Virtual screening: an in silico tool for interlacing the chemical universe with the proteome

Computer-Aided Strategy on 5-(Substituted benzylidene) Thiazolidine-2,4-Diones to Develop New and Potent PTP1B Inhibitors: QSAR Modeling, Molecular Docking, Molecular Dynamics, PASS Predictions, and DFT Investigations

A set of 5-(substituted benzylidene) thiazolidine-2,4-dione derivatives was explored to study the main structural requirement for the design of protein tyrosine phosphatase 1B (PTP1B) inhibitors. Utilizing multiple linear regression (MLR) analysis, we constructed a robust quantitative structure-activity relationship (QSAR) model to predict inhibitory activity, resulting in a noteworthy correlation coefficient (R2) of 0.942. Rigorous cross-validation using the leave-one-out (LOO) technique and statistical parameter calculations affirmed the model's reliability, with the QSAR analysis revealing 10 distinct structural patterns influencing PTP1B inhibitory activity. Compound 7e(ref) emerged as the optimal scaffold for drug design. Seven new PTP1B inhibitors were designed based on the QSAR model, followed by molecular docking studies to predict interactions and identify structural features. Pharmacokinetics properties were assessed through drug-likeness and ADMET studies. After that density functional theory (DFT) was conducted to assess the stability and reactivity of potential diabetes mellitus drug candidates. The subsequent dynamic simulation phase provided additional insights into stability and interactions dynamics of the top-ranked compound 11c. This comprehensive approach enhances our understanding of potential drug candidates for treating diabetes mellitus.

A combined in silico approaches of 2D-QSAR, molecular docking, molecular dynamics and ADMET prediction of anti-cancer inhibitor activity for actinonin derivatives

Inhibition of human mitochondrial peptide deformylase (HsPDF) plays a major role in reducing growth, proliferation, and cellular cancer survival. In this work, a series of 32 actinonin derivatives for HsPDF (PDB: 3G5K) inhibitor's anticancer activity was computationally analyzed for the first time, using an in silico study considering 2D-QSAR modeling, and molecular docking studies, and validated by molecular dynamics and ADMET properties. The results of multilinear regression (MLR) and artificial neural networks (ANN) statistical analysis reveal a good correlation between pIC50 activity and the seven (7) descriptors. The developed models were highly significant with cross-validation, the Y-randomization test and their applicability range. In addition, all considered data sets show that the AC30 compound, exhibits the best binding affinity (docking score = -212.074 kcal/mol and H-bonding energy = -15.879 kcal/mol). Furthermore, molecular dynamics simulations were performed at 500 ns, confirming the stability of the studied complexes under physiological conditions and validating the molecular docking results. Five selected actinonin derivatives (AC1, AC8, AC15, AC18 and AC30), exhibiting best docking score, were rationalized as potential leads for HsPDF inhibition, in well agreement with experimental outcomes. Furthermore, based on the in silico study, new six molecules (AC32, AC33, AC34, AC35, AC36 and AC37) were suggested as HsPDF inhibition candidates, which would be combined with in-vitro and in-vivo studies to perspective validation of their anticancer activity. Indeed, the ADMET predictions indicate that these six new ligands have demonstrated a fairly good drug-likeness profile.

Phenotypic and in silico studies for a series of synthetic thiosemicarbazones as New Delhi metallo-beta-lactamase carbapenemase inhibitors

The past two decades have been marked by a global spread of bacterial resistance to β-lactam drugs and carbapenems derivatives are the ultimate treatment against multidrug-resistant bacteria. β-lactamase expression is related to resistance which demands the development of bacterial resistance blockers. Drug inhibitor combinations of serine-β-lactamase and β-lactam were successful employed in therapy despite their inactivity against New Delhi metallo-beta-lactamase (NDM). Until now, few compounds are active against NDM-producing bacteria and no specific inhibitors are available yet. The rational strategy for NDM inhibitors development starts with in vitro assays aiming to seek compounds that could act synergistically with β-lactam antibiotics. Thus, eight thiosemicarbazone derivatives were synthesized and investigated for their ability to reverse the resistant phenotype in NDM in Enterobacter cloacae. Phenotypic screening indicated that four isatin-beta-thiosemicarbazones showed Fractional Inhibitory Concentration (FIC) ≤ 250 µM in the presence of meropenem (4 µg/mL). The most promising compound (FIC= 31.25 µM) also presented synergistic effect (FICI = 0.34). Docking and molecular dynamics studies on NDM-thiosemicarbazone complex suggested that 2,3-dihydro-1H-indol-2-one subunit interacts with catalytic zinc and interacted through hydrogen bonds with Asp124 acting like a carboxylic acid bioisostere. Additionally, thiosemicarbazone tautomer with oxidized sulfur (thione) seems to act as a spacer rather than zinc chelator, and the aromatic moieties are stabilized by pi-pi and cation-pi interactions with His189 and Lys221 residues. Our results addressed some thiosemicarbazone structural changes to increase its biological activity against NDM and highlight its scaffold as promising alternatives to treat bacterial resistance.Communicated by Ramaswamy H. Sarma.

