scholarly journals An atomistic perspective on ADCC quenching by core-fucosylation of IgG1 Fc N-glycans from enhanced sampling molecular dynamics

2019 ◽  
Author(s):  
Aoife Harbison ◽  
Elisa Fadda
Keyword(s):  
Molecular Dynamics ◽  
Binding Free Energy ◽  
Fine Tuning ◽  
Dependent Manner ◽  
Enhanced Sampling ◽  
Terminal Galactose ◽  
Molecular Determinants ◽  
Autoimmune Conditions ◽  
Membrane Bound ◽  
Core Fucosylation

AbstractThe immunoglobulin type G (IgG) Fc N-glycans are known to modulate the interaction with membrane-bound Fc γ receptors (FcγRs), fine-tuning the antibody’s effector function in a sequence-dependent manner. Particularly interesting in this respect are the roles of galactosylation, which levels are linked to autoimmune conditions and aging, of core fucosylation, which is known to reduce significantly the antibody-dependent cellular cytotoxicity (ADCC), and of sialylation, which also reduces ADCC but only in the context of core-fucosylation. In this work we provide an atomistic level perspective through enhanced sampling computer simulations, based on replica exchange molecular dynamics (REMD), to understand the molecular determinants linking the Fc N-glycans sequence to the observed IgG1 function. Our results indicate that the two symmetrically opposed N-glycans interact extensively through their core trimannose residues. At room temperature the terminal galactose on the α(1-6) arm is restrained to the protein through a network of interactions that keep the arm outstretched, meanwhile the α(1-3) arm extends towards the solvent where a terminal sialic acid remains fully accessible. We also find that the presence of core fucose interferes with the extended sialylated α(1-3) arm, altering its conformational propensity and as a consequence of steric hindrance, significantly enhancing the Fc dynamics. Furthermore, structural analysis shows that the core fucose position within the Fc core obstructs the access of N162 glycosylated FcγRs very much like a “door-stop”, potentially decreasing the IgG/FcγR binding free energy. All of these factors could represent important clues to understand at the molecular level the dramatic reduction of ADCC as a result of core fucosylation and provide an atomistic level-of-detail framework for the design of high potency IgG1 Fc N-glycoforms.

scholarly journals An atomistic perspective on antibody-dependent cellular cytotoxicity quenching by core-fucosylation of IgG1 Fc N-glycans from enhanced sampling molecular dynamics

Glycobiology ◽  
2019 ◽  
Vol 30 (6) ◽  
pp. 407-414 ◽  
Author(s):  
Aoife Harbison ◽  
Elisa Fadda
Keyword(s):  
Molecular Dynamics ◽  
Binding Free Energy ◽  
Fine Tuning ◽  
Dependent Manner ◽  
Cellular Cytotoxicity ◽  
Antibody Dependent Cellular Cytotoxicity ◽  
Enhanced Sampling ◽  
Terminal Galactose ◽  
Autoimmune Conditions ◽  
Core Fucosylation

Abstract The immunoglobulin type G (IgG) Fc N-glycans are known to modulate the interaction with membrane-bound Fc γ receptors (FcγRs), fine-tuning the antibody’s effector function in a sequence-dependent manner. Particularly interesting in this respect are the roles of galactosylation, which levels are linked to autoimmune conditions and aging, of core fucosylation, which is known to reduce significantly the antibody-dependent cellular cytotoxicity (ADCC), and of sialylation, which also reduces antibody-dependent cellular cytotoxicity (ADCC) but only in the context of core-fucosylation. In this article, we provide an atomistic level perspective through enhanced sampling computer simulations, based on replica exchange molecular dynamics (REMD), to understand the molecular determinants linking the Fc N-glycans sequence to the observed IgG1 function. Our results indicate that the two symmetrically opposed N-glycans interact extensively through their core trimannose residues. At room temperature, the terminal galactose on the α (1–6) arm is restrained to the protein through a network of interactions that keep the arm outstretched; meanwhile, the α (1–3) arm extends toward the solvent where a terminal sialic acid remains fully accessible. We also find that the presence of core fucose interferes with the extended sialylated α (1–3) arm, altering its conformational propensity and as a consequence of steric hindrance, significantly enhancing the Fc dynamics. Furthermore, structural analysis shows that the core-fucose position within the Fc core obstructs the access of N162 glycosylated FcγRs very much like a “door-stop,” potentially decreasing the IgG/FcγR binding free energy. These results provide an atomistic level-of-detail framework for the design of high potency IgG1 Fc N-glycoforms.

