Dissociation Process of a MDM2/p53 Complex Investigated by Parallel Cascade Selection Molecular Dynamics and the Markov State Model

Impact of Nonnative Interactions on the Binding Kinetics of Intrinsically Disordered p53 with MDM2: Insights from All-Atom Simulation and Markov State Model Analysis

Intrinsically disordered proteins (IDPs) lack a well-defined tertiary structure but are essential players in various biological processes. Their ability to undergo a disorder-to-order transition upon binding to their partners, known as the folding-upon-binding process, is crucial for their function. One classical example is the intrinsically disordered transactivation domain (TAD) of the tumor suppressor protein p53, which quickly forms a structured α-helix after binding to its partner MDM2, with clinical significance for cancer treatment. However, the contribution of nonnative interactions between the IDP and its partner to the rapid binding kinetics, as well as their interplay with native interactions, is not well understood at the atomic level. Here, we used molecular dynamics simulation and Markov state model (MSM) analysis to study the folding-upon-binding mechanism between p53-TAD and MDM2. Our results suggest that the system progresses from the nascent encounter complex to the well-structured encounter complex and finally reaches the native complex, following an induced-fit mechanism. We found that nonnative hydrophobic and hydrogen bond interactions, combined with native interactions, effectively stabilize the nascent and well-structured encounter complexes. Among the nonnative interactions, Leu25p53-Leu54MDM2 and Leu25p53-Phe55MDM2 are particularly noteworthy, as their interaction strength is close to the optimum. Evidently, strengthening or weakening these interactions could both adversely affect the binding kinetics. Overall, our findings suggest that nonnative interactions are evolutionarily optimized to accelerate the binding kinetics of IDPs in conjunction with native interactions.

PaCS-Toolkit: Optimized Software Utilities for Parallel Cascade Selection Molecular Dynamics (PaCS-MD) Simulations and Subsequent Analyses

Parallel cascade selection molecular dynamics (PaCS-MD) is an enhanced conformational sampling method conducted as a "repetition of time leaps in parallel worlds", comprising cycles of multiple molecular dynamics (MD) simulations performed in parallel and selection of the initial structures of MDs for the next cycle. We developed PaCS-Toolkit, an optimized software utility enabling the use of different MD software and trajectory analysis tools to facilitate the execution of the PaCS-MD simulation and analyze the obtained trajectories, including the preparation for the subsequent construction of the Markov state model. PaCS-Toolkit is coded with Python, is compatible with various computing environments, and allows for easy customization by editing the configuration file and specifying the MD software and analysis tools to be used. We present the software design of PaCS-Toolkit and demonstrate applications of PaCS-MD variations: original targeted PaCS-MD to peptide folding; rmsdPaCS-MD to protein domain motion; and dissociation PaCS-MD to ligand dissociation from adenosine A2A receptor.

Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch

Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site. While the association paths of neomycin to N1 and its variants remain unknown, recent fluorescence kinetic experiments indicate a two-step process driven by conformational selection. This raises the question of which step is affected by mutations. To address this, we performed all-atom two-dimensional replica-exchange molecular dynamics simulations for N1 and U14C, U14C[Formula: see text], U15A, and A17G mutants, ensuring extensive conformational sampling of both RNA and neomycin. The obtained neomycin association and binding paths, along with multidimensional free-energy profiles, revealed a two-step binding mechanism, consisting of conformational selection and induced fit. Neomycin binds to a preformed N1 conformation upon identifying a stable upper stem and U-turn motif in the riboswitch hairpin. However, the positioning of neomycin in the binding site occurs at different RNA-neomycin distances for each mutant, which may explain their different regulatory activities. The subsequent induced fit arises from the interactions of the neomycin's N3 amino group with RNA, causing the G9 backbone to rearrange. In the A17G mutant, the critical C6-A17/G17 stacking forms at a closer RNA-neomycin distance compared to N1. These findings together with estimated binding free energies coincide with experiments and elucidate why the A17G mutation decreases and U15A enhances N1 activity in response to neomycin.