Mono-n-butyl Malate-Derived Compounds from Camu-camu (Myrciaria dubia) Malic Acid: The Alkyl-Dependent Antihyperglycemic-Related Activity

Malic acid derivatives from camu-camu (Myrciaria dubia) fruit exhibited a strong in vitro inhibitory activity toward pancreatic α-amylase and α-glucosidase enzymes. During a bioguided chromatographic fractionation process of the whole fruit (pulp and peelings) polar extract, isomers (S)-4-butoxy-2-hydroxy-4-oxobutanoic acid (1) and (S)-4-butoxy-3-hydroxy-4-oxobutanoic acid (2) (84:16) were isolated and identified as a potent inhibitor of α-amylase (IC₅₀= 11.69 ± 1.75 μg/mL) and α-glucosidase (IC₅₀ = 102.69 ± 4.16 μg/mL). The chemical structures were confirmed by HPLC-ESIMS and ¹H and ¹³C NMR (one- and two-dimensional) analyses. The structure-based virtual screening demonstrated that the aliphatic moiety plays a significant role in the binding mode of the test alkyl malate esters. Compound 1 exhibited the best interaction profile to bind both enzymes, having key structural features to form relevant contacts by involving adequate enzyme-ligand complex stabilization and compactness over time.

Antifungal activity of linalool against fluconazole-resistant clinical strains of vulvovaginal Candida albicans and its predictive mechanism of action

Candida albicans is the most frequently isolated opportunistic pathogen in the female genital tract, with 92.3% of cases in Brazil associated with vulvovaginal candidiasis (VVC). Linalool is a monoterpene compound from plants of the genera Cinnamomum, Coriandrum, Lavandula, and Citrus that has demonstrated a fungicidal effect on strains of Candida spp., but its mechanism of action is still unknown. For this purpose, broth microdilution techniques were applied, as well as molecular docking in a predictive manner for this mechanism. The main results of this study indicated that the C. albicans strains analyzed were resistant to fluconazole and sensitive to linalool at a dose of 256 µg/mL. Furthermore, the increase in the minimum inhibitory concentration (MIC) of linalool in the presence of sorbitol and ergosterol indicated that this molecule possibly affects the cell wall and plasma membrane integrity of C. albicans. Molecular docking of linalool with proteins that are key in the biosynthesis and maintenance of the cell wall and the fungal plasma membrane integrity demonstrated the possibility of linalool interacting with three important enzymes: 1,3-β-glucan synthase, lanosterol 14α-demethylase, and Δ 14-sterol reductase. In silico analysis showed that this monoterpene has theoretical but significant oral bioavailability, low toxic potential, and high similarity to pharmaceuticals. Therefore, the findings of this study indicated that linalool probably causes damage to the cell wall and plasma membrane of C. albicans, possibly by interaction with important enzymes involved in the biosynthesis of these fungal structures, in addition to presenting low in silico toxic potential.

Identification of Potential Cytochrome P450 3A5 Inhibitors: An Extensive Virtual Screening through Molecular Docking, Negative Image-Based Screening, Machine Learning and Molecular Dynamics Simulation Studies

Cytochrome P450 3A5 (CYP3A5) is one of the crucial CYP family members and has already proven to be an important drug target for cardiovascular diseases. In the current study, the PubChem database was screened through molecular docking and high-affinity molecules were adopted for further assessment. A negative image-based (NIB) model was used for a similarity search by considering the complementary shape and electrostatics of the target and small molecules. Further, the molecules were segregated into active and inactive groups through six machine learning (ML) matrices. The active molecules found in each ML model were used for in silico pharmacokinetics and toxicity assessments. A total of five molecules followed the acceptable pharmacokinetics and toxicity profiles. Several potential binding interactions between the proposed molecules and CYP3A5 were observed. The dynamic behavior of the selected molecules in the CYP3A5 was explored through a molecular dynamics (MD) simulation study. Several parameters obtained from the MD simulation trajectory explained the stability of the protein–ligand complexes in dynamic states. The high binding affinity of each molecule was revealed by the binding free energy calculation through the MM-GBSA methods. Therefore, it can be concluded that the proposed molecules might be potential CYP3A5 molecules for therapeutic application in cardiovascular diseases subjected to in vitro/in vivo validations.

Virtual Screening of Drug-Like Compounds as Potential Inhibitors of the Dengue Virus NS5 Protein

Dengue virus (DENV) is the causative agent of dengue fever. Annually, there are about 400 million new cases of dengue worldwide, and so far there is no specific treatment against this disease. The NS5 protein is the largest and most conserved viral protein among flaviviruses and is considered a therapeutic target of great interest. This study aims to search drug-like compounds for possible inhibitors of the NS5 protein in the four serotypes of DENV. Using a virtual screening from a ∼642,759-compound database, we suggest 18 compounds with NS5 binding and highlight the best compound per region, in the methyltransferase and RNA-dependent RNA polymerase domains. These compounds interact mainly with the amino acids of the catalytic sites and/or are involved in processes of protein activity. The identified compounds presented physicochemical and pharmacological properties of interest for their use as possible drugs; furthermore, we found that some of these compounds do not affect cell viability in Huh-7; therefore, we suggest evaluating these compounds in vitro as candidates in future research.

