Locating sweet spots for screening hits and evaluating pan-assay interference filters from the performance analysis of two lead-like libraries

Discovery of Potential Inhibitors of SARS-CoV-2 Main Protease by a Transfer Learning Method

The COVID-19 pandemic caused by SARS-CoV-2 remains a global public health threat and has prompted the development of antiviral therapies. Artificial intelligence may be one of the strategies to facilitate drug development for emerging and re-emerging diseases. The main protease (Mpro) of SARS-CoV-2 is an attractive drug target due to its essential role in the virus life cycle and high conservation among SARS-CoVs. In this study, we used a data augmentation method to boost transfer learning model performance in screening for potential inhibitors of SARS-CoV-2 Mpro. This method appeared to outperform graph convolution neural network, random forest and Chemprop on an external test set. The fine-tuned model was used to screen for a natural compound library and a de novo generated compound library. By combination with other in silico analysis methods, a total of 27 compounds were selected for experimental validation of anti-Mpro activities. Among all the selected hits, two compounds (gyssypol acetic acid and hyperoside) displayed inhibitory effects against Mpro with IC50 values of 67.6 μM and 235.8 μM, respectively. The results obtained in this study may suggest an effective strategy of discovering potential therapeutic leads for SARS-CoV-2 and other coronaviruses.

Exhaustive in silico design and screening of novel antipsychotic compounds with improved pharmacodynamics and blood-brain barrier permeation properties

Antipsychotic drugs or neuroleptics are widely used in the treatment of psychosis as a manifestation of schizophrenia and bipolar disorder. However, their effectiveness largely depends on the blood-brain barrier (BBB) permeation (pharmacokinetics) and drug-receptor pharmacodynamics. Therefore, in this study, we developed and implemented the in silico pipeline to design novel compounds (n = 260) as leads using the standard drug scaffolds with improved PK/PD properties from the standard scaffolds. As a result, the best candidates (n = 3) were evaluated in molecular docking to interact with serotonin and dopamine receptors. Finally, haloperidol (HAL) derivative (1-(4-fluorophenyl)-4-(4-hydroxy-4-{4-[(2-phenyl-1,3-thiazol-4-yl)methyl]phenyl}piperidin-1-yl)butan-1-one) was identified as a "magic shotgun" lead compound with better affinity to the 5-HT2A, 5-HT1D, D2, D3, and 5-HT1B receptors than the control molecule. Additionally, this hit substance was predicted to possess similar BBB permeation properties and much lower toxicological profiles in comparison to HAL. Overall, the proposed rational drug design platform for novel antipsychotic drugs based on the BBB permeation and receptor binding might be an invaluable asset for a medicinal chemist or translational pharmacologist.Communicated by Ramaswamy H. Sarma.

In Silico and In Vitro Screening Constituents of Eclipta alba Leaf Extract to Reveal Antimicrobial Potential

Phytochemicals have been shown to possess multiple bioactives and have been reported to showcase many medicinal effects. A similar kind of evaluation of phytoconstituents for their antimicrobial action has been reported, based on in vitro and in silico data. The goal of the research was to explore bioactive phytoconstituents of Eclipta alba leaf for antimicrobial activity. The antimicrobial activity was validated by both molecular docking and antimicrobial assay. Bioactive metabolites were identified using GC-MS. The antimicrobial and antimycobacterial activity of Eclipta alba leaves was investigated using the Kirby–Bauer well diffusion method and the rapid culture—MGIT™ DST method against a variety of human pathogens, as well as Mycobacterium tuberculosis (H37Rv) and Mycobacterium tuberculosis bacteria resistant to isoniazid and rifampicin. Eclipta alba’s GC-MS studies confirmed the detection of 17 bioactive constituents. The extract demonstrates the highest antibacterial activity against Escherichia coli (sensitive), Pseudomonas aeruginosa (sensitive) and methicillin-resistant Staphylococcus aureus (MRSA), and Pseudomonas aeruginosa susceptible and MRSA (sensitive) with zone of inhibition of 27 mm, 24 mm, and 32 mm respectively. The extract showed no effect on Mycobacterium tuberculosis (H37Rv) and Mycobacterium tuberculosis bacteria resistant to isoniazid and rifampicin in antimycobacterial activity testing. Molecular docking investigation revealed that three compounds (phthalic acid, isobutyl octadecyl ester, hexadecanoic acid, 1(hydroxymethyl)1,2-ethanediylester, and 2,myristynoyl pantetheine) have generated the best results in terms of binding energies and significant interactions with key residues of target protein 3-hydroxydecanoyl-acyl carrier protein dehydratase (FabA) and confirm its activity as antimicrobial inhibitors. These two-dimensional plots show significant protein-ligand binding interactions (van der Waals interactions, hydrogen bond, alkyl, and Pi-alkyl interactions). ADMET (absorption, distribution, metabolism, excretion, and toxicity) results additionally support the drug-likeness characteristics of concluded potential compounds. The experimental and computational results demonstrated that methanolic extract of Eclipta alba leaves had antimicrobial effects for specific infections due to the presence of phytochemical compounds.

