scholarly journals Exploring the binding mode and thermodynamics of inverse agonists against estrogen-related receptor alpha

RSC Advances ◽  
2020 ◽  
Vol 10 (28) ◽  
pp. 16659-16668 ◽  
Author(s):  
Konda Reddy Karnati ◽  
Yixuan Wang ◽  
Yongli Du
Keyword(s):  
Md Simulations ◽  
Binding Mode ◽  
Free Energies ◽  
Inverse Agonists ◽  
Receptor Alpha ◽  
First Time ◽  
Estrogen Related Receptor ◽  
Binding Free Energies

All-atom MD simulations were for the first time carried out for the complexes of inverse agonists and ERRα, and their binding free energies were also calculated with MM-PBSA to quantitatively discuss the binding of the inverse agonists with ERRα.

scholarly journals Unraveling Sugar Binding Modes to DC-SIGN by Employing Fluorinated Carbohydrates

Molecules ◽  
2019 ◽  
Vol 24 (12) ◽  
pp. 2337 ◽  
Author(s):  
J. Daniel Martínez ◽  
Pablo Valverde ◽  
Sandra Delgado ◽  
Cecilia Romanò ◽  
Bruno Linclau ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Viral Infections ◽  
Md Simulations ◽  
Binding Mode ◽  
Intercellular Adhesion Molecule ◽  
Binding Modes ◽  
Binding Epitope ◽  
First Time ◽  
Biomedical Interest ◽  
Specific Sugar

A fluorine nuclear magnetic resonance (19F-NMR)-based method is employed to assess the binding preferences and interaction details of a library of synthetic fluorinated monosaccharides towards dendritic cell-specific intercellular adhesion molecule 3-grabbing non-integrin (DC-SIGN), a lectin of biomedical interest, which is involved in different viral infections, including HIV and Ebola, and is able to recognize a variety of self- and non-self-glycans. The strategy employed allows not only screening of a mixture of compounds, but also obtaining valuable information on the specific sugar–protein interactions. The analysis of the data demonstrates that monosaccharides Fuc, Man, Glc, and Gal are able to bind DC-SIGN, although with decreasing affinity. Moreover, a new binding mode between Man moieties and DC-SIGN, which might have biological implications, is also detected for the first time. The combination of the 19F with standard proton saturation transfer difference (1H-STD-NMR) data, assisted by molecular dynamics (MD) simulations, permits us to successfully define this new binding epitope, where Man coordinates a Ca2+ ion of the lectin carbohydrate recognition domain (CRD) through the axial OH-2 and equatorial OH-3 groups, thus mimicking the Fuc/DC-SIGN binding architecture.

scholarly journals Mechanism of self/nonself-discrimination in Brassica self-incompatibility

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kohji Murase ◽  
Yoshitaka Moriwaki ◽  
Tomoyuki Mori ◽  
Xiao Liu ◽  
Chiho Masaka ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Specific Interaction ◽  
Md Simulations ◽  
Self Incompatibility ◽  
Receptor Kinase ◽  
Free Energies ◽  
Detailed Mechanism ◽  
Pollen Rejection ◽  
Cross Fertilization ◽  
Binding Free Energies

Abstract Self-incompatibility (SI) is a breeding system that promotes cross-fertilization. In Brassica, pollen rejection is induced by a haplotype-specific interaction between pistil determinant SRK (S receptor kinase) and pollen determinant SP11 (S-locus Protein 11, also named SCR) from the S-locus. Although the structure of the B. rapa S9-SRK ectodomain (eSRK) and S9-SP11 complex has been determined, it remains unclear how SRK discriminates self- and nonself-SP11. Here, we uncover the detailed mechanism of self/nonself-discrimination in Brassica SI by determining the S8-eSRK–S8-SP11 crystal structure and performing molecular dynamics (MD) simulations. Comprehensive binding analysis of eSRK and SP11 structures reveals that the binding free energies are most stable for cognate eSRK–SP11 combinations. Residue-based contribution analysis suggests that the modes of eSRK–SP11 interactions differ between intra- and inter-subgroup (a group of phylogenetically neighboring haplotypes) combinations. Our data establish a model of self/nonself-discrimination in Brassica SI.

