Intra and Inter-Molecular Communications Through Protein Structure Network

Chokepoints in Mechanical Coupling Associated with Allosteric Proteins: The Pyruvate Kinase Example

Although the critical role of allostery in controlling enzymatic processes is well appreciated, there is a current dearth in our understanding of its underlying mechanisms, including communication between binding sites. One potential key aspect of intersite communication is the mechanical coupling between residues in a protein. Here, we introduce a graph-based computational approach to investigate the mechanical coupling between distant parts of a protein, highlighting effective pathways via which protein motion can transfer energy between sites. In this method, each residue is treated as a node on a weighted, undirected graph, in which the edges are defined by locally correlated motions of those residues and weighted by the strength of the correlation. The method was validated against experimental data on allosteric regulation in the human liver pyruvate kinase as obtained from full-protein alanine-scanning mutagenesis (systematic mutation) studies, as well as computational data on two G-protein-coupled receptors. The method provides semiquantitative information on the regulatory importance of specific structural elements. It is shown that these elements are key for the mechanical coupling between distant parts of the protein by providing effective pathways for energy transfer. It is also shown that, although there are a multitude of energy transfer pathways between distant parts of a protein, these pathways share a few common nodes that represent effective "chokepoints" for the communication.

Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications

Proteins are dynamical entities that undergo a plethora of conformational changes, accomplishing their biological functions. Molecular dynamics simulation and normal mode analysis methods have become the gold standard for studying protein dynamics, analyzing molecular mechanism and allosteric regulation of biological systems. The enormous amount of the ensemble-based experimental and computational data on protein structure and dynamics has presented a major challenge for the high-throughput modeling of protein regulation and molecular mechanisms. In parallel, bioinformatics and systems biology approaches including genomic analysis, coevolution and network-based modeling have provided an array of powerful tools that complemented and enriched biophysical insights by enabling high-throughput analysis of biological data and dissection of global molecular signatures underlying mechanisms of protein function and interactions in the cellular environment. These developments have provided a powerful interdisciplinary framework for quantifying the relationships between protein dynamics and allosteric regulation, allowing for high-throughput modeling and engineering of molecular mechanisms. Here, we review fundamental advances in protein dynamics, network theory and coevolutionary analysis that have provided foundation for rapidly growing computational tools for modeling of allosteric regulation. We discuss recent developments in these interdisciplinary areas bridging computational biophysics and network biology, focusing on promising applications in allosteric regulations, including the investigation of allosteric communication pathways, protein–DNA/RNA interactions and disease mutations in genomic medicine. We conclude by formulating and discussing future directions and potential challenges facing quantitative computational investigations of allosteric regulatory mechanisms in protein systems.

Evolutionary-Conserved Allosteric Properties of Three Neuronal Calcium Sensor Proteins

Neuronal Calcium Sensors (NCS) are highly conserved proteins specifically expressed in neurons. Calcium (Ca²⁺)-binding to their EF-hand motifs results in a conformational change, which is crucial for the recognition of a specific target and the downstream biological process. Here we present a comprehensive analysis of the allosteric communication between Ca²⁺-binding sites and the target interfaces of three NCS, namely NCS1, recoverin (Rec), and GCAP1. In particular, Rec was investigated in different Ca²⁺-loading states and in complex with a peptide from the Rhodopsin Kinase (GRK1) while NCS1 was studied in a Ca²⁺-loaded state in complex with either the same GRK1 target or a peptide from the D₂ Dopamine receptor. A Protein Structure Network (PSN) accounting for persistent non-covalent interactions between amino acids was built for each protein state based on exhaustive Molecular Dynamics simulations. Structural network analysis helped unveiling the role of key amino acids in allosteric mechanisms and their evolutionary conservation among homologous proteins. Results for NCS1 highlighted allosteric inter-domain interactions between Ca²⁺-binding motifs and residues involved in target recognition. Robust long range, allosteric protein-target interactions were found also in Rec, in particular originating from the EF3 motif. Interestingly, Tyr 86, involved the hydrophobic packing of the N-terminal domain, was found to be a key residue for both intra- and inter-molecular communication with EF3, regardless of the presence of target or Ca²⁺ ions. Finally, based on a comprehensive topological PSN analysis for Rec, NCS1, and GCAP1 and multiple sequence alignments with homolog proteins, we propose that an evolution-driven correlation may exist between the amino acids mediating the highest number of persistent interactions (high-degree hubs) and their conservation. Such conservation is apparently fundamental for the specific structural dynamics required in signaling events.

Analyzing Biomolecular Ensembles

Several techniques are available to generate conformational ensembles of proteins and other biomolecules either experimentally or computationally. These methods produce a large amount of data that need to be analyzed to identify structure-dynamics-function relationship. In this chapter, we will cover different tools to unveil the information hidden in conformational ensemble data and to guide toward the rationalization of the data. We included routinely used approaches such as dimensionality reduction, as well as new methods inspired by high-order statistics and graph theory.

Use multiscale simulation to explore the effects of the homodimerizations between different conformation states on the activation and allosteric pathway for the μ-opioid receptor

Recently, oligomers of G-protein coupled receptors (GPCRs) have been an important topic in the GPCR fields. However, knowledge about their structures and activation mechanisms is very limited due to the absence of crystal structures reported. In this work, we used multiscale simulations to study the effects of homodimerization between different conformation states on their activation, dynamic behaviors, and allosteric communication pathways for μ-OR. The results indicated that the dimerization of one inactive monomer with either one inactive monomer or one active one could enhance its constitutive activation. However, the conformation state of the other protomer (e.g., active or inactive) can influence the activated extent. The dimerization between the two inactive protomers leads to a negative cooperativity for their activation, which should contribute to the asymmetric activation of GPCR dimers observed in some experiments. On the other hand, for the active monomer, its dimerization with one inactive receptor could alleviate its deactivation, whereby negative and positive cooperativities can be observed between the two subunits of the dimer, depending on the different regions. Observations from protein structure network (PSN) analysis indicated that the dimerization of one inactive monomer with one active one would cause a significant drop in the number of main pathways from the ligand binding pocket to the G-protein coupled region for the inactive protomer, while the impact is minor for the active protomer. But, for the active monomer or the inactive one, its dimerization with one inactive monomer would significantly change the types of residues participating in the pathway with the highest frequency.

