Pharmacophore-based Virtual Screening Research Articles

Identification of potent anti-immunogenic agents through virtual screening, 3D-QSAR studies, and in vitro experiments.

A wealth of literature has highlighted the discovery of various immune modulators, frequently used in clinical practice, yet associated with numerous drawbacks. In light of this pharmacological deficiency, medical scientists are motivated to develop new immune modulators with minimized adverse effects yet retaining the improved therapeutic potential. T-cell differentiation and growth are central to human defense and are regulated by interleukin-2 (IL-2), an immune-modulatory cytokine. However, scientific investigation is hindered due to its flat binding site and widespread hotspot residues. In this regard, a prompt and logical investigation guided by integrated computational techniques was undertaken to unravel new and potential leads against IL-2. In particular, the combination of score-based and pharmacophore-based virtual screening approaches were employed, reducing the data from millions of small molecules to a manageable number. Subsequent docking and 3D-QSAR prediction via CoMFA further helped remove false positives from the data. The reliability of the model was assessed via standard metrics, which explain the model's fitness and the robustness of the model in predicting the activity of new compounds. The extensive virtual screening herein led to the identification of a total of 24 leads with potential anti-IL-2 activity. Furthermore, the theoretical findings were corroborated with in vitro testing, further endorsing the anti-inflammatory potential of the identified leads.

Pharmacophore based virtual screening for identification of effective inhibitors to combat HPV 16 E6 driven cervical cancer

Targeting HPV16 E6 has emerged as an effective drug target for the treatment/management of cervical cancer. We utilized pharmacophore-based virtual screening, molecular docking, absorption, distribution, metabolism and excretion (ADME) prediction, and molecular dynamics simulation approach for identifying potential inhibitors of HPV16 E6. Initially, we generated a ligand-based pharmacophore model based on the features of four known HPV16 E6 inhibitors (CA24, CA25, CA26, and CA27) via the PHASE module implanted in the Schrödinger suite. We constructed four-point pharmacophore features viz., three hydrogen bond acceptors (A) and one aromatic ring (R). The common pharmacophore feature further employed as a query for virtual screening against the ASINEX database via Schrödinger suite. The pharmacophore-based virtual screening filtered out top 2000 hits, based on the fitness score. We then applied the high throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP). 1000 compounds were obtained from HTVS docking. Based on the glide score, they were further filtered to 500 hits by employing docking in standard precision mode. Finally, the best four hits and a negative molecule were identified using docking in XP mode. The four lead compounds and a negative molecule were then further subjected to ADME profile prediction by engaging Qikprop module. The ADME properties of the four lead molecules indicate good pharmacokinetic (PK) properties rather than the negative molecule. The binding stability of the HPV16 E6-hit complexes were investigated at a different time scale (100 ns) by using the desmond package and the results were examined using Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) and it revealed the stability of the protein-ligand complex throughout the simulation. Key residues, CYS 51 and GLN 107, also play a crucial role in enhancing the stability of the protein-ligand complex during the simulation. Furthermore, the binding free energy of the HPV16 E6-leads complexes was analyzed by prime which revealed that the ΔGbind coulomb and ΔGbind vdW interactions are crucially contributes to the binding affinity. In order to validate the computational findings, the efficacy of benzoimidazole and benzotriazole were ascertained for regulating ME180 cervical cancer cell survival, migration and ability to release MMP-2.

A comprehensive protein interaction map and druggability investigation prioritized dengue virus NS1 protein as promising therapeutic candidate.

Dengue Virus (DENV) is a serious threat to human life worldwide and is one of the most dangerous vector-borne diseases, causing thousands of deaths annually. We constructed a comprehensive PPI map of DENV with its host Homo sapiens and performed various bioinformatics analyses. We found 1195 interactions between 858 human and 10 DENV proteins. Pathway enrichment analysis was performed on the two sets of gene products, and the top 5 human proteins with the maximum number of interactions with dengue viral proteins revealed noticeable results. The non-structural protein NS1 in DENV had the maximum number of interactions with the host protein, followed by NS5 and NS3. Among the human proteins, HBA1 and UBE2I were associated with 7 viral proteins, and 3 human proteins (CSNK2A1, RRP12, and HSP90AB1) were found to interact with 6 viral proteins. Pharmacophore-based virtual screening of millions of compounds in the public databases was performed to identify potential DENV-NS1 inhibitors. The lead compounds were selected based on RMSD values, docking scores, and strong binding affinities. The top ten hit compounds were subjected to ADME profiling which identified compounds C2 (MolPort-044-180-163) and C6 (MolPort-001-742-737) as lead inhibitors against DENV-NS1. Molecular dynamics trajectory analysis and intermolecular interactions between NS1 and the ligands displayed the molecular stability of the complexes in the cellular environment. The in-silico approaches used in this study could pave the way for the development of potential specie-specific drugs and help in eliminating deadly viral infections. Therefore, experimental and clinical assays are required to validate the results of this study.

