Parameter optimized surfaces (POPS): analysis of key interactions and conformational changes in the ribosome

In Silico and In Vitro Analysis of IL36RN Alterations Reveals Critical Residues for the Function of the Interleukin-36 Receptor Complex

Generalized pustular psoriasis is a potentially life-threatening skin disease, associated with IL36RN disease alleles. IL36RN encodes the IL-36 receptor antagonist (IL-36Ra), a protein that downregulates the activity of IL-36 cytokines by blocking their receptor (IL-36R). Although generalized pustular psoriasis can be treated with IL-36R inhibitors, the structural underpinnings of the IL-36Ra/IL-36R interaction remain poorly understood. In this study, we sought to address this question by systematically investigating the effects of IL36RN sequence changes. We experimentally characterized the effects of 30 IL36RN variants on protein stability. In parallel, we used a machinelearning tool (Rhapsody) to analyze the IL-36Ra three-dimensional structure and predict the impact of all possible amino acid substitutions. This integrated approach identified 21 amino acids that are essential for IL-36Ra stability. We next investigated the effects of IL36RN changes on IL-36Ra/IL-36R binding and IL-36R signaling. Combining invitro assays and machine learning with a second program (mCSM), we identified 13 amino acids that are critical for IL-36Ra/IL36R engagement. Finally, we experimentally validated three representative predictions, further confirming the reliability of Rhapsody and mCSM. These findings shed light on the structural determinants of IL-36Ra activity, with potential to facilitate the design of new IL-36 inhibitors and aid the interpretation of IL36RN variants in diagnostic settings.

Identification of potential molecular mimicry in pathogen-host interactions

Pathogens have evolved sophisticated strategies to manipulate host signaling pathways, including the phenomenon of molecular mimicry, where pathogen-derived biomolecules imitate host biomolecules. In this study, we resurrected, updated, and optimized a sequence-based bioinformatics pipeline to identify potential molecular mimicry candidates between humans and 32 pathogenic species whose proteomes' 3D structure predictions were available at the start of this study. We observed considerable variation in the number of mimicry candidates across pathogenic species, with pathogenic bacteria exhibiting fewer candidates compared to fungi and protozoans. Further analysis revealed that the candidate mimicry regions were enriched in solvent-accessible regions, highlighting their potential functional relevance. We identified a total of 1,878 mimicked regions in 1,439 human proteins, and clustering analysis indicated diverse target proteins across pathogen species. The human proteins containing mimicked regions revealed significant associations between these proteins and various biological processes, with an emphasis on host extracellular matrix organization and cytoskeletal processes. However, immune-related proteins were underrepresented as targets of mimicry. Our findings provide insights into the broad range of host-pathogen interactions mediated by molecular mimicry and highlight potential targets for further investigation. This comprehensive analysis contributes to our understanding of the complex mechanisms employed by pathogens to subvert host defenses and we provide a resource to assist researchers in the development of novel therapeutic strategies.

Structure Relaxation Approximation (SRA) for Elucidation of Protein Structures from Ion Mobility Measurements (II). Protein Complexes

Characterizing structures of protein complexes and their disease-related aberrations is essential to understanding molecular mechanisms of many biological processes. Electrospray ionization coupled with hybrid ion mobility/mass spectrometry (ESI-IM/MS) methods offer sufficient sensitivity, sample throughput, and dynamic range to enable systematic structural characterization of proteomes. However, because ESI-IM/MS characterizes ionized protein systems in the gas phase, it generally remains unclear to what extent the protein ions characterized by IM/MS have retained their solution structures. Here, we discuss the first application of our computational structure relaxation approximation [Bleiholder, C.; et al. J. Phys. Chem. B 2019, 123 (13), 2756-2769] to assign structures of protein complexes in the range from ∼16 to ∼60 kDa from their "native" IM/MS spectra. Our analysis shows that the computed IM/MS spectra agree with the experimental spectra within the errors of the methods. The structure relaxation approximation (SRA) indicates that native backbone contacts appear largely retained in the absence of solvent for the investigated protein complexes and charge states. Native contacts between polypeptide chains of the protein complex appear to be retained to a comparable extent as contacts within a folded polypeptide chain. Our computations also indicate that the hallmark "compaction" often observed for protein systems in native IM/MS measurements appears to be a poor indicator of the extent to which native residue-residue interactions are lost in the absence of solvent. Further, the SRA indicates that structural reorganization of the protein systems in IM/MS measurements appears driven largely by remodeling of the protein surface that increases its hydrophobic content by approximately 10%. For the systems studied here, this remodeling of the protein surface appears to occur mainly by structural reorganization of surface-associated hydrophilic amino acid residues not associated with β-strand secondary structure elements. Properties related to the internal protein structure, as assessed by void volume or packing density, appear unaffected by remodeling of the surface. Taken together, the structural reorganization of the protein surface appears to be generic in nature and to sufficiently stabilize protein structures to render them metastable on the time scale of IM/MS measurements.

Energy Landscapes for Base-Flipping in a Model DNA Duplex

We explore the process of base-flipping for four central bases, adenine, guanine, cytosine, and thymine, in a deoxyribonucleic acid (DNA) duplex using the energy landscape perspective. NMR imino-proton exchange and fluorescence correlation spectroscopy studies have been used in previous experiments to obtain lifetimes for bases in paired and extrahelical states. However, the difference of almost 4 orders of magnitude in the base-flipping rates obtained by the two methods implies that they are exploring different pathways and possibly different open states. Our results support the previous suggestion that minor groove opening may be favored by distortions in the DNA backbone and reveal links between sequence effects and the direction of opening, i.e., whether the base flips toward the major or the minor groove side. In particular, base flipping along the minor groove pathway was found to align toward the 5' side of the backbone. We find that bases align toward the 3' side of the backbone when flipping along the major groove pathway. However, in some cases for cytosine and thymine, the base flipping along the major groove pathway also aligns toward the 5' side. The sequence effect may be caused by the polar interactions between the flipping-base and its neighboring bases on either of the strands. For guanine flipping toward the minor groove side, we find that the equilibrium constant for opening is large compared to flipping via the major groove. We find that the estimated rates of base opening, and hence the lifetimes of the closed state, obtained for thymine flipping through small and large angles along the major groove differ by 6 orders of magnitude, whereas for thymine flipping through small angles along the minor groove and large angles along the major groove, the rates differ by 3 orders of magnitude.