scholarly journals S494 O-glycosylation site on the SARS-COV-2 RBD Affects the Virus Affinity to ACE2 and its Infectivity; A Molecular Dynamics Study

2020 ◽  
Author(s):  
Shadi Rahnama ◽  
Maryam Azimzadeh Irani ◽  
Mehriar Amininasab ◽  
Mohammad Reza Ejtehadi
Keyword(s):  
Molecular Dynamics ◽  
Md Simulations ◽  
Glycosylation Site ◽  
Virus Infectivity ◽  
Free Energies ◽  
S Protein ◽  
Angiotensin Converting Enzyme 2 ◽  
Host Interaction ◽  
Binding Free Energies

AbstractSARS-COV-2 is a strain of Coronavirus family which caused the extensive pandemic of COVID-19, which is still going on. Several studies showed that the glycosylation of virus spike (S) protein and the Angiotensin-Converting Enzyme 2 (ACE2) receptor on the host cell is critical for the virus infectivity. Molecular Dynamics (MD) simulations were used to explore the role of a novel mutated O-glycosylation site (D494S) on the Receptor Binding Domain (RBD) of S protein. This site was suggested as a key mediator of virus-host interaction. We showed that the decoration of S494 with elongated O-glycans results in stabilized interactions on the direct RBD-ACE2 interface with more favorable binding free energies for longer oligosaccharides. Hence, this crucial factor must be taken into account for any further inhibitory approaches towards RBD-ACE2 interaction.

Studies on binding free energies and the binding mode by docking and MM-PBSA in gp41-ligand complex

2005 ◽  
Vol 31 (14-15) ◽  
pp. 1051-1056 ◽  
Author(s):  
J. J. TAN ◽  
R. KONG ◽  
W. Z. CHEN ◽  
C. X. WANG
Keyword(s):  
Binding Mode ◽  
Free Energies ◽  
Ligand Complex ◽  
Binding Free Energies

scholarly journals Ligand Binding Mechanism and Its Relationship with Conformational Changes in Adenine Riboswitch

2020 ◽  
Vol 21 (6) ◽  
pp. 1926
Author(s):  
Guodong Hu ◽  
Haiyan Li ◽  
Shicai Xu ◽  
Jihua Wang
Keyword(s):  
Ligand Binding ◽  
Conformational Change ◽  
Conformational Changes ◽  
Md Simulations ◽  
Binding Pocket ◽  
Dynamical Analysis ◽  
Mass Center ◽  
Free Energies ◽  
Binding Model ◽  
Binding Free Energies

Riboswitches are naturally occurring RNA aptamers that control the expression of essential bacterial genes by binding to specific small molecules. The binding with both high affinity and specificity induces conformational changes. Thus, riboswitches were proposed as a possible molecular target for developing antibiotics and chemical tools. The adenine riboswitch can bind not only to purine analogues but also to pyrimidine analogues. Here, long molecular dynamics (MD) simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) computational methodologies were carried out to show the differences in the binding model and the conformational changes upon five ligands binding. The binding free energies of the guanine riboswitch aptamer with C74U mutation complexes were compared to the binding free energies of the adenine riboswitch (AR) aptamer complexes. The calculated results are in agreement with the experimental data. The differences for the same ligand binding to two different aptamers are related to the electrostatic contribution. Binding dynamical analysis suggests a flexible binding pocket for the pyrimidine ligand in comparison with the purine ligand. The 18 μs of MD simulations in total indicate that both ligand-unbound and ligand-bound aptamers transfer their conformation between open and closed states. The ligand binding obviously affects the conformational change. The conformational states of the aptamer are associated with the distance between the mass center of two key nucleotides (U51 and A52) and the mass center of the other two key nucleotides (C74 and C75). The results suggest that the dynamical character of the binding pocket would affect its biofunction. To design new ligands of the adenine riboswitch, it is recommended to consider the binding affinities of the ligand and the conformational change of the ligand binding pocket.