scholarly journals Phosphatidic acid inhibits SNARE priming by inducing conformational changes in Sec18 protomers

2018 ◽  
Author(s):  
Matthew L. Starr ◽  
Robert P. Sparks ◽  
Logan R. Hurst ◽  
Zhiyu Zhao ◽  
Andres Arango ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Phosphatidic Acid ◽  
Conformational Changes ◽  
Binding Sites ◽  
Membrane Curvature ◽  
Snare Proteins ◽  
Dependent Manner ◽  
Protein Architecture ◽  
Membrane Bound ◽  
Hexameric Form

SUMMARYEukaryotic homeostasis relies on membrane fusion catalyzed by SNARE proteins. Inactive SNARE bundles are re-activated by Sec18/NSF driven disassembly to enable a new round of fusion. We previously found that phosphatidic acid (PA) binds Sec18 to sequester it from SNAREs. Dephosphorylation of PA dissociates Sec18 from the membrane allowing it to engage SNARE complexes. We now report that PA induces conformational changes in Sec18 protomers, while hexameric Sec18 cannot bind PA membranes. The association of Sec18 with PA was shown to be sensitive to membrane curvature, suggesting that regulation could vary on different organelles in a curvature dependent manner. Molecular dynamics showed that PA binding sites exist on the D1 and D2 domains of Sec18 and that residues needed for binding were masked in the hexameric form of the protein. Together these data indicate that PA regulates Sec18 function through altering protein architecture and stabilizing membrane-bound protomers.

scholarly journals Achieving Reversible Ligand-Protein Unbinding with Deep Learning and Molecular Dynamics through RAVE

2018 ◽  
Author(s):  
João Marcelo Lamim Ribeiro ◽  
Pratyush Tiwary
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Deep Learning ◽  
Rare Events ◽  
Binding Free Energy ◽  
Piecewise Linear ◽  
Chem Phys ◽  
Enhanced Sampling ◽  
Order Of Magnitude ◽  
Low Dimensional

AbstractIn this work we demonstrate how to leverage our recent iterative deep learning–all atom molecular dynamics (MD) technique “Reweighted autoencoded variational Bayes for enhanced sampling (RAVE)” (Ribeiro, Bravo, Wang, Tiwary, J. Chem. Phys. 149, 072301 (2018)) for sampling protein-ligand unbinding mechanisms and calculating absolute binding affinities when plagued with difficult to sample rare events. RAVE iterates between rounds of MD and deep learning, and unlike other enhanced sampling methods, it stands out in simultaneously learning both a low-dimensional physically interpretable reaction coordinate (RC) and associated free energy. Here, we introduce a simple but powerful extension to RAVE which allows learning a position-dependent RC expressed as a superposition of piecewise linear RCs valid in different metastable states. With this approach, we retain the original physical interpretability of a RAVE-derived RC while making it applicable to a wider range of complex systems. We demonstrate how in its multi-dimensional form introduced here, RAVE can efficiently simulate the unbinding of the tightly bound benzene-lysozyme (L99A variant) complex, in all atom-precision and with minimal use of human intuition except for the choice of a larger dictionary of order parameters. These simulations had a 100 % success rate, and took between 3–50 nanoseconds for a process that takes on an average close to few hundred milliseconds, thereby reflecting a seven order of magnitude acceleration relative to straightforward MD. Furthermore, without any time-dependent biasing, the trajectories display clear back–and– forth movement between various metastable intermediates, demonstrating the reliability of the RC and its probability distribution learnt in RAVE. Our binding free energy is in good agreement with other reported simulation results. We thus believe that RAVE, especially in its multi-dimensional variant introduced here, will be a useful tool for simulating the dissociation process of practical biophysical systems with rare events in an automated manner with minimal use of human intuition.

