Pharmacophore Modeling Studies Research Articles

In silico Exploration of the Potential Inhibitory Activity of Novel Compounds Against Candida albicans N-myristoyltransferase

Background: Candida albicans is a fungal species associated with opportunistic fungal infectious agents in human populations, especially in immunocompromised patients, such as transplant patients, HIV-positive patients, chemotherapy patients, and low-birth-weight newborns. The death rate for systemic Candida illnesses ranges from 29 to 76 percent. Only a few medications are available to treat them, such as amphotericin B, fluconazole, terbinafine, and caspofungin, which have adverse reactions and are harmful. Objective: The goal of this research is to apply specialized bioinformatics approaches, such as molecular docking, scaffold hopping, virtual screening, pharmacophore modeling, and molecular dynamics (MD) simulation, to discover possibly novel and potent therapeutic drug candidates against Candida albicans in a shorter period and at a low cost. Methods: MDPI, MayBridge, Hitfinder, Mcule library, SQLite Database, DrugBank, ZINC, and NCI database were used to perform pharmacophore modeling, scaffold hopping, virtual screening, docking, and ADMET characteristics study against NMT. The molecular dynamics simulations for the best ten docked protein-ligand complexes were examined to determine the stability of protein-ligand interactions during a 200 ns simulation period, demonstrating their potential for lead molecule production via more improvement and experimental verification. Results: We have identified that compounds DB01940 ((3R,4R)-3-(4-hydroxybenzamido)azepan-4-yl 4- (2-hydroxybenzoyl)benzoate), DB01772 (3-(3-{[(2S)-2,3-dihydroxypropyl]amino}phenyl)-4-(5-fluoro-1- methyl-1H-indol-3-yl)-2,5-dihydro-1H-pyrrole-2,5-dione), and NCI5485 (1,3-bis((7-chloro-4- quinolinyl)amino)-2-propanol) could be more promising Candida albicans NMT inhibitors. Conclusion: In conclusion, these compounds have the potential to be effective anti-NMT medicines. The results demonstrated that our computational technique found some potential and effective NMT inhibitors that may be tested in clinical trials.

Unveiling the biomedical potential of thiophene‐derived Schiff base complexes: A comprehensive study of synthesis, spectral characterization, antimicrobial efficacy, antioxidant activity, and computational insights

In our pursuit of designing potent bioactive compounds, we synthesized six novel tellurium (IV) complexes through the condensation of 5‐methyl‐2‐thiophene carboxaldehyde and p‐nitroaniline. These compounds underwent rigorous investigation using various analytical techniques (TGA, SEM, EDAX, and powder XRD) and spectral analyses (NMR, mass spectrometry, UV–Vis, and FTIR). Spectroscopic analysis suggested an octahedral geometry for the complexes, revealing chelation through the thiophene sulfur and azomethine nitrogen atoms. Thermal analysis indicated a three‐step degradation process, ultimately leaving behind metal oxide as the end product. We conducted in‐vitro antimicrobial screening using the broth micro‐dilution method, highlighting the significant antimicrobial and antioxidant properties of complexes 3c and 3d, as well as the potent antimicrobial activity of 3b and 3f against various bacterial strains, including Candida albicans. To further substantiate our findings, we performed advanced computational analyses, including molecular docking, pharmacophore modeling, DFT, MESP, and ADMET studies. Molecular docking validated our antimicrobial results, whereas pharmacophore models enhanced our understanding of molecular interactions with proteins, potentially identifying novel bioactive compounds. Furthermore, DFT and MESP investigations underscored the superior biological efficacy of tellurium (IV) complexes over thiophene‐derived ligands, emphasizing their potential as therapeutic agents. ADMET analysis revealed their favorable profile as precursors for drug development with minimal adverse effects. In summary, our research seamlessly integrates experimental and theoretical aspects, offering innovative insights into drug design and potential applications in pharmaceuticals. This study represents a significant milestone, paving the way for future advancements in the field of pharmaceutical science.

