Showing papers on "Pharmacophore published in 2011"

Click Chemistry: 1,2,3‐Triazoles as Pharmacophores

Abstract: The copper(I)-catalyzed 1,2,3-triazole-forming reaction between azides and terminal alkynes has become the gold standard of 'click chemistry' due to its reliability, specificity, and biocompatibility. Applications of click chemistry are increasingly found in all aspects of drug discovery; they range from lead finding through combinatorial chemistry and target-templated in vitro chemistry, to proteomics and DNA research by using bioconjugation reactions. The triazole products are more than just passive linkers; they readily associate with biological targets, through hydrogen-bonding and dipole interactions. The present review will focus mainly on the recent literature for applications of this reaction in the field of medicinal chemistry, in particular on use of the 1,2,3-triazole moiety as pharmacophore.

Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach.

Abstract: In the absence of three-dimensional (3D) structures of potential drug targets, ligand-based drug design is one of the popular approaches for drug discovery and lead optimization. 3D structure-activity relationships (3D QSAR) and pharmacophore modeling are the most important and widely used tools in ligand-based drug design that can provide crucial insights into the nature of the interactions between drug target and ligand molecule and provide predictive models suitable for lead compound optimization. This review article will briefly discuss the features and potential application of recent advances in ligand-based drug design, with emphasis on a detailed description of a novel 3D QSAR method based on the conformationally sample pharmacophore (CSP) approach (denoted CSP-SAR). In addition, data from a published study are used to compare the CSP-SAR approach to the Catalyst method, emphasizing the utility of the CSP approach for ligand-based model development.

Cysteine mapping in conformationally distinct kinase nucleotide binding sites: application to the design of selective covalent inhibitors.

Abstract: Kinases have emerged as one of the most prolific therapeutic targets. An important criterion in the therapeutic success of inhibitors targeting the nucleotide binding pocket of kinases is the inhibitor residence time. Recently, covalent kinase inhibitors have attracted attention since they confer terminal inhibition and should thus be more effective than reversible inhibitors with transient inhibition. The most robust approach to design irreversible inhibitors is to capitalize on the nucleophilicity of a cysteine thiol group present in the target protein. Herein, we report a systematic analysis of cysteine residues present in the nucleotide binding site of kinases, which could be harnessed for irreversible inhibition, taking into consideration the different kinase conformations. We demonstrate the predictive power of this analysis with the design and validation of an irreversible inhibitor of KIT/PDGFR kinases. This is the first example of a covalent kinase inhibitor that combines a pharmacophore addressing the DFG-out conformation with a covalent trap.

The discovery of potential acetylcholinesterase inhibitors: a combination of pharmacophore modeling, virtual screening, and molecular docking studies.

Abstract: Alzheimer's disease (AD) is the most common cause of dementia characterized by progressive cognitive impairment in the elderly people. The most dramatic abnormalities are those of the cholinergic system. Acetylcholinesterase (AChE) plays a key role in the regulation of the cholinergic system, and hence, inhibition of AChE has emerged as one of the most promising strategies for the treatment of AD. In this study, we suggest a workflow for the identification and prioritization of potential compounds targeted against AChE. In order to elucidate the essential structural features for AChE, three-dimensional pharmacophore models were constructed using Discovery Studio 2.5.5 (DS 2.5.5) program based on a set of known AChE inhibitors. The best five-features pharmacophore model, which includes one hydrogen bond donor and four hydrophobic features, was generated from a training set of 62 compounds that yielded a correlation coefficient of R = 0.851 and a high prediction of fit values for a set of 26 test molecules with a correlation of R2 = 0.830. Our pharmacophore model also has a high Guner-Henry score and enrichment factor. Virtual screening performed on the NCI database obtained new inhibitors which have the potential to inhibit AChE and to protect neurons from Aβ toxicity. The hit compounds were subsequently subjected to molecular docking and evaluated by consensus scoring function, which resulted in 9 compounds with high pharmacophore fit values and predicted biological activity scores. These compounds showed interactions with important residues at the active site. The information gained from this study may assist in the discovery of potential AChE inhibitors that are highly selective for its dual binding sites.