scholarly journals Fine-tuning of the AMBER RNA Force Field with a New Term Adjusting Interactions of Terminal Nucleotides

2020 ◽  
Author(s):  
Vojtěch Mlýnský ◽  
Petra Kührová ◽  
Tomáš Kühr ◽  
Michal Otyepka ◽  
Giovanni Bussi ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
State Of The Art ◽  
Dynamic Properties ◽  
Md Simulations ◽  
Experimental Methods ◽  
Fine Tuning ◽  
Enhanced Sampling ◽  
Structural Dynamic ◽  
Nmr Data

ABSTRACTDetermination of RNA structural-dynamic properties is challenging for experimental methods. Thus atomistic molecular dynamics (MD) simulations represent a helpful technique complementary to experiments. However, contemporary MD methods still suffer from limitations of force fields (ffs), including imbalances in the non-bonded ff terms. We have recently demonstrated that some improvement of state-of-the-art AMBER RNA ff can be achieved by adding a new term for H-bonding called gHBfix, which increases tuning flexibility and reduces the risk of side-effects. Still, the first gHBfix version did not fully correct simulations of short RNA tetranucleotides (TNs). TNs are key benchmark systems due to availability of unique NMR data, although giving too much weight on improving TN simulations can easily lead to over-fitting to A-form RNA. Here we combine the gHBfix version with another term called tHBfix, which separately treats H-bond interactions formed by terminal nucleotides. This allows to refine simulations of RNA TNs without affecting simulations of other RNAs. The approach is in line with adopted strategy of current RNA ffs, where the terminal nucleotides possess different parameters for the terminal atoms than the internal nucleotides. The combination of gHBfix with tHBfix significantly improves the behavior of RNA TNs during well-converged enhanced-sampling simulations. TNs mostly populate canonical A-form like states while spurious intercalated structures are largely suppressed. Still, simulations of r(AAAA) and r(UUUU) TNs show some residual discrepancies with the primary NMR data which suggests that future tuning of some other ff terms might be useful.

Modelling Flexible Protein-Ligand Binding in p38α MAP Kinase using the QUBE Force Field

2019 ◽  
Author(s):  
Joshua Horton ◽  
Alice Allen ◽  
Daniel Cole
Keyword(s):  
Quantum Mechanics ◽  
Force Field ◽  
Map Kinase ◽  
Binding Free Energy ◽  
Quantum Mechanical ◽  
Enhanced Sampling ◽  
Relative Binding ◽  
Stringent Test ◽  
Flexible Protein ◽  
P38α Map Kinase

<div><div><div><p>The quantum mechanical bespoke (QUBE) force field is used to retrospectively calculate the relative binding free energy of a series of 17 flexible inhibitors of p38α MAP kinase. The size and flexibility of the chosen molecules represent a stringent test of the derivation of force field parameters from quantum mechanics, and enhanced sampling is required to reduce the dependence of the results on the starting structure. Competitive accuracy with a widely-used biological force field is achieved, indicating that quantum mechanics derived force fields are approaching the accuracy required to provide guidance in prospective drug discovery campaigns.</p></div></div></div>

Design of potential IKK-β inhibitors using molecular docking and molecular dynamics techniques for their anti-cancer potential

2020 ◽  
Vol 16 ◽  
Author(s):  
Salam Pradeep Singh ◽  
Iftikar Hussain ◽  
Bolin Kumar Konwar ◽  
Ramesh Chandra Deka ◽  
Chingakham Brajakishor Singh
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Md Simulation ◽  
Inflammatory Diseases ◽  
Binding Free Energy ◽  
Anti Cancer ◽  
Dietary Phytochemicals ◽  
Toxicity Analysis ◽  
The Stability ◽  
Stable Trajectory