Discovery of dual kinase inhibitors targeting VEGFR2 and FAK: structure-based pharmacophore modeling, virtual screening, and molecular docking studies

VEGFR2 and FAK signaling pathways are interconnected and have synergistic effects on tumor angiogenesis, growth, and metastasis. Thus, instead of the conventional targeting of each of these proteins individually with a specific inhibitor, the present work aimed to discover novel dual inhibitors targeting both VEGFR2 and FAK exploiting their association. To this end, receptor-based pharmacophore modeling technique was opted to generate 3D pharmacophore models for VEGFR2 and FAK type II kinase inhibitors. The generated pharmacophore models were validated by assessing their ability to discriminate between active and decoy compounds in a pre-compiled test set of VEGFR2 and FAK active compounds and decoys. ZINCPharmer web tool was then used to screen the ZINC database purchasable subset using the validated pharmacophore models retrieving 42,616 hits for VEGFR2 and 28,475 hits for FAK. Subsequently, they were filtered using various filters leaving 13,023 and 6,832 survived compounds for VEGFR2 and FAK, respectively, with 124 common compounds. Based on molecular docking simulations, thirteen compounds were found to satisfy all necessary interactions with VEGFR2 and FAK kinase domains. Thus, they are predicted to have a possible dual VEGFR2/FAK inhibitory activity. Finally, SwissADME web tool showed that compound ZINC09875266 is not only promising in terms of binding pattern to our target kinases, but also in terms of pharmacokinetic properties.

Design of new molecules against cervical cancer using DFT, theoretical spectroscopy, 2D/3D-QSAR, molecular docking, pharmacophore and ADMET investigations

Cervical cancer is a major health problem of women. Hormone therapy, via aromatase inhibition, has been proposed as a promising way of blocking estrogen production as well as treating the progression of estrogen-dependent cancer. To overcome the challenging complexities of costly drug design, in-silico strategy, integrating Structure-Based Drug Design (SBDD) and Ligand-Based Drug Design (LBDD), was applied to large representative databases of 39 quinazoline and thioquinazolinone compound derivatives. Quantum chemical and physicochemical descriptors have been investigated using density functional theory (DFT) and MM2 force fields, respectively, to develop 2D-QSAR models, while CoMSIA and CoMFA descriptors were used to build 3D-QSAR models. The robustness and predictive power of the reliable models were verified, via several validation methods, leading to the design of 6 new drug-candidates. Afterwards, 2 ligands were carefully selected using virtual screening methods, taking into account the applicability domain, synthetic accessibility, and Lipinski's criteria. Molecular docking and pharmacophore modelling studies were performed to examine potential interactions with aromatase (PDB ID: 3EQM). Finally, the ADMET properties were investigated in order to select potential drug-candidates against cervical cancer for experimental in vitro and in vivo testing.

Integrating computational methods guided the discovery of phytochemicals as potential Pin1 inhibitors for cancer: pharmacophore modeling, molecular docking, MM-GBSA calculations and molecular dynamics studies.

Pin1 is a pivotal player in interactions with a diverse array of phosphorylated proteins closely linked to critical processes such as carcinogenesis and tumor suppression. Its axial role in cancer initiation and progression, coupled with its overexpression and activation in various cancers render it a potential candidate for the development of targeted therapeutics. While several known Pin1 inhibitors possess favorable enzymatic profiles, their cellular efficacy often falls short. Consequently, the pursuit of novel Pin1 inhibitors has gained considerable attention in the field of medicinal chemistry. In this study, we employed the Phase tool from Schrödinger to construct a structure-based pharmacophore model. Subsequently, 449,008 natural products (NPs) from the SN3 database underwent screening to identify compounds sharing pharmacophoric features with the native ligand. This resulted in 650 compounds, which then underwent molecular docking and binding free energy calculations. Among them, SN0021307, SN0449787 and SN0079231 showed better docking scores with values of -9.891, -7.579 and -7.097kcal/mol, respectively than the reference compound (-6.064kcal/mol). Also, SN0021307, SN0449787 and SN0079231 exhibited lower free binding energies (-57.12, -49.81 and -46.05kcal/mol, respectively) than the reference ligand (-37.75kcal/mol). Based on these studies, SN0021307, SN0449787, and SN0079231 showed better binding affinity that the reference compound. Further the validation of these findings, molecular dynamics simulations confirmed the stability of the ligand-receptor complex for 100ns with RMSD ranging from 0.6 to 1.8Å. Based on these promising results, these three phytochemicals emerge as promising lead compounds warranting comprehensive biological screening in future investigations. These compounds hold great potential for further exploration regarding their efficacy and safety as Pin1 inhibitors, which could usher in new avenues for combating cancer.