SHAFTS: a hybrid approach for 3D molecular similarity calculation. 1. Method and assessment of virtual screening.

Abstract: We developed a novel approach called SHAFTS (SHApe-FeaTure Similarity) for 3D molecular similarity calculation and ligand-based virtual screening. SHAFTS adopts a hybrid similarity metric combined with molecular shape and colored (labeled) chemistry groups annotated by pharmacophore features for 3D similarity calculation and ranking, which is designed to integrate the strength of pharmacophore matching and volumetric overlay approaches. A feature triplet hashing method is used for fast molecular alignment poses enumeration, and the optimal superposition between the target and the query molecules can be prioritized by calculating corresponding “hybrid similarities”. SHAFTS is suitable for large-scale virtual screening with single or multiple bioactive compounds as the query “templates” regardless of whether corresponding experimentally determined conformations are available. Two public test sets (DUD and Jain’s sets) including active and decoy molecules from a panel of useful drug targets were adopted to e...

A Novel Approach for Predicting P-glycoprotein (ABCB1) Inhibition Using Molecular Interaction Fields

Abstract: P-glycoprotein (Pgp or ABCB1) is an ABC transporter protein involved in intestinal absorption, drug metabolism, and brain penetration, and its inhibition can seriously alter a drug's bioavailability and safety. In addition, inhibitors of Pgp can be used to overcome multidrug resistance. Given this dual purpose, reliable in silico procedures to predict Pgp inhibition are of great interest. A large and accurate literature collection yielded more than 1200 structures; a model was then constructed using various molecular interaction field-based technologies, considering pharmacophoric features and those physicochemical properties related to membrane partitioning. High accuracy was demonstrated internally with two different validation sets and, moreover, using a number of molecules, for which Pgp inhibition was not experimentally available but was evaluated in-house. All of the validations confirmed the robustness of the model and its suitability to help medicinal chemists in drug discovery. The information derived from the model was rationalized as a pharmacophore for competitive Pgp inhibition.

Caffeic Acid, a versatile pharmacophore: an overview.

Abstract: The caffeic acid scaffold, which is abundant in nature, is extremely versatile and is found in a number of biologically active molecules. The purpose of this review is to provide an overview of the pharmacological activity of synthetic caffeic acid analogs including recent reports of anti-inflammatory, anti-cancer, and antiviral activities of these compounds.

Integrating structure-based and ligand-based approaches for computational drug design

Abstract: Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

Identification of SAP155 as the target of GEX1A (Herboxidiene), an antitumor natural product.

Abstract: GEX1A is a microbial product with antitumor activity. HeLa cells cultured with GEX1A accumulated p27(Kip) and its C-terminally truncated form p27*. GEX1A inhibited the pre-mRNA splicing of p27, producing p27* from the unspliced mRNA containing the first intron. p27* lacked the site required for E3 ligase-mediated proteolysis of p27, leading to its accumulation in GEX1A-treated cells. The accumulated p27* was able to bind to and inhibit the cyclin E-Cdk2 complex that causes E3 ligase-mediated degradation of p27, which probably triggers the accumulation of p27. By using a series of photoaffinity-labeling derivatives of GEX1A, we found that GEX1A targeted SAP155 protein, a subunit of SF3b responsible for pre-mRNA splicing. The linker length between the GEX1A pharmacophore and the photoreactive group was critical for detection of the GEX1A-binding protein. GEX1A serves as a novel splicing inhibitor that specifically impairs the SF3b function by binding to SAP155.

Pharmer: efficient and exact pharmacophore search

Abstract: Pharmacophore search is a key component of many drug discovery efforts. Pharmer is a new computational approach to pharmacophore search that scales with the breadth and complexity of the query, not the size of the compound library being screened. Two novel methods for organizing pharmacophore data, the Pharmer KDB-tree and Bloom fingerprints, enable Pharmer to perform an exact pharmacophore search of almost two million structures in less than a minute. In general, Pharmer is more than an order of magnitude faster than existing technologies. The complete source code is available under an open-source license at http://pharmer.sourceforge.net.

