Molecular Mechanics Poisson-Boltzmann Surface Area Calculations Research Articles

Network Pharmacology Approach to Identify the Calotropis Phytoconstituents' Potential Epileptic Targets and Evaluation of Molecular Docking, MD Simulation, and MM-PBSA Performance.

Epilepsy originates from unusual electrical rhythm within brain cells, causes seizures. Calotropis species have been utilized to treat a wide spectrum of ailments since antiquity. Despite chemical and biological investigations, there have been minimal studies on their anticonvulsant activity, and the molecular targets of this plant constituents are unexplored. This study aimed to investigate the plausible epileptic targets of Calotropis phytoconstituents through network pharmacology, and to evaluate their binding strength and stability with the identified targets. In detail, 125 phytoconstituents of the Calotropis plant (C. procera and C. gigantea) were assessed for their drug-likeness (DL), blood-brain-barrier (BBB) permeability and oral bioavailability (OB). Network analysis revealed that targets PTGS2 and PPAR-γ were ranked first and fourth, respectively, among the top ten hub genes significantly linked with antiepileptic drug targets. Additionally, docking, molecular dynamic (MD) simulation, and Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) were employed to validate the compound-gene interactions. Docking studies suggested ergost-5-en-3-ol, stigmasterol and β-sitosterol exhibit stronger binding affinity and favorable interactions than co-crystallized ligands with both the targets. Furthermore, both MD simulations and MM-PBSA calculations substantiated the docking results. Combined data revealed that Calotropis phytoconstituents ergost-5-en-3-ol, stigmasterol, and β-sitosterol might be the best inhibitors of both PTGS2 and PPAR-γ.

Bioinformatics analysis and molecular dynamics simulations of azoreductases (AzrBmH2) from Bacillus megaterium H2 for the decolorization of commercial dyes

The present study aimed to investigate the decolorization of various commercial dyes by azoreductases (AzrBmH21, AzrBmH22/3, and AzrBmH24/5) through bioinformatics means, comprising molecular docking, molecular dynamics simulation, and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA). Therefore, four commercial dyes, namely acid orange 7, cresol red, methylene blue, and malachite green, were selected as potential targets for degradation by the above said azoreductases derived from Bacillus megaterium H2. The prediction of ligand binding or catalytic sites for AzrBmH21, AzrBmH22/3, and AzrBmH24/5 were performed using a machine learning algorithm based on the Prank Web and DeepSite chemoinformatic tool. This analysis revealed that several amino acids of AzrBmH2 interacted with the tested dyes, indicating the presence of distinct ligand-binding sites for AzrBmH2-dye complexes. Likewise, the binding affinity for AzrBmH21, AzrBmH22/3, and AzrBmH24/5 ranged from − 9.4 to − 5.5 kcal/mol, − 9.2 to − 5.4 kcal/mol, and − 9.0 to − 5.4 kcal/mol, respectively, with each complex stabilized at a minimum of 0–5 hydrogen bonds. MD simulations revealed stable AzrBmH2-dye complexes with RMSD and RMSF values ranging from 0.15 to 0.42 nm and 0.05 to 0.48 nm, respectively, with Rg values between 1.75 and 1.88 nm. MM-PBSA calculations indicated that the AzrBmH2–dye complexes, except for AzrBmH2–malachite green, exhibited the lowest binding energy (− 191.05 ± 7.08 to 314.19 ± 6.88 kcal/mol), with prevalent hydrophobic interactions (− 268.25 ± 12.25 to − 418.92 ± 29.45 kcal/mol) through van der Waals forces. Therefore, this study was able to highlight the potential role of enzymes, specifically azoreductases from Bacillus megaterium H2, in predicting the decolorization of commercial dyes. These findings could contribute to our understanding of the azoreductases’ mechanisms in bioremediation and for biotechnological applications.

Computational Screening of Neuropilin-1 Unveils Novel Potential Anti-SARS-CoV-2 Therapeutics.

