Practical Considerations in Virtual Screening and Molecular Docking

Chromatographic retention assisted in-silico prediction of anticancer potential of glucocorticoids on cancer cell lines

Glucocorticoids (GCs) are hallmarks of anti-inflammatory activity. They are used as adjuvant therapy in oncology medications to alleviate some of the associated side effects. Although recent research has indicated that GCs have favorable anticancer potential, some scientific evidence suggests a pro-proliferation impact of GCs on cancer cells. This may create a scientific confusion on the utility of GCs and the choice of which GC enhances the anticancer potential and mitigates the negative effect. Accurate in-silico prediction and correct ranking of biological activity may be limited by the impact of the physicochemical interaction between small molecules and biological membranes. Chromatographic retention is inherently dependent on the physicochemical properties of the test molecule. It can scale the relative hydrophobicity and tentatively indicate the membrane permeability. In this study, the relationship between the in-silico binding affinity, the chromatographic retention and the in-vitro anticancer activity was investigated. Fifteen GCs were chromatographically separated on an Inertsil® C18 (4.6 * 250 mm; 5 μm) HPLC column. The binding affinity of the test GCs was determined on three receptors involved in cancer cell proliferation (topoisomerase II (TOPII), glucocorticoid receptor (GR) and ATP-binding cassette (ABCG2)). The antiproliferative potential of the test steroids was determined as per their IC50. The correlation between chromatographic retention and the binding affinity to the observed IC50 was investigated by multiple linear regression (MLR). Results revealed that some GCs exhibited a remarkably favorable inhibitory potential against cancer cell lines over normal cell lines. Our data indicated a significant correlation between the retention times of different GCs and the determined binding affinity, especially to the GR (r2 = 0.677; p = 0.011) and the estrone sulphate (ESS) binding site of the ABCG2 (r2 = 0.643; p = 0.018). Concurrently, the retention times were well correlated to the observed IC50 on the colorectal cancer cell lines (r2 = 0.580; p = 0.038) and the hypopharyngeal cell lines (r2 = 0.638; p = 0.019). Significant MLR models (n = 4) correlating the retention times of the tested steroids and the binding affinity to the observed IC50 were created. The MLR model correlating the retention times and the ABCG2_ESS binding affinity to the IC50 on lung cancer was the most significant (p = 0.004). The accuracy of the model was 107.12 ± 29.18 % indicating good IC50 prediction abilities. In conclusion, chromatographic retention can be employed as a low-cost and simple auxiliary tool for improving the in-silico prediction of the in-vitro activities of small molecules.

Structure-based virtual screening against multiple Plasmodium falciparum kinases reveals antimalarial compounds

The continuous emergence of resistance against most frontline antimalarial drugs has led to countless deaths in malaria-endemic countries, counting 619,000 deaths in 2021, with mutation in drug targets being the sole cause. As mutation is correlated frequently with fitness cost, the likelihood of mutation emergence in multiple targets at a time is extremely low. Hence, multitargeting compounds may seem promising to address drug resistance issues with additional benefits like increased efficacy, improved safety profile, and the requirement of fewer pills compared to traditional single and combinational drugs. In this study, we attempted to use the High Throughput Virtual Screening approach to predict multitarget inhibitors against six chemically validated Plasmodium falciparum (Pf) kinases (PfPKG, PfMAP2, PfCDPK4, PfTMK, PfPK5, PfPI4K), resulting in 21 multitargeting hits. The molecular dynamic simulation of the top six complexes (Myricetin-MAP2, Quercetin-CDPK4, Myricetin-TMK, Quercetin-PKG, Salidroside-PK5, and Salidroside-PI4K) showed stable interactions. Moreover, hierarchical clustering reveals the structural divergence of the compounds from the existing antimalarials, indicating less chance of cross-resistance. Additionally, the top three hits were validated through parasite growth inhibition assays, with quercetin and myricetin exhibiting an IC50 value of 1.84 and 3.93 µM, respectively.