Design strategies for bivalent ligands targeting GPCRs.

Abstract: Specifically designed bivalent ligands targeting G protein-coupled receptor (GPCR) dimeric structures have become increasingly popular in recent literature. The advantages of the bivalent approach are numerous, including enhanced potency and receptor subtype specificity. However, the use of bivalent ligands as potential pharmacotherapeutics is limited by problematic molecular properties, such as high molecular weight and lipophilicity. This minireview focuses on the design of bivalent ligands recently described in the literature; discussing the choice of lead pharmacophore, the position and nature of the attachment point for linking the two pharmacophore units, and the length and composition of the spacer group. Furthermore, this minireview distils the molecular descriptors of the bivalent ligands that exhibit in vivo activity, as well as highlights their ability to access the central nervous system.

Inhibitors of HCV NS5A: From Iminothiazolidinones to Symmetrical Stilbenes

Abstract: The iminothiazolidinone BMS-858 (2) was identified as a specific inhibitor of HCV replication in a genotype 1b replicon assay via a high-throughput screening campaign. A more potent analogue, BMS-824 (18), was used in resistance mapping studies, which revealed that inhibitory activity was related to disrupting the function of the HCV nonstructural protein 5A. Despite the development of coherent and interpretable SAR, it was subsequently discovered that in DMSO 18 underwent an oxidation and structural rearrangement to afford the thiohydantoin 47, a compound with reduced HCV inhibitory activity. However, HPLC bioassay fractionation studies performed after incubation of 18 in assay media led to the identification of fractions containing a dimeric species 48 that exhibited potent antiviral activity. Excision of the key elements hypothesized to be responsible for antiviral activity based on SAR observations reduced 48 to a simplified, symmetrical, pharmacophore realized most effectively with the stilbene 55, a...

A dynamic pharmacophore drives the interaction between Psalmotoxin-1 and the putative drug target acid-sensing ion channel 1a.

Abstract: Acid-sensing ion channel 1a (ASIC1a) is a primary acid sensor in the peripheral and central nervous system. It has been implicated as a novel therapeutic target for a broad range of pathophysiological conditions including pain, ischemic stroke, depression, and autoimmune diseases such as multiple sclerosis. The only known selective blocker of ASIC1a is π-TRTX-Pc1a (PcTx1), a disulfide-rich 40-residue peptide isolated from spider venom. π-TRTX-Pc1a is an effective analgesic in rodent models of acute pain and it provides neuroprotection in a mouse model of ischemic stroke. Thus, understanding the molecular basis of the π-TRTX-Pc1a-ASIC1a interaction should facilitate development of therapeutically useful ASIC1a blockers. We therefore developed an efficient bacterial expression system to produce a panel of π-TRTX-Pc1a mutants for probing structure-activity relationships as well as isotopically labeled toxin for determination of its solution structure and dynamics. We demonstrate that the toxin pharmacophore resides in a β-hairpin loop that was revealed to be mobile over a wide range of time scales using molecular dynamics simulations in combination with NMR spin relaxation and relaxation dispersion measurements. The toxin-receptor interaction was modeled by in silico docking of the toxin structure onto a homology model of rat ASIC1a in a restraints-driven approach that was designed to take account of the dynamics of the toxin pharmacophore and the consequent remodeling of side-chain conformations upon receptor binding. The resulting model reveals new insights into the mechanism of action of π-TRTX-Pc1a and provides an experimentally validated template for the rational design of therapeutically useful π-TRTX-Pc1a mimetics.