The Compound (E)-2-Cyano-N,3-diphenylacrylamide (JMPR-01): A Potential Drug for Treatment of Inflammatory Diseases

The compound (E)-2-cyano-N,3-diphenylacrylamide (JMPR-01) was structurally developed using bioisosteric modifications of a hybrid prototype as formed from fragments of indomethacin and paracetamol. Initially, in vitro assays were performed to determine cell viability (in macrophage cultures), and its ability to modulate the synthesis of nitrite and cytokines (IL-1β and TNFα) in non-cytotoxic concentrations. In vivo, anti-inflammatory activity was explored using the CFA-induced paw edema and zymosan-induced peritonitis models. To investigate possible molecular targets, molecular docking was performed with the following crystallographic structures: LT-A4-H, PDE4B, COX-2, 5-LOX, and iNOS. As results, we observed a significant reduction in the production of nitrite and IL-1β at all concentrations used, and also for TNFα with JMPR-01 at 50 and 25 μM. The anti-edematogenic activity of JMPR-01 (100 mg/kg) was significant, reducing edema at 2-6 h, similar to the dexamethasone control. In induced peritonitis, JMPR-01 reduced leukocyte migration by 61.8, 68.5, and 90.5% at respective doses of 5, 10, and 50 mg/kg. In silico, JMPR-01 presented satisfactory coupling; mainly with LT-A4-H, PDE4B, and iNOS. These preliminary results demonstrate the strong potential of JMPR-01 to become a drug for the treatment of inflammatory diseases.

18:0 Lyso PC, a natural product with potential PPAR-γ agonistic activity, plays hypoglycemic effect with lower liver toxicity and cardiotoxicity in db/db mice

Rosiglitazone, a specific agonist of peroxisome proliferator-activated receptor-γ (PPAR-γ), displays a robust hypoglycemic action in patients with type 2 diabetes mellitus (T2DM) and elicits serious adverse reactions, especially hepatotoxicity and cardiotoxicity. Here, we aims to find a new natural PPAR-γ agonist with less adverse reactions than rosiglitazone in db/db mice. The method of virtual screening was used to identify a PPAR-γ agonist 18:0 Lyso PC from an in-house natural product library. We verified its pharmacological effects and adverse reactions comparing with rosiglitazone in vivo and in vitro. 18:0 Lyso PC exhibited pharmacological effects similar to those of rosiglitazone in db/db mice. Moreover, 18:0 Lyso PC showed a lower extent of liver injury and cardiotoxicity in db/db mice. The mechanism, by which this natural compound alleviates metabolic syndrome, involves a reduction in fatty acid synthesis mediated by activation of the phosphorylation of adenosine 5'-monophosphate (AMP)-activated protein kinase-alpha (AMPKα) and acetyl-CoA carboxylase (ACC) and an increase expression of uncoupled protein 1 (UCP1) and PPAR-γ coactivator-1 alpha (PGC1-α). 18:0 Lyso PC, a natural compound, can show a similar hypoglycemic effect to rosiglitazone by activating PPAR-γ, while eliciting markedly fewer adverse reactions than rosiglitazone.

Novel Mechanism for an Old Drug: Phenazopyridine is a Kinase Inhibitor Affecting Autophagy and Cellular Differentiation

Phenazopyridine is a widely used drug against urinary tract pain. The compound has also been shown to enhance neural differentiation of pluripotent stem cells. However, its mechanism of action is not understood. Based on its chemical structure, we hypothesized that phenazopyridine could be a kinase inhibitor. Phenazopyridine was investigated in the following experimental systems: 1) activity of kinases in pluripotent stem cells; 2) binding to recombinant kinases, and 3) functional impact on pluripotent stem cells. Upon addition to pluripotent stem cells, phenazopyridine induced changes in kinase activities, particularly involving Mitogen-Activated Protein Kinases, Cyclin-Dependent Kinases, and AKT pathway kinases. To identify the primary targets of phenazopyridine, we screened its interactions with 401 human kinases. Dose-inhibition curves showed that three of these kinases interacted with phenazopyridine with sub-micromolar binding affinities: cyclin-G-associated kinase, and the two phosphatidylinositol kinases PI4KB and PIP4K2C, the latter being known for participating in pain induction. Docking revealed that phenazopyridine forms strong H-bonds with the hinge region of the ATP-binding pocket of these kinases. As previous studies suggested increased autophagy upon inhibition of the phosphatidyl-inositol/AKT pathway, we also investigated the impact of phenazopyridine on this pathway and found an upregulation. In conclusion, our study demonstrates for the first time that phenazopyridine is a kinase inhibitor, impacting notably phosphatidylinositol kinases involved in nociception.

QSAR, molecular docking and ADMET properties in silico studies of novel 4,5,6,7-tetrahydrobenzo[D]-thiazol-2-Yl derivatives derived from dimedone as potent anti-tumor agents through inhibition of C-Met receptor tyrosine kinase

A quantitative structure-activity relationship (QSAR) study is performed on 48 novel 4,5,6,7-tetrahydrobenzo[D]-thiazol-2 derivatives as anticancer agents capable of inhibiting c-Met receptor tyrosine kinase. The present study is conducted using multiple linear regression, multiple nonlinear regression and artificial neural networks. Three QSAR models are developed after partitioning the database into two sets (training and test) via the k-means method. The obtained values of the correlation coefficients by the three developed QSAR models are 0.90, 0.91 and 0.92, respectively. The resulting models are validated by using the external validation, leave-one-out cross-validation, Y-randomization test, and applicability domain methods. Moreover, we evaluated the drug-likeness properties of seven selected molecules based on their observed high activity to inhibit the c-Met receptor. The results of the evaluation showed that three of the seven compounds present drug-like characteristics. In order to identify the important active sites for the inhibition of the c-Met receptor responsible for the development of cancer cell lines, the crystallized form of the Crizotinib-c-Met complex (PDB code: 2WGJ) is used. These sites are used as references in the molecular docking test of the three selected molecules to identify the most suitable molecule for use as a new c-Met inhibitor. A comparative study is conducted based on the evaluation of the predicted properties of ADMET in silico between the candidate molecule and the Crizotinib inhibitor. The comparison results show that the selected molecule can be used as new anticancer drug candidates.

