Danfeng Shi

Exploration of the antagonist CP-376395 escape pathway for the corticotropin-releasing factor receptor 1 by random acceleration molecular dynamics simulations.

Corticotropin-releasing factor receptor 1 (CRF1R), a member of class B G-protein-coupled receptors (GPCRs), plays an important role in the treatment of osteoporosis, diabetes, depression, migraine and anxiety. To explore the escape pathway of the antagonist CP-376395 in the binding pocket of CRF1R, molecular dynamics (MD) simulations, dynamical network analysis, random acceleration molecular dynamics (RAMD) simulations and adaptive biasing force (ABF) calculations were performed on the crystal structure of CRF1R in complex with CP-376395. The results of dynamical network analysis show that TM7 of CRF1R has the strongest edges during MD simulation. The bent part of TM7 forms a V-shape pocket with Gly356(7.50). Asn283(5.50) has high hydrogen bond occupancy during 100 ns MD simulations and is the key interaction residue with the antagonist in the binding pocket of CRF1R. RAMD simulation has identified three possible pathways (PW1, PW2 and PW3) for CP-376395 to escape from the binding pocket of CRF1R. The PW3 pathway was proved to be the most likely escape pathway for CP-376395. The free energy along the PW3 pathway was calculated by using ABF simulations. Two energy barriers were found along the reaction coordinates. Residues Leu323(6.49), Asn283(5.50) and Met206(3.47) contribute to the steric hindrance for the first energy barrier. Residues His199(3.40) and Gln355(7.49) contribute to the second energy barrier through the hydrogen bonding interaction between CP-376395 and CRF1R. The results of our study can not only provide useful information to understand the interaction mechanism between CP-376395 and CRF1R, but also provide the details about the possible escape pathway and the free energy profile of CP-376395 in the pocket of CRF1R.

Influence of Chirality of Crizotinib on Its MTH1 Protein Inhibitory Activity: Insight from Molecular Dynamics Simulations and Binding Free Energy Calculations

As a promising target for the treatment of lung cancer, the MutT Homolog 1 (MTH1) protein can be inhibited by crizotinib. A recent work shows that the inhibitory potency of (S)-crizotinib against MTH1 is about 20 times over that of (R)-crizotinib. But the detailed molecular mechanism remains unclear. In this study, molecular dynamics (MD) simulations and free energy calculations were used to elucidate the mechanism about the effect of chirality of crizotinib on the inhibitory activity against MTH1. The binding free energy of (S)-crizotinib predicted by the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Adaptive biasing force (ABF) methodologies is much lower than that of (R)-crizotinib, which is consistent with the experimental data. The analysis of the individual energy terms suggests that the van der Waals interactions are important for distinguishing the binding of (S)-crizotinib and (R)-crizotinib. The binding free energy decomposition analysis illustrated that residues Tyr7, Phe27, Phe72 and Trp117 were important for the selective binding of (S)-crizotinib to MTH1. The adaptive biasing force (ABF) method was further employed to elucidate the unbinding process of (S)-crizotinib and (R)-crizotinib from the binding pocket of MTH1. ABF simulation results suggest that the reaction coordinates of the (S)-crizotinib from the binding pocket is different from (R)-crizotinib. The results from our study can reveal the details about the effect of chirality on the inhibition activity of crizotinib to MTH1 and provide valuable information for the design of more potent inhibitors.

Molecular dynamics simulation, binding free energy calculation and unbinding pathway analysis on selectivity difference between FKBP51 and FKBP52: Insight into the molecular mechanism of isoform selectivity

As co‐chaperones of the 90‐kDa heat shock protein(HSP90), FK506 binding protein 51 (FKBP51) and FK506 binding protein 52 (FKBP52) modulate the maturation of steroid hormone receptor through their specific FK1 domains (FKBP12‐like domain 1). The inhibitors targeting FK1 domains are potential therapies for endocrine‐related physiological disorders. However, the structural conservation of the FK1 domains between FKBP51 and FKBP52 make it difficult to obtain satisfactory selectivity in FK506‐based drug design. Fortunately, a series of iFit ligands synthesized by Hausch et al exhibited excellent selectivity for FKBP51, providing new opportunity for design selective inhibitors. We performed molecular dynamics simulation, binding free energy calculation and unbinding pathway analysis to reveal selective mechanism for the inhibitor iFit4 binding with FKBP51 and FKBP52. The conformational stability evaluation of the “Phe67‐in” and “Phe67‐out” states implies that FKBP51 and FKBP52 have different preferences for “Phe67‐in” and “Phe67‐out” states, which we suggest as the determinant factor for the selectivity for FKBP51. The binding free energy calculations demonstrate that nonpolar interaction is favorable for the inhibitors binding, while the polar interaction and entropy contribution are adverse for the inhibitors binding. According to the results from binding free energy decomposition, the electrostatic difference of residue 85 causes the most significant thermodynamics effects on the binding of iFit4 to FKBP51 and FKBP52. Furthermore, the importance of substructure units on iFit4 were further evaluated by unbinding pathway analysis and residue‐residue contact analysis between iFit4 and the proteins. The results will provide new clues for the design of selective inhibitors for FKBP51.

