Study of the Allosteric Mechanism of Human Mitochondrial Phenylalanyl-tRNA Synthetase by Transfer Entropy via an Improved Gaussian Network Model and Co-evolution Analyses

We propose an improved transfer entropy approach called the dynamic version of the force constant fitted Gaussian network model based on molecular dynamics ensemble (dfcfGNMMD) to explore the allosteric mechanism of human mitochondrial phenylalanyl-tRNA synthetase (hmPheRS), one of the aminoacyl-tRNA synthetases that play a crucial role in translation of the genetic code. The dfcfGNMMD method can provide reliable estimates of the transfer entropy and give new insights into the role of the anticodon binding domain in driving the catalytic domain in aminoacylation activity and into the effects of tRNA binding and residue mutation on the enzyme activity, revealing the causal mechanism of the allosteric communication in hmPheRS. In addition, we incorporate the residue dynamic and co-evolutionary information to further investigate the key residues in hmPheRS allostery. This study sheds light on the mechanisms of hmPheRS allostery and can provide important information for related drug design

Computer-Aided Rational Construction of Mediated Bioelectrocatalysis with π‑Conjugated (Hetero)cyclic Molecules: Toward Promoted Distant Electron Tunneling and Improved Biosensing

Highly π-conjugated (hetero)­cyclic molecules having delocalized orbitals and tunable charge mobilities are attractive redox relays for mediated bioelectrocatalysis in manifold applications. As rigid molecules, their dynamics within the soft but confined intraprotein space becomes the crucial determinant of the enzyme-mediator electron-tunneling efficiency. However, it is rarely investigated in designing the mediated interface with a particular biocatalyst (e.g., oxidoreductase), which remains an empirical but try-and-error process. Herein, we present the computer-aided exploration of interactions between a flavin-containing reductive synthase and structurally diverse π-extended (hetero)­cyclic mediators to realize reversed bioelectrocatalytic oxidation at low overpotentials. Compared to ring-fused systems with unbroken molecular planarity, heteroatom-bridged cyclic, and rotatable conjugated structures (e.g., indophenols) can experience unusually large dynamic torsion under biased forces of hydrogen bonding with enzyme residues. This behavior led to fast intraprotein reorientation (<50 ps) that shortened the electron-tunneling distance from 12 to 9 Å. Meanwhile, the lowest unoccupied molecular orbital level upon molecular torsion was decreased by 0.5 eV to further promote electron abstraction from the reduced flavin cofactor. An efficient distant electron tunneling also obviated mediator transport through the substrate channel, thus avoiding competitive inhibition on enzyme kinetics to broaden the operating concentration range. The resulting bioelectrocatalytic interface enables low-potential biosensing of glutamate with improved selectivity. Our finding provides new structural insights into constructing efficient long-range heterogeneous charge transport with biomacromolecular catalysts

Key Residues in δ Opioid Receptor Allostery Explored by the Elastic Network Model and the Complex Network Model Combined with the Perturbation Method

Opioid receptors, a kind of G protein-coupled receptors (GPCRs), mainly mediate an analgesic response via allosterically transducing the signal of endogenous ligand binding in the extracellular domain to couple to effector proteins in the intracellular domain. The δ opioid receptor (DOP) is associated with emotional control besides pain control, which makes it an attractive therapeutic target. However, its allosteric mechanism and key residues responsible for the structural stability and signal communication are not completely clear. Here we utilize the Gaussian network model (GNM) and amino acid network (AAN) combined with perturbation methods to explore the issues. The constructed fcfGNMMD, where the force constants are optimized with the inverse covariance estimation based on the correlated fluctuations from the available DOP molecular dynamics (MD) ensemble, shows a better performance than traditional GNM in reproducing residue fluctuations and cross-correlations and in capturing functionally low-frequency modes. Additionally, fcfGNMMD can consider implicitly the environmental effects to some extent. The lowest mode can well divide DOP segments and identify the two sodium ion (important allosteric regulator) binding coordination shells, and from the fastest modes, the key residues important for structure stabilization are identified. Using fcfGNMMD combined with a dynamic perturbation-response method, we explore the key residues related to the sodium ion binding. Interestingly, we identify not only the key residues in sodium ion binding shells but also the ones far away from the perturbation sites, which are involved in binding with DOP ligands, suggesting the possible long-range allosteric modulation of sodium binding for the ligand binding to DOP. Furthermore, utilizing the weighted AAN combined with attack perturbations, we identify the key residues for allosteric communication. This work helps strengthen the understanding of the allosteric communication mechanism in δ opioid receptor and can provide valuable information for drug design

Insights into Activation Dynamics and Functional Sites of Inwardly Rectifying Potassium Channel Kir3.2 by an Elastic Network Model Combined with Perturbation Methods