Neuropilin 1 (NRP-1) inhibition has shown promise in reducing the infectivity of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and preventing the virus entry into nerve tissues, thereby mitigating neurological symptoms in COVID-19 patients. In this study, we employed virtual screening, including molecular docking, Molecular Dynamics (MD) simulation, and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculations, to identify potential NRP-1 inhibitors. From a compendium of 1930 drug-like natural compounds, we identified five potential leads: CNP0435132, CNP0435311, CNP0424372, CNP0429647, and CNP0427474, displaying robust binding energies of -8.2, -8.1, -10.7, -8.2, and -8.2 kcal/mol, respectively. These compounds demonstrated interactions with critical residues Tyr297, Trp301, Thr316, Asp320, Ser346, Thr349, and Tyr353 located within the b1 subdomain of NRP-1. Furthermore, MD simulations and MM-PBSA calculations affirmed the stability of the complexes formed, with average root mean square deviation, radius of gyration, and solvent accessible surface area values of 0.118 nm, 1.516 nm, and 88.667 nm2 , respectively. Notably, these lead compounds were estimated to penetrate the blood-brain barrier and displayed antiviral properties, with Pa values ranging from 0.414 to 0.779. The antagonistic effects of these lead compounds merit further investigation, as they hold the potential to serve as foundational scaffolds for the development of innovative therapeutics aimed at reducing the neuroinfectivity of SARS-CoV-2.

Screening of potent inhibitor from Aquilaria malaccensis Lam. against arachidonic inflammatory enzymes: an insight from molecular docking, ADMET, molecular dynamics simulation and MM-PBSA approaches

The three primary enzymes COX (cyclooxygenase), LOX (lipoxygenase) and CYT-P450 (cytochrome P450), which are part of the arachidonic inflammatory pathway, play crucial role in the development of asthma, rheumatoid arthritis and cardiovascular diseases. Ethnomedicinally, plant-derived chemicals have a major role in the treatment of fatal illnesses. Aquilaria malaccensis Lam. widely known as agarwood is prized for its fragrance and therapeutic properties. The phytochemicals and extracts of this plant have significant healing properties in the treatment of serious illnesses. In the current work, an in-silico approach including molecular docking, ADMET (absorption, distribution, metabolism, excretion and toxicity), molecular dynamics (MD) simulation and molecular mechanics/Poisson–Boltzmann surface area (MM-PBSA) was performed to screen 33 bioactive compounds from this plant against COX-2 and 5-LOX in order to find the most effective inhibitor. 2-(2-Phenylethyl)chromone was found to inhibit both 5-LOX and COX-2, showing the highest binding affinities (−9.1 kcal/mol and −9.0 kcal/mol, respectively) than standard Ibuprofen and nordihydroguaiaretic acid (NDGA). 2-(2-Phenylethyl)chromone showed the highest drug-likeness score and low risk of toxicity compared to other phytochemicals. MD modeling and MM-PBSA calculations showed that 2-(2-Phenylethyl)chromone had a strong persistent binding interaction with 5-LOX than COX-2, and this interaction is comparable to the bounded standards Ibuprofen and NDGA. From this study, we may infer that the 2-(2-Phenylethyl)chromone can serve as a potent inhibitor and has scope to be employed in the treatment of inflammatory ailments. Communicated by Ramaswamy H. Sarma

Revisiting MMPBSA by Adoption of MC-Based Surface Area/Volume, ANI-ML Potentials, and Two-Valued Interior Dielectric Constant.

Here, we report the accuracy improvements of molecular mechanics Poisson-Boltzmann surface area (MMPBSA) calculations by adoption of ANI-ML potentials in replacement of MM terms, the use of solvent-accessible surface area (SASA) and volume (SAV) values from the Monte Carlo sampling of the probe, and introducing two different interior dielectric constants for electrostatic interactions of protein-ligand (P-L) and polar solvation term in the MMPBSA calculations. Our results show that the Pearson correlation coefficients of MMPBSA-calculated values with respect to experimental binding free energies can be drastically improved from 0.48 to 0.90 by adoption of ANI-ML potentials in replacement of MM energy terms in the equation, referred to as ANI-PBSA. Moreover, we show that the SASA/SAV-combined equation in the scaled particle theory (SPT) can be a better choice to model nonpolar solvation term, reaching nearly the same accuracy by ANI-PBSA calculations. Finally, we introduce two different values of interior dielectric constants, which could be an alternative strategy between the single and variable constant definitions.

