Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore‐based virtual screening,molecular docking and molecular dynamics studies

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore‐based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well‐validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB.     

Pharmacophore‐based virtual screening,molecular docking,molecular dynamics simulation,and biological evaluation for the discovery of novel BRD4 inhibitors

Bromodomain is a recognition module in the signal transduction of acetylated histone. BRD4, one of the bromodomain members, is emerging as an attractive therapeutic target for several types of cancer. Therefore, in this study, an attempt has been made to screen compounds from an integrated database containing 5.5 million compounds for BRD4 inhibitors using pharmacophore‐based virtual screening, molecular docking, and molecular dynamics simulations. As a result, two molecules of twelve hits were found to be active in bioactivity tests. Among the molecules, compound 5 exhibited potent anticancer activity, and the IC₅₀ values against human cancer cell lines MV4‐11, A375, and HeLa were 4.2, 7.1, and 11.6 μm , respectively. After that, colony formation assay, cell cycle, apoptosis analysis, wound‐healing migration assay, and Western blotting were carried out to learn the bioactivity of compound 5 .     

Structure‐based discovery of novel US28 small molecule ligands with different modes of action

The human cytomegalovirus‐encoded G protein‐coupled receptor US28 is a constitutively active receptor, which can recognize various chemokines. Despite the recent determination of its 2.9 Å crystal structure, potent and US28‐specific tool compounds are still scarce. Here, we used structural information from a refined US28:VUF2274 complex for virtual screening of >12 million commercially available small molecule compounds. Using a combined receptor‐ and ligand‐based approach, we tested 98 of the top 0.1% ranked compounds, revealing novel chemotypes as compared to the ~1.45 million known ligands in the ChEMBL database. Two compounds were confirmed as agonist and inverse agonist, respectively, in both IP accumulation and Ca²⁺ mobilization assays. The screening setup presented in this work is computationally inexpensive and therefore particularly useful in an academic setting as it enables simultaneous testing in binding as well as in different functional assays and/or species without actual chemical synthesis.     

Sequential virtual screening approach to the identification of small organic molecules as potential BACE-1 inhibitors

In this letter, we report on the sequential application of two different in silico screening approaches combined with bioassays aimed at the identification of small organic molecules as potential BACE-1 inhibitors. Two hits endowed of micromolar inhibitory potency were selected, and the binding mode of the most potent compound was further characterized through docking simulations.     

Identification of novel polo-like kinase 1 inhibitors by a hybrid virtual screening

Polo-like kinase 1 is an important and attractive oncological target that plays a key role in mitosis and cytokinesis. A combined pharmacophore- and docking-based virtual screening was performed to identify novel polo-like kinase 1 inhibitors. A total of 34 hit compounds were selected and tested in vitro, and some compounds showed inhibition of polo-like kinase 1 and human tumor cell growth. The most potent compound (66) inhibited polo-like kinase 1 with an IC(50) value of 6.99 μm. The docked binding models of two hit compounds were discussed in detail. These compounds contained novel chemical scaffolds and may be used as foundations for the development of novel classes of polo-like kinase 1 inhibitors.     

Identification of novel inhibitors of dipeptidylcarboxypeptidase of Leishmania donovani via ligand-based virtual screening and biological evaluation

Current treatment of leishmaniasis is based on chemotherapy, which relies on a handful of drugs with serious limitations, such as high cost, toxicity, and lack of efficacy in endemic regions. Therefore, development of new, effective, and affordable anti-leishmanial drugs is a global health priority. Dipeptidylcarboxypeptidase has been characterized and established as a drug target for antileishmanial drug discovery. We virtually screened a large chemical library of 15 452 compounds against a 3D model of dipeptidylcarboxypeptidase to identify novel inhibitors. The initial virtual screening using a ligand-based pharmacophore model identified 103 compounds. Forty-six compounds were shortlisted based on the docking scores and other scoring functions. Further, these compounds were subjected to biological assay, and four of them belonging to two chemical classes were identified as the lead compounds. Identification of these novel and chemically diverse inhibitors should provide leads to be optimized into candidates to treat these protozoan infections.     