Accurate Estimation of Solvent Accessible Surface Area for Coarse-Grained Biomolecular Structures with Deep Learning

Coarse-grained (CG) models of biomolecules have been widely used in protein/ribonucleic acid (RNA) three-dimensional structure prediction, docking, drug design, and molecular simulations due to their superiority in computational efficiency. Most of these applications strongly depend on the reasonable estimation of solvation free energy, which requires the accurate calculation of solvent accessible surface area (SASA). Although algorithms for SASA calculations with all-atom protein and RNA structures have been well-established, accurately estimating the SASA based on CG structures is extremely challenging. In this work, we developed a deep learning-based SASA estimator (DeepCGSA), which can provide almost perfect SASA estimation based on CG structures of protein and RNA molecules. Extensive testing analysis showed that for three types of widely used CG protein models, including the Cα-based, Cα-Cβ, and Martini models, the correlation coefficients between the predicted values and the reference values can be as high as 0.95-0.99, which perform dramatically better than available methods. In addition, the new method can be used for CG RNA structures and unfolded protein structures with much improved accuracy. We anticipate that DeepCGSA will be highly useful in the protein/RNA structure prediction, drug design, and other applications, in which accurate estimations of SASA for CG biomolecular structures are critically important.

Methyltransferase Contingencies in the Pathway of Everninomicin D Antibiotics and Analogues

Everninomicins are orthoester oligosaccharide antibiotics with potent activity against multidrug-resistant bacterial pathogens. Everninomicins act by disrupting ribosomal assembly in a distinct region in comparison to clinically prescribed drugs. We employed microporous intergeneric conjugation with Escherichia coli to manipulate Micromonospora for targeted gene-replacement studies of multiple putative methyltransferases across the octasaccharide scaffold of everninomicin effecting the A₁ , C, F, and H rings. Analyses of gene-replacement and genetic complementation mutants established the mutability of the everninomicin scaffold through the generation of 12 previously unreported analogues and, together with previous results, permitted assignment of the ten methyltransferases required for everninomicin biosynthesis. The in vitro activity of A₁ - and H-ring-modifying methyltransferases demonstrated the ability to catalyze late-stage modification of the scaffold on an A₁ -ring phenol and H-ring C-4' hydroxy moiety. Together these results establish the potential of the everninomicin scaffold for modification through mutagenesis and in vitro modification of advanced biosynthetic intermediates.

A Heme Propionate Staples the Structure of Cytochrome c for Methionine Ligation to the Heme Iron

Ligand-switch reactions at the heme iron are common in biological systems, but their mechanisms and the features of the polypeptide fold that support dual ligation are not well understood. In cytochrome c (cyt c), two low-stability loops (Ω-loop C and Ω-loop D) are connected by the heme propionate HP6. At alkaline pH, the native Met80 ligand from Ω-loop D switches to a Lys residue from the same loop. Deprotonation of an as yet unknown group triggers the alkaline transition. We have created the two cyt c variants T49V/K79G and T78V/K79G with altered connections of these two loops to HP6. Electronic absorption, NMR, and EPR studies demonstrate that at pH 7.4 ferric forms of these variants are Lys-ligated, whereas ferrous forms maintain the native Met80 ligation. Measurements of protein stability, cyclic voltammetry, pH-jump and gated electron-transfer kinetics have revealed that these Thr to Val substitutions greatly affect the alkaline transition in both ferric and ferrous proteins. The substitutions modify the stability of the Met-ligated species and reduction potentials of the heme iron. The kinetics of ligand-switch processes are also altered, and analyses of these effects implicate redox-dependent differences in metal-ligand interactions and the role of the protein dynamics, including cross-talk between the two Ω-loops. With the two destabilized variants, it is possible to map energy levels for the Met- and Lys-ligated species in both ferric and ferrous proteins and assess the role of the protein scaffold in redox-dependent preferences for these two ligands. The estimated shift in the heme iron reduction potential upon deprotonation of the "trigger" group is consistent with those associated with deprotonation of an HP, suggesting that HP6, on its own or as a part of a hydrogen-bonded cluster, is a likely "trigger" for the Met to Lys ligand switch.

Glycine-induced formation and druggability score prediction of protein surface pockets

Nowadays, it is well established that most of the human diseases which are not related to pathogen infections have their origin from DNA disorders. Thus, DNA mutations, waiting for the availability of CRISPR-like remedies, will propagate into proteomics, offering the possibility to select natural or synthetic molecules to fight against the effects of malfunctioning proteins. Drug discovery, indeed, is a flourishing field of biotechnological research to improve human health, even though the development of a new drug is increasingly more expensive in spite of the massive use of informatics in Medicinal Chemistry. CRISPR technology adds new alternatives to cure diseases by removing DNA defects responsible of genome-related pathologies. In principle, the same technology, however, could also be exploited to induce protein mutations whose effects are controlled by the presence of suitable ligands. In this paper, a new idea is proposed for the realization of mutated proteins, on the surface of which more spacious transient pockets are formed and, therefore, are more suitable for hosting drugs. In particular, new allosteric sites are obtained by replacing amino-acids with bulky side chains with glycine, Gly, the smallest natural amino-acid. We also present a machine learning approach to evaluate the druggability score of new (or enlarged) pockets. Preliminary experimental results are very promising, showing that 10% of the sites created by the Gly-pipe software are druggable.

Identification of Alzheimer's Disease Autoantibodies and Their Target Biomarkers by Phage Microarrays

The characterization of the humoral response in Alzheimer's disease (AD) patients might aid in detecting the disease at early stages. We have combined phage display and protein microarrays to identify AD autoantibodies and their target biomarkers. After enrichment of the T7 phage display libraries from AD and healthy brain tissue mRNA in AD-specific phages, 1536 monoclonal phages were printed on microarrays to probe them with 8 AD and 8 healthy control sera. A total of 57 phages showed higher seroreactivity in AD. In total, 13 out of the 44 unique sequences displayed on the phages were selected for validation using 68 AD and 52 healthy control sera. Peptides from Anthrax toxin receptor 1, Nuclear protein 1, Glycogen phosphorylase, and Olfactory receptor 8J1 expressed in bacteria as HaloTag fusion proteins showed a statistically significant ability to discriminate between AD patients and controls. The identified panel of AD autoantibodies might provide new insights into the blood-based diagnosis of the disease.

Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method

Monoclonal antibodies (mAbs) have become a major class of protein therapeutics that target a spectrum of diseases ranging from cancers to infectious diseases. Similar to any protein molecule, mAbs are susceptible to chemical modifications during the manufacturing process, long-term storage, and in vivo circulation that can impair their potency. One such modification is the oxidation of methionine residues. Chemical modifications that occur in the complementarity-determining regions (CDRs) of mAbs can lead to the abrogation of antigen binding and reduce the drug's potency and efficacy. Thus, it is highly desirable to identify and eliminate any chemically unstable residues in the CDRs during the therapeutic antibody discovery process. To provide increased throughput over experimental methods, we extracted features from the mAbs' sequences, structures, and dynamics, used random forests to identify important features and develop a quantitative and highly predictive in silico methionine oxidation model.

Phosphorylated VP30 of Marburg Virus Is a Repressor of Transcription

The filoviruses Marburg virus (MARV) and Ebola virus (EBOV) cause hemorrhagic fever in humans and nonhuman primates, with high case fatality rates. MARV VP30 is known to be phosphorylated and to interact with nucleoprotein (NP), but its role in regulation of viral transcription is disputed. Here, we analyzed phosphorylation of VP30 by mass spectrometry, which resulted in identification of multiple phosphorylated amino acids. Modeling the full-length three-dimensional structure of VP30 and mapping the identified phosphorylation sites showed that all sites lie in disordered regions, mostly in the N-terminal domain of the protein. Minigenome analysis of the identified phosphorylation sites demonstrated that phosphorylation of a cluster of amino acids at positions 46 through 53 inhibits transcription. To test the effect of VP30 phosphorylation on its interaction with other MARV proteins, coimmunoprecipitation analyses were performed. They demonstrated the involvement of VP30 phosphorylation in interaction with two other proteins of the MARV ribonucleoprotein complex, NP and VP35. To identify the role of protein phosphatase 1 (PP1) in the identified effects, a small molecule, 1E7-03, targeting a noncatalytic site of the enzyme that previously was shown to increase EBOV VP30 phosphorylation was used. Treatment of cells with 1E7-03 increased phosphorylation of VP30 at a cluster of phosphorylated amino acids from Ser-46 to Thr-53, reduced transcription of MARV minigenome, enhanced binding to NP and VP35, and dramatically reduced replication of infectious MARV particles. Thus, MARV VP30 phosphorylation can be targeted for development of future antivirals such as PP1-targeting compounds. IMPORTANCE The largest outbreak of MARV occurred in Angola in 2004 to 2005 and had a 90% case fatality rate. There are no approved treatments available for MARV. Development of antivirals as therapeutics requires a fundamental understanding of the viral life cycle. Because of the close similarity of MARV to another member of Filoviridae family, EBOV, it was assumed that the two viruses have similar mechanisms of regulation of transcription and replication. Here, characterization of the role of VP30 and its phosphorylation sites in transcription of the MARV genome demonstrated differences from those of EBOV. The identified phosphorylation sites appeared to inhibit transcription and appeared to be involved in interaction with both NP and VP35 ribonucleoproteins. A small molecule targeting PP1 inhibited transcription of the MARV genome, effectively suppressing replication of the viral particles. These data demonstrate the possibility developing antivirals based on compounds targeting PP1.

Computational Design To Reduce Conformational Flexibility and Aggregation Rates of an Antibody Fab Fragment

Computationally guided semirational design has significant potential for improving the aggregation kinetics of protein biopharmaceuticals. While improvement in the global conformational stability can stabilize proteins to aggregation under some conditions, previous studies suggest that such an approach is limited, because thermal transition temperatures ( T_m) and the fraction of protein unfolded ( f_T) tend to only correlate with aggregation kinetics where the protein is incubated at temperatures approaching the T_m. This is because under these conditions, aggregation from globally unfolded protein becomes dominant. However, under native conditions, the aggregation kinetics are presumed to be dependent on local structural fluctuations or partial unfolding of the native state, which reveal regions of high propensity to form protein-protein interactions that lead to aggregation. In this work, we have targeted the design of stabilizing mutations to regions of the A33 Fab surface structure, which were predicted to be more flexible. This Fab already has high global stability, and global unfolding is not the main cause of aggregation under most conditions. Therefore, the aim was to reduce the conformational flexibility and entropy of the native protein at various locations and thus identify which of those regions has the greatest influence on the aggregation kinetics. Highly dynamic regions of structure were identified through both molecular dynamics simulation and B-factor analysis of related X-ray crystal structures. The most flexible residues were mutated into more stable variants, as predicted by Rosetta, which evaluates the ΔΔ G_ND for each potential point mutation. Additional destabilizing variants were prepared as controls to evaluate the prediction accuracy and also to assess the general influence of conformational stability on aggregation kinetics. The thermal conformational stability, and aggregation rates of 18 variants at 65 °C, were each examined at pH 4, 200 mM ionic strength, under which conditions the initial wild-type protein was <5% unfolded. Variants with decreased T_m values led to more rapid aggregation due to an increase in the fraction of protein unfolded under the conditions studied. As expected, no significant improvements were observed in the global conformational stability as measured by T_m. However, 6 of the 12 stable variants led to an increase in the cooperativity of unfolding, consistent with lower conformational flexibility and entropy in the native ensemble. Three of these had 5-11% lower aggregation rates, and their structural clustering indicated that the local dynamics of the C-terminus of the heavy chain had a role in influencing the aggregation rate.

Putative role of invariant water molecules in the X-ray structures of family G fungal endoxylanases

Fungal endo-1,4-beta-xylanases (EC3.2.1.8), because of their widespread industrial applications have become one of the most researched industrial enzymes in recent times. Despite its significance, the role of conserved water molecules in the catalytic activities and structural stability of these enzymes from the fungi have not been studied to a great extent. Our computational structural bioinformatics and MD simulation studies have identified the existence of seven invariant water molecules (IW1- IW7) and reveals the stereo-chemical and electronic consequences of those conserved water molecules in G-xylanase enzyme from eight different fungi. The buried water molecules IW1 and IW2 may have decisive roles in catalysis and may also be associated with ligand binding process of the enzyme, whereas IW3, IW4, IW5, IW6 and IW7 may be involved in stabilizing the important (H144/R145) residues through H-bonds. Possibly they are also involved in the stabilization of secondary structures and anchor to maintain its stereo-chemical architecture. Moreover, a distorted 'W' shaped signature geometry that is observed at the surface of the enzyme can be used to identify the hydrophilic centers in the electron density map of other unknown members of the family G xylanases. The results from this computational investigation could be of interest to a large number of researchers working with the xylanases.