Proposal of pharmacophore model for HIV reverse transcriptase inhibitors: Combined mutational effect analysis, molecular dynamics, molecular docking and pharmacophore modeling study.

Antiretroviral therapy (ART) efficacy is jeopardized by the emergence of drug resistance mutations in HIV, compromising treatment effectiveness. This study aims to propose novel analogs of Effavirenz (EFV) as potential direct inhibitors of HIV reverse transcriptase, employing computer-aided drug design methodologies. Three key approaches were applied: a mutational profile study, molecular dynamics simulations, and pharmacophore development. The impact of mutations on the stability, flexibility, function, and affinity of target proteins, especially those associated with NRTI, was assessed. Molecular dynamics analysis identified G190E as a mutation significantly altering protein properties, potentially leading to therapeutic failure. Comparative analysis revealed that among six first-line antiretroviral drugs, EFV exhibited notably low affinity with viral reverse transcriptase, further reduced by the G190E mutation. Subsequently, a search for EFV-similar inhibitors yielded 12 promising molecules based on their affinity, forming the basis for generating a pharmacophore model. Mutational analysis pinpointed G190E as a crucial mutation impacting protein properties, potentially undermining therapeutic efficacy. EFV demonstrated diminished affinity with viral reverse transcriptase, exacerbated by the G190E mutation. The search for EFV analogs identified 12 high-affinity molecules, culminating in a pharmacophore model elucidating key structural features crucial for potent inhibition. This study underscores the significance of EFV analogs as potential inhibitors of HIV reverse transcriptase. The findings highlight the impact of mutations on drug efficacy, particularly the detrimental effect of G190E. The generated pharmacophore model serves as a pivotal reference for future drug development efforts targeting HIV, providing essential structural insights for the design of potent inhibitors based on EFV analogs identified in vitro.

Discovery of dual-target natural inhibitors of meprins α and β metalloproteases for inflammation regulation: pharmacophore modelling, molecular docking, ADME prediction, and molecular dynamics studies

ABSTRACT Meprins, zinc-dependent metalloproteinases belonging to the metzincin family, have been associated with various inflammatory diseases due to their abnormal expression and activity. In this study, we utilized pharmacophore modelling to identify crucial features for discovering potential dual inhibitors targeting meprins α and β. We screened four pharmacophoric features against a library of 270,540 natural compounds from the Zinc database, resulting in 84,092 matching compounds. Molecular docking was then performed on these compounds, targeting the active sites of meprins α and β. Docking results revealed six compounds capable of interacting with both isoforms, with binding affinities ranging from −10.0 to −10.5 kcal/mol and −6.9 to −9.9 kcal/mol for meprin α and β, respectively. Among these compounds, ZINC000008790788 and ZINC000095099469 displayed superior docking scores and MM-GBSA binding free energy compared to reference ligands. Furthermore, these two compounds exhibited acceptable predicted pharmacokinetic properties and stable interactions with meprins α and β during molecular dynamics simulations. This study presents a comprehensive approach for identifying potential dual inhibitors of meprin α and β, offering insights into the development of therapeutic interventions for inflammatory diseases associated with meprin dysregulation.

