HADDOCK versus HADDOCK: new features and performance of HADDOCK2.0 on the CAPRI targets

Structure based peptide design, molecular dynamics and MM-PBSA studies for targeting C terminal dimerization of NFAT5 DNA binding domain

NFAT5 as a transcription factor with an established role in osmotic stress response, has also been revealed to be active under numerous settings, including pathological conditions such as diabetic microvascular complications, chronic arthritis and cancer. Despite these links, current strategies for downregulating NFAT5 activity only relies on indirect modulators, not directly targeting NFAT5, itself. With this study, through using a computational approach, an original peptide was explored to directly target C terminal dimerization of NFAT5 RHR, located in its DNA binding domain. At first, homodimeric NFAT5 RHR bound to its consensus DNA was used for prediction of a preliminary peptide sequence. Possible amino acid replacements for this preliminary peptide were predicted for optimization, which was followed by addition of a cell penetrating peptide sequence. These attempts yielded a small peptide library, which was further investigated for peptide affinities towards C terminal of NFAT5 RHR through molecular docking, 50 ns and 250 ns molecular dynamics simulations, followed by estimation of MM-PBSA based relative binding free energies. Results indicated that after receiving mutations on the preliminary peptide sequence for optimization, a unique peptide could target C terminal dimerization region of NFAT5 RHR through using its cell penetrating peptide sequence. In conclusion, this is the first study presenting computational evidence on identification of a novel peptide capable of directly targeting NFAT5 dimerization. Besides, future implications of these observations were also discussed in terms of methodology and possible applications.

Computational approaches to therapeutic antibody design: established methods and emerging trends

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.

Peptides targeting dengue viral nonstructural protein 1 inhibit dengue virus production

Viruses manipulate the life cycle in host cells via the use of viral properties and host machineries. Development of antiviral peptides against dengue virus (DENV) infection has previously been concentrated on blocking the actions of viral structural proteins and enzymes in virus entry and viral RNA processing in host cells. In this study, we proposed DENV NS1, which is a multifunctional non-structural protein indispensable for virus production, as a new target for inhibition of DENV infection by specific peptides. We performed biopanning assays using a phage-displayed peptide library and identified 11 different sequences of 12-mer peptides binding to DENV NS1. In silico analyses of peptide-protein interactions revealed 4 peptides most likely to bind to DENV NS1 at specific positions and their association was analysed by surface plasmon resonance. Treatment of Huh7 cells with these 4 peptides conjugated with N-terminal fluorescent tag and C-terminal cell penetrating tag at varying time-of-addition post-DENV infection could inhibit the production of DENV-2 in a time- and dose-dependent manner. The inhibitory effects of the peptides were also observed in other virus serotypes (DENV-1 and DENV-4), but not in DENV-3. These findings indicate the potential application of peptides targeting DENV NS1 as antiviral agents against DENV infection.

Refinement of pairwise potentials via logistic regression to score protein-protein interactions

Protein-protein interactions (PPIs) are ubiquitous and functionally of great importance in biological systems. Hence, the accurate prediction of PPIs by protein-protein docking and scoring tools is highly desirable in order to characterize their structure and biological function. Ab initio docking protocols are divided into the sampling of docking poses to produce at least one near-native structure, and then to evaluate the vast candidate structures by scoring. Concurrent development in both sampling and scoring is crucial for the deployment of protein-protein docking software. In the present work, we apply a machine learning model on pairwise potentials to refine the task of protein quaternary structure native structure detection among decoys. A decoy set was featurized using the Knowledge and Empirical Combined Scoring Algorithm 2 (KECSA2) pairwise potential. The highly unbalanced decoy set was then balanced using a comparison concept between native and decoy structures. The resultant comparison descriptors were used to train a logistic regression (LR) classifier. The LR model yielded the optimal performance for native detection among decoys compared with conventional scoring functions, while exhibiting lesser performance for the detection of low root mean square deviation decoy structures. Its deployment on an independent benchmark set confirms that the scoring function performs competitively relative to other scoring functions. The scripts used are available at https://github.com/TanemuraKiyoto/PPI-native-detection-via-LR.

How repertoire data are changing antibody science

Antibodies are vital proteins of the immune system that recognize potentially harmful molecules and initiate their removal. Mammals can efficiently create vast numbers of antibodies with different sequences capable of binding to any antigen with high affinity and specificity. Because they can be developed to bind to many disease agents, antibodies can be used as therapeutics. In an organism, after antigen exposure, antibodies specific to that antigen are enriched through clonal selection, expansion, and somatic hypermutation. The antibodies present in an organism therefore report on its immune status, describe its innate ability to deal with harmful substances, and reveal how it has previously responded. Next-generation sequencing technologies are being increasingly used to query the antibody, or B-cell receptor (BCR), sequence repertoire, and the amount of BCR data in public repositories is growing. The Observed Antibody Space database, for example, currently contains over a billion sequences from 68 different studies. Repertoires are available that represent both the naive state (i.e. antigen-inexperienced) and that after immunization. This wealth of data has created opportunities to learn more about our immune system. In this review, we discuss the many ways in which BCR repertoire data have been or could be exploited. We highlight its utility for providing insights into how the naive immune repertoire is generated and how it responds to antigens. We also consider how structural information can be used to enhance these data and may lead to more accurate depictions of the sequence space and to applications in the discovery of new therapeutics.

COVID-19 spike-host cell receptor GRP78 binding site prediction

OBJECTIVES

Understanding the novel coronavirus (COVID-19) mode of host cell recognition may help to fight the disease and save lives. The spike protein of coronaviruses is the main driving force for host cell recognition.

METHODS

In this study, the COVID-19 spike binding site to the cell-surface receptor (Glucose Regulated Protein 78 (GRP78)) is predicted using combined molecular modeling docking and structural bioinformatics. The COVID-19 spike protein is modeled using its counterpart, the SARS spike.

RESULTS

Sequence and structural alignments show that four regions, in addition to its cyclic nature have sequence and physicochemical similarities to the cyclic Pep42. Protein-protein docking was performed to test the four regions of the spike that fit tightly in the GRP78 Substrate Binding Domain β (SBDβ). The docking pose revealed the involvement of the SBDβ of GRP78 and the receptor-binding domain of the coronavirus spike protein in recognition of the host cell receptor.

CONCLUSIONS

We reveal that the binding is more favorable between regions III (C391-C525) and IV (C480-C488) of the spike protein model and GRP78. Region IV is the main driving force for GRP78 binding with the predicted binding affinity of -9.8 kcal/mol. These nine residues can be used to develop therapeutics specific against COVID-19.

A Review of Deep Learning Methods for Antibodies

Driven by its successes across domains such as computer vision and natural language processing, deep learning has recently entered the field of biology by aiding in cellular image classification, finding genomic connections, and advancing drug discovery. In drug discovery and protein engineering, a major goal is to design a molecule that will perform a useful function as a therapeutic drug. Typically, the focus has been on small molecules, but new approaches have been developed to apply these same principles of deep learning to biologics, such as antibodies. Here we give a brief background of deep learning as it applies to antibody drug development, and an in-depth explanation of several deep learning algorithms that have been proposed to solve aspects of both protein design in general, and antibody design in particular.