Energetic and Kinetic Origins of CALB Interfacial Activation Revealed by PaCS-MD/MSM

The conformational dynamics of Candida antarctica lipase B (CALB) was investigated by molecular dynamics (MD) simulation, parallel cascade selection MD (PaCS-MD), and the Markov state model (MSM) and mainly focused on the lid-opening motion closely related to substrate binding. All-atom MD simulation of CALB was conducted in water and on the interface of water and tricaprylin. CALB initially situated in water and separated by layers of water from the interface is spontaneously adsorbed onto the tricaprylin surface during MD simulation. The opening and closing motions of the lid are simulated by PaCS-MD, and subsequent MSM analysis provided the free-energy landscape and time scale of the conformational transitions among the closed, semiopen, and open states. The closed state is the most stable in the water system, but the stable conformation in the interface system shifts to the semiopen state. These effects could explain the energetics and kinetics origin of the previously reported interfacial activation of CALB. These findings could help expand the application of CALB toward a wide variety of substrates.

Molecular Simulation to Investigate Open-Close Motion of a Flagellar Export Apparatus Protein FlhAC

Molecular dynamics (MD) simulation and parallel cascade selection molecular dynamics (PaCS-MD) are widely used to investigate large-amplitude motions of proteins. PaCS-MD is an enhanced conformational sampling method consisting of cycles of parallel unbiased MD simulations combined with a selection of MD snapshots as the initial structures for the next cycle. In addition, free energy calculation can be achieved by the combination of PaCS-MD and the Markov state model (MSM). In this chapter, the protocols to investigate the open-close motion of a flagellar export apparatus protein, FlhA_C, by MD and the combination of PaCS-MD and MSM are described.

Simulation toolkits at the molecular scale for trans-scale thermal signaling

Thermogenesis is a physiological activity of releasing heat that originates from intracellular biochemical reactions. Recent experimental studies discovered that externally applied heat changes intracellular signaling locally, resulting in global changes in cell morphology and signaling. Therefore, we hypothesize an inevitable contribution of thermogenesis in modulating biological system functions throughout the spatial scales from molecules to individual organisms. One key issue examining the hypothesis, namely, the "trans-scale thermal signaling," resides at the molecular scale on the amount of heat released via individual reactions and by which mechanism the heat is employed for cellular function operations. This review introduces atomistic simulation tool kits for studying the mechanisms of thermal signaling processes at the molecular scale that even state-of-the-art experimental methodologies of today are hardly accessible. We consider biological processes and biomolecules as potential heat sources in cells, such as ATP/GTP hydrolysis and multiple biopolymer complex formation and disassembly. Microscopic heat release could be related to mesoscopic processes via thermal conductivity and thermal conductance. Additionally, theoretical simulations to estimate these thermal properties in biological membranes and proteins are introduced. Finally, we envisage the future direction of this research field.

How Peptides Bind to PSD-95/Discs-Large/ZO-1 Domains

PSD-95/discs-large/ZO-1 (PDZ) domains form a large family of adaptor proteins that bind to the C-terminal tails of their binding partner proteins. Via extensive molecular dynamics simulations and alchemical free energy calculations, we characterized the binding modi of phosphorylated and unphosphorylated EQVSAV peptides and of a EQVEAV phosphate mimic to the hPTP1E PDZ2 and MAGI1 PDZ1 domains. The simulations reproduced the well-known binding characteristics such as tight coordination of the peptidic carboxyl tail and pronounced hydrogen bonding between the peptide backbone and the backbone atoms of a β-sheet in PDZ. Overall, coordination by hPTP1E PDZ2 appeared tighter than by MAGI1 PDZ1. Simulations of wild-type PDZ and arginine mutants suggest that contacts with Arg79/85 in hPTP1E/MAGI1 are more important for the EQVEAV peptide than for EQVSAV. Alchemical free energy calculations and PaCS-MD simulations could well reproduce the difference in binding free energy between unphosphorylated EQVSAV and EQVEAV peptides and the absolute binding free energy of EQVSAV. However, likely due to small force field inaccuracies, the simulations erroneously favored binding of the phosphorylated peptide instead of its unphosphorylated counterpart, which is in contrast to the experiment.

