Ligand selectivity of estrogen receptors by a molecular dynamics study

Theoretical exploration of the binding selectivity of inhibitors to BRD7 and BRD9 with multiple short molecular dynamics simulations

Bromodomain-containing proteins 7 and 9 (BRD7 and BRD9) have been considered as potential targets of clinical drug design toward treatment of human cancers and other diseases. Multiple short molecular dynamics simulations and binding free energy predictions were carried out to decipher the binding selectivity of three inhibitors 4L2, 5U6, and 6KT toward BRD7 and BRD9. The results show that 4L2 has more favorable binding ability to BRD7 over BRD9 compared to 5U6 and 6KT, while 5U6 and 6KT possess more favorable associations with BRD9 than BRD7. Furthermore, estimations of residue-based free energy decompositions further identify that four common residue pairs, including (F155, F44), (V160, V49), (Y168, Y57) and (Y217, Y106) in (BRD7, BRD9) generate obvious binding differences with 4L2, 5U6, and 6KT, which mostly drives the binding selectivity of 4L2, 5U6, and 6KT to BRD7 and BRD9. Dynamic information arising from trajectory analysis also suggests that inhibitor bindings affect structural flexibility and motion modes, which is responsible for the partial selectivity of 4L2, 5U6, and 6KT toward BRD7 and BRD9. As per our expectation, this study theoretically provides useful hints for design of dual inhibitors with high selectivity on BRD7 and BRD9.

Bromodomains (BRDs) are structurally conserved epigenetic reader modules observed in numerous chromatin- and transcription-associated proteins that have a capability to identify acetylated lysine residues.

Deciphering binding mechanism of inhibitors to SARS-COV-2 main protease through multiple replica accelerated molecular dynamics simulations and free energy landscapes

The pneumonia outbreak caused by the SARS-CoV-2 virus poses a serious threat to human health and the world economy. Development of safe and highly effective antiviral drugs is of great...

Binding free energy decomposition and multiple unbinding paths of buried ligands in a PreQ1 riboswitch

Riboswitches are naturally occurring RNA elements that control bacterial gene expression by binding to specific small molecules. They serve as important models for RNA-small molecule recognition and have also become a novel class of targets for developing antibiotics. Here, we carried out conventional and enhanced-sampling molecular dynamics (MD) simulations, totaling 153.5 μs, to characterize the determinants of binding free energies and unbinding paths for the cognate and synthetic ligands of a PreQ₁ riboswitch. Binding free energy analysis showed that two triplets of nucleotides, U6-C15-A29 and G5-G11-C16, contribute the most to the binding of the cognate ligands, by hydrogen bonding and by base stacking, respectively. Mg²⁺ ions are essential in stabilizing the binding pocket. For the synthetic ligands, the hydrogen-bonding contributions of the U6-C15-A29 triplet are significantly compromised, and the bound state resembles the apo state in several respects, including the disengagement of the C15-A14-A13 and A32-G33 base stacks. The bulkier synthetic ligands lead to significantly loosening of the binding pocket, including extrusion of the C15 nucleobase and a widening of the C15-C30 groove. Enhanced-sampling simulations further revealed that the cognate and synthetic ligands unbind in almost opposite directions. Our work offers new insight for designing riboswitch ligands.

Riboswitches are bacterial RNA elements that change structures upon binding a cognate ligand. They are of great interest not only for understanding gene regulation but also as targets for designing small-molecule antibiotics and chemical tools. Understanding the molecular determinants for ligand affinity and selectivity is thus crucial for designing synthetic ligands. Here we carried out extensive molecular dynamics simulations of a PreQ₁ riboswitch bound to either cognate or synthetic ligands. By comparing and contrasting these two groups of ligands, we learn how the chemical (e.g., number of hydrogen bond donors and acceptors) and physical (e.g., molecular size) features of ligands affect binding affinity and ligand exit paths. While the number of hydrogen bond donors and acceptors is a key determinant for RNA binding affinity, the ligand size affects the rigidity of the binding pocket and thereby regulates the unbinding of the ligand. These lessons provide guidance for designing riboswitch ligands.

Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations

Estrogen receptor alpha (ERα) is a ligand-dependent transcriptional factor in the nuclear receptor superfamily. Many structures of ERα bound with agonists and antagonists have been determined. However, the dynamic binding patterns of agonists and antagonists in the binding site of ERα remains unclear. Therefore, we performed molecular docking, molecular dynamics (MD) simulations, and quantum mechanical calculations to elucidate agonist and antagonist dynamic binding patterns in ERα. 17β-estradiol (E2) and 4-hydroxytamoxifen (OHT) were docked in the ligand binding pockets of the agonist and antagonist bound ERα. The best complex conformations from molecular docking were subjected to 100 nanosecond MD simulations. Hierarchical clustering was conducted to group the structures in the trajectory from MD simulations. The representative structure from each cluster was selected to calculate the binding interaction energy value for elucidation of the dynamic binding patterns of agonists and antagonists in the binding site of ERα. The binding interaction energy analysis revealed that OHT binds ERα more tightly in the antagonist conformer, while E2 prefers the agonist conformer. The results may help identify ERα antagonists as drug candidates and facilitate risk assessment of chemicals through ER-mediated responses.

Binding mechanism of inhibitors to p38α MAP kinase deciphered by using multiple replica Gaussian accelerated molecular dynamics and calculations of binding free energies

The p38α MAP Kinase has been an important target of drug design for treatment of inflammatory diseases and cancers. This work applies multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations and the molecular mechanics generalized Born surface area (MM-GBSA) method to probe the binding mechanism of inhibitors L51, R24 and 1AU to p38α. Dynamics analyses show that inhibitor bindings exert significant effect on conformational changes of the active helix α2 and the conserved DFG loop. The rank of binding free energies calculated with MM-GBSA not only agrees well with that determined by the experimental IC50 values but also suggests that mutual compensation between the enthalpy and entropy changes can improve binding of inhibitors to p38α. The analyses of free energy landscapes indicate that the L51, R24 and 1AU bound p38α display a DFG-out conformation. The residue-based free energy decomposition method is used to evaluate contributions of separate residues to the inhibitor-p38α binding and the results imply that residues V30, V38, L74, L75, I84, T106, H107, L108, M109, L167, F169 and D168 can be utilized as efficient targets of potent inhibitors toward p38α.

Binding selectivity of inhibitors toward the first over the second bromodomain of BRD4: theoretical insights from free energy calculations and multiple short molecular dynamics simulations

Bromodomain-containing protein 4 (BRD4) plays an important role in mediating gene transcription involved in cancers and non-cancer diseases such as acute heart failure and inflammatory diseases. In this work, multiple short molecular dynamics (MSMD) simulations are integrated with a molecular mechanics generalized Born surface area (MM-GBSA) approach to decipher binding selectivity of three inhibitors 8NS, 82Y, and 837 toward two domains BD1 and BD2 of BRD4. The results demonstrate that the enthalpy effects play critical roles in selectivity identification of inhibitors toward BD1 and BD2, determining that 8NS has better selectivity toward BD2 than BD1, while 82Y and 837 more favorably bind to BD1 than BD2. A residue-based free-energy decomposition method was used to calculate an inhibitor-residue interaction spectrum and unveil contributions of separate residues to binding selectivity. The results identify six common residues, containing (P82, P375), (V87, V380), (L92, L385), (L94, L387), (N140, N433), and (I146, V439) individually belonging to (BD1, BD2) of BRD4, and yield a considerable binding difference of inhibitors to BD1 and BD2, suggesting that these residues play key roles in binding selectivity of inhibitors toward BD1 and BD2 of BRD4. Therefore, these results provide useful dynamics information and a structure affinity relationship for the development of highly selective inhibitors targeting BD1 and BD2 of BRD4.

Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens

In this review, applications of various molecular modelling methods in the study of estrogens and xenoestrogens are summarized. Selected biomolecules that are the most commonly chosen as molecular modelling objects in this field are presented. In most of the reviewed works, ligand docking using solely force field methods was performed, employing various molecular targets involved in metabolism and action of estrogens. Other molecular modelling methods such as molecular dynamics and combined quantum mechanics with molecular mechanics have also been successfully used to predict the properties of estrogens and xenoestrogens. Among published works, a great number also focused on the application of different types of quantitative structure-activity relationship (QSAR) analyses to examine estrogen's structures and activities. Although the interactions between estrogens and xenoestrogens with various proteins are the most commonly studied, other aspects such as penetration of estrogens through lipid bilayers or their ability to adsorb on different materials are also explored using theoretical calculations. Apart from molecular mechanics and statistical methods, quantum mechanics calculations are also employed in the studies of estrogens and xenoestrogens. Their applications include computation of spectroscopic properties, both vibrational and Nuclear Magnetic Resonance (NMR), and also in quantum molecular dynamics simulations and crystal structure prediction. The main aim of this review is to present the great potential and versatility of various molecular modelling methods in the studies on estrogens and xenoestrogens.

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

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.

Molecular Mechanism of Binding Selectivity of Inhibitors toward BACE1 and BACE2 Revealed by Multiple Short Molecular Dynamics Simulations and Free-Energy Predictions

The β-amyloid cleaving enzymes 1 and 2 (BACE1 and BACE2) have been regarded as the prospective targets for clinically treating Alzheimer's disease (AD) in the last two decades. Thus, insight into the binding differences of inhibitors to BACE1 and BACE2 is of significance for designing highly selective inhibitors toward the two proteins. In this work, multiple short molecular dynamics (MSMD) simulations are coupled with the molecular mechanics generalized Born surface area (MM-GBSA) method to probe the binding selectivity of three inhibitors DBO, CS9, and SC7 on BACE1 over BACE2. The results show that the entropy effect plays a key role in selectivity identification of inhibitors toward BACE1 and BACE2, which determines that DBO has better selectivity toward BACE2 over BACE1, while CS9 and CS7 can more favorably bind to BACE1 than BACE2. The hierarchical clustering analysis based on energetic contributions of residues suggests that BACE1 and BACE2 share the common hot interaction spots. The residue-based free-energy decomposition method was applied to compute the inhibitor-residue interaction spectrum, and the results recognize four common binding subpockets corresponding to the different groups of inhibitors, which can be used as efficient targets for designing highly selective inhibitors toward BACE1 and BACE2. Therefore, these results provide a useful molecular basis and dynamics information for development of highly selective inhibitors targeting BACE1 and BACE2.

Computational Study of the Binding Modes of Diverse DPN Analogues on Estrogen Receptors (ER) and the Biological Evaluation of a New Potential Antiestrogenic Ligand

Estrogen (17β-estradiol) is essential for normal growth and differentiation in the mammary gland. In the last three decades, previous investigations have revealed that Estrogen Receptor Alpha (ERα) plays a critical role in breast cancer. More recently, observations regarding the widespread expression of ERβ-like proteins in normal and neoplastic mammary tissues have suggested that ERβ is also involved in the mentioned pathology. Design of new drugs both steroidal and nonsteroidal that target any of these receptors represents a promise to treat breast cancer although it remains a challenge due to the sequence similarity between their catalytic domains. In this work, we propose a new set of compounds that could effectively target the estrogen receptors ERα and ERβ. These ligands were designed based on the chemical structure of the ERβ-selective agonist Diarylpropionitrile (DPN). The designed ligands were submitted to in silico ADMET studies, yielding in a filtered list of ligands that showed better drug-like properties. Molecular dynamics simulations of both estrogen receptors and docking analysis were carried-out employing the designed compounds, from which two were chosen due to their promising characteristics retrieved from theoretical results (docking analysis or targeting receptor predictions). They were chemically synthetized and during the process, two precursor ligands were also obtained. These four ligands were subjected to biological studies from which it could be detected that compound mol60b dislplayed inhibitory activity and its ability to activate the transcription via an estrogenic mechanism of action was also determined. Interestinly, this observation can be related to theoretical binding free energy calculations, where the complex: ERβ-mol60b showed the highest energy ΔGbind value in comparison to others.

