End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design

Phillygenin, a MELK Inhibitor, Inhibits Cell Survival and Epithelial-Mesenchymal Transition in Pancreatic Cancer Cells

Introduction

Pancreatic cancer (PC) is one of the leading causes of cancer, with the lowest 5-year survival rate of all cancer types. Given the fast metastasis of PC and its resistance to surgery, radiotherapy, chemotherapy, and combinations thereof, it is imperative to develop more effective anti-PC drugs. Phillygenin (PHI) has been reported to exert anti-cancer, anti-bacterial, and anti‐inflammatory properties. However, the mechanism of PHI in the development of PC is still unclear.

Methods

The cytotoxicity of PHI in pancreatic cancer cells was evaluated by MTT assay, and clonogenic assay was used to test the anti-proliferation of PHI. The pro-apoptotic effect of PHI was detected by flow cytometry analysis. The changes of epithelial–mesenchymal transition (EMT) in pancreatic cancer cells treated with PHI were determined by Western blot. Transwell assay was used to test the migration and invasion of PC cells after treatment with PHI. Molecular docking was used to predict the potential binding site of candidate target with PHI.

Results

PHI could inhibit the proliferation, migration, and EMT of PC cells (PANC-1 and SW1990) and induce its apoptosis. Analysis of the Cancer Genome Atlas database indicated that elevated MELK levels correlated with poor overall survival (OS) and disease-free survival (DFS) of PC patients. In addition, molecular modeling showed that PHI may potentially target the catalytic domain of maternal embryonic leucine zipper kinase (MELK). Overexpression of MELK muted the anti-PC effects of PHI.

Conclusion

PHI holds promise as a potent candidate drug for the treatment of PC via targeted MELK.

Identification of NUDT5 Inhibitors From Approved Drugs

Recent studies have revealed the important role of NUDT5 in estrogen signaling and breast cancer, but research on the corresponding targeted therapy has just started. Drug repositioning strategy can effectively reduce the time and economic resources spent on drug discovery. To find novel inhibitors of NUDT5, we investigated the previously identified connectivity map-based drug association models and found eighteen FDA approved drugs as candidates. The molecular docking and molecular dynamic simulation were performed and revealed that fourteen organic drugs have the potential to bind the NUDT5 target. Eight representative drugs were selected to perform the cell line viability inhibition analysis, and the results showed that seven of them were able to suppress MCF7 breast cancer cells. Two drugs, nomifensine and isoconazole, showed lower IC₅₀ than the known antiestrogens raloxifene and tamoxifen, and they deserve further pharmacodynamic investigations to test their feasibility for use as NUDT5 inhibitors.

Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method

Scoring functions are routinely deployed in structure-based drug design to quantify the potential for protein-ligand (PL) complex formation. Here, we present a new scoring function Bappl+ that is designed to predict the binding affinities of non-metallo and metallo PL complexes. Bappl+ outperforms other state-of-the-art scoring functions, achieving a high Pearson correlation coefficient of up to ~ 0.76 with low standard deviations. The biggest contributors to the increased performance are the use of a machine-learning model and the enlarged training dataset. We have also evaluated the performance of Bappl+ on target-specific proteins, which highlighted the limitations of our function and provides a way for further improvements. We believe that Bappl+ methodology could prove valuable in ranking candidate molecules against a target metallo or non-metallo protein by reliably predicting their binding affinities, thus helping in the drug discovery process.

Selective Inhibition of HDAC1 by Macrocyclic Polypeptide for the Treatment of Glioblastoma: A Binding Mechanistic Analysis Based on Molecular Dynamics

Glioblastoma (GBM) is the most common and aggressive intracranial malignant brain tumor, and the abnormal expression of HDAC1 is closely correlated to the progression, recurrence and metastasis of GBM cells, making selective inhibition of HDAC1 a promising strategy for GBM treatments. Among all available selective HDAC1 inhibitors, the macrocyclic peptides have gained great attention due to their remarkable inhibitory selectivity on HDAC1. However, the binding mechanism underlying this selectivity is still elusive, which increases the difficulty of designing and synthesizing the macrocyclic peptide-based anti-GBM drug. Herein, multiple computational approaches were employed to explore the binding behaviors of a typical macrocyclic peptide FK228 in both HDAC1 and HDAC6. Starting from the docking conformations of FK228 in the binding pockets of HDAC1&6, relatively long MD simulation (500 ns) shown that the hydrophobic interaction and hydrogen bonding of E91 and D92 in the Loop2 of HDAC1 with the Cap had a certain traction effect on FK228, and the sub-pocket formed by Loop1 and Loop2 in HDAC1 could better accommodate the Cap group, which had a positive effect on maintaining the active conformation of FK228. While the weakening of the interactions between FK228 and the residues in the Loop2 of HDAC6 during the MD simulation led to the large deflection of FK228 in the binding site, which also resulted in the decrease in the interactions between the Linker region of FK228 and the previously identified key amino acids (H134, F143, H174, and F203). Therefore, the residues located in Loop1 and Loop2 contributed in maintaining the active conformation of FK228, which would provide valuable hints for the discovery and design of novel macrocyclic polypeptide HDAC inhibitors.