Brazilin from Caesalpinia sappan L. as a Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Inhibitor: Pharmacophore-Based Virtual Screening, In Silico Molecular Docking, and In Vitro Studies.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a crucial regulator of low-density lipoprotein cholesterol (LDL-c) levels, as it binds to and degrades the LDL receptor (LDLR) in the lysosome of hepatocytes. Elevated levels of PCSK9 have been linked to an increased LDL-c plasma levels, thereby increasing the risk of cardiovascular disease (CVD), making it an attractive target for therapeutic interventions. As a way to inhibit PCSK9 action, we searched for naturally derived small molecules which can block the binding of PCSK9 to the LDLR. In this study, we carried out in silico studies which consist of virtual screening using an optimized pharmacophore model and molecular docking studies using Pyrx 0.98. Effects of the candidate compounds were evaluated using in vitro PCSK9-LDLR binding assays kit. Eleven natural compounds that bind to PCSK9 were virtually screened form HerbalDB database, including brazilin. Next, molecular docking studies using Pyrx 0.98 showed that brazilin had the highest binding affinity with PCSK9 at -9.0 (Kcal/mol), which was higher than that of the other ten compounds. Subsequent in vitro PCSK9-LDLR binding assays established that brazilin decreased the binding of PCSK9 to the EGF-A fragment of the LDLR in a dose-dependent manner, with an IC50 value of 2.19 μM. We have identified brazilin, which is derived from the Caesalpinia sappan herb, which can act as a small molecule inhibitor of PCSK9. Our findings suggest that screening for small molecules that can block the interaction between PCSK9 and the LDLR in silico and in vitro may be a promising approach for developing novel lipid-lowering therapy.

In-silicoidentification of small molecule benzofuran-1,2,3-triazole hybrids as potential inhibitors targeting EGFR in lung cancer via ligand-based pharmacophore modeling and molecular docking studies.

The online version contains supplementary material available at 10.1007/s40203-023-00157-1.

Structure-based pharmacophore modeling and DFT studies of Indian Ocean-derived red algal compounds as PI3Kα inhibitors.

Phosphoinositide kinases (PIKs) are a type of lipid kinase that acts as an upstream activator of oncogenic signaling. Presently accessible therapeutic compounds have downsides, such as toxicity and dubious efficacy, as well as lengthy treatment durations, which have bred resistance. Here we attempt to screen the Indian Ocean-derived red algal compounds to be used as a promising lead for PI3Kα inhibitor development. Experimental structure of the PI3K alpha Isoform-Specific Inhibitor alpelisib complex-based pharmacophore model was constructed and used as key to mark off the suitable lead compounds from the pool of marine-derived red algal compounds of Indian Ocean. Besides, the study encompasses pharmacophore scaffold screening as well as physicochemical and pharmacokinetic parameter assessment. We employed molecular docking and molecular dynamics simulation to assess the binding type and stability of 21 red algal derivatives. Twelve compounds demonstrated a sustained binding mode within the PI3Kα binding pocket with an optimal protein backbone root-mean-square deviation, also prompted hydrogen bonding throughout the simulations, and also implies that these MNPs have firmly mediated the interaction with prime hinge region residues in the PI3Kα ATP binding pocket. DFT studies revealed that proposed compounds had the greatest occupied molecular orbital electrophilicity index, basicity, and dipole moment, all of which attributed their stability as well as binding affinity at the PI3Kα active site. Our study's findings revealed that CMNPD31054, CMNPD4798, CMNPD27861, CMNPD4799, CMNPD27860, CMNPD9533, CMNPD3732, CMNPD4221, CMNPD31058, CMNPD31052, CMNPD29281, and CMNPD31055 can be used as lead compounds for PI3KΑ isoform inhibitors design.

Identification of Anti-Influenza A Compounds Inhibiting the Viral Non-Structural Protein 1 (NS1) Using a Type I Interferon-Driven Screening Strategy.