Resistance mechanism of the oncogenic β3-αC deletion mutation in BRAF kinase to dabrafenib and vemurafenib revealed by molecular dynamics simulations and binding free energy calculations

BRAF kinase is an essential target for anti-cancer drug development. Emergence of the β3-αC loop deletion mutation (ΔNVTAP) in BRAF kinase frequently occurred in human cancers seriously compromises the therapeutic efficacy of some BRAF kinase inhibitors, such as dabrafenib and vemurafenib. However, the mechanism of this resistance is still not well understood. In this study, the influence of the β3-αC deletion mutation on the binding profiles of three BRAF kinase inhibitors (AZ628, dabrafenib, and vemurafenib) with BRAF^V600E or BRAF^ΔNVTAP was explored by conventional molecular dynamics (MD) simulations and binding free energy calculations. The simulation results indicated that the β3-αC deletion mutation enhances the flexibility of the αC helix and alters their conformations, which amplify the conformational entropy change (-TΔS) and weaken the interactions between the inhibitors and BRAF. The further per-residue binding free energy decomposition analysis revealed that the ΔNVTAP mutation changed the contributions of a few key residues to the bindings of dabrafenib or vemurafenib, such as L57, L66, W83, C84, F135, G145, and F147, but did not have obvious impact on the contributions of these residues to AZ628. Our results provide valuable clues to understand the mechanisms of drug resistance conferred by the β3-αC deletion mutation.

Singular value decomposition for the correlation of atomic fluctuations with arbitrary angle

Many proteins exhibit a critical property called allostery, which enables intra-molecular transmission of information between distal sites. Microscopically, allosteric response is closely related to correlated atomic fluctuations. Conventional correlation analysis correlates the atomic fluctuations at two sites by taking the dot product (DP) between the fluctuations, which accounts only for the parallel and antiparallel components. Here, we present a singular value decomposition (SVD) method that analyzes the correlation coefficient of fluctuation dynamics with an arbitrary angle between the correlated directions. In a model allosteric system, the second PDZ domain (PDZ2) in the human PTP1E protein, approximately one third of the strong correlations have near-perpendicular directions, which are underestimated in the conventional method. The discrimination becomes more prominent for residue pairs with larger separation. The results of the proposed SVD method are more consistent with the experimentally determined PDZ2 dynamics than those of conventional method. In addition, the SVD method improved the prediction accuracy of the allosteric sites in a dataset of 23 known allosteric monomer proteins. The proposed method may inspire extended investigation not only into allostery, but also into protein dynamics and drug design.

The Binding Mechanism Between Inositol Phosphate (InsP) and the Jasmonate Receptor Complex: A Computational Study

Jasmonates are critical plant hormones, mediating stress response in plants and regulating plant growth and development. The jasmonate receptor is a multi-component complex, composed of Arabidopsis SKP-LIKE PROTEIN1 (ASK1), CORONATINE INSENSITIVE 1 (COI1), inositol phosphate (InsP), and jasmonate ZIM-domain protein (JAZ). COI1 acts as multi-component signaling hub that binds with each component. InsP is suggested to play important roles in the hormone perception. How InsP binds with COI1 and the structural changes in COI1 upon binding with InsP, JA-Ile, and JAZ are not well understood. In this study, we integrated multiple computational methods, such as molecular docking, molecular dynamics simulations, residue interaction network analysis and binding free energy calculation, to explore the effect of InsP on the dynamic behavior of COI1 and the recognition mechanism of each component of the jasmonate receptor complex. We found that upon binding with InsP, JA-Ile, and JAZ1, the structure of COI1 becomes more compact. The binding of InsP with COI1 stabilizes the conformation of COI1 and promotes the binding between JA-Ile or JAZ1 and COI1. Analysis of the network parameters led to the identification of some hub nodes in this network, including Met88, His118, Arg120, Arg121, Arg346, Tyr382, Arg409, Trp467, and Lys492. The structural and dynamic details will be helpful for understanding the recognition mechanism of each component and the discovery and design of novel jasmonate signaling pathway modulators.

A Small Chaperone Improves Folding and Routing of Rhodopsin Mutants Linked to Inherited Blindness

The autosomal dominant form of retinitis pigmentosa (adRP) is a blindness-causing conformational disease largely linked to mutations of rhodopsin. Molecular simulations coupled to the graph-based protein structure network (PSN) analysis and in vitro experiments were conducted to determine the effects of 33 adRP rhodopsin mutations on the structure and routing of the opsin protein. The integration of atomic and subcellular levels of analysis was accomplished by the linear correlation between indices of mutational impairment in structure network and in routing. The graph-based index of structural perturbation served also to divide the mutants in four clusters, consistent with their differences in subcellular localization and responses to 9-cis retinal. The stability core of opsin inferred from PSN analysis was targeted by virtual screening of over 300,000 anionic compounds leading to the discovery of a reversible orthosteric inhibitor of retinal binding more effective than retinal in improving routing of three adRP mutants.