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.

Residue-Residue Mutual Work Analysis of Retinal-Opsin Interaction in Rhodopsin: Implications for Protein-Ligand Binding

Energetic contributions at the single-residue level for retinal-opsin interactions in rhodopsin were studied by combining molecular dynamics simulations, transition path sampling, and a newly developed energy decomposition approach. The virtual work at an infinitesimal time interval was decomposed into the work components on one residue due to its interaction with another residue, which were then averaged over the transition path ensemble along a proposed reaction coordinate. Such residue-residue mutual work analysis on 62 residues within the active center of rhodopsin resulted in a very sparse interaction matrix, which is generally not symmetric but antisymmetric to some extent. Fourteen residues were identified to be major players in retinal relaxation along a plausible pathway from bathorhodopsin to the blue-shifted intermediate, which is in good agreement with an existing NMR study. Based on the matrix of mutual work, a comprehensive network was constructed to provide detailed insights into the chromophore-protein interaction from a viewpoint of energy flow.

Fast, Accurate, and Reliable Protocols for Routine Calculations of Protein-Ligand Binding Affinities in Drug Design Projects Using AMBER GPU-TI with ff14SB/GAFF

Accurate prediction of the absolute or relative protein-ligand binding affinity is one of the major tasks in computer-aided drug design projects, especially in the stage of lead optimization. In principle, the alchemical free energy (AFE) methods such as thermodynamic integration (TI) or free-energy perturbation (FEP) can fulfill this task, but in practice, a lot of hurdles prevent them from being routinely applied in daily drug design projects, such as the demanding computing resources, slow computing processes, unavailable or inaccurate force field parameters, and difficult and unfriendly setting up and post-analysis procedures. In this study, we have exploited practical protocols of applying the CPU (central processing unit)-TI and newly developed GPU (graphic processing unit)-TI modules and other tools in the AMBER software package, combined with ff14SB/GAFF1.8 force fields, to conduct efficient and accurate AFE calculations on protein-ligand binding free energies. We have tested 134 protein-ligand complexes in total for four target proteins (BACE, CDK2, MCL1, and PTP1B) and obtained overall comparable performance with the commercial Schrodinger FEP+ program (WangJ. Am. Chem. Soc.2015, 137, 2695-2703). The achieved accuracy fits within the requirements for computations to generate effective guidance for experimental work in drug lead optimization, and the needed wall time is short enough for practical application. Our verified protocol provides a practical solution for routine AFE calculations in real drug design projects.

Molecular Simulation of Oncostatin M and Receptor (OSM-OSMR) Interaction as a Potential Therapeutic Target for Inflammatory Bowel Disease

Therapeutics targeting cytokines such as the oncostatin M (OSM)-mediated inflammation represent a potential strategy for the treatment of inflammatory bowel disease (IBD). Despite the investigation of the specific role of the interactions between OSM and the receptor (OSMR) in IBD pathogenesis, the 3D structure of the OSM–OSMR complex remains elusive. In this work, the interaction mode between OSM and OSMR at atomic level was predicted by computational simulation approach. The interaction domain of the OSMR was built with the homology modeling method. The near-native structure of the OSM–OSMR complex was obtained by docking, and long-time scale molecular dynamics (MD) simulation in an explicit solvent was further performed to sample the conformations when OSM binds to the OSMR. After getting the equilibrated states of the simulation system, per-residue energy contribution was calculated to characterize the important residues for the OSM–OSMR complex formation. Based on these important residues, eight residues (OSM: Arg100, Leu103, Phe160, and Gln161; OSMR: Tyr214, Ser223, Asp262, and Trp267) were identified as the “hot spots” through computational alanine mutagenesis analysis and verified by additional MD simulation of R100A (one of the identified “hotspots”) mutant. Moreover, six cavities were detected at the OSM–OSMR interface through the FTMap analysis, and they were suggested as important binding sites. The predicted 3D structure of the OSM–OSMR complex and the identified “hot spots” constituting the core of the binding interface provide helpful information in understanding the OSM–OSMR interactions, and the detected sites serve as promising targets in designing small molecules to block the interactions.