There is an urgent need to identify efficient antiviral compounds to combat existing and emerging RNA virus infections, particularly those related to seasonal and pandemic influenza outbreaks. While inhibitors of the influenza viral integral membrane proton channel protein (M2), neuraminidase (NA), and cap-dependent endonuclease are available, circulating influenza viruses acquire resistance over time. Thus, the need for the development of additional anti-influenza drugs with novel mechanisms of action exists. In the present study, a cell-based screening assay and a small molecule library were used to screen for activities that antagonized influenza A non-structural protein 1 (NS1), a highly conserved, multifunctional accessory protein that inhibits the type I interferon response against influenza. Two potential anti-influenza agents, compounds 157 and 164, were identified with anti-NS1 activity, resulting in the reduction of A/PR/8/34(H1N1) influenza A virus replication and the restoration of IFN-β expression in human lung epithelial A549 cells. A 3D pharmacophore modeling study of the active compounds provided a glimpse of the structural motifs that may contribute to anti-influenza virus activity. This screening approach is amenable to a broader analysis of small molecule compounds to inhibit other viral targets.

Pharmacophore-based virtual screening, molecular docking and molecular dynamics studies for the discovery of novel neuraminidase inhibitors

The in silico evaluation of 27 p-aminosalicylic acid derivatives, also referred to as neuraminidase inhibitors was the focus of the current study. To search and predict new potential neuraminidase inhibitors, this study was based on the ligand-based pharmacophore modeling, 3D QSAR, molecular docking, ADMET and MD simulation studies. The data was generated from recently reported inhibitors and divided into two groups, one of these group has 17 compounds for training and the second group has 10 compounds for testing purpose. The generated pharmacophore has known as ADDPR_4 was found statistically significant 3D-QSAR model owing the high trust scores (R2 = 0.974, Q2 = 0.905, RMSE = 0.23). Morever external validation was also employed to evaluate the prediction capacity of the built pharmacophore model (R2 pred = 0.905). In addition, in silico ADMET, analyses were employed to evaluate the obtained hits for drug likeness properties. The stability of formed complexes was further evaluated using molecular dynamics. Top two hits showed stable complexes with Neuraminidase based on calculated total binding energy by MM-PBSA. Communicated by Ramaswamy H. Sarma

Selection of potential natural compounds for poly-ADP-ribose polymerase (PARP) inhibition in glioblastoma therapy by in silico screening methods

Glioblastoma (GBM), the most prevalent brain tumor, is one of the least treatable malignancies due to its propensity for intracranial spread, high proliferative potential, and innate resistance to radiation and chemotherapy. Current GBM therapy is limited due to unfavorable, non-specific therapeutic effects in healthy cells and the difficulty of small molecules to penetrate the blood brain barrier (BBB) and reach the tumor microenvironment. Adding PARP-1 inhibitors inhibit DNA repair enzymes thereby increasing the cytotoxicity of anticancer agents. Hence, we aimed to discover potential naturally occurring PARP-1 inhibitors that can be utilized in the treatment of glioma by using multiple in silico tools like molecular docking, absorption, distribution, metabolism, and excretion (ADME) profile, pharmacophore modeling, and molecular dynamic (MD) simulations. Among 43 phytocompounds we screened, two of them (Ellagic acid and Naringin) were discovered to be bound to the catalytic site of PARP-1 with an affinity more remarkable than commercially available PARP-1 inhibitors (Talazoparib, Niraparib, and Rucaparib) except Olaparib. The molecular interactions were analyzed, and data shows that bound entity attained a conserved domain via hydrogen bond interactions, polar interactions, and π-π stacking. Pharmacophore modeling studies showed electronic and steric features of ligands responsible for supramolecular interaction with PARP-1. ADME properties were studied, to assess drug-likeness, hydrophilic nature, hydrophobicity, brain permeability, and oral bioavailability of the natural PARP-1 inhibitors. The simulation study demonstrated the development of a stable complex between Naringin, Ellagic acid, and PARP-1 protein. Moreover, cell culture studies and animal investigations are essential to determine pharmacokinetics and pharmacodynamics.

