Homology modeling,molecular docking and spectra assay studies of sterol 14α-demethylase from <Emphasis Type="Italic">Penicillium digitatum</Emphasis>

Sterol 14α-demethylase from Penicillium digitatum (PdCYP51) is a prime target of antifungal drugs for citrus disease in plants. To design novel antifungal compounds, a homology model of PdCYP51 was constructed using the recently reported crystal structure of human CYP51 as the template. Molecular docking was performed to investigate the interaction of four commercial fungicides with the modeled enzyme. The side chain of these compounds interplayed with PdCYP51 mainly through hydrophobic and van der Waals interactions. Biochemical spectra analysis of inhibitors combined with PdCYP51 are also compatible with the docking results. This is the first molecular modeling for PdCYP51 based on the eukaryotic crystal structure of CYP51. The structural information and binding site mapping of PdCYP51 for different inhibitors obtained from this study could aid in screening and designing new antifungal compounds targeting this enzyme.     

Discovery of a novel protein kinase B inhibitor by structure-based virtual screening

Protein kinase B (PKB/AKT) is a promising and attractive therapeutic target in anticancer drug development. Herein, we report the findings of virtual screening for novel ATP-competitive inhibitors of AKT-2 using 2D- and 3D-similarity searching and sequential molecular docking with two crystal structures of AKT-2. Our multistep approach led to the identification of a low micromolar AKT-2 inhibitor (IC₅₀ = 1.5 μM) with a novel scaffold. The experimentally validated inhibitor represents the starting point for an optimization program.     

Structure-based virtual screening against SARS-3CL(pro) to identify novel non-peptidic hits

Severe acute respiratory syndrome is a highly infectious upper respiratory tract disease caused by SARS-CoV, a previously unidentified human coronavirus. SARS-3CL(pro) is a viral cysteine protease critical to the pathogen's life cycle and hence a therapeutic target of importance. The recently elucidated crystal structures of this enzyme provide an opportunity for the discovery of inhibitors through rational drug design. In the current study, Gold docking program was utilized to conduct extensive docking studies against the target crystal structure to develop a robust and predictive docking protocol. The validated docking protocol was used to conduct a structure-based virtual screening of the Asinex Platinum collection. Biological evaluation of a screened selection of compounds was carried out to identify novel inhibitors of the viral protease.     

Dynamic and Multi-Pharmacophore Modeling for Designing Polo-Box Domain Inhibitors

The polo-like kinase 1 (Plk1) is a critical regulator of cell division that is overexpressed in many types of tumors. Thus, a strategy in the treatment of cancer has been to target the kinase activity (ATPase domain) or substrate-binding domain (Polo-box Domain, PBD) of Plk1. However, only few synthetic small molecules have been identified that target the Plk1-PBD. Here, we have applied an integrative approach that combines pharmacophore modeling, molecular docking, virtual screening, and in vitro testing to discover novel Plk1-PBD inhibitors. Nine Plk1-PBD crystal structures were used to generate structure-based hypotheses. A common pharmacophore model (Hypo1) composed of five chemical features was selected from the 9 structure-based hypotheses and used for virtual screening of a drug-like database consisting of 159,757 compounds to identify novel Plk1-PBD inhibitors. The virtual screening technique revealed 9,327 compounds with a maximum fit value of 3 or greater, which were selected and subjected to molecular docking analyses. This approach yielded 93 compounds that made good interactions with critical residues within the Plk1-PBD active site. The testing of these 93 compounds in vitro for their ability to inhibit the Plk1-PBD, showed that many of these compounds had Plk1-PBD inhibitory activity and that compound Chemistry_28272 was the most potent Plk1-PBD inhibitor. Thus Chemistry_28272 and the other top compounds are novel Plk1-PBD inhibitors and could be used for the development of cancer therapeutics.     