Elucidation of 7,8-dihydroxy flavone in complexing with the oxidative stress-inducing enzymes, its impact on radical quenching and DNA damage: an in silico and in vitro approach

Oxidative stress (OS) has been attributed to the progression of various disorders, including cancer, diabetes, and cardiovascular diseases. Several antioxidant compounds and free radical quenchers have been shown to mitigate oxidative stress. However, large-scale randomized controlled trials of such compounds on chronic disease aversion have yielded paradoxical and disappointing results due to the constrained cognizance of their oxidative mechanisms and therapeutic targets. The current study sought to identify the potential therapeutic targets of 7,8-Dihydroxyflavone (7,8-DHF) by analyzing its interactions with the enzymes implicated in oxidative stress and also to explore its radicle quenching potential and prophylactic impact on the H2O2-induced DNA damage. Through the in silco approach, we investigated the antioxidant potential of 7,8-DHF by evaluating its interactions with the human oxidative stress-inducing enzymes such as myeloperoxidase (MPO), NADPH oxidase (NOX), nitric oxide synthase (NOS), and xanthine oxidase (XO) and a comparative analysis of those interactions with known antioxidants (Ascorbic acid, Melatonin, Tocopherol) used as controls. The best-scoring complex was adopted for the simulation analysis in investigating protein-ligand conformational dynamics. The in vitro radicle quenching potential was evaluated by performing a spectrum of antioxidant assays, and radical quenching was observed in a dose-dependent fashion with IC50 values of < 60 µM/mL. Further, we probed its anti-hemolytic potential and prophylactic impact in avian erythrocytes subjected to H2O2-induced hemolysis and DNA damage by implementing hemolysis and comet assays. The protective effect was more pronounced at higher concentrations of the drug.Communicated by Ramaswamy H. Sarma.

Virtual Screening Process: A Guide in Modern Drug Designing

Due to its capacity to drastically cut the cost and time necessary for experimental screening of compounds, virtual screening (VS) has grown to be a crucial component of drug discovery and development. VS is a computational method used in drug design to identify potential drugs from enormous libraries of chemicals. This approach makes use of molecular modeling and docking simulations to assess the small molecule's ability to bind to the desired protein. Virtual screening has a bright future, as high computational power and modern techniques are likely to further enhance the accuracy and speed of the process.

Entrectinib a Plausible Inhibitor for Osteopontin (SPP1) in Cervical Cancer-Integrated Bioinformatic Approach

Cervical cancer is one of the major causes of death in women, especially in developing countries bearing more than a quarter of the global burden. Secreted phosphoprotein-1, also known as OPN (osteopontin), is an integrin-binding glycophosphoprotein that is overexpressed in a variety of tumors. OPN is a chemokine-like calcified ECM-associated protein that plays a crucial role in evaluating the metastatic potential of various cancers. However, the role of SPP1 in the tumor microenvironment and associated signaling pathways in CC is still unclear. In our study, three CC microarray datasets (GSE9750, GSE46857, and GSE67522) were obtained from the GEO database to identify the differentially expressed genes. Enrichment analysis was carried out by Enrichr and ShinyGO and the PPI interaction network was created by using String and Cytoscape. GEPIA datasets were used to validate the top 10 hub genes, and virtual screening, docking, and dynamic simulation studies were used to identify a suitable inhibitor against the OPN protein using MVD, PyRx, and GROMACS respectively. Our results show that a total of 11 DEGs were common for three datasets and gene ontology pathway enrichment analysis revealed that 2 biological processes i.e. programmed cell death and animal organ development commonly affected mechanisms in all three datasets. Docking and dynamic studies revealed that Entrectinib showed excellent binding affinity against OPN protein. Based on the results, we conclude that OPN is one of the most upregulated genes in cervical cancer and Entrectinib emerges to be a promising potential OPN inhibitor to curtail cervical cancer progression. Schematic representation: The schematic representation of methodology steps is illustrated in the graphical abstract. Schematic representation of methodology.