Abstract 521: Discovery of novel TNKS inhibitors through structure-based virtual screening

Abstract More than 80% of colorectal cancers (CRCs) have somatic mutations in the adenomatous polyposis coli (APC) gene, which affects abnormal WNT/β-catenin signaling. Since inhibition of tankyrases (TNKS1 and TNKS2) belonging to the poly(ADP-ribose) polymerase family stabilizes AXINs and induces degradation of β-catenin, drug development as a therapeutic target for APC-mutated CRCs is required. To identify selective small molecule inhibitors of TNKS, we performed pharmacophore modeling and structural docking studies targeting nicotinamide, adenosine, and both binding subsites of TNKS. Among the 8 million compounds, 149 of the nicotinamide site binders, 23 of the adenosine site binders, and 15 of the dual-site binders of TNKS were selected through computer-based virtual screening. Using in vitro TNKS1 and TNKS2 enzyme assays, we identified that TI2-N17 and TI3-D11 significantly inhibited TNKS1 and TNKS2 enzyme activities at low nanomolar levels. TI2-N17 and TI3-D11 stabilized AXIN2, reduced active β-catenin, and downregulated β-catenin target genes in COLO320DM, APC-mutated CRC cells. Both compounds exhibited anticancer effects on COLO320DM and SW403 cells. In addition, the combination treatment of 5-Fluorouracil (5-FU), an anticancer agent for CRC patients, and these compounds synergistically inhibited the proliferation of CRC cells compared to single compound treatment. Our findings demonstrated that TI2-N17 and TI3-D11 are therapeutic candidates targeting TNKS for APC-mutated CRCs treatment and suggested that the combined treatment with the compounds and 5-FU chemotherapy may be an effective therapeutic strategy for APC-mutated CRCs. Based on these compounds, further study will develop potent and selective TNKS inhibitors by designing and synthesizing novel derivative compounds. Citation Format: Hwani Ryu, Hye-Ran Seo, Hyo Jeong Kim, Jiyeon Ahn. Discovery of novel TNKS inhibitors through structure-based virtual screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 521.

Ligand-based pharmacophore modelling, virtual screening and docking studies to identify potential compounds against FtsZ of Mycobacterium tuberculosis

Background and introductionTuberculosis (TB) is caused by Mycobacterium tuberculosis (M.tb) which is the most common cause of death from bacterial illness. Millions of victims of TB infections have been recorded including 20,800 deaths amongst HIV positive individuals. Hence, there is a rising need for new and active compounds against M. tb protein targets especially as there is a persistent resistance to the current drug treatment regime. AimThis study identifies new potential compounds against the M. tb target protein ftsZ via pharmacophore modelling, QSAR analysis and docking studies. MethodInhibitors with known PIC50 were used as a training set and the pharmacophore features (1 aromatic center, 2 hydrophobic, 2 hydrogen bond acceptors and 1 hydrogen bond donor) were validated against four test set compounds. The identified hits were subjected to rigorous ADMET properties and docked using PyRx. DS visualizer was used in binding interactions study. Stability was measured based on the total number of interactions and preference given to the number of hydrogen bond interactions. ResultsBased on the number of interactions, hydrogen bonds, extensive virtual screening and ADMET filtration, 40 compounds have been identified as potential inhibitors of ftsZ with only 3 considered to be the best leads. Significance of researchThe identified compounds have potential of being drug candidate against Mycobacterium tuberculosis and may possess a novel mechanistic route in inhibiting the resistant strains.

Molecular docking, QSAR, pharmacophore modeling, and dynamics studies of some chromone derivatives for the discovery of anti-breast cancer agents against hormone-dependent breast cancer