Protective V127 prion variant prevents prion disease by interrupting the formation of dimer and fibril from molecular dynamics simulations.

Recent studies uncovered a novel protective prion protein variant: V127 variant, which was reported intrinsically resistant to prion conversion and propagation. However, the structural basis of its protective effect is still unknown. To uncover the origin of the protective role of V127 variant, molecular dynamics simulations were performed to explore the influence of G127V mutation on two key processes of prion propagation: dimerization and fibril formation. The simulation results indicate V127 variant is unfavorable to form dimer by reducing the main-chain H-bond interactions. The simulations of formed fibrils consisting of β1 strand prove V127 variant will make the formed fibril become unstable and disorder. The weaker interaction energies between layers and reduced H-bonds number for V127 variant reveal this mutation is unfavorable to the formation of stable fibril. Consequently, we find V127 variant is not only unfavorable to the formation of dimer but also unfavorable to the formation of stable core and fibril, which can explain the mechanism on the protective role of V127 variant from the molecular level. Our findings can deepen the understanding of prion disease and may guide the design of peptide mimetics or small molecule to mimic the protective effect of V127 variant.

Molecular dynamics simulations and novel drug discovery

ABSTRACT Introduction: Molecular dynamics (MD) simulations can provide not only plentiful dynamical structural information on biomacromolecules but also a wealth of energetic information about protein and ligand interactions. Such information is very important to understanding the structure-function relationship of the target and the essence of protein–ligand interactions and to guiding the drug discovery and design process. Thus, MD simulations have been applied widely and successfully in each step of modern drug discovery. Areas covered: In this review, the authors review the applications of MD simulations in novel drug discovery, including the pathogenic mechanisms of amyloidosis diseases, virtual screening and the interaction mechanisms between drugs and targets. Expert opinion: MD simulations have been used widely in investigating the pathogenic mechanisms of diseases caused by protein misfolding, in virtual screening, and in investigating drug resistance mechanisms caused by mutations of the target. These issues are very difficult to solve by experimental methods alone. Thus, in the future, MD simulations will have wider application with the further improvement of computational capacity and the development of better sampling methods and more accurate force fields together with more efficient analysis methods.

Revealing inhibition difference between PFI-2 enantiomers against SETD7 by molecular dynamics simulations, binding free energy calculations and unbinding pathway analysis

SETD7 is associated with multiple diseases related signaling pathways. (R)-PFI-2 is the first SETD7 inhibitor with nanomolar inhibitory potency. The activity of (R)-PFI-2 is about 500 times over that of (S)-PFI-2. Understanding the mechanism behind this difference will be helpful to discovery and design of more potent SETD7 inhibitors. A computational study combining molecular dynamics simulation, binding free energy calculations, and residue interaction network (RIN) was performed on the (S)-PFI-2/SETD7 and (R)-PFI-2/SETD7 complexes to explore the molecular mechanism behind the different inhibition activity. The results from Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculation show (R)-PFI-2 has lower binding free energy. Residues H252, D256, L267, Y335, G336 and H339 are responsible for the binding of SETD7 to the (R)-PFI-2. RIN analysis indicates van der Waals interaction is critical for the binding of (R)-PFI-2. The results from adaptive basing force (ABF) simulation confirm that the free energy barrier of (R)-PFI-2 dissociating from the SETD7 is larger than that of (S)-PFI-2. (S)-PFI-2 and (R)-PFI-2 dissociate from the SETD7 binding site along different reaction coordinate and have potential mean of force (PMF) depth. Our simulations results will be useful to understand molecular mechanism of activity difference between PFI-2 enantiomers against SETD7.