Homology Modeling, Screening, and Identification of Potential FOXO6 Inhibitors Curtail Gastric Cancer Progression: an In Silico Drug Repurposing Approach

Gastric cancer is the world's second leading cause of cancer-related fatalities, with the epidemiology changing over the previous several decades. FOXOs are the O subfamily of the forkhead box (FOX) transcription factor family, which consists of four members: FOXO1, FOXO3, FOXO4, and FOXO6. FOXO6 mRNA and protein levels are increased in gastric cancer tissues. FOXO6 forced overexpression enhances gastric cancer cell growth, while knockdown decreases proliferation. In our study, the GEPIA, Kaplan-Meier, KEGG, and STRING databases were used to determine FOXO6 mRNA expression, overall survival ratio, interactive pathways, and top 10 associated proteins in gastric cancer respectively. Due to the lack of a solved structure for FOXO6, homology modeling was performed to obtain a 3D structure model, and we used anti-cancer drugs and small molecules to target FOXO6 for identifying a potential selective FOXO6 inhibitor. The chemical composition of the proteins and ligands has a significant impact on docking procedure performance. With this in mind, a critical evaluation of the performance of three regularly used docking routines was carried out: MVD, AutoDock Vina in PyRx, and ArgusLab. The binding affinities, docking scores, and intermolecular interactions were used as assessment criteria. In the study, the porfimer sodium showed excellent binding affinity to the FOXO6 protein. The major three docking software packages were used to analyze the scoring/H-bonding energy and intermolecular interactions. Based on the results, we concluded that FOXO6 was upregulated in gastric cancer and the ligand porfimer sodium emerges as a promising potential FOXO6 inhibitor to curtail gastric cancer progression.

In silico discovery of novel calcineurin inhibitors using ligand-based 3-D pharmacophore modelling and molecular dynamics simulation

Calcineurin is a serine-threonine protein phosphatase that is activated with the binding of calmodulin in the presence of increased calcium concentration and has a major role in various signaling pathways. Its role in regulating homeostasis, developmental processes, and different disease progression has already been reported. The dysregulated Ca2+/calcineurin/NFAT1-4 pathway is observed in Autoimmune disorders and hence the use of Calcineurin inhibitors like Cyclosporin A (CsA) and Tacrolimus (FK506) is widely done in such cases. Recent studies indicate the uncontrolled overexpression of the Calcineurin protein in the pathophysiological pathway of neurodegenerative diseases. The in vitro and animal model studies with standard calcineurin inhibitors (CnIs), which are widely labeled as immunosuppressant drugs, have shown a significant reduction of neurodegeneration in respective models. These results compel the identification of novel calcineurin inhibitors against neurodegenerative diseases. With this scenario, the present work focuses on the computer-aided identification of novel CnIs via ligand-based 3-D pharmacophore modelling. Known CnIs, CsA, and FK506, were used to build the pharmacophore models which were validated and screened against external databases to retrieve possible hits. Docking investigations, pharmacokinetic properties, and molecular dynamics simulations along with toxicity predictions were performed on the hits that were obtained. According to the study, a total of 5 molecules ILB 162, ILB 005, ILB 439, ILB 390, and ILB 198, were found to be the best calcineurin inhibitors with binding affinity in the range of -9.7 to -9.0 Kcal/mol with 1MF8 (PDB). The stability of interactions of these molecules was further validated via Molecular dynamics simulation studies to confirm these to be the potential calcineurin-inhibiting molecules. HIGHLIGHTSCalcineurin inhibitors can be a novel therapeutic candidate against neurodegenerative diseases.The identification of novel Calcineurin inhibitors was done in silico using ligand-based 3-D pharmacophore modelling using Ligand Scout Essential 4.4. software.The model could identify 440 hits from various external databases like PubChem (2432 molecules), ChemSpider, MayBridge, DrugBank, and e-Drug 3D by Cheminformatic Tools and Databases for Pharmacology.Out of which 5 molecules: ILB 162, ILB 005, ILB 439, ILB 390, and ILB 198, were found to be the best calcineurin inhibitors with binding affinity in the range of -9.7 to -9.0 Kcal/mol with 1MF8 (PDB) which were further confirmed to be the best CnI candidates via Molecular dynamics simulation studies.Communicated by Ramaswamy H. Sarma.

Identification of Unknown Inverted Singlet-Triplet Cores by High-Throughput Virtual Screening

Molecules where the energy of the lowest excited singlet state is found below the energy of the lowest triplet state (inverted singlet-triplet molecules) are extremely rare. It is particularly challenging to discover new ones through virtual screening because the required wavefunction-based methods are expensive and unsuitable for high-throughput calculations. Here, we devised a virtual screening approach where the molecules to be considered with advanced methods are pre-selected with increasingly more sophisticated filters that include the evaluation of the HOMO-LUMO exchange integral and approximate CASSCF calculations. A final set of 7 candidates (0.05% of the initial 15 000) were verified to possess inversion between singlet and triplet states with state-of-the-art multireference methods (MS-CASPT2). One of them is deemed of particular interest because it is unrelated to other proposals made in the literature.

