Lipinski Filter Research Articles

3D-QSAR and virtual screening studies in identification of new Rho kinase inhibitors with different scaffolds

Among the most well-known members of the serine/threonine (Ser/Thr) protein kinase family are Rho kinases. They are potential targets to treat some diseases, such as cancer, cardiovascular diseases and multiple sclerosis, because of their key roles in the organization of the actin cytoskeleton. In this study, 3D-QSAR (quantitative structure–activity relationship) techniques using popular CoMFA and CoMSIA tools as well as recently developed automated grid potential analysis (AutoGPA) based on pharmacophore alignment were applied on 41 urea-based derivatives as Rho kinase inhibitors, which were split into 32 and 9 compounds as train and test sets using Kennard and Stone algorithm. The statistical parameters of AutoGPA-based 3D-QSAR model were q 2 = 0.506, $$R_{\text{pred}}^{ 2}$$ = 0.844, $$R_{\text{m}}^{2}$$ = 0.806 which show its acceptable prediction reliability. The verified model was further utilized to search novel hits from ZINC database in virtual screening task. The obtained compounds were subjected to Lipinski filter, then their activities were predicted by AutoGPA model and docked with CDOCKER algorithm to discover potent hits. In silico ADME and toxicity risk assessment analyses were carried out on the seven hits with highest CDOCKER scores. Six out of the seven hits have diverse structures and are reported as new scaffold candidates for design of new Rho kinase inhibitors.

Screening and Toxicity Analysis of Catechin Isomers Against FemA Protein.

Fem proteins are the essential structural proteins of various gram-positive bacteria. These are of three different types namely FemX (FmhB), FemA and FemB. Only two Fem protein crystallographic structures are available till date, one for FemA in Staphylococcus aureus and another for FemX in Weissella viridescensis. In this study, computational methods are used to evaluate interaction of FemA protein with catechin and epicatechin analogues. The interaction of FemA protein with catechin and epicatechin analogues are confirmed by binding energy and scores given by Autodock Vina and UCSF Dock docking softwares, which is followed by Lipinski filters and toxicity studies using online Lipinski server of SCFBIO and OSIRIS. Catechin gallate has been found as the best ligand for FemA protein in all aspects and it has outperformed all catechin and epicatechin isomers.

Pharmacophore modeling, 3DQSAR, and docking-based design of polysubstituted quinolines derivatives as inhibitors of phosphodiesterase 4, and preliminary evaluation of their anti-asthmatic potential

3D QSAR models using 3D pharmacophore, CoMFA, and CoMSIA approaches were developed for a series of quinoline derivatives as PDE4 receptor antagonists. Hypogen method was used to engender the 3D pharmacophore model. The top scoring four feature pharmacophore models, Hypo1 contains one hydrogen-bond acceptor, two hydrogen-bond donors, and a hydrophobic feature. Hypo1 was validated using test set, Fischer’s randomization test, and screening of decoy set. CoMFA and CoMSIA models were developed using the alignment obtained by pharmacophore (Hypo1), substructure alignment, and by application of region focusing. Substructure alignment followed by region focusing provided the best CoMFA and CoMSIA models. Based on the results of 3D QSAR studies, some new molecules were designed and evaluated by Docking and Lipinski filters. The designed molecules were synthesized and two top scoring molecules were subjected to preliminary evaluation of their efficacy in treatment of asthma and COPD. The molecules demonstrated efficacy comparable to standard drugs in treatment of asthma and COPD.

In vivo and in silico pharmacological studies on some new 4-(1,3,4-thiadiazol-2-yl)benzene-1,3-diol analogues.

4-(1,3,4-Thiadiazol-2-yl)benzene-1,3-diols 5-substituted in the heterocyclic ring were obtained by the reaction of the commercially available hydrazides or thiosemicarbazides with sulfinylbis[(2,4-dihydroxyphenyl)methanethione]. The synthesized compounds were screened for their influence on CNS in the vivo model. Computer aided prediction tools were used for the evaluation of toxicological properties. Additionally, based on the Lipinski filters, the drug-likeness of compounds was assessed. They revealed that the compounds possess properties which can suggest favorable pharmacokinetics in the body after oral admission.

Identifying the Structural Features of Pyrazolo[4,3-c]Quinoline-3-ones as Inhibitors of Phosphodiesterase 4: An Exploratory CoMFA and CoMSIA Study