Structure based design of compounds from natural sources for diabetes and inflammation

Medicinal plants and marine sources are important elements of indigenous medical systems worldwide. The natural drugs from medicinal plants and marine sources have received considerable interest in treatment of diabetes and inflammation. Based on literature, alpha glucosidase, aldose reductase and PTP1B enzymes were chosen as anti-diabetes targets and PLA₂ was chosen for the anti-inflammatory target. In our study, plant and bromophenols (BPs) inhibitors were screened using High Throughput Virtual screening (HTVS) followed by Induced Fit Docking (IFD) studies were carried out against diabetes and inflammation targets. The IFD result of natural inhibitors has showed favorable docking score, glide energy and hydrogen bonds interactions with the active site residues. Some of the natural inhibitors successively satisfied all the in silico parameters among the others and seem to be potent inhibitors against diabetes and inflammation.     

IKKβ inhibitors identification part I: Homology model assisted structure based virtual screening

Control of NF-κB release through the inhibition of IKKβ has been identified as a potential target for the treatment of inflammatory and autoimmune diseases. We have employed structure based virtual screening scheme to identify lead like molecule from ChemDiv database. Homology models of IKKβ enzyme were developed based on the crystal structures of four kinases. The efficiency of the homology model has been validated at different levels. Docking of known inhibitors library revealed the possible binding mode of inhibitors. Besides, the docking sequence analyses results indicate the responsibility of Glu172 in selectivity. Structure based virtual screening of ChemDiv database has yielded 277 hits. Top scoring 75 compounds were selected and purchased for the IKKβ enzyme inhibition test. From the combined approach of virtual screening followed by biological screening, we have identified six novel compounds that can work against IKKβ, in which 1 compound had highest inhibition rate 82.09% at 10 μM and IC₅₀ 1.76 μM and 5 compounds had 25.35–48.80% inhibition.     

Virtual screening of small molecules databases for discovery of novel PARP-1 inhibitors: combination of in silico and in vitro studies

Poly(ADP-ribose) polymerase-1 (PARP-1) enzyme has critical roles in DNA replication repair and recombination. Thus, PARP-1 inhibitors play an important role in the cancer therapy. In the current study, we have performed combination of in silico and in vitro studies in order to discover novel inhibitors against PARP-1 target. Structure-based virtual screening was carried out for an available small molecules database. A total of 257,951 ligands from Otava database were screened at the binding pocket of PARP-1 using high-throughput virtual screening techniques. Filtered structures based on predicted binding energy results were then used in more sophisticated molecular docking simulations (i.e. Glide/standard precision, Glide/XP, induced fit docking – IFD, and quantum mechanics polarized ligand docking – QPLD). Potential high binding affinity compounds that are predicted by molecular simulations were then tested by in vitro methods. Computationally proposed compounds as PARP-1 inhibitors (Otava Compound Codes: 7111620047 and 7119980926) were confirmed by in vitro studies. In vitro results showed that compounds 7111620047 and 7119980926 have IC₅₀ values of 0.56 and 63 μM against PARP-1 target, respectively. The molecular mechanism analysis, free energy perturbation calculations using long multiple molecular dynamics simulations for the discovered compounds which showed high binding affinity against PARP-1 enzyme, as well as structure-based pharmacophore development (E-pharmacophore) studies were also studied.     

Discovering novel carbonic anhydrase type IX (CA IX) inhibitors from seven million compounds using virtual screening and in vitro analysis

Carbonic anhydrase type IX (CA IX) enzyme is mostly over expressed in different cancer cell lines and tumor tissues. Potent CA IX inhibitors can be effective for adjusting the pH imbalance in tumor cells. In the present work, we represented the successful application of high throughput virtual screening (HTVS) of large dataset from ZINC database included of ～7 million compounds to discover novel inhibitors of CA IX. HTVS and molecular docking were performed using consequence Glide/standard precision (SP), extra precision (XP) and induced fit docking (IFD) molecular docking protocols. For each compound, docking code calculates a set of low-energy poses and then exhaustively scans the binding pocket of the target with small compounds. Novel CA IX inhibitor candidates were suggested based on molecular modeling studies and a few of them were tested using in vitro analysis. These compounds were determined as good inhibitors against human CA IX target with K_i in the range of 0.85–1.58?μM. In order to predict the pharmaceutical properties of the selected compounds, ADME (absorption, distribution, metabolism and excretion) analysis was also carried out.     