Inhibition of the hexamerization of SARS-CoV-2 endoribonuclease and modeling of RNA structures bound to the hexamer

Non-structural protein 15 (Nsp15) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) forms a homo hexamer and functions as an endoribonuclease. Here, we propose that Nsp15 activity may be inhibited by preventing its hexamerization through drug binding. We first explored the stable conformation of the Nsp15 monomer as the global free energy minimum conformation in the free energy landscape using a combination of parallel cascade selection molecular dynamics (PaCS-MD) and the Markov state model (MSM), and found that the Nsp15 monomer forms a more open conformation with larger druggable pockets on the surface. Targeting the pockets with high druggability scores, we conducted ligand docking and identified compounds that tightly bind to the Nsp15 monomer. The top poses with Nsp15 were subjected to binding free energy calculations by dissociation PaCS-MD and MSM (dPaCS-MD/MSM), indicating the stability of the complexes. One of the identified pockets, which is distinctively bound by inosine analogues, may be an alternative binding site to stabilize viral RNA binding and/or an alternative catalytic site. We constructed a stable RNA structure model bound to both UTP and alternative binding sites, providing a reasonable proposed model of the Nsp15/RNA complex.

Dissociation Pathways of the p53 DNA Binding Domain from DNA and Critical Roles of Key Residues Elucidated by dPaCS-MD/MSM

p53 is a transcriptional factor that regulates cell response to a variety of stresses. About a half of all human tumors contain p53 mutations, and the accumulation of mutations in the DNA binding domain of p53 (p53-DBD) can cause destabilization of p53 and its complex with DNA. To identify the key residues of the p53-DBD/DNA binding and to understand the dissociation mechanisms of the p53-DBD/DNA complex, the dissociation process of p53-DBD from a DNA duplex that contains the consensus sequence (the specific target of p53-DBD) was investigated by a combination of dissociation parallel cascade selection molecular dynamics (dPaCS-MD) and the Markov state model (MSM). This combination (dPaCS-MD/MSM) enabled us to simulate dissociation of the two large molecules based on an all-atom model with a short simulation time (11.2 ± 2.2 ns per trial) and to analyze dissociation pathways, free energy landscape (FEL), and binding free energy. Among 75 trials of dPaCS-MD, p53-DBD dissociated first from the major groove and then detached from the minor groove in 93% of the cases, while 7% of the cases unbinding from the minor groove occurred first. Minor groove binding is mainly stabilized by R248, identified as the most important residue that tightly binds deep inside the minor groove. The standard binding free energy calculated from the FEL was -10.9 ± 0.4 kcal/mol, which agrees with an experimental value of -11.1 kcal/mol. These results indicate that the dPaCS-MD/MSM combination can be a powerful tool to investigate dissociation mechanisms of two large molecules. Analysis of the p53 key residues for DNA binding indicates high correlations with cancer-related mutations, confirming that impairment of the interactions between p53-DBD and DNA can be frequently related to cancer.

Mechanistic insight into the destabilization of p53TD tetramer by cancer-related R337H mutation: a molecular dynamics study

The p53 protein is a tumor suppressor crucial for cell cycle and genome integrity. In a very large proportion of human cancers, p53 is frequently inactivated by mutations located in its DNA-binding domain (DBD). Some experimental studies reported that the inherited R337H mutation located in the p53 tetramerization domain (p53TD) can also result in destabilization of the p53 protein, and consequently lead to an organism prone to cancer setup. However, the underlying R337H mutation-induced structural destabilization mechanism is not well understood. Herein, we investigate the structural stability and dynamic property of the wild type p53TD tetramer and its cancer-related R337H mutant by performing multiple microsecond molecular dynamics simulations. It is found that R337H mutation destroys the R337-D352 hydrogen bonds, weakens the F341-F341 π-π stacking interaction and the hydrophobic interaction between aliphatic hydrocarbons of R337 and M340, leading to more solvent exposure of all the hydrophobic cores, and thus disrupting the structural integrity of the tetramer. Importantly, our simulations show for the first time that R337H mutation results in unfolding of the α-helix starting from the N-terminal region (residues ³³⁵RER(H)FEM³⁴⁰). Consistently, community network analyses reveal that R337H mutation reduces dynamical correlation and global connectivity of p53TD tetramer, which destabilizes the structure of the p53TD tetramer. This study provides the atomistic mechanism of R337H mutation-induced destabilization of p53TD tetramer, which might be helpful for in-depth understanding of the p53 loss-of-function mechanism.

