Pharmacophore modelling,virtual screening and molecular docking studies on PLD1 inhibitors

Lipid metabolism plays a significant role in influenza virus replication and subsequent infection. The regulatory mechanism governing lipid metabolism and viral replication is not properly understood to date, but both Phospholipase D (PLD1 and PLD2) activities are stimulated in viral infection. In vitro studies indicate that chemical inhibition of PLD1 delays viral entry and reduction of viral loads. The current study reports a three-dimensional pharmacophore model based on 35 known PLD1 inhibitors. A sub-set of 25 compounds was selected as the training set and the remaining 10 compounds were kept in the test set. One hundred and twelve pharmacophore models were generated; a six-featured pharmacophore model (AADDHR.57) with survival score (2.69) produced a statistically significant three-dimensional quantitative structure–activity relationship model with r² = 0.97 (internal training set), r² = 0.71 (internal test set) and Q² = 0.64. The predictive power of the pharmacophore model was validated with an external test set (r² = 0.73) and a systematic virtual screening work-flow was employed showing an enrichment factor of 23.68 at the top 2% of the dataset (active and decoys). Finally, the model was used for screening of the filtered PubChem database to fetch molecules which can be proposed as potential PLD1 inhibitors for blocking influenza infection.     

Virtual screening studies to design potent CDK2-cyclin A inhibitors

The cell division cycle is controlled by cyclin-dependent kinases (CDK), which consist of a catalytic subunit (CDK1-CDK8) and a regulatory subunit (cyclin A-H). Pharmacophore analysis indicates that the best inhibitor model consists of (1) two hydrogen bond acceptors, (2) one hydrogen bond donor, and (3) one hydrophobic feature. The HypoRefine pharmacophore model gave an enrichment factor of 1.31 and goodness of fit score of 0.76. Docking studies were carried out to explore the structural requirements for the CDK2-cyclin A inhibitors and to construct highly predictive models for the design of new inhibitors. Docking studies demonstrate the important role of hydrogen bond and hydrophobic interactions in determining the inhibitor-receptor binding affinity. The validated pharmacophore model is further used for retrieving the most active hits/lead from a virtual library of molecules. Subsequently, docking studies were performed on the hits, and novel series of potent leads were suggested based on the interaction energy between CDK2-cyclin A and the putative inhibitors.     

Homology model-based virtual screening for GPCR ligands using docking and target-biased scoring

The current study investigates the combination of two recently reported techniques for the improvement of homology model-based virtual screening for G-protein coupled receptor (GPCR) ligands. First, ligand-supported homology modeling was used to generate receptor models that were in agreement with mutagenesis data and structure-activity relationship information of the ligands. Second, interaction patterns from known ligands to the receptor were applied for scoring and rank ordering compounds from a virtual library using ligand-receptor interaction fingerprint-based similarity (IFS). Our approach was evaluated in retrospective virtual screening experiments for antagonists of the metabotropic glutamate receptor (mGluR) subtype 5. The results of our approach were compared to the results obtained by conventional scoring functions (Dock-Score, PMF-Score, Gold-Score, ChemScore, and FlexX-Score). The IFS lead to significantly higher enrichment rates, relative to the competing scoring functions. Though using a target-biased scoring approach, the results were not biased toward the chemical classes of the reference structures. Our results indicate that the presented approach has the potential to serve as a general setup for successful structure-based GPCR virtual screening.     

Pharmacophore modelling,molecular docking and virtual screening for EGFR (HER 1) tyrosine kinase inhibitors

A pharmacophore model has been developed using diverse classes of epidermal growth factor receptor (EGFR) tyrosine kinase (TK) inhibitors useful in the treatment of human tumours. Among the top 10 generated hypotheses, the second hypothesis, with one hydrogen bond acceptor, one ring aromatic and three hydrophobic features, was found to be the best on the basis of Cat Scramble validation as well as test set prediction (r _training?=?0.89, r _test?=?0.82). The model also maps well to the external test set molecules as well as clinically active molecules and corroborates the docking studies. Finally, 10 hits were identified as potential leads after virtual screening of ZINC database for EGFR TK inhibition. The study may facilitate the designing and discovery of novel EGFR TK inhibitors.     

