Computer simulation of protein-protein association kinetics: acetylcholinesterase-fasciculin

Competitive Interaction of the SGFRKMAF Peptide with 3CLpro Dimerization Intermediates: A Brownian Dynamics Investigation

The SGFRKMAF peptide is known to inhibit the dimerization of 3CLpro monomers, which is essential for SARS-CoV-2 replication. The mechanism behind this, however, is largely unknown. In this work, we used Brownian dynamics simulations to compare and contrast 3CLpro monomer-monomer interactions and 3CLpro monomer-SGFRKMAF peptide interactions. We found that formation of the 3CLpro wild-type dimer could potentially involve formation of three intermediates that are primarily stabilized by G11-G124, S1-S301, and T118-G278 interactions. Analysis of 3CLpro monomer interaction with the SGFRKMAF peptide, however, revealed the presence of eight basins of interactions where the peptide assumes the highest local densities at the 3CLPro monomer surface. The second highest-density basin was found to coincide with the interface region of the wild-type 3CLpro dimer, thereby directly blocking the 3CLpro dimer-dimer interactions. The other basins, however, were found to lie far from the interface region. Notably, we found that only 6% of the BD trajectories end up directly into the basin at the interface region and ∼39% of the trajectories end up into those basins lying away from the interface region, indicating a greater role for peptide binding at sites away from the dimer interface region. Importantly, the locations of the basins lying away from the interface were found to coincide with the 3CLpro residues involved in stabilization of the 3CLpro monomer-monomer intermediates. Given that the rate constant of the peptide reaching the monomer surface was found to be almost an order of magnitude higher than the rate constant of monomer-monomer association, the SGFRKMAF peptide has the potential to inhibit dimerization of 3CLpro monomers not only through blocking the interface region but also through blocking the formation of the intermediates involved in the dimerization process. This could potentially open new avenues for 3CLpro dimerization inhibitors that transcend traditional X-ray-based discovery approaches.

SUMOylation controls Hu antigen R posttranscriptional activity in liver cancer

The posttranslational modification of proteins critically influences many biological processes and is a key mechanism that regulates the function of the RNA-binding protein Hu antigen R (HuR), a hub in liver cancer. Here, we show that HuR is SUMOylated in the tumor sections of patients with hepatocellular carcinoma in contrast to the surrounding tissue, as well as in human cell line and mouse models of the disease. SUMOylation of HuR promotes major cancer hallmarks, namely proliferation and invasion, whereas the absence of HuR SUMOylation results in a senescent phenotype with dysfunctional mitochondria and endoplasmic reticulum. Mechanistically, SUMOylation induces a structural rearrangement of the RNA recognition motifs that modulates HuR binding affinity to its target RNAs, further modifying the transcriptomic profile toward hepatic tumor progression. Overall, SUMOylation constitutes a mechanism of HuR regulation that could be potentially exploited as a therapeutic strategy for liver cancer.

ES-Screen: A Novel Electrostatics-Driven Method for Drug Discovery Virtual Screening

Electrostatic interactions drive biomolecular interactions and associations. Computational modeling of electrostatics in biomolecular systems, such as protein-ligand, protein-protein, and protein-DNA, has provided atomistic insights into the binding process. In drug discovery, finding biologically plausible ligand-protein target interactions is challenging as current virtual screening and adjuvant techniques such as docking methods do not provide optimal treatment of electrostatic interactions. This study describes a novel electrostatics-driven virtual screening method called 'ES-Screen' that performs well across diverse protein target systems. ES-Screen provides a unique treatment of electrostatic interaction energies independent of total electrostatic free energy, typically employed by current software. Importantly, ES-Screen uses initial ligand pose input obtained from a receptor-based pharmacophore, thus independent of molecular docking. ES-Screen integrates individual polar and nonpolar replacement energies, which are the energy costs of replacing the cognate ligand for a target with a query ligand from the screening. This uniquely optimizes thermodynamic stability in electrostatic and nonpolar interactions relative to an experimentally determined stable binding state. ES-Screen also integrates chemometrics through shape and other physicochemical properties to prioritize query ligands with the greatest physicochemical similarities to the cognate ligand. The applicability of ES-Screen is demonstrated with in vitro experiments by identifying novel targets for many drugs. The present version includes a combination of many other descriptor components that, in a future version, will be purely based on electrostatics. Therefore, ES-Screen is a first-in-class unique electrostatics-driven virtual screening method with a unique implementation of replacement electrostatic interaction energies with broad applicability in drug discovery.

Phosphorylation disrupts long-distance electron transport in cytochrome c

It has been recently shown that electron transfer between mitochondrial cytochrome c and the cytochrome c₁ subunit of the cytochrome bc₁ can proceed at long-distance through the aqueous solution. Cytochrome c is thought to adjust its activity by changing the affinity for its partners via Tyr48 phosphorylation, but it is unknown how it impacts the nanoscopic environment, interaction forces, and long-range electron transfer. Here, we constrain the orientation and separation between cytochrome c₁ and cytochrome c or the phosphomimetic Y48pCMF cytochrome c, and deploy an array of single-molecule, bulk, and computational methods to investigate the molecular mechanism of electron transfer regulation by cytochrome c phosphorylation. We demonstrate that phosphorylation impairs long-range electron transfer, shortens the long-distance charge conduit between the partners, strengthens their interaction, and departs it from equilibrium. These results unveil a nanoscopic view of the interaction between redox protein partners in electron transport chains and its mechanisms of regulation.

Homodimeric complexes of the 90-231 human prion: a multilayered computational study based on FMO/GRID-DRY approach

The molecular interaction properties and aggregation capabilities disclosed by PrP-E200K, a pathogenic mutant of the human prion protein, were investigated in detail using multilayered computational approaches. In a previous work, we reported that the electrostatic complementarity between region1 (negative) and region3 (positive) has been assumed to lead to a head-to tail interaction between 120 and 231 PrP-E200K units and to initiation of the aggregation process. In this work, we extended the PrP-E200K structure by including the unstructured 90–120 segment which was found to assume different conformations. Plausible models of 90–231 PrP-E200K dimers were calculated and analyzed in depth to identify the nature of the involved protein–protein interactions. The unstructured 90–120 segment was found to extend the positively charged region3 involved in the association of PrP-E200K units which resulted to be driven by hydrophobic interactions. The combination of molecular dynamics, protein–protein docking, grid-based mapping, and fragment molecular orbital approaches allowed us to provide a plausible mechanism of the early state of 90–231 PrP-E200K aggregation, considered a preliminary step of amyloid conversion.

