Changes in protein structure at the interface accompanying complex formation

LAFEM: A Scoring Model to Evaluate Functional Landscape of Lysine Acetylome

Protein lysine acetylation is a critical post-translational modification involved in a wide range of biological processes. To date, about 20,000 acetylation sites of Homo sapiens were identified through mass spectrometry-based proteomic technology, but more than 95% of them have unclear functional annotations because of the lack of existing prioritization strategy to assess the functional importance of the acetylation sites on large scale. Hence, we established a lysine acetylation functional evaluating model (LAFEM) by considering eight critical features surrounding lysine acetylation site to high-throughput estimate the functional importance of given acetylation sites. This was achieved by selecting one of the random forest models with the best performance in 10-fold cross-validation on undersampled training dataset. The global analysis demonstrated that the molecular environment of acetylation sites with high acetylation functional scores (AFSs) mainly had the features of larger solvent-accessible surface area, stronger hydrogen bonding-donating abilities, near motif and domain, higher homology, and disordered degree. Importantly, LAFEM performed well in validation dataset and acetylome, showing good accuracy to screen out fitness directly relevant acetylation sites and assisting to explain the core reason for the difference between biological models from the perspective of acetylome. We further used cellular experiments to confirm that, in nuclear casein kinase and cyclin-dependent kinase substrate 1, acetyl-K35 with higher AFS was more important than acetyl-K9 with lower AFS in the proliferation of A549 cells. LAFEM provides a prioritization strategy to large scale discover the fitness directly relevant acetylation sites, which constitutes an unprecedented resource for better understanding of functional acetylome.

MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations

Protein-protein interactions play a ubiquitous role in biological function. Knowledge of the three-dimensional (3D) structures of the complexes they form is essential for understanding the structural basis of those interactions and how they orchestrate key cellular processes. Computational docking has become an indispensable alternative to the expensive and time-consuming experimental approaches for determining the 3D structures of protein complexes. Despite recent progress, identifying near-native models from a large set of conformations sampled by docking-the so-called scoring problem-still has considerable room for improvement. We present MetaScore, a new machine-learning-based approach to improve the scoring of docked conformations. MetaScore utilizes a random forest (RF) classifier trained to distinguish near-native from non-native conformations using their protein-protein interfacial features. The features include physicochemical properties, energy terms, interaction-propensity-based features, geometric properties, interface topology features, evolutionary conservation, and also scores produced by traditional scoring functions (SFs). MetaScore scores docked conformations by simply averaging the score produced by the RF classifier with that produced by any traditional SF. We demonstrate that (i) MetaScore consistently outperforms each of the nine traditional SFs included in this work in terms of success rate and hit rate evaluated over conformations ranked among the top 10; (ii) an ensemble method, MetaScore-Ensemble, that combines 10 variants of MetaScore obtained by combining the RF score with each of the traditional SFs outperforms each of the MetaScore variants. We conclude that the performance of traditional SFs can be improved upon by using machine learning to judiciously leverage protein-protein interfacial features and by using ensemble methods to combine multiple scoring functions.

Mixed mechanism of conformational selection and induced fit as a molecular recognition process in the calreticulin family of proteins

The fundamental question on the mechanism of molecular recognition during ligand binding has attracted a lot of scientific scrutiny. The two competing theories of ligand binding-"induced fit" and "conformational selection" have been proposed to explain biomolecular recognition. Since exploring a family of proteins with similar structural architectures and conserved functional roles can provide valuable insight into the significance of molecular structure and function, we performed molecular dynamics simulations on the calreticulin family of proteins, which specifically recognize monoglucosylated N-glycan during the protein folding process. Atomistic simulations of lectins in free and bound forms demonstrated that they exist in several conformations spanning from favorable to unfavorable for glycan binding. Our analysis was confined to the carbohydrate recognition domain (CRD) of these lectins to demonstrate the degree of conservation in protein sequence and structure and relate them with their function. Furthermore, we computed the lectin-glycan binding affinity using the mmPBSA approach to identify the most favorable lectin conformation for glycan binding and compared the molecular interaction fields in terms of noncovalent bond interactions. We also demonstrated the involvement of Tyr and Trp residues in the CRD with the non-reducing end glucose and central mannose residues, which contribute to some of the specific interactions. Furthermore, we analyzed the conformational changes in the CRD through SASA, RMSFs and protein surface topography mapping of electrostatic and hydrophobic potentials. Our findings demonstrate a hybrid mechanism of molecular recognition, initially driven by conformational selection followed by glycan-induced fluctuations in the key residues to strengthen the glycan binding interactions.