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In silico and in vitro analyses of adRP rhodopsin mutants bridged folding and routing

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Structure network analysis grouped mutants amenable to treatment with small chaperones

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Virtual compound screening against the stability core of opsin found a small chaperone

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The pharmacoperone is a reversible orthosteric inhibitor of retinal binding

Probing subtle conformational changes induced by phosphorylation and point mutations in the TIR domains of TLR2 and TLR3

Extensive research performed on Toll-like receptor (TLR) signaling has identified residues in the Toll/interleukin-1 receptor (TIR) domains that are essential for its proper functioning. Among these residues, those in BB loop are particularly significant as single amino acid mutations in this region can cause drastic changes in downstream signaling. However, while the effect of these mutations on the function is well studied (like the P681H mutation in TLR2, the A795P mutation in TLR3, and the P714H mutation in TLR4), their influence on the dynamics and inter-residue networks is not well understood. The effects of local perturbations induced by these mutations could propagate throughout the TIR domain, influencing interactions with other TIR domain-containing proteins. The identification of these subtle changes in inter-residue interactions can provide new insights and structural rationale for how single-point mutations cause drastic changes in TIR-TIR interactions. We employed molecular dynamics simulations and protein structure network (PSN) analyses to investigate the structural transitions with special emphasis on TLR2 and TLR3. Our results reveal that phosphorylation of the Tyr 759 residue in the TIR domain of TLR3 introduces rigidity to its BB loop. Subtle differences in the intra BB loop hydrogen bonding network between TLR3 and TLR2 are also observed. The PSN analyses indicate that the TIR domain is highly connected and pinpoints key differences in the inter-residue interactions between the wild-type and mutant TIR domains, suggesting that TIR domain structure is prone to allosteric effects, consistent with the current view of the influence of allostery on TLR signaling.

Exploring the mechanism of F282L mutation-caused constitutive activity of GPCR by a computational study

G-protein-coupled receptors (GPCRs) are important drug targets and generally activated by ligands. However, some experiments found that GPCRs also give rise to constitutive activity through some mutations (viz., CAM), which are usually associated with different kinds of diseases. However, the mechanisms of CAMs and their roles in interactions with drug-ligands are unclear in experiments. Herein, we used microsecond molecular dynamics simulations to study the effect of one important F282L mutation on β2AR in order to address the questions above. With the aid of principle component and correlation analysis, our results revealed that the F282L mutation could increase the instability of the overall structure, increase the dramatic fluctuations of NPxxY and extracellular loops, and decrease restraint of the helices through weakening interhelical H-bonding and correlations between residues, which could partly contribute to the constitutive activity reported by the experiments. The observations from the protein structure network (PSN) analysis indicate that the mutant exhibits less information flow than the wild β2AR and weakens the role of TM5 and TM6 in the signal transmission, but it enhances the impact of TM3 on the orthosteric pathway and TM4 on the allosteric one. In addition, the results from the virtual screening reveal that the mutant prefers to select agonists rather than antagonists, similar to the active state but opposite of the inactive state, further confirming that the F282L mutation advances the activation of β2AR. Our observations provide valuable information for understanding the mechanism of the mutation-caused constitutive activity of GPCR and related drug-design.

Visualization and analysis of non-covalent contacts using the Protein Contacts Atlas

Visualizations of biomolecular structures empower us to gain insights into biological functions, generate testable hypotheses, and communicate biological concepts. Typical visualizations (such as ball and stick) primarily depict covalent bonds. In contrast, non-covalent contacts between atoms, which govern normal physiology, pathogenesis, and drug action, are seldom visualized. We present the Protein Contacts Atlas, an interactive resource of non-covalent contacts from over 100,000 PDB crystal structures. We developed multiple representations for visualization and analysis of non-covalent contacts at different scales of organization: atoms, residues, secondary structure, subunits, and entire complexes. The Protein Contacts Atlas enables researchers from different disciplines to investigate diverse questions in the framework of non-covalent contacts, including the interpretation of allostery, disease mutations and polymorphisms, by exploring individual subunits, interfaces, and protein-ligand contacts and by mapping external information. The Protein Contacts Atlas is available at http://www.mrc-lmb.cam.ac.uk/pca/ and also through PDBe.

Probing the cooperative mechanism of the μ–δ opioid receptor heterodimer by multiscale simulation

The activation-cooperativity of the μ–δ opioid receptor heterodimer was probed by multiscale simulation coupled with a protein structure network.

Normal mode analysis as a method to derive protein dynamics information from the Protein Data Bank

Normal mode analysis (NMA) can facilitate quick and systematic investigation of protein dynamics using data from the Protein Data Bank (PDB). We developed an elastic network model-based NMA program using dihedral angles as independent variables. Compared to the NMA programs that use Cartesian coordinates as independent variables, key attributes of the proposed program are as follows: (1) chain connectivity related to the folding pattern of a polypeptide chain is naturally embedded in the model; (2) the full-atom system is acceptable, and owing to a considerably smaller number of independent variables, the PDB data can be used without further manipulation; (3) the number of variables can be easily reduced by some of the rotatable dihedral angles; (4) the PDB data for any molecule besides proteins can be considered without coarse-graining; and (5) individual motions of constituent subunits and ligand molecules can be easily decomposed into external and internal motions to examine their mutual and intrinsic motions. Its performance is illustrated with an example of a DNA-binding allosteric protein, a catabolite activator protein. In particular, the focus is on the conformational change upon cAMP and DNA binding, and on the communication between their binding sites remotely located from each other. In this illustration, NMA creates a vivid picture of the protein dynamics at various levels of the structures, i.e., atoms, residues, secondary structures, domains, subunits, and the complete system, including DNA and cAMP. Comparative studies of the specific protein in different states, e.g., apo- and holo-conformations, and free and complexed configurations, provide useful information for studying structurally and functionally important aspects of the protein.