Targeting Natural Plant Metabolites for Hunting SARS-CoV-2 Omicron BA.1 Variant Inhibitors: Extraction, Molecular Docking, Molecular Dynamics, and Physicochemical Properties Study.

(1) Background: SARS-CoV-2 Omicron BA.1 is the most common variation found in most countries and is responsible for 99% of cases in the United States. To overcome this challenge, there is an urgent need to discover effective inhibitors to prevent the emerging BA.1 variant. Natural products, particularly flavonoids, have had widespread success in reducing COVID-19 prevalence. (2) Methods: In the ongoing study, fifteen compounds were annotated from Echium angustifolium and peach (Prunus persica), which were computationally analyzed using various in silico techniques. Molecular docking calculations were performed for the identified phytochemicals to investigate their efficacy. Molecular dynamics (MD) simulations over 200 ns followed by molecular mechanics Poisson–Boltzmann surface area calculations (MM/PBSA) were performed to estimate the binding energy. Bioactivity was also calculated for the best components in terms of drug likeness and drug score. (3) Results: The data obtained from the molecular docking study demonstrated that five compounds exhibited remarkable potency, with docking scores greater than −9.0 kcal/mol. Among them, compounds 1, 2 and 4 showed higher stability within the active site of Omicron BA.1, with ΔGbinding values of −49.02, −48.07, and −67.47 KJ/mol, respectively. These findings imply that the discovered phytoconstituents are promising in the search for anti-Omicron BA.1 drugs and should be investigated in future in vitro and in vivo research.

Exploration of potential inhibitors for SARS-CoV-2 Mpro considering its mutants via structure-based drug design, molecular docking, MD simulations, MM/PBSA, and DFT calculations.

The main protease (Mpro) of SARS-COV-2 plays a vital role in the viral life cycle and pathogenicity. Due to its specific attributes, this 3-chymotrypsin like protease can be a reliable target for the drug design to combat COVID-19. Since the advent of COVID-19, Mpro has undergone many mutations. Here, the impact of 10 mutations based on their frequency and five more based on their proximity to the active site was investigated. For comparison purposes, the docking process was also performed against the Mpros of SARS-COV and MERS-COV. Four inhibitors with the highest docking score (11b, α-ketoamide 13b, Nelfinavir, and PF-07321332) were selected for the structure-based ligand design via fragment replacement, and around 2000 new compounds were thus obtained. After the screening of these new compounds, the pharmacokinetic properties of the best ones were predicted. In the last step, comparative molecular dynamics (MD) simulations, molecular mechanics Poisson-Boltzmann surface area calculations (MM/PBSA), and density functional theory calculations were performed. Among the 2000 newly designed compounds, three of them (NE1, NE2, and NE3), which were obtained by modifications of Nelfinavir, showed the highest affinity against all the Mpro targets. Together, NE1 compound is the best candidate for follow-up Mpro inhibition and drug development studies.

In-silico study of the interactions between acylated glucagon like-peptide-1 analogues and the native receptor

We have performed a series of multiple molecular dynamics (MD) simulations of glucagon-like peptide-1 (GLP-1) and acylated GLP-1 analogues in complex with the endogenous receptor (GLP-1R) to obtain a molecular understanding of how fatty acid (FA) chain structure, acylation position on the peptide, and presence of a linker affect the binding. MD simulations were analysed to extract heatmaps of receptor–peptide interaction patterns and to determine the free energy of binding using the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach. The extracted free energies from MM-PBSA calculations are in qualitative agreement with experimentally determined potencies. Furthermore, the interaction patterns seen in the receptor–GLP-1 complex simulations resemble previously reported binding interactions validating the simulations. Analysing the receptor–GLP-1 analogue complex simulations, we found that the major differences between the systems stem from FA interactions and positioning of acylation in the peptide. Hydrophobic interactions between the FA chain and a hydrophobic patch on the extracellular domain contribute significantly to the binding affinity. Acylation on Lys26 resulted in noticeably more interactions between the FA chain and the extracellular domain hydrophobic patch than found for acylation on Lys34 and Lys38, respectively. The presence of a charged linker between the peptide and FA chain can potentially stabilise the complex by forming hydrogen bonds to arginine residues in the linker region between the extracellular domain and the transmembrane domain. A molecular understanding of the fatty acid structure and its effect on binding provides important insights into designing acylated agonists for GLP-1R. Communicated by Ramaswamy H. Sarma

