Molecular Mechanics Poisson-Boltzmann Surface Research Articles

A molecular docking study of potential inhibitors and repurposed drugs against SARS-CoV-2 main protease enzyme

COVID-19 has affected millions of people. Although many drugs are in use to combat disease, there is not any sufficient treatment yet. Having critical role in propagation of the novel coronavirus (SARS-CoV-2) works Main Protease up into a significant drug target. We have performed a molecular docking study to define possible inhibitor candidates against SARS-CoV-2 Main Protease enzyme. Besides docking Remdesivir, Ribavirin, Chloroquine and 28 other antiviral inhibitors (totally 31 inhibitors) to Main Protease enzyme, we have also performed a molecular docking study of 2177 ligands, which are used against Main Protease for the first time by using molecular docking program Autodock4. All ligands were successfully docked into Main Protease enzyme binding site. Among all ligands, EY16 coded ligand which previously used as EBNA1-DNA binding blocker candidate showed the best score for Main Protease with a binding free energy of −10.83 ​kcal/mol which was also lower than re-docking score of N3 ligand (−10.72 ​kcal/mol) contained in crystal structure of Main Protease. After analyzing the docking modes and docking scores we have found that our ligands have better binding free energy values than the inhibitors in use of treatment. We believe that further studies such as molecular dynamics or Molecular Mechanic Poisson Boltzmann Surface Area studies can make contribution that is more exhaustive to the docking results.

Detailed Characterization of the Cooperative Binding of Piperine with Heat Shock Protein 70 by Molecular Biophysical Approaches.

In this work, for the first time, details of the complex formed by heat shock protein 70 (HSP70) independent nucleotide binding domain (NBD) and piperine were characterized through experimental and computational molecular biophysical methods. Fluorescence spectroscopy results revealed positive cooperativity between the two binding sites. Circular dichroism identified secondary conformational changes. Molecular dynamics along with molecular mechanics Poisson Boltzmann surface area (MM/PBSA) reinforced the positive cooperativity, showing that the affinity of piperine for NBD increased when piperine occupied both binding sites instead of one. The spontaneity of the complexation was demonstrated through the Gibbs free energy (∆G < 0 kJ/mol) for different temperatures obtained experimentally by van’t Hoff analysis and computationally by umbrella sampling with the potential of mean force profile. Furthermore, the mean forces which drove the complexation were disclosed by van’t Hoff and MM/PBSA as being the non-specific interactions. In conclusion, the work revealed characteristics of NBD and piperine interaction, which may support further drug discover studies.

A Computational Study to Identify Potential Inhibitors of SARS-CoV-2 Main Protease (Mpro) from Eucalyptus Active Compounds

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was found to be a severe threat to global public health in late 2019. Nevertheless, no approved medicines have been found to inhibit the virus effectively. Anti-malarial and antiviral medicines have been reported to target the SARS-CoV-2 virus. This paper chose eight natural eucalyptus compounds to study their binding interactions with the SARS-CoV-2 main protease (Mpro) to assess their potential for becoming herbal drugs for the new SARS-CoV-2 infection virus. In-silico methods such as molecular docking, molecular dynamics (MD) simulations, and Molecular Mechanics Poisson Boltzmann Surface Area (MM/PBSA) analysis were used to examine interactions at the atomistic level. The results of molecular docking indicate that Mpro has good binding energy for all compounds studied. Three docked compounds, α-gurjunene, aromadendrene, and allo-aromadendrene, with highest binding energies of −7.34 kcal/mol (−30.75 kJ/mol), −7.23 kcal/mol (−30.25 kJ/mol), and −7.17 kcal/mol (−29.99 kJ/mol) respectively, were simulated with GROningen MAchine for Chemical Simulations (GROMACS) to measure the molecular interactions between Mpro and inhibitors in detail. Our MD simulation results show that α-gurjunene has the strongest binding energy of −20.37 kcal/mol (−85.21 kJ/mol), followed by aromadendrene with −18.99 kcal/mol (−79.45 kJ/mol), and finally allo-aromadendrene with −17.91 kcal/mol (−74.95 kJ/mol). The findings indicate that eucalyptus may be used to inhibit the Mpro enzyme as a drug candidate. This is the first computational analysis that gives an insight into the potential role of structural flexibility during interactions with eucalyptus compounds. It also sheds light on the structural design of new herbal medicinal products against Mpro.