Uncovering GPCR and G Protein Function by Protein Structure Network Analysis

Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used for investigating structural communication in biomolecular systems. Information on the system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). This chapter reports on selected applications of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs) and G proteins. Strategies to highlight changes in structural communication caused by mutations, ligand and protein binding are described. Conserved amino acids, sites of misfolding mutations, or ligands acting as functional switches tend to behave as hubs in the native structure networks. Densely linked regions in the protein structure graphs could be identified as playing central roles in protein stability and function. Changes in the communication pathway fingerprints depending on the bound ligand or following amino acid mutation could be highlighted as well. A bridge between misfolding and misrouting could be established in rhodopsin mutants linked to inherited blindness. The analysis of native network perturbations by misfolding mutations served to infer key structural elements of protein responsiveness to small chaperones with implications for drug discovery.

Integrative modelling of TIR domain-containing adaptor molecule inducing interferon-β (TRIF) provides insights into its autoinhibited state

BACKGROUND

TRIF is a key protein in antiviral innate immunity, operating downstream of TLRs. TRIF activation leads to the production of interferon-β and pro-inflammatory cytokines. There is evidence from experiments to suggest that the N-terminal domain of TRIF binds to its TIR domain to avoid constitutive activation. However, no structure of a complex between the N-terminal domain and the TIR domain exists till date. The disordered nature of the region connecting the N-terminal domain and the TIR domain compounds the issue of elucidating the mechanism of autoinhibition of TRIF. In this study, we have employed an integrative approach consisting of mutual information analysis, docking, molecular dynamics simulations and residue network analysis, in combination with existing experimental data to provide a glimpse of TRIF in its autoinhibited state.

RESULTS

Our extensive docking approach reveals that the N-terminal domain binds to the BB loop-B helix region of the TIR domain, consistent with experimental observations. Long length molecular dynamics simulations of 1 microsecond performed on the docked model highlights residues participating in hydrogen bonding and hydrophobic interactions at the interface. A pair of residues present in the vicinity of the interface is also predicted by mutual information analysis, to co-evolve. Residues mediating long-range interactions within the TIR domain of TRIF were identified using residue network analysis.

CONCLUSIONS

Based on the results of the modelling and residue network analysis, we propose that the N-terminal domain binds to the BB loop region of the TIR domain, thereby preventing its homodimersation. The binding of TRIF to TLR3 or TRAM could induce a slight conformational change, causing the interactions between the N-terminal domain and TIR domain to disrupt, thereby exposing the BB loop and rendering it amenable for higher-order oligomerisation.

REVIEWERS

This article was reviewed by Michael Gromiha, Srikrishna Subramaniam and Peter Bond (nominated by Chandra Verma).

Revealing inhibition difference between PFI-2 enantiomers against SETD7 by molecular dynamics simulations, binding free energy calculations and unbinding pathway analysis

SETD7 is associated with multiple diseases related signaling pathways. (R)-PFI-2 is the first SETD7 inhibitor with nanomolar inhibitory potency. The activity of (R)-PFI-2 is about 500 times over that of (S)-PFI-2. Understanding the mechanism behind this difference will be helpful to discovery and design of more potent SETD7 inhibitors. A computational study combining molecular dynamics simulation, binding free energy calculations, and residue interaction network (RIN) was performed on the (S)-PFI-2/SETD7 and (R)-PFI-2/SETD7 complexes to explore the molecular mechanism behind the different inhibition activity. The results from Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation show (R)-PFI-2 has lower binding free energy. Residues H252, D256, L267, Y335, G336 and H339 are responsible for the binding of SETD7 to the (R)-PFI-2. RIN analysis indicates van der Waals interaction is critical for the binding of (R)-PFI-2. The results from adaptive basing force (ABF) simulation confirm that the free energy barrier of (R)-PFI-2 dissociating from the SETD7 is larger than that of (S)-PFI-2. (S)-PFI-2 and (R)-PFI-2 dissociate from the SETD7 binding site along different reaction coordinate and have potential mean of force (PMF) depth. Our simulations results will be useful to understand molecular mechanism of activity difference between PFI-2 enantiomers against SETD7.

A comparative study of cold- and warm-adapted Endonucleases A using sequence analyses and molecular dynamics simulations

The psychrophilic and mesophilic endonucleases A (EndA) from Aliivibrio salmonicida (VsEndA) and Vibrio cholera (VcEndA) have been studied experimentally in terms of the biophysical properties related to thermal adaptation. The analyses of their static X-ray structures was no sufficient to rationalize the determinants of their adaptive traits at the molecular level. Thus, we used Molecular Dynamics (MD) simulations to compare the two proteins and unveil their structural and dynamical differences. Our simulations did not show a substantial increase in flexibility in the cold-adapted variant on the nanosecond time scale. The only exception is a more rigid C-terminal region in VcEndA, which is ascribable to a cluster of electrostatic interactions and hydrogen bonds, as also supported by MD simulations of the VsEndA mutant variant where the cluster of interactions was introduced. Moreover, we identified three additional amino acidic substitutions through multiple sequence alignment and the analyses of MD-based protein structure networks. In particular, T120V occurs in the proximity of the catalytic residue H80 and alters the interaction with the residue Y43, which belongs to the second coordination sphere of the Mg2+ ion. This makes T120V an amenable candidate for future experimental mutagenesis.