Modeling of alcohol oxidase enzyme of Candida boidinii and in silico analysis of competitive binding of proton ionophores and FAD with enzyme

Alcohol oxidase (AOX) is an important flavin adenine dinucleotide (FAD) dependent oxidoreductase, which is responsible for converting methanol into formaldehyde and hydrogen peroxide for the growth of methylotrophic yeast Candida boidinii. Although AOX plays a crucial role in methanol catabolism, the experimental structure of AOX from Candida boidinii has not been elucidated. This study reports the first complete in silico model of AOX from C. boidinii. This paper also reports the AOX structure modeled using the threading approach, followed by structure analysis and molecular dynamics simulation. The modeled structure was compared with the aryl alcohol oxidase structure (a glucose-methanol-choline family member, pdbID: 3fim). A docking study was performed to analyze the interaction between AOX and its cofactor FAD. The AOX modeled structure also exhibited high similarity with respect to the FAD binding sites, which are the substrate binding sites as seen with 3fim. It was observed that the adenosine part of FAD was deeply buried inside AOX while the isoalloxazine ring stuck to the surface. This paper reports the interaction of selective proton ionophores (CCCP and DNP) with AOX and also reports their binding sites. These proton ionophores showed competitive binding with FAD. The occupancy of the FAD binding sites by the proton ionophore may lead to blocking of the entry of FAD and thereby disruption of AOX import into peroxisomes.

Binding Mechanism of the N-Terminal SH3 Domain of CrkII and Proline-Rich Motifs in cAbl

The N-terminal Src homology 3 (nSH3) domain of a signaling adaptor protein, CT-10 regulator of kinase II (CrkII), recognizes proline-rich motifs (PRMs) of binding partners, such as cAbl kinase. The interaction between CrkII and cAbl kinase is involved in the regulation of cell spreading, microbial pathogenesis, and cancer metastasis. Here, we report the detailed biophysical characterizations of the interactions between the nSH3 domain of CrkII and PRMs in cAbl. We identified that the nSH3 domain of CrkII binds to three PRMs in cAbl with virtually identical affinities. Structural studies, by using x-ray crystallography and NMR spectroscopy, revealed that the binding modes of all three nSH3:PRM complexes are highly similar to each other. Van 't Hoff analysis revealed that nSH3:PRM interaction is associated with favorable enthalpy and unfavorable entropy change. The combination of experimentally determined thermodynamic parameters, structure-based calculations, and (15)N NMR relaxation analysis highlights the energetic contribution of conformational entropy change upon the complex formation, and water molecules structured in the binding interface of the nSH3:PRM complex. Understanding the molecular basis of nSH3:PRM interaction will provide, to our knowledge, new insights for the rational design of small molecules targeting the interaction between CrkII and cAbl.

Geometric Potentials for Computational Protein Sequence Design

Computational protein sequence design is the rational design based on computer simulation of new protein molecules to fold to target three-dimensional structures, with the ultimate goal of designing novel functions. It requires a good understanding of the thermodynamic equilibrium properties of the protein of interest. Here, we consider the contribution of the solvent to the stability of the protein. We describe implicit solvent models, focusing on approximations of their nonpolar components using geometric potentials. We consider the surface area (SA) model in which the nonpolar solvation free energy is expressed as a sum of the contributions of all atoms, assumed to be proportional to their accessible surface areas (ASAs). We briefly review existing numerical and analytical approaches that compute the ASA. We describe in more detail the alpha shape theory as it provides a unifying mathematical framework that enables the analytical calculations of the surface area of a macromolecule represented as a union of balls.

Evidence that the Rhodopsin Kinase (GRK1) N-Terminus and the Transducin Gα C-Terminus Interact with the Same "Hydrophobic Patch" on Rhodopsin TM5

Phosphorylation of G protein-coupled receptors (GPCRs) terminates their ability to couple with and activate G proteins by increasing their affinity for arrestins. Unfortunately, detailed information regarding how GPCRs interact with the kinases responsible for their phosphorylation is still limited. Here, we purified fully functional GPCR kinase 1 (GRK1) using a rapid method and used it to gain insights into how this important kinase interacts with the GPCR rhodopsin. Specifically, we find that GRK1 uses the same site on rhodopsin as the transducin (Gt) Gtα C-terminal tail and the arrestin "finger loop", a cleft formed in the cytoplasmic face of the receptor upon activation. Our studies also show GRK1 requires two conserved residues located in this cleft (L226 and V230) that have been shown to be required for Gt activation due to their direct interactions with hydrophobic residues on the Gα C-terminal tail. Our data and modeling studies are consistent with the idea that all three proteins (Gt, GRK1, and visual arrestin) bind, at least in part, in the same site on rhodopsin and interact with the receptor through a similar hydrophobic contact-driven mechanism.

Binding interface change and cryptic variation in the evolution of protein-protein interactions

Background

Physical interactions between proteins are essential for almost all biological functions and systems. To understand the evolution of function it is therefore important to understand the evolution of molecular interactions. Of key importance is the evolution of binding specificity, the set of interactions made by a protein, since change in specificity can lead to “rewiring” of interaction networks. Unfortunately, the interfaces through which proteins interact are complex, typically containing many amino-acid residues that collectively must contribute to binding specificity as well as binding affinity, structural integrity of the interface and solubility in the unbound state.

Results

In order to study the relationship between interface composition and binding specificity, we make use of paralogous pairs of yeast proteins. Immediately after duplication these paralogues will have identical sequences and protein products that make an identical set of interactions. As the sequences diverge, we can correlate amino-acid change in the interface with any change in the specificity of binding. We show that change in interface regions correlates only weakly with change in specificity, and many variants in interfaces are functionally equivalent. We show that many of the residue replacements within interfaces are silent with respect to their contribution to binding specificity.