Conducting the RBD of SARS-CoV-2 Omicron Variant with Phytoconstituents from Euphorbia dendroides to Repudiate the Binding of Spike Glycoprotein Using Computational Molecular Search and Simulation Approach.

(1) Background: Natural constituents are still a preferred route for counteracting the outbreak of COVID-19. Essentially, flavonoids have been found to be among the most promising molecules identified as coronavirus inhibitors. Recently, a new SARS-CoV-2 B.1.1.529 variant has spread in many countries, which has raised awareness of the role of natural constituents in attempts to contribute to therapeutic protocols. (2) Methods: Using various chromatographic techniques, triterpenes (1–7), phenolics (8–11), and flavonoids (12–17) were isolated from Euphorbia dendroides and computationally screened against the receptor-binding domain (RBD) of the SARS-CoV-2 Omicron variant. As a first step, molecular docking calculations were performed for all investigated compounds. Promising compounds were subjected to molecular dynamics simulations (MD) for 200 ns, in addition to molecular mechanics Poisson–Boltzmann surface area calculations (MM/PBSA) to determine binding energy. (3) Results: MM/PBSA binding energy calculations showed that compound 14 (quercetin-3-O-β-D-glucuronopyranoside) and compound 15 (quercetin-3-O-glucuronide 6″-O-methyl ester) exhibited strong inhibition of Omicron, with ΔGbinding of −41.0 and −32.4 kcal/mol, respectively. Finally, drug likeness evaluations based on Lipinski’s rule of five also showed that the discovered compounds exhibited good oral bioavailability. (4) Conclusions: It is foreseeable that these results provide a novel intellectual contribution in light of the decreasing prevalence of SARS-CoV-2 B.1.1.529 and could be a good addition to the therapeutic protocol.

Key criteria for engineering mycotoxin binding aptamers via computational simulations: Aflatoxin B1 as a case study.

Due to the difficulties in monoclonal antibody production specific to mycotoxins, aptameric probes have been considered as suitable alternatives. The low efficiency of the SELEX procedure in screening high affinity aptamers for binding mycotoxins as small molecules can be significantly improved through computational techniques. Previously, we designed five new aptamers to aflatoxin B1 (AFB1) based on a known aptamer sequence (Patent: PCT/CA2010/001 292, Apt1) through a genetic algorithm-based in silico maturation strategy and experimentally measured their affinity to the target toxin. Here, integrated molecular dynamic simulation (MDs) studies with molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analysis to clarify the binding modes, critical interacting nucleic bases and energy component contributions in the six AFB1-binding aptamers. The aptamer F20, which was selected in the first work, showed the best free binding energy and complex stability compared to other aptamers. The trajectory analysis revealed that AFB1 recognized F20 through the groove binding mode along with precise shape complementarity. The MD simulation results revealed that dynamic water intermediate interactions also play a key role in promoting complex stability. According to the MM-PBSA calculations, van der Waals contacts were identified as dominant energy components in all complexes. Interestingly, a high consistency is observed between the experimentally obtained binding affinities of the six aptamers with their free energy solvation. The computational findings, confirmed via previous experiments, highlighted the binding modes, the dynamic hydration of complex components and the total free interacting energy as the crucial criteria in discovering high functional aptameric probes.