Structural Determinants of Constitutive Activation of Gα Proteins: Transducin as a Paradigm

Heterotrimeric guanine nucleotide-binding proteins (Gα proteins) are intracellular nanomachines deputed to signal transduction. The switch-on process requires the release of bound GDP from a site at the interface between GTPase and helical domains. Nucleotide release is catalyzed by G protein Coupled Receptors (GPCRs). Here we investigate the functional dynamics of wild type (WT) and six constitutively active mutants (CAMs) of the Gα protein transducin (Gt) by combining atomistic molecular dynamics (MD) simulations with Maxwell-Demod discrete MD (MDdMD) simulations of the receptor-catalyzed transition between GDP-bound and nucleotide-free states. Compared to the WT, Gt CAMs increase the overall fluctuations of nucleotide and its binding site. This is accompanied by weakening of native links involving GDP, α1, the G boxes, β1-β3, and α5. Collectively, constitutive activation by the considered mutants seems to associate with weakening of the interfaces between α5 and the surrounding portions and the interface between GTPase (G) and helical (H) domains. These mutational effects associate with increases in the overall fluctuations of the G and H domains, which reflect on the collective motions of the protein. Gt CAMs, with prominence to G56P, T325A, and F332A, prioritize collective motions of the H domain overlapping with the collective motions associated with receptor-catalyzed nucleotide release. In spite of different local perturbations, the mechanisms of nucleotide exchange catalyzed by activating mutations and by receptor are expected to employ similar molecular switches in the nucleotide binding site and to share the detachment of the H domain from the G domain.

Allosteric communication pathways routed by Ca2+/Mg2+ exchange in GCAP1 selectively switch target regulation modes

GCAP1 is a neuronal calcium sensor protein that regulates the phototransduction cascade in vertebrates by switching between activator and inhibitor of the target guanylate cyclase (GC) in a Ca²⁺-dependent manner. We carried out exhaustive molecular dynamics simulations of GCAP1 and determined the intramolecular communication pathways involved in the specific GC activator/inhibitor switch. The switch was found to depend on the Mg²⁺/Ca²⁺ loading states of the three EF hands and on the way the information is transferred from each EF hand to specific residues at the GCAP1/GC interface. Post-translational myristoylation is fundamental to mediate long range allosteric interactions including the EF2-EF4 coupling and the communication between EF4 and the GC binding interface. Some hubs in the identified protein network are the target of retinal dystrophy mutations, suggesting that the lack of complete inhibition of GC observed in many cases is likely due to the perturbation of intra/intermolecular communication routes.

Drug targets evolve, and so should the methods

Design of specific kinase inhibitors is an appealing approach for developing new anticancer treatments. However, only a few success stories have been reported to date. Here we demonstrate how the combination of old-fashioned and new biophysical tools together with recent advances in genomics and molecular evolution can aid in overcoming existing limitations.

Exploration of the conformational landscape in pregnane X receptor reveals a new binding pocket

Ligand-regulated pregnane X receptor (PXR), a member of the nuclear receptor superfamily, plays a central role in xenobiotic metabolism. Despite its critical role in drug metabolism, PXR activation can lead to adverse drug-drug interactions and early stage metabolism of drugs. Activated PXR can induce cancer drug resistance and enhance the onset of malignancy. Since promiscuity in ligand binding makes it difficult to develop competitive inhibitors targeting PXR ligand binding pocket (LBP), it is essential to identify allosteric sites for effective PXR antagonism. Here, molecular dynamics (MD) simulation studies unravelled the existence of two different conformational states, namely "expanded" and "contracted", in apo PXR ligand binding domain (LBD). Ligand binding events shifted this conformational equilibrium and locked the LBD in a single "ligand-adaptable" conformational state. Ensemble-based computational solvent mapping identified a transiently open potential small molecule binding pocket between α5 and α8 helices, named "α8 pocket", whose opening-closing mechanism directly correlated with the conformational shift in LBD. A virtual hit identified through structure-based virtual screening against α8 pocket locks the pocket in its open conformation. MD simulations further revealed that the presence of small molecule at allosteric site disrupts the LBD dynamics and locks the LBD in a "tightly-contracted" conformation. The molecular details provided here could guide new structural studies to understand PXR activation and antagonism.

Pyruvate Occupancy in the Carboxyl Transferase Domain of Pyruvate Carboxylase Facilitates Product Release from the Biotin Carboxylase Domain through an Intermolecular Mechanism

Protein structure, ligand binding, and catalytic turnover contributes to the governance of catalytic events occurring at spatially distinct domains in multifunctional enzymes. Coordination of these catalytic events partially rests on the ability of spatially discrete active sites to communicate with other allosteric and active sites on the same polypeptide chain (intramolecular) or on different polypeptide chains (intermolecular) within the holoenzyme. Often, communication results in long-range effects on substrate binding or product release. For example, pyruvate binding to the carboxyl transferase (CT) domain of pyruvate carboxylase (PC) increases the rate of product release in the biotin carboxylase (BC) domain. In order to address how CT domain ligand occupancy is "sensed" by other domains, we generated functional, mixed hybrid tetramers using the E218A (inactive BC domain) and T882S (low pyruvate binding, low activity) mutant forms of PC. The apparent Ka pyruvate for the pyruvate-stimulated release of Pi catalyzed by the T882S:E218A[1:1] hybrid tetramer was comparable to the wild-type enzyme and nearly 10-fold lower than that for the T882S homotetramer. In addition, the ratio of the rates of oxaloacetate formation to Pi release for the WT:T882S[1:1] and E218A:T882S[1:1] hybrid tetramer-catalyzed reactions was 0.5 and 0.6, respectively, while the T882S homotetramer exhibited a near 1:1 coupling of the two domains, suggesting that the mechanisms coordinating catalytic events is more complicated that we initially assumed. The results presented here are consistent with an intermolecular communication mechanism, where pyruvate binding to the CT domain is "sensed" by domains on a different polypeptide chain within the tetramer.

The RING 2.0 web server for high quality residue interaction networks

Residue interaction networks (RINs) are an alternative way of representing protein structures where nodes are residues and arcs physico–chemical interactions. RINs have been extensively and successfully used for analysing mutation effects, protein folding, domain–domain communication and catalytic activity. Here we present RING 2.0, a new version of the RING software for the identification of covalent and non-covalent bonds in protein structures, including π–π stacking and π–cation interactions. RING 2.0 is extremely fast and generates both intra and inter-chain interactions including solvent and ligand atoms. The generated networks are very accurate and reliable thanks to a complex empirical re-parameterization of distance thresholds performed on the entire Protein Data Bank. By default, RING output is generated with optimal parameters but the web server provides an exhaustive interface to customize the calculation. The network can be visualized directly in the browser or in Cytoscape. Alternatively, the RING-Viz script for Pymol allows visualizing the interactions at atomic level in the structure. The web server and RING-Viz, together with an extensive help and tutorial, are available from URL: http://protein.bio.unipd.it/ring.