Structural insights on binding mechanism of CAD complexes (CPSase, ATCase and DHOase)

Pyrimidine biosynthetic pathway enzymes constitute an important target for the development of antitumor drugs. To understand the role of binding mechanisms underlying the inborn errors of pyrimidine biosynthetic pathway, structure and function of enzymes have been analyzed. Pyrimidine biosynthetic pathway is initiated by CAD enzymes that harbor the first three enzymatic activities facilitated by Carbamoyl Phosphate Synthetase (CPSase), Aspartate Transcarbamoylase (ATCase) and Dihydroorotase (DHOase). While being an attractive therapeutic target, the lack of data driven us to study the CPSase (CarA and CarB) and its mode of binding to ATCase and DHOase which are the major limitation for its structural optimization. Understanding the binding mode of CPSase, ATCase and DHOase could help to identify the potential interface hotspot residues that favor the mechanism behind it. The mechanistic insight into the CAD complexes were achieved through Molecular modeling, Protein-Protein docking, Alanine scanning and Molecular dynamics (MD) Studies. The hotspot residues present in the CarB region of carboxy phosphate and carbamoyl phosphate synthetic domains are responsible for the assembly of CAD (CPSase-ATCase-DHOase) complexes. Overall analysis suggests that the identified hotspot residues were confirmed by alanine scanning and important for the regulation of pyrimidine biosynthesis. MD simulations analysis provided the prolonged stability of the interacting complexes. The present study reveals the novel hotspot residues such as Glu134, Glu147, Glu154, Asp266, Lys269, Glu274, Asp333, Trp459, Asp526, Asp528, Glu533, Glu544, Glu546, Glu800, Val855, Asp877, Tyr884 and Gln919 which could be targeted for structure-based inhibitor design to potentiate the CAD mediated regulation of aggressive tumors.Communicated by Ramaswamy H. Sarma.

Structural Insights Into How Proteoglycans Determine Chemokine-CXCR1/CXCR2 Interactions: Progress and Challenges

Proteoglycans (PGs), present in diverse environments, such as the cell membrane surface, extracellular milieu, and intracellular granules, are fundamental to life. Sulfated glycosaminoglycans (GAGs) are covalently attached to the core protein of proteoglycans. PGs are complex structures, and are diverse in terms of amino acid sequence, size, shape, and in the nature and number of attached GAG chains, and this diversity is further compounded by the phenomenal diversity in GAG structures. Chemokines play vital roles in human pathophysiology, from combating infection and cancer to leukocyte trafficking, immune surveillance, and neurobiology. Chemokines mediate their function by activating receptors that belong to the GPCR class, and receptor interactions are regulated by how, when, and where chemokines bind GAGs. GAGs fine-tune chemokine function by regulating monomer/dimer levels and chemotactic/haptotactic gradients, which are also coupled to how they are presented to their receptors. Despite their small size and similar structures, chemokines show a range of GAG-binding geometries, affinities, and specificities, indicating that chemokines have evolved to exploit the repertoire of chemical and structural features of GAGs. In this review, we summarize the current status of research on how GAG interactions regulate ELR-chemokine activation of CXCR1 and CXCR2 receptors, and discuss knowledge gaps that must be overcome to establish causal relationships governing the impact of GAG interactions on chemokine function in human health and disease.

Prediction of protein-protein complexes using replica exchange with repulsive scaling

The realistic prediction of protein-protein complex structures is import to ultimately model the interaction of all proteins in a cell and for the design of new protein-protein interactions. In principle, molecular dynamics (MD) simulations allow one to follow the association process under realistic conditions including full partner flexibility and surrounding solvent. However, due to the many local binding energy minima at the surface of protein partners, MD simulations are frequently trapped for long times in transient association states. We have designed a replica-exchange based scheme employing different levels of a repulsive biasing between partners in each replica simulation. The bias acts only on intermolecular interactions based on an increase in effective pairwise van der Waals radii (repulsive scaling (RS)-REMD) without affecting interactions within each protein or with the solvent. For a set of five protein test cases (out of six) the RS-REMD technique allowed the sampling of near-native complex structures even when starting from the opposide site with respect to the native binding site for one partner. Using the same start structures and same computational demand regular MD simulations sampled near native complex structures only for one case. The method showed also improved results for the refinement of docked structures in the vicinity of the native binding geometry compared to regular MD refinement.

Structural Determinants Mediating Tertiapin Block of Neuronal Kir3.2 Channels

Tertiapin (TPN) is a 21 amino acid venom peptide from Apis mellifera that inhibits certain members of the inward rectifier potassium (Kir) channel family at a nanomolar affinity with limited specificity. Structure-based computational simulations predict that TPN behaves as a pore blocker; however, the molecular determinants mediating block of neuronal Kir3 channels have been inconclusive and unvalidated. Here, using molecular docking and molecular dynamics (MD) simulations with 'potential of mean force' (PMF) calculations, we investigated the energetically most favored interaction of TPN with several Kir3.x channel structures. The resulting binding model for Kir3.2-TPN complexes was then tested by targeted mutagenesis of the predicted contact sites, and their impact on the functional channel block was measured electrophysiologically. Together, our findings indicate that a high-affinity TPN block of Kir3.2 channels involves a pore-inserting lysine side chain requiring (1) hydrophobic interactions at a phenylalanine ring surrounding the channel pore and (2) electrostatic interactions with two adjacent Kir3.2 turret regions. Together, these interactions collectively stabilize high-affinity toxin binding to the Kir3.2 outer vestibule, which orients the ε-amino group of TPN-K21 to occupy the outermost K⁺ binding site of the selectivity filter. The structural determinants for the TPN block described here also revealed a favored subunit arrangement for assembled Kir3.x heteromeric channels, in addition to a multimodal binding capacity of TPN variants consistent with the functional dyad model for polybasic peptide pore blockers. These novel findings will aid efforts in re-engineering the TPN pharmacophore to develop peptide variants having unique and distinct Kir channel blocking properties.

Challenges and opportunities of automated protein-protein docking: HDOCK server vs human predictions in CAPRI Rounds 38-46

Protein-protein docking plays an important role in the computational prediction of the complex structure between two proteins. For years, a variety of docking algorithms have been developed, as witnessed by the critical assessment of prediction interactions (CAPRI) experiments. However, despite their successes, many docking algorithms often require a series of manual operations like modeling structures from sequences, incorporating biological information, and selecting final models. The difficulties in these manual steps have significantly limited the applications of protein-protein docking, as most of the users in the community are nonexperts in docking. Therefore, automated docking like a web server, which can give a comparable performance to human docking protocol, is pressingly needed. As such, we have participated in the blind CAPRI experiments for Rounds 38-45 and CASP13-CAPRI challenge for Round 46 with both our HDOCK automated docking web server and human docking protocol. It was shown that our HDOCK server achieved an "acceptable" or higher CAPRI-rated model in the top 10 submitted predictions for 65.5% and 59.1% of the targets in the docking experiments of CAPRI and CASP13-CAPRI, respectively, which are comparable to 66.7% and 54.5% for human docking protocol. Similar trends can also be observed in the scoring experiments. These results validated our HDOCK server as an efficient automated docking protocol for nonexpert users. Challenges and opportunities of automated docking are also discussed.