Structure-based pharmacophore design and virtual screening for novel angiotensin converting enzyme 2 inhibitors

The metallopeptidase Angiotensin Converting Enzyme (ACE) is an important drug target for the treatment of hypertension, heart, kidney, and lung disease. Recently, a close and unique human ACE homologue termed ACE2 has been identified and found to be an interesting new cardiorenal disease target. With the recently resolved inhibitor-bound ACE2 crystal structure available, we have attempted a structure-based approach to identify novel potent and selective inhibitors. Computational approaches focus on pharmacophore-based virtual screening of large compound databases. Selectivity was ensured by initial screening for ACE inhibitors within an internal database and the Derwent World Drug Index, which could be reduced to zero false positives and 0.1% hit rate, respectively. An average hit reduction of 0.44% was achieved with a five feature hypothesis, searching approximately 3.8 million compounds from various commercial databases. Seventeen compounds were selected based on high fit values as well as diverse structure and subjected to experimental validation in a bioassay. We show that all compounds displayed an inhibitory effect on ACE2 activity, the six most promising candidates exhibiting IC50 values in the range of 62-179 microM.     

Multiple QSAR and molecular modelling for identification of potent human adenovirus inhibitors

This study has investigated docking-based 2D- and 3D-quantitative structure-activity relationships (QSARs) for a range of 53 hydroxybenzamide analogues as anti- Human adenoviruses (HAdVs). The best 3D-QSAR (Schrodinger, LLC, NY, 2020) and 2D-QSAR models were obtained for the training set and were found to be statistically significant, with cross-validated coefficients (q²) of 0.6775 and 0.7875, and coefficients of determination (r²) of 0.8106 and 0.8122, respectively. Our in-silico docking and virtual screening studies revealed significant higher binding affinity of dataset molecule 34 (-141.444 ​kcal/mol) and hit ZINC01088642 (-114.357 ​kcal/mol) with 4PIE protein than the standard drugs. In in-silico ADME/toxicity studies, molecule 34 and proposed hit ZINC01088642 were found safe with good intestinal absorption, aqueous solubility, medium blood–brain barrier (BBB), no eye corrosion, no skin irritancy, and non-mutagenic profiles. Molecular dynamics analysis showed good stability of complex, hit ZINC01088642 with protein, 4PIE over the simulation period of 20 ns. We believe that further experimental, as well as in-vitro investigation, will shed more lights on the identification of ZINC01088642 as a potential human adenovirus agent.     

Discovery and design of new PI3K inhibitors through pharmacophore-based virtual screening,molecular docking,and binding free energy analysis

Phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/the mammalian target of rapamycin (mTOR) signaling pathway is one of the sought after therapeutic target for treating human cancers. This pathway is often hyper activated in cancers. In the present study, pharmacophore-based virtual screening, molecular docking, and binding free energy calculations were performed on a series of quinoline derivatives which were reported to be effective against PI3Kα. A five-point pharmacophore hypothesis with one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic group (H), and two aromatic rings (R) was developed with acceptable R² and Q² values of 0.93 and 0.60 respectively. Eventually, common pharmacophore hypothesis-based screening was conducted against TOSLab, CPP, and ASINEX macrocylce databases, and potential hits were identified which were further subjected to rigorous docking process in order to screen out drug like molecules having crucial interactions with the target PI3Kα. Finally, binding free energy analysis was carried out for the top hits obtained from docking process. We also designed new 1, 3, 4-oxadiazole-based cyclic peptides by incorporating the structural features of the hits obtained from the above databases. Among the designed cyclic peptides, the cyclic peptide with tryptophan moiety showed good interactions and free binding energy values. On the whole, this study helped us in identifying new promising molecules as PI3Kα inhibitors which can be explored further to generate greater number of compounds with better pharmacokinetic properties.     

Structure-based virtual screening to identify inhibitors against Staphylococcus aureus MurD enzyme

Structural Chemistry - The MurD enzyme of Staphylococcus aureus is an attractive drug target as it is essential and ubiquitous in bacteria but absent in mammalian cells. In the present study, we...     

Identification of novel inhibitors of mitogen-activated protein kinase phosphatase-1 with structure-based virtual screening

Mitogen-activated protein kinase phosphatase-1 (MKP-1) has proved to be an attractive target for the development of therapeutics for the treatment of cancer. We report the first example for a successful application of the structure-based virtual screening to identify the novel inhibitors of MKP-1. It is shown that the efficiency of virtual screening can be enhanced significantly by the incorporation of a new solvation energy term in the scoring function. The newly found inhibitors have desirable physicochemical properties as a drug candidate and reveal a moderate potency with IC₅₀ values ranging from 20 to 50 μM. Therefore, they deserve a consideration for further development by structure–activity relationship studies to optimize the inhibitory activities. Structural features relevant to the stabilization of the inhibitors in the active site of MKP-1 are discussed in detail.     

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.     