Aim and Objective: To evaluate a set of seventy phytochemicals for their potential ability to bind the inhibitor of nuclear factor kappaB kinase beta (IKK-β) which is a prime target for cancer and inflammatory diseases. Materials and Methods: Seventy phytochemicals were screened against IKK-β enzyme using DFT-based molecular docking technique and the top docking hits were carried forward for molecular dynamics (MD) simulation protocols. The adme-toxicity analysis was also carried out for the top docking hits. Results: Sesamin, matairesinol and resveratrol were found to be the top docking hits with a total score of -413 kJ/mol, -398.11 kJ/mol and 266.73 kJ/mol respectively. Glu100 and Gly102 were found to be the most common interacting residues. The result from MD simulation observed a stable trajectory with a binding free energy of -107.62 kJ/mol for matairesinol, -120.37 kJ/mol for sesamin and -40.56 kJ/mol for resveratrol. The DFT calculation revealed the stability of the compounds. The ADME-Toxicity prediction observed that these compounds fall within the permissible area of Boiled-Egg and it does not violate any rule for pharmacological criteria, drug-likeness etc. Conclusion: The study interprets that dietary phytochemicals are potent inhibitors of IKK-β enzyme with favourable binding affinity and less toxic effects. In fact, there is a gradual rise in the use of plant-derived molecules because of its lesser side effects compared to chemotherapy. The study has also provided an insight by which the phytochemicals inhibited the IKK-β enzyme. The investigation would also provide in understanding the inhibitory mode of certain dietary phytochemicals in treating cancer.

scholarly journals Binding free energy predictions in host-guest systems using Autodock4. A retrospective analysis on SAMPL6, SAMPL7 and SAMPL8 challenges

2021 ◽  
Author(s):  
Lorenzo Casbarra ◽  
Piero Procacci
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Drug Discovery ◽  
Binding Free Energy ◽  
Cost Ratio ◽  
Benefit Cost Ratio ◽  
Docking Program ◽  
Benefit Cost ◽  
Overall Reliability ◽  
Absolute Binding Free Energy

AbstractWe systematically tested the Autodock4 docking program for absolute binding free energy predictions using the host-guest systems from the recent SAMPL6, SAMPL7 and SAMPL8 challenges. We found that Autodock4 behaves surprisingly well, outperforming in many instances expensive molecular dynamics or quantum chemistry techniques, with an extremely favorable benefit-cost ratio. Some interesting features of Autodock4 predictions are revealed, yielding valuable hints on the overall reliability of docking screening campaigns in drug discovery projects.

scholarly journals Decoding the temporal nature of brain GR activity in the NFκB signal transition leading to depressive-like behavior

2021 ◽  
Author(s):  
Young-Min Han ◽  
Min Sun Kim ◽  
Juyeong Jo ◽  
Daiha Shin ◽  
Seung-Hae Kwon ◽  
...  
Keyword(s):  
Inhibitory Action ◽  
Time Course ◽  
Molecular Mechanisms ◽  
Late Phase ◽  
Fine Tuning ◽  
Dependent Manner ◽  
Middle Phase ◽  
Temporal Shift

AbstractThe fine-tuning of neuroinflammation is crucial for brain homeostasis as well as its immune response. The transcription factor, nuclear factor-κ-B (NFκB) is a key inflammatory player that is antagonized via anti-inflammatory actions exerted by the glucocorticoid receptor (GR). However, technical limitations have restricted our understanding of how GR is involved in the dynamics of NFκB in vivo. In this study, we used an improved lentiviral-based reporter to elucidate the time course of NFκB and GR activities during behavioral changes from sickness to depression induced by a systemic lipopolysaccharide challenge. The trajectory of NFκB activity established a behavioral basis for the NFκB signal transition involved in three phases, sickness-early-phase, normal-middle-phase, and depressive-like-late-phase. The temporal shift in brain GR activity was differentially involved in the transition of NFκB signals during the normal and depressive-like phases. The middle-phase GR effectively inhibited NFκB in a glucocorticoid-dependent manner, but the late-phase GR had no inhibitory action. Furthermore, we revealed the cryptic role of basal GR activity in the early NFκB signal transition, as evidenced by the fact that blocking GR activity with RU486 led to early depressive-like episodes through the emergence of the brain NFκB activity. These results highlight the inhibitory action of GR on NFκB by the basal and activated hypothalamic-pituitary-adrenal (HPA)-axis during body-to-brain inflammatory spread, providing clues about molecular mechanisms underlying systemic inflammation caused by such as COVID-19 infection, leading to depression.

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