Systematic Modeling, Prediction, and Comparison of Domain–Peptide Affinities: Does it Work Effectively With the Peptide QSAR Methodology?

Liu, Qian; Lin, Jing; Wen, Li; Wang, Shaozhou; Zhou, Peng; Mei, Li; Shang, Shuyong

doi:10.3389/fgene.2021.800857

Cited by 40 publications

(14 citation statements)

References 40 publications

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“…In addition, the conformational flexibility of the peptide ligand was dissected with normal mode analysis (NMA) to estimate entropy penalty − T Δ S upon the interaction 28 . Consequently, the total binding energy can be expressed as Δ G ttl = Δ E int + Δ G dslv − T Δ S , which was further corrected using machine learning‐based protein‐peptide affinity predictors 29‐31 …”

Section: Methodsmentioning

confidence: 99%

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Interleukin‐1α, interleukin‐1β and interleukin‐1 receptor antagonist share a common U‐shaped recognition epitope on interleukin‐1 receptor surface

Liu

et al. 2022

J of Molecular Recognition

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Interleukin‐1 (IL‐1) plays a central role in the regulation of immune and inflammatory responses. There are two forms of IL‐1 agonists (IL‐1α and IL‐1β) and one form of IL‐1 antagonist (IL‐1Ra); they share a similar binding mode to the IL‐1 receptor (IL‐1R) but exhibit opposite biological functions on the receptor. In this study, the intermolecular interactions of IL‐1R receptors with IL‐1α, IL‐1β and IL‐1Ra ligands were systematically investigated at structural, energetic and dynamic levels. It was found that the receptor primarily adopts a U‐shaped, double‐stranded and linear/conformational‐hybrid epitope to commonly interact with the three ligands. The epitope covers a common protein segment (residues 107‐127), which is fully located within the C2T2 subdomain of the IL‐1R extracellular domain and contributes ~40% to the total binding energy of IL‐1R/ligand association. The epitope is natively folded into an ordered conformation in the IL‐1R protein context but would become largely disordered out of the context. Here, we adopted a disulfide bridge to staple U‐shaped epitope‐derived peptides, which can be effectively constrained into a native‐like conformation and thus exhibit an improved affinity to ligands as compared to their unstapled counterpart, with affinity increase by up to ~15‐fold. These disulfide bridges were designed to point out of ligand/peptide complex interface and thus would not disrupt the direct complex interaction. Energetic decomposition imparted that the stapling has only a modest influence on the interaction enthalpy and desolvation effect of ligand/peptide binding, but can substantially reduce entropy penalty upon the binding. For a peptide, the stapling‐addressed entropic reduction can be roughly regarded as a constant, which only improves peptide affinity to these ligands, but does not change peptide selectivity over different ligands.

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Section: Methodsmentioning

confidence: 99%

“…28 Consequently, the total binding energy can be expressed as ΔG ttl = ΔE int + ΔG dslv À TΔS, which was further corrected using machine learning-based proteinpeptide affinity predictors. [29][30][31]…”

Section: Dynamics and Energeticsmentioning

confidence: 99%

Interleukin‐1α, interleukin‐1β and interleukin‐1 receptor antagonist share a common U‐shaped recognition epitope on interleukin‐1 receptor surface

Liu

et al. 2022

J of Molecular Recognition

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“…The QM/MM and PB/SA have been proved to be compatible in energetic analysis of protein‐protein binding 27 . In this way, the total PHHI binding free energy (Δ G ttl ) can be obtained as follows: Δ G ttl = ∆ U pkg + ∆ G plr + ∆ G nplr , which was further corrected using machine learning‐based protein‐protein/peptide affinity scoring functions 28‐30 …”

Section: Methodsmentioning

confidence: 99%

“…27 In this way, the total PHHI binding free energy (ΔG ttl ) can be obtained as follows: ΔG ttl = ΔU pkg + ΔG plr + ΔG nplr , which was further corrected using machine learning-based protein-protein/peptide affinity scoring functions. [28][29][30]…”

Section: Quantum Mechanics/molecular Mechanics Analysismentioning

confidence: 99%

Molecular design and rational optimization of synergistic effect between the two wings of a roughly orthogonal cation‐π‐π stacking system at nasopharyngeal carcinoma YAP1‐TEAD4 parallel Helix‐Helix interaction interface

