Human microsomal prostaglandin E synthase-1 (mPGES-1) binding with inhibitors and the quantitative structure-activity correlation

The detailed structures of microsomal prostaglandin E synthase-1 (mPGES-1) binding with inhibitors have been studied, for the first time, by using a newly developed computational three-dimensional (3D) structural model of mPGES-1 along with a 3D-quantitative structure--activity relationship (3D-QSAR) analysis. The obtained satisfactory binding structures and 3D-QSAR models strongly suggest that the 3D structural model of mPGES-1 is reasonable for study of mPGES-1 binding with inhibitors and for future design of novel mPGES-1 inhibitors.     

Homo-timeric structural model of human microsomal prostaglandin E synthase-1 and characterization of its substrate/inhibitor binding interactions

Inducible, microsomal prostaglandin E synthase 1 (mPGES-1), the terminal enzyme in the prostaglandin (PG) biosynthetic pathway, constitutes a promising therapeutic target for the development of new anti-inflammatory drugs. To elucidate structure–function relationships and to enable structure-based design, an mPGES-1 homology model was developed using the three-dimensional structure of the closest homologue of the MAPEG family (Membrane Associated Proteins in Eicosanoid and Glutathione metabolism), mGST-1. The ensuing model of mPGES-1 is a homo-trimer, with each monomer consisting of four membrane-spanning segments. Extensive structure refinement revealed an inter-monomer salt bridge (K26-E77) as well as inter-helical interactions within each monomer, including polar hydrogen bonds (e.g. T78-R110-T129) and hydrophobic π-stacking (F82-F103-F106), all contributing to the overall stability of the homo-trimer of mPGES-1. Catalytic co-factor glutathione (GSH) was docked into the mPGES-1 model by flexible optimization of both the ligand and the protein conformations, starting from the initial location ascertained from the mGST-1 structure. Possible binding site for the substrate, prostaglandin H₂ (PGH₂), was identified by systematically probing the refined molecular structure of mPGES-1. A binding model was generated by induced fit docking of PGH₂ in the presence of GSH. The homology model prescribes three potential inhibitor binding sites per mPGES-1 trimer. This was further confirmed experimentally by equilibrium dialysis study which generated a binding stoichiometric ratio of approximately three inhibitor molecules to three mPGES-1 monomers. The structural model that we have derived could serve as a useful tool for structure-guided design of inhibitors for this emergently important therapeutic target.     

Molecular docking and competitive binding study discovered different binding modes of microsomal prostaglandin E synthase-1 inhibitors

Microsomal prostaglandin E synthase-1 (mPGES-1) is a newly recognized therapeutic target for the treatment of inflammation, pain, cancer, atherosclerosis, and stroke. Many mPGES-1 inhibitors have been discovered. However, as the structure of the binding site is not well-characterized, none of these inhibitors was designed based on the mPGES-1 structure, and their inhibition mechanism remains to be fully disclosed. Recently, we built a new structural model of mPGES-1 which was well supported by experimental data. Based on this model, molecular docking and competition experiments were used to investigate the binding modes of four representive mPGES-1 inhibitors. As the inhibitor binding sites predicted by docking overlapped with both the substrate and the cofactor binding sites, mPGES-1 inhibitors might act as dual-site inhibitors. This inhibitory mechanism was further verified by inhibitor-cofactor and inhibitor-substrate competition experiments. To investigate the potency-binding site relationships of mPGES-1 inhibitors, we also carried out molecular docking studies for another series of compounds. The docking results correlated well with the different inhibitory effects observed experimentally. Our data revealed that mPGES-1 inhibitors could bind to the substrate and the cofactor binding sites simultaneously, and this dual-site binding mode improved their potency. Future rational design and optimization of mPGES-1 inhibitors can be carried out based on this binding mechanism.     

Microscopic modes and free energies of 3-phosphoinositide-dependent kinase-1 (PDK1) binding with celecoxib and other inhibitors