Combined Receptor and Ligand-Based Approach to the Universal Pharmacophore Model Development for Studies of Drug Blockade to the hERG1 Pore Domain

Abstract: Long QT syndrome, LQTS, results in serious cardiovasculardisorders,suchastachyarrhythmiaandsudden cardiacdeath.Apromiscuousbindingofdifferentdrugstothe intracavitary binding site in the pore domain (PD) of human ether-a-go-gorelatedgene(hERG)channelsleadstoasimilar dysfunction, known as a drug-induced LQTS. Therefore, an assessment of the blocking ability for potent drugs is of great pragmatic value for molecular pharmacology and medicinal chemistryofhERGs.Thus,weattemptedtocreateaninsilico model aimed at blinded drug screening for their blocking abilitytothehERG1PD.Twodistinctapproachestothedrug blockage, ligand-based QSAR and receptor-based molecular docking methods, are combined for development of a universal pharmacophore model, which provides rapid assessment of drug blocking ability to the hERG1 channel. The best 3D-QSAR model (AAADR.7) from PHASE modeling was selected from a pool consisting of 44 initial candidates. The constructed model using 31 hERG blockers was validated with 9 test set compounds. The resulting model correctly predicted the pIC50 values of test set compounds as true unknowns. To further evaluate the pharmacophore model, 14 hERG blockers with diverse hERG blocking potencies were selected from literature and they were usedasadditionalexternalblindtestsets.TheresultingaveragedeviationbetweeninvitroandpredictedpIC50valuesofexternaltest set blockers is found as 0.29 suggesting that the model is able to accuretely predict the pIC50 values as true unknowns. These pharmacophoremodels were mergedwith apreviouslydeveloped atomistic receptormodel for the hERG1 PD and exhibited a high consistencybetweenligand-basedandreceptor-basedmodels.Therefore,thedeveloped3D-QSARmodelprovidesapredictivetool for profiling candidate compounds before their synthesis. This model also indicated the key functional groups determining a high- affinity blockade of the hERG1 channel. To cross-validate consistency between the constructed hERG1 pore domain and the pharmacophoremodels,weperformeddockingstudiesusingthehomologymodelofhERG1.Tounderstandhowpolarornonpolar moieties of inhibitors stimulate channel inhibition, critical amino acid replacement (i.e., T623, S624, S649, Y652 and F656) at the hERG cavity was examined by in silico mutagenesis. The average docking score differences between wild type and mutated hERG channels was found to have the following order: F656A > Y652A > S624A > T623A > S649A. These results are in agreement with experimental data.

Homology Model and Docking-Based Virtual Screening for Ligands of the σ1 Receptor.

Abstract: This study presents for the first time the 3D model of the σ1 receptor protein as obtained from homology modeling techniques, shows the applicability of this structure to docking-based virtual screening, defines a computational strategy to optimize the results based on a combination of 3D pharmacophore-based docking and MM/PBSA free energy of binding scoring, and provides evidence that these in silico models and recipes are powerful tools on which virtual screening of new σ1 ligands can be based. In particular, the validation of the applicability of docking-based virtual screening to homology models is of utmost importance, since no crystal structure is available to date for the σ1 receptor, and this missing information still constitutes a major hurdle for a rational ligand design for this important protein target.

Homology modeling, docking and structure-based pharmacophore of inhibitors of DNA methyltransferase.

Abstract: DNA methyltransferase 1 (DNMT1) is an emerging epigenetic target for the treatment of cancer and other diseases. To date, several inhibitors from different structural classes have been published. In this work, we report a comprehensive molecular modeling study of 14 established DNTM1 inhibitors with a herein developed homology model of the catalytic domain of human DNTM1. The geometry of the homology model was in agreement with the proposed mechanism of DNA methylation. Docking results revealed that all inhibitors studied in this work have hydrogen bond interactions with a glutamic acid and arginine residues that play a central role in the mechanism of cytosine DNA methylation. The binding models of compounds such as curcumin and parthenolide suggest that these natural products are covalent blockers of the catalytic site. A pharmacophore model was also developed for all DNMT1 inhibitors considered in this work using the most favorable binding conformations and energetic terms of the docked poses. To the best of our knowledge, this is the first pharmacophore model proposed for compounds with inhibitory activity of DNMT1. The results presented in this work represent a conceptual advance for understanding the protein-ligand interactions and mechanism of action of DNMT1 inhibitors. The insights obtained in this work can be used for the structure-based design and virtual screening for novel inhibitors targeting DNMT1.