Conclusions

We conclude that such functionally-equivalent change has the potential to contribute to evolutionary plasticity in interfaces by creating cryptic variation, which in turn may provide the raw material for functional innovation and coevolution.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0608-1) contains supplementary material, which is available to authorized users.

Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations

Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to emulate one ATP cycle of a molecular motor, kinesin. Second, nonspecific protein-DNA binding was studied by a combination of elaborate protein and DNA models. Third, a transcription factor, p53, that contains highly fluctuating regions was simulated on two perpendicularly arranged DNA segments, addressing intersegmental transfer of p53. Fourth, we simulated structural dynamics of dinucleosomes connected by a linker DNA finding distinct types of internucleosome docking and salt-concentration-dependent compaction. Finally, we discuss many of limitations in the current approaches and future directions. Especially, more accurate electrostatic treatment and a phospholipid model that matches our CG resolutions are of immediate importance.

The putative role of some conserved water molecules in the structure and function of human transthyretin

Human transthyretin (hTTR) is a multifunctional protein that is involved in several neurodegenerative diseases. Besides the transportation of thyroxin and vitamin A, it is also involved in the proteolysis of apolipoprotein A1 and Aβ peptide. Extensive analyses of 32 high-resolution X-ray and neutron diffraction structures of hTTR followed by molecular-dynamics simulation studies using a set of 15 selected structures affirmed the presence of 44 conserved water molecules in its dimeric structure. They are found to play several important roles in the structure and function of the protein. Eight water molecules stabilize the dimeric structure through an extensive hydrogen-bonding network. The absence of some of these water molecules in highly acidic conditions (pH ≤ 4.0) severely affects the interfacial hydrogen-bond network, which may destabilize the native tetrameric structure, leading to its dissociation. Three pairs of conserved water molecules contribute to maintaining the geometry of the ligand-binding cavities. Some other water molecules control the orientation and dynamics of different structural elements of hTTR. This systematic study of the location, absence, networking and interactions of the conserved water molecules may shed some light on various structural and functional aspects of the protein. The present study may also provide some rational clues about the conserved water-mediated architecture and stability of hTTR.

Binding energies of tyrosine kinase inhibitors: Error assessment of computational methods for imatinib and nilotinib binding

The binding energies of imatinib and nilotinib to tyrosine kinase have been determined by quantum mechanical (QM) computations, and compared with literature binding energy studies using molecular mechanics (MM). The potential errors in the computational methods include these critical factors. Errors in X-ray structures such as structural distortions and steric clashes give unrealistically high van der Waals energies, and erroneous binding energies.MM optimization gives a very different configuration to the QM optimization for nilotinib, whereas the imatinib ion gives similar configurations. Solvation energies are a major component of the overall binding energy. The QM based solvent model (PCM/SMD) gives different values from those used in the implicit PBSA solvent MM models. A major error in inhibitor—kinase binding lies in the non-polar solvation terms. Solvent transfer free energies and the required empirical solvent accessible surface area factors for nilotinib and imatinib ion to give the transfer free energies have been reverse calculated. These values differ from those used in the MM PBSA studies.An intertwined desolvation—conformational binding selectivity process is a balance of thermodynamic desolvation and intramolecular conformational kinetic control.The configurational entropies (TΔS) are minor error sources.

Zinc finger oxidation of Fpg/Nei DNA glycosylases by 2-thioxanthine: biochemical and X-ray structural characterization

DNA glycosylases from the Fpg/Nei structural superfamily are base excision repair enzymes involved in the removal of a wide variety of mutagen and potentially lethal oxidized purines and pyrimidines. Although involved in genome stability, the recent discovery of synthetic lethal relationships between DNA glycosylases and other pathways highlights the potential of DNA glycosylase inhibitors for future medicinal chemistry development in cancer therapy. By combining biochemical and structural approaches, the physical target of 2-thioxanthine (2TX), an uncompetitive inhibitor of Fpg, was identified. 2TX interacts with the zinc finger (ZnF) DNA binding domain of the enzyme. This explains why the zincless hNEIL1 enzyme is resistant to 2TX. Crystal structures of the enzyme bound to DNA in the presence of 2TX demonstrate that the inhibitor chemically reacts with cysteine thiolates of ZnF and induces the loss of zinc. The molecular mechanism by which 2TX inhibits Fpg may be generalized to all prokaryote and eukaryote ZnF-containing Fpg/Nei-DNA glycosylases. Cell experiments show that 2TX can operate in cellulo on the human Fpg/Nei DNA glycosylases. The atomic elucidation of the determinants for the interaction of 2TX to Fpg provides the foundation for the future design and synthesis of new inhibitors with high efficiency and selectivity.

Design and application of implicit solvent models in biomolecular simulations

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Implicit solvent replaces explicit water by a potential of mean force.

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Popular models are SASA, VOL and Generalized Born.

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Implicit solvent is used in MD, protein modelling, folding, design, prediction and drug screening.

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Large-scale simulations allow for parametrisation via force matching.

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Application to nucleic acids and membranes is challenging.

We review implicit solvent models and their parametrisation by introducing the concepts and recent devlopments of the most popular models with a focus on parametrisation via force matching. An overview of recent applications of the solvation energy term in protein dynamics, modelling, design and prediction is given to illustrate the usability and versatility of implicit solvation in reproducing the physical behaviour of biomolecular systems. Limitations of implicit modes are discussed through the example of more challenging systems like nucleic acids and membranes.

Identification and comparative quantitation of glycation by stable isotope labeling and LC-MS

Glycation is a common modification of proteins both in vitro and in vivo. To aid identification and comparative quantitation, a method of stable isotope labeling followed by LC-MS analysis was proposed. The samples were reduced using sodium borohydride or sodium borodeuteride. Reduction of the Schiff base between the amine group and the reducing sugars resulted in a molecular weight increase of 2Da using sodium borohydride or a molecular weight increase of 3Da using sodium borodeuteride. The molecular weight difference of 1Da between peptides containing glycated lysine residue reduced using sodium borohydride or sodium borodeuteride was used to identify glycated peptides and to calculate the glycation difference between samples. The method was used to investigate glycation of a recombinant human IgG1 antibody under native and denaturing conditions. The result demonstrated a good correlation between glycation propensity of lysine residues and their solvent exposure levels.