Celecoxib, also known as Celebrex (approved by FDA in 1998) and remembered as the fastest-selling drug in history, was used as a cyclooxygenase-2 (COX-2) selective inhibitor having both anti-inflammatory and anticancer activities. Most recent studies have revealed that the apoptotic activity of celecoxib (and its derivatives) is actually independent of the COX-2 inhibitory activity and that celecoxib also inhibits the kinase activity of 3-phosphoinositide-dependent protein kinase-1 (PDK1), suggesting that the well-known anticancer activity of celecoxib is not due to the inhibition of COX-2, but possibly is due to the inhibition of PDK1. It is highly desirable to develop new celecoxib derivatives as PDK1-specifc inhibitors to avoid the side effects of COX-2 inhibitors. To understand how PDK1 binds with celecoxib and its derivatives, we have performed extensive molecular docking and combined molecular dynamics (MD) simulations and molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations on eight representative PDK1 inhibitors, leading to the finding of a new, more favorable binding mode which is remarkably different from the previously proposed binding mode. Based on the determined most stable binding structures, the calculated binding free energies are all in good agreement with the corresponding experimental data, and the biological activity data available for celecoxib and its derivatives can be better interpreted. The obtained new insights, concerning both the binding mode and computational protocol, will be valuable not only for future rational design of novel, more potent PDK1-specific inhibitors as promising anticancer therapeutics, but also for rational design of drugs targeting other proteins.     

How can (-)-epigallocatechin gallate from green tea prevent HIV-1 infection? Mechanistic insights from computational modeling and the implication for rational design of anti-HIV-1 entry inhibitors

Possible inhibitors preventing human immunodeficiency virus type 1 (HIV-1) entry into the cells are recognized as hopeful next-generation anti-HIV-1 drugs. It is highly desirable to develop a potent inhibitor blocking binding of glycoprotein CD4 of the cell with glycoprotein gp120 of HIV-1, because the gp120-CD4 binding is the initial step of HIV-1 entry into the cells. It has been recently reported that (-)-epigallocatechin gallate (EGCG) from green tea is an inhibitor blocking gp120-CD4 binding. But the inhibitory mechanism remains unknown. For understanding the inhibitory mechanism, extensive molecular docking, molecular dynamics simulations, and binding free-energy calculations have been performed in this study to predict the most favorable structures of CD4-EGCG, gp120-CD4, and gp120-CD4-EGCG binding complexes in water. The results reveal that EGCG binds with CD4 in such a way that the calculated binding affinity of gp120 with the CD4-EGCG complex is negligible. So, the favorable binding of EGCG with CD4 can effectively block gp120-CD4 binding. The calculated CD4-EGCG binding affinity (DeltaG(bind) = -5.5 kcal/mol, K(d) = 94 microM) is in excellent agreement with available experimental data suggesting IC(50) approximately 100 microM for EGCG-blocking CD4-gp120 binding. These results and insights provide a rational basis for future design of novel, more potent inhibitors to block gp120-CD4 binding.     

Combined 3D-QSAR modeling and molecular docking study on indolinone derivatives as inhibitors of 3-phosphoinositide-dependent protein kinase-1

3-Phosphoinositide-dependent protein kinase-1 (PDK1) is a promising target for developing novel anticancer drugs. In order to understand the structure-activity correlation of indolinone-based PDK1 inhibitors, we have carried out a combined molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling study. The study has resulted in two types of satisfactory 3D-QSAR models, including the CoMFA model (r(2)=0.907; q(2)=0.737) and CoMSIA model (r(2)=0.991; q(2)=0.824), for predicting the biological activity of new compounds. The detailed microscopic structures of PDK1 binding with inhibitors have been studied by molecular docking. We have also developed docking-based 3D-QSAR models (CoMFA with q(2)=0.729; CoMSIA with q(2)=0.79). The contour maps obtained from the 3D-QSAR models in combination with the docked binding structures help to better interpret the structure-activity relationship. All of the structural insights obtained from both the 3D-QSAR contour maps and molecular docking are consistent with the available experimental activity data. This is the first report on 3D-QSAR modeling of PDK1 inhibitors. The satisfactory results strongly suggest that the developed 3D-QSAR models and the obtained PDK1-inhibitor binding structures are reasonable for the prediction of the activity of new inhibitors and in future drug design.     

Structural Insights into Pixatimod (PG545) Inhibition of Heparanase,a Key Enzyme in Cancer and Viral Infections

Pixatimod (PG545), a heparan sulfate (HS) mimetic and anticancer agent currently in clinical trials, is a potent inhibitor of heparanase. Heparanase is an endo-β-glucuronidase that degrades HS in the extracellular matrix and basement membranes and is implicated in numerous pathological processes such as cancer and viral infections, including SARS−CoV-2. To understand how PG545 interacts with heparanase, we firstly carried out a conformational analysis through a combination of NMR experiments and molecular modelling which showed that the reducing end β-D-glucose residue of PG545 adopts a distorted conformation. This was followed by docking and molecular dynamics simulations to study the interactions of PG545 with heparanase, revealing that PG545 is able to block the active site by binding in different conformations, with the cholestanol side-chain making important hydrophobic interactions. While PG545 blocks its natural substrate HS from binding to the active site, small synthetic heparanase substrates are only partially excluded, and thus pentasaccharide or larger substrates are preferred for assaying this class of inhibitor. This study provides new insights for the design of next-generation heparanase inhibitors and substrates.     