Fast Identification of Possible Drug Treatment of Coronavirus Disease -19 (COVID-19) Through Computational Drug Repurposing Study

The recent outbreak of novel coronavirus disease -19 (COVID-19) calls for and welcomes possible treatment strategies using drugs on the market. It is very efficient to apply computer-aided drug design techniques to quickly identify promising drug repurposing candidates, especially after the detailed 3D-structures of key virous proteins are resolved. Taking the advantage of a recently released crystal structure of COVID-19 protease in complex with a covalently-bonded inhibitor, N3,1 I conducted virtual docking screening of approved drugs and drug candidates in clinical trials. For the top docking hits, I then performed molecular dynamics simulations followed by binding free energy calculations using an endpoint method called MM-PBSA-WSAS.2-4 Several promising known drugs stand out as potential inhibitors of COVID-19 protease, including Carfilzomib, Eravacycline, Valrubicin, Lopinavir and Elbasvir. Carfilzomib, an approved anti-cancer drug acting as a proteasome inhibitor, has the best MM-PBSA-WSAS binding free energy, -13.82 kcal/mol. Streptomycin, an antibiotic and a charged molecule, also demonstrates some inhibitory effect, even though the predicted binding free energy of the charged form (-3.82 kcal/mol) is not nearly as low as that of the neutral form (-7.92 kcal/mol). One bioactive, PubChem 23727975, has a binding free energy of -12.86 kcal/mol. Detailed receptor-ligand interactions were analyzed and hot spots for the receptor-ligand binding were identified. I found that one hotspot residue HIS41, is a conserved residue across many viruses including COVID-19, SARS, MERS, and HCV. The findings of this study can facilitate rational drug design targeting the COVID-19 protease.

Advances in the calculation of binding free energies

In recent years, calculations of binding affinities from molecular simulations seem to have matured significantly. While the number of applications of such methods in drug design and biotechnology increases, the number of truly new methodological developments decreases. This review provides an overview of the current status of the field as reflected in recent publications. The focus is on the challenges that remain when using endstate, alchemical and pathway methods. For endstate methods this is the calculation of entropic contributions. For alchemical methods there are unsolved problems associated with the solvation of the active site, sampling slow degrees of freedom and when modifying the net charge. For pathway methods achieving sufficient sampling remains challenging. New trends are also highlighted, including the use of pathway methods for the quantification of protein-protein interactions.

Effect of CTerm of human albumin on the aggregation propensity of Aβ1-42 peptide: a potential of mean force study

Alzheimer's disease (AD) is the most common progressive neurodegenerative brain disorder. It is characterized by the presence of extracellular aggregated fibrillary form of amyloid beta (Aβ) peptide and intraneuronal neurofibrillary tangles caused by the hyperphosphorylation of tau protein. Monomeric form of Aβ peptide in α-conformation is not toxic but it can undergo self-aggregation to form β-conformation which is neurotoxic. The most promising approach to combat AD is to prevent the self-aggregation of Aβ peptide. Recently, it has been reported that C-terminal (CTerm) of human albumin (HA) binds to the Aβ_1-42 peptide and impairs the Aβ_1-42 aggregation and promotes disassembly of Aβ_1-42 aggregates. In this work, using potential of mean force (PMF) and binding free energy (BFE) calculations, we have demonstrated the effect of CTerm of HA on the dimerization of Aβ_1-42 peptide. From the PMF profile, we noticed Aβ_1-42-CTerm Heterodimer (10.99 kcal mol - 1) complex to have higher disassociation energy than Aβ_1-42-Aβ_1-42 homodimer (2.23 kcal mol - 1) complex. And also from the BFE calculations, we found that the binding affinity between Aβ_1-42 peptide and CTerm (ΔG_bind = -32.27 kcal mol - 1 from MM-GBSA and ΔG_bind = -2.83 kcal mol - 1 from MM-PBSA (molecular mechanics-Poisson - Boltzmann surface area)) to be stronger than the Aβ_1-42 peptide and another Aβ_1-42 peptide (ΔG_bind = -16.20 kcal mol - 1 from MM-GBSA and ΔG_bind = -1.95 kcal mol - 1 from MM-PBSA). In this study, our findings from PMF and BFE analysis of the two complexes provide salient structural, binding and unbinding features and thermodynamics that support the ability of CTerm of HA in affecting the dimerization of Aβ_1-42. Communicated by Ramaswamy H. Sarma.

