Cross-reactivity of two human IL-6 family cytokines OSM and LIF explored by protein-protein docking and molecular dynamics simulation

Du, Qingqing; Yan, Qian; Xue, Weiwei

doi:10.1016/j.bbagen.2021.129907

Cited by 18 publications

(14 citation statements)

References 37 publications

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“…Similarities in amino acid residues within the so called binding site III, comprising the AB loop, BC loop and D helix, as revealed by superposition of their crystal structures, may account for the common use of LIFR by OSM and LIF. This was further evidenced by protein–protein docking and molecular dynamics simulations [ 62 ]. Importantly, based on these docking experiments, the stability of the OSM:LIFR complex appears to be less stable than the LIF:LIFR complex.…”

Section: Bone Cell Expression and Binding Specificity Of Osm Osmr And...mentioning

confidence: 92%

“…The common use of the type I complex by OSM and LIF may be explained by similarities of the two cytokines revealed by computational modeling of their interaction with LIFR [ 62 ] based on existing data from crystallography studies of LIF–LIFR interaction [ 63 ] and site-directed mutagenesis of OSM [ 64 , 65 ]. Although the percentage of matching amino acid residues between human OSM and human LIF is only between 22 and 29% [ 66 ], they have convergent 3D structures comprising 4α-helices, named A, B C and D, linked by polypeptide loops [ 51 , 67 ].…”

Section: Bone Cell Expression and Binding Specificity Of Osm Osmr And...mentioning

confidence: 99%

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Stimulation of Osteoclast Formation by Oncostatin M and the Role of WNT16 as a Negative Feedback Regulator

Souza

Henning

Lerner

2022

IJMS

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Oncostatin M (OSM), which belongs to the IL-6 family of cytokines, is the most potent and effective stimulator of osteoclast formation in this family, as assessed by different in vitro assays. Osteoclastogenesis induced by the IL-6 type of cytokines is mediated by the induction and paracrine stimulation of the osteoclastogenic cytokine receptor activator of nuclear factor κ-B ligand (RANKL), expressed on osteoblast cell membranes and targeting the receptor activator of nuclear factor κ-B (RANK) on osteoclast progenitor cells. The potent effect of OSM on osteoclastogenesis is due to an unusually robust induction of RANKL in osteoblasts through the OSM receptor (OSMR), mediated by a JAK–STAT/MAPK signaling pathway and by unique recruitment of the adapter protein Shc1 to the OSMR. Gene deletion of Osmr in mice results in decreased numbers of osteoclasts and enhanced trabecular bone caused by increased trabecular thickness, indicating that OSM may play a role in physiological regulation of bone remodeling. However, increased amounts of OSM, either through administration of recombinant protein or of adenoviral vectors expressing Osm, results in enhanced bone mass due to increased bone formation without any clear sign of increased osteoclast numbers, a finding which can be reconciled by cell culture experiments demonstrating that OSM can induce osteoblast differentiation and stimulate mineralization of bone nodules in such cultures. Thus, in vitro studies and gene deletion experiments show that OSM is a stimulator of osteoclast formation, whereas administration of OSM to mice shows that OSM is not a strong stimulator of osteoclastogenesis in vivo when administered to adult animals. These observations could be explained by our recent finding showing that OSM is a potent stimulator of the osteoclastogenesis inhibitor WNT16, acting in a negative feedback loop to reduce OSM-induced osteoclast formation.

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Section: Bone Cell Expression and Binding Specificity Of Osm Osmr And...mentioning

confidence: 92%

Section: Bone Cell Expression and Binding Specificity Of Osm Osmr And...mentioning

confidence: 99%

Stimulation of Osteoclast Formation by Oncostatin M and the Role of WNT16 as a Negative Feedback Regulator

Souza

Henning

Lerner

2022

IJMS

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“…First, HawkDock [ 46 ] was performed to preliminarily explore the poses of each VNAR and TNFα, which generated the top 10 prediction complex models. Referring to the binding epitopes of Nanobodies on human TNFα [ 48 ], 5 reasonable models were then selected for RosettaDock using the same setup as recent studies [ 55 , 56 ]. In brief, the initial model was prepacked and used as a starting point for several rounds of local docking to generate 1000 decoys by running RosettaDock with the Monte Carlo (MC) refinement method [ 57 ].…”

Section: Methodsmentioning

confidence: 99%

“…In brief, the initial model was prepacked and used as a starting point for several rounds of local docking to generate 1000 decoys by running RosettaDock with the Monte Carlo (MC) refinement method [ 57 ]. Finally, the docking funnel of the trajectory describing the characteristics of the interface score (I-sc) of each decoy and the interface root-mean-square deviation (I_rmsd) was made to find the reasonable model of each complex [ 55 , 56 , 58 ].…”

