New Co(II), Ni(II) and Cu(II) complexes were prepared from thiophene derivative and then characterized to elucidate their chemical formulae. IR-spectral data suggested a monobasic tridentate binding ...mode for the ligand towards the metal ions within mono-nuclear complexes. Ligand filed transitions as well as magnetic susceptibility, orient strongly for square-planer geometry with Ni(II) and Cu(II) complexes, while octahedral geometry for Co(II) complex. Mass spectroscopy and TGA were performed for complexes to assess on their molecular formulae and the molecular ion peak is attributing to dehydrating complex (M+-nH2O). TEM, EDX and XRD were carried out to indicate morphology, crystallinity and chemical composition of tested complexes. The crystal data estimated, reflect nanometer sizes of studied complexes. DFT method was utilized to obtain optimized structures under 6-31G and LANL2DZ basis sets. Hirshfeld surface properties were estimated for 3D crystal models of complexes, to put view about the contact strength within crystal packing. 2D-fingerprint plots for elemental contribution, clarify the effective contribution of O and H atoms in surface contact between crystals. Cu (II) complex showed greatest potent cytotoxic profile against MCF-7, HepG2 and PC-3 carcinoma cell lines, by IC50s 2.2, 2.6 and 2.1 μg, respectively. High killing rate for tumor cells was observed with an early apoptotic pathway under treatment with all compounds. Also, Cu(II) complex stimulates necrosis killing effect on prostate (PC-3) and breast (MCF-7) cancer cells. Ligand-based pharmacophore methodology, was performed to indicate the most suitable contact sites in compounds towards 1z8l & 3rcd proteins. The search hits several compounds reach 3,732,214 hits and a closer 3D-fingerprint drug model was obtained. MOE docking was performed for most compounds to explain all interaction features through such simulation process. Best docking scores were recorded with HL-3rcd, Co(II)complex-1z8l, Co(II) complex-3rcd and Cu(II) complex-3rcd by values of −60,628, −6.1447, −6.055 and −6.0626, respectively. Amino acid residues that contributing in allosteric binding were clearly categorized. Finally in-silico approach confirms the superiority of Co(II)-L, Cu(II)-L and free thiophene derivative in controlling human cancer cells, which agree with in vitro results.
Apoptosis of tested ligand and its complexes against three selected tumor cell-lines. Display omitted
•Synthesis for new nonmetric thiophene complexes, analytical and spectral characterization techniques were implemented.•Crustal surface properties as well as molecular modeling features were estimated.•Antitumor activity screening as well as the apoptosis behavior towards three human cancer cells, were investigated.•In-silico approaches were utilized to confirm and simulate antitumor efficiency.
Computer-aided drug discovery techniques reduce the time and the costs needed to develop novel drugs. Their relevance becomes more and more evident with the needs due to health emergencies as well as ...to the diffusion of personalized medicine. Pharmacophore approaches represent one of the most interesting tools developed, by defining the molecular functional features needed for the binding of a molecule to a given receptor, and then directing the virtual screening of large collections of compounds for the selection of optimal candidates. Computational tools to create the pharmacophore model and to perform virtual screening are available and generated successful studies. This article describes the procedure of pharmacophore modelling followed by virtual screening, the most used software, possible limitations of the approach, and some applications reported in the literature.
In the era of druggable genome, the assessment of the numerous molecular targets represents remarkable therapeutic opportunities in the pharmaceutical and chemical biology, simultaneously ...understanding the properties required for the small molecules to emerge as good drug candidate. Incorporation of readily amenable biological properties and pharmaceutical modulation is the core key for the small molecule driven target studies in cancer related disease, especially in the case of inhibitory type mechanisms. Among huge protein targets, CK2 which is a protein serine/threonine kinase, also called the “Predominant monitor” of the cell plays comprehensive role in the various cellular machinery pertaining to cell growth and cell death. Due to its ubiquitous nature and its activity to block its activity by small molecules resulting in favorably targeting prostate cancer, CK2 was identified to be the distinct element of our study. In this study, we invested rapid computational techniques to uncover the new CK2 inhibitors with promising pharmaceutical traits and advantages when matched with existing drugs. Initially, pharmacophore modeling and atom-based 3Dimensional-Quantitative structure activity relationship of 45 known CK2 inhibitors resulted in over few hundred hypotheses. The most excellent five point pharmacophore model (AAHHR) with two hydrogen bond acceptor (A), two hydrophobic groups (H), and one aromatic ring (R) was built. 3D-QSAR studies of the finest model yielded correlation co-efficient, R2 (0.9728) and Q2 (0.7965) for training and test set compounds respectively. Our effort of externally validating the generated QSAR model was quite momentous and encouraging with rm2 = 0.682, rcv2 = 0.779, k = 1.027 and r02 = 0.817 values points out the profoundness in predicting preeminence of model. The robust model was further employed as 3D query for virtual screening against ZINC database. The lead molecules were selected based on the fitness score, and then the lead molecules subsequently taken to molecular docking studies using Glide. Finally we identified six potential lead molecules were further subjected into ADME properties prediction by engaging Qikprop module. The ADME properties of six lead molecules ZINC15955420, Zinc13412605, Zinc40763681, Zinc40763677, Zinc26178676 and Zinc01536721 are under satisfactory range with desired ADME properties. On the whole, we believe our design of the new CK2 inhibitor serves as the approachable end resultant hits the can be researched further for clinical trials evaluation in prostate cancer and emphasize on choosing CK2 as the target that holds true protential for the genesis and proliferation of anti-CK2 agents to address prostate cancer therapeutics.
