3D QSAR Pharmacophore Modeling, in Silico Screening, and Density Functional Theory (DFT) Approaches for Identification of Human Chymase Inhibitors

Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (r = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating “Hypo1”, it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high GOLD fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC50) data thus successfully validating “Hypo1” by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors

Development, evaluation and application of 3D QSAR Pharmacophore model in the discovery of potential human renin inhibitors

<p>Abstract</p> <p>Background</p> <p>Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study.</p> <p>Methods</p> <p>Ligand-based quantitative pharmacophore modeling methodology was used in identifying the important molecular chemical features present in the set of already known active compounds and the missing features from the set of inactive compounds. A training set containing 18 compounds including active and inactive compounds with a substantial degree of diversity was used in developing the pharmacophore models. A test set containing 93 compounds, Fischer randomization, and leave-one-out methods were used in the validation of the pharmacophore model. Database screening was performed using the best pharmacophore model as a 3D structural query. Molecular docking and density functional theory calculations were used to select the hit compounds with strong molecular interactions and favorable electronic features.</p> <p>Results</p> <p>The best quantitative pharmacophore model selected was made of one hydrophobic, one hydrogen bond donor, and two hydrogen bond acceptor features with high a correlation value of 0.944. Upon validation using an external test set of 93 compounds, Fischer randomization, and leave-one-out methods, this model was used in database screening to identify chemical compounds containing the identified pharmacophoric features. Molecular docking and density functional theory studies have confirmed that the identified hits possess the essential binding characteristics and electronic properties of potent inhibitors.</p> <p>Conclusion</p> <p>A quantitative pharmacophore model of predictive ability was developed with essential molecular features of a potent renin inhibitor. Using this pharmacophore model, two potential inhibitory leads were identified to be used in designing novel and future renin inhibitors as antihypertensive drugs.</p

Dynamic Structure-Based Pharmacophore Model Development: A New and Effective Addition in the Histone Deacetylase 8 (HDAC8) Inhibitor Discovery

Histone deacetylase 8 (HDAC8) is an enzyme involved in deacetylating the amino groups of terminal lysine residues, thereby repressing the transcription of various genes including tumor suppressor gene. The over expression of HDAC8 was observed in many cancers and thus inhibition of this enzyme has emerged as an efficient cancer therapeutic strategy. In an effort to facilitate the future discovery of HDAC8 inhibitors, we developed two pharmacophore models containing six and five pharmacophoric features, respectively, using the representative structures from two molecular dynamic (MD) simulations performed in Gromacs 4.0.5 package. Various analyses of trajectories obtained from MD simulations have displayed the changes upon inhibitor binding. Thus utilization of the dynamically-responded protein structures in pharmacophore development has the added advantage of considering the conformational flexibility of protein. The MD trajectories were clustered based on single-linkage method and representative structures were taken to be used in the pharmacophore model development. Active site complimenting structure-based pharmacophore models were developed using Discovery Studio 2.5 program and validated using a dataset of known HDAC8 inhibitors. Virtual screening of chemical database coupled with drug-like filter has identified drug-like hit compounds that match the pharmacophore models. Molecular docking of these hits reduced the false positives and identified two potential compounds to be used in future HDAC8 inhibitor design

Molecular Dynamics Simulation Study and Hybrid Pharmacophore Model Development in Human LTA4H Inhibitor Design

Human leukotriene A4 hydrolase (hLTA4H) is a bi-functional enzyme catalyzes the hydrolase and aminopeptidase functions upon the fatty acid and peptide substrates, respectively, utilizing the same but overlapping binding site. Particularly the hydrolase function of this enzyme catalyzes the rate-limiting step of the leukotriene (LT) cascade that converts the LTA4 to LTB4. This product is a potent pro-inflammatory activator of inflammatory responses and thus blocking this conversion provides a valuable means to design anti-inflammatory agents. Four structurally very similar chemical compounds with highly different inhibitory profile towards the hydrolase function of hLTA4H were selected from the literature. Molecular dynamics (MD) simulations of the complexes of hLTA4H with these inhibitors were performed and the results have provided valuable information explaining the reasons for the differences in their biological activities. Binding mode analysis revealed that the additional thiophene moiety of most active inhibitor helps the pyrrolidine moiety to interact the most important R563 and K565 residues. The hLTA4H complexes with the most active compound and substrate were utilized in the development of hybrid pharmacophore models. These developed pharmacophore models were used in screening chemical databases in order to identify lead candidates to design potent hLTA4H inhibitors. Final evaluation based on molecular docking and electronic parameters has identified three compounds of diverse chemical scaffolds as potential leads to be used in novel and potent hLTA4H inhibitor design

Molecular dynamics simulations of sonic hedgehog-receptor and inhibitor complexes and their applications for potential anticancer agent discovery.

