Predicting stable binding modes from simulated dimers of the D76N mutant of β2-microglobulin

The D76N mutant of the beta-2-microgobulin protein is a biologically motivated model system to study protein aggregation. There is strong experimental evidence, supported by molecular simulations, that D76N populates a highly dynamic conformation (which we originally named I2) that exposes aggregation-prone patches as a result of the detachment of the two terminal regions. Here, we use Molecular Dynamics simulations to study the stability of an ensemble of dimers of I2 generated via protein-protein docking. MM-PBSA calculations indicate that within the ensemble of investigated dimers the major contribution to interface stabilization at physiological pH comes from hydrophobic interactions between apolar residues. Our structural analysis also reveals that the interfacial region associated with the most stable binding modes are particularly rich in residues pertaining to both the N- and C-terminus, as well residues from the BC- and DE-loops. On the other hand, the less stable interfaces are stabilized by intermolecular interactions involving residues from the CD- and EF-loops. By focusing on the most stable binding modes, we used a simple geometric rule to propagate the corresponding dimer interfaces. We found that, in the absence of any kind of structural rearrangement occurring at an early stage of the oligomerization pathway, some interfaces drive a self-limited growth process, while others can be propagated indefinitely allowing the formation of long, polymerized chains. In particular, the interfacial region of the most stable binding mode reported here falls in the class of self-limited growth.

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Flavonoids as Putative Epi-Modulators: Insight into Their Binding Mode with BRD4 Bromodomains Using Molecular Docking and Dynamics

Biomolecules ◽

10.3390/biom8030061 ◽

2018 ◽

Vol 8 (3) ◽

pp. 61 ◽

Cited By ~ 9

Author(s):

Fernando Prieto-Martínez ◽

José Medina-Franco

Keyword(s):

Kinase Inhibitors ◽

Binding Mode ◽

Binding Modes ◽

Ligand Interaction ◽

Bet Inhibitors ◽

Protein Ligand Interaction ◽

Brd4 Inhibition ◽

Dynamics Simulations ◽

Insight Into

Flavonoids are widely recognized as natural polydrugs, given their anti-inflammatory, antioxidant, sedative, and antineoplastic activities. Recently, different studies showed that flavonoids have the potential to inhibit bromodomain and extraterminal (BET) bromodomains. Previous reports suggested that flavonoids bind between the Z and A loops of the bromodomain (ZA channel) due to their orientation and interactions with P86, V87, L92, L94, and N140. Herein, a comprehensive characterization of the binding modes of fisetin and the biflavonoid, amentoflavone, is discussed. To this end, both compounds were docked with BET bromodomain 4 (BRD4) using four docking programs. The results were post-processed with protein–ligand interaction fingerprints. To gain further insight into the binding mode of the two natural products, the docking results were further analyzed with molecular dynamics simulations. The results showed that amentoflavone makes numerous contacts in the ZA channel, as previously described for flavonoids and kinase inhibitors. It was also found that amentoflavone can potentially make contacts with non-canonical residues for BET inhibition. Most of these contacts were not observed with fisetin. Based on these results, amentoflavone was experimentally tested for BRD4 inhibition, showing activity in the micromolar range. This work may serve as the basis for scaffold optimization and the further characterization of flavonoids as BET inhibitors.

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Numerical analysis of Pickering emulsion stability: insights from ABMD simulations

Faraday Discussions ◽

10.1039/c6fd00055j ◽

2016 ◽

Vol 191 ◽

pp. 287-304 ◽

Cited By ~ 9

Author(s):

François Sicard ◽

Alberto Striolo

Keyword(s):

Early Stage ◽

Dissipative Particle Dynamics ◽

Contact Angles ◽

Hydrodynamic Resistance ◽

Interfacial Region ◽

Dense Layer ◽

Pickering Emulsions ◽

Mesoscopic Level ◽

Nanoparticle Mobility ◽

Dynamics Simulations

The issue of the stability of Pickering emulsions is tackled at a mesoscopic level using dissipative particle dynamics simulations within the Adiabatic Biased Molecular Dynamics framework. We consider the early stage of the coalescence process between two spherical water droplets in a decane solvent. The droplets are stabilized by Janus nanoparticles of different shapes (spherical and ellipsoidal) with different three-phase contact angles. Given a sufficiently dense layer of particles on the droplets, we show that the stabilization mechanism strongly depends on the collision speed. This is consistent with a coalescence mechanism governed by the rheology of the interfacial region. When the system is forced to coalesce sufficiently slowly, we investigate at a mesoscopic level how the ability of the nanoparticles to stabilize Pickering emulsions is discriminated by nanoparticle mobility and the associated caging effect. These properties are both related to the interparticle interaction and the hydrodynamic resistance in the liquid film between the approaching interfaces.