Computational studies on horseshoe shape pocket of human orexin receptor type 2 and boat conformation of suvorexant by molecular dynamics simulations

The FDA approved drug suvorexant binds to the horseshoe shape pocket of OX2R with the boat conformation. The horseshoe shape pocket plays an important role on the biological activity of OX2R in the cell membrane. To study the binding mechanism between the horseshoe shape pocket of OX2R and boat conformation of suvorexant, the crystal structures of wild type and N324A mutant of OX2R in complex with antagonist suvorexant are chosen to perform molecular dynamics (MD) simulations, QM/MM, and MMGBSA calculations. By comparison with the wild type of OX2R, the results show the 1,2,3‐triazole and p‐toluamide groups of suvorexant are changed in the N324A mutant of OX2R during 200 ns MD simulations. The QM/MM and weak interaction analysis are employed to calculate the non‐covalent bonds interaction between suvorexant and key residues in the wild type and N324A mutant of OX2R. The MMGBSA calculations indicate the entropy energy is an important influence factor for suvorexant affinity in the distorted horseshoe shape pocket of OX2R. Our results not only show the horseshoe shape pocket of OX2R is the necessary conformation for the binding of antagonist suvorexant, but also give the important sites and structural features for antagonist design of OX2R.

Understanding the structural and energetic basis of PD-1 and monoclonal antibodies bound to PD-L1: A molecular modeling perspective

BACKGROUND The inhibitors blocking the interaction between programmed cell death protein 1(PD-1) and programmed death-ligand 1(PD-L1) can activate the immune response of T cell and eliminate cancer cells. The crystallographic studies have provided structural insights of the interactive interfaces between PD-L1 and its protein ligands. However, the hotspot residues on PD-L1 as well as structural and energetic basis for different protein ligands still need to be further investigated. METHODS Molecular modeling methods including molecular dynamics simulation, per-residue free energy decomposition, virtual alanine scanning mutagenesis and residue-residue contact analysis were used to qualitatively and quantitatively analyze the interactions between PD-L1 and different protein ligands. RESULTS The results of virtual alanine scanning mutagenesis suggest that Y56, Q66, M115, D122, Y123, R125 are the hotspot residues on PD-L1. The residue-residue contact analysis further shows that PD-1 interacts with PD-L1 mainly by F and G strands while monoclonal antibodies like avelumab and BMS-936559 mainly interact with PD-L1 by CDR2 and CDR3 loops of the heavy chain. CONCLUSIONS A structurally similar β-hairpin peptide with 13 or 14 residues was extracted from each protein ligand and these β-hairpin peptides were found tightly binding to the putative hotspot residues on PD-L1. GENERAL SIGNIFICANCE This study recognizes the hotspot residues on PD-L1 and uncovers the common structural and energetic basis of different protein ligands binding to PD-L1. These results will be valuable for the design of small molecule or peptide inhibitors targeting on PD-L1.

Computational study on the selective inhibition mechanism of MS402 to the first and second bromodomains of BRD4

As a member of the bromodomain and extraterminal domain (BET) family, BRD4 is considered as a potential target for cancer treatment. However, because of the highly conservation of its two homologous bromodomains (BD1/BD2), selective inhibition of each bromodomain remains a challenge. MS402 is a domain‐selective inhibitor of BRD4‐BD1 over BRD4‐BD2 reported recently. Understanding the selectivity mechanism would be very useful for the further design of more potent BD1‐selectivity inhibitors. Molecular dynamics simulation, adaptive biasing force and multiple‐walker adaptive biasing force were performed to study the inhibition and domain‐selective mechanism of MS402 toward BRD4‐BD1 over BRD4‐BD2 here. Results demonstrate BRD4‐BD1 binds to MS402 with lower binding free energy than BRD4‐BD2. Residues Gln85, Pro86, Asn140, and Ile146 are crucial for MS402s selectively binding to BRD4‐BD1. MS402 needs to overcome more energy barrier to dissociate from BD1 than from BD2 pocket. These findings will be helpful for rational structural modification of existing inhibitors to increase their BD1‐selectivity.

Influence of EGCG on α‐synuclein (αS) aggregation and identification of their possible binding mode: A computational study using molecular dynamics simulation

The accumulation of intrinsically disordered α‐synuclein (αS) protein that can form β‐sheet‐rich fibrils is linked to Parkinsons disease. (−)‐Epigallocatechin‐3‐gallate (EGCG) is the most abundant active component in green tea and can inhibit the fibrillation of αS. The elucidation of this molecular mechanism will be helpful to understand the inhibition mechanism of EGCG to the fibrillation of αS and also to find more potential small molecules that can inhibit the aggregation of αS. In this work, to study the influence of EGCG on the structure of β‐sheet‐rich fibrils of αS and identification of their possible binding mode, molecular dynamics simulations of pentamer and decamer aggregates of αS in complex with EGCG were performed. The obtained results indicate that EGCG can remodel the αS fibrils and break the initial ordered pattern by reducing the β‐sheet content. EGCG can also break the Greek conformation of αS by the disappeared H‐bond in the secondary structure of turn. The results from our study can not only reveal the specific interaction between EGCG and β‐sheet‐rich fibrils of αS, but also provide the useful guidance for the discovery of other potential inhibitors.