An insight into the binding mechanism of Viprinin and its morpholine and piperidine derivatives with HIV-1 Vpr: molecular dynamics simulation, principal component analysis and binding free energy calculation study

HIV-1 Vpr is an accessory protein responsible for a plethora of functions inside the host cell to promote viral pathogenesis. One of the major functions of Vpr is the G2 cell cycle arrest. Among several small molecule inhibitors, Viprinin, a coumarin derivative, has been shown to specifically inhibit the G2 cell cycle arrest activity of Vpr thus making it an excellent choice for a lead molecule to design antiretroviral drug. But the exact mechanism of binding of the Viprinin and its two potent derivatives with Vpr is still not understood. In this study with combined molecular docking, molecular dynamics simulation, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method, Principal component analysis and Umbrella sampling simulation, we have explored the binding mechanism of Viprinin and its two derivatives with Vpr. MM-PBSA and Umbrella sampling calculations suggest that Viprinin and ViprininD1 have higher binding energy than ViprininD2. Molecular dynamics simulation shows that the ligands are not very stable inside the initial binding pocket and various hydrophobic interactions are responsible to hold the ligands with Vpr. Vpr backbone Principle Component Analysis (PCA) shows various unique essential motions of Vpr bound with Viprinin and its two derivatives. This study may give detailed insight of the mode of binding of the specified compounds at atomic scale and provide valuable information about the possibility of using these compounds as a potent Vpr inhibitor. Communicated by Ramaswamy H. Sarma

Ligand-Based Virtual Screening, Molecular Docking, Molecular Dynamics, and MM-PBSA Calculations towards the Identification of Potential Novel Ricin Inhibitors.

Ricin is a toxin found in the castor seeds and listed as a chemical weapon by the Chemical Weapons Convention (CWC) due to its high toxicity combined with the easiness of obtention and lack of available antidotes. The relatively frequent episodes of usage or attempting to use ricin in terrorist attacks reinforce the urge to develop an antidote for this toxin. In this sense, we selected in this work the current RTA (ricin catalytic subunit) inhibitor with the best experimental performance, as a reference molecule for virtual screening in the PubChem database. The selected molecules were then evaluated through docking studies, followed by drug-likeness investigation, molecular dynamics simulations and Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) calculations. In every step, the selection of molecules was mainly based on their ability to occupy both the active and secondary sites of RTA, which are located right next to each other, but are not simultaneously occupied by the current RTA inhibitors. Results show that the three PubChem compounds 18309602, 18498053, and 136023163 presented better overall results than the reference molecule itself, showing up as new hits for the RTA inhibition, and encouraging further experimental evaluation.

Molecular docking and molecular dynamics simulation of Bacillus thuringiensis dehalogenase against haloacids, haloacetates and chlorpyrifos

The high dependency and surplus use of agrochemical products have liberated enormous quantities of toxic halogenated pollutants into the environment and threaten the well-being of humankind. Herein, this study performed molecular docking, molecular dynamic (MD) simulations, molecular mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculations on the DehH2 from Bacillus thuringiensis, to identify the order of which the enzyme degrades different substrates, haloacids, haloacetate and chlorpyrifos. The study discovered that the DehH2 favored the degradation of haloacids and haloacetates (−3.3 − 4.6 kcal/mol) and formed three hydrogen bonds with Asp125, Arg201 and Lys202. Despite the inconclusive molecular docking result, chlorpyrifos was consistently shown to be the least favored substrate of the DehH2 in MD simulations and MM-PBSA calculations. Results of MD simulations revealed the DehH2-haloacid- (RMSD 0.15 − 0.25 nm) and DehH2-haloacetates (RMSF 0.05 − 0.25 nm) were more stable, with the DehH2-L-2CP complex being the most stable while the least was the DehH2-chlorpyrifos (RMSD 0.295 nm; RMSF 0.05 − 0.59 nm). The Molecular Mechanics Poisson-Boltzmann Surface Area calculations showed the DehH2-L-2CP complex (−24.27 kcal/mol) having the lowest binding energy followed by DehH2-MCA (−22.78 kcal/mol), DehH2-D-2CP (−21.82 kcal/mol), DehH2-3CP (−21.11 kcal/mol), DehH2-2,2-DCP (−18.34 kcal/mol), DehH2-2,3-DCP (−8.34 kcal/mol), DehH2-TCA (−7.62 kcal/mol), while chlorpyrifos was unable to spontaneously bind to DehH2 (+127.16 kcal/mol). In a nutshell, the findings of this study offer valuable insights into the rational tailoring of the DehH2 for expanding its substrate specificity and catalytic activity in the near future. Communicated by Ramaswamy H. Sarma

Role of Thermolysin in Catalytic-Controlled Self-Assembly of Fmoc-Dipeptides

In recent years, short peptide self-assembled materials, prepared under the control of the thermolysin catalyst, have been investigated extensively and shown to acquire various morphologies and fun...