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Structural Effects of Cation Binding to DPPC Monolayers

10.26434/chemrxiv.12894962 ◽

2020 ◽

Author(s):

Matti Javanainen ◽

Wei Hua ◽

Ondrej Tichacek ◽

Pauline Delcroix ◽

Lukasz Cwiklik ◽

...

Keyword(s):

Radical Change ◽

Binding Mode ◽

Cation Binding ◽

Head Group ◽

Binding Modes ◽

Sum Frequency ◽

Area Per Lipid ◽

Simulation And Experiment ◽

Lipid Head Group ◽

Dynamics Simulations

Ions at the two sides of the plasma membrane maintain the transmembrane potential, participate in signaling, and affect the properties of the membrane itself. The extracellular leaflet is particularly enriched in phosphatidylcholine lipids an under the influence of Na+, Ca2+, and Cl− ions. In this work, we combined molecular dynamics simulations performed using state-of-the-art models with vibrational sum frequency generation (VSFG) spectroscopy to study the effects of these key ions on the structure of dipalmitoylphosphatidylcholine. We used lipid monolayers as a proxy for membranes, as this approach enabled a direct comparison between simulation and experiment. We find that the effects of Na+ are minor. Ca2+, on the other hand, strongly affects the lipid head group conformations and induces a tighter packing of lipids, thus promoting the liquid condensed phase. It does so by binding to both the phosphate and carbonyl oxygens via direct and water-mediated binding modes, the ratios of which depend on the monolayer packing. Clustering analysis performed on simulation data revealed that changes in area per lipid or CaCl2 concentration both affect the head group conformations, yet their effects are anti-correlated. Cations at the monolayer surface also attract Cl−, which at large CaCl2 concentrations penetrates deep to the monolayer. This phenomenon coincides with a radical change in the VSFG spectra of the phosphate group, thus indicating the emergence of a new binding mode.

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Structural Effects of Cation Binding to DPPC Monolayers

10.26434/chemrxiv.12894962.v1 ◽

2020 ◽

Author(s):

Matti Javanainen ◽

Wei Hua ◽

Ondrej Tichacek ◽

Pauline Delcroix ◽

Lukasz Cwiklik ◽

...

Keyword(s):

Radical Change ◽

Binding Mode ◽

Cation Binding ◽

Head Group ◽

Binding Modes ◽

Sum Frequency ◽

Area Per Lipid ◽

Simulation And Experiment ◽

Lipid Head Group ◽

Dynamics Simulations

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Molecular basis for lipid recognition by the prostaglandin D2 receptor CRTH2

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2102813118 ◽

2021 ◽

Vol 118 (32) ◽

pp. e2102813118

Author(s):

Heng Liu ◽

R. N. V. Krishna Deepak ◽

Anna Shiriaeva ◽

Cornelius Gati ◽

Alexander Batyuk ◽

...

Keyword(s):

Inflammatory Responses ◽

D2 Receptor ◽

Binding Mode ◽

Lipid Binding ◽

Prostaglandin D2 ◽

Polar Group ◽

Binding Modes ◽

Binding Pockets ◽

Dynamics Simulations ◽

G Protein Coupled

Prostaglandin D2 (PGD2) signals through the G protein–coupled receptor (GPCR) CRTH2 to mediate various inflammatory responses. CRTH2 is the only member of the prostanoid receptor family that is phylogenetically distant from others, implying a nonconserved mechanism of lipid action on CRTH2. Here, we report a crystal structure of human CRTH2 bound to a PGD2 derivative, 15R-methyl-PGD2 (15mPGD2), by serial femtosecond crystallography. The structure revealed a “polar group in”–binding mode of 15mPGD2 contrasting the “polar group out”–binding mode of PGE2 in its receptor EP3. Structural comparison analysis suggested that these two lipid-binding modes, associated with distinct charge distributions of ligand-binding pockets, may apply to other lipid GPCRs. Molecular dynamics simulations together with mutagenesis studies also identified charged residues at the ligand entry port that function to capture lipid ligands of CRTH2 from the lipid bilayer. Together, our studies suggest critical roles of charge environment in lipid recognition by GPCRs.