Proposing novel MDM2 inhibitors: Combined physics‐driven high‐throughput virtual screening and in vitro studies

The mouse double minute 2 (MDM2) protein acts as a negative regulator of the p53 tumor suppressor. It directly binds to the N terminus of p53 and promotes p53 ubiquitination and degradation. Since the most common p53‐suppressing mechanisms involve the MDM2, proposing novel inhibitors has been the focus of many in silico and also experimental studies. Thus, here we screened around 500,000 small organic molecules from Enamine database at the binding pocket of this oncogenic target. The screening was achieved systematically with starting from the high‐throughput virtual screening method followed by more sophisticated docking approaches. The initial high number of screened molecules was reduced to 100 hits which then were studied extensively for their therapeutic activity and pharmacokinetic properties using binary QSAR models. The structural and dynamical profiles of the selected molecules at the binding pocket of the target were studied thoroughly by all‐atom molecular dynamics simulations. The free energy of the binding of the hit molecules was estimated by the MM/GBSA method. Based on docking simulations, binary QSAR model results, and free energy calculations, 11 compounds ( E1 – E11 ) were selected for in vitro studies. HUVEC vascular endothelium, colon cancer, and breast cancer cell lines were used for testing the binding affinities of the identified hits and for further cellular effects on human cancer cell. Based on in vitro studies, six compounds ( E1 , E2 , E5 , E6 , E9 , and E11 ) in breast cancer cell lines and six compounds ( E1 , E2 , E5 , E6 , E8 , and E10 ) in colon cancer cell lines were found as active. Our results showed that these compounds inhibit proliferation and lead to apoptosis.     

Identification of novel topoisomerase II alpha inhibitors by virtual screening,molecular docking,and bioassay

Breast cancer is one of the most common tumors, and its treatment still leaves room for improvement. Topoisomerase II alpha is a potential target for the treatment of human diseases such as breast cancer. In this article, we attempted to discover a novel anticancer drug. We have used the topoisomerase II alpha protein-Homo sapiens (Human) to hierarchically screen the Maybridge database. Based on their docking score, the top hit compounds have been assayed for inhibition in a topoisomerase II pBR322 DNA relaxation assay in vitro. Candidate compound 6 (CP6) was found to have the best inhibitory effect for topoisomerase II among the 20 tested compounds. In addition, CP6 had potent cytotoxicity against eight tested tumor cell lines. At the same time, CP6 was shown to have potential anti-multidrug resistance capabilities. This study identifies CP6, which can contribute to the development of new topoisomerase II inhibitors as anticancer agents.     

ENRI: A tool for selecting structure‐based virtual screening target conformations

Finding pharmaceutically relevant target conformations from an arbitrary set of protein conformations remains a challenge in structure‐based virtual screening (SBVS). The growth in the number of available conformations, either experimentally determined or computationally derived, obscures the situation further. While the inflated conformation space potentially contains viable druggable targets, the increase of conformational complexity, as a consequence, poses a selection problem. To address this challenge, we took advantage of machine learning methods, namely an over‐sampling and a binary classification procedure, and present a novel method to select druggable receptor conformations. Specifically, we trained a binary classifier on a set of nuclear receptor conformations, wherein each conformation was labeled with an enrichment measure for a corresponding SBVS. The classifier enabled us to formulate suggestions and identify enriching SBVS targets for six of seven nuclear receptors. Further, the classifier can be extended to other proteins of interest simply by feeding new training data sets to the classifier. Our work, thus, provides a methodology to identify pharmaceutically interesting receptor conformations for nuclear receptors and other drug targets.     

In silico screening and surface plasma resonance‐based verification of programmed death 1‐targeted peptides

Programmed death 1 (PD‐1) is a key immune checkpoint molecule. When it binds to programmed death‐ligand 1 (PD‐L1), it can negatively regulate the immune response. Therefore, blockade of the PD‐1/PD‐L1 interaction could unleash the power of immune system. Though successes achieved by anti‐PD‐1/PD‐L1 antibody drugs in clinical for various cancers, many intrinsic limitations of the high molecular weight drugs require alternatives such as peptide drugs and chemical compounds. In this study, we described a novel in silico approach which was used to screen peptides from PDB database and aimed to identify peptides that have potential to bind the PD‐L1 binding area of PD‐1 molecule. Based on the docking poses, eight peptides were synthesized and measured for their binding abilities by surface plasma resonance technique. The K_D values of the synthesized peptides ranged from 10.0 to 133.0 μM. Furthermore, the binding mechanism between PD‐1 and the peptides was studied. In conclusion, we established a fast and reliable screening method for peptide discovery, which could be applied for identifying peptide inhibitors of various targets. The synthesized peptides could be served as starting points for designing PD‐1 drug for cancer immunotherapy.     