Docking and molecular dynamics study on the inhibitory activity of novel inhibitors on epidermal growth factor receptor (EGFR).

Abstract: EGFR is the cell-surface receptor. Its overexpression or overactivity has been associated with a number of cancers, including breast, lung, ovarian, and anal cancers. Many therapeutic approaches are aimed at the EGFR. A series of 2, 7-diamino-thiazolo [4,5-d] pyrimidine analogues are among the most highly potent and selective inhibitors of EGFR described to date. For in-depth investigation into the structural and chemical features responsible for the binding recognition mechanism concerned, as well as for exploring the binding pocket of these compounds, we performed a series of automated molecular docking operations. It was revealed that the binding site consisted of three main areas (P1, P2 and P3) composed of most of the hydrophobic amino acids able to accommodate the lipophilic arms of the compounds investigated. However, the solvent interface did not make much contribution to the binding of the inhibitors. The presence of residues Met793 and Asp855 may also be responsible for the binding recognition through H-bond interactions, with Phe856 through a T-shape π-π stacking interaction. The interaction model and pharmacophore of EGFR inhibitors were derived that can be successfully used to explain the different biologic activities of these inhibitors. Moreover, the docking results were quite robust as further validated by molecular dynamics. It is anticipated that the findings reported here may provide very useful information or clue for designing effective drugs for the therapeutic treatment of EGFR-related cancer.

Potent bace-1 inhibitor design using pharmacophore modeling, in silico screening and molecular docking studies

Abstract: Background: Beta-site amyloid precursor protein cleaving enzyme (BACE-1) is a single-membrane protein belongs to the aspartyl protease class of catabolic enzymes. This enzyme involved in the processing of the amyloid precursor protein (APP). The cleavage of APP by BACE-1 is the rate-limiting step in the amyloid cascade leading to the production of two peptide fragments Ab40 and Ab42. Among two peptide fragments Ab42 is the primary species thought to be responsible for the neurotoxicity and amyloid plaque formation that lead to memory and cognitive defects in Alzheimer’s disease (AD). AD is a ravaging neurodegenerative disorder for which no diseasemodifying treatment is currently available. Inhibition of BACE-1 is expected to stop amyloid plaque formation and emerged as an interesting and attractive therapeutic target for AD. Methods: Ligand-based computational approach was used to identify the molecular chemical features required for the inhibition of BACE-1 enzyme. A training set of 20 compounds with known experimental activity was used to generate pharmacophore hypotheses using 3D QSAR Pharmacophore Generation module available in Discovery studio. The hypothesis was validated by four different methods and the best hypothesis was utilized in database screening of four chemical databases like Maybridge, Chembridge, NCI and Asinex. The retrieved hit compounds were subjected to molecular docking study using GOLD 4.1 program. Results: Among ten generated pharmacophore hypotheses, Hypo 1 was chosen as best pharmacophore hypothesis. Hypo 1 consists of one hydrogen bond donor, one positive ionizable, one ring aromatic and two hydrophobic features with high correlation coefficient of 0.977, highest cost difference of 121.98 bits and lowest RMSD value of 0.804. Hypo 1 was validated using Fischer randomization method, test set with a correlation coefficient of 0.917, leave-one-out method and decoy set with a goodness of hit score of 0.76. The validated Hypo 1 was used as a 3D query in database screening and retrieved 773 compounds with the estimated activity value <100 nM. These hits were docked into the active site of BACE-1 and further refined based on molecular interactions with the essential amino acids and good GOLD fitness score. Conclusion: The best pharmacophore hypothesis, Hypo 1, with high predictive ability contains chemical features required for the effective inhibition of BACE-1. Using Hypo 1, we have identified two compounds with diverse chemical scaffolds as potential virtual leads which, as such or upon further optimization, can be used in the designing of new BACE-1 inhibitors.