Zhu

et al. 2022

J of Molecular Recognition

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The Yes-associated protein-1 (YAP1) is an essential regulator of human Hippo signaling pathway and functions through interaction with TEA domain-4 (TEAD4) transcription factor involved in the tumorigenesis of nasopharyngeal cancer. Previously, a parallel helix-helix interaction (PHHI) was identified as the key hotspot at YAP1-TEAD4 complex interface and has been exploited as an attractive druggable target to disrupt the complex. In this study, we investigated a roughly orthogonal cation-π-π stacking system across the crystal PHHI packing interface by integrating computational modeling and binding assay, which forms between one YAP1 helical residue Phe69 and two TEAD4 helical residues Phe373/Lys376. A synergistic effect between cation-π and π-π interactions was observed; they separately represent two wings of the stacking system. The π-electron is primarily responsible for the synergistic effect. Combination between diverse aromatic/charged amino acids. as well as neutral alanine on the cation-π-π stacking, revealed that the presence of aromatic tryptophan and charged arginine at, respectively, the residues 373 and 376 of TEAD4 helix can considerably improve PHHI binding affinity by $6-fold, whereas neutral alanine substitution on each residue and on both would reduce the affinity significantly, confirming a strong synergistic effect involved in the roughly orthogonal cation-π-π stacking system at YAP1-TEAD4 PHHI interface.

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“…Evidently, there is a good consistence (R p = 0.771) between the calculated interaction energies (ΔU int ) of halogen binding systems and the measured binding affinities (LogK d ) of peptides to ACEII. The [Br]Phecontaining BNPΔN(I À2 F-mBr) and [I]Phe-containing BNPΔN(K À3 F-pI) were determined to have high affinities (K d = 7.6 and 23 nM) in all tested peptides, which were improved by 6.7-and 4.6-fold relative to their unsubstituted counterparts BNPΔN(I À2 F) and BNPΔN(K À3 F) (K d = 51 and 107 nM), respectively, [53] confirming that the halogen bonds indeed exist in the designed [X]Phe-containing peptide complexes with ACEII, conferring high stability and specificity to the ACEII-peptide recognition and association.…”

Section: Design and Optimization Of Halogen Bonding Across Aceii-pept...mentioning

confidence: 99%

Rational truncation, mutation, and halogenation of bradykinin neuropeptides as potent ACEII inhibitors by integrating molecular dynamics simulations, quantum mechanics calculations, and in vitro assays

Chen

2022

J Chinese Chemical Soc

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Human angiotensin‐converting enzyme‐ii (ACEII) is involved in the brain renin‐angiotensin system and plays a key role in angiotensin metabolism and neural regulation. Here, we systematically investigated the intermolecular interaction of ACEII with its natural inhibitor bradykinin neuropeptide (BNP) at molecular level and found that the residue importance increases from peptide N‐ to C‐terminus; the four C‐terminal residues accumulatively account for ~70% total binding potency for BNP∆N to ACEII, which represent an N‐truncated tetrapeptide (BNP∆N) with comparable ACEII‐inhibitory activity with the full‐length BNP peptide. Mutagenesis analysis imparted that the mutation of BPPb∆N's two C‐terminal residues to phenylalanine (Phe) would largely impair its inhibitory activity, whereas such mutation on the two N‐terminal residues has only a moderate effect on the activity. The two N‐terminal Phe‐mutated tetrapeptides BNP∆N(I−2F) and BNP∆N(K−3F) were then used as templates and the ortho (o)‐, meta (m)‐, para (p)‐positions of the phenyl ring of their Phe residues were systematically substituted with different halogen types. The halogen substitution separately at the m‐position of BNP∆N(I−2F) Phe−2 residue and at the p‐position of BNP∆N(K−3F) Phe−3 residue can form a ternary halogen bonding system with ACEII His353/Lys368 residues and a binary bonding system with ACEII Glu403 residue, respectively. The [Br]Phe‐containing BNP∆N(I−2F‐mBr) and [I]Phe‐containing BNP∆N(K−3F‐pI) were determined to have high affinities for ACEII, which were improved considerably from their unsubstituted counterparts BNP∆N(I−2F) and BNP∆N(K−3F), respectively.

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Systematic Modeling, Prediction, and Comparison of Domain–Peptide Affinities: Does it Work Effectively With the Peptide QSAR Methodology?

Cited by 40 publications

References 40 publications

Interleukin‐1α, interleukin‐1β and interleukin‐1 receptor antagonist share a common U‐shaped recognition epitope on interleukin‐1 receptor surface

Interleukin‐1α, interleukin‐1β and interleukin‐1 receptor antagonist share a common U‐shaped recognition epitope on interleukin‐1 receptor surface

Molecular design and rational optimization of synergistic effect between the two wings of a roughly orthogonal cation‐π‐π stacking system at nasopharyngeal carcinoma YAP1‐TEAD4 parallel Helix‐Helix interaction interface

Rational truncation, mutation, and halogenation of bradykinin neuropeptides as potent ACEII inhibitors by integrating molecular dynamics simulations, quantum mechanics calculations, and in vitro assays

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