Identification of a novel binding mechanism of Quinoline based molecules with lactate dehydrogenase of Plasmodium falciparum

The deadliest disease caused by the Plasmodium species is malaria. Among other species, the infection caused by Plasmodium falciparum (Pf) is life-threatening. The biological function and three-dimensional structure of PfLDH and human LDH are very similar. Any treatment aiming to inhibit the PfLDH can also affect the activity of human LDH. This study aims to identify molecules that show high selectivity for PfLDH without having a profound effect on the activity of human LDH. In this study, 30 in-house synthesized Quinolines based molecules were docked with both PfLDH and human LDH. Based on molecular docking results, molecules 3j, 4b, 4h, 4m were showed selectivity towards PfLDH. All the four molecules had better binding affinity, ligand efficiency, lipophilic ligand efficiency, and torsion than Chloroquine (referenced inhibitor). Further, molecular dynamics (MD) simulations and molecular mechanics Poisson Boltzmann surface area (MM-PBSA) calculations were carried out to validate the docking results and to compare the stability of selected complexes against the complex with Chloroquine. MD simulations showed stable dynamic behavior of all the selected molecules in comparison to Chloroquine. Finally, on the basis of MM-PBSA analysis, molecule 3j was revealed novel binding mechanism and was selected as the potent and selective inhibitor of PfLDH.Communicated by Ramaswamy H. Sarma

Computational Modeling Explains the Multi Sterol Ligand Specificity of the N-Terminal Domain of Niemann-Pick C1-Like 1 Protein.

Niemann–Pick C1 like 1 (NPC1L1) is a sterol transporter expressed in the apical membrane of enterocytes and hepatocytes. NPC1L1 resembles the lysosomal NPC1 protein including an N-terminal domain (NTD), which binds a variety of sterols. The molecular mechanisms underlying this multiligand specificity of the NTD of NPC1L1 (NPC1L1–NTD) are not known. On the basis of the crystal structure of NPC1L1–NTD, we have investigated the structural details of protein–sterol interactions using molecular mechanics Poisson Boltzmann surface area calculations here. We found a good agreement between experimental and calculated binding affinities with similar ranking of various sterol ligands. We defined hydrogen bonding of sterol ligands via the 3′-β-hydroxy group inside the binding pose as instrumental in stabilizing the interaction. A leucine residue (LEU213) at the mouth of the binding pocket transiently opens to allow for the access of sterol into the binding pose. Our calculations also predict that NPC1L1–NTD binds polyene sterols, such as dehydroergosterol or cholestatrienol with high affinity, which validates their use in future experiments as close intrinsically fluorescent cholesterol analogs. A free energy decomposition and computational mutation analysis revealed that the binding of various sterols to NPC1L1–NTD depends critically on specific amino acid residues within the binding pocket. Some of these residues were previously detected as being relevant for intestinal cholesterol absorption. We show that clinically known mutations in the NPC1L1–NTD associated with lowered risk of coronary heart disease result in strongly reduced binding energies, providing a molecular explanation for the clinical phenotype.

Prediction of novel inhibitors for Crotalus adamanteus l-amino acid oxidase by repurposing FDA-approved drugs: a virtual screening and molecular dynamics simulation investigation

One of the deadliest enzymes in the snake venom is l-amino acid oxidase (LAAO) which plays an important role in the pathophysiological effects during snake envenomation. Some effects of this enzyme on the human body are apoptosis, platelet aggregation, edema, hemorrhage, and cytotoxicity. Hence, inhibiting the enzyme activity to reduce its degradation effects is of great medical and pharmacological importance. On the other hand, drug repurposing is a process to find the new existing drug for a new medical indication. Since Crotalus adamanteus LAAO has no crystal structure in the protein data bank, first, its 3D structure was constructed by homology modeling using 1REO as the template and then modeled structure was evaluated by several algorithms. We screened the FDA-approved drugs by structure-based virtual screening, molecular dynamics (MD) simulation, and Molecular Mechanics Poisson Boltzmann Surface Area (MM/PBSA) to identify new inhibitors for the snake venom LAAO. Interestingly, docking results revealed that half of the hits belong to the propionic acid derivatives drugs. In addition, MD simulation was performed to assess the interaction profile of the docked protein–hits complexes. Meanwhile, Arg88, Gln112, Lys345, Trp356 form consistent hydrogen bond interactions with Dexketoprofen, Flurbiprofen, Ketoprofen, Morphine, and Citric acid during simulation. According to the results, each of the four compounds can be an appropriate inhibitor of LAAO and since our study was based on drug repurposing could be evaluated in phase II clinical trials.