PP2A is activated by cytochrome c upon formation of a diffuse encounter complex with SET/TAF-Iβ

Intrinsic protein flexibility is of overwhelming relevance for intermolecular recognition and adaptability of highly dynamic ensemble of complexes, and the phenomenon is essential for the understanding of numerous biological processes. These conformational ensembles-encounter complexes-lack a unique organization, which prevents the determination of well-defined high resolution structures. This is the case for complexes involving the oncoprotein SET/template-activating factor-Iβ (SET/TAF-Iβ), a histone chaperone whose functions and interactions are significantly affected by its intrinsic structural plasticity. Besides its role in chromatin remodeling, SET/TAF-Iβ is an inhibitor of protein phosphatase 2A (PP2A), which is a key phosphatase counteracting transcription and signaling events controlling the activity of DNA damage response (DDR) mediators. During DDR, SET/TAF-Iβ is sequestered by cytochrome c (Cc) upon migration of the hemeprotein from mitochondria to the cell nucleus. Here, we report that the nuclear SET/TAF-Iβ:Cc polyconformational ensemble is able to activate PP2A. In particular, the N-end folded, globular region of SET/TAF-Iβ (a.k.a. SET/TAF-Iβ ΔC)-which exhibits an unexpected, intrinsically highly dynamic behavior-is sufficient to be recognized by Cc in a diffuse encounter manner. Cc-mediated blocking of PP2A inhibition is deciphered using an integrated structural and computational approach, combining small-angle X-ray scattering, electron paramagnetic resonance, nuclear magnetic resonance, calorimetry and molecular dynamics simulations.

Effect of gold nanoparticles on the structure and neuroprotective function of protein L-isoaspartyl methyltransferase (PIMT)

Fibrillation of peptides and proteins is implicated in various neurodegenerative diseases and is a global concern. Aging leads to the formation of abnormal isoaspartate (isoAsp) residues from isomerization of normal aspartates in proteins, triggering fibril formation that leads to neurodegenerative diseases. Protein L-isoaspartyl methyltransferase (PIMT) is a repair enzyme which recognizes and converts altered isoAsp residues back to normal aspartate. Here we report the effect of gold nanoparticles (AuNPs) of different sizes on the structure and function of PIMT. Spherical AuNPs, viz. AuNS5, AuNS50 and AuNS100 (the number indicating the diameter in nm) stabilize PIMT, with AuNS100 exhibiting the best efficacy, as evident from various biophysical experiments. Isothermal titration calorimetry (ITC) revealed endothermic, but entropy driven mode of binding of PIMT with all the three AuNSs. Methyltransferase activity assay showed enhanced activity of PIMT in presence of all AuNSs, the maximum being with AuNS100. The efficacy of PIMT in presence of AuNS100 was further demonstrated by the reduction of fibrillation of Aβ42, the peptide that is implicated in Alzheimer's disease. The enhancement of anti-fibrillation activity of PIMT with AuNS100 was confirmed from cell survival assay with PC12 derived neuronal cells against Aβ42 induced neurotoxicity.