NAPS: Network Analysis of Protein Structures

Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue-residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein-protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/.

Structure network analysis to gain insights into GPCR function

G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM–NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM–NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor.

PDB2Graph: A toolbox for identifying critical amino acids map in proteins based on graph theory

The integrative and cooperative nature of protein structure involves the assessment of topological and global features of constituent parts. Network concept takes complete advantage of both of these properties in the analysis concomitantly. High compatibility to structural concepts or physicochemical properties in addition to exploiting a remarkable simplification in the system has made network an ideal tool to explore biological systems. There are numerous examples in which different protein structural and functional characteristics have been clarified by the network approach. Here, we present an interactive and user-friendly Matlab-based toolbox, PDB2Graph, devoted to protein structure network construction, visualization, and analysis. Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices. It maps critical amino acids in protein networks and can greatly aid structural biologists in selecting proper amino acid candidates for manipulating protein structures in a more reasonable and rational manner. To introduce the capability and efficiency of PDB2Graph in detail, the structural modification of Calmodulin through allosteric binding of Ca(2+) is considered. In addition, a mutational analysis for three well-identified model proteins including Phage T4 lysozyme, Barnase and Ribonuclease HI, was performed to inspect the influence of mutating important central residues on protein activity.

Dissecting protein architecture with communication blocks and communicating segment pairs

BACKGROUND

Proteins adapt to environmental conditions by changing their shape and motions. Characterising protein conformational dynamics is increasingly recognised as necessary to understand how proteins function. Given a conformational ensemble, computational tools are needed to extract in a systematic way pertinent and comprehensive biological information.

RESULTS

Here, we present a method, Communication Mapping (COMMA), to decipher the dynamical architecture of a protein. The method first extracts residue-based dynamic properties from all-atom molecular dynamics simulations. Then, it integrates them in a graph theoretic framework, where it identifies groups of residues or protein regions that mediate short- and long-range communication. COMMA introduces original concepts to contrast the different roles played by these regions, namely communication blocks and communicating segment pairs, and evaluates the connections and communication strengths between them. We show the utility and capabilities of COMMA by applying it to three archetypal proteins, namely protein A, the tyrosine kinase KIT and the tumour suppressor p53.

CONCLUSION

Our method permits to compare in a direct way the dynamical behaviour either of proteins with different characteristics or of the same protein in different conditions. It is useful to identify residues playing a key role in protein allosteric regulation and to explain the effects of deleterious mutations in a mechanistic way. COMMA is a fully automated tool with broad applicability. It is freely available to the community at www.lcqb.upmc.fr/COMMA .

The dynamics of the β-propeller domain in Kelch protein KLHL40 changes upon nemaline myopathy-associated mutation

The nemaline myopathy-associated E528K mutation in the KLHL40 alters the communication between the Kelch propeller blades.

Use of network model to explore dynamic and allosteric properties of three GPCR homodimers

We used an elastic network model and protein structure network to study three class A GPCR homodimers.

Analysis of core-periphery organization in protein contact networks reveals groups of structurally and functionally critical residues

The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the native states of 66 proteins (belonging to different families) in terms of their core-periphery organization. The resulting hierarchical classification of the amino acid constituents of a protein arranges the residues into successive layers - having higher core order - with increasing connection density, ranging from a sparsely linked periphery to a densely intra-connected core (distinct from the earlier concept of protein core defined in terms of the three-dimensional geometry of the native state, which has least solvent accessibility). Our results show that residues in the inner cores are more conserved than those at the periphery. Underlining the functional importance of the network core, we see that the receptor sites for known ligand molecules of most proteins occur in the innermost core. Furthermore, the association of residues with structural pockets and cavities in binding or active sites increases with the core order. From mutation sensitivity analysis, we show that the probability of deleterious or intolerant mutations also increases with the core order. We also show that stabilization centre residues are in the innermost cores, suggesting that the network core is critically important in maintaining the structural stability of the protein. A publicly available Web resource for performing core-periphery analysis of any protein whose native state is known has been made available by us at http://www.imsc.res.in/ ~sitabhra/proteinKcore/index.html.

Molecular features of interaction between VEGFA and anti-angiogenic drugs used in retinal diseases: a computational approach

Anti-angiogenic agents are biological drugs used for treatment of retinal neovascular degenerative diseases. In this study, we aimed at in silico analysis of interaction of vascular endothelial growth factor A (VEGFA), the main mediator of angiogenesis, with binding domains of anti-angiogenic agents used for treatment of retinal diseases, such as ranibizumab, bevacizumab and aflibercept. The analysis of anti-VEGF/VEGFA complexes was carried out by means of protein-protein docking and molecular dynamics (MD) coupled to molecular mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculation. Molecular dynamics simulation was further analyzed by protein contact networks. Rough energetic evaluation with protein-protein docking scores revealed that aflibercept/VEGFA complex was characterized by electrostatic stabilization, whereas ranibizumab and bevacizumab complexes were stabilized by Van der Waals (VdW) energy term; these results were confirmed by MM-PBSA. Comparison of MM-PBSA predicted energy terms with experimental binding parameters reported in literature indicated that the high association rate (Kon) of aflibercept to VEGFA was consistent with high stabilizing electrostatic energy. On the other hand, the relatively low experimental dissociation rate (Koff) of ranibizumab may be attributed to lower conformational fluctuations of the ranibizumab/VEGFA complex, higher number of contacts and hydrogen bonds in comparison to bevacizumab and aflibercept. Thus, the anti-angiogenic agents have been found to be considerably different both in terms of molecular interactions and stabilizing energy. Characterization of such features can improve the design of novel biological drugs potentially useful in clinical practice.