The sonic hedgehog (Shh) signaling pathway is necessary for a variety of development and differentiation during embryogenesis as well as maintenance and renascence of diverse adult tissues. However, an abnormal activation of the signaling pathway is related to various cancers. In this pathway, the Shh signaling transduction is facilitated by binding of Shh to its receptor protein, Ptch. In this study, we modeled the 3D structure of functionally important key loop peptides of Ptch based on homologous proteins. Using this loop model, the molecular interactions between the structural components present in the pseudo-active site of Shh and key residues of Ptch was investigated in atomic level through molecular dynamics (MD) simulations. For the purpose of developing inhibitor candidates of the Shh signaling pathway, the Shh pseudo-active site of this interface region was selected as a target to block the direct binding between Shh and Ptch. Two different structure-based pharmacophore models were generated considering the key loop of Ptch and known inhibitor-induced conformational changes of the Shh through MD simulations. Finally two hit compounds were retrieved through a series of virtual screening combined with molecular docking simulations and we propose two hit compounds as potential inhibitory lead candidates to block the Shh signaling pathway based on their strong interactions to receptor or inhibitor induced conformations of the Shh

Final hit compounds and their pharmacophore overlay.

<p>The hit compounds depicted in stick representation. 2D chemical structures of (a) Hit 1 (BAS 13382537) and (b) Hit 2 (BAS 06350510). Mapping of (c) Hit 1 and (d) Hit 2 upon Pharm-P. Mapping of (e) Hit 1 and (f) Hit 2 upon Pharm-R.</p

Comparison of the binding of loop peptides at the pseudo-active site of Shh.

<p>(a) RMSD plots for Shh backbone during 2 ns MD simulations for following complex structures: Shh-Hhip L2 complex with all metal ions, salmon; Shh-PL2 with all metal ions, green; Shh-PL2 with no zinc ion, yellow; Shh-PL2 with no calcium ions, cyan; Shh-PL2 with no metal ions, magenta. All loop structures also painted according to the colors of RMSD plots. (b) Superimposition of final snapshots of the Shh-Hhip L2 and Shh-PL2 complexes. Electrostatic potential surface was calculated from the Shh of Shh-PL2 structure. The zinc and calcium ions are shown as bluish-gray and green spheres. (c) The PL2 forming hydrophobic residues are shown by the space-filling model. (d) Superimposition of all complex structures of the Shh-PL2 with different composition of the metal ions. Electrostatic potential surface was calculated from the Shh of Shh-PL2 structure.</p

Structural origins for the loss of catalytic activities of bifunctional human LTA4H revealed through molecular dynamics simulations.

Human leukotriene A4 hydrolase (hLTA4H), which is the final and rate-limiting enzyme of arachidonic acid pathway, converts the unstable epoxide LTA4 to a proinflammatory lipid mediator LTB4 through its hydrolase function. The LTA4H is a bi-functional enzyme that also exhibits aminopeptidase activity with a preference over arginyl tripeptides. Various mutations including E271Q, R563A, and K565A have completely or partially abolished both the functions of this enzyme. The crystal structures with these mutations have not shown any structural changes to address the loss of functions. Molecular dynamics simulations of LTA4 and tripeptide complex structures with functional mutations were performed to investigate the structural and conformation changes that scripts the observed differences in catalytic functions. The observed protein-ligand hydrogen bonds and distances between the important catalytic components have correlated well with the experimental results. This study also confirms based on the structural observation that E271 is very important for both the functions as it holds the catalytic metal ion at its location for the catalysis and it also acts as N-terminal recognition residue during peptide binding. The comparison of binding modes of substrates revealed the structural changes explaining the importance of R563 and K565 residues and the required alignment of substrate at the active site. The results of this study provide valuable information to be utilized in designing potent hLTA4H inhibitors as anti-inflammatory agents

Design of structure-based pharmacophore models.

<p>The metal ions and key residues of the representative Shh structure of (a) the Shh-PL2 (slashdot green) and (b) the Shh-robotnikinin (gold). The zinc and calcium ions are marked by blue-gray and green spheres, and the key residues are represented by stick model. Chemical features are color coded as follows: HBA, green; HBD, magenta; HYP, cyan. Selected chemical features based on the representative Shh structure generated from (c) the Shh-PL2 and (d) Shh-robotnikinin. Completed pharmacophore models of (e) the Shh-PL2 and (f) Shh-robotnikinin.</p