scholarly journals An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors

2021 ◽  
Author(s):  
Qianqian Zhao ◽  
Riccardo Capelli ◽  
Paolo Carloni ◽  
Bernhard Luescher ◽  
Jinyu Li ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Absolute Error ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Induced Fit ◽  
Adp Ribosylation ◽  
Free Energy Landscapes ◽  
First Time ◽  
Enzyme Complexes ◽  
Binding Free Energies

A variety of enhanced sampling methods can predict free energy landscapes associated with protein/ligand binding events, characterizing in a precise way the intermolecular interactions involved. Unfortunately, these approaches are challenged by not uncommon induced fit mecchanisms. Here, we present a variant of the recently reported volume-based metadynamics (MetaD) method which describes ligand binding even when it affects protein structure. The validity of the approach is established by applying it to a substrate/enzyme complexes of pharmacological relevance: this is the mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be operative. The calculated binding free energies are consistent with experiments, with an absolute error less than 0.5 kcal/mol. Our simulations reveal that in all circumstances the active loops, delimiting the boundaries of the binding site, rearrange from an open to a closed conformation upon ligand binding. The calculations further provide, for the first time, the molecular basis of the experimentally observed affinity changes in ADPr binding on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to investigate in a completely general manner ligand binding to proteins and receptors.

scholarly journals Simulations reveal increased fluctuations in estrogen receptor-alpha conformation upon antagonist binding

2016 ◽  
Author(s):  
Ho Leung Ng
Keyword(s):  
Estrogen Receptor ◽  
Estrogen Receptor Alpha ◽  
Dynamic Properties ◽  
Md Simulations ◽  
Binding Mode ◽  
Cancer Drug ◽  
Conformational Ensemble ◽  
Receptor Alpha ◽  
Agonist And Antagonist ◽  
17Β Estradiol

AbstractMolecular dynamics (MD) simulations have been used to model dynamic fluctuations in the structure of estrogen receptor-alpha (ER-α) upon binding to the natural agonist 17β-estradiol (E2) and to the active metabolite of the breast cancer drug and antagonist, 4-hydroxytamoxifen (OHT). We present the most extensive MD simulations to date of ER-α with over 1 μs of combined simulations for the monomer and dimer forms. Simulations reveal that the antagonist-bound complex includes significant fluctuations while the agonist-bound complex is tightly restrained. OHT increases dynamic disorder in the loops located to either side of the tail H12 helix; H12 has been associated with the activation status of ER-α. We also report that fluctuations near H12 lead to greater conformational variation in the binding mode of the ethylamine tail of OHT. Both the agonist and antagonist conformations are stable throughout the 240 ns simulations, supporting the hypothesis that there are no transitions between these two states or into intermediate states. The stable position of H12 in the OHT-bound conformation suggests that OHT stabilizes a well-defined antagonist conformational ensemble rather than merely blocking the agonist-driven activation of ER-α. Simultaneously, the increased dynamic properties of the OHT-bound complex is a potential source of binding entropy.

scholarly journals Critical interactions for SARS-CoV-2 spike protein binding to ACE2 identified by machine learning

2021 ◽  
Author(s):  
Anna Pavlova ◽  
Zijian Zhang ◽  
Atanu Acharya ◽  
Diane L. Lynch ◽  
Yui Tik Pang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Experimental Studies ◽  
Md Simulations ◽  
Spike Protein ◽  
Free Energy Perturbation ◽  
Receptor Binding Domain ◽  
Free Energies ◽  
Energy Perturbation ◽  
The Individual ◽  
Binding Free Energies

ABSTRACTBoth SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor. Based on high-resolution structures, the two viruses bind in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Here we have used molecular dynamics (MD) simulations, machine learning (ML), and free energy perturbation (FEP) calculations to elucidate the differences in RBD binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD-ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

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