•Different pharmacophore hypothesis were generated for CK2 inhibitors.•A five point Pharmacophore with two hydrogen bond acceptors two hydrophobic groups and one aromatic ring as pharmacophore features has been generated.•An atom-based 3D-qsar has been carried out with better statistical values.•Molecular docking of six novel compounds and co-crystal ligand with CK2.•ADME properties of six potential compound was analyzed.
Pharmacophore modeling, molecular docking, and in silico ADME studies have been carried out to determine the binding mode and drug likeliness profile of acyl 1,3,4-thiadiazole amides and sulfonamides ...as antitubulin agents. A four point pharmacophore model (AAHR.11) was generated using 63 compounds with IC50 values ranging from 3.16 to 505.76μM. A statistically significant 3D-QSAR model was generated from the pharmacophore hypothesis. The model had a high correlation coefficient (R2=0.8925), cross validation coefficient (Q2=0.8204) and F value (44.3) at 6 component PLS factor. The results of external validation indicated that the generated QSAR model possessed a high predictive power (R2=0.83). The generated model also passed Tropsha’s test for predictive ability and Y-Randomisation test. The Domain of Applicability (APD) of the model was also successfully defined to ascertain that a given estimation can be considered reliable. Further, the restrictivity of the model was checked with inactive compounds by enrichment studies using the decoy test. In order to evaluate the effectiveness of the docking protocol, co-crystallized ligand was extracted from the ligand binding domain of the protein and was re-docked into the same position. The conformer obtained on re-docking and the co-crystallized ligand were superimposed and the RMSD between the two was found to be 0.853Å. ADME predictions were also performed for these compounds. Outcomes of the present study have been first utilized to get insight into the molecular feature that promotes bioactivity, and then within screening procedure, have been exploited for the estimation of novel potential antitubulin compounds prior to their synthesis and biological tests.
•Indicaxanthin is a bioactive betalain extracted from Opuntia ficus indica fruits.•Indicaxanthin provides a broad-spectrum of pharmaceutical activity.•Reverse screening of Indicaxanthin identified ...potential targets.•MD simulations and ∆Gbind calculation showed behavior of drug-target complexes.•Indicaxanthin could act as neuromodulator, anti-inflammatory, and anticancer agent.
Indicaxanthin is a bioactive and bioavailable betalain pigment extracted from Opuntia ficus indica fruits. Indicaxanthin has pharmacokinetic proprieties, rarely found in other phytochemicals, and it has been demonstrated that it provides a broad-spectrum of pharmaceutical activity, exerting anti-proliferative, anti-inflammatory, and neuromodulator effects. The discovery of the Indicaxanthin physiological targets plays an important role in understanding the biochemical mechanism. In this study, combined reverse pharmacophore mapping, reverse docking, and text-based database search identified Inositol Trisphosphate 3-Kinase (ITP3K-A), Glutamate carboxypeptidase II (GCPII), Leukotriene-A4 hydrolase (LTA4H), Phosphoserine phosphatase (HPSP), Phosphodiesterase 4D (PDE4D), AMPA receptor (GluA3 and GluA2 subunits) and Kainate receptor (GluK1 isoform) as potential targets for Indicaxanthin. These targets are implicated in neuromodulation, and inflammatory regulation, normally expressed mostly in the CNS, and expressed (or overexpressed) in cancer tissues (i.e. breast, thyroid, and prostate cancer cells). Moreover, this study provides qualitative and quantitative information about dynamic interactions of Indicaxanthin at the binding site of target proteins, through molecular dynamics simulations and MM-GBSA.