Molecular dynamics simulation of interleukin-2 and its complex and determination of the binding free energy

ABSTRACTInterleukin-2 (IL-2) protein belongs to the signal modulator cytokine's family and therefore it is prevalent for immunological responses. It has been identified as a centrally important potential drug target for the inhibition of protein-protein interactions; so as to suppress the immunological responses associated with autoimmune, inflammatory and immunological diseases, and cancer. In the present work, we have performed two independent 100 ns of molecular dynamics (MD) simulations on the apo IL-2 protein and its ligand-bound complex (with a potent inhibitor FRG), to study the effect of inhibitor binding on the dynamics and stability of the protein. The calculation of binding free energy via post-processing end state method of Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA) and Molecular Mechanics Generalised Born Surface Area (MM-GBSA) has inferred a good correlation in accordance with the already reported experimental data, demonstrating that the free energy of binding calculated by the two methods has no significant difference. The investigation of individual components of free energy revealed that the association of IL-2 protein with FRG ligand is primarily driven by the van der Waals energy contribution that represents the non-polar/hydrophobic energy contribution as dominant in this case of ligand binding.

Molecular Dynamic Simulation of Hydroxymethylglutaryl-CoA Reductase Inhibitors from Gnetum gnemon L. Seed Extract

Objective: Gnetum gnemon L. (melinjo) seed extract contained trans-resveratrol which has been shown to inhibit hydroxymethylglutaryl-CoA (HMG-CoA) reductase. Therefore it has a potent activity for lowering blood cholesterol. This study was carried out to determine the molecular dynamics simulation of HMG-CoA reductase inhibitors from Gnetum gnemon L. seed extract. Methods: Molecular dynamics simulation using AMBER was used. The simulation was set at 300 K as default temperature and 310 K, average human body temperature. The main parameters of this study were ligand-residue interaction, binding affinity, root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bonds analysis, molecular mechanics Poisson Boltzmann surface area (MMPBSA), and molecular mechanics generalized born surface area (MMGBSA). Results: In the simulation study, trans-resveratrol, trans-piceid, gnemonol M, gnemonoside B, viniferin and gnetin C had shown lower energy than HMG (PDB ID: MAH), the substrate of HMG-CoA Reductase. Free energy binding obtained from simulation was between 11.1 to -31.38 kcal/mol. Conclusion: The simulation at 310 K was preferable than 300 K as more interactions were performed and higher affinity was obtained.

Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR.

The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

Rational design and structure-activity relationship studies of quercetin-amino acid hybrids targeting the anti-apoptotic protein Bcl-xL.

Anti-apoptotic proteins, like the Bcl-2 family proteins, present an important therapeutic cancer drug target. Their activity is orchestrated through neutralization upon interaction of pro-apoptotic protein counterparts that leads to immortality of cancer cells. Therefore, generating compounds targeting these proteins is of immense therapeutic importance. Herein, Induced Fit Docking (IFD) and Molecular Dynamics (MD) simulations were performed to rationally design quercetin analogues that bind in the BH3 site of the Bcl-xL protein. IFD calculations determined their binding cavity while Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA) and Molecular Mechanics Generalised Born Surface Area (MM-GBSA) calculations provided an insight into the binding enthalpies of the analogues. The quercetin analogues were synthesized and their binding to Bcl-xL was verified with fluorescence spectroscopy. The binding affinity and the thermodynamic parameters between Bcl-xL and quercetin-glutamic acid were estimated through Isothermal Titration Calorimetry. 2D 1H-15N HSQC NMR chemical shift perturbation mapping was used to chart the binding site of the quercetin analogues in the Bcl-xL that overlapped with the predicted poses generated by both IFD and MD calculations. Furthermore, evaluation of the four conjugates against the prostate DU-145 and PC-3 cancer cell lines, revealed quercetin-glutamic acid and quercetin-alanine as the most potent conjugates bearing the higher cytostatic activity. This pinpoints that the chemical space of natural products can be tailored to exploit new hits for difficult tractable targets such as protein-protein interactions.

Which Free Energy Methods can Predict Transport by Proton-Dependent Oligopeptide Symporters?