From Conception to Development: Investigating PROTACs Features for Improved Cell Permeability and Successful Protein Degradation

Proteolysis Targeting Chimeras (PROTACs) are heterobifunctional degraders that specifically eliminate targeted proteins by hijacking the ubiquitin-proteasome system (UPS). This modality has emerged as an orthogonal approach to the use of small-molecule inhibitors for knocking down classic targets and disease-related proteins classified, until now, as "undruggable." In early 2019, the first targeted protein degraders reached the clinic, drawing attention to PROTACs as one of the most appealing technology in the drug discovery landscape. Despite these promising results, PROTACs are often affected by poor cellular permeability due to their high molecular weight (MW) and large exposed polar surface area (PSA). Herein, we report a comprehensive record of PROTAC design, pharmacology and thermodynamic challenges and solutions, as well as some of the available strategies to enhance cellular uptake, including suggestions of promising biological tools for the in vitro evaluation of PROTACs permeability toward successful protein degradation.

Evaluation of potential MHC-I allele-specific epitopes in Zika virus proteins and the effects of mutations on peptide-MHC-I interaction studied using in silico approaches

Zika virus (ZIKV) infection is a global health concern due to its association with microcephaly and neurological complications. The development of a T-cell vaccine is important to combat this disease. In this study, we propose ZIKV major histocompatibility complex I (MHC-I) epitopes based on in silico screening consensus followed by molecular docking, PRODIGY, and molecular dynamics (MD) simulation analyses. The effects of the reported mutations on peptide-MHC-I (pMHC-I) complexes were also evaluated. In general, our data indicate an allele-specific peptide-binding human leukocyte antigen (HLA) and potential epitopes. For HLA-B44, we showed that the absence of acidic residue Glu at P2, due to the loss of the electrostatic interaction with Lys45, has a negative impact on the pMHC-I complex stability and explains the low free energy estimated for the immunodominant peptide E-4 (IGVSNRDFV). Our MD data also suggest the deleterious effects of acidic residue Asp at P1 on the pMHC-I stability of HLA-B8 due to destabilization of the α-helix and β-strand. Free energy estimation further indicated that the mutation from Val to Ala at P9 of peptide E-247 (DAHAKRQTV), which was found exclusively in microcephaly samples, did not reduce HLA-B8 affinity. In contrast, the mutation from Thr to Pro at P2 of the peptide NS5-832 (VTKWTDIPY) decreased the interaction energy, number of intermolecular interactions, and adversely affected its binding mode with HLA-A1. Overall, our findings are important with regard to the design of T-cell peptide vaccines and for understanding how ZIKV escapes recognition by CD8 + T-cells.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

An ABSINTH-Based Protocol for Predicting Binding Affinities between Proteins and Small Molecules

The core task in computational drug discovery is to accurately predict binding free energies in receptor-ligand systems for large libraries of putative binders. Here, the ABSINTH implicit solvent model and force field are extended to describe small, organic molecules and their interactions with proteins. We show that an automatic pipeline based on partitioning arbitrary molecules into substructures corresponding to model compounds with known free energies of solvation can be combined with the CHARMM general force field into a method that is successful at the two important challenges a scoring function faces in virtual screening work flows: it ranks known binders with correlation values rivaling that of comparable state-of-the-art methods and it enriches true binders in a set of decoys. Our protocol introduces innovative modifications to common virtual screening workflows, notably the use of explicit ions as competitors and the integration over multiple protein and ligand species differing in their protonation states. We demonstrate the value of modifications to both the protocol and ABSINTH itself. We conclude by discussing the limitations of high-throughput implicit methods such as the one proposed here.

Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches

Virtual screening (VS) is an outstanding cornerstone in the drug discovery pipeline. A variety of computational approaches, which are generally classified as ligand-based (LB) and structure-based (SB) techniques, exploit key structural and physicochemical properties of ligands and targets to enable the screening of virtual libraries in the search of active compounds. Though LB and SB methods have found widespread application in the discovery of novel drug-like candidates, their complementary natures have stimulated continued efforts toward the development of hybrid strategies that combine LB and SB techniques, integrating them in a holistic computational framework that exploits the available information of both ligand and target to enhance the success of drug discovery projects. In this review, we analyze the main strategies and concepts that have emerged in the last years for defining hybrid LB + SB computational schemes in VS studies. Particularly, attention is focused on the combination of molecular similarity and docking, illustrating them with selected applications taken from the literature.

How 'Protein-Docking' Translates into the New Emerging Field of Docking Small Molecules to Nucleic Acids?