Heterogeneous Dielectric Implicit Membrane Model for the Calculation of MMPBSA Binding Free Energies.

Membrane-bound protein receptors are a primary biological drug target, but the computational analysis of membrane proteins has been limited. In order to improve molecular mechanics Poisson-Boltzmann surface area (MMPBSA) binding free energy calculations for membrane protein-ligand systems, we have optimized a new heterogeneous dielectric implicit membrane model, with respect to free energy simulations in explicit membrane and explicit water, and implemented it into the Amber software suite. This new model supersedes our previous uniform, single dielectric implicit membrane model by allowing the dielectric constant to vary with depth within the membrane. We calculated MMPBSA binding free energies for the human purinergic platelet receptor (P2Y12R) and two of the muscarinic acetylcholine receptors (M2R and M3R) bound to various antagonist ligands using both membrane models, and we found that the heterogeneous dielectric membrane model has a stronger correlation with experimental binding affinities compared to the older model under otherwise identical conditions. This improved membrane model increases the utility of MMPBSA calculations for the rational design and improvement of future drug candidates.

Statistical Analysis on the Performance of Molecular Mechanics Poisson–Boltzmann Surface Area versus Absolute Binding Free Energy Calculations: Bromodomains as a Case Study

Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson–Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain–inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson () and Spearman () correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ( = 0.64 and = 0.66 for ABFE; = 0.39 and = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: = 0.55 and = 0.56 when including an entropy estimate, and = 0.53 and = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein–ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost.

Systems Pharmacology Dissection of Multiscale Mechanisms of Action for Herbal Medicines in Treating Rheumatoid Arthritis.

As a chronic inflammatory and angiogenic disease with increased morbidity and mortality, rheumatoid arthritis (RA) is characterized by the proliferation of synovial tissue and the accumulation of excessive mononuclear infiltration, which always results in the joint deformity, disability, and eventually the destruction of the bone and cartilage. Traditional Chinese Medicine (TCM), with rich history of proper effectiveness in treating the inflammatory joint disease containing RA, has long combated such illness from, actually, an integrative and holistic point of view. However, its "multi-components" and "multi-targets" features make it very difficult to decipher the molecular mechanisms of RA from a systematic perspective if employing only routine methods. Presently, an innovative systems-pharmacology approach was introduced, which combined the ADME screening model, drug targeting, and network pharmacology, to explore the action mechanisms of botanic herbs for the treatment of RA. As a result, we uncovered 117 active compounds and 85 key molecular targets from seven RA-related herbs, which are mainly implicated in four signaling pathways, that is, vascular endothelial growth factor, PI3K-Akt, Toll-like receptor, and T-cell-receptor pathways. Additionally, the network relationships among the active components, target proteins, and pathways were further built to uncover the pharmacological characters of these herbs. Besides, molecular dynamics (MD) simulations and molecular mechanics-Poisson-Boltzmann surface area calculations were carried out to explore the binding interactions between the compounds and their receptors as well as to investigate the binding affinity of the ligand to their protein targets. In vitro experiments by ligand binding assays validate the reliability of the drug-target interactions as well as the MD results. The high binding affinities and good inhibitions of the active compounds indicate that the potential therapeutic effects of these herbal medicines for treating RA are exerted probably through the modulation of these relevant proteins, which further validates the rationality and reliability of the drug-target interactions as well as our the network-based analytical methods. This work may be of help for not only understanding the action mechanisms of TCM and for discovering new drugs from plants for the treatment of RA, but also providing a novel potential method for modern medicine in treating complex diseases.