Effect of double mutations T790M/L858R on conformation and drug-resistant mechanism of epidermal growth factor receptor explored by molecular dynamics simulations

Epidermal growth factor receptor (EGFR) is one of the most promising targets for the treatment of cancers. Double mutations T790M/L858R lead to different degrees of drug resistance toward inhibitors. In this study, molecular dynamics (MD) simulations followed by principal component analysis are performed to study the conformational changes of EGFR induced by T790M/L858R. The results suggest that T790M/L858R cause obvious disturbance of the structural stability of EGFR. Molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) and residue-based free energy decomposition methods are integrated to explore the drug-resistant mechanism of T790M/L858R toward inhibitors. The results show that the decrease in van der Waals interactions of inhibitors with the mutated EFGR relative to the wild-type (WT) one is the main force inducing drug resistance of T790M/L858R toward inhibitors TAK-285, while drug resistance toward W2P and HKI-272 is dominated by the decrease in van der Waals interactions and the increase in polar interactions. We expect that the information obtained from this study can aid rational design of effective drugs to relieve drug resistance of EGFR induced by T790M/L858R.

Atomistic Analysis of ToxN and ToxI Complex Unbinding Mechanism

ToxIN is a triangular structure formed by three protein toxins (ToxNs) and three specific noncoding RNA antitoxins (ToxIs). To respond to stimuli, ToxI is preferentially degraded, releasing the ToxN. Thus, the dynamic character is essential in the normal function interactions between ToxN and ToxI. Here, equilibrated molecular dynamics (MD) simulations were performed to study the stability of ToxN and ToxI. The results indicate that ToxI adjusts the conformation of 3' and 5' termini to bind to ToxN. Steered molecular dynamics (SMD) simulations combined with the recently developed thermodynamic integration in 3nD (TI3nD) method were carried out to investigate ToxN unbinding from the ToxIN complex. The potentials of mean force (PMFs) and atomistic pictures suggest the unbinding mechanism as follows: (1) dissociation of the 5' terminus from ToxN, (2) missing the interactions involved in the 3' terminus of ToxI without three nucleotides (G31, A32, and A33), (3) starting to unfold for ToxI, (4) leaving the binding package of ToxN for three nucleotides of ToxI, (5) unfolding of ToxI. This work provides information on the structure-function relationship at the atomistic level, which is helpful for designing new potent antibacterial drugs in the future.

Insight into selective mechanism of class of I-BRD9 inhibitors toward BRD9 based on molecular dynamics simulations

Recently, bromodomain-containing protein 9 (BRD9), 7 (BRD7), and 4 (BRD4) have been potential targets of anticancer drug design. Molecular dynamic simulations followed by molecular mechanics Poisson-Boltzmann surface area calculation were performed to study the selective mechanism of I-BRD9 inhibitor H1B and its derivatives N1D, TVU, and 5V2 toward BRD9 and BRD4. The rank of our calculated binding free energies agrees with that of the experimental data. The results show that binding free energy of H1B to BRD7 is slightly lower than that of H1B to BRD9, and all four inhibitors bind more tightly to BRD9 than to BRD4. Decomposition of binding free energies into individual residues implies that Ile164 and Asn211 in BRD7 and Ile53 and Asn100 in BRD9 play a significant role in the selectivity of H1B toward BRD7 and BRD9. Besides, several key residues Phe44, Ile53, Asn100, Thr104 in BRD9 and Pro82, Lys91, Asn140, Asp144 in BRD4 that are located in the ZA-loop and BC-loop provide significant contributions to binding selectivity of inhibitors to BRD9 and BRD4. This study is expected to provide important theoretical guidance for rational designs of highly selective inhibitors targeting BRD9 and BRD4.