Tuning the Biological Activity of PI3Kδ Inhibitor by the Introduction of a Fluorine Atom Using the Computational Workflow

As a member of the class I PI3K family, phosphoinositide 3-kinase δ (PI3Kδ) is an important signaling biomolecule that controls immune cell differentiation, proliferation, migration, and survival. It also represents a potential and promising therapeutic approach for the management of numerous inflammatory and autoimmune diseases. We designed and assessed the biological activity of new fluorinated analogues of CPL302415, taking into account the therapeutic potential of our selective PI3K inhibitor and fluorine introduction as one of the most frequently used modifications of a lead compound to further improve its biological activity. In this paper, we compare and evaluate the accuracy of our previously described and validated in silico workflow with that of the standard (rigid) molecular docking approach. The findings demonstrated that a properly fitted catalytic (binding) pocket for our chemical cores at the induced-fit docking (IFD) and molecular dynamics (MD) stages, along with QM-derived atomic charges, can be used for activity prediction to better distinguish between active and inactive molecules. Moreover, the standard approach seems to be insufficient to score the halogenated derivatives due to the fixed atomic charges, which do not consider the response and indictive effects caused by fluorine. The proposed computational workflow provides a computational tool for the rational design of novel halogenated drugs.

Application of Computational Biology and Artificial Intelligence in Drug Design

Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, we propose a methodology for integrating various computational techniques into new drug discovery and design.

Antiproliferative Activity of Some Newly Synthesized Substituted Nicotinamides Candidates Using Pyridine-2(1H) thione Derivatives as Synthon

Some new pyridinethione and thienopyridine derivatives have been synthesized and evaluated for their antiproliferative activity using the MTT assay. Nicotinamide derivatives 3 have been synthesized and used for the preparation of new condensed thieno [2,3-b]pyridines by their reactions with active halo compounds. Finally the synthesized thienopyridine underwent ring closure whenever possible through boiling in a solution of sodium ethoxide. The antiproliferative evaluation against (HCT-116, HepG-2, and MCF-7) human cancer cells and one human healthy cell line (BJ-1) revealed that compounds 3b, 4c-5d, 7b-12a, 10d, and 13b have interesting antitumor activity specifically as antihepatocellular and anticolon cellular carcinoma agents. Besides, the docking results for most active derivatives were in agreement with the in vitro antitumor results.

Dry Grinding Synthesis and Docking Study of Cyclopentanone-Sulfur Containing Compounds with Anti-Proliferative Activity for HepG-2 and A-549 Cancer Cell Lines

BACKGROUND

The dry grinding method is a green technique for efficient organic synthesis with numerous advantages, such as: mild reaction conditions, environmental acceptability, simple segregation and refinement as well as the elevated selectivity and efficiency.

OBJECTIVE

The aim of the present work is to design and synthesize of cyclopentylidene-hydrazino)-thiazole derivatives using dry grinding condition to investigate their antitumor activity aganist two cell lines namely, HepG-2 and A-549.

METHODS

In this context, we synthesized series of thiazole incorporated cyclopentane through hydrazone-group and 2-cyclopentylidenehydrazine-1-carbimidic-2-ethoxy-N-aryl-2-oxoacetohydrazonic thioanhydride under dry grinding within minutes and excellent to good yield.

RESULTS

All spectral data confirmed the proposed structures. The molecular docking studies have been performed using Macrophage Migration Inhibitory Factor (Pdb: 4k9g) and Lysozyme C (Pdb: 2f4a), the overexpressed proteins in human liver cancer cell (HepG-2) and lung cancer cell lines (A-549), respectively, in addition to the antitumor activity investigations contra the two types of tumor cells.

CONCLUSION

Two derivatives 9b and 9d showed the highest antitumor activity against the two cell lines HepG-2 and A-549. Also, docking results revealed high energy score ranging from -7.1590 to -5.9364 Kcal/mol with Macrophage Migration Inhibitory Factor (Pdb: 4k9g) which is more than the energy score = -4.118 Kcal/mol of co-crystallized ligand. Moreover, the tested derivatives showed energy score varies from -6.0802 to -4.5503 Kcal/mol against Lysozyme C (Pdb: 2f4a).