In this review, we retraced the '40-year evolution' of molecular docking algorithms. Over the course of the years, their development allowed to progress from the so-called 'rigid-docking' searching methods to the more sophisticated 'semi-flexible' and 'flexible docking' algorithms. Together with the advancement of computing architecture and power, molecular docking's applications also exponentially increased, from a single-ligand binding calculation to large screening and polypharmacology profiles. Recently targeting nucleic acids with small molecules has emerged as a valuable therapeutic strategy especially for cancer treatment, along with bacterial and viral infections. For example, therapeutic intervention at the mRNA level allows to overcome the problematic of undruggable proteins without modifying the genome. Despite the promising therapeutic potential of nucleic acids, molecular docking programs have been optimized mostly for proteins. Here, we have analyzed literature data on nucleic acid to benchmark some of the widely used docking programs. Finally, the comparison between proteins and nucleic acid targets docking highlighted similarity and differences, which are intrinsically related to their chemical and structural nature.

Identification of Selective Novel Hits against Plasmodium falciparum Prolyl tRNA Synthetase Active Site and a Predicted Allosteric Site Using in silico Approaches

Recently, there has been increased interest in aminoacyl tRNA synthetases (aaRSs) as potential malarial drug targets. These enzymes play a key role in protein translation by the addition of amino acids to their cognate tRNA. The aaRSs are present in all Plasmodium life cycle stages, and thus present an attractive malarial drug target. Prolyl tRNA synthetase is a class II aaRS that functions in charging tRNA with proline. Various inhibitors against Plasmodium falciparum ProRS (PfProRS) active site have been designed. However, none have gone through clinical trials as they have been found to be highly toxic to human cells. Recently, a possible allosteric site was reported in PfProRS with two possible allosteric modulators: glyburide and TCMDC-124506. In this study, we sought to identify novel selective inhibitors targeting PfProRS active site and possible novel allosteric modulators of this enzyme. To achieve this, virtual screening of South African natural compounds against PfProRS and the human homologue was carried out using AutoDock Vina. The modulation of protein motions by ligand binding was studied by molecular dynamics (MD) using the GROningen MAchine for Chemical Simulations (GROMACS) tool. To further analyse the protein global motions and energetic changes upon ligand binding, principal component analysis (PCA), and free energy landscape (FEL) calculations were performed. Further, to understand the effect of ligand binding on the protein communication, dynamic residue network (DRN) analysis of the MD trajectories was carried out using the MD-TASK tool. A total of ten potential natural hit compounds were identified with strong binding energy scores. Binding of ligands to the protein caused observable global and residue level changes. Dynamic residue network calculations showed increase in betweenness centrality (BC) metric of residues at the allosteric site implying these residues are important in protein communication. A loop region at the catalytic domain between residues 300 and 350 and the anticodon binding domain showed significant contributions to both PC1 and PC2. Large motions were observed at a loop in the Z-domain between residues 697 and 710 which was also in agreement with RMSF calculations that showed increase in flexibility of residues in this region. Residues in this loop region are implicated in ATP binding and thus a change in dynamics may affect ATP binding affinity. Free energy landscape (FEL) calculations showed that the holo protein (protein-ADN complex) and PfProRS-SANC184 complexes were stable, as shown by the low energy with very few intermediates and hardly distinguishable low energy barriers. In addition, FEL results agreed with backbone RMSD distribution plots where stable complexes showed a normal RMSD distribution while unstable complexes had multimodal RMSD distribution. The betweenness centrality metric showed a loss of functional importance of key ATP binding site residues upon allosteric ligand binding. The deep basins in average L observed at the allosteric region imply that there is high accessibility of residues at this region. To further analyse BC and average L metrics data, we calculated the ΔBC and ΔL values by taking each value in the holo protein BC or L matrix less the corresponding value in the ligand-bound complex BC or L matrix. Interestingly, in allosteric complexes, residues located in a loop region implicated in ATP binding had negative ΔL values while in orthosteric complexes these residues had positive ΔL values. An increase in contact frequency between residues Ser263, Thr267, Tyr285, and Leu707 at the allosteric site and residues Thr397, Pro398, Thr402, and Gln395 at the ATP binding TXE loop was observed. In summary, this study identified five potential orthosteric inhibitors and five allosteric modulators against PfProRS. Allosteric modulators changed ATP binding site dynamics, as shown by RMSF, PCA, and DRN calculations. Changes in dynamics of the ATP binding site and increased contact frequency between residues at the proposed allosteric site and the ATP binding site may explain how allosteric modulators distort the ATP binding site and thus might inhibit PfProRS. The scaffolds of the identified hits in the study can be used as a starting point for antimalarial inhibitor development with low human cytotoxicity.

Virtual screening web servers: designing chemical probes and drug candidates in the cyberspace

The interplay between life sciences and advancing technology drives a continuous cycle of chemical data growth; these data are most often stored in open or partially open databases. In parallel, many different types of algorithms are being developed to manipulate these chemical objects and associated bioactivity data. Virtual screening methods are among the most popular computational approaches in pharmaceutical research. Today, user-friendly web-based tools are available to help scientists perform virtual screening experiments. This article provides an overview of internet resources enabling and supporting chemical biology and early drug discovery with a main emphasis on web servers dedicated to virtual ligand screening and small-molecule docking. This survey first introduces some key concepts and then presents recent and easily accessible virtual screening and related target-fishing tools as well as briefly discusses case studies enabled by some of these web services. Notwithstanding further improvements, already available web-based tools not only contribute to the design of bioactive molecules and assist drug repositioning but also help to generate new ideas and explore different hypotheses in a timely fashion while contributing to teaching in the field of drug development.

