Integrated workflow for the identification of new GABAA R positive allosteric modulators based on the in†silico screening with further in†vitro validation. Case study using Enamine's stock chemical space.

Numerous studies reported an association between GABAA R subunit genes and epilepsy, eating disorders, autism spectrum disorders, neurodevelopmental disorders, and bipolar disorders. This study was aimed to find some potential positive allosteric modulators and was performed by combining the in silico approach with further in vitro evaluation of its real activity. We started from the GABAA R-diazepam complexes and assembled a lipid embedded protein ensemble to refine it via molecular dynamics (MD) simulation. Then we focused on the interaction of α1ß2γ2 with some Z-drugs (non-benzodiazepine compounds) using an Induced Fit Docking (IFD) into the relaxed binding site to generate a pharmacophore model. The pharmacophore model was validated with a reference set and applied to decrease the pre-filtered Enamine database before the main docking procedure. Finally, we succeeded in identifying a set of compounds, which met all features of the docking model. The aqueous solubility and stability of these compounds in mouse plasma were assessed. Then they were tested for the biological activity using the rat Purkinje neurons and CHO cells with heterologously expressed human α1ß2γ2 GABAA receptors. Whole-cell patch clamp recordings were used to reveal the GABA induced currents. Our study represents a convenient and tunable model for the discovery of novel positive allosteric modulators of GABAA receptors. A High-throughput virtual screening of the largest available database of chemical compounds resulted in the selection of 23 compounds. Further electrophysiological tests allowed us to determine a set of 3 the most outstanding active compounds. Considering the structural features of leader compounds, the study can develop into the MedChem project soon.

Ivermectin affects Arabidopsis thaliana microtubules through predicted binding site of ß-tubulin.

The ivermectin is a potent nematocide and insecticide, which has low toxicity for humans and domestic animals, but due to low biotransformation, it can be dangerous for non-target organisms. The recent determination of ivermectin absorption and accumulation in tissues of higher plants and multiple shreds of evidence of its negative impact on plant physiology provide a basis for the search for ivermectin's molecular targets and mechanisms of action in plant cells. In this research, for the first time, the ivermectin effect on microtubules of Arabidopsis thaliana cells was studied. It was revealed that ivermectin (250 µg mL-1) disrupts the microtubule network, induces the loss of microtubule orientation, leads to microtubule curvature and shrinkage, and their longitudinal and cross-linked bundling in various cells of A. thaliana primary roots. Further, the previously proposed binding of ivermectin to the ß1-tubulin taxane site was developed and confirmed using molecular dynamics simulations of ivermectin complexes with Haemonchus contortus and A. thaliana ß1-tubulins. It was predicted that similar to other microtubule stabilizing agents ivermectin binding causes M-loop stabilization in both H. contortus and A. thaliana ß-tubulin, which leads to the enhancement of lateral contacts between subunits of adjacent protofilaments preventing microtubule depolymerization.

In silico induced effect of N-ε-lysine acetylation on microtubule stability and subsequent interaction of microtubule-associated proteins.

Plant systems have been considered valuable models for addressing fundamental questions of microtubule (MT) organization due to their considerable practical utility. Protein acetylation is a very common protein modification, and therate of acetylation can be modulated in cells in different biological states, and these changes can be detected at a molecular level. Here, we focused on K40, K112, and K394 residues as putative acetylation sites, which were shown to exist in both plants and mammals. Such residual effect of acetylation causes critical but unclear effect on MT stability. In turn, it was shown that acetylation indirectly affects the probability of interaction with different MAPs (Microtubule-associated proteins). In a multiscale study using an all-atom force field to reproduce several lattice-forming elements found on the surface the microtubule, we assembled a fragment of a plant microtubule composed of nine tubulins and used it as a model object along with the existing human complex. Triplets of tubulins assembled in a lattice cell were then simulated for both human and plant protein complexes, using a coarse-grained force field. We then analyzed the trajectories and identified some critical deformations of the MAP interaction surface. The initial coordinates were used to investigate the structural scenario in which autophagy-related protein 8 (ATG8) was able to interact with the MT fragment.