Novel US-CpHMD Protocol to Study the Protonation-Dependent Mechanism of the ATP/ADP Carrier

We have designed a protocol combining constant-pH molecular dynamics (CpHMD) simulations with an umbrella sampling (US) scheme (US-CpHMD) to study the mechanism of ADP/ATP transport (import and export) by their inner mitochondrial membrane carrier protein [ADP/ATP carrier (AAC)]. The US scheme helped overcome the limitations of sampling the slow kinetics involved in these substrates' transport, while CpHMD simulations provided an unprecedented realism by correctly capturing the associated protonation changes. The import of anionic substrates along the mitochondrial membrane has a strong energetic disadvantage due to a smaller substrate concentration and an unfavorable membrane potential. These limitations may have created an evolutionary pressure on AAC to develop specific features benefiting the import of ADP. In our work, the potential of mean force profiles showed a clear selectivity in the import of ADP compared to ATP, while in the export, no selectivity was observed. We also observed that AAC sequestered both substrates at longer distances in the import compared to the export process. Furthermore, only in the import process do we observe transient protonation of both substrates when going through the AAC cavity, which is an important advantage to counteract the unfavorable mitochondrial membrane potential. Finally, we observed a substrate-induced disruption of the matrix salt-bridge network, which can promote the conformational transition (from the C- to M-state) required to complete the import process. This work unraveled several important structural features where the complex electrostatic interactions were pivotal to interpreting the protein function and illustrated the potential of applying the US-CpHMD protocol to other transport processes involving membrane proteins.

High affinity protein surface binding through co-engineering of nanoparticles and proteins

Control over supramolecular recognition between proteins and nanoparticles (NPs) is of fundamental importance in therapeutic applications and sensor development. Most NP-protein binding approaches use 'tags' such as biotin or His-tags to provide high affinity; protein surface recognition provides a versatile alternative strategy. Generating high affinity NP-protein interactions is challenging however, due to dielectric screening at physiological ionic strengths. We report here the co-engineering of nanoparticles and protein to provide high affinity binding. In this strategy, 'supercharged' proteins provide enhanced interfacial electrostatic interactions with complementarily charged nanoparticles, generating high affinity complexes. Significantly, the co-engineered protein-nanoparticle assemblies feature high binding affinity even at physiologically relevant ionic strength conditions. Computational studies identify both hydrophobic and electrostatic interactions as drivers for these high affinity NP-protein complexes.

Crowding within synaptic junctions influences the degradation of nucleotides by CD39 and CD73 ectonucleotidases

Synapsed cells can communicate using exocytosed nucleotides like adenosine triphosphate (ATP). Ectonucleotidases localized to synaptic junctions degrade nucleotides into metabolites like adenosine monophosphate (AMP) or adenosine. Oftentimes nucleotide degradation occurs in a sequential manner, of which ATP degradation by CD39 and CD73 is a representative example. Here, CD39 first converts ATP and adenosine diphosphate (ADP) into AMP, after which AMP is dephosphorylated into adenosine by CD73. Hence, the concerted activity of CD39 and CD73 can help shape cellular responses to extracellular ATP. In a previous study, we demonstrated that coupled CD39 and CD73 activity within synapse-like junctions is strongly controlled by the enzymes' co-localization, their surface charge densities, and the electrostatic potential of the surrounding cell membranes. In this study, we demonstrate that crowders within synaptic junctions, which can include globular proteins like cytokines and membrane-bound proteins, impact coupled CD39 and CD73 ectonucleotidase activity and, in turn, the availability of intrasynapse ATP. Specifically, we developed a spatially explicit, reaction-diffusion model for the coupled conversion of ATP → AMP and AMP → adenosine in a model synaptic junction with crowders that is solved via the finite element method. Our modeling results suggest that the association rate for ATP to CD39 is strongly influenced by the density of intrasynaptic protein crowders, as increasing crowder density generally suppressed ATP association kinetics. Much of this suppression can be rationalized based on a loss of configurational entropy. The surface charges of crowders can further influence the association rate, with the surprising result that favorable crowder-nucleotide electrostatic interactions can yield CD39 association rates that are faster than crowder-free configurations. However, attractive crowder-nucleotide interactions decrease the rate and efficiency of adenosine production, which in turn increases the availability of ATP and AMP within the synapse relative to crowder-free configurations. These findings highlight how CD39 and CD73 ectonucleotidase activity, electrostatics, and crowding within synapses influence the availability of nucleotides for intercellular communication.

Brownian Dynamics Simulations of Proteins in the Presence of Surfaces: Long-Range Electrostatics and Mean-Field Hydrodynamics

Simulations of macromolecular diffusion and adsorption in confined environments can offer valuable mechanistic insights into numerous biophysical processes. In order to model solutes at atomic detail on relevant time scales, Brownian dynamics simulations can be carried out with the approximation of rigid body solutes moving through a continuum solvent. This allows the precomputation of interaction potential grids for the solutes, thereby allowing the computationally efficient calculation of forces. However, hydrodynamic and long-range electrostatic interactions cannot be fully treated with grid-based approaches alone. Here, we develop a treatment of both hydrodynamic and electrostatic interactions to include the presence of surfaces by modeling grid-based and long-range interactions. We describe its application to simulate the self-association and many-molecule adsorption of the well-characterized protein hen egg-white lysozyme to mica-like and silica-like surfaces. We find that the computational model can recover a number of experimental observables of the adsorption process and provide insights into their determinants. The computational model is implemented in the Simulation of Diffusional Association (SDA) software package.

ARL15 modulates magnesium homeostasis through N-glycosylation of CNNMs

Cyclin M (CNNM1-4) proteins maintain cellular and body magnesium (Mg²⁺) homeostasis. Using various biochemical approaches, we have identified members of the CNNM family as direct interacting partners of ADP-ribosylation factor-like GTPase 15 (ARL15), a small GTP-binding protein. ARL15 interacts with CNNMs at their carboxyl-terminal conserved cystathionine-β-synthase (CBS) domains. In silico modeling of the interaction between CNNM2 and ARL15 supports that the small GTPase specifically binds the CBS1 and CNBH domains. Immunocytochemical experiments demonstrate that CNNM2 and ARL15 co-localize in the kidney, with both proteins showing subcellular localization in the endoplasmic reticulum, Golgi apparatus and the plasma membrane. Most importantly, we found that ARL15 is required for forming complex N-glycosylation of CNNMs. Overexpression of ARL15 promotes complex N-glycosylation of CNNM3. Mg²⁺ uptake experiments with a stable isotope demonstrate that there is a significant increase of ²⁵Mg²⁺ uptake upon knockdown of ARL15 in multiple kidney cancer cell lines. Altogether, our results establish ARL15 as a novel negative regulator of Mg²⁺ transport by promoting the complex N-glycosylation of CNNMs.

Understanding the mechanism of HIV-1 protease inhibition by monoclonal antibodies

HIV-1 protease is an essential enzyme in the life cycle of human immunodeficiency virus (HIV) and hence is one of the most important targets for antiviral drug design. Although there are ten FDA approved drugs against HIV protease (PR), their long term usage elicits mutations leading to drug resistance. As a result, novel therapeutic approaches are being explored including synthetic antibodies. Recently, a murine monoclonal antibody, mAB1696 (mAB) was reported to inhibit PR by preventing dimerization. Crystallographic data could reveal only six protease residues that interact with mAB. The present study employs a range of computational techniques, starting from protein-protein docking to all-atomic molecular dynamics simulations to generate plausible 3D structures of PR-mAB complex. Results show that mAB interacts very strongly with several PR dimer interface residues, such as Gln7, Arg8 (N-terminal), Cys95, Leu97 (C-terminal), Thr26, Gly27 (active site), Gly49, Ile50 (flap), apart from its interactions with the PR epitope region, Pro1-Trp6 (N-terminal). These observations support the hypothesis that binding of mAB prevents the dimerization of PR. The interactions and binding conformations identified in this study could form the basis for designing allosteric inhibitors preventing the dimerization of HIV-1 Protease.