5-Arylidene(chromenyl-methylene)-thiazolidinediones: Potential New Agents against Mutant Oncoproteins K-Ras, N-Ras and B-Raf in Colorectal Cancer and Melanoma

Background and objectives: Cancer represents the miscommunication between and within the body cells. The mutations of the oncogenes encoding the MAPK pathways play an important role in the development of tumoral diseases. The mutations of KRAS and BRAF oncogenes are involved in colorectal cancer and melanoma, while the NRAS mutations are associated with melanoma. Thiazolidine-2,4-dione is a versatile scaffold in medicinal chemistry and a useful tool in the development of new antitumoral compounds. The aim of our study was to predict the pharmacokinetic/pharmacodynamic properties, the drug-likeness and lead-likeness of two series of synthetic 5-arylidene(chromenyl-methylene)-thiazolidinediones, the molecular docking on the oncoproteins K-Ras, N-Ras and B-Raf, and to investigate the cytotoxicity of the compounds, in order to select the best structural profile for potential anticancer agents. Materials and Methods: In our paper we studied the cytotoxicity of two series of thiazolidine-2,4-dione derivatives, their ADME-Tox properties and the molecular docking on a mutant protein of K-Ras, two isoforms of N-Ras and an isoform of B-Raf with 16 mutations. Results: The heterocyclic compounds strongly interact with K-Ras and N-Ras right after their posttranslational processing and/or compete with GDP for the nucleotide-binding site of the two GTPases. They are less active against the GDP-bound states of the two targets. All derivatives have a similar binding pattern in the active site of B-Raf. Conclusions: The data obtained encourage the further investigation of the 5-arylidene(chromenyl-methylene)-thiazolidinediones as potential new agents against the oncoproteins K-Ras, N-Ras and B-Raf.

Antibacterial Evaluation and Virtual Screening of New Thiazolyl-Triazole Schiff Bases as Potential DNA-Gyrase Inhibitors

The global spread of bacterial resistance to drugs used in therapy requires new potent and safe antimicrobial agents. DNA gyrases represent important targets in drug discovery. Schiff bases, thiazole, and triazole derivatives are considered key scaffolds in medicinal chemistry. Fifteen thiazolyl-triazole Schiff bases were evaluated for their antibacterial activity, measuring the growth inhibition zone diameter, the minimum inhibitory concentration (MIC), and the minimum bactericidal concentration (MBC), against Gram-positive (Staphylococcus aureus, Listeria monocytogenes) and Gram-negative (Escherichia coli, Salmonella typhimurium, Pseudomonas aeruginosa) bacteria. The inhibition of S. aureus and S. typhimurium was modest. Compounds B1, B2, and B9 showed a similar effect as ciprofloxacin, the antimicrobial reference, against L. monocytogenes. B10 displayed a better effect. Derivatives B1, B5–7, B9, and B11–15 expressed MIC values lower than the reference, against L. monocytogenes. B5, B6, and B11–15 strongly inhibited the growth of P. aeruginosa. All compounds were subjected to an in silico screening of the ADMET (absorption, distribution, metabolism, elimination, toxicity) properties. Molecular docking was performed on the gyrA and gyrB from L. monocytogenes. The virtual screening concluded that thiazolyl-triazole Schiff base B8 is the best drug-like candidate, satisfying requirements for both safety and efficacy, being more potent against the bacterial gyrA than ciprofloxacin.