Molecular description of pyrimidine-based inhibitors with activity against FAK combining 3D-QSAR analysis,molecular docking and molecular dynamics

Focal adhesion kinase (FAK) is a promising target for developing more effective anticancer drugs. To better understand the structure-activity relationships and mechanism of actions of FAK inhibitors, a molecular modeling study using 3D-QSAR, molecular docking, molecular dynamics simulations, and binding free energy analysis were conducted. Two types of satisfactory 3D-QSAR models were generated, comprising the CoMFA model (R²_cv = 0.528, R²_pred = 0.7557) and CoMSIA model (R²_cv = 0.757, R²_pred = 0.8362), for predicting the inhibitory activities of novel inhibitors. The derived contour maps indicate structural characteristics for substituents on the template. Molecular docking, molecular dynamic simulations and binding free energy calculations further reveal that the binding of inhibitors to FAK is mainly contributed from hydrophobic, electrostatic and hydrogen bonding interactions. In addition, some key residues (Arg14, Glu88, Cys90, Arg138, Asn139, Leu141, and Leu155) responsible for ligand-receptor binding are highlighted. All structural information obtained from 3D-QSAR models and molecular dynamics is consist with the available experimental activities. All the results will facilitate the optimization of this series of FAK inhibitors with higher inhibitory activities.     

Discovery of small molecule inhibitors of ubiquitin-like poxvirus proteinase I7L using homology modeling and covalent docking approaches

Essential for viral replication and highly conserved among poxviridae, the vaccinia virus I7L ubiquitin-like proteinase (ULP) is an attractive target for development of smallpox antiviral drugs. At the same time, the I7L proteinase exemplifies several interesting challenges from the rational drug design perspective. In the absence of a published I7L X-ray structure, we have built a detailed 3D model of the I7L ligand binding site (S2-S2' pocket) based on exceptionally high structural conservation of this site in proteases of the ULP family. The accuracy and limitations of this model were assessed through comparative analysis of available X-ray structures of ULPs, as well as energy based conformational modeling. The 3D model of the I7L ligand binding site was used to perform covalent docking and VLS of a comprehensive library of about 230,000 available ketone and aldehyde compounds. Out of 456 predicted ligands, 97 inhibitors of I7L proteinase activity were confirmed in biochemical assays ( approximately 20% overall hit rate). These experimental results both validate our I7L ligand binding model and provide initial leads for rational optimization of poxvirus I7L proteinase inhibitors. Thus, fragments predicted to bind in the prime portion of the active site can be combined with fragments on non-prime side to yield compounds with improved activity and specificity.     

Molecular dynamics simulation and free energy calculation studies of the binding mechanism of allosteric inhibitors with p38α MAP kinase

p38 MAP kinase is a promising target for anti-inflammatory treatment. The classical kinase inhibitors imatinib and sorafenib as well as BI-1 and BIRB-796 were reported to bind in the DFG-out form of human p38α, known as type II or allosteric kinase inhibitors. Although DFG-out conformation has attracted great interest in the design of type II kinase inhibitors, the structural requirements for binding and mechanism of stabilization of DFG-out conformation remain unclear. As allosteric inhibition is important to the selectivity of kinase inhibitor, herein the binding modes of imatinib, sorafenib, BI-1 and BIRB-796 to p38α were investigated by molecular dynamics simulation. Binding free energies were calculated by molecular mechanics/Poisson-Boltzmann surface area method. The predicted binding affinities can give a good explanation of the activity difference of the studied inhibitors. Furthermore, binding free energies decomposition analysis and further structural analysis indicate that the dominating effect of van der Waals interaction drives the binding process, and key residues, such as Lys53, Gly71, Leu75, Ile84, Thr106, Met109, Leu167, Asp168, and Phe169, play important roles by forming hydrogen bond, salt bridge, and hydrophobic interactions with the DFG-out conformation of p38α. Finally, we also conducted a detailed analysis of BI-1, imatinib, and sorafenib binding to p38α in comparison with BIRB-796 exploited for gaining potency as well as selectivity of p38 inhibitors. These results are expected to be useful for future rational design of novel type II p38 inhibitors.     