Discovery of multiple interacting partners of gankyrin, a proteasomal chaperone and an oncoprotein--evidence for a common hot spot site at the interface and its functional relevance

Gankyrin, a non-ATPase component of the proteasome and a chaperone of proteasome assembly, is also an oncoprotein. Gankyrin regulates a variety of oncogenic signaling pathways in cancer cells and accelerates degradation of tumor suppressor proteins p53 and Rb. Therefore gankyrin may be a unique hub integrating signaling networks with the degradation pathway. To identify new interactions that may be crucial in consolidating its role as an oncogenic hub, crystal structure of gankyrin-proteasome ATPase complex was used to predict novel interacting partners. EEVD, a four amino acid linear sequence seems a hot spot site at this interface. By searching for EEVD in exposed regions of human proteins in PDB database, we predicted 34 novel interactions. Eight proteins were tested and seven of them were found to interact with gankyrin. Affinity of four interactions is high enough for endogenous detection. Others require gankyrin overexpression in HEK 293 cells or occur endogenously in breast cancer cell line- MDA-MB-435, reflecting lower affinity or presence of a deregulated network. Mutagenesis and peptide inhibition confirm that EEVD is the common hot spot site at these interfaces and therefore a potential polypharmacological drug target. In MDA-MB-231 cells in which the endogenous CLIC1 is silenced, trans-expression of Wt protein (CLIC1_EEVD) and not the hot spot site mutant (CLIC1_AAVA) resulted in significant rescue of the migratory potential. Our approach can be extended to identify novel functionally relevant protein-protein interactions, in expansion of oncogenic networks and in identifying potential therapeutic targets.

Structure and stability insights into tumour suppressor p53 evolutionary related proteins

The p53 family of genes and their protein products, namely, p53, p63 and p73, have over one billion years of evolutionary history. Advances in computational biology and genomics are enabling studies of the complexities of the molecular evolution of p53 protein family to decipher the underpinnings of key biological conditions spanning from cancer through to various metabolic and developmental disorders and facilitate the design of personalised medicines. However, a complete understanding of the inherent nature of the thermodynamic and structural stability of the p53 protein family is still lacking. This is due, to a degree, to the lack of comprehensive structural information for a large number of homologous proteins and to an incomplete knowledge of the intrinsic factors responsible for their stability and how these might influence function. Here we investigate the thermal stability, secondary structure and folding properties of the DNA-binding domains (DBDs) of a range of proteins from the p53 family using biophysical methods. While the N- and the C-terminal domains of the p53 family show sequence diversity and are normally targets for post-translational modifications and alternative splicing, the central DBD is highly conserved. Together with data obtained from Molecular Dynamics simulations in solution and with structure based homology modelling, our results provide further insights into the molecular properties of evolutionary related p53 proteins. We identify some marked structural differences within the p53 family, which could account for the divergence in biological functions as well as the subtleties manifested in the oligomerization properties of this family.

Specialized Dynamical Properties of Promiscuous Residues Revealed by Simulated Conformational Ensembles

The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein–protein interaction prediction and design methods.

Replica exchange improves sampling in low-resolution docking stage of RosettaDock

Many protein-protein docking protocols are based on a shotgun approach, in which thousands of independent random-start trajectories minimize the rigid-body degrees of freedom. Another strategy is enumerative sampling as used in ZDOCK. Here, we introduce an alternative strategy, ReplicaDock, using a small number of long trajectories of temperature replica exchange. We compare replica exchange sampling as low-resolution stage of RosettaDock with RosettaDock's original shotgun sampling as well as with ZDOCK. A benchmark of 30 complexes starting from structures of the unbound binding partners shows improved performance for ReplicaDock and ZDOCK when compared to shotgun sampling at equal or less computational expense. ReplicaDock and ZDOCK consistently reach lower energies and generate significantly more near-native conformations than shotgun sampling. Accordingly, they both improve typical metrics of prediction quality of complex structures after refinement. Additionally, the refined ReplicaDock ensembles reach significantly lower interface energies and many previously hidden features of the docking energy landscape become visible when ReplicaDock is applied.

Large-scale modelling of the divergent spectrin repeats in nesprins: giant modular proteins

Nesprin-1 and nesprin-2 are nuclear envelope (NE) proteins characterized by a common structure of an SR (spectrin repeat) rod domain and a C-terminal transmembrane KASH [Klarsicht-ANC-Syne-homology] domain and display N-terminal actin-binding CH (calponin homology) domains. Mutations in these proteins have been described in Emery-Dreifuss muscular dystrophy and attributed to disruptions of interactions at the NE with nesprins binding partners, lamin A/C and emerin. Evolutionary analysis of the rod domains of the nesprins has shown that they are almost entirely composed of unbroken SR-like structures. We present a bioinformatical approach to accurate definition of the boundaries of each SR by comparison with canonical SR structures, allowing for a large-scale homology modelling of the 74 nesprin-1 and 56 nesprin-2 SRs. The exposed and evolutionary conserved residues identify important pbs for protein-protein interactions that can guide tailored binding experiments. Most importantly, the bioinformatics analyses and the 3D models have been central to the design of selected constructs for protein expression. 1D NMR and CD spectra have been performed of the expressed SRs, showing a folded, stable, high content α-helical structure, typical of SRs. Molecular Dynamics simulations have been performed to study the structural and elastic properties of consecutive SRs, revealing insights in the mechanical properties adopted by these modules in the cell.

Urea-Water Solvation Forces on Prion Structures

Solvation forces are crucial determinants in the equilibrium between the folded and unfolded state of proteins. Particularly interesting are the solvent forces of denaturing solvent mixtures on folded and misfolded states of proteins involved in neurodegeneration. The C-terminal globular domain of the ovine prion protein (1UW3) and its analogue H2H3 in the α-rich and β-rich conformation were used as model structures to study the solvation forces in 4 M aqueous urea using molecular dynamics. The model structures display very different secondary structures and solvent exposures. Most protein atoms favor interactions with urea over interactions with water. The force difference between protein-urea and protein-water interactions correlates with hydrophobicity; i.e., urea interacts preferentially with hydrophobic atoms, in agreement with results from solvent transfer experiments. Solvent Shannon entropy maps illustrate the mobility gradient of the urea-water mixture from the first solvation shell to the bulk. Single urea molecules replace water in the first solvation shell preferably at locations of relatively high solvent entropy.