The binding mode of vilazodone in the human serotonin transporter elucidated by ligand docking and molecular dynamics simulations

Vilazodone is a novel antidepressant used for the treatment of major depressive disorder (MDD) with a primary action mechanism of inhibiting the human serotonin reuptake transporter (hSERT) and acting as a 5-HT_1A receptor partial agonist. The interaction between vilazodone and the 5-HT_1A receptor has been reported, however, the binding mode of vilazodone in the hSERT remains elusive. In the current study, to elucidate the molecular mechanism of vilazodone binding in the hSERT, the drug and its five analogs were docked into the hSERT crystal structure as initial conformations and were sampled by 400 ns molecular dynamics (MD) simulations. Through the analysis of the profiles of protein-ligand binding free energies, interaction fingerprints, and conformational rearrangements, the binding mode of vilazodone in the hSERT was revealed. As a result, unlike the classical antidepressants located in the S1 site of the hSERT, vilazodone adopted a linear pose in the binding pocket. Its arylpiperazine fragment occupies the central site (S1) and interacts with Y95, D98, I172, Y176, F335, F341, S438, and T439, while the indole fragment extends to the allosteric site (S2) via interacting with the ionic switch (R104/E403) between the two sites. The new insights obtained are not only helpful in understanding the binding mode of vilazodone in the hSERT, but also provide valuable guidance to the discovery of novel antidepressant drugs.

Molecular Basis for Metabolic Regioselectivity and Mechanism of Cytochrome P450s toward Carcinogenic 4-(Methylnitrosamino)-(3-pyridyl)-1-butanone

As an abundantly present tobacco component, carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) has also been detected in atmospheric particulate matter, suggesting the ineluctable exposure risk of this contaminant. NNK metabolic activation by cytochrome P450 enzymes (CYPs) is a prerequisite to exerting its genotoxicity, but the metabolic regioselectivity and mechanism are still unknown. Here the binding feature and regioselectivity of CYPs 1A1, 1A2, 2A6, 2A13, 2B6, and 3A4 toward NNK are unraveled through molecular docking and molecular dynamics (MD) simulations. Binding mode analyses reveal that 1A2 and 2B6 have definite preferences for NNK α-methyl hydroxylation, while the other four CYPs preferentially catalyze α-methylene hydroxylation. The binding affinities between NNK and CYPs evaluated by the binding free energies follow the order 2A13 > 2B6 > 1A2 > 2A6 > 1A1 > 3A4. Density functional theory (DFT) calculations are further performed to characterize the mechanism of NNK biotransformation. Results show that the α-hydroxyNNK generated from α-hydroxylation may undergo nonenzymatic decomposition to form genotoxic diazohydroxide and aldehyde, and further oxidation by P450 to yield nitrosamide, which mainly contributes to NNK toxification capacity. Meanwhile the pyridine N-oxidation and denitrosation of C_α-radical intermediate play an important role in detoxifying NNK. Overall, the present study provides the molecular basis for CYP-catalyzed regioselectivity and mechanism of NNK biotransformation, which can enable the identification of metabolites for assessing the health risk of individual NNK exposure.

Discovery of novel and potent P2Y14R antagonists via structure-based virtual screening for the treatment of acute gouty arthritis

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A reliable Glide docking-based virtual screening (VS) pipeline for P2Y₁₄R was developed.

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Several potent P2Y₁₄R antagonists with novel scaffolds were identified utilizing the VS strategy.

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P2Y₁₄R inhibitory effect was evaluated by testing cAMP levels in HEK293 cells.

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Anti-gout activity of screened compound was detected in MSU-treated THP-1 cells.

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The mechanism of test compound in treating acute gouty arthritis was elucidated.

P2Y₁₄ nucleotide receptor is a Gi protein-coupled receptor, which is widely involved in physiological and pathologic events. Although several P2Y₁₄R antagonists have been developed thus far, few have successfully been developed into a therapeutic drug. In this study, on the basis of two P2Y₁₄R homology models, Glide docking-based virtual screening (VS) strategy was employed for finding potent P2Y₁₄R antagonists with novel chemical architectures. A total of 19 structurally diverse compounds identified by VS and drug-like properties testing were set to experimental testing. 10 of them showed good inhibitory effects against the P2Y₁₄R (IC₅₀ < 50 nM), including four compounds (compounds 8, 10, 18 and 19) with IC₅₀ value below 10 nM. The best VS hit, compound 8 exhibited the best antagonistic activity, with IC₅₀ value of 2.46 nM. More importantly, compound 8 restrained monosodium uric acid (MSU)-induced pyroptosis of THP-1 cells through blocking the activation of Nod-like receptor 3 (NLRP3) inflammasome, which was attributed to its inhibitory effects on P2Y₁₄R-cAMP pathways. The key favorable residues uncovered using MM/GBSA binding free energy calculations/decompositions were detected and discussed. These findings suggest that the compound 8 can be used as a good lead compound for further optimization to obtain more promising P2Y₁₄R antagonists for the treatment of acute gouty arthritis.