Peptide transporters use a proton electrochemical gradient to move di- and tripeptides across the membrane. Despite having crystal stuctures from bacteria, little is known on how these transporters achieve a broad substrate specificity. In this study, we modelled the binding of peptides and drugs on peptide transporters based on recently published crystal structures [1] and used a range of free energy methods to predict transport. The binding free energies calculated were compared to IC50 values from in vitro transport assay. We found that while docking scores produced inaccurate results, a reasonable correlation can be achieved by end-point methods such as molecular mechanics Poisson Boltzmann surface area (MMPBSA). Theoretically-rigorous methods such as thermodynamic integration (TI) can subsequently be employed to fine-tune the predictions amongst substrates with similar transport properties. Our calculations reproduced this transporter's preference for hydrophobic ligands (due to a hydrophobic pocket formed by Tyr68 and Trp296), while charged substrates showed lower affinity as they can disrupt existing salt bridges in the protein. Overall, our study reveals the potential use of free energy methods to predict the transport of small molecules by a symporter protein and help understand its substrate selectivity.[1] Lyons, J.; Parker, J.; Solcan, N.; Brinth, A.; Li, D.; Shah, S.; Caffrey, M.; Newstead, S.; EMBO Rep., 15 (8), 886-893, 2014

Studies of N(9)-arenthenyl purines as novel DFG-in and DFG-out dual Src/Abl inhibitors using 3D-QSAR, docking and molecular dynamics simulations.

Recently, the development of Src/Abl (c-Src/Bcr-Abl tyrosine kinases) dual inhibitors has attracted considerable attention from the research community for treatment of malignancies. In order to explore the different structural features impacting the Src and Abl inhibitory activities of N(9)-arenethenyl purines and to investigate the molecular mechanisms of ligand-receptor interactions, a molecular modeling study combining the three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations was performed. The obtained CoMFA (comparative molecular field analysis) models exhibited satisfactory internal and external predictability. The plots of the CoMFA fields could be used to investigate the structural differences between DFG-in (targeting the active enzyme conformation) and DFG-out (targeting the inactive enzyme conformation) inhibitors. The key amino acid residues were identified by docking studies, and the detailed binding modes of the compounds with different activities were determined by MD simulations. The binding free energies gave a good correlation with the experimental determined activities. In an energetic analysis, the MM-PBSA (molecular mechanics Poisson-Boltzmann surface) energy decomposition revealed that the van der Waals interactions were the major driving force for the binding of the DFG-in and DFG-out compounds to Src and Abl, especially the hydrophobic interactions between ligands and residues Ala403/380, Asp404/381, and Phe405/382 in DFG-out Src and Abl complexes. They also help to stabilize the DFG-out conformations. These results can offer useful references for designing novel potential DFG-in and DFG-out dual Src/Abl inhibitors.

Atomistic characterization of binding modes and affinity of peptide inhibitors to amyloid-β protein

The aggregation of amyloid β-protein (Aβ) is tightly linked to the pathogenesis of Alzheimer’s disease. Previous studies have found that three peptide inhibitors (i.e., KLVFF, VVIA, and LPFFD) can inhibit Aβ aggregation and alleviate Aβ-induced neurotoxicity. However, atomic details of binding modes and binding affinities between these peptide inhibitors and Aβ have not been revealed. Here, using molecular dynamics simulations and molecular mechanics Poisson Boltzmann surface area (MM/PBSA) analysis, we examined the effect of three peptide inhibitors (KLVFF, VVIA, and LPFFD) on their sequence-specific interactions with Aβ and the molecular basis of their inhibition. All inhibitors exhibit varied binding affinity to Aβ, in which KLVFF has the highest binding affinity, whereas LPFFD has the least. MM/PBSA analysis further revealed that different peptide inhibitors have different modes of interaction with Aβ, consequently hotspot binding residues, and underlying driving forces. Specific residue-based interactions between inhibitors and Aβ were determined and compared for illustrating different binding and inhibition mechanisms. This work provides structure-based binding information for further modification and optimization of these three peptide inhibitors to enhance their binding and inhibitory abilities against Aβ aggregation.

Investigation on the mechanism for the binding and drug resistance of wild type and mutations of G86 residue in HIV-1 protease complexed with Darunavir by molecular dynamic simulation and free energy calculation

Residue Gly86 is considered as the highly conversed residue in the HIV-1 protease. In our work, the detailed binding free energies for the wild-type (WT) and mutated proteases binding to the TMC-114 are estimated to investigate the protein-inhibitor binding and drug resistance mechanism by molecule dynamic simulations and molecular mechanics Poisson Boltzmann surface area (MM-PBSA) method. The binding affinities between the mutants and inhibitor are different than that in the wild-type complex and the major resistance to Darunavir (DRV) of G86A and G86S originate from the electrostatic energy and entropy, respectively. Furthermore, free energy decomposition analysis for the WT and mutated complexes on the basis of per-residue indicates that the mutagenesis influences the energy contribution of the residue located at three regions: active site region (residue 24-32), the flap region, and the region around the mutated residue G86 (residue 79-88), especially the flap region. Finally, further hydrogen bonds and structure analysis are carried out to detect the relationship between the energy and conformation. In all, the G86 mutations change the flap region's conformation. The experimental results are in good agreement with available results.