Discovery of raffinose sulfate as a potential SARS CoV-2 inhibitor via blocking its binding with angiotensin converting enzyme 2

The present study aimed to characterize the possible binding sites on the SARS CoV-2 RBD-ACE2 complex and to highlight sulfated oligosaccharides as potential anti-SARS CoV-2 via inducing RBD-ACE2 complex destabilization and dissociation. By combining pharmacophore-based and structural-based virtual screening approaches we were able to discover raffinose sulfate (RS) as a potential antiviral sulfated oligosaccharide against two SARS CoV-2 variants (i.e., wild type and Omicron) (IC50 = 4.45 ± 0.28 μM and 4.65 ± 0.32 μM, respectively). Upon MD simulation, RS was able to establish stable binding at the RBD-ACE2 interface inducing a rapid dissociation. Accordingly, and by using bio-layer interferometry (BLI) assays, RS was able to significantly weaken the affinity between RBD (of both variants) and ACE2. Additionally, we found that RS has a poor cellular permeability indicating that its interaction with the RBD-ACE2 complex may be the main mechanism by which it mediates its antiviral activity against SARS CoV-2. Despite its proposed interaction with the RBD-ACE2 complex, RS did not show any inhibitory activity against ACE2 catalytic activity. In light of these findings, the RS scaffold can be further developed into a novel anti-SARS CoV-2 drug with improved activity and tolerability in comparison with other sulfated polysaccharides e.g., heparin and heparan.

Discovery of a new Daboia russelli viper venom PLA2 inhibitor using virtual screening of pharmacophoric features of co-crystallized compound

Snake venom PLA2, a member of the group of hydrolase enzymes, has been recognized as a promising drug target for snake envenomation. In the present study, an attempt was made to identify potential inhibitors of snake venom PLA2 by employing a pharmacophore-based virtual screening, docking, and dynamics approach. A receptor-based pharmacophore model was generated based on the features of the established and bound co-crystal ligand (2-carbamoylmethyl-5-propyl-octahydro-indol-7-yl)-acetic acid in the PLA2 complex. The best pharmacophore model (ADDH) derived, consisted of four features, namely one hydrogen bond acceptor, two hydrogen bond donors, and one hydrophobic region. This common pharmacophore was then used to perform virtual screening against a drug-like diverse database, with due consideration to the Lipinski ‘rule of five’, so as to obtain a pool of lead molecules. The short-listed lead molecules were then subjected to docking analysis with that of the Daboia russelli viper venom PLA2 followed by a molecular simulation study for a duration of 100 ns. CAP04815700 was chosen as the best compound based on the simulation parameters, which were then taken for MM/PBSA calculation, and it was revealed that it has a similar effective inhibitory potential as that of the crystal ligand. Further, the cluster analysis also revealed the structural significance of the backbone protein after the interaction with CAP04815700. This study will continue to explore its bioactivity in vitro and in vivo. Communicated by Ramaswamy H. Sarma

Computer-Aided Identification of Kinase-Targeted Small Molecules for Cancer: A Review on AKT Protein.

AKT (also known as PKB) is a serine/threonine kinase that plays a pivotal regulatory role in the PI3K/AKT/mTOR signaling pathway. Dysregulation of AKT activity, especially its hyperactivation, is closely associated with the development of various human cancers and resistance to chemotherapy. Over the years, a wide array of AKT inhibitors has been discovered through experimental and computational approaches. In this regard, herein we present a comprehensive overview of AKT inhibitors identified using computer-assisted drug design methodologies (including docking-based and pharmacophore-based virtual screening, machine learning, and quantitative structure-activity relationships) and successfully validated small molecules endowed with anticancer activity. Thus, this review provides valuable insights to support scientists focused on AKT inhibition for cancer treatment and suggests untapped directions for future computer-aided drug discovery efforts.