Phosphodiesterases (PDEs) are responsible for the hydrolysis of cyclic nucleotides (cAMP and c-GMP). Cyclic nucleotides are important intracellular secondary messengers in cell function, relaying the signals from hormones at specific cell-surface receptors. An increase of cAMP due to the stimulation of adenylyl cyclase or the inhibition of PDEs affects the activity of immune system and inflammatory cells. Thus, PDE4, a cAMP specific PDE, received much attention as a target for the treatment of the diseases like asthma and Chronic Obstructive Pulmonary Disease (COPD). Pyrazolo[4,3-c]quinoline-3-one nucleus has attracted considerable attention recently as PDE4 receptor antagonists which have shown remarkable therapeutic potential in the treatment of asthma and Chronic Obstructive Pulmonary Disease (COPD). In the present study, three dimensional quantitative structure activity relationship (3D QSAR) approach using CoMFA and CoMSIA was applied to a series of 2, 5-dihydropyrazolo [4, 3-c] quinoline-3-ones as PDE4 receptor antagonists. For the purpose, 22 compounds from the series were used to develop and validate models. The robustness of the model was confirmed with the help of leave one out cross-validation method, while the predictive ability of models was tested using a test set containing three molecules. Novel compounds were designed on the basis of results of CoMFA and CoMSIA studies. Designed compounds were evaluated by Docking and Lipinski filters. 3D-QSAR models with high squared correlation coefficient of up to 0.9590 for CoMFA and 0.9740 for CoMSIA were established. Robustness of the models is demonstrated by R2 cv values of up to 0.8600 and 0.8230 for CoMFA and CoMSIA, respectively. Predictive ability of the models is reflected by R2 pred values of 0.865 and 0.926 for CoMFA and CoMSIA respectively. Predicted activity of the designed molecules correlated well with the docking scores and the molecules also passed the Lipinski filters. Developed models highlighted the importance of steric, electrostatic and hydrophobic properties of the molecules for PDE 4 receptor affinity. The designed compounds may serve as lead for the development of newer PDE4 inhibitors based on the 2, 5-dihydropyrazolo [4, 3-c] quinoline-3-one scaffold.

Shape and pharmacophore-based virtual screening to identify potential cytochrome P450 sterol 14α-demethylase inhibitors

Sterol 14α-demethylase (CYP51) is a cytochrome P450 heme thiolate containing enzyme involved in biosynthesis of membrane sterols, including sterol in animals, ergosterol in fungi, and a variety of C24-modified sterols in plants and protozoa. Several clinical drugs have been developed to reduce the impact of fungal diseases, but their clinical uses have been limited by the emergence of drug resistance and insufficiencies in their antifungal activity. Therefore, in order to identify potential CYP51 inhibitors, we have implemented a virtual screening (VS) protocol by using both phase shape and pharmacophore model (AHHRR) against Asinex, ChemBridge and Maybridge databases. A filtering protocol, including Lipinski filter, number of rotatable bonds and different precisions of molecular docking was applied in hits selection. The results indicated that both shape-based and pharmacophore-based screening yielded the best result with potential inhibitors. The searched compounds were also evaluated with ADME properties, which show excellent pharmacokinetic properties under the acceptable range. We identified potential CYP51 inhibitors for further investigation, they could also be employed to design ligands with enhanced inhibitory potencies and to predict the potencies of analogs to guide synthesis/or prepare synthetic antifungal analogs against CYP51.

In silico investigations on HSP90 and its inhibition for the therapeutic prevention of breast cancer

BackgroundMolecular chaperones are proteins that are responsible for an appropriate folding, function and stability of client proteins. Out of these, heat shock protein 90 (Hsp90) has recently emerged as a focus of interest for its role in regulating proteins such as ERBB2, C-RAF, CDK2, AKT steroid hormone receptors, mutant p53, HIF-1α which are associated with malignant transformation. AimPresent investigations cover trials to identify more effective HSP90 inhibitors after obtaining multichaperone complex of HSP90 as an outcome of protein–protein docking. We have included biological events taking place sequentially in computational frame to evaluate binding of proposed inhibitors. MethodWe have extensively used homology modeling using MODELLER, structure preparation and validation to obtain HSP90 with full sequence length. Hydrophobic patches recognition, protein–protein docking and protein–ligand docking were then used to investigate better HSP90 inhibition. ResultsResults include generation of multichaperone complex by docking Hsp90 to its partner chaperone Hsp70 and co chaperones like Aha1 and Hsp40 which gave a favorable complex with docking energy of −711 kcal/mol. The result suggests that Hsp90 in association with its partner chaperone (Hsp70) and co chaperones (Hsp40 and Aha1) forms stable multichaperone complex which favors strong interactions with mutant p53 (Docking energy = −1103.9 kcal/mol) as compared to wild type p53 (Docking energy = −894.6 kcal/mol). Protein–ligand docking revealed EGCG as the most potent inhibitor with formation of 14 Hydrogen-bonds with the key residues of Hsp90 and RMSD value 0.09. ConclusionBased on the protein–ligand docking results and drug-likeness of various molecules (Lipinski's filter criteria) selected for studying their inhibitory action over Hsp90, we found that 17-DMAG can be used into further investigations as a therapeutic molecule for breast cancer.

Synthesis and biological evaluation of 1,3,4-thiadiazole analogues as novel AChE and BuChE inhibitors

In this paper a series of new 1,3,4-thiadiazole derivatives has been designed, synthesized and evaluated as the acetyl- and butyrylcholinesterase inhibitors. Some analogues showed promising inhibition of both enzymes in vitro in the nM range. Generally, inhibitory potency of compounds was stronger against AChE than BuChE, and one of them was 1154-fold more active inhibiting AChE (IC50 = 0.17 μM) than BuChE. The kinetic studies showed that one of the most active analogues 8 (IC50 = 0.09 μM, AChE) acted as a non-competitive AChE inhibitor and was characterized by the high selectivity index (300). The other derivative (1) exhibited a mixed-type of AChE inhibition. Docking simulations enabled the detection of key binding interactions of the compounds with AChE and revealed that they occupied mainly the catalytic active site. The scoring function for the novel compounds was similar or higher than for the reference inhibitor. Additionally, based on Lipinski and other filters, the drug-likeness of compounds was assessed. They revealed that the compounds possess properties which can suggest the favourable pharmacokinetics in the human body after oral admission.