Discovery of novel small-molecule Src kinase inhibitors via a kinase-focused druglikeness rule and structure-based virtual screening

Overexpression of the non-receptor tyrosine kinase Src is implicated in the development and progression of various human cancers. Blocking signalling pathways mediated by Src is believed to be a promising anticancer strategy. We report herein the discovery of novel small-molecule Src inhibitors by crystal structure-based virtual screening. A kinase-focused druglikeness rule was proposed and used in the design of compound library. Combination of large-scale docking with DOCK and rescoring with GOLD resulted in 6 hits with moderate to potent inhibitory activity against Src. Among them, compound 1 with an IC₅₀ of 1.2 μM shows the most potent inhibitory activity. By using molecular docking, binding models of the top 3 hits (ranked by potency and ligand efficiency) with Src were constructed to provide a rational strategy that simultaneously exploits hydrogen bonding interaction in the hinge region and hydrophobic stacking in the back pocket. This approach is instructive and meaningful to further structure-based drug design of Src inhibitors.     

Models of Ternary Complexes for Nonpeptidic Farnesyltransferase Inhibitors: Insights into Structure-Based Screen and Design of Potential Anticancer Therapeutics

Farnesyltransferase (FT) inhibitors can repress tumor cell proliferation without substantially interfering with normal cell growth and are thus promising in cancer treatment. A detailed knowledge of how substrates and inhibitors bind to FT at the atomic level can expedite screening and rational design of improved FT inhibitors. Here we report theoretical models of the FT complexed with FPP and the potent nonpeptidic inhibitor SCH 56580 and other inhibitor-FPP-FT ternary complexes derived from the docking studies prior to any crystal structures of the FT liganded with nonpeptidic inhibitors. On the basis of these models we evaluate the roles of FPP, Zn²⁺ and the zinc-coordinated water molecule in inhibitor binding, and propose the structural determinants of binding of nonpeptidic FT inhibitors. Furthermore, we suggest the use of the FPP-FT binary complex as a novel and effective drug target structure for screening and rational design of improved FT inhibitors.     

Discovery of novel inhibitors of Trypanosoma cruzi trans-sialidase from in silico screening

trans-Sialidase from Trypanosoma cruzi (TcTS) has emerged as a potential drug target for treatment of Chagas disease. Here, we report the results of virtual screening for the discovery of novel TcTS inhibitors, which targeted both the sialic acid and sialic acid acceptor sites of this enzyme. A library prepared from the Evotec database of commercially available compounds was screened using the molecular docking program GOLD, following the application of drug-likeness filters. Twenty-three compounds selected from the top-scoring ligands were purchased and assayed using a fluorimetric assay. Novel inhibitor scaffolds, with IC₅₀ values in the submillimolar range were discovered. The 3-benzothiazol-2-yl-4-phenyl-but-3-enoic acid scaffold was studied in more detail, and TcTS inhibition was confirmed by an alternative sialic acid transfer assay. Attempts to obtain crystal structures of these compounds with TcTS proved unsuccessful but provided evidence of ligand binding at the active site.     

Structural comparison of Mtb-DHFR and h-DHFR for design,synthesis and evaluation of selective non-pteridine analogues as antitubercular agents

Tuberculosis is an infectious disease that affects millions of population every year. Mtb-DHFR is a validated target that is vital for nucleic acids biosynthesis and therefore DNA formation and cell replication. This paper report identification and synthesis of novel compounds for selective inhibition of Mtb-DHFR and unleash the selective structural features necessary to inhibit the same. Virtual screening of databases was carried out to identify novel compounds on the basis of difference between the binding pockets of the two proteins. Consensus docking was performed to improve upon the results and best ten hits were selected. Hit 1 was subjected to analogues design and the analogues were docked against Mtb-DHFR. From the docking results 11 compounds were selected for synthesis and biological assay against H₃₇Rv. Most potent compound (IND-07) was tested for selectivity using enzymatic assay against Mtb-DHFR and h-DHFR. The compounds were found to have good inhibitory activity (25–200 µM) against H₃₇Rv and in enzyme assay against Mtb-DHFR and h-DHFR the compound was found selective towards Mtb-DHFR with selectivity index of 6.53. This work helped to identify indole moiety as novel scaffold for development of novel selective Mtb-DHFR inhibitors as antimycobacterial agents.     

Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Discovery of a novel azetidine scaffold for colony stimulating factor-1 receptor (CSF-1R) Type II inhibitors by the use of docking models

We report the discovery of a novel azetidine scaffold for colony stimulating factor-1 receptor (CSF-1R) Type II inhibitors by using a structure-based drug design (SBDD) based on a docking model. The work leads to the representative compound 4a with high CSF-1R inhibitory activity (IC₅₀?=?9.1?nM). The obtained crystal structure of an azetidine compound with CSF-1R, which matched our predicted docking model, demonstrates that the azetidine compounds bind to the DFG-out conformation of the protein as a Type II inhibitor.     

Multiple e-pharmacophore modelling pooled with high-throughput virtual screening,docking and molecular dynamics simulations to discover potential inhibitors of Plasmodium falciparum lactate dehydrogenase (PfLDH)

Development of new antimalarial drugs continues to be of huge importance because of the resistance of malarial parasite towards currently used drugs. Due to the reliance of parasite on glycolysis for energy generation, glycolytic enzymes have played important role as potential targets for the development of new drugs. Plasmodium falciparum lactate dehydrogenase (PfLDH) is a key enzyme for energy generation of malarial parasites and is considered to be a potential antimalarial target. Presently, there are nearly 15 crystal structures bound with inhibitors and substrate that are available in the protein data bank (PDB). In the present work, we attempted to consider multiple crystal structures with bound inhibitors showing affinity in the range of 1.4 × 10²–1.3 × 10⁶ nM efficacy and optimized the pharmacophore based on the energy involved in binding termed as e-pharmacophore mapping. A high throughput virtual screening (HTVS) combined with molecular docking, ADME predictions and molecular dynamics simulation led to the identification of 20 potential compounds which could be further developed as novel inhibitors for PfLDH.     

Discovery of non-peptide inhibitors of Plasmepsin II by structure-based virtual screening

Plasmepsin II (PM II) is an attractive target for anti-malaria drug discovery, which involves in host hemoglobin degradation in the acidic food vacuole. In this study, we demonstrated the successful use of structure-based virtual screening to identify inhibitors of PM II from two chemical database. Five novel non-peptide inhibitors were identified and revealed moderate inhibitory potencies with IC₅₀ ranged from 4.62 ± 0.39 to 9.47 ± 0.71 μM. The detailed analysis of binding modes using docking simulations for five inhibitors showed that the inhibitors could be stabilized by forming multiple hydrogen bonds with catalytic residues (Asp 34 and Asp 214) and also with other key residues.     

Chemical inhibition of fatty acid synthase: molecular docking analysis and biochemical validation in ocular cancer cells

Fatty acid biosynthesis is an attractive target for anti-cancer therapeutics. The ocular cancer, retinoblastoma cells were treated with fatty acid synthase (FASN) enzyme inhibitors: cerulenin, triclosan and orlistat. The IC₅₀ and dose-dependent sensitivity of cancer cells to FASN inhibitors decrease in biologic enzyme activity, and cell morphology alterations were analysed. Molecular interactions of enzyme-inhibitor complexes were studied by molecular modelling and docking simulations. The crystal structures of ketoacyl synthase (PDB ID:3HHD) (cerulenin) and thioesterase (PDB ID:2PX6) (orlistat) domains of human FASN were utilized for docking, while for the non-crystallised human FASN enoyl reductase domain (triclosan), homology model was built and used for docking. All three inhibitors showed significant binding energy indicating stable complex formation with their respective FASN subunits. The predicted Ki value of the FASN inhibitors corroborated well with their corresponding anti-cancer effects.     