Catching Functional Modes and Structural Communication in Dbl Family Rho Guanine Nucleotide Exchange Factors

Computational approaches such as Principal Component Analysis (PCA) and Elastic Network Model-Normal Mode Analysis (ENM-NMA) are proving to be of great value in investigating relevant biological problems linked to slow motions with no demand in computer power. In this study, these approaches have been coupled to the graph theory-based Protein Structure Network (PSN) analysis to dissect functional dynamics and structural communication in the Dbl family of Rho Guanine Nucleotide Exchange Factors (RhoGEFs). They are multidomain proteins whose common structural feature is a DH-PH tandem domain deputed to the GEF activity that makes them play a central role in cell and cancer biology. While their common GEF action is accomplished by the DH domain, their regulatory mechanisms are highly variegate and depend on the PH and the additional domains as well as on interacting proteins. Major evolutionary-driven deformations as inferred from PCA concern the α6 helix of DH that dictates the orientation of the PH domain. Such deformations seem to depend on the mechanisms adopted by the GEF to prevent Rho binding, i.e. functional specialization linked to autoinhibition. In line with PCA, ENM-NMA indicates α6 and the linked PH domain as the portions of the tandem domain holding almost the totality of intrinsic and functional dynamics, with the α6/β1 junction acting as a hinge point for the collective motions of PH. In contrast, the DH domain holds a static scaffolding and hub behavior, with structural communication playing a central role in the regulatory actions by other domains/proteins. Possible allosteric communication pathways involving essentially DH were indeed found in those RhoGEFs acting as effectors of small or heterotrimeric RasGTPases. The employed methodology is suitable for deciphering structure/dynamics relationships in large sets of homologous or analogous proteins.

Characteristics Analyses and Comparisons of the Protein Structure Networks Constructed by Different Methods

Protein structure networks (PSNs) were widely used in analyses of protein structure and function. In this work, we analyzed and compared the characters of PSNs by different methods. The degrees of the different types of the nodes were found to be associated with the amino acid characters, including SAS, secondary structure, hydropathy and the volume of amino acids. It showed that PSNs by the methods of CA10, SC10 and AT5 inherited more amino acid characters and had higher correlations with the original protein structures. And PSNs by these three methods would be powerful tools in understanding the characters of protein structures.

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics: strength in unity

In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

Communication routes in ARID domains between distal residues in helix 5 and the DNA-binding loops

ARID is a DNA-binding domain involved in several transcriptional regulatory processes, including cell-cycle regulation and embryonic development. ARID domains are also targets of the Human Cancer Protein Interaction Network. Little is known about the molecular mechanisms related to conformational changes in the family of ARID domains. Thus, we have examined their structural dynamics to enrich the knowledge on this important family of regulatory proteins. In particular, we used an approach that integrates atomistic simulations and methods inspired by graph theory. To relate these properties to protein function we studied both the free and DNA-bound forms. The interaction with DNA not only stabilizes the conformations of the DNA-binding loops, but also strengthens pre-existing paths in the native ARID ensemble for long-range communication to those loops. Residues in helix 5 are identified as critical mediators for intramolecular communication to the DNA-binding regions. In particular, we identified a distal tyrosine that plays a key role in long-range communication to the DNA-binding loops and that is experimentally known to impair DNA-binding. Mutations at this tyrosine and in other residues of helix 5 are also demonstrated, by our approach, to affect the paths of communication to the DNA-binding loops and alter their native dynamics. Overall, our results are in agreement with a scenario in which ARID domains exist as an ensemble of substates, which are shifted by external perturbation, such as the interaction with DNA. Conformational changes at the DNA-binding loops are transmitted long-range by intramolecular paths, which have their heart in helix 5.

PyInteraph: a framework for the analysis of interaction networks in structural ensembles of proteins

In the last years, a growing interest has been gathering around the ability of Molecular Dynamics (MD) to provide insight into the paths of long-range structural communication in biomolecules. The knowledge of the mechanisms related to structural communication helps in the rationalization in atomistic details of the effects induced by mutations, ligand binding, and the intrinsic dynamics of proteins. We here present PyInteraph, a tool for the analysis of structural ensembles inspired by graph theory. PyInteraph is a software suite designed to analyze MD and structural ensembles with attention to binary interactions between residues, such as hydrogen bonds, salt bridges, and hydrophobic interactions. PyInteraph also allows the different classes of intra- and intermolecular interactions to be represented, combined or alone, in the form of interaction graphs, along with performing network analysis on the resulting interaction graphs. The program also integrates the network description with a knowledge-based force field to estimate the interaction energies between side chains in the protein. It can be used alone or together with the recently developed xPyder PyMOL plugin through an xPyder-compatible format. The software capabilities and associated protocols are here illustrated by biologically relevant cases of study. The program is available free of charge as Open Source software via the GPL v3 license at http://linux.btbs.unimib.it/pyinteraph/.

The construction of an amino acid network for understanding protein structure and function

Amino acid networks (AANs) are undirected networks consisting of amino acid residues and their interactions in three-dimensional protein structures. The analysis of AANs provides novel insight into protein science, and several common amino acid network properties have revealed diverse classes of proteins. In this review, we first summarize methods for the construction and characterization of AANs. We then compare software tools for the construction and analysis of AANs. Finally, we review the application of AANs for understanding protein structure and function, including the identification of functional residues, the prediction of protein folding, analyzing protein stability and protein-protein interactions, and for understanding communication within and between proteins.