MENSAdb: a thorough structural analysis of membrane protein dimers

Membrane proteins (MPs) are key players in a variety of different cellular processes and constitute the target of around 60% of all Food and Drug Administration-approved drugs. Despite their importance, there is still a massive lack of relevant structural, biochemical and mechanistic information mainly due to their localization within the lipid bilayer. To help fulfil this gap, we developed the MEmbrane protein dimer Novel Structure Analyser database (MENSAdb). This interactive web application summarizes the evolutionary and physicochemical properties of dimeric MPs to expand the available knowledge on the fundamental principles underlying their formation. Currently, MENSAdb contains features of 167 unique MPs (63% homo- and 37% heterodimers) and brings insights into the conservation of residues, accessible solvent area descriptors, average B-factors, intermolecular contacts at 2.5 Å and 4.0 Å distance cut-offs, hydrophobic contacts, hydrogen bonds, salt bridges, π-π stacking, T-stacking and cation-π interactions. The regular update and organization of all these data into a unique platform will allow a broad community of researchers to collect and analyse a large number of features efficiently, thus facilitating their use in the development of prediction models associated with MPs. Database URL: http://www.moreiralab.com/resources/mensadb.

Assessment of structural protein expression by FTIR and biochemical assays as biomarkers of metabolites response in gastric and colon cancer

Colon and gastric cancers are the widespread benign types of cancers which are synchronous and metachronous neoplasms. In terms of the progression and progress of the disease, metabolic processes and differentiation in protein structures have an important role in for treatment of the disease. In this study we proposed to investigate the metabolic process and the differentiation of protein secondary structure among colon and gastric cancer as well as healthy controls using biochemistry and Fourier Transform InfraRed spectroscopy (FTIR) methods. For this purpose, we measured blood serum of 133 patients, which were conducted upon oncology department (45 colon cancer, 45 gastric cancer and 43 control individuals). The obtained spectroscopic results and biochemical assays showed significant reduction in the amount of functional groups in cancer groups contrary with total protein measurements and structure of protein differences between colon and gastric cancers. Differentiations were visible in serum levels of CEA, CA-125, CA-15-3, CA-19-9 AFP (Alpha fetoprotein) of gastric and colon cancer patients as well as in amide III and secondly described amide I regions. Our findings suggest that amide I bonds in colon cancer cells can be helpful in diagnosis of colon cancer. Indeed, our results showed that metabolic processes were higher in gastric cancer group than in colon cancer. Hence, FTIR spectroscopy and curve-fitting analysis of amide I profile can be successfully applied as tools for identifying quantitative and qualitative changes of proteins in human cancerous blood serum. However, what is very important, in PCA analysis we see, that the scatter plot of PC1 (variability 80%) and PC2 (variability 15%) show that the data related to the control and two cancer groups are clustered together with different magnitudes and directions.

Structural characterization of a PCP-R didomain from an archaeal nonribosomal peptide synthetase reveals novel interdomain interactions

Nonribosomal peptide synthetases (NRPSs) are multimodular enzymes that produce a wide range of bioactive peptides, such as siderophores, toxins, and antibacterial and insecticidal agents. NRPSs are dynamic proteins characterized by extensive interdomain communications as a consequence of their assembly-line mode of synthesis. Hence, crystal structures of multidomain fragments of NRPSs have aided in elucidating crucial interdomain interactions that occur during different steps of the NRPS catalytic cycle. One crucial yet unexplored interaction is that between the reductase (R) domain and the peptide carrier protein (PCP) domain. R domains are members of the short-chain dehydrogenase/reductase family and function as termination domains that catalyze the reductive release of the final peptide product from the terminal PCP domain of the NRPS. Here, we report the crystal structure of an archaeal NRPS PCP-R didomain construct. This is the first NRPS R domain structure to be determined together with the upstream PCP domain and is also the first structure of an archaeal NRPS to be reported. The structure reveals that a novel helix-turn-helix motif, found in NRPS R domains but not in other short-chain dehydrogenase/reductase family members, plays a major role in the interface between the PCP and R domains. The information derived from the described PCP-R interface will aid in gaining further mechanistic insights into the peptide termination reaction catalyzed by the R domain and may have implications in engineering NRPSs to synthesize novel peptide products.