Binding free energy of protein/ligand complexes calculated using dissociation Parallel Cascade Selection Molecular Dynamics and Markov state model

We recently proposed a computational procedure to simulate the dissociation of protein/ligand complexes using the dissociation Parallel Cascade Selection Molecular Dynamics simulation (dPaCS-MD) method and to analyze the generated trajectories using the Markov state model (MSM). This procedure, called dPaCS-MD/MSM, enables calculation of the dissociation free energy profile and the standard binding free energy. To examine whether this method can reproduce experimentally determined binding free energies for a variety of systems, we used it to investigate the dissociation of three protein/ligand complexes: trypsin/benzamine, FKBP/FK506, and adenosine A_2A receptor/T4E. First, dPaCS-MD generated multiple dissociation pathways within a reasonable computational time for all the complexes, although the complexes differed significantly in the size of the molecules and in intermolecular interactions. Subsequent MSM analyses produced free energy profiles for the dissociations, which provided insights into how each ligand dissociates from the protein. The standard binding free energies obtained by dPaCS-MD/MSM are in good agreement with experimental values for all the complexes. We conclude that dPaCS-MD/MSM can accurately calculate the binding free energies of these complexes.

Computer simulation of the Receptor-Ligand Interactions of Mannose Receptor CD206 in Comparison with the Lectin Concanavalin A Model

Computer modeling of complexation of mono- and oligosaccharide ligands with the main (fourth) carbohydrate-binding domain of the mannose receptor CD206 (CRD4), as well as with the model receptor concanavalin A (ConA), was carried out for the first time, using methods of molecular dynamics and neural network analysis. ConA was shown to be a relevant model of CD206 (CRD4) due to similarity of the structural organization of the binding sites and high correlation of the values of free energies of complexation between the literature data and computer modeling (r > 0.9). Role of the main factors affecting affinity of the ligand–receptor interactions is discussed: the number and nature of carbohydrate residues, presence of Me-group in the O1 position, type of the glycoside bond in dimannose. Complexation of ConA and CD206 with ligands is shown to be energetically caused by electrostatic interactions (E) of the charged residues (Asn, Asp, Arg) with oxygen and hydrogen atoms in carbohydrates; contributions of hydrophobic and van der Waals components is lower. Possibility of the additional stabilization of complexes due to the CH–π stacking interactions of Tyr with the Man plane is discussed. The role of calcium and manganese ions in binding ligands has been studied. The values of free energies of complexation calculated in the course of molecular dynamics simulation correlate with experimental data (published for the model ConA): correlation coefficient r = 0.68. The Pafnucy neural network was trained based on the set of PDBbind2020 ligand–receptor complexes, which significantly increased accuracy of the energy predictions to r = 0.8 and 0.82 for CD206 and ConA receptors, respectively. A model of normalization of the complexation energy values for calculating the relevant values of ΔG_bind, K_d is proposed. Based on the developed technique, values of the dissociation constants of a series of CD206 complexes with nine carbohydrate ligands of different structures were determined, which were not previously known. The obtained data open up possibilities for using computer modeling for the development of optimal drug carriers capable of active macrophage targeting, and also determine the limits of applicability of using ConA as a relevant model for studying parameters of the CD206 binding to various carbohydrate ligands.

Atomistic description of molecular binding processes based on returning probability theory

The efficiency of molecular binding such as host-guest binding is commonly evaluated in terms of kinetics, such as rate coefficients. In general, to compute the coefficient of the overall binding process, we need to consider both the diffusion of reactants and barrier crossing to reach the bound state. Here, we develop a methodology of quantifying the rate coefficient of binding based on molecular dynamics simulation and returning probability (RP) theory proposed by Kim and Lee [J. Chem. Phys. 131, 014503 (2009)]. RP theory provides a tractable formula of the rate coefficient in terms of the thermodynamic stability and kinetics of the intermediate state on a predefined reaction coordinate. In this study, the interaction energy between reactants is utilized as the reaction coordinate, enabling us to effectively describe the reactants' relative position and orientation on one-dimensional space. Application of this method to the host-guest binding systems, which consist of β-cyclodextrin and small guest molecules, yields the rate coefficients consistent with the experimental results.