Ligand Selectivity Mechanism and Conformational Changes in Guanine Riboswitch by Molecular Dynamics Simulations and Free Energy Calculations

Riboswitches regulate gene expression through direct and specific interactions with small metabolite molecules. Binding of a ligand to its RNA target is high selectivity and affinity and induces conformational changes of the RNA's secondary and tertiary structure. The structural difference of two purine riboswitches aptamers is caused by only one single mutation, where cytosine 74 in the guanine riboswitch is corresponding to a uracil 74 in adenine riboswitch. Here we employed molecular dynamics (MD) simulation, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and thermodynamic integration computational methodologies to evaluate the energetic and conformational changes of ligands binding to purine riboswitches. The snapshots used in MM-PBSA calculation were extracted from ten 50 ns MD simulation trajectories for each complex. These free energy results are in consistent with the experimental data and rationalize the selectivity of the riboswitches for different ligands. In particular, it is found that the loss in binding free energy upon mutation is mainly electrostatic in guanine (GUA) and riboswitch complex. Furthermore, new hydrogen bonds are found in mutated complexes. To reveal the conformational properties of guanine riboswitch, we performed a total of 6 μs MD simulations in both the presence and the absence of the ligand GUA. The MD simulations suggest that the conformation of guanine riboswitch depends on the distance of two groups in the binding pocket of ligand. The conformation is in a close conformation when U51-A52 is close to C74-U75.

Clarifying binding difference of ATP and ADP to extracellular signal-regulated kinase 2 by using molecular dynamics simulations

Extracellular signal-regulated kinase 2 is a promising target for designs and development of anticancer drugs. Molecular dynamics simulations and molecular mechanics Poisson-Boltzmann method were applied to study binding difference of ADP and ATP to extracellular signal-regulated kinase 2. The results prove that the binding ability of ATP to extracellular signal-regulated kinase 2 is stronger than that of ADP. Principal component analysis performed by using molecular dynamics trajectories suggests that binding of ADP and ATP to extracellular signal-regulated kinase 2 change motion directions of two helices α1 and α2. Residue-based free energy decomposition method was adopted to calculate contributions of separate residues to associations of ADP and ATP with extracellular signal-regulated kinase 2. The results show that ADP and ATP produce strong CH-π interactions with five residues Ile29, Val37, Ala50, Leu105, and Leu154. In addition, five hydrogen bonding interactions of ADP and ATP with residues Lys52, Gln103, Asp104, and Met106 also stabilize bindings of ADP and ATP to extracellular signal-regulated kinase 2. Overall, the CH-π interactions of ATP with five residues Ile29, Val37, Ala50, Leu105, and Leu154 are stronger than ADP. This study is expected to contribute a significant theoretical hint for designs of anticancer drugs targeting extracellular signal-regulated kinase 2.

A transgenic mouse model expressing an ERα folding biosensor reveals the effects of Bisphenol A on estrogen receptor signaling

