual FnIII-3 and FnIII-4 domains were solved and the relative arrangement of the FnIII domains was elucidated by combining DEER with site-directed spin labelling. Multiple structures of the interdomain linker were modelled by Monte Carlo methods complying with DEER constraints, and the final structures were selected against experimental scattering data. FnIII-3,4 has a compact and cambered flat structure with an evolutionary conserved surface that is likely to correspond to a protein-interaction site. Finally, this hybrid method is of general application for the study of other macromolecules and complexes.