Unraveling the Allosteric Mechanism of Four Cancer-related Mutations in the Disruption of p53-DNA Interaction

The p53 protein plays active roles in the physiological regulation of cell cycle as well as in cancer developments. In more than half of human cancers, the protein is inactivated by mutations located primarily in its DNA-binding domain (DBD), and some mutations located in the β-sandwich region of DBD are reported to decrease p53-DNA binding affinities. To understand the long-range correlation between p53 β-sandwich and DNA, and the allosteric mechanism of β-sandwich mutations in the disruption of p53-DNA interactions, we first identify three regions with a strong correlation with DNA based on microsecond molecular dynamics (MD) simulations of wild-type p53-DNA complex and then perform multiple MD simulations on four cancer-related mutants L145Q, P151S, Y220C, and G266R, which are located in these three regions. Our simulations show that these mutations allosterically destabilize the structural stability of the DNA-binding groove in p53 and disrupt the p53-DNA interactions. Network analyses reveal optimal correlation paths through which the mutation-induced allosteric signal passes to DNA, and the disturbance effect of these mutations on the global connectivity and dynamical correlation of the p53-DNA complex. This work paves the way for the in-depth understanding of the mutation-induced loss in p53's DNA-recognition ability and the pathological mechanism of cancer development.

Mechanism of Vitamin D Receptor Ligand-Binding Domain Regulation Studied by gREST Simulations

The vitamin D receptor ligand-binding domain (VDR-LBD) undergoes conformational changes upon ligand binding. In this nuclear receptor family, agonistic or antagonistic activities are controlled by the conformation of the helix (H)12. However, all crystal structures of VDR-LBD reported to date correspond to the active H12 conformation, regardless of agonist/antagonist binding. To understand the mechanism of VDR-LBD regulation structurally, conformational samplings of agonist- and antagonist-bound rat VDR-LBD were performed using the generalized replica exchange with solute tempering (gREST) method. The gREST simulations demonstrated different structural responses of rat VDR-LBD to agonist or antagonist binding, whereas in conventional molecular dynamics simulations, the conformation was the same as that of the crystal structures, regardless of agonist/antagonist binding. In the gREST simulations, a spontaneous conformational change of H12 was observed only for the antagonist complex. The different responses to agonist/antagonist binding were attributed to hydrophobic core formation at the ligand-binding pocket and cooperative rearrangements of H11. The gREST method can be applied to the examination of structure-activity relationships for multiple VDR-LBD ligands.

Reaction Pathway Sampling and Free-Energy Analyses for Multimeric Protein Complex Disassembly by Employing Hybrid Configuration Bias Monte Carlo/Molecular Dynamics Simulation

Physicochemical characterization of multimeric biomacromolecule assembly and disassembly processes is a milestone to understand the mechanisms for biological phenomena at the molecular level. Mass spectroscopy (MS) and structural bioinformatics (SB) approaches have become feasible to identify subcomplexes involved in assembly and disassembly, while they cannot provide atomic information sufficient for free-energy calculation to characterize transition mechanism between two different sets of subcomplexes. To combine observations derived from MS and SB approaches with conventional free-energy calculation protocols, we here designed a new reaction pathway sampling method by employing hybrid configuration bias Monte Carlo/molecular dynamics (hcbMC/MD) scheme and applied it to simulate the disassembly process of serum amyloid P component (SAP) pentamer. The results we obtained are consistent with those of the earlier MS and SB studies with respect to SAP subcomplex species and the initial stage of SAP disassembly processes. Furthermore, we observed a novel dissociation event, ring-opening reaction of SAP pentamer. Employing free-energy calculation combined with the hcbMC/MD reaction pathway trajectories, we moreover obtained experimentally testable observations on (1) reaction time of the ring-opening reaction and (2) importance of Asp42 and Lys117 for stable formation of SAP oligomer.

Recent advances in atomic molecular dynamics simulation of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) play important roles in cellular functions. The inherent structural heterogeneity of IDPs makes the high-resolution experimental characterization of IDPs extremely difficult. Molecular dynamics (MD) simulation could provide the atomic-level description of the structural and dynamic properties of IDPs. This perspective reviews the recent progress in atomic MD simulation studies of IDPs, including the development of force fields and sampling methods, as well as applications in IDP-involved protein-protein interactions. The employment of large-scale simulations and advanced sampling techniques allows more accurate estimation of the thermodynamics and kinetics of IDP-mediated protein interactions, and the holistic landscape of the binding process of IDPs is emerging.