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Structural Design and Analysis of the RHOA-ARHGEF1 Binding Mode: Challenges and Applications for Protein-Protein Interface Prediction

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.643728 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ennys Gheyouche ◽

Matthias Bagueneau ◽

Gervaise Loirand ◽

Bernard Offmann ◽

Stéphane Téletchéa

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulations ◽

Interface Design ◽

Protein Structures ◽

Binding Mode ◽

Protein Docking ◽

Protein Interface ◽

Nucleotide Exchange ◽

Protein Protein Interaction ◽

Dynamics Simulations

The interaction between two proteins may involve local movements, such as small side-chains re-positioning or more global allosteric movements, such as domain rearrangement. We studied how one can build a precise and detailed protein-protein interface using existing protein-protein docking methods, and how it can be possible to enhance the initial structures using molecular dynamics simulations and data-driven human inspection. We present how this strategy was applied to the modeling of RHOA-ARHGEF1 interaction using similar complexes of RHOA bound to other members of the Rho guanine nucleotide exchange factor family for comparative assessment. In parallel, a more crude approach based on structural superimposition and molecular replacement was also assessed. Both models were then successfully refined using molecular dynamics simulations leading to protein structures where the major data from scientific literature could be recovered. We expect that the detailed strategy used in this work will prove useful for other protein-protein interface design. The RHOA-ARHGEF1 interface modeled here will be extremely useful for the design of inhibitors targeting this protein-protein interaction (PPI).

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The Early Phase of β2m Aggregation: An Integrative Computational Study Framed on the D76N Mutant and the ΔN6 Variant

Biomolecules ◽

10.3390/biom9080366 ◽

2019 ◽

Vol 9 (8) ◽

pp. 366 ◽

Cited By ~ 4

Author(s):

Rui J. S. Loureiro ◽

Diogo Vila-Viçosa ◽

Miguel Machuqueiro ◽

Eugene I. Shakhnovich ◽

Patrícia F. N. Faísca

Keyword(s):

Hot Spots ◽

Ex Vivo ◽

Computational Study ◽

Early Stage ◽

Single Point ◽

Protein Docking ◽

Docking Simulations ◽

C Terminus ◽

N Terminus ◽

Self Association

Human β2-microglobulin (b2m) protein is classically associated with dialysis-related amyloidosis (DRA). Recently, the single point mutant D76N was identified as the causative agent of a hereditary systemic amyloidosis affecting visceral organs. To get insight into the early stage of the β2m aggregation mechanism, we used molecular simulations to perform an in depth comparative analysis of the dimerization phase of the D76N mutant and the ΔN6 variant, a cleaved form lacking the first six N-terminal residues, which is a major component of ex vivo amyloid plaques from DRA patients. We also provide first glimpses into the tetramerization phase of D76N at physiological pH. Results from extensive protein–protein docking simulations predict an essential role of the C- and N-terminal regions (both variants), as well as of the BC-loop (ΔN6 variant), DE-loop (both variants) and EF-loop (D76N mutant) in dimerization. The terminal regions are more relevant under acidic conditions while the BC-, DE- and EF-loops gain importance at physiological pH. Our results recapitulate experimental evidence according to which Tyr10 (A-strand), Phe30 and His31 (BC-loop), Trp60 and Phe62 (DE-loop) and Arg97 (C-terminus) act as dimerization hot-spots, and further predict the occurrence of novel residues with the ability to nucleate dimerization, namely Lys-75 (EF-loop) and Trp-95 (C-terminus). We propose that D76N tetramerization is mainly driven by the self-association of dimers via the N-terminus and DE-loop, and identify Arg3 (N-terminus), Tyr10, Phe56 (D-strand) and Trp60 as potential tetramerization hot-spots.

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Molecular Recognition between Aβ-Specific Single-Domain Antibody and Aβ Misfolded Aggregates

Antibodies ◽

10.3390/antib7030025 ◽

2018 ◽

Vol 7 (3) ◽

pp. 25 ◽

Cited By ~ 5

Author(s):

Mingzhen Zhang ◽

Jie Zheng ◽

Ruth Nussinov ◽

Buyong Ma

Keyword(s):

Dynamic Properties ◽

Binding Mode ◽

Single Domain ◽

Binding Modes ◽

Single Domain Antibody ◽

Domain Antibody ◽

Ad Prevention ◽

Dynamics Simulations ◽

Β Sheet ◽

Complementarity Determining Region

Aβ is the toxic amyloid polypeptide responsible for Alzheimer’s disease (AD). Prevention and elimination of the Aβ misfolded aggregates are the promising therapeutic strategies for the AD treatments. Gammabody, the Aβ-Specific Single-domain (VH) antibody, recognizes Aβ aggregates with high affinity and specificity and reduces their toxicities. Employing the molecular dynamics simulations, we studied diverse gammabody-Aβ recognition complexes to get insights into their structural and dynamic properties and gammabody-Aβ recognitions. Among many heterogeneous binding modes, we focused on two gammabody-Aβ recognition scenarios: recognition through Aβ β-sheet backbone and on sidechain surface. We found that the gammabody primarily uses the complementarity-determining region 3 (CDR3) loop with the grafted Aβ sequence to interact with the Aβ fibril, while CDR1/CDR2 loops have very little contact. The gammabody-Aβ complexes with backbone binding mode are more stable, explaining the gammabody’s specificity towards the C-terminal Aβ sequence.