Impact of lymphoma-linked Asn11Tyr point mutation on the interaction between Bcl-2 and a BH3 mimetic: Insights from molecular dynamics simulation

Frequent mutations in the Bcl-2 anti-apoptotic protein are often implicated in diffuse large B-cell lymphoma (DLBCL), a disease profoundly resistant to drugs. Bcl-2-competitive inhibitors, "BH3 mimetics," activate apoptosis by interfering with the interactions between pro-apoptotic BH3 domains and the hydrophobic groove of Bcl-2. The aim of our research is to determine the potential of DLBCL-linked N11Y mutation to facilitate resistance against a "BH3 mimetic" using molecular dynamics simulation. Binding free energy calculations suggest a significant decrease in the binding affinity in the mutant model. In-depth analysis of the models using residue interaction network, dynamic cross-correlation, and free energy landscape approaches reveal that the mutation modifies the conformations of key residues, thereby altering the shape of the hydrophobic groove. This subsequently changes the ligand orientation and counteracts the phenomenon of LB region unwinding, a crucial event observed in the wild-type model. Lowest frequency motions captured by principal component analysis reflect the stretching of the groove for efficient ligand accommodation in the wild-type complex but not in the mutant model. This is the first in silico study that unravels the mechanism of drug resistance induced by a Bcl-2 mutation, which could be of great relevance while designing and tailoring therapeutics.

Rational Drug Design of Axl Tyrosine Kinase Type I Inhibitors as Promising Candidates Against Cancer

The high level of Axl tyrosine kinase expression in various cancer cell lines makes it an attractive target for the development of anti-cancer drugs. In this study, we carried out several sets of in silico screening for the ATP-competitive Axl kinase inhibitors based on different molecular docking protocols. The best drug-like candidates were identified, after parental structure modifications, by their highest affinity to the target protein. We found that our newly designed compound R5, a derivative of the R428 patented analog, is the most promising inhibitor of the Axl kinase according to the three molecular docking algorithms applied in the study. The molecular docking results are in agreement with the molecular dynamics simulations using the MM-PBSA/GBSA implicit solvation models, which confirm the high affinity of R5 toward the protein receptor. Additionally, the selectivity test against other kinases also reveals a high affinity of R5 toward ABL1 and Tyro3 kinases, emphasizing its promising potential for the treatment of malignant tumors.

Novel MscL agonists that allow multiple antibiotics cytoplasmic access activate the channel through a common binding site

The antibiotic resistance crisis is becoming dire, yet in the past several years few potential antibiotics or adjuvants with novel modes of action have been identified. The bacterial mechanosensitive channel of large conductance, MscL, found in the majority of bacterial species, including pathogens, normally functions as an emergency release valve, sensing membrane tension upon low-osmotic stress and discharging cytoplasmic solutes before cell lysis. Opening the huge ~30Å diameter pore of MscL inappropriately is detrimental to the cell, allowing solutes from and even passage of drugs into to cytoplasm. Thus, MscL is a potential novel drug target. However, there are no known natural agonists, and small compounds that modulate MscL activity are just now being identified. Here we describe a small compound, K05, that specifically modulates MscL activity and we compare results with those obtained for the recently characterized MscL agonist 011A. While the structure of K05 only vaguely resembles 011A, many of the findings, including the binding pocket, are similar. On the other hand, both in vivo and molecular dynamic simulations indicate that the two compounds modulate MscL activity in significantly different ways.

Exploring the binding mode and thermodynamics of inverse agonists against estrogen-related receptor alpha