Protein electrostatics: From computational and structural analysis to discovery of functional fingerprints and biotechnological design

Computationally driven engineering of proteins aims to allow them to withstand an extended range of conditions and to mediate modified or novel functions. Therefore, it is crucial to the biotechnological industry, to biomedicine and to afford new challenges in environmental sciences, such as biocatalysis for green chemistry and bioremediation. In order to achieve these goals, it is important to clarify molecular mechanisms underlying proteins stability and modulating their interactions. So far, much attention has been given to hydrophobic and polar packing interactions and stability of the protein core. In contrast, the role of electrostatics and, in particular, of surface interactions has received less attention. However, electrostatics plays a pivotal role along the whole life cycle of a protein, since early folding steps to maturation, and it is involved in the regulation of protein localization and interactions with other cellular or artificial molecules. Short- and long-range electrostatic interactions, together with other forces, provide essential guidance cues in molecular and macromolecular assembly. We report here on methods for computing protein electrostatics and for individual or comparative analysis able to sort proteins by electrostatic similarity. Then, we provide examples of electrostatic analysis and fingerprints in natural protein evolution and in biotechnological design, in fields as diverse as biocatalysis, antibody and nanobody engineering, drug design and delivery, molecular virology, nanotechnology and regenerative medicine.

Specifying the role of BAK1-interacting receptor-like kinase 3 in brassinosteroid signaling

Brassinosteroids (BR) are involved in the control of several developmental processes ranging from root elongation to senescence and adaptation to environmental cues. Thus, BR perception and signaling have to be precisely regulated. One regulator is BRI1-associated kinase 1 (BAK1)-interacting receptor-like kinase 3 (BIR3). In the absence of BR, BIR3 forms complexes with BR insensitive 1 (BRI1) and BAK1. However, the biophysical and energetic requirements for complex formation in the absence of the ligand have yet to be determined. Using computational modeling, we simulated the potential complexes between the cytoplasmic domains of BAK1, BRI1 and BIR3. Our calculations and experimental data confirm the interaction of BIR3 with BAK1 and BRI1, with the BAK1 BIR3 interaction clearly favored. Furthermore, we demonstrate that BIR3 and BRI1 share the same interaction site with BAK1. This suggests a competition between BIR3 and BRI1 for binding to BAK1, which results in preferential binding of BIR3 to BAK1 in the absence of the ligand thereby preventing the active participation of BAK1 in BR signaling. Our model also suggests that BAK1 and BRI1 can interact even while BAK1 is in complex with BIR3 at an additional binding site of BAK1 that does not allow active BR signaling.

Rotational and Translational Diffusion of Proteins as a Function of Concentration

Atomistic simulations of three different proteins at different concentrations are performed to obtain insight into protein mobility as a function of protein concentration. We report on simulations of proteins from diluted to the physiological water concentration (about 70% of the mass). First, the viscosity was computed and found to increase by a factor of 7-9 going from pure water to the highest protein concentration, in excellent agreement with in vivo nuclear magnetic resonance results. At a physiological concentration of proteins, the translational diffusion is found to be slowed down to about 30% of the in vitro values. The slow-down of diffusion found here using atomistic models is slightly more than that of a hard sphere model that neglects the electrostatic interactions. Interestingly, rotational diffusion of proteins is slowed down somewhat more (by about 80-95% compared to in vitro values) than translational diffusion, in line with experimental findings and consistent with the increased viscosity. The finding that rotation is retarded more than translation is attributed to solvent-separated clustering. No direct interactions between the proteins are found, and the clustering can likely be attributed to dispersion interactions that are stronger between proteins than between protein and water. Based on these simulations, we can also conclude that the internal dynamics of the proteins in our study are affected only marginally under crowding conditions, and the proteins become somewhat more stable at higher concentrations. Simulations were performed using a force field that was tuned for dealing with crowding conditions by strengthening the protein-water interactions. This force field seems to lead to a reproducible partial unfolding of an α-helix in one of the proteins, an effect that was not observed in the unmodified force field.

Regulation of adenylyl cyclase 5 in striatal neurons confers the ability to detect coincident neuromodulatory signals

Long-term potentiation and depression of synaptic activity in response to stimuli is a key factor in reinforcement learning. Strengthening of the corticostriatal synapses depends on the second messenger cAMP, whose synthesis is catalysed by the enzyme adenylyl cyclase 5 (AC5), which is itself regulated by the stimulatory Gαolf and inhibitory Gαi proteins. AC isoforms have been suggested to act as coincidence detectors, promoting cellular responses only when convergent regulatory signals occur close in time. However, the mechanism for this is currently unclear, and seems to lie in their diverse regulation patterns. Despite attempts to isolate the ternary complex, it is not known if Gαolf and Gαi can bind to AC5 simultaneously, nor what activity the complex would have. Using protein structure-based molecular dynamics simulations, we show that this complex is stable and inactive. These simulations, along with Brownian dynamics simulations to estimate protein association rates constants, constrain a kinetic model that shows that the presence of this ternary inactive complex is crucial for AC5's ability to detect coincident signals, producing a synergistic increase in cAMP. These results reveal some of the prerequisites for corticostriatal synaptic plasticity, and explain recent experimental data on cAMP concentrations following receptor activation. Moreover, they provide insights into the regulatory mechanisms that control signal processing by different AC isoforms.

Molecular Mechanism of Aggregation of the Cataract-Related γD-Crystallin W42R Variant from Multiscale Atomistic Simulations

The mechanisms leading to aggregation of the crystallin proteins of the eye lens remain largely unknown. We use atomistic multiscale molecular simulations to model the solution-state conformational dynamics of γD-crystallin and its cataract-related W42R variant at both infinite dilution and physiologically relevant concentrations. We find that the W42R variant assumes a distinct conformation in solution that leaves the Greek key domains of the native fold largely unaltered but lacks the hydrophobic interdomain interface that is key to the stability of wild-type γD-crystallin. At physiologically relevant concentrations, exposed hydrophobic regions in this alternative conformation become primary sites for enhanced interprotein interactions leading to large-scale aggregation.