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Mechanistic insights of the attenuation of quorum-sensing-dependent virulence factors of Pseudomonas aeruginosa: Molecular modeling of the interaction of taxifolin with transcriptional regulator LasR

10.1101/500157 ◽

2018 ◽

Author(s):

Hovakim Grabski ◽

Susanna Tiratsuyan

Keyword(s):

Pseudomonas Aeruginosa ◽

Quorum Sensing ◽

Biofilm Formation ◽

Principal Component ◽

Binding Mode ◽

Machine Learning Techniques ◽

Hydroxyl Group ◽

Binding Modes ◽

And Cluster Analysis ◽

Dynamics Simulations

Pseudomonas aeruginosa is one of the most dangerous superbugs and is responsible for both acute and chronic infection. Current therapies are not effective because of biofilms that increase antibiotic resistance. Bacterial virulence and biofilm formation are regulated through a system called quorum sensing, which includes transcriptional regulators LasR and RhIR. These regulators are activated by their own natural autoinducers. Targeting this system is a promising strategy to combat bacterial pathogenicity. Flavonoids are very well known for their antimicrobial activity and taxifolin is one of them. It is also known that flavonoids inhibit Pseudomonas aeruginosa biofilm formation, but the mechanism of action is unknown. In the present study, we tried to analyse the mode of interactions of LasR with taxifolin. We used a combination of molecular docking, molecular dynamics simulations and machine learning techniques, which includes principal component and cluster analysis to study the interaction of the LasR protein with taxifolin. We show that taxifolin has two binding modes. One binding mode is the interaction with ligand binding domain. The second mode is the interaction with the "bridge", which is a cryptic binding site. It involves conserved amino acid interactions from multiple domains. Biochemical studies show hydroxyl group of ring A in flavonoids is necessary for inhibition. In our model the hydroxyl group ensures the formation of many hydrogen bonds during the second binding mode. Microsecond simulations also show the stability of the formed complex. This study may offer insights on how taxifolin inhibits LasR and the quorum sensing circuitry.

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Molecular Basis of Artemisinin Derivatives Inhibition of Myeloid Differentiation Protein 2 by Combined in Silico and Experimental Study

Molecules ◽

10.3390/molecules26185698 ◽

2021 ◽

Vol 26 (18) ◽

pp. 5698

Author(s):

Sennan Qiao ◽

Hansi Zhang ◽

Fei Sun ◽

Zhenyan Jiang

Keyword(s):

Free Energy ◽

Hydrophobic Interactions ◽

Binding Free Energy ◽

Binding Mode ◽

Experimental Results ◽

Myeloid Differentiation ◽

Inhibition Mechanism ◽

Artemisinin Derivatives ◽

Anti Inflammatory ◽

Dynamics Simulations

Artemisinin (also known as Qinghaosu) , an active component of the Qinghao extract, is widely used as antimalarial drug. Previous studies reveal that artemisinin and its derivatives also have effective anti-inflammatory and immunomodulatory properties, but the direct molecular target remains unknown. Recently, several reports mentioned that myeloid differentiation factor 2 (MD-2, also known as lymphocyte antigen 96) may be the endogenous target of artemisinin in the inhibition of lipopolysaccharide signaling. However, the exact interaction between artemisinin and MD-2 is still not fully understood. Here, experimental and computational methods were employed to elucidate the relationship between the artemisinin and its inhibition mechanism. Experimental results showed that artemether exhibit higher anti-inflammatory activity performance than artemisinin and artesunate. Molecular docking results showed that artemisinin, artesunate, and artemether had similar binding poses, and all complexes remained stable throughout the whole molecular dynamics simulations, whereas the binding of artemisinin and its derivatives to MD-2 decreased the TLR4(Toll-Like Receptor 4)/MD-2 stability. Moreover, artemether exhibited lower binding energy as compared to artemisinin and artesunate, which is in good agreement with the experimental results. Leu61, Leu78, and Ile117 are indeed key residues that contribute to the binding free energy. Binding free energy analysis further confirmed that hydrophobic interactions were critical to maintain the binding mode of artemisinin and its derivatives with MD-2.

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