Since estrogen-related receptor alpha (ERRα), one of three estrogen-related receptors, displays constitutively active transcriptional activities and important implications in both physiological and pathological processes of breast cancers, ERRα was recently recognized as a new target to fight breast cancers, and regulating the activity of ERRα with inverse agonists has thus become a promising new therapeutic strategy. A few inverse agonists cyclohexylmethyl-(1-p-tolyl-1H-indol-3-ylmethyl)-amine (compound 1), thiadiazoacrylamide (XCT790), and 1-(2,5-diethoxy-benzyl)-3-phenyl-area analogues (compounds 2 and 3) were reported to be capable of targeting ERRα. However, the detailed mechanism by which the inverse agonists deactivate ERRα remains unclear, especially in the aspects of quantitative binding and hot spot residues. Therefore, to gain insights into the interaction modes between inverse agonists and ERRα ligand binding domain, all-atom molecular dynamics (MD) simulations were firstly carried out for the complexes of inverse agonists and ERRα. The binding free energies were then calculated with MM-PBSA method to quantitatively discuss the binding of the inverse agonists with ERRα. The binding affinities were finally decomposed to per-residue contributions to identify the hot spot residues as well as assess their role in the binding mechanism. MD simulations show that the inverse agonists stretch downwards into the ERRα ligand binding pocket (LBP) formed by H3 and H11 helices, and upon the binding H12 adopts a well-defined position in the coactivator groove, where PGC-1α binds to ERRα. Binding energy analysis indicates that compound 3 and XCT790 bind more tightly to ERRα than compounds 1 and 2, and the energy difference mainly results from the contribution of van der Waals interaction. Both binding mode analysis and affinity decomposition per-residue indicate that compound 1, XCT790, and compound 3 have similar binding spectra to ERRα, primarily interacting with the residues of H3, H5, H6/H7 loop, and H11 helix, while compound 2 lacks a significant interaction with the H5 region. The hot spot residues significantly binding to the three inverse agonists in common include Leu324, Phe328, Phe382, Leu398, Phe495, and Leu500. It is essential for an effective inverse agonist to strongly bind with the aromatic ring cluster consisting of Phe328(H3), Phe495(H11), and Phe382(H5/H6 loop) as well as Leu500.

All-atom MD simulations were for the first time carried out for the complexes of inverse agonists and ERRα, and their binding free energies were also calculated with MM-PBSA to quantitatively discuss the binding of the inverse agonists with ERRα.

Improving the performance of the MM/PBSA and MM/GBSA methods in recognizing the native structure of the Bcl-2 family using the interaction entropy method

Correct discrimination of native structure plays an important role in drug design. IE method significantly improves the performance of MM/PB(GB)SA method in discriminating native and decoy structures in protein–ligand/protein systems of Bcl-2 family.

Calculating the absolute binding free energy of the insulin dimer in an explicit solvent

Insulin is a significant hormone in the regulation of glucose level in the blood. Its monomers bind to each other to form dimers or hexamers through a complex process. To study the binding of the insulin dimer, we first calculate its absolute binding free energy by the steered molecular dynamics method and the confinement method based on a fictitious thermodynamic cycle. After considering some special correction terms, the final calculated binding free energy at 298 K is −8.97 ± 1.41 kcal mol⁻¹, which is close to the experimental value of −7.2 ± 0.8 kcal mol⁻¹. Furthermore, we discuss the important residue–residue interactions between the insulin monomers, including hydrophobic interactions, π–π interactions and hydrogen bond interactions. The analysis reveals five key residues, Vla^B12, Tyr^B16, Phe^B24, Phe^B25, and Tyr^B26, for the dimerization of the insulin. We also perform MM-PBSA calculations for the wild-type dimer and some mutants and study the roles of the key residues by the change of the binding energy of the insulin dimer.

In this paper, we calculate the absolute binding free energy of an insulin dimer by steered MD method. The result of −8.97 kcal mol⁻¹ is close to the experimental value −7.2 kcal mol⁻¹. We also analyze the residue–residue interactions.

Dimerization energetics of the G-protein coupled bile acid receptor TGR5 from all-atom simulations

We describe the first extensive energetic evaluation of GPCR dimerization on the atomistic level by means of potential of mean force (PMF) computations and implicit solvent/implicit membrane end-point free energy calculations (MM-PBSA approach). Free energies of association computed from the PMFs show that the formation of both the 1/8 and 4/5 interface is energetically favorable for TGR5, the first GPCR known to be activated by hydrophobic bile acids and neurosteroids. Furthermore, formation of the 1/8 interface is favored over that of the 4/5 interface. Both results are in line with our previous FRET experiments in live cells. Differences in lipid-protein interactions are identified to contribute to the observed differences in free energies of association. A per-residue decomposition of the MM-PBSA effective binding energy reveals hot spot residues specific for both interfaces that form clusters. This knowledge may be used to guide the design of dimerization inhibitors or perform mutational studies to explore physiological consequences of distorted TGR5 association. Finally, we characterized the role of Y111, located in the conserved (D/E)RY motif, as a facilitator of TGR5 interactions. The types of computations performed here should be transferable to other transmembrane proteins that form dimers or higher oligomers as long as good structural models of the dimeric or oligomeric states are available. Such computations may help to overcome current restrictions due to an imperfect energetic representation of protein association at the coarse-grained level. © 2019 Wiley Periodicals, Inc.