Identification of Anti-Mycobacterium and Anti-Legionella Compounds With Potential Distinctive Structural Scaffolds From an HD-PBL Using Phenotypic Screens in Amoebae Host Models

Tubercular Mycobacteria and Legionella pneumophila are the causative agents of potentially fatal respiratory diseases due to their intrinsic pathogenesis but also due to the emergence of antibiotic resistance that limits treatment options. The aim of our study was to explore the antimicrobial activity of a small ligand-based chemical library of 1255 structurally diverse compounds. These compounds were screened in a combination of three assays, two monitoring the intracellular growth of the pathogenic bacteria, Mycobacterium marinum and L. pneumophila, and one assessing virulence of M. marinum. We set up these assays using two amoeba strains, the genetically tractable social amoeba Dictyostelium discoideum and the free-living amoeba Acanthamoeba castellanii. In summary, 64 (5.1%) compounds showed anti-infective/anti-virulence activity in at least one of the three assays. The intracellular assays hit rate varied between 1.7% (n = 22) for M. marinum and 2.8% (n = 35) for L. pneumophila with seven compounds in common for both pathogens. In parallel, 1.2% (n = 15) of the tested compounds were able to restore D. discoideum growth in the presence of M. marinum spiked in a lawn of food bacteria. We also validated the generality of the hits identified in the A. castellanii–M. marinum anti-infective screen using the D. discoideum–M. marinum host–pathogen model. The characterization of anti-infective and antibacterial hits in the latter infection model revealed compounds able to reduce intracellular growth more than 50% at 30 μM. Moreover, the chemical space and physico-chemical properties of the anti-M. marinum hits were compared to standard and candidate Mycobacterium tuberculosis (Mtb) drugs using ChemGPS-NP. A principle component analysis identified separate clusters for anti-M. marinum and anti-L. pneumophila hits unveiling the potentially new physico-chemical properties of these hits compared to standard and candidate M. tuberculosis drugs. Our studies underscore the relevance of using a combination of low-cost and low-complexity assays with full 3R compliance in concert with a rationalized focused library of compounds to identify new chemical scaffolds and to dissect some of their properties prior to taking further steps toward compound development.

Discrimination of Naturally-Occurring 2-Arylbenzofurans as Cyclooxygenase-2 Inhibitors: Insights into the Binding Mode and Enzymatic Inhibitory Activity

2-arylbenzofuran-containing compounds are chemical entities that can be naturally produced by several organisms. A wide-range of activities is described for several compounds of this kind and they are, therefore, valuable moieties for a lead finding from nature. Although there are in-vitro data about the activity of 2-arylbenzofuran-related compounds against cyclooxygenase (COX) enzymes, the molecular level of these COX-inhibiting constituents had not been deeply explored. Thus, 58 2-arylbenzofurans were initially screened through molecular docking within the active site of nine COX-2 crystal structures. The resulting docking scores were statistically analyzed and good reproducibility and convergence were found to discriminate the best-docked compounds. Discriminated compounds exhibited the best performance in molecular dynamics simulations as well as the most-favorable binding energies and the lowest in-vitro IC₅₀ values for COX-2 inhibition. A three-dimensional quantitative activity-structure relationship (3D-QSAR) was also demonstrated, which showed some crucial structural requirements for enhanced enzyme inhibition. Therefore, four hits are proposed as lead structures for the development of COX-2 inhibitors based on 2-arylbenzofurans in further studies.

Dihydroquinoline derivative as a potential anticancer agent: synthesis, crystal structure, and molecular modeling studies

Cancer is one of the leading causes of death worldwide and requires intense and growing research investments from the public and private sectors. This is expected to lead to the development of new medicines. A determining factor in this process is the structural understanding of molecules with potential anticancer properties. Since the major compounds used in cancer therapies fail to encompass every spectrum of this disease, there is a clear need to research new molecules for this purpose. As it follows, we have studied the class of quinolinones that seem effective for such therapy. This paper describes the structural elucidation of a novel dihydroquinoline by single-crystal X-ray diffraction and spectroscopy characterization. Topology studies were carried through Hirshfeld surfaces analysis and molecular electrostatic potential map; electronic stability was evaluated from the calculated energy of frontier molecular orbitals. Additionally, in silico studies by molecular docking indicated that this dihydroquinoline could act as an anticancer agent due to their higher binding affinity with human aldehyde dehydrogenase 1A1 (ALDH 1A1). Tests in vitro were performed for VERO (normal human skin keratinocytes), B16F10 (mouse melanoma), and MDA-MB-231 (metastatic breast adenocarcinoma), and the results certified that compound as a potential anticancer agent. A Dihydroquinoline derivative was tested against three cancer cell lines and the results attest that compound as potential anticancer agent.