Modified Potential Functions Result in Enhanced Predictions of a Protein Complex by All-Atom Molecular Dynamics Simulations, Confirming a Stepwise Association Process for Native Protein-Protein Interactions

The relative prevalence of native protein-protein interactions (PPIs) are the cornerstone for understanding the structure, dynamics and mechanisms of function of protein complexes. In this study, we develop a scheme for scaling the protein-water interaction in the CHARMM36 force field, in order to better fit the solvation free energy of amino acids side-chain analogues. We find that the molecular dynamics simulation with the scaled force field, CHARMM36s, as well as a recently released version, CHARMM36m, effectively improve on the overly sticky association of proteins, such as ubiquitin. We investigate the formation of a heterodimer protein complex between the SAM domains of the EphA2 receptor and the SHIP2 enzyme by performing a combined total of 48 μs simulations with the different potential functions. While the native SAM heterodimer is only predicted at a low rate of 6.7% with the original CHARMM36 force field, the yield is increased to 16.7% with CHARMM36s, and to 18.3% with CHARMM36m. By analyzing the 25 native SAM complexes formed in the simulations, we find that their formation involves a preorientation guided by Coulomb interactions, consistent with an electrostatic steering mechanism. In 12 cases, the complex could directly transform to the native protein interaction surfaces with only small adjustments in domain orientation. In the other 13 cases, orientational and/or translational adjustments are needed to reach the native complex. Although the tendency for non-native complexes to dissociate has nearly doubled with the modified potential functions, a dissociation followed by a reassociation to the correct complex structure is still rare. Instead, the remaining non-native complexes undergo configurational changes/surface searching, which, however, rarely leads to native structures on a time scale of 250 ns. These observations provide a rich picture of the mechanisms of protein-protein complex formation and suggest that computational predictions of native complex PPIs could be improved further.

Applications of in Silico Methods for Design and Development of Drugs Targeting Protein-Protein Interactions

BACKGROUND

Identification of Protein-Protein Interactions (PPIs) is a major challenge in modern molecular biology and biochemistry research, due to the unquestionable role of proteins in cells, biological process and pathological states. Over the past decade, the PPIs have evolved from being considered a highly challenging field of research to being investigated and examined as targets for pharmacological intervention.

OBJECTIVE

Comprehension of protein interactions is crucial to known how proteins come together to build signalling pathways, to carry out their functions, or to cause diseases, when deregulated. Multiplicity and great amount of PPIs structures offer a huge number of new and potential targets for the treatment of different diseases.

METHODS

Computational techniques are becoming predominant in PPIs studies for their effectiveness, flexibility, accuracy and cost. As a matter of fact, there are effective in silico approaches which are able to identify PPIs and PPI site. Such methods for computational target prediction have been developed through molecular descriptors and data-mining procedures.

RESULTS

In this review, we present different types of interactions between protein-protein and the application of in silico methods for design and development of drugs targeting PPIs. We described computational approaches for the identification of possible targets on protein surface and to detect of stimulator/ inhibitor molecules.

CONCLUSION

A deeper study of the most recent bioinformatics methodologies for PPIs studies is vital for a better understanding of protein complexes and for discover new potential PPI modulators in therapeutic intervention.

Unbiased Atomistic Insight into the Mechanisms and Solvent Role for Globular Protein Dimer Dissociation

Association and dissociation of proteins are fundamental processes in nature. Although simple to understand conceptually, the details of the underlying mechanisms and role of the solvent are poorly understood. Here, we investigate the dissociation of the hydrophilic β-lactoglobulin dimer by employing transition path sampling. Analysis of the sampled path ensembles reveals a variety of mechanisms: (1) a direct aligned dissociation (2) a hopping and rebinding transition followed by unbinding, and (3) a sliding transition before unbinding. Reaction coordinate and transition-state analysis predicts that, besides native contact and neighboring salt-bridge interactions, solvent degrees of freedom play an important role in the dissociation process. Bridging waters, hydrogen-bonded to both proteins, support contacts in the native state and nearby lying transition-state regions, whereas they exhibit faster dynamics in further lying transition-state regions, rendering the proteins more mobile and assisting in rebinding. Analysis of the structure and dynamics of the solvent molecules reveals that the dry native interface induces enhanced populations of both disordered hydration water near hydrophilic residues and tetrahedrally ordered hydration water nearby hydrophobic residues. Although not exhaustive, our sampling of rare unbiased reactive molecular dynamics trajectories enhances the understanding of protein dissociation via complex pathways including (multiple) rebinding events.

Citrate stabilized gold nanoparticles interfere with amyloid fibril formation: D76N and ΔN6 β2-microglobulin variants

Protein aggregation including the formation of dimers and multimers in solution, underlies an array of human diseases such as systemic amyloidosis which is a fatal disease caused by misfolding of native globular proteins damaging the structure and function of affected organs. Different kind of interactors can interfere with the formation of protein dimers and multimers in solution. A very special class of interactors are nanoparticles thanks to the extremely efficient extension of their interaction surface. In particular citrate-coated gold nanoparticles (cit-AuNPs) were recently investigated with amyloidogenic protein β2-microglobulin (β₂m). Here we present the computational studies on two challenging models known for their enhanced amyloidogenic propensity, namely ΔN6 and D76N β₂m naturally occurring variants, and disclose the role of cit-AuNPs on their fibrillogenesis. The proposed interaction mechanism lies in the interference of the cit-AuNPs with the protein dimers at the early stages of aggregation, that induces dimer disassembling. As a consequence, natural fibril formation can be inhibited. Relying on the comparison between atomistic simulations at multiple levels (enhanced sampling molecular dynamics and Brownian dynamics) and protein structural characterisation by NMR, we demonstrate that the cit-AuNPs interactors are able to inhibit protein dimer assembling. As a consequence, the natural fibril formation is also inhibited, as found in experiment.

Computational Studies on Acetylcholinesterases

Functions of biomolecules, in particular enzymes, are usually modulated by structural fluctuations. This is especially the case in a gated diffusion-controlled reaction catalyzed by an enzyme such as acetylcholinesterase. The catalytic triad of acetylcholinesterase is located at the bottom of a long and narrow gorge, but it catalyzes the extremely rapid hydrolysis of the neurotransmitter, acetylcholine, with a reaction rate close to the diffusion-controlled limit. Computational modeling and simulation have produced considerable advances in exploring the dynamical and conformational properties of biomolecules, not only aiding in interpreting the experimental data, but also providing insights into the internal motions of the biomolecule at the atomic level. Given the remarkably high catalytic efficiency and the importance of acetylcholinesterase in drug development, great efforts have been made to understand the dynamics associated with its functions by use of various computational methods. Here, we present a comprehensive overview of recent computational studies on acetylcholinesterase, expanding our views of the enzyme from a microstate of a single structure to conformational ensembles, strengthening our understanding of the integration of structure, dynamics and function associated with the enzyme, and promoting the structure-based and/or mechanism-based design of new inhibitors for it.

"Martinizing" the Variational Implicit Solvent Method (VISM): Solvation Free Energy for Coarse-Grained Proteins

Solvation is a fundamental driving force in many biological processes including biomolecular recognition and self-assembly, not to mention protein folding, dynamics, and function. The variational implicit solvent method (VISM) is a theoretical tool currently developed and optimized to estimate solvation free energies for systems of very complex topology, such as biomolecules. VISM's theoretical framework makes it unique because it couples hydrophobic, van der Waals, and electrostatic interactions as a functional of the solvation interface. By minimizing this functional, VISM produces the solvation interface as an output of the theory. In this work, we push VISM to larger scale applications by combining it with coarse-grained solute Hamiltonians adapted from the MARTINI framework, a well-established mesoscale force field for modeling large-scale biomolecule assemblies. We show how MARTINI-VISM (^MVISM) compares with atomistic VISM (^AVISM) for a small set of proteins differing in size, shape, and charge distribution. We also demonstrate ^MVISM's suitability to study the solvation properties of an interesting encounter complex, barnase-barstar. The promising results suggest that coarse-graining the protein with the MARTINI force field is indeed a valuable step to broaden VISM's and MARTINI's applications in the near future.