Effects of Computer Virtual Screening and Treatment Based on Pharmacophore BRD4-Targeted Small-Molecule Inhibitors on NSE and CA19-9 Levels in Patients with Liver Cancer

Objective: Neuron-specific enolase (NSE) and carbohydrate antigen 19-9 (CA19-9) levels were compared before and after treatment with brd4-targeting small-molecule inhibitors based on pharmacophores and computer technology to investigate an efficient virtual screening method for bromodomain protein 4 (brd4)-targeted small-molecule inhibitors. The purpose of this research was to examine the efficacy of pharmacophore screening and BRD4 targeting by small-molecule inhibitors in the management of liver cancer. Methods: Subjects included 106 individuals with hepatocellular cancer who were hospitalised between July 2019 and December 2021. Using a receiver operating characteristic (ROC) curve, we assessed the clinical relevance and utility of pharmacophore-based virtual screening for brd4-targeted small-molecule inhibitors. The levels of the tumour markers NSE and CA19-9 were analysed for changes using computational methods. Results: The pharmacophore model was built using the HipHop technique, and its results were validated and optimised utilising computational technology analysis. Twenty-four small-molecule classes were covered by the pharmacophore, and the number of mismatched pharmacodynamic characteristics was 0. The first eight pharmacophores each had two clusters of hydrophobic atoms, a hydrogen bond receptor, and an aromatic ring at its core. There were no changes to the pharmacodynamic characteristics, although their locations varied. False-positive and true-positive rates are depicted on the horizontal and vertical axes, respectively, in the figure below; the other two pharmacophore groups contained a hydrophobic cluster, a hydrogen bond receptor, and the centre of an aromatic ring. The ROC curve was quite consistent, as indicated by an AUC value close to 1, which was between 0 and 1. For pharmacophores 07 and 06, the area under the curve (AUC) was 0.949 and 0.955, respectively, very near to 1. Both the hydrophobic cluster and the hydrogen bond receptor are required for a pharmacophore to exist. The examination of pharmacodynamic definitions revealed a positive correlation between database reliability and element type (P <0.05). Compared to pre-healing levels, post-healing CA19-9 and NSE levels were statistically considerably reduced (P < 0.05). Conclusions: The assessment approach was highly accurate and specific, and the pharmacophore-based virtual screening method and computer technology for brd4-targeting small-molecule inhibitors were of great benefit in the regulation of the cell cycle and the process of cell proliferation. Effective treatment modalities can be created to increase levels of tumour markers NSE and CA19-9, and pharmacophore and computational-based small-molecule inhibitors of brd4 can be employed as crucial virtual screening criteria for the evaluation of liver cancer.

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

N-alkylamides from Litsea cubeba (Lour.) Pers. with potential anti-inflammatory activity

Six amides, including a new N-alkylamide (1), four known N-alkylamides (2–5) and one nicotinamide (6) were isolated from Litsea cubeba (Lour.) Pers., which is a pioneer herb traditionally utilized in medicine. Their structures were elucidated on the basis of 1D and 2D NMR experiments and by comparison of their spectroscopic and physical data with the literature values. Cubebamide (1) is a new cinnamoyltyraminealkylamide and possessed obvious anti-inflammatory activity against NO production with IC50 values of 18.45 μM. Further in-depth pharmacophore-based virtual screening and molecular docking were carried out to reveal the binding mode of the active compound inside the 5-LOX enzyme. The results indicate that L. cubeba, and the isolated amides might be useful in the development of lead compounds for the prevention of inflammatory diseases.