Estrogen receptor-α (ERα) plays an important role in normal and abnormal physiology of the human reproductive system by interacting with the endogenous ligand estradiol (E2). However, other ligands, either analogous or dissimilar to E2, also bind to ERα. This may create unintentional activation of ER signaling in reproductive tissues that can lead to cancer development. We developed a transgenic mouse model that constitutively expresses a firefly luciferase (FLuc) split reporter complementation biosensor (NFLuc-ER-LBD_G521T-CFLuc) to simultaneously evaluate the dynamics and potency of ligands that bind to ERα. We first validated this model using various ER ligands, including Raloxifene, Diethylstilbestrol, E2, and 4-hydroxytamoxifen, by employing FLuc-based optical bioluminescence imaging of living mice. We then used the model to investigate the carcinogenic property of Bisphenol A (BPA), an environmental estrogen, by long-term exposure at full and half environmental doses. We showed significant carcinogenic effects on female animals while revealing activated downstream ER signaling as measured by bioluminescence imaging. BPA induced tumor-like outgrowths in female transgenic mice, histopathologically confirmed to be neoplastic and epithelial in origin. This transgenic mouse model expressing an ERα folding-biosensor is useful in evaluation of estrogenic ligands and their downstream effects, and in studying environmental estrogen induced carcinogenesis in vivo.

Probing Origin of Binding Difference of inhibitors to MDM2 and MDMX by Polarizable Molecular Dynamics Simulation and QM/MM-GBSA Calculation

Binding abilities of current inhibitors to MDMX are weaker than to MDM2. Polarizable molecular dynamics simulations (MD) followed by Quantum mechanics/molecular mechanics generalized Born surface area (QM//MM-GBSA) calculations were performed to investigate the binding difference of inhibitors to MDM2 and MDMX. The predicted binding free energies not only agree well with the experimental results, but also show that the decrease in van der Walls interactions of inhibitors with MDMX relative to MDM2 is a main factor of weaker bindings of inhibitors to MDMX. The analyses of dihedral angles based on MD trajectories suggest that the closed conformation formed by the residues M53 and Y99 in MDMX leads to a potential steric clash with inhibitors and prevents inhibitors from arriving in the deep of MDMX binding cleft, which reduces the van der Waals contacts of inhibitors with M53, V92, P95 and L98. The calculated results using the residue-based free energy decomposition method further prove that the interaction strength of inhibitors with M53, V92, P95 and L98 from MDMX are obviously reduced compared to MDM2. We expect that this study can provide significant theoretical guidance for designs of potent dual inhibitors to block the p53-MDM2/MDMX interactions.

Revealing the binding modes and the unbinding of 14-3-3σ proteins and inhibitors by computational methods

The 14-3-3σ proteins are a family of ubiquitous conserved eukaryotic regulatory molecules involved in the regulation of mitogenic signal transduction, apoptotic cell death, and cell cycle control. A lot of small-molecule inhibitors have been identified for 14-3-3 protein-protein interactions (PPIs). In this work, we carried out molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method to study the binding mechanism between a 14-3-3σ protein and its eight inhibitors. The ranking order of our calculated binding free energies is in agreement with the experimental results. We found that the binding free energies are mainly from interactions between the phosphate group of the inhibitors and the hydrophilic residues. To improve the binding free energy of Rx group, we designed the inhibitor R9 with group R9 = 4-hydroxypheny. However, we also found that the binding free energy of inhibitor R9 is smaller than that of inhibitor R1. By further using the steer molecular dynamics (SMD) simulations, we identified a new hydrogen bond between the inhibitor R8 and residue Arg64 in the pulling paths. The information obtained from this study may be valuable for future rational design of novel inhibitors, and provide better structural understanding of inhibitor binding to 14-3-3σ proteins.

Probing Difference in Binding Modes of Inhibitors to MDMX by Molecular Dynamics Simulations and Different Free Energy Methods

The p53-MDMX interaction has attracted extensive attention of anti-cancer drug development in recent years. This current work adopted molecular dynamics (MD) simulations and cross-correlation analysis to investigate conformation changes of MDMX caused by inhibitor bindings. The obtained information indicates that the binding cleft of MDMX undergoes a large conformational change and the dynamic behavior of residues obviously change by the presence of different structural inhibitors. Two different methods of binding free energy predictions were employed to carry out a comparable insight into binding mechanisms of four inhibitors PMI, pDI, WK23 and WW8 to MDMX. The data show that the main factor controlling the inhibitor bindings to MDMX arises from van der Waals interactions. The binding free energies were further divided into contribution of each residue and the derived information gives a conclusion that the hydrophobic interactions, such as CH-CH, CH-π and π-π interactions, are responsible for the inhibitor associations with MDMX.