The conformational feasibility for the formation of reaching dimer in ASV and HIV integrase: a molecular dynamics study

Retroviral integrases are reported to form alternate dimer assemblies like the core-core dimer and reaching dimer. The core-core dimer is stabilized predominantly by an extensive interface between two catalytic core domains. The reaching dimer is stabilized by N-terminal domains that reach to form intermolecular interfaces with the other subunit's core and C-terminal domains (CTD), as well as CTD-CTD interactions. In this study, molecular dynamics (MD), Brownian dynamics (BD) simulations, and free energy analyses, were performed to elucidate determinants for the stability of the reaching dimer forms of full-length Avian Sarcoma Virus (ASV) and Human Immunodeficiency Virus (HIV) IN, and to examine the role of the C-tails (the last ~16-18 residues at the C-termini) in their structural dynamics. The dynamics of an HIV reaching dimer derived from small angle X-ray scattering and protein crosslinking data, was compared with the dynamics of a core-core dimer model derived from combining the crystal structures of two-domain fragments. The results showed that the core domains in the ASV reaching dimer express free dynamics, whereas those in the HIV reaching dimer are highly stable. BD simulations suggest a higher rate of association for the HIV core-core dimer than the reaching dimer. The predicted stability of these dimers was therefore ranked in the following order: ASV reaching dimer < HIV reaching dimer < composite core-core dimer. Analyses of MD trajectories have suggested residues that are critical for intermolecular contacts in each reaching dimer. Tests of these predictions and insights gained from these analyses could reveal a potential pathway for the association and dissociation of full-length IN multimers.

Enzyme localization, crowding, and buffers collectively modulate diffusion-influenced signal transduction: Insights from continuum diffusion modeling

Biochemical reaction networks consisting of coupled enzymes connect substrate signaling events with biological function. Substrates involved in these reactions can be strongly influenced by diffusion "barriers" arising from impenetrable cellular structures and macromolecules, as well as interactions with biomolecules, especially within crowded environments. For diffusion-influenced reactions, the spatial organization of diffusion barriers arising from intracellular structures, non-specific crowders, and specific-binders (buffers) strongly controls the temporal and spatial reaction kinetics. In this study, we use two prototypical biochemical reactions, a Goodwin oscillator, and a reaction with a periodic source/sink term to examine how a diffusion barrier that partitions substrates controls reaction behavior. Namely, we examine how conditions representative of a densely packed cytosol, including reduced accessible volume fraction, non-specific interactions, and buffers, impede diffusion over nanometer length-scales. We find that diffusion barriers can modulate the frequencies and amplitudes of coupled diffusion-influenced reaction networks, as well as give rise to "compartments" of decoupled reactant populations. These effects appear to be intensified in the presence of buffers localized to the diffusion barrier. These findings have strong implications for the role of the cellular environment in tuning the dynamics of signaling pathways.

Recognition Dynamics of p53 and MDM2: Implications for Peptide Design

Peptides that inhibit MDM2 and attenuate MDM2-p53 interactions, thus activating p53, are currently being pursued as anticancer drug leads for tumors harboring wild type p53. The thermodynamic determinants of peptide-MDM2 interactions have been extensively studied. However, a detailed understanding of the dynamics that underlie these interactions is largely missing. In this study, we explore the kinetics of the binding of a set of peptides using Brownian dynamics simulations. We systematically investigate the effect of peptide C-terminal substitutions (Ser, Ala, Asn, Pro) of a Q16ETFSDLWKLLP27 p53-based peptide and a M1PRFMDYWEGLN12 12/1 phage-derived peptide on their interaction dynamics with MDM2. The substitutions modulate peptide residence times around the MDM2 protein. In particular, the highest affinity peptide, Q16ETFSDLWKLLS27, has the longest residence time (t ∼ 25 μs) around MDM2, suggesting its potentially important contribution to binding affinity. The binding of the p53-based peptides appears to be kinetically driven while that of the phage-derived series appears to be thermodynamically driven. The phage-derived peptides were found to adopt distinctly different modes of interaction with the MDM2 protein compared to their p53-based counterparts. The p53-based peptides approach the N-terminal region of the MDM2 protein with the peptide C-terminal end oriented toward the protein, while the M1PRFMDYWEGLN12-based peptides adopt the reverse orientation. To probe the determinants of this switch in orientation, a designed mutant of the phage-derived peptide, R3E (M1PEFMDYWEGLN12), was simulated and found to adopt the orientation adopted by the p53-based peptides and also to result in almost a 5-fold increase in the peptide residence time (∼120 μs) relative to the p53-based peptides. On this basis, we suggest that the R3E mutant phage-derived peptide has a higher affinity for MDM2 than the p53-based peptides and would therefore, competitively inhibit MDM2-p53. The study, therefore, provides a novel computational framework for kinetics-based lead optimization for anticancer drug development strategies.

Epitope mapping of monoclonal antibody HPT-101: a study combining dynamic force spectroscopy, ELISA and molecular dynamics simulations

By combining enzyme-linked immunosorbent assay (ELISA) and optical tweezers-assisted dynamic force spectroscopy (DFS), we identify for the first time the binding epitope of the phosphorylation-specific monoclonal antibody (mAb) HPT-101 to the Alzheimer's disease relevant peptide tau[pThr231/pSer235] on the level of single amino acids. In particular, seven tau isoforms are synthesized by replacing binding relevant amino acids by a neutral alanine (alanine scanning). From the binding between mAb HPT-101 and the alanine-scan derivatives, we extract specific binding parameters such as bond lifetime τ0, binding length x(ts), free energy of activation ΔG (DFS) and affinity constant K(a) (ELISA, DFS). Based on these quantities, we propose criteria to identify essential, secondary and non-essential amino acids, being representative of the antibody binding epitope. The obtained results are found to be in full accord for both experimental techniques. In order to elucidate the microscopic origin of the change in binding parameters, we perform molecular dynamics (MD) simulations of the free epitope in solution for both its parent and modified form. By taking the end-to-end distance d(E-E) and the distance between the α-carbons d(C-C) of the phosphorylated residues as gauging parameters, we measure how the structure of the epitope depends on the type of substitution. In particular, whereas d(C-C) is sometimes conserved between the parent and modified form, d(E-E) strongly changes depending on the type of substitution, correlating well with the experimental data. These results are highly significant, offering a detailed microscopic picture of molecular recognition.