Indole-Containing Phytoalexin-Based Bioisosteres as Antifungals: In Vitro and In Silico Evaluation against Fusarium oxysporum

There is a continuous search for more reliable and effective alternatives to control phytopathogens through different strategies. In this context, indole-containing phytoalexins are stimuli-induced compounds implicated in plant defense against plant pathogens. However, phytoalexins' efficacy have been limited by fungal detoxifying mechanisms, thus, the research on bioisosteres-based analogs can be a friendly alternative regarding the control of Fusarium phytopathogens, but there are currently few studies on it. Thus, as part of our research on antifungal agents, a set of 21 synthetic indole-containing phytoalexin analogs were evaluated as inhibitors against the phyopathogen Fusarium oxysporum. Results indicated that analogs of the N,N-dialkylthiourea, N,S-dialkyldithiocarbamate and substituted-1,3-thiazolidin-5-one groups exhibited the best docking scores and interaction profiles within the active site of Fusarium spp. enzymes. Vina scores exhibited correlation with experimental mycelial growth inhibition using supervised statistics, and this antifungal dataset correlated with molecular interaction fields after CoMFA. Compound 24 (tert-butyl (((3-oxo-1,3-diphenylpropyl)thio)carbonothioyl)-l-tryptophanate), a very active analog against F. oxysporum, exhibited the best interaction with lanosterol 14α-demethylase according to molecular docking, molecular dynamics and molecular mechanic/poisson-boltzmann surface area (MM/PBSA) binding energy performance. After data analyses, information on mycelial growth inhibitors, structural requirements and putative enzyme targets may be used in further antifungal development based on phytoalexin analogs for controlling phytopathogens.

South African Abietane Diterpenoids and Their Analogs as Potential Antimalarials: Novel Insights from Hybrid Computational Approaches

The hemoglobin degradation process in Plasmodium parasites is vital for nutrient acquisition required for their growth and proliferation. In P. falciparum, falcipains (FP-2 and FP-3) are the major hemoglobinases, and remain attractive antimalarial drug targets. Other Plasmodium species also possess highly homologous proteins to FP-2 and FP-3. Although several inhibitors have been designed against these proteins, none has been commercialized due to associated toxicity on human cathepsins (Cat-K, Cat-L and Cat-S). Despite the two enzyme groups sharing a common structural fold and catalytic mechanism, distinct active site variations have been identified, and can be exploited for drug development. Here, we utilize in silico approaches to screen 628 compounds from the South African natural sources to identify potential hits that can selectively inhibit the plasmodial proteases. Using docking studies, seven abietane diterpenoids, binding strongly to the plasmodial proteases, and three additional analogs from PubChem were identified. Important residues involved in ligand stabilization were identified for all potential hits through binding pose analysis and their energetic contribution determined by binding free energy calculations. The identified compounds present important scaffolds that could be further developed as plasmodial protease inhibitors. Previous laboratory assays showed the effect of the seven diterpenoids as antimalarials. Here, for the first time, we demonstrate that their possible mechanism of action could be by interacting with falcipains and their plasmodial homologs. Dynamic residue network (DRN) analysis on the plasmodial proteases identified functionally important residues, including a region with high betweenness centrality, which had previously been proposed as a potential allosteric site in FP-2.

Computational Drug Repurposing: Current Trends

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Biomedical discovery has been reshaped upon the exploding digitization of data which can be retrieved from a number of sources, ranging from clinical pharmacology to cheminformatics-driven databases. Now, supercomputing platforms and publicly available resources such as biological, physicochemical, and clinical data, can all be integrated to construct a detailed map of signaling pathways and drug mechanisms of action in relation to drug candidates. Recent advancements in computer-aided data mining have facilitated analyses of ‘big data’ approaches and the discovery of new indications for pre-existing drugs has been accelerated. Linking gene-phenotype associations to predict novel drug-disease signatures or incorporating molecular structure information of drugs and protein targets with other kinds of data derived from systems biology provide great potential to accelerate drug discovery and improve the success of drug repurposing attempts. In this review, we highlight commonly used computational drug repurposing strategies, including bioinformatics and cheminformatics tools, to integrate large-scale data emerging from the systems biology, and consider both the challenges and opportunities of using this approach. Moreover, we provide successful examples and case studies that combined various in silico drug-repurposing strategies to predict potential novel uses for known therapeutics.

Perspectives towards antiviral drug discovery against Ebola virus

Ebola virus disease (EVD), caused by Ebola viruses, resulted in more than 11 500 deaths according to a recent 2018 WHO report. With mortality rates up to 90%, it is nowadays one of the most deadly infectious diseases. However, no Food and Drug Administration‐approved Ebola drugs or vaccines are available yet with the mainstay of therapy being supportive care. The high fatality rate and absence of effective treatment or vaccination make Ebola virus a category‐A biothreat pathogen. Fortunately, a series of investigational countermeasures have been developed to control and prevent this global threat. This review summarizes the recent therapeutic advances and ongoing research progress from research and development to clinical trials in the development of small‐molecule antiviral drugs, small‐interference RNA molecules, phosphorodiamidate morpholino oligomers, full‐length monoclonal antibodies, and vaccines. Moreover, difficulties are highlighted in the search for effective countermeasures against EVD with additional focus on the interplay between available in silico prediction methods and their evidenced potential in antiviral drug discovery.