Self-assembling as regular nanoparticles dramatically minimizes photobleaching of tumour-targeted GFP

Fluorescent proteins are useful imaging and theranostic agents, but their potential superiority over alternative dyes is weakened by substantial photobleaching under irradiation. Enhancing protein photostability has been attempted through diverse strategies, with irregular results and limited applicability. In this context, we wondered if the controlled oligomerization of Green Fluorescent Protein (GFP) as nanoscale supramolecular complexes could stabilize the fluorophore through the newly formed protein-protein contacts, and thus, enhance its global photostability. For that, we have here analyzed the photobleaching profile of several GFP versions, engineered to self-assemble as tumour-homing nanoparticles with different targeting, size and structural stability. This has been done under prolonged irradiation in confocal laser scanning microscopy and by small-angle X-ray scattering. The results show that the oligomerization of GFP at the nanoscale enhances, by more than seven-fold, the stability of fluorescence emission. Interestingly, GFP nanoparticles are much more resistant to X-ray damage than the building block counterparts, indicating that the gained photostability is linked to enhanced structural resistance to radiation. Therefore, the controlled oligomerization of self-assembling fluorescent proteins as protein nanoparticles is a simple, versatile and powerful method to enhance their photostability for uses in precision imaging and therapy. STATEMENT OF SIGNIFICANCE: Fluorescent protein assembly into regular and highly symmetric nanoscale structures has been identified to confer enhanced structural stability against radiation stresses dramatically reducing their photobleaching. Being this the main bottleneck in the use of fluorescent proteins for imaging and theranostics, this protein architecture engineering principle appears as a powerful method to enhance their photostability for a broad applicability in precision imaging, drug delivery and theranostics.

Elucidation of WW domain ligand binding specificities in the Hippo pathway reveals STXBP4 as YAP inhibitor

The Hippo pathway, which plays a critical role in organ size control and cancer, features numerous WW domain-based protein-protein interactions. However, ~100 WW domains and 2,000 PY motif-containing peptide ligands are found in the human proteome, raising a "WW-PY" binding specificity issue in the Hippo pathway. In this study, we have established the WW domain binding specificity for Hippo pathway components and uncovered a unique amino acid sequence required for it. By using this criterion, we have identified a WW domain-containing protein, STXBP4, as a negative regulator of YAP. Mechanistically, STXBP4 assembles a protein complex comprising α-catenin and a group of Hippo PY motif-containing components/regulators to inhibit YAP, a process that is regulated by actin cytoskeleton tension. Interestingly, STXBP4 is a potential tumor suppressor for human kidney cancer, whose downregulation is correlated with YAP activation in clear cell renal cell carcinoma. Taken together, our study not only elucidates the WW domain binding specificity for the Hippo pathway, but also reveals STXBP4 as a player in actin cytoskeleton tension-mediated Hippo pathway regulation.

Protein-Protein Modeling Using Cryo-EM Restraints

Recent improvements in cryo-electron microscopy (cryo-EM) in the past few years are now allowing to observe molecular complexes at atomic resolution. As a consequence, numerous structures derived from cryo-EM are now available in the Protein Data Bank. However, if for some complexes atomic resolution is reached, this is not true for all. This is also the case in cryo-electron tomography where the achievable resolution is still limited. Furthermore the resolution in a cryo-EM map is not a constant, with often outer regions being of lower resolution, possibly linked to conformational variability. Although those low- to medium-resolution EM maps (or regions thereof) cannot directly provide atomic structure of large molecular complexes, they provide valuable information to model the individual components and their assembly into them. Most approaches for this kind of modeling are performing rigid fitting of the individual components into the EM density map. While this would appear an obvious option, they ignore key aspects of molecular recognition, the energetics and flexibility of the interfaces. Moreover, this often restricts the modeling to a unique source of data, the EM density map.In this chapter, we describe a protocol where an EM map is used as restraint in HADDOCK to guide the modeling process. In the first step, rigid-body fitting is performed with PowerFit in order to identify the most likely locations of the molecules into the map. These are then used as centroids to which distance restraints are defined from the center of mass of the components of the complex for the initial rigid-body docking. The EM density is then directly used as an additional restraint energy term, which can be combined with all the other types of data supported by HADDOCK. This protocol relies on the new version 2.4 of both the HADDOCK webserver and software. Preparation steps consisting of cropping the EM map and rigid-body fitting of the atomic structure are explained. Then, the EM-driven docking protocol using HADDOCK is illustrated.

A protocol to automatically calculate homo-oligomeric protein structures through the integration of evolutionary constraints and NMR ambiguous contacts

Protein assemblies are involved in many important biological processes. Solid-state NMR (SSNMR) spectroscopy is a technique suitable for the structural characterization of samples with high molecular weight and thus can be applied to such assemblies. A significant bottleneck in terms of both effort and time required is the manual identification of unambiguous intermolecular contacts. This is particularly challenging for homo-oligomeric complexes, where simple uniform labeling may not be effective. We tackled this challenge by exploiting coevolution analysis to extract information on homo-oligomeric interfaces from NMR-derived ambiguous contacts. After removing the evolutionary couplings (ECs) that are already satisfied by the 3D structure of the monomer, the predicted ECs are matched with the automatically generated list of experimental contacts. This approach provides a selection of potential interface residues that is used directly in monomer-monomer docking calculations. We validated the protocol on tetrameric L-asparaginase II and dimeric Sod1.

Solution structure of human myeloid-derived growth factor suggests a conserved function in the endoplasmic reticulum

Human myeloid-derived growth factor (hMYDGF) is a 142-residue protein with a C-terminal endoplasmic reticulum (ER) retention sequence (ERS). Extracellular MYDGF mediates cardiac repair in mice after anoxic injury. Although homologs of hMYDGF are found in eukaryotes as distant as protozoans, its structure and function are unknown. Here we present the NMR solution structure of hMYDGF, which consists of a short α-helix and ten β-strands distributed in three β-sheets. Conserved residues map to the unstructured ERS, loops on the face opposite the ERS, and the surface of a cavity underneath the conserved loops. The only protein or portion of a protein known to have a similar fold is the base domain of VNN1. We suggest, in analogy to the tethering of the VNN1 nitrilase domain to the plasma membrane via its base domain, that MYDGF complexed to the KDEL receptor binds cargo via its conserved residues for transport to the ER.

CD8 Binding of MHC-Peptide Complexes in cis or trans Regulates CD8+ T-cell Responses

The coreceptor CD8αβ can greatly promote activation of T cells by strengthening T-cell receptor (TCR) binding to cognate peptide-MHC complexes (pMHC) on antigen presenting cells and by bringing p56^Lck to TCR/CD3. Here, we demonstrate that CD8 can also bind to pMHC on the T cell (in cis) and that this inhibits their activation. Using molecular modeling, fluorescence resonance energy transfer experiments on living cells, biochemical and mutational analysis, we show that CD8 binding to pMHC in cis involves a different docking mode and is regulated by posttranslational modifications including a membrane-distal interchain disulfide bond and negatively charged O-linked glycans near positively charged sequences on the CD8β stalk. These modifications distort the stalk, thus favoring CD8 binding to pMHC in cis. Differential binding of CD8 to pMHC in cis or trans is a means to regulate CD8⁺ T-cell responses and provides new translational opportunities.

ATP binds nucleic-acid-binding domains beyond RRM fold

It has remained a mystery why cells maintain ATP concentrations of 2-12 mM, much higher than required for its known functions, until ATP is decoded to act as a hydrotrope to non-specifically control protein homeostasis above 5 mM. Unexpectedly, our NMR studies further reveal that by specific binding, ATP also mediates liquid-liquid phase separation in a two-stage style and inhibits fibrillation of RRM domains of FUS and TDP-43, implying that ATP might have a second category of functions previously unknown. So can ATP also bind nucleic-acid-binding proteins without RRM fold? Here we characterized the interaction between ATP and SYNCRIP acidic domain (AcD), a non-canonical RNA-binding domain with no similarity to RRM fold in sequence and structure. The results reveal that ATP does bind AcD at physiologically-relevant concentrations with the affinity determinants generally underlying protein-nucleic acid interactions. Therefore, at concentrations above mM, ATP might bind most, if not all, nucleic-acid-binding proteins.