Surveying FDA-approved drugs as new potential inhibitors of N-cadherin protein: a virtual screening approach

Since N-cadherin protein plays a remarkable role in cancer metastasis and tumor growth and progression, finding new effective inhibitors of this protein can be of high importance in cancer treatment. Nevertheless, few molecules have been introduced to inhibit N-cadherin protein to date. In this work, in order to find and present potent inhibitors, 3358 FDA-approved small molecules were docked against N-cadherin protein. All complexes with binding energy ??9 to ??8 kcal/mol were selected for protein-ligand interaction analysis. In the following, Tanimoto coefficient (T_c) was calculated for those molecules that established appropriate interactions with N-cadherin in order to compute the similarity score between them. Afterwards, molecular dynamics simulation and free energy calculations were done to estimate the stability and ability of the chosen ligands in complex with the target protein. Finally, seven small molecules among 3358 FDA-approved were suggested as potential inhibitors of N-cadherin protein.

     

Rational design of inhibitors against LpxA protein of Acinetobacter baumannii using a virtual screening method

BackgroundAcinetobacter baumannii is a highly antimicrobial resistant nosocomial pathogen. Resistance to currently used antibiotics has limited effective drugs against this bacterium. This study aimed to propose a rational inhibitor design against the LpxA protein of A. baumannii using a virtual screening method based on a similar structure of ligands.MethodsIn this study, we targeted LpxA protein, which is involved in the early stage of LPS biosynthesis. In the next step, we used Peptide920 and 1,2- Ethanediol as templates to find similar compounds using Drugbank and Zinc15 webservers, respectively. Subsequently, molecular dynamics (MD) simulations were carried out for LpxA protein and two complexes of ZINC895081 and Macrolactam-1 which represented the highest binding affinity and best conformation. Finally, ADMET properties, water solubility and drug-likeness of the desired compounds were evaluated using SwissADME and DruLiTo softwares.ResultsAccording to considered criteria, Drugbank suggested 5 compunds including Ilomastat, Macrolactam-1, Macrolactam-2, Macimorelin, and Oglufanide. On the other hand, Zinc15 webserver suggested 4 compunds including ZINC895048, ZINC895081, ZINC901061 and ZINC1531008. The result of the HDOCK server and Molegro virtual docker (MVD) showed that Macrolactam-1 and ZINC895081 (Citrate) had the highest docking score. In addition, MD simulations showed that ZINC895081 and Macrolactam-1 ligands have the stable binding to the LpxA protein. According to Lipinski's rule, these two compounds are non-carcinogenic, non-toxic and promising inhibitors against LpxA of A. baumannii.ConclusionIt seems that Macrolactam-1 and ZINC895081 (Citrate) are two valuable promising inhibitors against the LpxA protein of A. baumannii. Further in vitro and in vivo experiments are needed to confirm the capabilities of these proposed compounds against A. baumannii.     

Proteoliposome-based capillary electrophoresis for screening membrane protein inhibitors

A method for screening of monoamine oxidase (MAO) inhibitor was carried out using capillary electrophoresis (CE) based on the interaction of MAO and its substrate kynuramine (Kyn). Bioactive proteoliposome was reconstituted by liposome and MAO and then was applied as the pseudostationary phase (PSP) of CE to mimic the interaction between the enzyme and its substrate. N-prolmrgyl-R-2-heptylamine (R-2-HPA) and rasagiline [N-propargyl-1-(R)-aminoindan], which are two kinds of MAO inhibitors, were added into the running buffers containing proteoliposome. The results showed that the relative migration time ratio (RMTR × 10(-1)) values of Kyn were enhanced from 8.88 to 9.31 with an increase of the concentrations of rasagiline from 10(-6) to 1 mM. However, the RMTR values of Kyn were enhanced from 8.83 to 9.14 with an increase of the concentrations of R-2-HPA from 10(-6) to 1 mM. The RMTR value of Kyn in the presence of rasagiline was larger than that in the presence of R-2-HPA when rasagiline and R-2-HPA were at the same concentration. The results indicated that the interaction between Kyn and MAO was weakened with the increase of the inhibitors. In addition, the results of offline incubation showed that the inhibitions of rasagiline were 100.0, 72.1, 51.8 and 5.4% at the concentration of 1, 10(-2), 10(-4) and 10(-6) mM; moreover, the inhibitions of R-2-HPA were 70.0, 44.9, 4.1 and 0.9% at the concentrations of 1, 10(-2), 10(-4) and 10(-6) mM. The inhibition efficiency of rasagiline was stronger than that of R-2-HPA at the same concentration. Additionally, the interaction between Kyn and liposome was also investigated. This newly developed method might provide a potential tool for screening MAO inhibitor.