DNA-recognition process described by MD simulations of the lactose repressor protein on a specific and a non-specific DNA sequence

The lactose repressor protein may bind DNA in two possible configurations: a specific one, if the DNA sequence corresponds to a binding site, and a non-specific one otherwise. To find its target sequences, the lactose repressor first binds non-specifically to DNA, and subsequently, it rapidly searches for a binding site. Atomic structures of non-specific and specific complexes are available from crystallographic and nuclear magnetic resonance experiments. However, what remains unknown is a detailed description of the steps that transform the non-specific complex into the specific one. Here, how the protein first recognizes its binding site has been studied using molecular dynamics simulations. The picture that emerges is that of a protein that is as mobile when interacting with non-specific DNA sequences as when free in solution. This high degree of mobility allows the protein to rapidly sample different DNA sequences. In contrast, when the protein encounters a binding site, the configuration ensemble collapses, and the protein sliding movements along the DNA sequence become scarce. The binding energies in the specific and non-specific complexes were analysed using the Molecular Mechanics Poisson Boltzmann Surface Area approach. These results represent a first step towards a throughout characterization of the DNA-recognition process.

The Role of Phe82 and Phe351 in Auxin-Induced Substrate Perception by TIR1 Ubiquitin Ligase: A Novel Insight from Molecular Dynamics Simulations

It is well known that Auxin plays a key role in controlling many aspects of plant growth and development. Crystal structures of Transport inhibitor response 1 (TIR1), a true receptor of auxin, were very recently determined for TIR1 alone and in complexes with auxin and different synthetic analogues and an Auxin/Indole-3-Acetic Acid (Aux/IAA) substrate peptide. However, the dynamic conformational changes of the key residues of TIR1 that take place during the auxin and substrate perception by TIR1 and the detailed mechanism of these changes are still unclear. In the present study, various computational techniques were integrated to uncover the detailed molecular mechanism of the auxin and Aux/IAA perception process; these simulations included molecular dynamics (MD) simulations on complexes and the free enzyme, the molecular mechanics Poisson Boltzmann surface area (MM-PBSA) calculations, normal mode analysis, and hydrogen bond energy (HBE) calculations. The computational simulation results provided a reasonable explanation for the structure-activity relationships of auxin and its synthetic analogues in view of energy. In addition, a more detailed model for auxin and Aux/IAA perception was also proposed, indicating that Phe82 and Phe351 played a pivotal role in Aux/IAA perception. Upon auxin binding, Phe82 underwent conformational changes to accommodate the subsequent binding of Aux/IAA. As a result, auxin enhances the TIR1-Aux/IAA interactions by acting as a “molecular glue”. Besides, Phe351 acts as a “fastener” to further improve the substrate binding. The structural and mechanistic insights obtained from the present study will provide valuable clues for the future design of promising auxin analogues.

Molecular modeling of Protein A affinity chromatography

The properties of the complex between fragment B of Protein A and the Fc domain of IgG were investigated adopting molecular dynamics with the intent of providing useful insight that might be exploited to design mimetic ligands with properties similar to those of Protein A. Simulations were performed both for the complex in solution and supported on an agarose surface, which was modeled as an entangled structure constituted by two agarose double chains. The energetic analysis was performed by means of the molecular mechanics Poisson Boltzmann surface area (MM/PBSA), molecular mechanics generalized Born surface area (MM/GBSA), and the linear interaction energy (LIE) approaches. An alanine scan was performed to determine the relative contribution of Protein A key amino acids to the complex interaction energy. It was found that three amino acids play a dominant role: Gln 129, Phe 132 and Lys 154, though also four other residues, Tyr 133, Leu 136, Glu 143 and Gln 151 contribute significantly to the overall binding energy. A successive molecular dynamics analysis of Protein A re-organization performed when it is not in complex with IgG has however shown that Phe 132 and Tyr 133 interact among themselves establishing a significant π–π interaction, which is disrupted upon formation of the complex with IgG and thus reduces consistently their contribution to the protein–antibody bond. The effect that adsorbing fragment B of Protein A on an agarose support has on the stability of the protein–antibody bond was investigated using a minimal molecular model and compared to a similar study performed for a synthetic ligand. It was found that the interaction with the surface does not hinder significantly the capability of Protein A to interact with IgG, while it is crucial for the synthetic ligand. These results indicate that ligand–surface interactions should be considered in the design of new synthetic affinity ligands in order to achieve results comparable to those of Protein A right from the ligand design stage.