Structural characterization of B. subtilis m1A22 tRNA methyltransferase TrmK: insights into tRNA recognition

1-Methyladenosine (m¹A) is a modified nucleoside found at positions 9, 14, 22 and 58 of tRNAs, which arises from the transfer of a methyl group onto the N1-atom of adenosine. The yqfN gene of Bacillus subtilis encodes the methyltransferase TrmK (_BsTrmK) responsible for the formation of m¹A₂₂ in tRNA. Here, we show that _BsTrmK displays a broad substrate specificity, and methylates seven out of eight tRNA isoacceptor families of B. subtilis bearing an A₂₂. In addition to a non-Watson–Crick base-pair between the target A₂₂ and a purine at position 13, the formation of m¹A₂₂ by _BsTrmK requires a full-length tRNA with intact tRNA elbow and anticodon stem. We solved the crystal structure of _BsTrmK showing an N-terminal catalytic domain harbouring the typical Rossmann-like fold of Class-I methyltransferases and a C-terminal coiled-coil domain. We used NMR chemical shift mapping to drive the docking of _BstRNA^Ser to _BsTrmK in complex with its methyl-donor cofactor S-adenosyl-L-methionine (SAM). In this model, validated by methyltransferase activity assays on _BsTrmK mutants, both domains of _BsTrmK participate in tRNA binding. _BsTrmK recognises tRNA with very few structural changes in both partner, the non-Watson–Crick R₁₃–A₂₂ base-pair positioning the A₂₂ N1-atom close to the SAM methyl group.

ATP is a cryptic binder of TDP-43 RRM domains to enhance stability and inhibit ALS/AD-associated fibrillation

ATP is the universal energy currency for all cells but has cellular concentrations of 2-12 mM, much higher than required for its classic functions. RNA-recognition motif (RRM) constitutes one of the most abundant domains in eukaryotes and most heterogeneous nuclear ribonucleoproteins (hnRNP) contain RRM domains which not only mediate direct interactions with nucleic acids, but whose aggregation/fibrillation is the pathological hallmark of various human diseases. Here, by NMR and molecular docking, ATP has been decoded to bind TDP-43 two tandem RRM domains with distinctive types of interactions, thus resulting in diverse affinities. Most strikingly, the binding of ATP enhances thermodynamic stability of TDP-43 RRM domains and inhibits ALS-/AD-associated fibrillation. Together, ATP is a cryptic binder of RRM-containing proteins which generally safeguards functional phase separation from transforming into pathological aggregation/fibrillation associated with various diseases and ageing. Our study thus reveals a mechanism of ATP to control protein homeostasis by specific binding.

Structural basis of chemokine interactions with heparan sulfate, chondroitin sulfate, and dermatan sulfate

Chemokines play diverse roles in human pathophysiology, ranging from trafficking leukocytes and immunosurveillance to the regulation of metabolism and neural function. Chemokine function is intimately coupled to binding tissue glycosaminoglycans (GAGs), heparan sulfate (HS), chondroitin sulfate (CS), and dermatan sulfate (DS). Currently, very little is known about how the structural features and sequences of a given chemokine, the structure and sulfation pattern of a given GAG, and structural differences among GAGs and among chemokines impact binding interactions. In this study, we used solution NMR spectroscopy to characterize the binding interactions of two related neutrophil-activating chemokines, CXCL1 and CXCL5, with HS, CS, and DS. For both chemokines, the dimer bound all three GAGs with higher affinity than did the monomer, and affinities of the chemokines for CS and DS were lower than for HS. NMR-based structural models reveal diverse binding geometries and show that the binding surfaces for each of the three GAGs were different between the two chemokines. However, a given chemokine had similar binding interactions with CS and DS that were different from HS. Considering the fact that CXCL1 and CXCL5 activate the same CXCR2 receptor, we conclude that GAG interactions play a role in determining the nature of chemokine gradients, levels of free chemokine available for receptor activation, how chemokines bind their receptors, and that differences in these interactions determine chemokine-specific function.

DeepBindRG: a deep learning based method for estimating effective protein-ligand affinity

Proteins interact with small molecules to modulate several important cellular functions. Many acute diseases were cured by small molecule binding in the active site of protein either by inhibition or activation. Currently, there are several docking programs to estimate the binding position and the binding orientation of protein–ligand complex. Many scoring functions were developed to estimate the binding strength and predict the effective protein–ligand binding. While the accuracy of current scoring function is limited by several aspects, the solvent effect, entropy effect, and multibody effect are largely ignored in traditional machine learning methods. In this paper, we proposed a new deep neural network-based model named DeepBindRG to predict the binding affinity of protein–ligand complex, which learns all the effects, binding mode, and specificity implicitly by learning protein–ligand interface contact information from a large protein–ligand dataset. During the initial data processing step, the critical interface information was preserved to make sure the input is suitable for the proposed deep learning model. While validating our model on three independent datasets, DeepBindRG achieves root mean squared error (RMSE) value of pKa (−logK_d or −logK_i) about 1.6–1.8 and R value around 0.5–0.6, which is better than the autodock vina whose RMSE value is about 2.2–2.4 and R value is 0.42–0.57. We also explored the detailed reasons for the performance of DeepBindRG, especially for several failed cases by vina. Furthermore, DeepBindRG performed better for four challenging datasets from DUD.E database with no experimental protein–ligand complexes. The better performance of DeepBindRG than autodock vina in predicting protein–ligand binding affinity indicates that deep learning approach can greatly help with the drug discovery process. We also compare the performance of DeepBindRG with a 4D based deep learning method “pafnucy”, the advantage and limitation of both methods have provided clues for improving the deep learning based protein–ligand prediction model in the future.

ATP binds and inhibits the neurodegeneration-associated fibrillization of the FUS RRM domain

Adenosine triphosphate (ATP) provides energy for cellular processes but has recently been found to act also as a hydrotrope to maintain protein homeostasis. ATP bivalently binds the disordered domain of FUS containing the RG/RGG sequence motif and thereby affects FUS liquid-liquid phase separation. Here, using NMR spectroscopy and molecular docking studies, we report that ATP specifically binds also to the well-folded RRM domain of FUS at physiologically relevant concentrations and with the binding interface overlapping with that of its physiological ssDNA ligand. Importantly, although ATP has little effect on the thermodynamic stability of the RRM domain or its binding to ssDNA, ATP kinetically inhibits the RRM fibrillization that is critical for the gain of cytotoxicity associated with ALS and FTD. Our study provides a previously unappreciated mechanism for ATP to inhibit fibrillization by specific binding, and suggests that ATP may bind additional proteins other than the classic ATP-dependent enzymes.