Novel scaffolds targeting Mycobacterium tuberculosis plasma membrane Ca2+ transporter CtpF by structure-based strategy

CtpF is a Ca2+ transporter P-type ATPase key to the response to stress conditions and to Mycobacterium tuberculosis virulence, therefore, an interesting target for the design of novel anti-Mtb compounds. In this work, molecular dynamics simulations of four previously identified CtpF inhibitors allowed recognizing the key protein–ligand (P-L) interactions, which were then used to perform a pharmacophore-based virtual screening (PBVS) of 22 million compounds from ZINCPharmer. The top-rated compounds were then subjected to molecular docking, and their scores were refined by MM-GBSA calculations. In vitro assays showed that ZINC04030361 (Compound 7) was the best promising candidate, showing a MIC of 25.0 μg/mL, inhibition of Ca2+-ATPase activity (IC50) of 3.3 μM, cytotoxic activity of 27.2 %, and hemolysis of red blood cells lower than 0.2 %. Interestingly, the ctpF gene is upregulated in the presence of compound 7, compared to other alkali/alkaline P-type ATPases coding genes, strongly suggesting that CtpF is a compound 7-specific target.

Pharmacophore-Based Virtual Screening and In-Silico Explorations of Biomolecules (Curcumin Derivatives) of Curcuma longa as Potential Lead Inhibitors of ERBB and VEGFR-2 for the Treatment of Colorectal Cancer.

The newly FDA-approved drug, Axitinib, is an effective therapy against RTKs, but it possesses severe adverse effects like hypertension, stomatitis, and dose-dependent toxicity. In order to ameliorate Axitinib's downsides, the current study is expedited to search for energetically stable and optimized pharmacophore features of 14 curcumin (1,7-bis(4-hydroxy-3-methoxyphenyl)hepta-1,6-diene-3,5-dione) derivatives. The rationale behind the selection of curcumin derivatives is their reported anti-angiogenic and anti-cancer properties. Furthermore, they possessed a low molecular weight and a low toxicity profile. In the current investigation, the pharmacophore model-based drug design, facilitates the filtering of curcumin derivatives as VEGFR2 interfacial inhibitors. Initially, the Axitinib scaffold was used to build a pharmacophore query model against which curcumin derivatives were screened. Then, top hits from pharmacophore virtual screening were subjected to in-depth computational studies such as molecular docking, density functional theory (DFT) studies, molecular dynamics (MD) simulations, and ADMET property prediction. The findings of the current investigation revealed the substantial chemical reactivity of the compounds. Specifically, compounds S8, S11, and S14 produced potential molecular interactions against all four selected protein kinases. Docking scores of -41.48 and -29.88 kJ/mol for compounds S8 against VEGFR1 and VEGFR3, respectively, were excellent. Whereas compounds S11 and S14 demonstrated the highest inhibitory potential against ERBB and VEGFR2, with docking scores of -37.92 and -38.5 kJ/mol against ERBB and -41.2 and -46.5 kJ/mol against VEGFR-2, respectively. The results of the molecular docking studies were further correlated with the molecular dynamics simulation studies. Moreover, HYDE energy was calculated through SeeSAR analysis, and the safety profile of the compounds was predicted through ADME studies.

Design and development of novel potential inhibitors of the human USP21 enzyme using a pharmacophore-based virtual screening technique.

An overexpression and increase have been observed in the concentration and activity of the USP21 enzyme in many cancers, necessitating the need for the development of new inhibitor drugs against the same. The current study attempts to discover one such novel potential inhibitor of USP21 by the application of various bioinformatics techniques which include molecular modelling, pharmacophore mapping, and pharmacophore-based virtual screening, molecular docking, and ADMET prediction followed by molecular dynamics simulations. Following this inverted-funnel-like approach, we finally ended up with one ligand- ZINC02422616 which displays a very high binding affinity towards the USP21 domain. This ligand contains all the pharmacophoric features displayed by the compounds that are potential inhibitors of the USP21 domain. Moreover, it shows a favourable pharmacokinetic, pharmacodynamic, and ADMET profile along with strong hydrophobic interaction and hydrogen bonding with the domain. Simulation studies showed that the complex remains stable over time, with the bound protein displaying a more constrained motion in the conformational space compared to the unbound form. The ligand showed a highly favourable free energy landscape/surface, forming several energy minimas in contrast to the unbound domain in which most conformations occupied a relatively higher energy state. Moreover, the ligand also displayed a Kd of 422.8nM and a free energy of binding ΔG of -8.6kcal/mol, both of which indicate a very high affinity towards the target domain.This potential drug candidate can then be used as a viable treatment method for many types of cancers caused by USP21. his article is protected by copyright. All rights reserved.

Pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation for identification of potential ERK inhibitors

As the downstream component of the mitogen-activated protein kinases (MAPK) pathway, the extracellular signal-regulated kinase (ERK) is responsible for phosphorylating a broad range of substrates in cell proliferation, differentiation, and survival. Direct targeting the ERK proteins by the piperidinopyrimidine urea-based inhibitors has been demonstrated to be an effective way to block the MAPK signaling pathway in inhibiting tumor growth. In order to discover better inhibitors, a computer-aided drug design (CADD) approach was employed to reveal the pharmacological characteristics and mechanisms of action. The pharmacophore model was generated on the basis of the compounds with eight features, i.e., four hydrogen bond acceptor atoms, one hydrogen bond donor atom, and three hydrophobic centers. A total of 14 hit compounds were obtained through virtual screening. Two potential inhibitors, namely VS01 and VS02, have been identified by molecular docking and molecular dynamics simulations. Both compounds are capable of attaching to the ERK pocket precisely. The binding free energies of VS01 and VS02 are about 15 kJ/mol and 4 kJ/mol stronger than that of the clinic Ulixertinib because of the characteristic hydrogen bonding, electrostatic, and hydrophilic interactions. The present theoretical investigations shed new light on the rational design of the potential ERK inhibitors to stimulate further experimental tests. Communicated by Ramaswamy H. Sarma

Structure-Based Design and Pharmacophore-Based Virtual Screening of Combinatorial Library of Triclosan Analogues Active against Enoyl-Acyl Carrier Protein Reductase of Plasmodium falciparum with Favourable ADME Profiles.

Cost-effective therapy of neglected and tropical diseases such as malaria requires everlasting drug discovery efforts due to the rapidly emerging drug resistance of the plasmodium parasite. We have carried out computational design of new inhibitors of the enoyl-acyl carrier protein reductase (ENR) of Plasmodium falciparum (PfENR) using computer-aided combinatorial and pharmacophore-based molecular design. The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) complexation QSAR model was developed for triclosan-based inhibitors (TCL) and a significant correlation was established between the calculated relative Gibbs free energies of complex formation (∆∆Gcom) between PfENR and TCL and the observed inhibitory potencies of the enzyme (IC50exp) for a training set of 20 known TCL analogues. Validation of the predictive power of the MM-PBSA QSAR model was carried out with the generation of 3D QSAR pharmacophore (PH4). We obtained a reasonable correlation between the relative Gibbs free energy of complex formation ∆∆Gcom and IC50exp values, which explained approximately 95% of the PfENR inhibition data: pIC50exp=-0.0544×∆∆Gcom+6.9336,R2=0.95. A similar agreement was established for the PH4 pharmacophore model of the PfENR inhibition (pIC50exp=0.9754×pIC50pre+0.1596, R2=0.98). Analysis of enzyme-inhibitor binding site interactions suggested suitable building blocks to be used in a virtual combinatorial library of 33,480 TCL analogues. Structural information derived from the complexation model and the PH4 pharmacophore guided us through in silico screening of the virtual combinatorial library of TCL analogues to finally identify potential new TCL inhibitors effective at low nanomolar concentrations. Virtual screening of the library by PfENR-PH4 led to a predicted IC50pre value for the best inhibitor candidate as low as 1.9 nM. Finally, the stability of PfENR-TCLx complexes and the flexibility of the active conformation of the inhibitor for selected top-ranking TCL analogues were checked with the help of molecular dynamics. This computational study resulted in a set of proposed new potent inhibitors with predicted antimalarial effects and favourable pharmacokinetic profiles that act on a novel pharmacological target, PfENR.

Identification of BACE-1 Inhibitors against Alzheimer's Disease through E-Pharmacophore-Based Virtual Screening and Molecular Dynamics Simulation Studies: An Insilco Approach.