Identify old drugs as selective bacterial β-GUS inhibitors by structural-based virtual screening and bio-evaluations

Irinotecan (CPT-11) is a cytotoxic drug that has wide applicability and usage in cancer treatment. Despite its success, patients suffer dose-dependent diarrhea, limiting the drug's efficacy. No effective therapy is available for this unmet medical need. The bacterial β-glucuronidase (β-GUS) plays pivotal role in CPT-11-induced diarrhea (CID) via activating the non-toxic SN-38G to toxic SN-38 inside intestine. By using structural-based virtual screening, three old drugs (N-Desmethylclozapine, Aspartame, and Gemifloxacin) were firstly identified as selective bacterial β-GUS inhibitors. The IC₅₀ values of the compounds in the enzyme-based and cell-based assays range from 0.0389 to 3.6040 and 0.0105 to 5.3730 μM, respectively. The compounds also showed good selectivity against mammalian β-GUS and no significant cytotoxicity in bacteria. Molecular docking and molecular dynamics simulations were performed to further investigate the binding modes of compounds with bacterial β-GUS. Binding free energy decomposition revealed that the compounds formed strong interactions with E413 in catalytic trail from primary monomer and F365' on the bacterial loop from the other monomer of bacterial β-GUS, explaining the selectivity against mammalian β-GUS. The old drugs identified here may be used as bacterial β-GUS inhibitors for CID or other bacterial β-GUS-related disorders.

Probing the Druggablility on the Interface of the Protein-Protein Interaction and Its Allosteric Regulation Mechanism on the Drug Screening for the CXCR4 Homodimer

Modulating protein–protein interactions (PPIs) with small drug-like molecules targeting it exhibits great promise in modern drug discovery. G protein-coupled receptors (GPCRs) are the largest family of targeted proteins and could form dimers in living biological cells through PPIs. However, compared to drug development of the orthosteric site, there has been lack of investigations on the druggability of the PPI interface for GPCRs and its functional implication on experiments. Thus, in order to address these issues, we constructed a novel computational strategy, which involved in molecular dynamics simulation, virtual screening and protein structure network (PSN), to study one representative GPCR homodimer (CXCR4). One druggable pocket was identified in the PPI interface and one small molecule targeting it was screened, which could strengthen PPI mainly through hydrophobic interaction between the benzene rings of the PPI molecule and TM4 of the receptor. The PSN results further reveals that the PPI molecule could increase the number of the allosteric regulation pathways between the druggable pocket of the dimer interface to the orthostatic site for the subunit A but only play minor role for the other subunit B, leading to the asymmetric change in the volume of the binding pockets for the two subunits (increase for the subunit A and minor change for the subunit B). Consequently, the screening performance of the subunit A to the antagonists is enhanced while the subunit B is unchanged nearly, implying that the PPI molecule may be beneficial to enhance the drug efficacies of the antagonists. In addition, one main regulation pathway with the highest frequency was identified for the subunit A, which consists of Trp195^5.34–Tyr190^ECL2–Val196^5.35–Gln200^5.39–Asp262^6.58–Cys28^N-term, revealing their importance in the allosteric regulation from the PPI molecule. The observations from the work could provide valuable information for the development of the PPI drug-like molecule for GPCRs.

Computational insights into the binding pattern of mitochondrial calcium uniporter inhibitor through homology modeling, molecular dynamics simulation, binding free energy prediction and density functional theory calculation

The mitochondrial calcium uniporter (MCU) is the critical protein of the inner mitochondrial membrane that is the primary mediator for calcium uptake into the mitochondrial matrix. Herein we built the optimal homology model of human MCU which was refined through all-atom molecular dynamics simulation. Then, the binding mode of known inhibitor was predicted through molecular docking method, along with molecular dynamics simulation and binding free energy calculation to verify the docking result and stability of the protein-inhibitor complex. Finally, density functional theory (DFT) calculation enhanced our understanding of the molecular interaction of MCU inhibitor. Our research would provide a deeper insight into the interactions between human MCU and its inhibitor, which boosts to develop novel therapy against MCU related disease.Communicated by Ramaswamy H. Sarma.

Computational investigation of a ternary model of SnoN-SMAD3-SMAD4 complex

The transforming growth factor β (TGFβ) plays an essential role in the regulation of cellular processes such as cell proliferation, migration, differentiation, and apoptosis by association with SMAD transcriptional factors that are regulated by the transcriptional regulator SnoN. The crystal structure of SnoN-SMAD4 reveals that SnoN can adopt two binding modes, the open and closed forms, at the interfaces of SMAD4 subunits. Accumulating evidence indicates that SnoN can interact with both SMAD3 and SMAD4 to form a ternary SnoN-SMAD3-SMAD4 complex in the TGFβ signaling pathway. However, how the interaction of SnoN with the SMAD3 and SMAD4 remains unclear. Here, molecular dynamics (MD) simulations and molecular modeling methods were performed to figure out this issue. The simulations reveal that SnoN^open exists in two, open and semi-closed, conformations. Molecular modeling and MD simulation studies suggest that the SnoN^closed form interferes with the SMAD3-SMAD4 protein; in contract, the SnoN^open can form a stable SnoN-SMAD3-SMAD4 complex. These mechanistic mechanisms may help elucidate the detailed engagement of SnoN with two SMAD3 and SMAD4 transcriptional factors in the regulation of TGFβ signaling pathway.