Binding properties of the quaternary assembly protein SPAG1

In cells, many constituents are able to assemble resulting in large macromolecular machineries possessing very specific biological and physiological functions, e.g. ribosome, spliceosome and proteasome. Assembly of such entities is commonly mediated by transient protein factors. SPAG1 is a multidomain protein, known to participate in the assembly of both the inner and outer dynein arms. These arms are required for the function of sensitive and motile cells. Together with RUVBL1, RUVBL2 and PIH1D2, SPAG1 is a key element of R2SP, a protein complex assisting the quaternary assembly of specific protein clients in a tissue-specific manner and associating with heat shock proteins (HSPs) and regulators. In this study, we have investigated the role of TPR domains of SPAG1 in the recruitment of HSP chaperones by combining biochemical assays, ITC, NMR spectroscopy and molecular dynamics (MD) simulations. First, we propose that only two, out of the three TPR domains, are able to recruit the protein chaperones HSP70 and HSP90. We then focused on one of these TPR domains and elucidated its 3D structure using NMR spectroscopy. Relying on an NMR-driven docking approach and MD simulations, we deciphered its binding interface with the C-terminal tails of both HSP70 and HSP90. Finally, we addressed the biological function of SPAG1 and specifically demonstrated that a SPAG1 sub-fragment, containing a putative P-loop motif, cannot efficiently bind and hydrolyze GTP in vitro Our data challenge the interpretation of SPAG1 possessing GTPase activity. We propose instead that SPAG1 regulates nucleotide hydrolysis activity of the HSP and RUVBL1/2 partners.

HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy

Protein–protein and protein–DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein–protein and protein–DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10–20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein–protein and protein–DNA benchmarks and performed better than template-based modeling on the three protein–RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/.

Structural Basis of Protein Kinase Cα Regulation by the C-Terminal Tail

Protein kinase C (PKC) isoenzymes are multi-modular proteins activated at the membrane surface to regulate signal transduction processes. When activated by second messengers, PKC undergoes a drastic conformational and spatial transition from the inactive cytosolic state to the activated membrane-bound state. The complete structure of either state of PKC remains elusive. We demonstrate, using NMR spectroscopy, that the isolated Ca²⁺-sensing membrane-binding C2 domain of the conventional PKCα interacts with a conserved hydrophobic motif of the kinase C-terminal region, and we report a structural model of the complex. Our data suggest that the C-terminal region plays a dual role in regulating the PKC activity: activating, through sensitization of PKC to intracellular Ca²⁺ oscillations; and auto-inhibitory, through its interaction with a conserved positively charged region of the C2 domain.

LipidII interaction with specific residues of Mycobacterium tuberculosis PknB extracytoplasmic domain governs its optimal activation

The Mycobacterium tuberculosis kinase PknB is essential for growth and survival of the pathogen in vitro and in vivo. Here we report the results of our efforts to elucidate the mechanism of regulation of PknB activity. The specific residues in the PknB extracytoplasmic domain that are essential for ligand interaction and survival of the bacterium are identified. The extracytoplasmic domain interacts with mDAP-containing LipidII, and this is abolished upon mutation of the ligand-interacting residues. Abrogation of ligand-binding or sequestration of the ligand leads to aberrant localization of PknB. Contrary to the prevailing hypothesis, abrogation of ligand-binding is linked to activation loop hyperphosphorylation, and indiscriminate hyperphosphorylation of PknB substrates as well as other proteins, ultimately causing loss of homeostasis and cell death. We propose that the ligand-kinase interaction directs the appropriate localization of the kinase, coupled to stringently controlled activation of PknB, and consequently the downstream processes thereof.

The Mycobacterium tuberculosis kinase PknB regulates essential cell functions via interactions with muropeptides. Here the authors identify interaction sites in the extracytoplasmic PASTA domain and show that abrogation of ligand binding leads to a hyper-activated kinase, causing loss of homeostasis and cell death.

Interaction between Cellobiose Dehydrogenase and Lytic Polysaccharide Monooxygenase

Lytic polysaccharide monooxygenases (LPMOs) are ubiquitous oxidoreductases, facilitating the degradation of polymeric carbohydrates in biomass. Cellobiose dehydrogenase (CDH) is a biologically relevant electron donor in this process, with the electrons resulting from cellobiose oxidation being shuttled from the CDH dehydrogenase domain to its cytochrome domain and then to the LPMO catalytic site. In this work, we investigate the interaction of four Neurospora crassa LPMOs and five CDH cytochrome domains from different species using computational methods. We used HADDOCK to perform protein-protein docking experiments on all 20 combinations and subsequently to select four complexes for extensive molecular dynamics simulations. The potential of mean force is computed for a rotation of the cytochrome domain relative to LPMO. We find that the LPMO loops are largely responsible for the preferred orientations of the cytochrome domains. This leads us to postulate a hybrid version of NcLPMO9F, with exchanged loops and predicted altered cytochrome binding preferences for this variant. Our work provides insight into the possible mechanisms of electron transfer between the two protein systems, in agreement with and complementary to previously published experimental data.

Evaluation of Predicted Protein-Protein Complexes by Binding Free Energy Simulations

The accurate prediction of protein-protein complex geometries is of major importance to ultimately model the complete interactome of interacting proteins in a cell. A major bottleneck is the realistic free energy evaluation of predicted docked structures. Typically, simple scoring functions applied to single-complex structures are employed that neglect conformational entropy and often solvent effects completely. The binding free energy of a predicted protein-protein complex can, however, be calculated using umbrella sampling (US) along a predefined dissociation/association coordinate of a complex. We employed atomistic US-molecular dynamics simulations including appropriate conformational and axial restraints and an implicit generalized Born solvent model to calculate binding free energies of a large set of docked decoys for 20 different complexes. Free energies associated with the restraints were calculated separately. In principle, the approach includes all energetic and entropic contributions to the binding process. The evaluation of docked complexes based on binding free energy calculation was in better agreement with experiment compared to a simple scoring based on energy minimization or MD refinement using exactly the same force field description. Even calculated absolute binding free energies of structures close to the native binding geometry showed a reasonable correlation to experiment. However, still for a number of complexes docked decoys of lower free energy than near-native geometries were found indicating inaccuracies in the force field or the implicit solvent model. Although time consuming the approach may open up a new route for realistic ranking of predicted geometries based on calculated free energy of binding.

Protein-Protein Docking in Drug Design and Discovery

Protein-protein interactions (PPIs) are responsible for a number of key physiological processes in the living cells and underlie the pathomechanism of many diseases. Nowadays, along with the concept of so-called "hot spots" in protein-protein interactions, which are well-defined interface regions responsible for most of the binding energy, these interfaces can be targeted with modulators. In order to apply structure-based design techniques to design PPIs modulators, a three-dimensional structure of protein complex has to be available. In this context in silico approaches, in particular protein-protein docking, are a valuable complement to experimental methods for elucidating 3D structure of protein complexes. Protein-protein docking is easy to use and does not require significant computer resources and time (in contrast to molecular dynamics) and it results in 3D structure of a protein complex (in contrast to sequence-based methods of predicting binding interfaces). However, protein-protein docking cannot address all the aspects of protein dynamics, in particular the global conformational changes during protein complex formation. In spite of this fact, protein-protein docking is widely used to model complexes of water-soluble proteins and less commonly to predict structures of transmembrane protein assemblies, including dimers and oligomers of G protein-coupled receptors (GPCRs). In this chapter we review the principles of protein-protein docking, available algorithms and software and discuss the recent examples, benefits, and drawbacks of protein-protein docking application to water-soluble proteins, membrane anchoring and transmembrane proteins, including GPCRs.

Structure-Guided Exploration of SDS22 Interactions with Protein Phosphatase PP1 and the Splicing Factor BCLAF1

SDS22 is an ancient regulator of protein phosphatase-1 (PP1). Our crystal structure of SDS22 shows that its twelve leucine-rich repeats adopt a banana-shaped fold that is shielded from solvent by capping domains at its extremities. Subsequent modeling and biochemical studies revealed that the concave side of SDS22 likely interacts with PP1 helices α5 and α6, which are distal from the binding sites of many previously described PP1 interactors. Accordingly, we found that SDS22 acts as a "third" subunit of multiple PP1 holoenzymes. The crystal structure of SDS22 also revealed a large basic surface patch that enables binding of a phosphorylated form of splicing factor BCLAF1. Taken together, our data provide insights into the formation of PP1:SDS22 and the recruitment of additional interaction proteins, such as BCLAF1.