Edge expansion parallel cascade selection molecular dynamics simulation for investigating large-amplitude collective motions of proteins

We propose edge expansion parallel cascade selection molecular dynamics (eePaCS-MD) as an efficient adaptive conformational sampling method to investigate the large-amplitude motions of proteins without prior knowledge of the conformational transitions. In this method, multiple independent MD simulations are iteratively conducted from initial structures randomly selected from the vertices of a multi-dimensional principal component subspace. This subspace is defined by an ensemble of protein conformations sampled during previous cycles of eePaCS-MD. The edges and vertices of the conformational subspace are determined by solving the "convex hull problem." The sampling efficiency of eePaCS-MD is achieved by intensively repeating MD simulations from the vertex structures, which increases the probability of rare event occurrence to explore new large-amplitude collective motions. The conformational sampling efficiency of eePaCS-MD was assessed by investigating the open-close transitions of glutamine binding protein, maltose/maltodextrin binding protein, and adenylate kinase and comparing the results to those obtained using related methods. In all cases, the open-close transitions were simulated in ∼10 ns of simulation time or less, offering 1-3 orders of magnitude shorter simulation time compared to conventional MD. Furthermore, we show that the combination of eePaCS-MD and accelerated MD can further enhance conformational sampling efficiency, which reduced the total computational cost of observing the open-close transitions by at most 36%.

An integrated view of p53 dynamics, function, and reactivation

The tumor suppressor p53 plays a vital role in responding to cell stressors such as DNA damage, hypoxia, and tumor formation by inducing cell-cycle arrest, senescence, or apoptosis. Expression level alterations and mutational frequency implicates p53 in most human cancers. In this review, we show how both computational and experimental methods have been used to provide an integrated view of p53 dynamics, function, and reactivation potential. We argue that p53 serves as an exceptional case study for developing methods in modeling intrinsically disordered proteins. We describe how these methods can be leveraged to improve p53 reactivation molecule design and other novel therapeutic modalities, such as PROteolysis TARgeting Chimeras (PROTACs).

A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors

Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better indicator of in vivo drug efficacy than binding affinity. However, obtaining drug-target unbinding rates poses significant challenges, both computationally and experimentally. This is particularly palpable for complex systems like G Protein-Coupled Receptors (GPCRs) whose ligand unbinding typically requires very long timescales oftentimes inaccessible by standard molecular dynamics simulations. Enhanced sampling methods offer a useful alternative, and their efficiency can be further improved by using machine learning tools to identify optimal reaction coordinates. Here, we test the combination of two machine learning techniques, automatic mutual information noise omission and reweighted autoencoded variational Bayes for enhanced sampling, with infrequent metadynamics to efficiently study the unbinding kinetics of two classical drugs with different RTs in a prototypic GPCR, the μ-opioid receptor. Dissociation rates derived from these computations are within one order of magnitude from experimental values. We also use the simulation data to uncover the dissociation mechanisms of these drugs, shedding light on the structures of rate-limiting transition states, which, alongside metastable poses, are difficult to obtain experimentally but important to visualize when designing drugs with a desired kinetic profile.

Effect of linker on the binding free energy of stapled p53/HDM2 complex

Inactivation of the tumor suppressor p53 resulting from the binding with a negative regulator HDM2 is among the predominant defects in human cancers. p53-mimicking peptides whose conformational and proteolytic stability is enhanced by an all-hydrocarbon staple are being recognized as promising anticancer agents for disrupting the p53–HDM2 binding and reactivating p53. Herein, we conduct a computational modeling and thermodynamic characterization of stapled p53/HDM2 complex via molecular docking, simulations, and binding free energy analysis. The binding thermodynamics analysis is done based on the end-point calculation of the effective binding energy—a sum of the direct peptide–protein interaction energy and the dehydration penalty—and on its decomposition into contributions from specific groups constituting the complex. This allows us to investigate how individual amino acids in the stapled p53 and HDM2 contribute to the binding affinity. We find that not only the epitope residues (F19, W23 and L26), but also the hydrocarbon linker of the stapled p53 impart significant contributions. Our computational approach will be useful in designing new stapled peptides in which the staple location is also optimized to improve the binding affinity.