Homoharringtonine targets Smad3 and TGF-β pathway to inhibit the proliferation of acute myeloid leukemia cells

Homoharringtonine (HHT) has long and widely been used in China for the treatment of acute myeloid leukemia (AML), the clinical therapeutic effect is significant but the working mechanism is poorly understood. The purpose of this study is to screen the possible target for HHT with virtual screening and verify the findings by cell experiments. Software including Autodock, Python, and MGL tools were used, with HHT being the ligand and proteins from PI3K-Akt pathway, Jak-stat pathway, TGF-β pathway and NK-κB pathway as the receptors. Human AML cell lines including U937, KG-1, THP-1 were cultured and used as the experiment cell lines. MTT assay was used for proliferation detection, flowcytometry was used to detect apoptosis and cell cycle arrest upon HHT functioning, western blotting was used to detect the protein level changes, viral shRNA transfection was used to suppress the expression level of the target protein candidate, and viral mRNA transfection was used for over-expression. Virtual screening revealed that smad3 from TGF-β pathway might be the candidate for HHT binding. In AML cell line U937 and KG-1, HHT can induce the Ser423/425 phosphorylation of smad3, and this phosphorylation can subsequently activate the TGF-β pathway, causing cell cycle arrest at G1 phase in U937 cells and apoptosis in KG-1 cells, knockdown of smad3 can impair the sensitivity of U937 cell to HHT, and over-expression of smad3 can re-establish the sensitivity in both cell lines. We conclude that smad3 is the probable target protein of HHT and plays an important role in the functioning mechanism of HHT.

The impact of in silico screening in the discovery of novel and safer drug candidates

Drug discovery is a multidisciplinary and multivariate optimization endeavor. As such, in silico screening tools have gained considerable importance to archive, analyze and exploit the vast and ever-increasing amount of experimental data generated throughout the process. The current review will focus on the computer-aided prediction of the numerous properties that need to be controlled during the discovery of a preliminary hit and its promotion to a viable clinical candidate. It does not pretend to the almost impossible task of an exhaustive report but will highlight a few key points that need to be collectively addressed both by chemists and biologists to fuel the drug discovery pipeline with innovative and safe drug candidates.

Successful application of virtual screening and molecular dynamics simulations against antimalarial molecular targets

The main challenge in the control of malaria has been the emergence of drug-resistant parasites. The presence of drug-resistant Plasmodium sp. has raised the need for new antimalarial drugs. Molecular modelling techniques have been used as tools to develop new drugs. In this study, we employed virtual screening of a pyrazol derivative (Tx001) against four malaria targets: plasmepsin-IV, plasmepsin-II, falcipain-II, and PfATP6. The receiver operating characteristic curves and area under the curve (AUC) were established for each molecular target. The AUC values obtained for plasmepsin-IV, plasmepsin-II, and falcipain-II were 0.64, 0.92, and 0.94, respectively. All docking simulations were carried out using AutoDock Vina software. The ligand Tx001 exhibited a better interaction with PfATP6 than with the reference compound (-12.2 versus -6.8 Kcal/mol). The Tx001-PfATP6 complex was submitted to molecular dynamics simulations in vacuum implemented on an NAMD program. The ligand Tx001 docked at the same binding site as thapsigargin, which is a natural inhibitor of PfATP6. Compound TX001 was evaluated in vitro with a P. falciparum strain (W2) and a human cell line (WI-26VA4). Tx001 was discovered to be active against P. falciparum (IC50 = 8.2 µM) and inactive against WI-26VA4 (IC50 > 200 µM). Further ligand optimisation cycles generated new prospects for docking and biological assays.

Discovery of Novel Human Epidermal Growth Factor Receptor-2 Inhibitors by Structure-based Virtual Screening

BACKGROUND

Human epidermal growth factor receptor-2 (HER2) is a trans-membrane receptor like protein, and aberrant signaling of HER2 is implicated in many human cancers, such as ovarian cancer, gastric cancer, and prostate cancer, most notably breast cancer. Moreover, it has been in the spotlight in the recent years as a promising new target for therapy of breast cancer.

OBJECTIVE

Since virtual screening has become an integral part of the drug discovery process, it is of great significant to identify novel HER2 inhibitors by structure-based virtual screening.

MATERIALS AND METHODS

In this study, we carried out a series of elegant bioinformatics approaches, such as virtual screening and molecular dynamics (MD) simulations to identify HER2 inhibitors from Food and Drug Administration-approved small molecule drug as potential "new use" drugs.

RESULTS

Molecular docking identified top 10 potential drugs which showed spectrum affinity to HER2. Moreover, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) might exert potential inhibitory effects against HER2-targeted anti-breast cancer therapeutics.

CONCLUSION

Together, our findings may provide successful application of virtual screening studies in the lead discovery process, and suggest that our discovered small molecules could be effective HER2 inhibitor candidates for further study.

SUMMARY

A series of elegant bioinformatics approaches, including virtual screening and molecular dynamics (MD) simulations were took advantage to identify human epidermal growth factor receptor-2 (HER2) inhibitors. Molecular docking recognized top 10 candidate compounds, which showed spectrum affinity to HER2. Further, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) in candidate compounds were identified as potential "new use" drugs against HER2-targeted anti-breast cancer therapeutics. Abbreviations used: HER2: Human epidermal growth factor receptor-2, FDA: Food and Drug Administration, PDB: Protein Database Bank, RMSDs: Root mean square deviations, SPC: Single point charge, PME: Particle mesh Ewald, NVT: Constant volume, NPT: Constant pressure, RMSF: Root-mean-square fluctuation.