Development of phosphocellulose paper-based screening of inhibitors of lipid kinases: Case study with PI3Kβ

The phosphatidylinositol 3-kinases (PI3Ks) are lipid kinases that regulate the cellular signal transduction pathways involved in cell growth, proliferation, survival, apoptosis, and adhesion. Deregulation of these pathways are common in oncogenesis, and they are known to be altered in other metabolic disorders as well. Despite its huge potential as an attractive target in these diseases, there is an unmet need for the development of a successful inhibitor. Unlike protein kinase inhibitors, screening for lipid kinase inhibitors has been challenging. Here we report, for the first time, the development of a radioactive lipid kinase screening platform using a phosphocellulose plate that involves transfer of radiolabeled [γ-³²P]ATP to phosphatidylinositol 4,5-phosphate forming phosphatidylinositol 3,4,5-phosphate, captured on the phosphocellulose plate. Enzyme kinetics and inhibitory properties were established in the plate format using standard inhibitors, such as LY294002, TGX-221, and wortmannin, having different potencies toward PI3K isoforms. ATP and lipid apparent K_m for both were determined and IC₅₀ values generated that matched the historical data. Here we report the use of a phosphocellulose plate for a lipid kinase assay (PI3Kβ as the target) as an excellent platform for the identification of novel chemical entities in PI3K drug discovery.     

Pharmacophore modeling,multiple docking,and molecular dynamics studies on Wee1 kinase inhibitors

Wee1-like protein kinase (Wee1) is a tyrosine kinase that regulates the G₂ checkpoint and prevents entry into mitosis in response to DNA damage. Based on a series of signaling pathways initiated by Wee1, Wee1 has been recognized as a potential target for cancer therapy. To discover potent Wee1 inhibitors with novel scaffolds, ligand-based pharmacophore model has been built based on 101 known Wee1 inhibitors. Then the best pharmacophore model, AADRRR.340, with good partial least square (PLS) statistics (R²?=?0.9212, Q²?=?0.7457), was selected and validated. The validated model was used as a three-dimensional (3D) search query for databases virtual screening. The filtered molecules were further analyzed and refined by Lipinski’s rule of 5, multiple docking procedures (high throughput virtual screening (HTVS), standard precision (SP), genetic optimization for ligand docking (GOLD), extra precision (XP), and unique quantum polarized ligand docking (QPLD)); absorption, distribution, metabolism, excretion, and toxicity (ADMET) screening; and the Prime/molecular mechanics generalized born surface area (MM-GBSA) method binding free energy calculations. Eight leads were identified as potential Wee1 inhibitors, and a 50?ns molecular dynamics (MD) simulation was carried out for top four inhibitors to predict the stability of ligand–protein complex. Molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) based on MD simulation and the energy contribution per residue to the binding energy were calculated. In the end, three hits with good stabilization and affinity to protein were identified.

Communicated by Ramaswamy H. Sarma     

Efficient molecular docking of NMR structures: application to HIV-1 protease

Docking ligands into an ensemble of NMR conformers is essential to structure-based drug discovery if only NMR structures are available for the target. However, sequentially docking ligands into each NMR conformer through standard single-receptor-structure docking, referred to as sequential docking, is computationally expensive for large-scale database screening because of the large number of NMR conformers involved. Recently, we developed an efficient ensemble docking algorithm to consider protein structural variations in ligand binding. The algorithm simultaneously docks ligands into an ensemble of protein structures and achieves comparable performance to sequential docking without significant increase in computational time over single-structure docking. Here, we applied this algorithm to docking with NMR structures. The HIV-1 protease was used for validation in terms of docking accuracy and virtual screening. Ensemble docking of the NMR structures identified 91% of the known inhibitors under the criterion of RMSD < 2.0 A for the best-scored conformation, higher than the average success rate of single docking of individual crystal structures (66%). In the virtual screening test, on average, ensemble docking of the NMR structures obtained higher enrichments than single-structure docking of the crystal structures. In contrast, docking of either the NMR minimized average structure or a single NMR conformer performed less satisfactorily on both binding mode prediction and virtual screening, indicating that a single NMR structure may not be suitable for docking calculations. The success of ensemble docking of the NMR structures suggests an efficient alternative method for standard single docking of crystal structures and for considering protein flexibility.