An Integrated Pharmacology-Based Strategy to Investigate the Potential Mechanism of Xiebai San in Treating Pediatric Pneumonia

Xiebai San (XBS) is a traditional Chinese medicine (TCM) prescription that has been widely used to treat pediatric pneumonia since the Song dynasty. To reveal its underlying working mechanism, a network pharmacology approach was used to predict the active ingredients and potential targets of XBS in treating pediatric pneumonia. As a result, 120 active ingredients of XBS and 128 potential targets were screened out. Among them, quercetin, kaempferol, naringenin, licochalcone A and isorhamnetin showed to be the most potential ingredients, while AKT1, MAPK3, VEGFA, TP53, JUN, PTGS2, CASP3, MAPK8 and NF-κB p65 showed to be the most potential targets. IL-17 signaling pathway, TNF signaling pathway and PI3K-Akt signaling pathway, which are involved in anti-inflammation processes, immune responses and apoptosis, showed to be the most probable pathways regulated by XBS. UPLC-Q/Orbitrap HRMS analysis was then performed to explore the main components of XBS, and liquiritin, quercetin, kaempferol, licochalcone A and glycyrrhetinic acid were identified. Molecular docking analysis of the compounds to inflammation-associated targets revealed good binding abilities of quercetin, kaempferol, licochalcone A and liquiritin to NF-κB p65 and of quercetin and kaempferol to Akt1 or Caspase-3. Moreover, molecular dynamics (MD) simulation for binding of quercetin or kaempferol to NF-κB p65 revealed dynamic properties of high stability, high flexibility and lowbinding free energy. In the experiment with macrophages, XBS markedly suppressed the (Lipopolysaccharides) LPS-induced expression of NF-κB p65 and the production of pro-inflammatory cytokines IL-6 and IL-1β, supporting XBS to achieve an anti-inflammatory effect through regulating NF-κB p65. XBS also down-regulated the expression of p-Akt (Ser473)/Akt, Bax and Caspase-3 and up-regulated the expression of Bcl-2, indicating that regulating Akt1 and Caspase-3 to achieve anti-apoptotic effect is also the mechanism of XBS for treating pediatric pneumonia. Our study helped to reveal the pharmacodynamics material basis as well as the mechanism of XBS in treating pediatric pneumonia.

Molecular docking and MD: mimicking the real biological process

In the processes of molecular docking and simulation studies; the computational techniques have a vast and significant role in drug discovery process. The rigid view in the binding of both target and ligand is the basis of modeling strategy process. More evolution to such processes with the time has lead in revealing the path of understanding the dynamic nature of binding processes. In this chapter we have focused on molecular docking along with dynamic studies in reference to biological processes.

Investigating natural compounds against oncogenic RET tyrosine kinase using pharmacoinformatic approaches for cancer therapeutics

Rearranged during transfection (RET) tyrosine kinase is a transmembrane receptor tyrosine kinase regulating vital aspects of cellular proliferation, differentiation, and survival. An outstanding challenge in designing protein kinase inhibitors is due to the development of drug resistance. The “gain of function” mutations in the RET gate-keeper residue, Val804, confers resistance to the majority of known RET inhibitors, including vandetanib. To curtail this resistance, researchers developed selpercatinib (LOXO-292) against the RET gate-keeper mutant forms – V804M and V804L. In the present in silico investigation, a receptor–ligand pharmacophore model was generated to identify small molecule inhibitors effective for wild-type (WT) as well as mutant RET kinase variants. The generated model was employed to screen 144 766 natural products (NPs) available in the ZINC database and the retrieved NPs were filtered for their drug-likeness. The resulting 2696 drug-like NPs were subjected to molecular docking with the RET WT kinase domain and a total of 27 molecules displayed better dock scores than the reference inhibitors – vandetanib and selpercatinib. From 27 NPs, an aggregate of 12 compounds demonstrated better binding free energy (BFE) scores than the reference inhibitors, towards RET. Thus, the 12 NPs were also subjected to docking, simulation, and BFE estimation towards the constructed gate-keeper RET mutant structures. The BFE calculations revealed 3 hits with better BFE scores than the reference inhibitors towards WT, V804M, and V804L RET variants. Thus, the scaffolds of hit compounds presented in this study could act as potent RET inhibitors and further provide insights for drug optimization targeting aberrant activation of RET signaling, specifically the mutation of gate-keeper residue – Val804.