Conformational stability of PCID2 upon DSS1 binding with molecular dynamics simulation

DSS1 is a small acidic intrinsically disordered protein (IDP) that can fold upon binding with PCID2 TREX-2. The resulting complex plays a key role in mRNA export. However, the binding mechanism between DSS1 and PCID2 is unsolved. Here, three independent 500-ns molecular dynamics (MD) simulations were performed to study the DSS1-PCID2 binding mechanism by comparing apo-PCID2 and bound PCID2. The results show that the conformational variation of bound PCID2 is smaller than that of apo-PCID2, especially in the binding domain of two helices (helix IV and VIII). The probability of coil formation between helix III and helix IV of bound PCID2 increases, and a short anti-parallel β-sheet forms upon DSS1 binding. The decomposition of binding free energy into protein and residue pairs suggests that electrostatic and hydrophobic interactions play key roles in the recognition between DSS1 and PCID2. There is a hydrophobic core of seven residues in DSS1 favorable to the binding of PCID2. These analytical methods can be used to reveal the recognition mechanisms of other IDPs and their partners.

A comparative study of trypsin specificity based on QM/MM molecular dynamics simulation and QM/MM GBSA calculation

Hydrogen bonding and polar interactions play a key role in identification of protein-inhibitor binding specificity. Quantum mechanics/molecular mechanics molecular dynamics (QM/MM MD) simulations combined with DFT and semi-empirical Hamiltonian (AM1d, RM1, PM3, and PM6) methods were performed to study the hydrogen bonding and polar interactions of two inhibitors BEN and BEN1 with trypsin. The results show that the accuracy of treating the hydrogen bonding and polar interactions using QM/MM MD simulation of PM6 can reach the one obtained by the DFT QM/MM MD simulation. Quantum mechanics/molecular mechanics generalized Born surface area (QM/MM-GBSA) method was applied to calculate binding affinities of inhibitors to trypsin and the results suggest that the accuracy of binding affinity prediction can be significantly affected by the accurate treatment of the hydrogen bonding and polar interactions. In addition, the calculated results also reveal the binding specificity of trypsin: (1) the amidinium groups of two inhibitors generate favorable salt bridge interaction with Asp189 and form hydrogen bonding interactions with Ser190 and Gly214, (2) the phenyl of inhibitors can produce favorable van der Waals interactions with the residues His58, Cys191, Gln192, Trp211, Gly212, and Cys215. This systematic and comparative study can provide guidance for the choice of QM/MM MD methods and the designs of new potent inhibitors targeting trypsin.

Revealing origin of decrease in potency of darunavir and amprenavir against HIV-2 relative to HIV-1 protease by molecular dynamics simulations

Clinical inhibitors Darunavir (DRV) and Amprenavir (APV) are less effective on HIV-2 protease (PR2) than on HIV-1 protease (PR1). To identify molecular basis associated with the lower inhibition, molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations were performed to investigate the effectiveness of the PR1 inhibitors DRV and APV against PR1/PR2. The rank of predicted binding free energies agrees with the experimental determined one. Moreover, our results show that two inhibitors bind less strongly to PR2 than to PR1, again in agreement with the experimental findings. The decrease in binding free energies for PR2 relative to PR1 is found to arise from the reduction of the van der Waals interactions induced by the structural adjustment of the triple mutant V32I, I47V and V82I. This result is further supported by the difference between the van der Waals interactions of inhibitors with each residue in PR2 and in PR1. The results from the principle component analysis suggest that inhibitor binding tends to make the flaps of PR2 close and the one of PR1 open. We expect that this study can theoretically provide significant guidance and dynamics information for the design of potent dual inhibitors targeting PR1/PR2.