Distinct Interaction Sites of Rac GTPase with WAVE Regulatory Complex Have Non-redundant Functions in Vivo

Cell migration often involves the formation of sheet-like lamellipodia generated by branched actin filaments. The branches are initiated when Arp2/3 complex [1] is activated by WAVE regulatory complex (WRC) downstream of small GTPases of the Rac family [2]. Recent structural studies defined two independent Rac binding sites on WRC within the Sra-1/PIR121 subunit of the pentameric WRC [3, 4], but the functions of these sites in vivo have remained unknown. Here we dissect the mechanism of WRC activation and the in vivo relevance of distinct Rac binding sites on Sra-1, using CRISPR/Cas9-mediated gene disruption of Sra-1 and its paralog PIR121 in murine B16-F1 cells combined with Sra-1 mutant rescue. We show that the A site, positioned adjacent to the binding region of WAVE-WCA mediating actin and Arp2/3 complex binding, is the main site for allosteric activation of WRC. In contrast, the D site toward the C terminus is dispensable for WRC activation but required for optimal lamellipodium morphology and function. These results were confirmed in evolutionarily distant Dictyostelium cells. Moreover, the phenotype seen in D site mutants was recapitulated in Rac1 E31 and F37 mutants; we conclude these residues are important for Rac-D site interaction. Finally, constitutively activated WRC was able to induce lamellipodia even after both Rac interaction sites were lost, showing that Rac interaction is not essential for membrane recruitment. Our data establish that physical interaction with Rac is required for WRC activation, in particular through the A site, but is not mandatory for WRC accumulation in the lamellipodium.

Large-scale docking predicts that sORF-encoded peptides may function through protein-peptide interactions in Arabidopsis thaliana

Several recent studies indicate that small Open Reading Frames (sORFs) embedded within multiple eukaryotic non-coding RNAs can be translated into bioactive peptides of up to 100 amino acids in size. However, the functional roles of the 607 Stress Induced Peptides (SIPs) previously identified from 189 Transcriptionally Active Regions (TARs) in Arabidopsis thaliana remain unclear. To provide a starting point for functional annotation of these plant-derived peptides, we performed a large-scale prediction of peptide binding sites on protein surfaces using coarse-grained peptide docking. The docked models were subjected to further atomistic refinement and binding energy calculations. A total of 530 peptide-protein pairs were successfully docked. In cases where a peptide encoded by a TAR is predicted to bind at a known ligand or cofactor-binding site within the protein, it can be assumed that the peptide modulates the ligand or cofactor-binding. Moreover, we predict that several peptides bind at protein-protein interfaces, which could therefore regulate the formation of the respective complexes. Protein-peptide binding analysis further revealed that peptides employ both their backbone and side chain atoms when binding to the protein, forming predominantly hydrophobic interactions and hydrogen bonds. In this study, we have generated novel predictions on the potential protein-peptide interactions in A. thaliana, which will help in further experimental validation.

Structural basis, stoichiometry, and thermodynamics of binding of the chemokines KC and MIP2 to the glycosaminoglycan heparin

Keratinocyte-derived chemokine (KC or mCXCL1) and macrophage inflammatory protein 2 (MIP2 or mCXCL2) play nonredundant roles in trafficking blood neutrophils to sites of infection and injury. The functional responses of KC and MIP2 are intimately coupled to their interactions with glycosaminoglycans (GAGs). GAG interactions orchestrate chemokine concentration gradients and modulate receptor activity, which together regulate neutrophil trafficking. Here, using NMR, molecular dynamics (MD) simulations, and isothermal titration calorimetry (ITC), we characterized the molecular basis of KC and MIP2 binding to the GAG heparin. Both chemokines reversibly exist as monomers and dimers, and the NMR analysis indicates that the dimer binds heparin with higher affinity. The ITC experiments indicate a stoichiometry of two GAGs per KC or MIP2 dimer and that the enthalpic and entropic contributions vary significantly between the two chemokine-heparin complexes. NMR-based structural models of heparin-KC and heparin-MIP2 complexes reveal that different combinations of residues from the N-loop, 40s turn, β₃-strand, and C-terminal helix form a binding surface within a monomer and that both conserved residues and residues unique to a particular chemokine mediate the binding interactions. MD simulations indicate significant residue-specific differences in their contribution to binding and affinity for a given chemokine and between chemokines. On the basis of our observations that KC and MIP2 bind to GAG via distinct molecular interactions, we propose that the differences in these GAG interactions lead to differences in neutrophil recruitment and play nonoverlapping roles in resolution of inflammation.

Structural analysis of the woodland strawberry COI1-JAZ1 co-receptor for the plant hormone jasmonoyl-isoleucine

The phytohormone jasmonoyl-isoleucine (JA-Ile) regulates fundamental plant processes. Fragaria vesca, the woodland strawberry, is a model plant for the Rosaceae family, in which the JA-Ile perception is poorly understood at the molecular level. JA-Ile promotes binding of JAZ repressor to COI1 protein in Arabidopsis to activate jasmonate (JA)-dependent responses. The aim of this work was to understand the molecular basis of the interaction between the F. vesca COI1 (FvCOI1) and JAZ1 (FvJAZ1) promoted by JA-Ile using a computational approach. Multiple sequence alignments and phylogenetic analyses of amino acid sequences were performed for FvCOI1, FvJAZ1 and their ortholog sequences. 3D structures for FvCOI1 and FvJAZ1 proteins were built by methods of homology modeling, using AtCOI1-JA-Ile-AtJAZ1 as template and then they were further refined and validated by molecular dynamics (MD) simulation. A molecular docking approach along with MDS analysis were used to gain insights into the interaction between a putative degron-like sequence present in FvJAZ1 with the FvCOI1-JA-Ile complex. FvCOI1 and FvJAZ1 showed high and moderate sequence identity, respectively, with the corresponding ortholog proteins from other plant species including apple, grape, tomato and Arabidopsis. Moreover, the FvJAZ1 has a variant C-terminal IPMQRK sequence instead of the canonical LPIARR degron sequence located in the Jas domain of AtJAZ1. The MD simulation results showed that the FvCOI1-JA-Ile-FvJAZ1 complex was stable, and the IPMQRK peptide of FvJAZ1 directly interacted with FvCOI1 and JA-Ile. The present research provides novel insight into the molecular interactions among key JA-signaling components in the model plant F. vesca, being few examples of characterized JA-Ile receptors at a structural level in plants.