Alzheimer is a severe memory and cognitive impairment neurodegenerative disease that is the most common cause of dementia worldwide and characterized by the pathological accumulation of tau protein and amyloid-beta peptides. In this study, we have developed E-pharmacophore modeling to screen the eMolecules database with the help of a reported co-crystal structure bound with Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE-1). Flumemetamol, florbetaben, and florbetapir are currently approved drugs for use in the clinical diagnosis of Alzheimer's disease. Despite the benefits of commercially approved drugs, there is still a need for novel diagnostic agents with enhanced physicochemical and pharmacokinetic properties compared to those currently used in clinical practice and research. In the E-pharmacophore modeling results, it is revealed that two aromatic rings (R19, R20), one donor (D12), and one acceptor (A8) are obtained, and also that similar pharmacophoric features of compounds are identified from pharmacophore-based virtual screening. The identified screened hits were filtered for further analyses using structure-based virtual screening and MM/GBSA. From the analyses, top hits such as ZINC39592220 and en1003sfl.46293 are selected based on their top docking scores (-8.182 and -7.184 Kcal/mol, respectively) and binding free energy (-58.803 and -56.951 Kcal/mol, respectively). Furthermore, a molecular dynamics simulation and MMPBSA study were performed, which revealed admirable stability and good binding free energy throughout the simulation period. Moreover, Qikprop results revealed that the selected, screened hits have good drug-likeness and pharmacokinetic properties. The screened hits ZINC39592220 and en1003sfl.46293 could be used to develop drug molecules against Alzheimer's disease.

Identification of RdRp inhibitors against SARS-CoV-2 through E-pharmacophore-based virtual screening, molecular docking and MD simulations approaches

The outbreak of novel Coronavirus, an enduring pandemic declared by WHO, has consequences to an alarming ongoing public health menace which has already claimed several million human lives. In addition to numerous vaccinations and medications for mild to moderate COVID-19 infection, lack of promising medication or therapeutic pharmaceuticals remains a serious concern to counter the ongoing coronavirus infections and to hinder its dreadful spread. Global health emergencies have called for urgency for potential drug discovery and time is the biggest constraint apart from the financial and human resources required for the high throughput drug screening. However, computational screening or in-silico approaches appeared to be an effective and faster approach to discover potential molecules without sacrificing the model animals. Accumulated shreds of evidence on computational studies against viral diseases have revealed significance of in-silico drug discovery approaches especially in the time of urgency. The central role of RdRp in SARS-CoV-2 replication makes it promising drug target to curtain on going infection and its spread. The present study aimed to employ E-pharmacophore-based virtual screening to reveal potent inhibitors of RdRp as potential leads to block the viral replication. An energy-optimised pharmacophore model was generated to screen the Enamine REAL DataBase (RDB). Then, ADME/T profiles were determined to validate the pharmacokinetics and pharmacodynamics properties of the hit compounds. Moreover, High Throughput Virtual Screening (HTVS) and molecular docking (SP & XP) were employed to screen the top hits from pharmacophore-based virtual screening and ADME/T screen. The binding free energies of the top hits were calculated by conducting MM-GBSA analysis followed by MD simulations to determine the stability of molecular interactions between top hits and RdRp protein. These virtual investigations revealed six compounds having binding free energies of −57.498, −45.776, −46.248, −35.67, −25.15 and −24.90 kcal/mol respectively as calculated by the MM-GBSA method. The MD simulation studies confirmed the stability of protein ligand complexes, hence, indicating as potent RdRp inhibitors and are promising candidate drugs to be further validated and translated into clinics in future.

In Silico Identification of Lead Compounds for Pseudomonas Aeruginosa PqsA Enzyme: Computational Study to Block Biofilm Formation.

Pseudomonas aeruginosa is an opportunistic Gram-negative bacterium implicated in acute and chronic nosocomial infections and a leading cause of patient mortality. Pseudomonas aeruginosa infections are frequently associated with the development of biofilms, which give the bacteria additional drug resistance and increase their virulence. The goal of this study was to find strong compounds that block the Anthranilate-CoA ligase enzyme made by the pqsA gene. This would stop the P. aeruginosa quorum signaling system. This enzyme plays a crucial role in the pathogenicity of P. aeruginosa by producing autoinducers for cell-to-cell communication that lead to the production of biofilms. Pharmacophore-based virtual screening was carried out utilizing a library of commercially accessible enzyme inhibitors. The most promising hits obtained during virtual screening were put through molecular docking with the help of MOE. The virtual screening yielded 7/160 and 10/249 hits (ZINC and Chembridge). Finally, 2/7 ZINC hits and 2/10 ChemBridge hits were selected as potent lead compounds employing diverse scaffolds due to their high pqsA enzyme binding affinity. The results of the pharmacophore-based virtual screening were subsequently verified using a molecular dynamic simulation-based study (MDS). Using MDS and post-MDS, the stability of the complexes was evaluated. The most promising lead compounds exhibited a high binding affinity towards protein-binding pocket and interacted with the catalytic dyad. At least one of the scaffolds selected will possibly prove useful for future research. However, further scientific confirmation in the form of preclinical and clinical research is required before implementation.