QM/MM simulations provide insight into the mechanism of bioluminescence triggering in ctenophore photoproteins.

Photoproteins are responsible for light emission in a variety of marine ctenophores and coelenterates. The mechanism of light emission in both families occurs via the same reaction. However, the arrangement of amino acid residues surrounding the chromophore, and the catalytic mechanism of light emission is unknown for the ctenophore photoproteins. In this study, we used quantum mechanics/molecular mechanics (QM/MM) and site-directed mutagenesis studies to investigate the details of the catalytic mechanism in berovin, a member of the ctenophore family. In the absence of a crystal structure of the berovin-substrate complex, molecular docking was used to determine the binding mode of the protonated (2-hydroperoxy) and deprotonated (2-peroxy anion) forms of the substrate to berovin. A total of 13 mutants predicted to surround the binding site were targeted by site-directed mutagenesis which revealed their relative importance in substrate binding and catalysis. Molecular dynamics simulations and MM-PBSA (Molecular Mechanics Poisson-Boltzmann/surface area) calculations showed that electrostatic and polar solvation energy are +115.65 and -100.42 kcal/mol in the deprotonated form, respectively. QM/MM calculations and pKa analysis revealed the deprotonated form of substrate is unstable due to the generation of a dioxetane intermediate caused by nucleophilic attack of the substrate peroxy anion at its C3 position. This work also revealed that a hydrogen bonding network formed by a D158- R41-Y204 triad could be responsible for shuttling the proton from the 2- hydroperoxy group of the substrate to bulk solvent.

Effect of the R119G mutation on human P5CR structure and its interactions with NAD: Insights derived from molecular dynamics simulation and free energy analysis

Pyrroline-5-carboxylate reductase (P5CR), an enzyme with conserved housekeeping roles, is involved in the etiology of cutis laxa. While previous work has shown that the R119G point mutation in the P5CR protein is involved, the structural mechanism behind the pathology remains to be elucidated. In order to probe the role of the R119G mutation in cutis laxa, we performed molecular dynamics (MD) simulations, essential dynamics (ED) analysis, and Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations on wild type (WT) and mutant P5CR-NAD complex. These MD simulations and ED analyses suggest that the R119G mutation decreases the flexibility of P5CR, specifically in the substrate binding pocket, which could decrease the kinetics of the cofactor entrance and egress. Furthermore, the MM-PBSA calculations suggest the R119G mutant has a lower cofactor binding affinity for NAD than WT. Our study provides insight into the possible role of the R119G mutation during interactions between P5CR and NAD, thus bettering our understanding of how the mutation promotes cutis laxa.

Calculating protein-ligand binding affinities with MMPBSA: Method and error analysis.

Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) methods have become widely adopted in estimating protein-ligand binding affinities due to their efficiency and high correlation with experiment. Here different computational alternatives were investigated to assess their impact to the agreement of MMPBSA calculations with experiment. Seven receptor families with both high-quality crystal structures and binding affinities were selected. First the performance of nonpolar solvation models was studied and it was found that the modern approach that separately models hydrophobic and dispersion interactions dramatically reduces RMSD's of computed relative binding affinities. The numerical setup of the Poisson-Boltzmann methods was analyzed next. The data shows that the impact of grid spacing to the quality of MMPBSA calculations is small: the numerical error at the grid spacing of 0.5 Å is already small enough to be negligible. The impact of different atomic radius sets and different molecular surface definitions was further analyzed and weak influences were found on the agreement with experiment. The influence of solute dielectric constant was also analyzed: a higher dielectric constant generally improves the overall agreement with experiment, especially for highly charged binding pockets. The data also showed that the converged simulations caused slight reduction in the agreement with experiment. Finally the direction of estimating absolute binding free energies was briefly explored. Upon correction of the binding-induced rearrangement free energy and the binding entropy lost, the errors in absolute binding affinities were also reduced dramatically when the modern nonpolar solvent model was used, although further developments were apparently necessary to further improve the MMPBSA methods. © 2016 Wiley Periodicals, Inc.