Identification of natural product inhibitors against rearranged during transfection (RET) tyrosine kinase as cancer therapeutics using combination of in silico techniques.

Current trends in computer aided drug design and a highlight of drugs discovered via computational techniques: A review

Computer-aided drug design (CADD) is one of the pivotal approaches to contemporary pre-clinical drug discovery, and various computational techniques and software programs are typically used in combination, in a bid to achieve the desired outcome. Several approved drugs have been developed with the aid of CADD. On SciFinder®, we evaluated more than 600 publications through systematic searching and refining, using the terms, virtual screening; software methods; computational studies and publication year, in order to obtain data concerning particular aspects of CADD. The primary focus of this review was on the databases screened, virtual screening and/or molecular docking software program used. Furthermore, we evaluated the studies that subsequently performed molecular dynamics (MD) simulations and we reviewed the software programs applied, the application of density functional theory (DFT) calculations and experimental assays. To represent the latest trends, the most recent data obtained was between 2015 and 2020, consequently the most frequently employed techniques and software programs were recorded. Among these, the ZINC database was the most widely preferred with an average use of 31.2%. Structure-based virtual screening (SBVS) was the most prominently used type of virtual screening and it accounted for an average of 57.6%, with AutoDock being the preferred virtual screening/molecular docking program with 41.8% usage. Following the screening process, 38.5% of the studies performed MD simulations to complement the virtual screening and GROMACS with 39.3% usage, was the popular MD software program. Among the computational techniques, DFT was the least applied whereby it only accounts for 0.02% average use. An average of 36.5% of the studies included reports on experimental evaluations following virtual screening. Ultimately, since the inception and application of CADD in pre-clinical drug discovery, more than 70 approved drugs have been discovered, and this number is steadily increasing over time.

Chemo-informatics guided study of natural inhibitors targeting rho GTPase: a lead for treatment of glaucoma

Glaucoma, the most perilous disease leading to blindness is a result of optical neuropathy. Accumulation of aqueous humor in the posterior chamber due to a large difference in the rate of formation and its drainage in the anterior chamber causes an increase in intraocular pressure (IOP) leading to damage of nerve cells. A literature survey has revealed that inhibition of the Rho guanosine triphosphatases (rho GTPase) pathway by specific inhibitors leads to the relaxation of contractile cells involved in the aqueous outflow pathway. Relaxation of the strained contractile cells results in increased outflow thereby releasing IOP. In the present study molecular docking has been used to screen twenty seven bioactive (17 natural compounds and 10 conventional drugs) compounds that may play a significant role in relaxing contractile cells by inhibiting rho-GTPase protein. Docking results showed that among all-natural bioactive compounds Cyanidin and Delphinidine have a good binding affinity (- 8.4 kcal/mol) than the top screened conventional drug molecule Mitomycin, (- 6.3 kcal/mol) when docked with rho-GTPase protein. Cyanidin and Delphinidin belong to anthocyanidin, a glycoside form of anthocyanins from Vaccinium myrtillus L. and Punica granatum. The resembling potential of Cyanidin and Delphinidin concerning the drug Mitomycin was confirmed through simulation analysis. Molecular dynamics study (MDS) for 100 ns, showed that the rho GTPase-Delphinidine complex structure was energetically more stable than rho GTPase-Cyaniding complex in comparison to rho GTPase-Mitomycin complex. The comparative study of both the selected hits (Cyanidin and Delphinidin) was assessed by RMSD, RMSF, Rg, SASA, H-bond, PCA MM/PBSA analysis. The analysis revealed that Delphinidine is more potent to inhibit the rho GTPase as compare to Cyaniding and available conventional drugs in terms of stability and binding free energy. Based on the results, these molecules have good pharmacokinetic and pharmacodynamics properties and will prove to be a promising lead compound as a future drug for Glaucoma.