In search of new anti-breast cancer agents, the present study envisaged the design and synthesis of a series of benzopyran-chalcones. All the synthesized compounds were assayed for their in-vitro anticancer activity against ER + MCF-7 and triple-negative MDA-MB-231 breast cancer cell lines using SRB assay. The synthesized compounds were found active against ER + MCF-7 cell lines. Based on the in-vitro data, in-silico analysis was performed using hormone-dependent breast cancer targets such as hER-α and aromatase because the compounds showed activity against MCF-7 cells and none was active against MDA-MB-231. The in-silico results supported the in-vitro anticancer activity suggesting the affinity of compounds toward hormone-dependant breast cancer. Compounds 4A1 to 4A3 were found to be most cytotoxic to MCF-7 cells with IC50 values of 31.87, 22.95, and 20.34 μg/ml, respectively (Doxorubicin IC50: <10 μg/ml). In addition, they showed the interactions with the amino acid residues of a binding cavity of an hER-α. Furthermore, quantitative structure-activity relationship (QSAR) studies were performed to reveal the vital structural features required for anticancer activity against breast cancer. Molecular dynamic simulation studies of hER-α and 4A3 in comparison with the raloxifene complex ensure the appropriate refinement of compounds in the dynamic system. Additionally, a generated pharmacophore model explored the essential pharmacophoric features of the synthesized scaffolds with respect to clinically used drug molecules for optimal hormone-dependant anti-breast cancer activity. Communicated by Ramaswamy H. Sarma

Discovery of potential FGFR3 inhibitors via QSAR, pharmacophore modeling, virtual screening and molecular docking studies against bladder cancer

BackgroundFibroblast growth factor receptor 3 is known as a favorable aim in vast range of cancers, particularly in bladder cancer treatment. Pharmacophore and QSAR modeling approaches are broadly utilized for developing novel compounds for the determination of inhibitory activity versus the biological target. In this study, these methods employed to identify FGFR3 potential inhibitors.MethodsTo find the potential compounds for bladder cancer targeting, ZINC and NCI databases were screened. Pharmacophore and QSAR modeling of FGFR3 inhibitors were utilized for dataset screening. Then, with regard to several factors such as Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties and Lipinski’s Rule of Five, the recognized compounds were filtered. In further step, utilizing the flexible docking technique, the obtained compounds interactions with FGFR3 were analyzed.ResultsThe best five compounds, namely ZINC09045651, ZINC08433190, ZINC00702764, ZINC00710252 and ZINC00668789 were selected for Molecular Dynamics (MD) studies. Off-targeting of screened compounds was also investigated through CDD search and molecular docking. MD outcomes confirmed docking investigations and revealed that five selected compounds could make steady interactions with the FGFR3 and might have effective inhibitory potencies on FGFR3.ConclusionThese compounds can be considered as candidates for bladder cancer therapy with improved therapeutic properties and less adverse effects.

Structure-based pharmacophore modeling, virtual screening, and molecular dynamics simulation studies for identification of Plasmodium falciparum 5-aminolevulinate synthase inhibitors.

Plasmodium falciparum (Pf) 5-aminolevulinic acid synthase (5-ALAS) is an essential enzyme with high selectivity during liver stage development, signifying its potential as a prophylactic antimalarial drug target. The aim of this study was to identify important potential lead compounds which can serve as inhibitors of Pf 5-ALAS using pharmacophore modeling, virtual screening, qualitative structural assessment, in silico ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) evaluation and molecular dynamics simulation. The best model of the tertiary structure of Pf 5-ALAS was obtained using MolProbity, while the following databases were explored for the pharmacophore-based virtual screening: CHEMBL, ChemDiv, ChemSpace, MCULE, MCULE-ULTIMATE, MolPort, NCI Open Chemical Repository, LabNetwork and ZINC databases. 2,621 compounds were screened against the modeled Pf 5-ALAS using AutoDock vina. The post-screening analysis was carried out using Discovery Studio while molecular dynamics simulation was performed on the best hits using NAMD-VMD and Galaxy Europe platform. Compound CSMS00081585868 was observed as the best hit with a binding affinity of -9.9 kcal/mol and predicted Ki of 52.10 nM, engaging in seven hydrogen bonds with the target's active site amino acid residues. The in silico ADMET prediction showed that all ten best hits possessed relatively good pharmacokinetic properties. The qualitative structural assessment of the best hit, CSMS00081585868, revealed that the presence of two pyridine scaffolds bearing hydroxy and fluorine groups linked by a pyrrolidine scaffold contributed significantly to its ability to have a strong binding affinity with the receptor. The best hit also showed stability in the active site of Pf 5-ALAS as confirmed from the RMSD obtained during the MD simulation.