QSAR analyses on avian influenza virus neuraminidase inhibitors using CoMFA, CoMSIA, and HQSAR

The recent wide spreading of the H5N1 avian influenza virus (AIV) in Asia, Europe and Africa and its ability to cause fatal infections in human has raised serious concerns about a pending global flu pandemic. Neuraminidase (NA) inhibitors are currently the only option for treatment or prophylaxis in humans infected with this strain. However, drugs currently on the market often meet with rapidly emerging resistant mutants and only have limited application as inadequate supply of synthetic material. To dig out helpful information for designing potent inhibitors with novel structures against the NA, we used automated docking, CoMFA, CoMSIA, and HQSAR methods to investigate the quantitative structure-activity relationship for 126 NA inhibitors (NIs) with great structural diversities and wide range of bioactivities against influenza A virus. Based on the binding conformations discovered via molecular docking into the crystal structure of NA, CoMFA and CoMSIA models were successfully built with the cross-validated q (2) of 0.813 and 0.771, respectively. HQSAR was also carried out as a complementary study in that HQSAR technique does not require 3D information of these compounds and could provide a detailed molecular fragment contribution to the inhibitory activity. These models also show clearly how steric, electrostatic, hydrophobicity, and individual fragments affect the potency of NA inhibitors. In addition, CoMFA and CoMSIA field distributions are found to be in well agreement with the structural characteristics of the corresponding binding sites. Therefore, the final 3D-QSAR models and the information of the inhibitor-enzyme interaction should be useful in developing novel potent NA inhibitors.     

Pharmacophore modelling,atom-based 3D-QSAR generation and virtual screening of molecules projected for mPGES-1 inhibitory activity

COX-2 inhibitors exhibit anticancer effects in various cancer models but due to the adverse side effects associated with these inhibitors, targeting molecules downstream of COX-2 (such as mPGES-1) has been suggested. Even after calls for mPGES-1 inhibitor design, to date there are only a few published inhibitors targeting the enzyme and displaying anticancer activity. In the present study, we have deployed both ligand and structure-based drug design approaches to hunt novel drug-like candidates as mPGES-1 inhibitors. Fifty-four compounds with tested mPGES-1 inhibitory value were used to develop a model with four pharmacophoric features. 3D-QSAR studies were undertaken to check the robustness of the model. Statistical parameters such as r² = 0.9924, q² = 0.5761 and F test = 1139.7 indicated significant predictive ability of the proposed model. Our QSAR model exhibits sites where a hydrogen bond donor, hydrophobic group and the aromatic ring can be substituted so as to enhance the efficacy of the inhibitor. Furthermore, we used our validated pharmacophore model as a three-dimensional query to screen the FDA-approved Lopac database. Finally, five compounds were selected as potent mPGES-1 inhibitors on the basis of their docking energy and pharmacokinetic properties such as ADME and Lipinski rule of five.     

Polymer-ligand interaction studies. Part I. Binding of some drugs to poly(N-vinyl-2-pyrrolidone)

A physico-chemical investigation on the binding of some nonsteroidal anti-inflammatory drugs, Naproxen (NP) and Ketoprofen (KP) and a drug model compound, salicylic acid (SA) to poly(N-vinyl-2-pyrrolidone) (PVP, molecular weight = 360,000), was performed at pH 7.1 by the fluorescence competition method employing 1-anilinonaphthalene-8-sulphonate (ANS) as the fluorescent probe. The binding affinities of these substrates to PVP are in the order KP < SA < NP which has been explained on the basis of their structural features and the consequent effect on the interacting forces. Theπ-π interaction between the carbonyl group of PVP and theπ-ring system of the substrate molecule seems to be crucial in deciding the binding affinities of the substrates     

Ligand- and protein-based modeling studies of the inhibitors of human cytochrome P450 2D6 and a virtual screening for potential inhibitors from the Chinese herbal medicine, Scutellaria baicalensis (Huangqin,Baikal Skullcap)