Rapid Estimation of Solvation Energy for Simulations of Protein-Protein Association

We have formulated the Energy by Linear Superposition of Corrections Approximation (ELSCA) for estimating the electrostatic and apolar solvation energy of bringing two proteins into close proximity or into contact as defined by the linearized Poisson-Boltzmann model and a linear function of the solvent-accessible surface area. ELSCA utilizes potentials of mean force between atom types found in the AMBER ff99 force field, a uniform distance-dependent dielectric, and a potential that mimics the change in solvent accessible surface area for bringing two solvated spheres into contact. ELSCA was trained by a linear least-squares fit on more than 39 000 putative complexes, each formed from pairs of nonhomologous proteins with a range of shapes, sizes, and charges. The training set was also designed to capture various stages of complex formation. ELSCA was tested against over 8000 non-native complexes of 45 enzyme/inhibitor, antibody/antigen, and other systems that are known to form complexes and gives an overall correlation of 0.962 with PBSA-derived energies for these complexes. The predictions have a slope of 0.89 on the actual values with a bias of 11.1 kcal/mol. When applied to native complexes of these 45 protein systems, ELSCA reproduces PBSA results with a correlation of 0.787, a slope of 1.13, and a bias of 13.0 kcal/mol. We report parameters for ELSCA in the context of the AMBER ff99 parameter set. Our model is most useful in macromolecular docking and protein association simulations, where large portions of each molecule may be considered rigid.

A spatiotemporal characterization of the effect of p53 phosphorylation on its interaction with MDM2

The interaction of p53 and MDM2 is modulated by the phosphorylation of p53. This mechanism is key to activating p53, yet its molecular determinants are not fully understood. To study the spatiotemporal characteristics of this molecular process we carried out Brownian dynamics simulations of the interactions of the MDM2 protein with a p53 peptide in its wild type state and when phosphorylated at Thr18 (pThr18) and Ser20 (pSer20). We found that p53 phosphorylation results in concerted changes in the topology of the interaction landscape in the diffusively bound encounter complex domain. These changes hinder phosphorylated p53 peptides from binding to MDM2 well before reaching the binding site. The underlying mechanism appears to involve shift of the peptide away from the vicinity of the MDM2 protein, peptide reorientation, and reduction in peptide residence time relative to wild-type p53 peptide. pThr18 and pSr20 p53 peptides experience reduction in residence times by factors of 13.6 and 37.5 respectively relative to the wild-type p53 peptide, indicating a greater role for Ser20 phosphorylation in abrogating p53 MDM2 interactions. These detailed insights into the effect of phosphorylation on molecular interactions are not available from conventional experimental and theoretical approaches and open up new avenues that incorporate molecular interaction dynamics, for stabilizing p53 against MDM2, which is a major focus of anticancer drug lead development.

Crucial HSP70 co-chaperone complex unlocks metazoan protein disaggregation

Protein aggregates are the hallmark of stressed and ageing cells, and characterize several pathophysiological states. Healthy metazoan cells effectively eliminate intracellular protein aggregates, indicating that efficient disaggregation and/or degradation mechanisms exist. However, metazoans lack the key heat-shock protein disaggregase HSP100 of non-metazoan HSP70-dependent protein disaggregation systems, and the human HSP70 system alone, even with the crucial HSP110 nucleotide exchange factor, has poor disaggregation activity in vitro. This unresolved conundrum is central to protein quality control biology. Here we show that synergic cooperation between complexed J-protein co-chaperones of classes A and B unleashes highly efficient protein disaggregation activity in human and nematode HSP70 systems. Metazoan mixed-class J-protein complexes are transient, involve complementary charged regions conserved in the J-domains and carboxy-terminal domains of each J-protein class, and are flexible with respect to subunit composition. Complex formation allows J-proteins to initiate transient higher order chaperone structures involving HSP70 and interacting nucleotide exchange factors. A network of cooperative class A and B J-protein interactions therefore provides the metazoan HSP70 machinery with powerful, flexible, and finely regulatable disaggregase activity and a further level of regulation crucial for cellular protein quality control.

SDA 7: A modular and parallel implementation of the simulation of diffusional association software

The simulation of diffusional association (SDA) Brownian dynamics software package has been widely used in the study of biomacromolecular association. Initially developed to calculate bimolecular protein-protein association rate constants, it has since been extended to study electron transfer rates, to predict the structures of biomacromolecular complexes, to investigate the adsorption of proteins to inorganic surfaces, and to simulate the dynamics of large systems containing many biomacromolecular solutes, allowing the study of concentration-dependent effects. These extensions have led to a number of divergent versions of the software. In this article, we report the development of the latest version of the software (SDA 7). This release was developed to consolidate the existing codes into a single framework, while improving the parallelization of the code to better exploit modern multicore shared memory computer architectures. It is built using a modular object-oriented programming scheme, to allow for easy maintenance and extension of the software, and includes new features, such as adding flexible solute representations. We discuss a number of application examples, which describe some of the methods available in the release, and provide benchmarking data to demonstrate the parallel performance.

Dimerization model of the C-terminal RNA Recognition Motif of HuR

Human antigen R (HuR) is a ubiquitous 32 kDa protein comprising three RNA Recognition Motifs (RRMs), whose main function is to bind Adenylate and uridylate Rich Elements (AREs) in 3' UnTranslated Regions (UTRs) of mRNAs. In addition to binding RNA molecules, the third domain (RRM3) is involved in HuR oligomerization and apoptotic signaling. The RRM3 monomer is able to dimerize, with its self-binding affinity being dependent on ionic strength. Here we provide a deeper structural insight into the nature of the encounter complexes leading to the formation of RRM3 dimers by using Brownian Dynamics and Molecular Dynamics. Our computational data show that the initial unspecific encounter follows a downhill pathway until reaching an optimum conformation stabilized by hydrophobic interactions.

Probing the influence of citrate-capped gold nanoparticles on an amyloidogenic protein

Nanoparticles (NPs) are known to exhibit distinct physical and chemical properties compared with the same materials in bulk form. NPs have been repeatedly reported to interact with proteins, and this interaction can be exploited to affect processes undergone by proteins, such as fibrillogenesis. Fibrillation is common to many proteins, and in living organisms, it causes tissue-specific or systemic amyloid diseases. The nature of NPs and their surface chemistry is crucial in assessing their affinity for proteins and their effects on them. Here we present the first detailed structural characterization and molecular mechanics model of the interaction between a fibrillogenic protein, β2-microglobulin, and a NP, 5 nm hydrophilic citrate-capped gold nanoparticles. NMR measurements and simulations at multiple levels (enhanced sampling molecular dynamics, Brownian dynamics, and Poisson-Boltzmann electrostatics) explain the origin of the observed protein perturbations mostly localized at the amino-terminal region. Experiments show that the protein-NP interaction is weak in the physiological-like, conditions and do not induce protein fibrillation. Simulations reproduce these findings and reveal instead the role of the citrate in destabilizing the lower pH protonated form of β2-microglobulin. The results offer possible strategies for controlling the desired effect of NPs on the conformational changes of the proteins, which have significant roles in the fibrillation process.