Targeting Leishmania donovani sterol methyltransferase for leads using pharmacophore modeling and computational molecular mechanics studies

The mortalities and morbidities of leishmaniasis are high and the disease is under reported globally. The absence of vaccines coupled with chemotherapeutic challenges including chemoresistance, scarcity and toxicity have made the fight against leishmaniasis an arduous one. Furthermore, the treatment options currently available for leishmaniasis are long and sometimes require hospitalization. There is therefore the need to explore novel pathways to identify new compounds with alternative mechanisms of action. A pharmacophore-based screening was employed in identifying new potential inhibitors with unique scaffolds targeting Leishmania donovani sterol methyltransferase (LdSMT), a key enzyme for ergosterol biosynthesis. To accomplish this, 22,26-azasterol, a known inhibitor of this target and five other derivatives with IC50 less than 10 μM were used to generate a robust 3D pharmacophore model via LigandScout with a score of 0.9144. The validated model was used as a query to screen a library of 69034 natural products obtained from the InterBioScreen Limited. Compounds with pharmacophore fit scores above 50 were docked against the modelled structure of LdSMT. Altogether, ten molecules with binding energies between −7 and −11 kcal/mol were identified as potential bioactive molecules. The molecular dynamics simulation and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) calculations reinforced the results from the docking studies suggesting the selected hits bind effectively at the active sites of the target protein. The compounds were observed to bind in the S-adenosine-L-homocysteine binding pocket of the modelled LdSMT with Trp208 and Val330 predicted as key residues critical for ligand binding. Prediction of biological activity with probability of activity (Pa) greater than probability of inactivity (Pi) revealed that seven compounds (STOCKIN-54848, STOCKIN-89115, STOCKIN-68720, STOCKIN-44724, STOCKIN-76694, STOCKIN-47277 and STOCKIN-95708) possessed antileishmanial properties. STOCKIN-89115, STOCKIN-68720, STOCKIN-44724, and STOCKIN-47277 were predicted to be membrane permeability inhibitors, while all ten hit compounds possessed antineoplastic activity. The compounds have the propensity of disrupting ergosterol biosynthesis leading to the suppression of growth in Leishmania donovani. The compounds were predicted to have good absorption, distribution, metabolism, excretion and toxicity profiles, hence their potential antileishmanial activity can be exploited upon experimental corroboration.

Pharmacophore modeling, molecular docking, and molecular dynamics studies to identify new 5-HT2AR antagonists with the potential for design of new atypical antipsychotics.

Some important atypical antipsychotic drugs target the serotonergic receptor 2A (5-HT2AR). Currently, new therapeutic strategies are needed to offer faster onset of action with fewer side effects and, therefore, greater efficacy in a substantial proportion of patients with neuropsychological disorders such as Autism and Parkinson. The main objective of this work was to use SBDD methods to identify new hit compounds potentially useful as precursors of novel and selective 5-HT2AR antagonists. A structure-based pharmacophore screening study based on a selective antagonist was carried out in ten databases. The set obtained was refined using molecular docking, and the five most promising compounds were subjected to molecular dynamics simulations. The most stable and promising hit occupied a side pocket present in the 5-HT2AR, a site that can be explored to obtain selective ligands. Simulations against 5-HT2CR and D2R showed that the best hit could not form stable complexes with these targets, strengthening the hypothesis that the hit presents selective binding by the receptor of interest. The selected hits showed some predicted toxicity risk or violated some drug-likeness property. However, it can be concluded that the identified hits are the most promising for performing in vitro assays. Once the presence of activity is confirmed, they could become precursors of optimized and selective antagonists of 5-HT2AR. An SBDD study was carried out to identify new selective 5-HT2AR ligands potentially useful for designing selective atypical antipsychotics.