Recombinant Enterovirus 71 Viral Protein 1 Fused to a Truncated Newcastle Disease Virus NP (NPt) Carrier Protein

Enterovirus 71 (EV71) is the major causative agent in hand, foot, and mouth disease (HFMD), and it mainly infects children worldwide. Despite the risk, there is no effective vaccine available for this disease. Hence, a recombinant protein construct of truncated nucleocapsid protein viral protein 1 (NPt-VP1_198–297), which is capable of inducing neutralizing antibody against EV71, was evaluated in a mouse model. Truncated nucleocapsid protein Newcastle disease virus that was used as immunological carrier fused to VP1 of EV71 as antigen. The recombinant plasmid carrying corresponding genes was constructed by recombinant DNA technology and the corresponding protein was produced in Escherichia coli expression system. The recombinant NPt-VP1_198–297 protein had elicited neutralizing antibodies against EV71 with the titer of 1:16, and this result is higher than the titer that is elicited by VP1 protein alone (1:8). It was shown that NPt containing immunogenic epitope(s) of VP1 was capable of inducing a greater functional immune response when compared to full-length VP1 protein alone. It was capable to carry larger polypeptide compared to full-length NP protein. The current study also proved that NPt-VP1_198–297 protein can be abundantly produced in recombinant protein form by E. coli expression system. The findings from this study support the importance of neutralizing antibodies in EV71 infection and highlight the potential of the recombinant NPt-VP1_198–297 protein as EV71 vaccine.

The R882H substitution in the human de novo DNA methyltransferase DNMT3A disrupts allosteric regulation by the tumor supressor p53

A myriad of protein partners modulate the activity of the human DNA methyltransferase 3A (DNMT3A), whose interactions with these other proteins are frequently altered during oncogenesis. We show here that the tumor suppressor p53 decreases DNMT3A activity by forming a heterotetramer complex with DNMT3A. Mutational and modeling experiments suggested that p53 interacts with the same region in DNMT3A as does the structurally characterized DNMT3L. We observed that the p53-mediated repression of DNMT3A activity is blocked by amino acid substitutions within this interface, but surprisingly, also by a distal DNMT3A residue, R882H. DNMT3A R882H occurs frequently in various cancers, including acute myeloid leukemia, and our results suggest that the effects of R882H and other DNMT3A mutations may go beyond changes in DNMT3A methylation activity. To further understand the dynamics of how protein-protein interactions modulate DNMT3A activity, we determined that p53 has a greater affinity for DNMT3A than for DNMT3L and that p53 readily displaces DNMT3L from the DNMT3A:DNMT3L heterotetramer. Interestingly, this occurred even when the preformed DNMT3A:DNMT3L complex was actively methylating DNA. The frequently identified p53 substitutions (R248W and R273H), whereas able to regulate DNMT3A function when forming the DNMT3A:p53 heterotetramer, no longer displaced DNMT3L from the DNMT3A:DNMT3L heterotetramer. The results of our work highlight the complex interplay between DNMT3A, p53, and DNMT3L and how these interactions are further modulated by clinically derived mutations in each of the interacting partners.

Structural changes in DNA-binding proteins on complexation

Characterization and prediction of the DNA-biding regions in proteins are essential for our understanding of how proteins recognize/bind DNA. We analyze the unbound (U) and the bound (B) forms of proteins from the protein–DNA docking benchmark that contains 66 binary protein–DNA complexes along with their unbound counterparts. Proteins binding DNA undergo greater structural changes on complexation (in particular, those in the enzyme category) than those involved in protein–protein interactions (PPI). While interface atoms involved in PPI exhibit an increase in their solvent-accessible surface area (ASA) in the bound form in the majority of the cases compared to the unbound interface, protein–DNA interactions indicate increase and decrease in equal measure. In 25% structures, the U form has missing residues which are located in the interface in the B form. The missing atoms contribute more toward the buried surface area compared to other interface atoms. Lys, Gly and Arg are prominent in disordered segments that get ordered in the interface on complexation. In going from U to B, there may be an increase in coil and helical content at the expense of turns and strands. Consideration of flexibility cannot distinguish the interface residues from the surface residues in the U form.