Construction of a versatile expression library for all human single-pass transmembrane proteins for receptor pairings by high throughput screening

Interactions between protein ligands and receptors play crucial roles in cell-cell signalling. Most of the human cell surface receptors have been identified in the post-Human Genome Project era but many of their corresponding ligands remain unknown. To facilitate the pairing of orphan receptors, 2762 sequences encoding all human single-pass transmembrane proteins were selected for inclusion into a mammalian-cell expression library. This expression library, consisting of all the individual extracellular domains (ECDs), was constructed as a Fab fusion for each protein. In this format, individual ECD can be produced as a soluble protein or displayed on cell surface, depending on the applied heavy-chain Fab configuration. The unique design of the Fab fusion concept used in the library led to not only superior success rate of protein production, but also versatile applications in various high-throughput screening paradigms including protein-protein binding assays as well as cell binding assays, which were not possible for any other existing expression libraries. The protein library was screened against human coagulation factor VIIa (FVIIa), an approved therapeutic for the treatment of hemophilia, for binding partners by AlphaScreen and ForteBio assays. Two previously known physiological ligands of FVIIa, tissue factor (TF) and endothelial protein C receptor (EPCR) were identified by both assays. The cell surface displayed library was screened against V-domain Ig suppressor of T-cell activation (VISTA), an important immune-checkpoint regulator. Immunoglobulin superfamily member 11 (IgSF11), a potential target for cancer immunotherapy, was identified as a new and previously undescribed binding partner for VISTA. The specificity of the binding was confirmed and validated by both fluorescence-activated cell sorting (FACS) and surface plasmon resonance (SPR) assays in different experimental setups.

VSPrep: A General KNIME Workflow for the Preparation of Molecules for Virtual Screening

Over the past decades, virtual screening has proved itself to be a valuable asset to identify new bioactive compounds. The vast majority of commonly used techniques can be described in three steps: pre-processing the dataset i. e. small (ligands) and eventually larger (receptors) molecules, execute the method and finally analyse the results. Hence, the preparation of ligands is a critical step for success of commonly used virtual screening approaches such as protein-ligand docking, similarity or pharmacophore search. We present here a new workflow, VSPrep, for the pre-processing of small molecules; it is based on freely accessible tools for academics and is integrated within the KNIME platform. It can be used to perform several chemoinformatics tasks such as molecular database cleaning, tautomer and stereoisomer enumeration, focused library design and conformer generation. Additionally, graphical reports of the results are provided to the user as a convenient analysis tool.

Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundS

The use of substructural alerts to identify Pan-Assay INterference compoundS (PAINS) has become a common component of the triage process in biological screening campaigns. These alerts, however, were originally derived from a proprietary library tested in just six assays measuring protein-protein interaction (PPI) inhibition using the AlphaScreen detection technology only; moreover, 68% (328 out of the 480 alerts) were derived from four or fewer compounds. In an effort to assess the reliability of these alerts as indicators of pan-assay interference, we performed a large-scale analysis of the impact of PAINS alerts on compound promiscuity in bioassays using publicly available data in PubChem. We found that the majority (97%) of all compounds containing PAINS alerts were actually infrequent hitters in AlphaScreen assays measuring PPI inhibition. We also found that the presence of PAINS alerts, contrary to expectations, did not reflect any heightened assay activity trends across all assays in PubChem including AlphaScreen, luciferase, beta-lactamase, or fluorescence-based assays. In addition, 109 PAINS alerts were present in 3570 extensively assayed, but consistently inactive compounds called Dark Chemical Matter. Finally, we observed that 87 small molecule FDA-approved drugs contained PAINS alerts and profiled their bioassay activity. Based on this detailed analysis of PAINS alerts in nonproprietary compound libraries, we caution against the blind use of PAINS filters to detect and triage compounds with possible PAINS liabilities and recommend that such conclusions should be drawn only by conducting orthogonal experiments.