Conformational frustration in calmodulin-target recognition

Calmodulin (CaM) is a primary calcium (Ca(2+) )-signaling protein that specifically recognizes and activates highly diverse target proteins. We explored the molecular basis of target recognition of CaM with peptides representing the CaM-binding domains from two Ca(2+) -CaM-dependent kinases, CaMKI and CaMKII, by employing experimentally constrained molecular simulations. Detailed binding route analysis revealed that the two CaM target peptides, although similar in length and net charge, follow distinct routes that lead to a higher binding frustration in the CaM-CaMKII complex than in the CaM-CaMKI complex. We discovered that the molecular origin of the binding frustration is caused by intermolecular contacts formed with the C-domain of CaM that need to be broken before the formation of intermolecular contacts with the N-domain of CaM. We argue that the binding frustration is important for determining the kinetics of the recognition process of proteins involving large structural fluctuations.

Can small hydrophobic gold nanoparticles inhibit β₂-microglobulin fibrillation?

Inorganic nanoparticles stabilized by a shell of organic ligands can enhance or suppress the natural propensity of proteins to form fibrils. Functionalization facilitates targeted delivery of the nanoparticles to various cell types, bioimaging, drug delivery and other therapeutic and diagnostic applications. In this study, we provide a computational model of the effect of a prototypical thiol-protected gold nanoparticle, Au₂₅L₁₈(-) (L = S(CH₂)₂Ph) on the β₂-microglobulin natural fibrillation propensity. To reveal the molecular basis of the protein-nanoparticle association process, we performed various simulations at multiple levels (Classical Molecular Dynamics and Brownian Dynamics) that cover multiple length- and timescales. The results provide a model of the ensemble of structures constituting the protein-gold nanoparticle complexes, and insights into the driving forces for the binding of β₂-microglobulin to hydrophobic small size gold nanoparticles. We have found that the small nanoparticles can bind the protein to form persistent complexes. This binding of nanoparticles is able to block the active sites of domains from binding to another protein, thus leading to potential inhibition of the fibrillation activity. A comparison with the binding patches identified for the interaction of the protein with a known inhibitor of fibrillation, supports our conclusion.

Long range Debye-Hückel correction for computation of grid-based electrostatic forces between biomacromolecules

Background

Brownian dynamics (BD) simulations can be used to study very large molecular systems, such as models of the intracellular environment, using atomic-detail structures. Such simulations require strategies to contain the computational costs, especially for the computation of interaction forces and energies. A common approach is to compute interaction forces between macromolecules by precomputing their interaction potentials on three-dimensional discretized grids. For long-range interactions, such as electrostatics, grid-based methods are subject to finite size errors. We describe here the implementation of a Debye-Hückel correction to the grid-based electrostatic potential used in the SDA BD simulation software that was applied to simulate solutions of bovine serum albumin and of hen egg white lysozyme.

Results

We found that the inclusion of the long-range electrostatic correction increased the accuracy of both the protein-protein interaction profiles and the protein diffusion coefficients at low ionic strength.

Conclusions

An advantage of this method is the low additional computational cost required to treat long-range electrostatic interactions in large biomacromolecular systems. Moreover, the implementation described here for BD simulations of protein solutions can also be applied in implicit solvent molecular dynamics simulations that make use of gridded interaction potentials.

On the electrostatic properties of homodimeric proteins

A large fraction of proteins function as homodimers, but it is not always clear why the dimerization is important for functionality since frequently each monomer possesses a distinctive active site. Recent work (PLoS Computational Biology, 9(2), e1002924) indicates that homodimerization may be important for forming an electrostatic funnel in the spermine synthase homodimer which guides changed substrates toward the active centers. This prompted us to investigate the electrostatic properties of a large set of homodimeric proteins and resulted in an observation that in a vast majority of the cases the dimerization indeed results in specific electrostatic features, although not necessarily in an electrostatic funnel. It is demonstrated that the electrostatic dipole moment of the dimer is predominantly perpendicular to the axis connecting the centers of the mass of the monomers. In addition, the surface points with highest potential are located in the proximity of the interfacial plane of the homodimeric complexes. These findings indicate that frequently homodimerization provides specific electrostatic features needed for the function of proteins.

Protein recognition and selection through conformational and mutually induced fit

Protein-protein interactions drive most every biological process, but in many instances the domains mediating recognition are disordered. How specificity in binding is attained in the absence of defined structure contrasts with well-established experimental and theoretical work describing ligand binding to protein. The signaling protein calmodulin presents a unique opportunity to investigate mechanisms for target recognition given that it interacts with several hundred different targets. By advancing coarse-grained computer simulations and experimental techniques, mechanistic insights were gained in defining the pathways leading to recognition and in how target selectivity can be achieved at the molecular level. A model requiring mutually induced conformational changes in both calmodulin and target proteins was necessary and broadly informs how proteins can achieve both high affinity and high specificity.

On the origin of the stereoselective affinity of Nutlin-3 geometrical isomers for the MDM2 protein

The stereoselective affinity of small-molecule binding to proteins is typically broadly explained in terms of the thermodynamics of the final bound complex. Using Brownian dynamics simulations, we show that the preferential binding of the MDM2 protein to the geometrical isomers of Nutlin-3, an effective anticancer lead that works by inhibiting the interaction between the proteins p53 and MDM2, can be explained by kinetic arguments related to the formation of the MDM2:Nutlin-3 encounter complex. This is a diffusively bound state that forms prior to the final bound complex. We find that the MDM2 protein stereoselectivity for the Nutlin-3a enantiomer stems largely from the destabilization of the encounter complex of its mirror image enantiomer Nutlin-3b, by the K70 residue that is located away from the binding site. On the other hand, the trans-Nutlin-3a diastereoisomer exhibits a shorter residence time in the vicinity of MDM2 compared with Nutlin-3a due to destabilization of its encounter complex by the collective interaction of pairs of charged residues on either side of the binding site: Glu25 and Lys51 on one side, and Lys94 and Arg97 on the other side. This destabilization is largely due to the electrostatic potential of the trans-Nutlin-3a isomer being largely positive over extended continuous regions around its structure, which are otherwise well-identified into positive and negative regions in the case of the Nutlin-3a isomer. Such rich insight into the binding processes underlying biological selectivity complements the static view derived from the traditional thermodynamic analysis of the final bound complex. This approach, based on an explicit consideration of the dynamics of molecular association, suggests new avenues for kinetics-based anticancer drug development and discovery.

The role of shape complementarity in the protein-protein interactions

We use a dissipative particle dynamic simulation to investigate the effects of shape complementarity on the protein-protein interactions. By monitoring different kinds of protein shape-complementarity modes, we gave a clear mechanism to reveal the role of the shape complementarity in the protein-protein interactions, i.e., when the two proteins with shape complementarity approach each other, the conformation of lipid chains between two proteins would be restricted significantly. The lipid molecules tend to leave the gap formed by two proteins to maximize the configuration entropy, and therefore yield an effective entropy-induced protein-protein attraction, which enhances the protein aggregation. In short, this work provides an insight into understanding the importance of the shape complementarity in the protein-protein interactions especially for protein aggregation and antibody-antigen complexes. Definitely, the shape complementarity is the third key factor affecting protein aggregation and complex, besides the electrostatic-complementarity and hydrophobic complementarity.