Discovery of Novel Pim-1 Kinase Inhibitors by a Hierarchical Multistage Virtual Screening Approach Based on SVM Model, Pharmacophore, and Molecular Docking

Abstract: In this investigation, we describe the discovery of novel potent Pim-1 inhibitors by employing a proposed hierarchical multistage virtual screening (VS) approach, which is based on support vector machine-based (SVM-based VS or SB-VS), pharmacophore-based VS (PB-VS), and docking-based VS (DB-VS) methods. In this approach, the three VS methods are applied in an increasing order of complexity so that the first filter (SB-VS) is fast and simple, while successive ones (PB-VS and DB-VS) are more time-consuming but are applied only to a small subset of the entire database. Evaluation of this approach indicates that it can be used to screen a large chemical library rapidly with a high hit rate and a high enrichment factor. This approach was then applied to screen several large chemical libraries, including PubChem, Specs, and Enamine as well as an in-house database. From the final hits, 47 compounds were selected for further in vitro Pim-1 inhibitory assay, and 15 compounds show nanomolar level or low micromolar inhibition potency against Pim-1. In particular, four of them were found to have new scaffolds which have potential for the chemical development of Pim-1 inhibitors.

Mangiferin, an anti-HIV-1 agent targeting protease and effective against resistant strains.

Abstract: The anti-HIV-1 activity of mangiferin was evaluated. Mangiferin can inhibit HIV-1(Ⅲ)(B) induced syncytium formation at non-cytotoxic concentrations, with a 50% effective concentration (EC₅₀) at 16.90 μM and a therapeutic index (TI) above 140. Mangiferin also showed good activities in other laboratory-derived strains, clinically isolated strains and resistant HIV-1 strains. Mechanism studies revealed that mangiferin might inhibit the HIV-1 protease, but is still effective against HIV peptidic protease inhibitor resistant strains. A combination of docking and pharmacophore methods clarified possible binding modes of mangiferin in the HIV-1 protease. The pharmacophore model of mangiferin consists of two hydrogen bond donors and two hydrogen bond acceptors. Compared to pharmacophore features found in commercially available drugs, three pharmacophoric elements matched well and one novel pharmacophore element was observed. Moreover, molecular docking analysis demonstrated that the pharmacophoric elements play important roles in binding HIV-1 protease. Mangiferin is a novel nonpeptidic protease inhibitor with an original structure that represents an effective drug development strategy for combating drug resistance.

Docking-Based Comparative Intermolecular Contacts Analysis as New 3-D QSAR Concept for Validating Docking Studies and in Silico Screening: NMT and GP Inhibitors as Case Studies

Abstract: The significant role played by docking algorithms in drug discovery combined with their serious pitfalls prompted us to envisage a novel concept for validating docking solutions, namely, docking-based comparative intermolecular contacts analysis (dbCICA). This novel approach is based on the number and quality of contacts between docked ligands and amino acid residues within the binding pocket. It assesses a particular docking configuration on the basis of its ability to align a set of ligands within a corresponding binding pocket in such a way that potent ligands come into contact with binding site spots distinct from those approached by low-affinity ligands and vice versa. In other words, dbCICA evaluates the consistency of docking by assessing the correlation between ligands’ affinities and their contacts with binding site spots. Optimal dbCICA models can be translated into valid pharmacophore models that can be used as 3-D search queries to mine structural databases for new bioactive compounds. dbCICA ...

Pharmacophore modelling: a forty year old approach and its modern synergies.

Abstract: A pharmacophore represents a simple and intuitive concept that can be used in many different drug discovery applications. Ligand-based and structure-based pharmacophore models continue to play a pivotal role in hit discovery and may guide lead optimization. Moreover, owing to the versatility of the pharmacophore concept, pharmacophore modelling has been routinely used in combination with other molecular modelling techniques. The synergistic use of different tools in drug discovery workflows may allow to fully exploit the advantages, while compensating for some of the intrinsic limitations, of each methodology. This review will focus on the synergistic combination of pharmacophore modelling with other molecular modelling approaches such as the hot spot analysis of protein binding sites, molecular dynamics, and docking.

3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors

Abstract: 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.