The inwardly rectifying potassium channel Kir3.2, a member of the inward rectifier potassium (Kir) channel family, exerts important biological functions through transporting potassium ions outside of the cell, during which a large-scale synergistic movement occurs among its different domains. Currently, it is not fully understood how the binding of the ligand to the Kir3.2 channel leads to the structural changes and which key residues are responsible for the channel gating and allosteric dynamics. Here, we construct the Gaussian network model (GNM) of the Kir3.2 channel with the secondary structure and covalent interaction information considered (sscGNM), which shows a better performance in reproducing the channel’s flexibility compared with the traditional GNM. In addition, the sscANM-based perturbation method is used to simulate the channel’s conformational transition caused by the activator PIP2’s binding. By applying certain forces to the PIP2 binding pocket, the coarse-grained calculations generate the similar conformational changes to the experimental observation, suggesting that the topology structure as well as PIP2 binding are crucial to the allosteric activation of the Kir3.2 channel. We also utilize the sscGNM-based thermodynamic cycle method developed by us to identify the key residues whose mutations significantly alter the channel’s binding free energy with PIP2. We identify not only the residues important for the specific binding but also the ones critical for the allosteric transition coupled with PIP2 binding. This study is helpful for understanding the working mechanism of Kir3.2 channels and can provide important information for related drug design

Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G‑Protein-Coupled Receptor GPR52

Within over 800 members of G-protein-coupled receptors, there are numerous orphan receptors whose endogenous ligands are largely unknown, providing many opportunities for novel drug discovery. However, the lack of an in-depth understanding of the intrinsic working mechanism for orphan receptors severely limits the related rational drug design. The G-protein-coupled receptor 52 (GPR52) is a unique orphan receptor that constitutively increases cellular 5′-cyclic adenosine monophosphate (cAMP) levels without binding any exogenous agonists and has been identified as a promising therapeutic target for central nervous system disorders. Although recent structural biology studies have provided snapshots of both active and inactive states of GPR52, the mechanism of the conformational transition between these states remains unclear. Here, an acceptable self-activation pathway for GPR52 was proposed through 6 μs Gaussian accelerated molecular dynamics (GaMD) simulations, in which the receptor spontaneously transitions from the active state to that matching the inactive crystal structure. According to the three intermediate states of the receptor obtained by constructing a reweighted potential of mean force, how the allosteric regulation occurs between the extracellular orthosteric binding pocket and the intracellular G-protein-binding site is revealed. Combined with the independent gradient model, several important microswitch residues and the allosteric communication pathway that directly links the two regions are both identified. Transfer entropy calculations not only reveal the complex allosteric signaling within GPR52 but also confirm the unique role of ECL2 in allosteric regulation, which is mutually validated with the results of GaMD simulations. Overall, this work elucidates the allosteric mechanism of GPR52 at the atomic level, providing the most detailed information to date on the self-activation of the orphan receptor

Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G‑Protein-Coupled Receptor GPR52

Within over 800 members of G-protein-coupled receptors, there are numerous orphan receptors whose endogenous ligands are largely unknown, providing many opportunities for novel drug discovery. However, the lack of an in-depth understanding of the intrinsic working mechanism for orphan receptors severely limits the related rational drug design. The G-protein-coupled receptor 52 (GPR52) is a unique orphan receptor that constitutively increases cellular 5′-cyclic adenosine monophosphate (cAMP) levels without binding any exogenous agonists and has been identified as a promising therapeutic target for central nervous system disorders. Although recent structural biology studies have provided snapshots of both active and inactive states of GPR52, the mechanism of the conformational transition between these states remains unclear. Here, an acceptable self-activation pathway for GPR52 was proposed through 6 μs Gaussian accelerated molecular dynamics (GaMD) simulations, in which the receptor spontaneously transitions from the active state to that matching the inactive crystal structure. According to the three intermediate states of the receptor obtained by constructing a reweighted potential of mean force, how the allosteric regulation occurs between the extracellular orthosteric binding pocket and the intracellular G-protein-binding site is revealed. Combined with the independent gradient model, several important microswitch residues and the allosteric communication pathway that directly links the two regions are both identified. Transfer entropy calculations not only reveal the complex allosteric signaling within GPR52 but also confirm the unique role of ECL2 in allosteric regulation, which is mutually validated with the results of GaMD simulations. Overall, this work elucidates the allosteric mechanism of GPR52 at the atomic level, providing the most detailed information to date on the self-activation of the orphan receptor

Molecular interactions between receptor molecules (Chain A) and vaccine construct (Chain B).

Molecular interactions between receptor molecules (Chain A) and vaccine construct (Chain B).</p

Fig 6 -

(A) The active site of the protein CD630_32050 was used to create a pharmacophore model. The characteristics are denoted by different colors. White represents a hydrogen-bond donor, yellow represents a hydrogen acceptor, green represents hydrophobic properties, and aromatic represents aromatic features (pink). (B) The molecular interactions of the top hit docked compound (CD630_32050) within the substrate-binding site. The nature of protein-ligand interactions is shown in different colors.</p

Fig 7 -

Molecular dynamics (MD) simulation results A) C7-putative nitroreductase RMSD analysis B) RMSF analysis of Cα atoms C) H-bond estimation during 100 ns simulation D) Radius of gyration (Rg) analysis.</p