Computational Investigation on the p53-MDM2 Interaction Using the Potential of Mean Force Study

Murine double minute 2 (MDM2) proteins are found to be overproduced by many human tumors in order to inhibit the functioning of p53 molecules, a tumor suppressor protein. Thus, reactivating p53 functioning in cancer cells by disrupting p53-MDM2 interactions may offer a significant approach in cancer treatment. However, the structural characterization of the p53-MDM2 complex at the atomistic level and the mechanism of binding/unbinding of the p53-MDM2 complex still remain unclear. Therefore, we demonstrate here the probable binding (unbinding) pathway of transactivation domain 1 of p53 during the formation (dissociation) of the p53-MDM2 complex in terms of free energy as a function of reaction coordinate from the potential of mean force (PMF) study using two different force fields: ff99SB and ff99SB-ILDN. From the PMF plot, we noticed the PMF to have a minimum value at a p53-MDM2 separation of 12 Å, with a dissociation energy of 30 kcal mol^-1. We also analyzed the conformational dynamics and stability of p53 as a function of its distance of separation from MDM2. The secondary structure content (helix and turns) in p53 was found to vary with its distance of separation from MDM2. The p53-MDM2 complex structure with lowest potential energy was isolated from the ensemble at the reaction coordinate corresponding to the minimum PMF value and subjected to molecular dynamics simulation to identify the interface surface area, interacting residues at the interface, and the stability of the complex. The simulation results highlight the importance of hydrogen bonds and the salt bridge between Lys94 of MDM2 and Glu17 of p53 in the stability of the p53-MDM2 complex. We also carried out the binding free energy calculations and the per residue energy decomposition analyses of the interface residues of the p53-MDM2 complex. We found that the binding affinity between MDM2 and p53 is indeed high [ΔG _bind = -7.29 kcal mol^-1 from molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) and ΔG _bind = -53.29 kcal mol^-1 from molecular mechanics/generalized borne surface area]. The total binding energy obtained using the MM/PBSA method was noticed to be closer to the experimental values (-6.4 to -9.0 kcal mol^-1). The p53-MDM2 complex binding profile was observed to follow the same trend even in the duplicate simulation run and also in the simulation carried out with different force fields. We found that Lys51, Leu54, Tyr100, and Tyr104 from MDM2 and the residues Phe19, Trp23, and Leu26 from p53 provide the highest energy contributions for the p53-MDM2 interaction. Our findings highlight the prominent structural and binding characteristics of the p53-MDM2 complex that may be useful in designing potential inhibitors to disrupt the p53-MDM2 interactions.

High pressure inhibits signaling protein binding to the flagellar motor and bacterial chemotaxis through enhanced hydration

High pressure below 100 MPa interferes inter-molecular interactions without causing pressure denaturation of proteins. In Escherichia coli, the binding of the chemotaxis signaling protein CheY to the flagellar motor protein FliM induces reversal of the motor rotation. Using molecular dynamics (MD) simulations and parallel cascade selection MD (PaCS-MD), we show that high pressure increases the water density in the first hydration shell of CheY and considerably induces water penetration into the CheY-FliM interface. PaCS-MD enabled us to observe pressure-induced dissociation of the CheY-FliM complex at atomic resolution. Pressure dependence of binding free energy indicates that the increase of pressure from 0.1 to 100 MPa significantly weakens the binding. Using high-pressure microscopy, we observed that high hydrostatic pressure fixes the motor rotation to the counter-clockwise direction. In conclusion, the application of pressure enhances hydration of the proteins and weakens the binding of CheY to FliM, preventing reversal of the flagellar motor.

ATP Converts Aβ42 Oligomer into Off-Pathway Species by Making Contact with Its Backbone Atoms Using Hydrophobic Adenosine