New application of in silico methods in identifying mechanisms of action and key components of anti-cancer herbal formulation YIV-906 (PHY906)

YIV-906 (formally PHY906, KD018) is a four-herb formulation that is currently being developed to improve the therapeutic index and ameliorate the side effects of many chemotherapeutic drugs including sorafenib, irinotecan, and capecitabine. However, as a promising anti-cancer adjuvant, the molecular mechanism of action of YIV-906 remains unrevealed due to its multi-component and multi-target features. Since YIV-906 has been shown to induce apoptosis and autophagy in cancer cells through modulating the negative regulators of ERK1/2, namely DUSPs, it is of great interest to elucidate the key components that cause the therapeutic effect of YIV-906. In this work, we investigated the mechanism of YIV-906 inhibiting DUSPs, using a broad spectrum of molecular modelling techniques, including molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. In total, MD simulations and binding free energy calculations were performed for 99 DUSP-ligand complexes. We found that some herbal components or their metabolites could inhibit DUSPs. Based on the docking scores and binding free energies, the sulfation and glucuronidation metabolites of the S ingredient in YIV-906 play a leading role in inhibiting DUSPs, although several original herbal chemicals with carboxyl groups from the P and Z ingredients also make contributions to this inhibitory effect. It is not a surprise that the electrostatic interaction plays the dominant role in the ligand binding process, given the fact that several charged residues reside in the binding pockets of DUSPs. Our MD simulation results demonstrate that the sulfate moieties and carboxyl moieties of the advantageous ligands from YIV-906 can occupy the enzymes' catalytic sites, mimicking the endogenous phosphate substrates of DUSPs. As such, the ligand binding can inhibit the association of DUSPs and ERK1/2, which in turn reduces the dephosphorylation of ERK1/2 and causes cell cycle arrest in the tumor. Our modelling study provides useful insights into the rational design of highly potent anti-cancer drugs targeting DUSPs. Finally, we have demonstrated that multi-scale molecular modelling techniques are able to elucidate molecular mechanisms involving complex molecular systems.

The guanidiniocarbonylpyrrole-fluorophore conjugates as theragnostic tools for dipeptidyl peptidase III monitoring and inhibition

Study of seven new guanidiniocarbonylpyrrole (GCP)-fluorophore conjugates interactions with dipeptidyl peptidase III (DPP III) showed that all compounds bind strongly (K_s ≈ µM) to enzyme active site, but with very different fluorimetric response (varying from quenching to strong increase), dependent on the fluorophore type and intramolecular pre-organisation of molecule. Positively charged lysine side chain improved significantly compound solubility but diminished fluorescence increase upon DPP III binding and completely abolished inhibitory effect on DPP III activity, whereas linker-neutral analogues showed stronger emission increase and were efficient enzyme inhibitors. By far the best fluorimetric response and inhibitive properties showed cyanine-GCP analogue, thus being promising lead compound for both enzyme sensing and bio-activity inhibiting (theragnostic) studies of DPP III in the future.Communicated by Ramaswamy H. Sarma.

A Comparative Linear Interaction Energy and MM/PBSA Study on SIRT1-Ligand Binding Free Energy Calculation

Binding free energy (ΔGbind) computation can play an important role in prioritizing compounds to be evaluated experimentally on their affinity for target proteins, yet fast and accurate ΔGbind calculation remains an elusive task. In this study, we compare the performance of two popular end-point methods, i.e., linear interaction energy (LIE) and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), with respect to their ability to correlate calculated binding affinities of 27 thieno[3,2-d]pyrimidine-6-carboxamide-derived sirtuin 1 (SIRT1) inhibitors with experimental data. Compared with the standard single-trajectory setup of MM/PBSA, our study elucidates that LIE allows to obtain direct ("absolute") values for SIRT1 binding free energies with lower compute requirements, while the accuracy in calculating relative values for ΔGbind is comparable (Pearson's r = 0.72 and 0.64 for LIE and MM/PBSA, respectively). We also investigate the potential of combining multiple docking poses in iterative LIE models and find that Boltzmann-like weighting of outcomes of simulations starting from different poses can retrieve appropriate binding orientations. In addition, we find that in this particular case study the LIE and MM/PBSA models can be optimized by neglecting the contributions from electrostatic and polar interactions to the ΔGbind calculations.