Molecular docking-based virtual screening and dynamics simulation study of novel and potential SIRT7 inhibitors

In cancer cells, short for sirtuin (SIRT7) stabilizes the transformed state via its nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase activity. Epigenetic factor SIRT7 plays important roles in cancer biology, reversing cancer phenotypes and suppressing tumor growth when inactive. In the present study, we got the SIRT7 protein structure from Alpha Fold2 Database and performed structure-based virtual screening to develop specific SIRT7 inhibitors using the SIRT7 inhibitor 97,491 interaction mechanism. As candidates for specific SIRT7 inhibitors, compounds with high affinities to SIRT7 were chosen. ZINC000001910616 and ZINC000014708529, two of our leading compounds, showed strong interactions with SIRT7. Our MD simulation results also revealed that the 5-hydroxy-4H-thioxen-4-one group and terminal carboxyl group were critical groups responsible for interaction of small molecules with SIRT7. In our study, we demonstrated that targeting SIRT7 may offer novel therapeutic options for cancer treatment. Compounds ZINC000001910616 and ZINC000014708529 can serve as chemical probes to investigate SIRT7 biological functions and provide starting points for the development of novel therapeutics against cancers.     

Structure-based virtual screening approach to the discovery of novel inhibitors of eyes absent 2 phosphatase with various metal chelating moieties

Despite a series of persuasive experimental evidence for the involvement of eyes absent protein tyrosine phosphatases in various human cancers, no small-molecule inhibitor has been reported so far. We have identified seven novel inhibitors of eyes absent homologue 2 (Eya2) with IC(50) values ranging from 1 to 70 μm by the virtual screening with docking simulations and enzyme inhibition assay. Atomic charges of the active-site Mg(2+) ion complex are calculated to enhance the accuracy of docking simulations. The newly discovered inhibitors are structurally diverse and have various chelating groups for the Mg(2+) ion. The interactions with the amino acid residues responsible for the stabilizations of the inhibitors in the active site of Eya2 are addressed in detail.     

Structure‐based discovery of new selective small‐molecule sirtuin 5 inhibitors

Human sirtuin 5 (SIRT5) is a protein deacylase regulating metabolic pathways and stress responses and is implicated in metabolism‐related diseases. Small‐molecule inhibitors for SIRT5 are sought as chemical tools and potential therapeutics. Herein, we proposed a customized virtual screening approach targeting catalytically important and unique residues Tyr102 and Arg105 of SIRT5. Of the 20 tested virtual screening hits, six compounds displayed marked inhibitory activities against SIRT5. For the hit compound 19 , a series of newly synthesized (E)‐2‐cyano‐N‐phenyl‐3‐(5‐phenylfuran‐2‐yl)acrylamide derivatives/analogues were carried out structure–activity relationship analyses, resulting in new more potent inhibitors, among which 37 displayed the most potent inhibition to SIRT5 with an IC₅₀ value of 5.59 ± 0.75 μM. The biochemical studies revealed that 37 likely acts via competitive inhibition with the succinyl‐lysine substrate, rather than the NAD⁺ cofactor, and it manifested substantial selectivity for SIRT5 over SIRT2 and SIRT6. This study will aid further efforts to develop new selective SIRT5 inhibitors as tools and therapeutics.     

Identification of novel antilipogenic agents targeting fatty acid biosynthesis through structure‐based virtual screening

An Asinex Gold Platinium chemical library subset of 12 055 compounds was screened employing docking simulations in the active site of the human FAS KS domain. Among them, 13 compounds were further evaluated for their ability to inhibit fatty acid biosynthesis. Four compounds were found to be active in particular ASN05064661 and ASN05374526 with IC50 values of 6.6 and 10.5 μm , respectively. A binding mode study was further conducted with these two compounds structurally related to benzene sulfonamide and aromatic polyamide. This study showed that they fit tightly with the active site with several interactions, notably with the key residues Cys161, His293, and His331.     

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile.     

The discovery of novel vascular endothelial growth factor receptor tyrosine kinases inhibitors: pharmacophore modeling, virtual screening and docking studies

We have applied pharmacophore generation, database searching and docking methodologies to discover new structures for the design of vascular endothelial growth factor receptors, the tyrosine kinase insert domain-containing receptor kinase inhibitors. The chemical function based pharmacophore models were built for kinase insert domain-containing receptor kinase inhibitors from a set of 10 known inhibitors using the algorithm HipHop, which is implemented in the CATALYST software. The highest scoring HipHop model consists of four features: one hydrophobic, one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic function. Using the algorithm CatShape within CATALYST, the bound conformation of 4-amino-furo [2, 3-d] pyrimidine binding to kinase insert domain-containing receptor kinase was used to generate a shape query. A merged shape and hypothesis query that is in an appropriate alignment was then built. The combined shape and hypothesis model was used as a query to search Maybridge database for other potential lead compounds. A total of 39 compounds were retrieved as hits. The hits obtained were docked into kinase insert domain-containing receptor kinase active site. One novel potential lead was proposed based on CATALYST fit value, LigandFit docking scores, and examination of how the hit retain key interactions known to be required for kinase binding. This compound inhibited vascular endothelial growth factor stimulated kinase insert domain-containing receptor phosphorylation in human umbilical vein endothelial cells.     