Structure-based Virtual Screening Approach for the Discovery of Potent Inhibitors of Aminoglycoside 6'-N-Acetyltransferase Type Ib [AAC(6')-Ib] against K. pneumoniae Infections

Background:

Aminoglycoside 6'-N-acetyltransferase type Ib (AAC(6')-Ib) from Klebsiella pneumoniae is an established drug target and has conferred insensitivity to aminoglycosides. Aminoglycosides are often inactivated by aminoglycoside modifying enzymes encoded by genes present in the chromosome, plasmids, and other genetic elements. The AAC(6′)- Ib is an enzyme of clinical importance found in a wide variety of gram-negative pathogens. The AAC(6′)-Ib enzyme is of interest not only because of its ubiquity but also because of other characteristics e.g., it presents significant microheterogeneity at the N-termini and the aac(6′)-Ib gene is often present in integrons, transposons, plasmids, genomic islands, and other genetic structures. The majority of the reported potent inhibitors against the target are substrate analogs. Therefore, there is a need to develop or discover new scaffolds other than substrate analogs as AAC(6')-Ib inhibitor.

Objective:

The objective of this study is to set optimum parameters for the structure-based virtual screening by multiple docking and scoring methods. The multiple scoring of each ligand also incorporates the ‘Induced Fit’ docking effect that helps to build further confidence in the shortlisted compounds. The method eventually is able to predict the potential inhibitors that bind to the active site and can potentially inhibit the activity of the Aminoglycoside 6′-N-acetyltransferase type Ib [AAC(6’)-Ib] from Klebsiella pneumoniae.

Methods:

Using the available three-dimensional structure of enzyme AAC(6')-Ib inhibitor complex, a structure-based virtual screening was performed with the hope of prioritizing the promising leads. In order to set up the protocol, 30,000 drug-like molecules were selected from the ChemBridge library. Multiple docking programs, i.e. UCSF DOCK6 and AutoDock Vina have been applied in the current study so that a consensus is developed to the predicted binding modes and thus the docking accuracy. The Amber scores of the Dock6 – a secondary scoring function was also used to perform the ‘Induced Fit’ effect and correspondingly re-rank the compounds.

Results:

The top 30 ranked compounds of the most frequent scored were selected from the histogram. The 2D interactions of those 30 compounds were drawn from the Ligplot+ tool. Six of the compounds were prioritized as potential inhibitors as they are representing the maximum number of interactions from the rest of the compounds and also possess the drug-likeness as predicted by the estimated ADMET properties.

Conclusion:

This study provided useful insight that the proposed compounds have the potential to bind to the aminoglycoside binding site of AAC(6′)-Ib that may eventually inhibit the Klebsiella pneumoniae. This study has the potential to propose putative new and novel inhibitors against a resistant drug target of Klebsiella pneumoniae.

In silico identification of mimicking molecule(s) triggering von Willebrand factor in human: a molecular drug target for regulating coagulation pathway

Blood coagulation is a complex and dynamic process wherein the body activates its emergency mechanism to stop bleeding and wound healing via the interactions of prothrombotic and antithrombotic agents. von Willebrand factor (VWF) is a complex glycoprotein and initial component of the hemostasis pathway which serves a multipurpose role in blood coagulation process. There are reports of various plants that contain several bioactive compounds possessing properties of inducing blood coagulation directly or indirectly. In the present study, efforts have been made to identify bioactive compounds that may play a significant role in regulation of the coagulation cascade by accelerating VWF and thus enhance the hemostasis process. An antidiuretic peptide drug, Desmopressin, works on VWF and releases them in circulation. Forty-seven compounds from different plant sources were screened through molecular docking, out of which two compounds, Emodin and Peruvianoside II, showed more binding affinity than the reference drug Desmopressin. Emodin and Peruvianoside II showed binding energies -7.2 and -7.0 kcal/mol, respectively, when docked with VWF, whereas Desmopressin displayed less binding energy (-6.9 kcal/mol). Emodin belongs to anthraquinone from Rumex hastasus and Peruvianoside II belongs to flavanone glycosides from Thevetia peruviana. The mimicking potential of top identified molecules with respect to the drug was confirmed through simulation analysis. Besides, the molecular dynamics simulation (MDS) study (for 20 ns) showed that the Peruvianoside II protein complex was energetically more stable than Emodin protein complex. Based on the results, Peruvianoside II possesses great potential and thus may be considered for development of drugs for hemostasis.