The future of crystallography in drug discovery

INTRODUCTION

X-ray crystallography plays an important role in structure-based drug design (SBDD), and accurate analysis of crystal structures of target macromolecules and macromolecule-ligand complexes is critical at all stages. However, whereas there has been significant progress in improving methods of structural biology, particularly in X-ray crystallography, corresponding progress in the development of computational methods (such as in silico high-throughput screening) is still on the horizon. Crystal structures can be overinterpreted and thus bias hypotheses and follow-up experiments. As in any experimental science, the models of macromolecular structures derived from X-ray diffraction data have their limitations, which need to be critically evaluated and well understood for structure-based drug discovery.

AREAS COVERED

This review describes how the validity, accuracy and precision of a protein or nucleic acid structure determined by X-ray crystallography can be evaluated from three different perspectives: i) the nature of the diffraction experiment; ii) the interpretation of an electron density map; and iii) the interpretation of the structural model in terms of function and mechanism. The strategies to optimally exploit a macromolecular structure are also discussed in the context of 'Big Data' analysis, biochemical experimental design and structure-based drug discovery.

EXPERT OPINION

Although X-ray crystallography is one of the most detailed 'microscopes' available today for examining macromolecular structures, the authors would like to re-emphasize that such structures are only simplified models of the target macromolecules. The authors also wish to reinforce the idea that a structure should not be thought of as a set of precise coordinates but rather as a framework for generating hypotheses to be explored. Numerous biochemical and biophysical experiments, including new diffraction experiments, can and should be performed to verify or falsify these hypotheses. X-ray crystallography will find its future application in drug discovery by the development of specific tools that would allow realistic interpretation of the outcome coordinates and/or support testing of these hypotheses.

Residue interaction network analysis of Dronpa and a DNA clamp

Topology is an essential aspect of protein structure. The network paradigm is increasingly used to describe the topology and dynamics of proteins. In this paper, the effect of topology on residue interaction network was investigated for two different proteins: Dronpa and a DNA clamp, which have cylindrical and toroidal topologies, respectively. Network metrics including characteristic path lengths, clustering coefficients, and diameters were calculated to investigate their global topology parameters such as small-world properties and packing density. Measures of centrality including betweenness, closeness, and residue centrality were computed to predict residues critical to function. Additionally, the detailed topology of the hydrophobic pocket in Dronpa, and communication pathways across the interface in the DNA clamp, were investigated using the network. The results are presented and discussed with regard to existing residue interaction network properties of globular proteins and elastic network models on Dronpa and the DNA clamp. The topological principle underlying residue interaction networks provided insight into the architectural organization of proteins.

Molecular modeling and residue interaction network studies on the mechanism of binding and resistance of the HCV NS5B polymerase mutants to VX-222 and ANA598

Hepatitis C virus (HCV) NS5B protein is an RNA-dependent RNA polymerase (RdRp) with essential functions in viral genome replication and represents a promising therapeutic target to develop direct-acting antivirals (DAAs). Multiple nonnucleoside inhibitors (NNIs) binding sites have been identified within the polymerase. VX-222 and ANA598 are two NNIs targeting thumb II site and palm I site of HCV NS5B polymerase, respectively. These two molecules have been shown to be very effective in phase II clinical trials. However, the emergence of resistant HCV replicon variants (L419M, M423T, I482L mutants to VX-222 and M414T, M414L, G554D mutants to ANA598) has significantly decreased their efficacy. To elucidate the molecular mechanism about how these mutations influenced the drug binding mode and decreased drug efficacy, we studied the binding modes of VX-222 and ANA598 to wild-type and mutant polymerase by molecular modeling approach. Molecular dynamics (MD) simulations results combined with binding free energy calculations indicated that the mutations significantly altered the binding free energy and the interaction for the drugs to polymerase. The further per-residue binding free energy decomposition analysis revealed that the mutations decreased the interactions with several key residues, such as L419, M423, L474, S476, I482, L497, for VX-222 and L384, N411, M414, Y415, Q446, S556, G557 for ANA598. These were the major origins for the resistance to these two drugs. In addition, by analyzing the residue interaction network (RIN) of the complexes between the drugs with wild-type and the mutant polymerase, we found that the mutation residues in the networks involved in the drug resistance possessed a relatively lower size of topology centralities. The shift of betweenness and closeness values of binding site residues in the mutant polymerase is relevant to the mechanism of drug resistance of VX-222 and ANA598. These results can provide an atomic-level understanding about the mechanisms of drug resistance conferred by the studied mutations and will be helpful to design more potent inhibitors which could effectively overcome drug resistance of antivirus agents.

Exploring signal transduction in heteromultimeric protein based on energy dissipation model

Dynamic intersubunit interactions are key elements in the regulation of many biological systems. A better understanding of how subunits interact with each other and how their interactions are related to dynamic protein structure is a fundamental task in biology. In this paper, a heteromultimeric allosteric protein, Corynebacterium glutamicum aspartokinase, is used as a model system to explore the signal transduction involved in intersubunit interactions and allosteric communication with an emphasis on the intersubunit signaling process. For this purpose, energy dissipation simulation and network construction are conducted for each subunit and the whole protein. Comparison with experimental results shows that the new approach is able to predict all the mutation sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. Additionally, analysis revealed that the function of the effector threonine is to facilitate the binding of the two subunits without contributing to the allosteric communication. During the allosteric regulation upon the binding of the effector lysine, signals can be transferred from the β-subunit to the catalytic site of the α-subunit through both a direct way of intersubunit signal transduction, and an indirect way: first, to the regulatory region of the α-subunit by intersubunit signal transduction and then to the catalytic region by intramolecular signal transduction. Therefore, the new approach is able to illustrate the diversity of the underlying mechanisms when the strength of feedback inhibition by the effector(s) is modulated, providing useful information that has potential applications in engineering heteromultimeric allosteric regulation.