Identification of Novel Natural Dual HDAC and Hsp90 Inhibitors for Metastatic TNBC Using e-Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Studies.

Breast cancer (BC) is one of the main types of cancer that endangers women's lives. The characteristics of triple-negative breast cancer (TNBC) include a high rate of recurrence and the capacity for metastasis; therefore, new therapies are urgently needed to combat TNBC. Dual targeting HDAC6 and Hsp90 has shown good synergistic effects in treating metastatic TNBC. The goal of this study was to find potential HDAC6 and Hsp90 dual inhibitors. Therefore, several in silico approaches have been used. An e-pharmacophore model generation based on the HDAC6-ligand complex and subsequently a pharmacophore-based virtual screening on 270,450 natural compounds from the ZINC were performed, which resulted in 12,663 compounds that corresponded to the obtained pharmacophoric hypothesis. These compounds were docked into HDAC6 and Hsp90. This resulted in the identification of three compounds with good docking scores and favorable free binding energy against the two targets. The top three compounds, namely ZINC000096116556, ZINC000020761262, and ZINC000217668954, were further subjected to ADME prediction and molecular dynamic simulations, which showed promising results in terms of pharmacokinetic properties and stability. As a result, these three compounds can be considered potential HDAC6 and Hsp90 dual inhibitors and are recommended for experimental evaluation.

Virtual screening (VS) based in the common binding site for negativelycharged activators of K+ channels: A comparison with a pharmacophore-based VS.

A master key mechanism related to the pharmacophore of negatively charged activators (NCAs) to modulate TREK, BKca and hERG potassium (K+) channels was recently described. A polypharmacological behavior of NCAs was assessed, because all NCA found could activate these three type of K+ channels. However, the role of the binding sites (BS) in the polypharmacological nature of NCAs remains unknown. In this context, the presence of structural common patterns at the BS appears to be a valid hypothesis. Residues determined experimentally as having a significant role on K+ channel-NCAs interaction were retrieved. Structural common patterns at the NCAs BS were found between TREK, BKca and hERG K+ channels using our program Geomfinder comparing by pairs. These common BS were used for a structure-based virtual screening (VS). In parallel, a pharmacophore-based VS was carried out based in the common features of the NCAs. The VS results were organized using MM-GBSA. Nineteen compounds target in silico at least two of the three types of K+ channels studied. They also accomplish two features: 1) they were found simultaneously by structure-based VS and pharmacophore-based VS; 2) all of them point their negative charge to the pore, a feature that it is mandatory for the activation of TREK, BKca and hERG K+ channelsby NCAs. These nineteen compounds will be proposed to test by means of two-electrode voltage clamp technique in the three types of K+ channels studied.

Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies

The lack of effective treatment remains a bottleneck in combating the current coronavirus family pandemic, particularly coronavirus 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection of host cells by SARS-CoV-2 is mediated by the binding of its receptor-binding domain (RBD) on the spike (S) glycoprotein to the host angiotensin-converting enzyme (ACE2) receptor. As all developed and available vaccines against COVID-19 do not provide long-term immunity, the creation of an effective drug for the treatment of COVID-19 is necessary and cannot be ignored. Therefore, the aim of this study is to present a computational screening method to identify potential inhibitor candidates with a high probability of blocking the binding of RBD to the ACE2 receptor. Pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations, and binding free-energy analyses were performed to identify potential inhibitor candidates against ACE2/SARS-CoV-2. In conclusion, we propose the compound PubChem-84280085 as a potential inhibitor of protein–protein interactions to disrupt the binding of the SARS-CoV-2-RBD to the ACE2 receptor.