Structural basis for recognition of human 7SK long noncoding RNA by the La-related protein Larp7

The La and the La-related protein (LARP) superfamily is a diverse class of RNA binding proteins involved in RNA processing, folding, and function. Larp7 binds to the abundant long noncoding 7SK RNA and is required for 7SK ribonucleoprotein (RNP) assembly and function. The 7SK RNP sequesters a pool of the positive transcription elongation factor b (P-TEFb) in an inactive state; on release, P-TEFb phosphorylates RNA Polymerase II to stimulate transcription elongation. Despite its essential role in transcription, limited structural information is available for the 7SK RNP, particularly for protein-RNA interactions. Larp7 contains an N-terminal La module that binds UUU-3'OH and a C-terminal atypical RNA recognition motif (xRRM) required for specific binding to 7SK and P-TEFb assembly. Deletion of the xRRM is linked to gastric cancer in humans. We report the 2.2-Å X-ray crystal structure of the human La-related protein group 7 (hLarp7) xRRM bound to the 7SK stem-loop 4, revealing a unique binding interface. Contributions of observed interactions to binding affinity were investigated by mutagenesis and isothermal titration calorimetry. NMR 13C spin relaxation data and comparison of free xRRM, RNA, and xRRM-RNA structures show that the xRRM is preordered to bind a flexible loop 4. Combining structures of the hLarp7 La module and the xRRM-7SK complex presented here, we propose a structural model for Larp7 binding to the 7SK 3' end and mechanism for 7SK RNP assembly. This work provides insight into how this domain contributes to 7SK recognition and assembly of the core 7SK RNP.

Development of a new benchmark for assessing the scoring functions applicable to protein–protein interactions

Aim: Scoring functions are important component of protein–protein docking methods. They need to be evaluated on high-quality benchmarks to reveal their strengths and weaknesses. Evaluation results obtained on such benchmarks can provide valuable guidance for developing more advanced scoring functions. Methodology & results: In our comparative assessment of scoring functions for protein–protein interactions benchmark, the performance of a scoring function was characterized by ‘docking power’ and ‘scoring power’. A high-quality dataset of 273 protein–protein complexes was compiled and employed in both tests. Four scoring functions, including FASTCONTACT, ZRANK, dDFIRE and ATTRACT were tested as demonstration. ZRANK and ATTRACT exhibited encouraging performance in the docking power test. However, all four scoring functions failed badly in the scoring power test. Conclusion: Our comparative assessment of scoring functions for protein–protein interaction benchmark is created especially for assessing the scoring functions applicable to protein–protein interactions. It is different from other benchmarks for assessing protein–protein docking methods. Our benchmark is available to the public at www.pdbbind-cn.org/download/CASF-PPI/ .

Reducing Mutant Huntingtin Protein Expression in Living Cells by a Newly Identified RNA CAG Binder

Expanded CAG trinucleotide repeats in Huntington's disease (HD) are causative for neurotoxicity. The mutant CAG repeat RNA encodes neurotoxic polyglutamine proteins and can lead to a toxic gain of function by aberrantly recruiting RNA-binding proteins. One of these is the MID1 protein, which induces aberrant Huntingtin (HTT) protein translation upon binding. Here we have identified a set of CAG repeat binder candidates by in silico methods. One of those, furamidine, reduces the level of binding of HTT mRNA to MID1 and other target proteins in vitro. Metadynamics calculations, fairly consistent with experimental data measured here, provide hints about the binding mode of the ligand. Importantly, furamidine also decreases the protein level of HTT in a HD cell line model. This shows that small molecules masking RNA-MID1 interactions may be active against mutant HTT protein in living cells.

Prediction of spacer-α6 complex: a novel insight into binding of ADAMTS13 with A2 domain of von Willebrand factor under forces

Force-regulated cleavage of A2 domain of von Willebrand factor (vWF) by ADAMTS13 is a key event in preventing thrombotic thrombocytopenic purpura (TTP). Recognition and cleavage depend on cooperative and modular contacts between several ADAMTS13 subdomains and discrete segments of vWF A2 domain. Spacer domain of ADAMTS13 contains an important exosite interacting with α6 helix of unfold A2 domain, but it remains unclear whether stretching of α6 regulates binding to spacer. To understand the molecular mechanism underlying the interactions between spacer and α6 under stretching, we successfully predicted spacer-α6 complex by a novel computer strategy combined the steered molecular dynamics (SMD) and flexible docking techniques. This strategy included three steps: (1) constant-velocity SMD simulation of α6; (2) zero-velocity SMD simulations of α6, and (3) flexible dockings of α6 to spacer. In our spacer-α6 complex model, 13 key residues, six in α6 and seven in spacer, were identified. Our data demonstrated a biphasic extension-regulated binding of α6 to spacer. The binding strength of the complex increased with α6 extension until it reaches its optimum of 0.25 nm, and then decreased as α6 extension further increased, meaning that spacer is in favor to binding with a partially extended α6, which may contribute to the optimal contact and proteolysis. Changes of interface area and intermolecular salt bridge may serve as the molecular basis for this characteristic. These findings provide a novel insight into mechano-chemical regulation on interaction between ADAMTS13 and vWF A2 domain under forces.

Modeling the Early Stages of Phase Separation in Disordered Elastin-like Proteins

Elastin-like proteins (ELPs) are known to undergo liquid-liquid phase separation reversibly above a concentration-dependent transition temperature. Previous studies suggested that, as temperature increases, ELPs experience an increased propensity for type II β-turns. However, how the ELPs behave below the phase transition temperature itself is still elusive. Here, we investigate the importance of β-turn formation during the early stages of ELP self-association. We examined the behavior of two ELPs, a 150-repeat construct that had been investigated previously (ELP[V5G3A2-150] as well as a new 40-repeat construct (ELP40) suitable for nuclear magnetic resonance measurements. Structural analysis of ELP40 reveals a disordered conformation, and chemical shifts throughout the sequence are insensitive to changes in temperature over 20°C. However, a low population of β-turn conformation cannot be ruled out based on chemical shifts alone. To examine the structural consequences of β-turns in ELPs, a series of structural ensembles of ELP[V5G3A2-150] were generated, incorporating differing amounts of β-turn bias throughout the chain. To mimic the early stages of the phase change, two monomers were paired, assuming preferential interaction at β-turn regions. This approach was justified by the observation that buried hydrophobic turns are commonly observed to interact in the Protein Data Bank. After dimerization, the ensemble-averaged hydrodynamic properties were calculated for each degree of β-turn bias, and the results were compared with analytical ultracentrifugation experiments at various temperatures. We find that the temperature dependence of the sedimentation coefficient (s20,wo) can be reproduced by increasing the β-turn content in the structural ensemble. This analysis allows us to estimate the presence of β-turns and weak associations under experimental conditions. Because disordered proteins frequently exhibit weak biases in secondary structure propensity, these experimentally-driven ensemble calculations may complement existing methods for modeling disordered proteins generally.

Cytochrome c speeds up caspase cascade activation by blocking 14-3-3ε-dependent Apaf-1 inhibition

Apoptosis is a highly regulated form of programmed cell death, essential to the development and homeostasis of multicellular organisms. Cytochrome c is a central figure in the activation of the apoptotic intrinsic pathway, thereby activating the caspase cascade through its interaction with Apaf-1. Our recent studies have revealed 14-3-3ε (a direct inhibitor of Apaf-1) as a cytosolic cytochrome c target. Here we explore the cytochrome c / 14-3-3ε interaction and show the ability of cytochrome c to block 14-3-3ε-mediated Apaf-1 inhibition, thereby unveiling a novel function for cytochrome c as an indirect activator of caspase-9/3. We have used calorimetry, NMR spectroscopy, site mutagenesis and computational calculations to provide an insight into the structural features of the cytochrome c / 14-3-3ε complex. Overall, these findings suggest an additional cytochrome c-mediated mechanism to modulate apoptosome formation, shedding light onto the rigorous apoptotic regulation network.

Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data

This protocol describes a workflow for creating structural models of proteins or protein complexes using distance restraints derived from cross-linking mass spectrometry experiments. The distance restraints are used (i) to adjust preliminary models that are calculated on the basis of a homologous template and primary sequence, and (ii) to select the model that is in best agreement with the experimental data. In the case of protein complexes, the cross-linking data are further used to dock the subunits to one another to generate models of the interacting proteins. Predicting models in such a manner has the potential to indicate multiple conformations and dynamic changes that occur in solution. This modeling protocol is compatible with many cross-linking workflows and uses open-source programs or programs that are free for academic users and do not require expertise in computational modeling. This protocol is an excellent additional application with which to use cross-linking results for building structural models of proteins. The established protocol is expected to take 6-12 d to complete, depending on the size of the proteins and the complexity of the cross-linking data.

The Structure of the Biofilm-controlling Response Regulator BfmR from Acinetobacter baumannii Reveals Details of Its DNA-binding Mechanism

The rise of drug-resistant bacterial infections coupled with decreasing antibiotic efficacy poses a significant challenge to global health care. Acinetobacter baumannii is an insidious, emerging bacterial pathogen responsible for severe nosocomial infections aided by its ability to form biofilms. The response regulator BfmR, from the BfmR/S two-component system, is the master regulator of biofilm initiation in A. baumannii and is a tractable therapeutic target. Here we present the structure of A. baumannii BfmR using a hybrid approach combining X-ray crystallography, nuclear magnetic resonance spectroscopy, chemical crosslinking mass spectrometry, and molecular modeling. We also show that BfmR binds the previously proposed bfmRS promoter sequence with moderate affinity. While BfmR shares many traits with other OmpR/PhoB family response regulators, some unusual properties were observed. Most importantly, we observe that when phosphorylated, BfmR binds this promoter sequence with a lower affinity than when not phosphorylated. All other OmpR/PhoB family members studied to date show an increase in DNA-binding affinity upon phosphorylation. Understanding the structural and biochemical mechanisms of BfmR will aid in the development of new antimicrobial therapies.

NMR Spectroscopy to Study MAP Kinase Binding to MAP Kinase Phosphatases

NMR spectroscopy and other solution methods are increasingly being used to obtain novel insights into the mechanisms by which MAPK regulatory proteins bind and direct the activity of MAPKs. Here, we describe how interactions between the MAPK p38α and its regulatory proteins are studied using NMR spectroscopy, isothermal titration calorimetry, and small angle X-ray scattering (SAXS).

Functional and DNA-protein binding studies of WRKY transcription factors and their expression analysis in response to biotic and abiotic stress in wheat (Triticum aestivum L.)

WRKY, a plant-specific transcription factor family, plays vital roles in pathogen defense, abiotic stress, and phytohormone signalling. Little is known about the roles and function of WRKY transcription factors in response to rust diseases in wheat. In the present study, three TaWRKY genes encoding complete protein sequences were cloned. They belonged to class II and III WRKY based on the number of WRKY domains and the pattern of zinc finger structures. Twenty-two DNA-protein binding docking complexes predicted stable interactions of WRKY domain with W-box. Quantitative real-time-PCR using wheat near-isogenic lines with or without Lr28 gene revealed differential up- or down-regulation in response to biotic and abiotic stress treatments which could be responsible for their functional divergence in wheat. TaWRKY62 was found to be induced upon treatment with JA, MJ, and SA and reduced after ABA treatments. Maximum induction of six out of seven genes occurred at 48 h post inoculation due to pathogen inoculation. Hence, TaWRKY (49, 50, 52, 55, 57, and 62) can be considered as potential candidate genes for further functional validation as well as for crop improvement programs for stress resistance. The results of the present study will enhance knowledge towards understanding the molecular basis of mode of action of WRKY transcription factor genes in wheat and their role during leaf rust pathogenesis in particular.

Identification and characterization of a novel zebrafish (Danio rerio) pentraxin-carbonic anhydrase

Background

Carbonic anhydrases (CAs) are ubiquitous, essential enzymes which catalyze the conversion of carbon dioxide and water to bicarbonate and H⁺ ions. Vertebrate genomes generally contain gene loci for 15–21 different CA isoforms, three of which are enzymatically inactive. CA VI is the only secretory protein of the enzymatically active isoforms. We discovered that non-mammalian CA VI contains a C-terminal pentraxin (PTX) domain, a novel combination for both CAs and PTXs.

Methods

We isolated and sequenced zebrafish (Danio rerio) CA VI cDNA, complete with the sequence coding for the PTX domain, and produced the recombinant CA VI–PTX protein. Enzymatic activity and kinetic parameters were measured with a stopped-flow instrument. Mass spectrometry, analytical gel filtration and dynamic light scattering were used for biophysical characterization. Sequence analyses and Bayesian phylogenetics were used in generating hypotheses of protein structure and CA VI gene evolution. A CA VI–PTX antiserum was produced, and the expression of CA VI protein was studied by immunohistochemistry. A knock-down zebrafish model was constructed, and larvae were observed up to five days post-fertilization (dpf). The expression of ca6 mRNA was quantitated by qRT-PCR in different developmental times in morphant and wild-type larvae and in different adult fish tissues. Finally, the swimming behavior of the morphant fish was compared to that of wild-type fish.

Results

The recombinant enzyme has a very high carbonate dehydratase activity. Sequencing confirms a 530-residue protein identical to one of the predicted proteins in the Ensembl database (ensembl.org). The protein is pentameric in solution, as studied by gel filtration and light scattering, presumably joined by the PTX domains. Mass spectrometry confirms the predicted signal peptide cleavage and disulfides, and N-glycosylation in two of the four observed glycosylation motifs. Molecular modeling of the pentamer is consistent with the modifications observed in mass spectrometry. Phylogenetics and sequence analyses provide a consistent hypothesis of the evolutionary history of domains associated with CA VI in mammals and non-mammals. Briefly, the evidence suggests that ancestral CA VI was a transmembrane protein, the exon coding for the cytoplasmic domain was replaced by one coding for PTX domain, and finally, in the therian lineage, the PTX-coding exon was lost. We knocked down CA VI expression in zebrafish embryos with antisense morpholino oligonucleotides, resulting in phenotype features of decreased buoyancy and swim bladder deflation in 4 dpf larvae.

Discussion

These findings provide novel insights into the evolution, structure, and function of this unique CA form.

Computational Model and Dynamics of Monomeric Full-Length APOBEC3G

APOBEC3G (A3G) is a restriction factor that provides innate immunity against HIV-1 in the absence of viral infectivity factor (Vif) protein. However, structural information about A3G, which can aid in unraveling the mechanisms that govern its interactions and define its antiviral activity, remains unknown. Here, we built a computer model of a full-length A3G using docking approaches and molecular dynamics simulations, based on the available X-ray and NMR structural data for the two protein domains. The model revealed a large-scale dynamics of the A3G monomer, as the two A3G domains can assume compact forms or extended dumbbell type forms with domains visibly separated from each other. To validate the A3G model, we performed time-lapse high-speed atomic force microscopy (HS-AFM) experiments enabling us to get images of a fully hydrated A3G and to directly visualize its dynamics. HS-AFM confirmed that A3G exists in two forms, a globular form (∼84% of the time) and a dumbbell form (∼16% of the time), and can dynamically switch from one form to the other. The obtained HS-AFM results are in line with the computer modeling, which demonstrates a similar distribution between two forms. Furthermore, our simulations capture the complete process of A3G switching from the DNA-bound state to the closed state. The revealed dynamic nature of monomeric A3G could aid in target recognition including scanning for cytosine locations along the DNA strand and in interactions with viral RNA during packaging into HIV-1 particles.