Section: Methodsmentioning

confidence: 99%

Identification of Anti-TNFα VNAR Single Domain Antibodies from Whitespotted Bambooshark (Chiloscyllium plagiosum)

et al. 2022

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Tumor necrosis factor α (TNFα), an important clinical testing factor and drug target, can trigger serious autoimmune diseases and inflammation. Thus, the TNFα antibodies have great potential application in diagnostics and therapy fields. The variable binding domain of IgNAR (VNAR), the shark single domain antibody, has some excellent advantages in terms of size, solubility, and thermal and chemical stability, making them an ideal alternative to conventional antibodies. This study aims to obtain VNARs that are specific for mouse TNF (mTNF) from whitespotted bamboosharks. After immunization of whitespotted bamboosharks, the peripheral blood leukocytes (PBLs) were isolated from the sharks, then the VNAR phage display library was constructed. Through phage display panning against mTNFα, positive clones were validated through ELISA assay. The affinity of the VNAR and mTNFα was measured using ELISA and Bio-Layer Interferometry. The binding affinity of 3B11 VNAR reached 16.7 nM. Interestingly, one new type of VNAR targeting mTNF was identified that does not belong to any known VNAR type. To understand the binding mechanism of VNARs to mTNFα, the models of VNARs-mTNFα complexes were predicted by computational modeling combining HawkDock and RosettaDock. Our results showed that four VNARs’ epitopes overlapped in part with that of mTNFR. Furthermore, the ELISA assay shows that the 3B11 potently inhibited mTNFα binding to mTNFR. This study may provide the basis for the TNFα blockers and diagnostics applications.

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“…An Amber 18 graphic processing unit (GPU) particle mesh Ewald molecular dynamic (PMEMD) was employed in the MD simulations. The force-field-related parameters and protein description were handled with FF14SB [ 37 , 38 ]. LEAP module implementation of Amber18 was utilised in the addition of hydrogen atoms to the neuraminidase (protein) and subsequent counter-ions additions to neutralise the system [ 39 ].…”

Section: Methodsmentioning

confidence: 99%

Intermolecular Mechanism and Dynamic Investigation of Avian Influenza H7N9 Virus’ Susceptibility to E119V-Substituted Peramivir–Neuraminidase Complex

et al. 2022

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The H7N9 virus attaches itself to the human cell receptor protein containing the polysaccharide that terminates with sialic acid. The mutation of neuraminidase at residue E119 has been explored experimentally. However, there is no adequate information on the substitution with E119V in peramivir at the intermolecular level. Therefore, a good knowledge of the interatomic interactions is a prerequisite in understanding its transmission mode and subsequent effective inhibitions of the sialic acid receptor cleavage by neuraminidase. Herein, we investigated the mechanism and dynamism on the susceptibility of the E119V mutation on the peramivir–neuraminidase complex relative to the wildtype complex at the intermolecular level. This study aims to investigate the impact of the 119V substitution on the neuraminidase–peramivir complex and unveil the residues responsible for the complex conformations. We employed molecular dynamic (MD) simulations and extensive post-MD analyses in the study. These extensive computational investigations were carried out on the wildtype and the E119V mutant complex of the protein for holistic insights in unveiling the effects of this mutation on the binding affinity and the conformational terrain of peramivir–neuraminidase E119V mutation. The calculated total binding energy (ΔGbind) for the peramivir wildtype is −49.09 ± 0.13 kcal/mol, while the E119V mutant is −58.55 ± 0.15 kcal/mol. The increase in binding energy (9.46 kcal/mol) is consistent with other post-MD analyses results, confirming that E119V substitution confers a higher degree of stability on the protein complex. This study promises to proffer contributory insight and additional knowledge that would enhance future drug designs and help in the fight targeted at controlling the avian influenza H7N9 virus. Therefore, we suggest that experimentalists collaborate with computational chemists for all investigations of this topic, as we have done in our previous studies.

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Cross-reactivity of two human IL-6 family cytokines OSM and LIF explored by protein-protein docking and molecular dynamics simulation

Cited by 18 publications

References 37 publications

Stimulation of Osteoclast Formation by Oncostatin M and the Role of WNT16 as a Negative Feedback Regulator

Stimulation of Osteoclast Formation by Oncostatin M and the Role of WNT16 as a Negative Feedback Regulator

Identification of Anti-TNFα VNAR Single Domain Antibodies from Whitespotted Bambooshark (Chiloscyllium plagiosum)

Intermolecular Mechanism and Dynamic Investigation of Avian Influenza H7N9 Virus’ Susceptibility to E119V-Substituted Peramivir–Neuraminidase Complex

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