We have previously examined the binding patterns of various substrates to human cytochrome P450 2D6 (CYP2D6) using a series of molecular modeling methods. In this study, we further explored the binding modes of various types of inhibitors to CYP2D6 using a combination of ligand- and protein-based modeling approaches. Firstly, we developed and validated a pharmacophore model for CYP2D6 inhibitors, which consisted of two hydrophobic features and one hydrogen bond acceptor feature. Secondly, we constructed and validated a quantitative structure-activity relationship (QSAR) model for CYP2D6 inhibitors which gave a poor to moderate prediction accuracy. Thirdly, a panel of CYP2D6 inhibitors were subject to molecular docking into the active site of wild-type and mutated CYP2D6 enzyme. We demonstrated that 8 residues in the active site (Leu213, Glu216, Ser217, Gln244, Asp301, Ser304, Ala305, and Phe483) played an important role in the binding to the inhibitors via hydrogen bond formation and/or π-π stacking interaction. Apparent changes in the binding modes of the inhibitors have been observed with Phe120Ile, Glu216Asp, Asp301Glu mutations in CYP2D6. Finally, we screened for potential binders/inhibitors from the Chinese herbal medicine Scutellaria baicalensis (Huangqin, Baikal Skullcap) using the established pharmacophore model for CYP2D6 inhibitors and molecular docking approach. Overall, 18 out of 40 compounds from S. baicalensis were mapped to the pharmacophore model of CYP2D6 inhibitors and most herbal compounds from S. baicalensis could be docked into the active site of CYP2D6. Our study has provided insights into the molecular mechanisms of interaction of synthetic and herbal compounds with human CYP2D6 and further benchmarking studies are needed to validate our modeling and virtual screening results.     

Discovery of SARS-CoV-2 Mpro peptide inhibitors from modelling substrate and ligand binding

The main protease (M^pro) of SARS-CoV-2 is central to viral maturation and is a promising drug target, but little is known about structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of biomolecular simulation techniques, including automated docking, molecular dynamics (MD) and interactive MD in virtual reality, QM/MM, and linear-scaling DFT, to investigate the molecular features underlying recognition of the natural M^pro substrates. We extensively analysed the subsite interactions of modelled 11-residue cleavage site peptides, crystallographic ligands, and docked COVID Moonshot-designed covalent inhibitors. Our modelling studies reveal remarkable consistency in the hydrogen bonding patterns of the natural M^pro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular plasticity at the S2 site. Building on our initial M^pro-substrate models, we used predictive saturation variation scanning (PreSaVS) to design peptides with improved affinity. Non-denaturing mass spectrometry and other biophysical analyses confirm these new and effective ‘peptibitors’ inhibit M^pro competitively. Our combined results provide new insights and highlight opportunities for the development of M^pro inhibitors as anti-COVID-19 drugs.

The main protease (M^pro) of SARS-CoV-2 is central to viral maturation and is a promising drug target. In silico methods reveal structural aspects of how it binds to its 11 natural cleavage sites, the design of novel peptide inhibitors, and insights into drug design.     

Pharmacophore generation,atom-based 3D-QSAR and molecular dynamics simulation analyses of pyridine-3-carboxamide-6-yl-urea analogues as potential gyrase B inhibitors

DNA gyrase subunit B (GyrB) is an attractive drug target for the development of antibacterial agents with therapeutic potential. In the present study, computational studies based on pharmacophore modelling, atom-based QSAR, molecular docking, free binding energy calculation and dynamics simulation were performed on a series of pyridine-3-carboxamide-6-yl-urea derivatives. A pharmacophore model using 49 molecules revealed structural and chemical features necessary for these molecules to inhibit GyrB. The best fitted model AADDR.13 was generated with a coefficient of determination (r²) of 0.918. This model was validated using test set molecules and had a good r² of 0.78. 3D contour maps generated by the 3D atom-based QSAR revealed the key structural features responsible for the GyrB inhibitory activity. Extra precision molecular docking showed hydrogen bond interactions with key amino acid residues of ATP-binding pocket, important for inhibitor binding. Further, binding free energy was calculated by the MM-GBSA rescoring approach to validate the binding affinity. A 10 ns MD simulation of inhibitor #47 showed the stability of the predicted binding conformations. We identified 10 virtual hits by in silico high-throughput screening. A few new molecules were also designed as potent GyrB inhibitors. The information obtained from these methodologies may be helpful to design novel inhibitors of GyrB.     

Inhibition by protease inhibitors of binding of adrenal and sex steroid hormones.

Binding of steroid hormones is inhibited by protease inhibitors and substrates. The protease inhibitors phenylmethyl sulphonylfluoride, tosyl-lysine chloromethyl ketone, and tosylamide-phenylethyl-chloromethyl ketone and the protease substrates tosyl arginine methyl ester and tryptophan methyl ester eliminate specific binding of aldosterone, dexamethasone, dihydrotestosterone, estrogen, and progesterone to their respective receptors. These protease inhibitors and substrates also inhibit binding of progesterone to the 20,000 molecular weight mero-receptor formed from the progesterone receptor in chick oviduct. The binding of estradiol to rat alpha-fetoprotein is inhibited by the protease inhibitors and substrates but not by tryptophan or tryptophan amide, indicating the importance of an ester structure in the inhibition of steroid binding. Our results suggest that all steroid hormone receptors have a site with both common structural features and a role in the regulation of steroid hormone binding.