Open Source Drug Discovery: Highly Potent Antimalarial Compounds Derived from the Tres Cantos Arylpyrroles

The development of new antimalarial compounds remains a pivotal part of the strategy for malaria elimination. Recent large-scale phenotypic screens have provided a wealth of potential starting points for hit-to-lead campaigns. One such public set is explored, employing an open source research mechanism in which all data and ideas were shared in real time, anyone was able to participate, and patents were not sought. One chemical subseries was found to exhibit oral activity but contained a labile ester that could not be replaced without loss of activity, and the original hit exhibited remarkable sensitivity to minor structural change. A second subseries displayed high potency, including activity within gametocyte and liver stage assays, but at the cost of low solubility. As an open source research project, unexplored avenues are clearly identified and may be explored further by the community; new findings may be cumulatively added to the present work.

FAF-Drugs3: a web server for compound property calculation and chemical library design

Drug attrition late in preclinical or clinical development is a serious economic problem in the field of drug discovery. These problems can be linked, in part, to the quality of the compound collections used during the hit generation stage and to the selection of compounds undergoing optimization. Here, we present FAF-Drugs3, a web server that can be used for drug discovery and chemical biology projects to help in preparing compound libraries and to assist decision-making during the hit selection/lead optimization phase. Since it was first described in 2006, FAF-Drugs has been significantly modified. The tool now applies an enhanced structure curation procedure, can filter or analyze molecules with user-defined or eight predefined physicochemical filters as well as with several simple ADMET (absorption, distribution, metabolism, excretion and toxicity) rules. In addition, compounds can be filtered using an updated list of 154 hand-curated structural alerts while Pan Assay Interference compounds (PAINS) and other, generally unwanted groups are also investigated. FAF-Drugs3 offers access to user-friendly html result pages and the possibility to download all computed data. The server requires as input an SDF file of the compounds; it is open to all users and can be accessed without registration at http://fafdrugs3.mti.univ-paris-diderot.fr.

In silico design of low molecular weight protein-protein interaction inhibitors: Overall concept and recent advances

Protein-protein interactions (PPIs) are carrying out diverse functions in living systems and are playing a major role in the health and disease states. Low molecular weight (LMW) "drug-like" inhibitors of PPIs would be very valuable not only to enhance our understanding over physiological processes but also for drug discovery endeavors. However, PPIs were deemed intractable by LMW chemicals during many years. But today, with the new experimental and in silico technologies that have been developed, about 50 PPIs have already been inhibited by LMW molecules. Here, we first focus on general concepts about protein-protein interactions, present a consensual view about ligandable pockets at the protein interfaces and the possibilities of using fast and cost effective structure-based virtual screening methods to identify PPI hits. We then discuss the design of compound collections dedicated to PPIs. Recent financial analyses of the field suggest that LMW PPI modulators could be gaining momentum over biologics in the coming years supporting further research in this area.

New imidazo[1,2-b]pyrazoles as anticancer agents: synthesis, biological evaluation and structure activity relationship analysis

Synthesis and functionalization strategies of the imidazo[1,2-b]pyrazole core were developed giving a rapid access to three series of novel imidazo[1,2-b]pyrazole type derivatives: C-2/C-6/C-7 trisubstituted, C-2/C-3/C-6 tri(hetero)arylated and C-2/C-3/C-6/C-7 tetrasubstituted imidazo[1,2-b]pyrazoles. 39 of the synthetized products were evaluated for in vitro anticancer activity using the MTT colorimetric assay against 5 human and 1 murine cancer cell lines. Promising in vitro growth inhibitory activities were exhibited by some of the target compounds. Of the 39 evaluated products, 4 displayed an IC50 ≤ 10 μM in the 6 cell lines analyzed (compounds 4d, 4g, 9a, 11a). A structure activity relationship analysis is also reported in this paper.

Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology

[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.