An account of solvent accessibility in protein-RNA recognition

Protein–RNA recognition often induces conformational changes in binding partners. Consequently, the solvent accessible surface area (SASA) buried in contact estimated from the co-crystal structures may differ from that calculated using their unbound forms. To evaluate the change in accessibility upon binding, we compare SASA of 126 protein-RNA complexes between bound and unbound forms. We observe, in majority of cases the interface of both the binding partners gain accessibility upon binding, which is often associated with either large domain movements or secondary structural transitions in RNA-binding proteins (RBPs), and binding-induced conformational changes in RNAs. At the non-interface region, majority of RNAs lose accessibility upon binding, however, no such preference is observed for RBPs. Side chains of RBPs have major contribution in change in accessibility. In case of flexible binding, we find a moderate correlation between the binding free energy and change in accessibility at the interface. Finally, we introduce a parameter, the ratio of gain to loss of accessibility upon binding, which can be used to identify the native solution among the flexible docking models. Our findings provide fundamental insights into the relationship between flexibility and solvent accessibility, and advance our understanding on binding induced folding in protein-RNA recognition.

Analysis of the interactions between GMF and Arp2/3 complex in two binding sites by molecular dynamics simulation

The Arp2/3 complex plays a key role in nucleating actin filaments branching. The glia maturation factor (GMF) competes with activators for interacting with the Arp2/3 complex and initiates the debranching of actin filaments. In this study, we performed a comparative analysis of interactions between GMF and the Arp2/3 complex and identified new amino acid residues involved in GMF binding to the Arp2/3 complex at two separate sites, revealed by X-ray and single particle EM techniques. Using molecular dynamics simulations we demonstrated the quantitative and qualitative changes in hydrogen bonds upon binding with GMF. We identified the specific amino acid residues in GMF and Arp2/3 complex that stabilize the interactions and estimated the mean force profile for the GMF using umbrella sampling. Phylogenetic and structural analyses of the recently defined GMF binding site on the Arp3 subunit indicate a new mechanism for Arp2/3 complex inactivation that involves interactions between the Arp2/3 complex and GMF at two binding sites.

Identifying and Visualizing Macromolecular Flexibility in Structural Biology

Structural biology comprises a variety of tools to obtain atomic resolution data for the investigation of macromolecules. Conventional structural methodologies including crystallography, NMR and electron microscopy often do not provide sufficient details concerning flexibility and dynamics, even though these aspects are critical for the physiological functions of the systems under investigation. However, the increasing complexity of the molecules studied by structural biology (including large macromolecular assemblies, integral membrane proteins, intrinsically disordered systems, and folding intermediates) continuously demands in-depth analyses of the roles of flexibility and conformational specificity involved in interactions with ligands and inhibitors. The intrinsic difficulties in capturing often subtle but critical molecular motions in biological systems have restrained the investigation of flexible molecules into a small niche of structural biology. Introduction of massive technological developments over the recent years, which include time-resolved studies, solution X-ray scattering, and new detectors for cryo-electron microscopy, have pushed the limits of structural investigation of flexible systems far beyond traditional approaches of NMR analysis. By integrating these modern methods with powerful biophysical and computational approaches such as generation of ensembles of molecular models and selective particle picking in electron microscopy, more feasible investigations of dynamic systems are now possible. Using some prominent examples from recent literature, we review how current structural biology methods can contribute useful data to accurately visualize flexibility in macromolecular structures and understand its important roles in regulation of biological processes.

Proteins: interaction at a distance

How do the surface side chains of a protein behave when it binds to another protein? Do they optimize interactions by crumpling inwards or by extending outwards?