Adenosine triphosphate (ATP) is newly expected to be involved in the clearance of amyloid β 1-42 (Aβ₄₂) fibril and its precursors, Aβ₄₂ oligomer. Meanwhile, the microscopic mechanism of the role in dissolving the protein aggregate still remains elusive. Aiming to elucidate the mechanism, we examined effects of ATP on the conformational change and thermodynamic stability of the protomer dimer of Aβ₄₂ pentamer and tetramer, Aβ₄₂(9), by employing all-atom molecular dynamics simulations. We observed interprotomer twisting and intraprotomer peeling of Aβ₄₂(9). These conformational changes remarkably accelerate dissociation of the protomer dimer. However, the presence of ATP itself has no positive effect on dissociation processes of the protomer dimer and a monomer from the dimer, indicating its irrelevance to decomposition of the Aβ₄₂ oligomer. Rather, it could be supposed that ATP prevents additional binding and rebinding of Aβ₄₂ monomers to the Aβ₄₂ oligomer and it then converts Aβ₄₂ oligomer into an off-pathway species which is excluded from Aβ₄₂ fibril growth processes. Interestingly, hydrophobic adenosine in ATP makes contact with Aβ₄₂(9) on its backbone atoms, with respect to both Aβ₄₂ monomers on the edge of Aβ₄₂(9) and dissociated Aβ₄₂ monomers in Aβ₄₂(9). These roles of ATP would be applied without regard to the structural polymorphism of the Aβ₄₂ fibril.

Encounter complexes and hidden poses of kinase-inhibitor binding on the free-energy landscape

Modern drug discovery increasingly focuses on the drug-target binding kinetics which depend on drug (un)binding pathways. The conventional molecular dynamics simulation can observe only a few binding events even using the fastest supercomputer. Here, we develop 2D gREST/REUS simulation with enhanced flexibility of the ligand and the protein binding site. Simulation (43 μs in total) applied to an inhibitor binding to c-Src kinase covers 100 binding and unbinding events. On the statistically converged free-energy landscapes, we succeed in predicting the X-ray binding structure, including water positions. Furthermore, we characterize hidden semibound poses and transient encounter complexes on the free-energy landscapes. Regulatory residues distant from the catalytic core are responsible for the initial inhibitor uptake and regulation of subsequent bindings, which was unresolved by experiments. Stabilizing/blocking of either the semibound poses or the encounter complexes can be an effective strategy to optimize drug-target residence time.

How Does the Recently Discovered Peptide MIP Exhibit Much Higher Binding Affinity than an Anticancer Protein p53 for an Oncoprotein MDM2?

An oncoprotein MDM2 binds to the extreme N-terminal peptide region of a tumor suppressor protein p53 (p53NTD) and inhibits its anticancer activity. We recently discovered a peptide named MIP which exhibits much higher binding affinity for MDM2 than p53NTD. Experiments showed that the binding free energy (BFE) of MDM2-MIP is lower than that of MDM2-p53NTD by approximately -4 kcal/mol. Here, we develop a theoretical method which is successful in reproducing this quantitative difference and elucidating its physical origins. It enables us to decompose the BFE into a variety of energetic and entropic components, evaluate their relative magnitudes, and identify the physical factors driving or opposing the binding. It should be applicable also to the assessment of differences among ligands in the binding affinity for a particular receptor, which is a central issue in modern chemistry. In the MDM2 case, the higher affinity of MIP is ascribed to a larger gain of translational, configurational entropy of water upon binding. This result is useful to the design of a peptide possessing even higher affinity for MDM2 as a reliable drug against a cancer.

Molecular dynamics simulation of proteins under high pressure: Structure, function and thermodynamics

BACKGROUND

Molecular dynamics (MD) simulation is well-recognized as a powerful tool to investigate protein structure, function, and thermodynamics. MD simulation is also used to investigate high pressure effects on proteins. For conducting better MD simulation under high pressure, the main issues to be addressed are: (i) protein force fields and water models were originally developed to reproduce experimental properties obtained at ambient pressure; and (ii) the timescale to observe the pressure effect is often much longer than that of conventional MD simulations.

SCOPE OF REVIEW

First, we describe recent developments in MD simulation methodologies for studying the high-pressure structure and dynamics of protein molecules. These developments include force fields for proteins and water molecules, and enhanced simulation techniques. Then, we summarize recent studies of MD simulations of proteins in water under high pressure.

MAJOR CONCLUSIONS

Recent MD simulations of proteins in solution under pressure have reproduced various phenomena identified by experiments using high pressure, such as hydration, water penetration, conformational change, helix stabilization, and molecular stiffening.

GENERAL SIGNIFICANCE

MD simulations demonstrate differences in the properties of proteins and water molecules between ambient and high-pressure conditions. Comparing the results obtained by MD calculations with those obtained experimentally could reveal the mechanism by which biological molecular machines work well in collaboration with water molecules.