Protein signatures using electrostatic molecular surfaces in harmonic space

We developed a novel method based on the Fourier analysis of protein molecular surfaces to speed up the analysis of the vast structural data generated in the post-genomic era. This method computes the power spectrum of surfaces of the molecular electrostatic potential, whose three-dimensional coordinates have been either experimentally or theoretically determined. Thus we achieve a reduction of the initial three-dimensional information on the molecular surface to the one-dimensional information on pairs of points at a fixed scale apart. Consequently, the similarity search in our method is computationally less demanding and significantly faster than shape comparison methods. As proof of principle, we applied our method to a training set of viral proteins that are involved in major diseases such as Hepatitis C, Dengue fever, Yellow fever, Bovine viral diarrhea and West Nile fever. The training set contains proteins of four different protein families, as well as a mammalian representative enzyme. We found that the power spectrum successfully assigns a unique signature to each protein included in our training set, thus providing a direct probe of functional similarity among proteins. The results agree with established biological data from conventional structural biochemistry analyses.

On the importance of polar interactions for complexes containing intrinsically disordered proteins

There is a growing recognition for the importance of proteins with large intrinsically disordered (ID) segments in cell signaling and regulation. ID segments in these proteins often harbor regions that mediate molecular recognition. Coupled folding and binding of the recognition regions has been proposed to confer high specificity to interactions involving ID segments. However, researchers recently questioned the origin of the interaction specificity of ID proteins because of the overrepresentation of hydrophobic residues in their interaction interfaces. Here, we focused on the role of polar and charged residues in interactions mediated by ID segments. Making use of the extended nature of most ID segments when in complex with globular proteins, we first identified large numbers of complexes between globular proteins and ID segments by using radius-of-gyration-based selection criteria. Consistent with previous studies, we found the interfaces of these complexes to be enriched in hydrophobic residues, and that these residues contribute significantly to the stability of the interaction interface. However, our analyses also show that polar interactions play a larger role in these complexes than in structured protein complexes. Computational alanine scanning and salt-bridge analysis indicate that interfaces in ID complexes are highly complementary with respect to electrostatics, more so than interfaces of globular proteins. Follow-up calculations of the electrostatic contributions to the free energy of binding uncovered significantly stronger Coulombic interactions in complexes harbouring ID segments than in structured protein complexes. However, they are counter-balanced by even higher polar-desolvation penalties. We propose that polar interactions are a key contributing factor to the observed high specificity of ID segment-mediated interactions.

Protein-protein interactions are essential to communication and signal integration in cells. For these processes to be precise, interactions between proteins have to be specific and well coordinated. In order to understand the specificity in protein interactions, researches have focused on interfaces between two or more folded proteins. It has been shown that specificity in interactions between folded proteins relies on shape complementarity, hydrogen bonding, and salt-bridge formation. However, many proteins lack a unique folded structure; the so-called intrinsically disordered proteins. These proteins fluctuate between different conformations in isolation but often adopt a single structure when interacting with partner proteins. As many intrinsically disordered proteins are involved in signaling and regulation, their interactions have to be highly specific. The finding that the interaction interfaces of intrinsically disordered proteins are enriched in hydrophobic residues has led to questions regarding the specificity of interactions mediated by this group of proteins. Here, we show that polar and charged residues play a larger role in interfaces that involve intrinsically disordered proteins compared to interfaces that involve only folded proteins. Our results suggest that polar interactions are key contributors to the specificity of interactions that involve intrinsically disordered proteins.

Crowding induced entropy-enthalpy compensation in protein association equilibria

A statistical mechanical theory is presented to predict the effects of macromolecular crowding on protein association equilibria, accounting for both excluded volume and attractive interactions between proteins and crowding molecules. Predicted binding free energies are in excellent agreement with simulation data over a wide range of crowder sizes and packing fractions. It is shown that attractive interactions between proteins and crowding agents counteract the stabilizing effects of excluded volume interactions. A critical attraction strength, for which there is no net effect of crowding, is approximately independent of the crowder packing fraction.

Computer Simulations of the Bacterial Cytoplasm

Ever since the pioneering work of Minton, it has been recognized that the highly crowded interior of biological cells has the potential to cause dramatic changes to both the kinetics and thermodynamics of protein folding and association events relative to behavior that might be observed in dilute solution conditions. One very productive way to explore the effects of crowding on protein behavior has been to use macromolecular crowding agents that exclude volume without otherwise strongly interacting with the protein under study. An alternative, complementary approach to understanding the potential differences between behavior in vivo and in vitro is to develop simulation models that explicitly attempt to model intracellular environments at the molecular scale, and that thereby can be used to directly monitor biophysical behavior in conditions that accurately mimic those encountered in vivo. It is with studies of this type that the present review will be concerned. We review in detail four published studies that have attempted to simulate the structure and dynamics of the bacterial cytoplasm and that have each explored different biophysical aspects of the cellular interior. While each of these studies has yielded important new insights, there are important questions that remain to be resolved in terms of determining the relative contributions made by energetic and hydrodynamic interactions to the diffusive behavior of macromolecules and to the thermodynamics of protein folding and associations in vivo. Some possible new directions for future generation simulation models of the cytoplasm are outlined.

On the interaction mechanisms of a p53 peptide and nutlin with the MDM2 and MDMX proteins: a Brownian dynamics study

The interaction of p53 with its regulators MDM2 and MDMX plays a major role in regulating the cell cycle. Inhibition of this interaction has become an important therapeutic strategy in oncology. Although MDM2 and MDMX share a very high degree of sequence/structural similarity, the small-molecule inhibitor nutlin appears to be an efficient inhibitor only of the p53-MDM2 interaction. Here, we investigate the mechanism of interaction of nutlin with these two proteins and contrast it with that of p53 using Brownian dynamics simulations. In contrast to earlier attempts to examine the bound states of the partners, here we locate initial reaction events in these interactions by identifying the regions of space around MDM2/MDMX, where p53/nutlin experience associative encounters with prolonged residence times relative to that in bulk solution. We find that the initial interaction of p53 with MDM2 is long-lived relative to nutlin, but, unlike nutlin, it takes place at the N- and C termini of the MDM2 protein, away from the binding site, suggestive of an allosteric mechanism of action. In contrast, nutlin initially interacts with MDM2 directly at the clefts of the binding site. The interaction of nutlin with MDMX, however, is very short-lived compared with MDM2 and does not show such direct initial interactions with the binding site. Comparison of the topology of the electrostatic potentials of MDM2 and MDMX and the locations of the initial encounters with p53/nutlin in tandem with structure-based sequence alignment revealed that the origin of the diminished activity of nutlin toward MDMX relative to MDM2 may stem partly from the differing topologies of the electrostatic potentials of the two proteins. Glu25 and Lys51 residues underpin these topological differences and appear to collectively play a key role in channelling nutlin directly toward the binding site on the MDM2 surface and are absent in MDMX. The results, therefore, provide new insight into the mechanism of p53/nutlin interactions with MDM2 and MDMX and could potentially have a broader impact on anticancer drug optimization strategies.