3D QSAR Pharmacophore, CoMFA and CoMSIA Based Design and Docking Studies on Phenyl Alkyl Ketones as Inhibitors of Phosphodiesterase 4

In the present study, three dimensional quantitative structure activity relationship (3D QSAR) models using 3D Pharmacophore, CoMFA and CoMSIA approaches were developed for a series of phenyl alkyl ketone derivatives as PDE4 receptor antagonists. An ideal 3D QSAR pharmacophore model was developed and validated using external test set, Fischer's randomization method and decoy set screening. The top scoring four feature pharmacophore model, Hypo1, includes two hydrogen bond acceptors, two hydrophobic features. Amongst the developed models, Hypo1 has the maximum correlation coefficient (0.9658), cost difference (349.593), low RMS (1.41), and high goodness of fit. CoMFA and CoMSIA models were developed based on the alignment obtained using the pharmacophore (Hypo1), substructure alignment and by application of region focusing. The robustness of CoMFA and CoMSIA model was confirmed with the help of leave one out cross-validation method, while the predictive ability of models was tested using a test set. 3D-QSAR models with high squared correlation coefficient of up to 0.9720 for CoMFA and 0.9610 for CoMSIA were established. Robustness of the models is demonstrated by R(2)(cv) values of up to 0.7582 and 0.8539 for CoMFA and CoMSIA, respectively. Predictive ability of the models is reflected by R(2)(pred) values of 0.9630 and 0.9470 for CoMFA and CoMSIA respectively. Novel molecules were designed on the basis of results of 3D QSAR studies. Designed molecules were evaluated by Docking and Lipinski filters. Predicted activity of the designed molecules correlated well with the docking scores and the molecules also passed the Lipinski filters.

Identification of small molecule inhibitor of cyclophilin-A using high throughput virtual screening and molecular docking Studies

The inhibitors of cyclophilin A (CyPA) have drawn a great deal of attention due to their promising potential as small-molecule therapeutics for the treatment of cardiovascular diseases. This ultimately prompts to explore structural geometries of these inhibitors to obtain insights on next generation CyPA inhibitors through rational drug designing. Herein, 2D similarity search for the seven CyPA inhibitors was performed using Ligand.Info database. Small subsets of 2800 molecules from one million compounds were predicted to have activity against cardiovascular drug target CyPA. The binding strength of 2800 ligands with CyPA was assessed through molecular docking analysis using Schrodinger software 2011. The CyPA co-crystal structure and ligand dataset were preprocessed using protein preparation wizard and LigPrep, respectively. Lipinski filter and reactive filter evaluations were applied to 10,351 tautomeric states of 2800 ligands to achieve conformations with good pharmacological properties. Further, systematic Glide HTVS, SP and XP docking had resulted 151 ligands with good binding affinities towards CyPA. Ten best ranked compounds having good correlation with seven published CyPA inhibitors were proposed as potential leads. These ten leads had the advantage of good drug like properties compared to experimentally validated inhibitors. Lead1 (SQ29548) showed XP GScore of -12.11 Kcal/mol and two hydrogen bonds with Asp102 of CyPA which is in well agreement with crystallographic data of ‘CyPA - Sanglifehrin A’ complex. SQ29548 is already used as an antagonist for human recombinant thromboxane receptor which supports ten proposed potential inhibitors identified through virtual screening approach as a starting point for new generation drug designing to combat cardiovascular associated diseases.

Identification and Characterization of Novel Small-Molecule Inhibitors against Hepatitis Delta Virus Replication by Using Docking Strategies

The small delta antigen protein of hepatitis delta virus (HDV) has been shown to be important for replication of the virus and essential for the viral life cycle. Therefore, it may be an appropriate target for designing biological experiments for drug development to identify the potential inhibitors of hepatitis D. To identify a novel molecule as possible drug candidate for the treatment of Hepatitis D. In the present study, a computational approach was used for the identification of novel small-molecule inhibitors against HDV replication using docking studies. An Autodock tool was used for docking and identifying the active binding sites in target proteins. The Lipinski filter and preADMET program were also used for determining the pharmacokinetic properties in order to filter out potential ligand molecules to restrain virus replication. Our results suggest that pyridinone (3-[(4,7-dichloro-1,3-benzoxazol-2-yl) methylamino]-5-ethyl-6-methyl-pyridin-2(1H)-one) is a validated potential inhibitor of HDV replication and could be as a novel antiviral drug for the treatment of hepatitis D. COUNCLUSIONS: We have identified a novel antiviral drug by using innovative computational approaches. The results provide a basis to experimentally develop into drug which can be used for the treatment of delta hepatitis.