Electrostatic interactions play an essential role in the binding of oleic acid with α-lactalbumin in the HAMLET-like complex: a study using charge-specific chemical modifications

Human α-lactalbumin made lethal to tumor cells (HAMLET) and its analogs are partially unfolded protein-oleic acid (OA) complexes that exhibit selective tumoricidal activity normally absent in the native protein itself. To understand the nature of the interaction between protein and OA moieties, charge-specific chemical modifications of lysine side chains involving citraconylation, acetylation, and guanidination were employed and the biophysical and biological properties were probed. Upon converting the original positively-charged lysine residues to negatively-charged citraconyl or neutral acetyl groups, the binding of OA to protein was eliminated, as were any cytotoxic activities towards osteosarcoma cells. Retention of the positive charges by converting lysine residues to homoarginine groups (guanidination); however, yielded unchanged binding of OA to protein and identical tumoricidal activity to that displayed by the wild-type α-lactalbumin-oleic acid complex. With the addition of OA, the wild-type and guanidinated α-lactalbumin proteins underwent substantial conformational changes, such as partial unfolding, loss of tertiary structure, but retention of secondary structure. In contrast, no significant conformational changes were observed in the citraconylated and acetylated α-lactalbumins, most likely because of the absence of OA binding. These results suggest that electrostatic interactions between the positively-charged basic groups on α-lactalbumin and the negatively-charged carboxylate groups on OA molecules play an essential role in the binding of OA to α-lactalbumin and that these interactions appear to be as important as hydrophobic interactions.

Role of salt bridge dynamics in inter domain recognition of human IMPDH isoforms: an insight to inhibitor topology for isoform-II

Inosine monophosphate dehydrogenase (IMPDH) enzyme involves in the biosynthesis pathway of guanosine nucleotide. Type II isoform of the enzyme is selectively upregulated in neoplastic fast replicating lymphocytes and CML cancer cells. The hIMPDH-II is an excellent target for antileukemic agent. The detailed investigation during MD-Simulation (15 ns) of three different unliganded structures (1B3O, 1JCN and 1JR1) have clearly explored the salt bridge mediated stabilization of inter or intra domain (catalytic domains I(N), I(C) with res. Id. 28-111 and 233-504, whereas two CBS domains C₁, C₂ are 112-171 and 172-232) in IMPDH enzyme which are mostly inaccessible in their X-rays structures. The salt bridge interaction in I(N)---C₁ inter-domain of hIMPDH-I, I(N)---C₂ of IMPDH-II and C₁---I(C) of nhIMPDH-II are discriminative features among the isoforms. The I(N)---C₂ recognition in hIMPDH-II (1B3O) is missing in type-I isoform (1JCN). The salt bridge interaction D232---K238 at the surface of protein and the involvement of three conserved water molecules or the hydrophilic centers (WA²³²(OD1), WB ²³²(OD2) and W²³⁸(NZ)) to those acidic and basic residues seem to be unique in hIMPDH-II. The hydrophilic susceptibility, geometrical and electronic consequences of this salt bridge interaction could be useful to design the topology of specific inhibitor for hIMPDH-II which may not be effective for hIMPDH-I. Possibly, the aliphatic ligand containing carboxyl, amide or hydrophilic groups with flexible structure may be implicated for hIMPDH-II inhibitor design using the conserved water mimic drug design protocol.

Implicit Solvation Parameters Derived from Explicit Water Forces in Large-Scale Molecular Dynamics Simulations

Implicit solvation is a mean force approach to model solvent forces acting on a solute molecule. It is frequently used in molecular simulations to reduce the computational cost of solvent treatment. In the first instance, the free energy of solvation and the associated solvent–solute forces can be approximated by a function of the solvent-accessible surface area (SASA) of the solute and differentiated by an atom–specific solvation parameter σ_i^SASA. A procedure for the determination of values for the σ_i^SASA parameters through matching of explicit and implicit solvation forces is proposed. Using the results of Molecular Dynamics simulations of 188 topologically diverse protein structures in water and in implicit solvent, values for the σ_i^SASA parameters for atom types i of the standard amino acids in the GROMOS force field have been determined. A simplified representation based on groups of atom types σ_g^SASA was obtained via partitioning of the atom–type σ_i^SASA distributions by dynamic programming. Three groups of atom types with well separated parameter ranges were obtained, and their performance in implicit versus explicit simulations was assessed. The solvent forces are available at http://mathbio.nimr.mrc.ac.uk/wiki/Solvent_Forces.

Combinatorial complexity and compositional drift in protein interaction networks

The assembly of molecular machines and transient signaling complexes does not typically occur under circumstances in which the appropriate proteins are isolated from all others present in the cell. Rather, assembly must proceed in the context of large-scale protein-protein interaction (PPI) networks that are characterized both by conflict and combinatorial complexity. Conflict refers to the fact that protein interfaces can often bind many different partners in a mutually exclusive way, while combinatorial complexity refers to the explosion in the number of distinct complexes that can be formed by a network of binding possibilities. Using computational models, we explore the consequences of these characteristics for the global dynamics of a PPI network based on highly curated yeast two-hybrid data. The limited molecular context represented in this data-type translates formally into an assumption of independent binding sites for each protein. The challenge of avoiding the explicit enumeration of the astronomically many possibilities for complex formation is met by a rule-based approach to kinetic modeling. Despite imposing global biophysical constraints, we find that initially identical simulations rapidly diverge in the space of molecular possibilities, eventually sampling disjoint sets of large complexes. We refer to this phenomenon as "compositional drift". Since interaction data in PPI networks lack detailed information about geometric and biological constraints, our study does not represent a quantitative description of cellular dynamics. Rather, our work brings to light a fundamental problem (the control of compositional drift) that must be solved by mechanisms of assembly in the context of large networks. In cases where drift is not (or cannot be) completely controlled by the cell, this phenomenon could constitute a novel source of phenotypic heterogeneity in cell populations.

Improving your target-template alignment with MODalign

Summary: MODalign is an interactive web-based tool aimed at helping protein structure modelers to inspect and manually modify the alignment between the sequences of a target protein and of its template(s). It interactively computes, displays and, upon modification of the target-template alignment, updates the multiple sequence alignments of the two protein families, their conservation score, secondary structure and solvent accessibility values, and local quality scores of the implied three-dimensional model(s). Although it has been designed to simplify the target-template alignment step in modeling, it is suitable for all cases where a sequence alignment needs to be inspected in the context of other biological information.