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Interleukin-1β (IL1β) is a keynote mediator of inflammation with diverse physiological functions, playing a fundamental role in memory and mood regulation. The pleiotropic effects of IL-1β have been ...proposed to be implicated in the pathogenesis and etiology of depression. Thus, targeting IL-1β offers an inimitable opportunity to develop new strategies for an alternative therapy to treat depression. The focus of this study is to find out the potential inhibitors against IL-1β. Since, there is no oral specific drug reported yet thus, demanding an urgent need to develop new immunomodulatory drugs to combat chronic diseases. In this study, ligand-based pharmacophore modeling integrated with virtual screening and molecular docking strategy was designed to identify novel compounds capable of inhibiting the interactions towards cognitive receptor IL-1RI. In this connection, a set of 30,000 compounds were screened by a developed pharmacophore model that led to the retrieval of 2043 molecules from the in-house library and ZINC Database. Primarily, specific binding regions for IL-1β inhibitors have been explored by blind docking studies. After the selection of the binding site, the hits identified as actives based on the 3D-pharmacophore model were assessed by molecular docking studies. In a stepwise screening, six potential virtual hits were shortlisted for molecular dynamic simulation to acquire insights into their dynamic behavior. The obtained results highlighted that these compounds are stabilized in the targeted pocket of IL-1β and possibly block the formation of an active heterocomplex, subsequently locking the associated signaling cascade. Further in vitro experiments confirmed the inhibitory potential of Compound-157 and compound-283 with the IC50 of 1.6 ± 0.1 and 9.1 ± 1.7 µg/mL respectively.
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•The study encompasses of Ligand-Based pharmacophore modelling, docking simulation and mechanistic analysis.•Interfacial key residues were identified to design IL-1β/IL-1RI potential inhibitors.•The mechanistic results highlighted that shortlisted six virtual hits are stabilized in the targeted pocket of IL-1β and possibly block the formation of active heterocomplex.•IL-1β inhibitors are found in good agreement withexperimental studies.
Molecular dynamics simulations of twelve protein—ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the ...initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding PDB pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in the traditional approach, as well as features which disappeared rapidly during the molecular dynamics simulations and which may well be artifacts of the initial PDB structure-derived pharmacophore model. Our approach helps mitigate the sensitivity of structure based pharmacophore models to the single set of coordinates present in the experimental structure. Further, the frequency with which specific features occur during the MD simulation may aid in ranking the importance of individual features.
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•Pharmacophore feature types display varying stability in MD simulations.•Features obtained from the crystal structure are on average stable.•Some features obtained from the crystal structure appear less than 10%.•Frequency information from MD simulations can be used to add/remove features.
A new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide and become pandemic with thousands new deaths and infected cases globally. To treat the patients with ...coronavirus disease (COVID-19), currently no effective drug or vaccine is available. This necessity motivated us to explore potential lead compounds based natural products targeting main protease (M
pro
) enzyme of SARS-CoV-2. The M
pro
enzyme plays a key role in mediating viral replication and transcription and thus being considered as an attractive drug target. Herein, comprehensive computational investigations were performed to identify new lead compounds against main protease enzyme. In this study, the candidate anthocyanin-derived compounds from PubChem database were filtered considering antiviral characteristics of anthocyanins. The structure-based pharmacophore modeling was developed based on the co-crystallized structure of the enzyme with its biological active inhibitor. The generated hypotheses were applied for virtual screening-based PHASE Screen Score. Docking based virtual screening work flow was used to generate hit compounds using HTVS, SP and XP based Glide Gscore. The obtained hit compounds were filtered using ADMET pharmacological and physicochemical properties screening. Molecular dynamics simulations were performed to explore the binding affinities of the considered compounds. Our study identified six best anthocyanin-derived natural compounds which could be used as promising lead compounds against main protease SARS-CoV-2 virus.
Communicated by Ramaswamy H. Sarma
•Four abietane-type diterpenoids were isolated and identified from roots of Salvia hydrangea.•Antileishmanial activity of purified compounds was tested against the promastigotes of leishmania ...major.•The cytotoxicity of the plant's root extract was assessed against two human cancer cell lines, MCF-7 and MOLT-4.•A pharmacophore modeling study for antileishmanial activity was carried out.
Four abietane diterpenoids, agastanol, (1), 6, 7-dehydroroyleanone (2), 7α-acetoxyroyleanone (3), and ferruginol (4) were isolated from root extract of Salvia hydrangea. The chemical structures of compounds were identified using EI-MS, ESI-MS, 1D, and 2D NMR spectroscopic analyses. Antileishmanial activity of 1–4 was tested against the promastigotes of Leishmania major using in vitro antiparasitic activity assay. Compound 4 (IC50 = 12.1 ± 2.1 µg/mL) showed considerable antileishmanial activity. The root extract showed significant cytotoxicity against two cancer cell lines including, MCF-7 (IC50 = 7.0 ± 2.0 µg/mL), and, MOLT-4 (IC50 = 2.8 ± 0.7 µg/mL) using the MTT bioassay. A pharmacophore modeling study for antileishmanial activity was carried out to render essential features for an effective inhibition. The model has 7 features, including 1 hydrogen bond acceptor, 1 aromatic, and 5 hydrophobic features. In conclusion, the roots of S. hydrangea are presented as the potential source for further investigation of antileishmanial and cytotoxic compounds.
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This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of ...traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as
or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.
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