Pharmacophore-based virtual screening and density functional theory approach to identifying novel butyrylcholinesterase inhibitors

Aim:

To identify the critical chemical features, with reliable geometric constraints, that contributes to the inhibition of butyrylcholinesterase (BChE) function.

Methods:

Ligand-based pharmacophore modeling was used to identify the critical chemical features of BChE inhibitors. The generated pharmacophore model was validated using various techniques, such as Fischer''s randomization method, test set, and decoy set. The best pharmacophore model was used as a query in virtual screening to identify novel scaffolds that inhibit BChE. Compounds selected by the best hypothesis in the virtual screening were tested for drug-like properties, and molecular docking study was applied to determine the optimal orientation of the hit compounds in the BChE active site. To find the reactivity of the hit compounds, frontier orbital analysis was carried out using density functional theory.

Results:

Based on its correlation coefficient (0.96), root mean square (RMS) deviation (1.01), and total cost (105.72), the quantitative hypothesis Hypo1 consisting of 2 HBA, 1 Hy-Ali, and 1 Hy-Ar was selected as the best hypothesis. Thus, Hypo1 was used as a 3D query in virtual screening of the Maybridge and Chembridge databases. The hit compounds were filtered using ADMET, Lipinski''s Rule of Five, and molecular docking to reduce the number of false positive results. Finally, 33 compounds were selected based on their critical interactions with the significant amino acids in BChE''s active site. To confirm the inhibitors'' potencies, the orbital energies, such as HOMO and LUMO, of the hit compounds and 7 training set compounds were calculated. Among the 33 hit compounds, 10 compounds with the highest HOMO values were selected, and this set was further culled to 5 compounds based on their energy gaps important for stability and energy transfer. From the overall results, 5 hit compounds were confirmed to be potential BChE inhibitors that satisfied all the pharmacophoric features in Hypo1.

Conclusion:

This study pinpoints important chemical features with geometric constraints that contribute to the inhibition of BChE activity. Five compounds are selected as the best hit BchE-inhibitory compounds.     

Ligand-based virtual screening and molecular docking studies to identify the critical chemical features of potent cathepsin D inhibitors

Cathepsin D is a major component of lysosomes and plays a major role in catabolism and degenerative diseases. The quantitative structure-activity relationship study was used to explore the critical chemical features of cathepsin D inhibitors. Top 10 hypotheses were built based on 36 known cathepsin D inhibitors using HypoGen/Discovery Studio v2.5. The best hypothesis Hypo1 consists of three hydrophobic, one hydrogen bond acceptor lipid, and one hydrogen bond acceptor features. The selected Hypo1 model was cross-validated using Fischer's randomization method to identify the strong correlation between experimental and predicted activity value as well as the test set and decoy sets used to validate its predictability. Moreover, the best hypothesis was used as a 3D query in virtual screening of Scaffold database. Subsequently, the screened hit molecules were filtered by applying Lipinski's rule of five, absorption, distribution, metabolism, and toxicity, and molecular docking studies. Finally, 49 compounds were obtained as potent cathepsin D inhibitors based on the consensus scoring values, critical interactions with protein active site residues, and predicted activity values. Thus, we suggest that the application of Hypo1 could assist in the selection of potent cathepsin D leads from various databases. Hence, this model was used as a valuable tool to design new candidate for cathepsin D inhibitors.     

Identification of Novel Selective Lysine‐Specific Demethylase 1 (LSD1) Inhibitors Using a Pharmacophore‐Based Virtual Screening Combined with Docking

Lysine‐specific demethylase 1 (LSD1) plays an important role in regulating the lysine methylation at residues K4 and K9 on histone H3. High levels of LSD1 expression have been observed in several malignant tumors. In this study, we presented a pharmacophore‐based virtual screening of a moderate database of 171 143 small molecules. A pharmacophore of LSD1 inhibitors was constructed for the first time and then used to screen the compound library combined with validated molecular docking tools followed by biochemical assays, led to the identification of 9 novel LSD1 inhibitors, showing their IC₅₀ values in a range of 2.41–101 μm . Furthermore, compound XZ 09 exhibited less inhibition against the homologous monoamine oxidase A (MAO‐A) and B (MAO‐B) displaying its moderate selectivity. Our study provides an effective virtual screening method to identify new LSD1 inhibitors and XZ09 represents a potent and selective lead compound to deserve further optimization for the treatment of LSD1 overexpressing cancers.