Availability and implementation: Freely available on the web at http://modorama.biocomputing.it/modalign. Website implemented in HTML and JavaScript with all major browsers supported.

Contact:jan.kosinski@uniroma1.it

Protein-water interactions in MD simulations: POPS/POPSCOMP solvent accessibility analysis, solvation forces and hydration sites

The effects of solvation on molecular recognition are investigated from different perspectives, ranging from methods to analyse explicit solvent dynamical behaviour at the protein surface to methods for the implicit treatment of solvent effects associated with the conformational behaviour of biomolecules. The here presented implicit solvation method is based on an analytical approximation of the Solvent Accessible Surface Area (SASA) of solute molecules, which is computationally efficient and easy to parametrise. The parametrised SASA solvation method is discussed in the light of protein design and ligand binding studies. The POPS program for the SASA computation on single molecules and complex interfaces is described in detail. Explicit solvent behaviour is described here in the form of solvent density maps at the protein surface. We highlight the usefulness of that approach in defining the organisation of specific water molecules at functional sites and in determining hydrophobicity scores for the identification of potential interaction patches.

New functionalities in the GROMOS biomolecular simulation software

Since the most recent description of the functionalities of the GROMOS software for biomolecular simulation in 2005 many new functions have been implemented. In this article, the new functionalities that involve modified forces in a molecular dynamics (MD) simulation are described: the treatment of electronic polarizability, an implicit surface area and internal volume solvation term to calculate interatomic forces, functions for the GROMOS coarse-grained supramolecular force field, a multiplicative switching function for nonbonded interactions, adiabatic decoupling of a number of degrees of freedom with temperature or force scaling to enhance sampling, and nonequilibrium MD to calculate the dielectric permittivity or viscosity. Examples that illustrate the use of these functionalities are given.

Benchmarks for flexible and rigid transcription factor-DNA docking

BACKGROUND

Structural insight from transcription factor-DNA (TF-DNA) complexes is of paramount importance to our understanding of the affinity and specificity of TF-DNA interaction, and to the development of structure-based prediction of TF binding sites. Yet the majority of the TF-DNA complexes remain unsolved despite the considerable experimental efforts being made. Computational docking represents a promising alternative to bridge the gap. To facilitate the study of TF-DNA docking, carefully designed benchmarks are needed for performance evaluation and identification of the strengths and weaknesses of docking algorithms.

RESULTS

We constructed two benchmarks for flexible and rigid TF-DNA docking respectively using a unified non-redundant set of 38 test cases. The test cases encompass diverse fold families and are classified into easy and hard groups with respect to the degrees of difficulty in TF-DNA docking. The major parameters used to classify expected docking difficulty in flexible docking are the conformational differences between bound and unbound TFs and the interaction strength between TFs and DNA. For rigid docking in which the starting structure is a bound TF conformation, only interaction strength is considered.

CONCLUSIONS

We believe these benchmarks are important for the development of better interaction potentials and TF-DNA docking algorithms, which bears important implications to structure-based prediction of transcription factor binding sites and drug design.

Systematic classification and analysis of themes in protein-DNA recognition

Protein-DNA recognition plays a central role in the regulation of gene expression. With the rapidly increasing number of protein-DNA complex structures available at atomic resolution in recent years, a systematic, complete, and intuitive framework to clarify the intrinsic relationship between the global binding modes of these complexes is needed. In this work, we modified, extended, and applied previously defined RNA-recognition themes to describe protein-DNA recognition and used a protocol that incorporates automatic methods into manual inspection to plant a comprehensive classification tree for currently available high-quality protein-DNA structures. Further, a nonredundant (representative) data set consisting of 200 thematically diverse complexes was extracted from the leaves of the classification tree by using a locally sensitive interface comparison algorithm. On the basis of the representative data set, various physical and chemical properties associated with protein-DNA interactions were analyzed using empirical or semiempirical methods. We also examined the individual energetic components involved in protein-DNA interactions and highlighted the importance of conformational entropy, which has been almost completely ignored in previous studies of protein-DNA binding energy.

In silico phosphorylation of the autoinhibited form of p47(phox): insights into the mechanism of activation

Activation of the multicomponent enzyme NADPH oxidase requires the interaction between the tandem SH3 domain of the cytosolic subunit p47(phox) and the cytoplasmic tail of membrane-bound p22(phox). In the resting state, p47(phox) exists in an autoinhibited conformation stabilized by intramolecular contacts between the SH3 domains and an adjacent polybasic region. Phosphorylation of three serine residues, Ser(303), Ser(304), and Ser(328) within this polybasic region has been shown to be sufficient for the disruption of the intramolecular interactions thereby inducing an active state of p47(phox). This active conformation is accessible to the cytoplasmic tail of p22(phox) and initiates the formation of the membrane-bound functional enzyme complex. Molecular dynamics simulations reveal insights in the mechanism of activation of the autoinhibited form of p47(phox) by in silico phosphorylation, of the three serine residues, Ser(303), Ser(304), and Ser(328). The simulations highlight the major collective coordinates generating the opening and the closing of the two SH3 domains and the residues that cause the unmasking of the p22(phox) binding site.

Molecular crowding stabilizes folded RNA structure by the excluded volume effect

Crowder molecules in solution alter the equilibrium between folded and unfolded states of biological macromolecules. It is therefore critical to account for the influence of these other molecules when describing the folding of RNA inside the cell. Small angle X-ray scattering experiments are reported on a 64 kDa bacterial group I ribozyme in the presence of polyethylene-glycol 1000 (PEG-1000), a molecular crowder with an average molecular weight of 1000 Da. In agreement with expected excluded volume effects, PEG favors more compact RNA structures. First, the transition from the unfolded to the folded (more compact) state occurs at lower MgCl(2) concentrations in PEG. Second, the radius of gyration of the unfolded RNA decreases from 76 to 64 A as the PEG concentration increases from 0 to 20% wt/vol. Changes to water and ion activities were measured experimentally, and theoretical models were used to evaluate the excluded volume. We conclude that the dominant influence of the PEG crowder on the folding process is the excluded volume effect.