Anti-MRSA drug discovery by ligand-based virtual screening and biological evaluation.

S. aureus resistant to methicillin (MRSA) is one of the most-concerned multidrug resistant bacteria, due to its role in life-threatening infections. There is an urgent need to develop new antibiotics against MRSA. In this study, we firstly compiled a data set of 2,3-diaminoquinoxalines by chemical synthesis and antibacterial screening against S. aureus, and then performed cheminformatics modeling and virtual screening. The compound with the Specs ID of AG-205/33156020 was discovered as a new antibacterial agent, and was further identified as a Gyrase B (GyrB) inhibitor. In light of the common features, we hypothesized that the 6c as the representative of 2,3-diaminoquinoxalines also inhibited GyrB and eventually proved it. Via molecular docking and molecular dynamics simulations, we identified binding modes of AG-205/33156020 and 6c to the ATPase domain of GyrB. Importantly, these GyrB inhibitors inhibited the MRSA strains and showed selectivity to HepG2 and HUVEC. Taken together, this research work provides an effective ligand-based computational workflow for scaffold hopping in anti-MRSA drug discovery, and discovers two new GyrB inhibitors that are worthy of further development.

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495.

Structure-Activity Relationship Modeling and Experimental Validation of the Imidazolium and Pyridinium Based Ionic Liquids as Potential Antibacterials of MDR Acinetobacter Baumannii and Staphylococcus Aureus.

Online Chemical Modeling Environment (OCHEM) was used for QSAR analysis of a set of ionic liquids (ILs) tested against multi-drug resistant (MDR) clinical isolate Acinetobacter baumannii and Staphylococcus aureus strains. The predictive accuracy of regression models has coefficient of determination q2 = 0.66 - 0.79 with cross-validation and independent test sets. The models were used to screen a virtual chemical library of ILs, which was designed with targeted activity against MDR Acinetobacter baumannii and Staphylococcus aureus strains. Seven most promising ILs were selected, synthesized, and tested. Three ILs showed high activity against both these MDR clinical isolates.

Proposal of Potent Inhibitors for a Bacterial Cell Division Protein FtsZ: Molecular Simulations Based on Molecular Docking and ab Initio Molecular Orbital Calculations.

The inhibition of a bacterial cell division protein, filamentous temperature-sensitive Z (FtsZ), prevents the reproduction of Mycobacteria. To propose potent inhibitors of FtsZ, the binding properties of FtsZ with various derivatives of Zantrin ZZ3 were investigated at an electronic level, using molecular simulations. We here employed protein-ligand docking, classical molecular mechanics (MM) optimizations, and ab initio fragment molecular orbital (FMO) calculations. Based on the specific interactions between FtsZ and the derivatives, as determined by FMO calculations, we proposed novel ligands, which can strongly bind to FtsZ and inhibit its aggregations. The introduction of a hydroxyl group into ZZ3 was found to enhance its binding affinity to FtsZ.

State-of-the-art augmented NLP transformer models for direct and single-step retrosynthesis.

We investigated the effect of different training scenarios on predicting the (retro)synthesis of chemical compounds using text-like representation of chemical reactions (SMILES) and Natural Language Processing (NLP) neural network Transformer architecture. We showed that data augmentation, which is a powerful method used in image processing, eliminated the effect of data memorization by neural networks and improved their performance for prediction of new sequences. This effect was observed when augmentation was used simultaneously for input and the target data simultaneously. The top-5 accuracy was 84.8% for the prediction of the largest fragment (thus identifying principal transformation for classical retro-synthesis) for the USPTO-50k test dataset, and was achieved by a combination of SMILES augmentation and a beam search algorithm. The same approach provided significantly better results for the prediction of direct reactions from the single-step USPTO-MIT test set. Our model achieved 90.6% top-1 and 96.1% top-5 accuracy for its challenging mixed set and 97% top-5 accuracy for the USPTO-MIT separated set. It also significantly improved results for USPTO-full set single-step retrosynthesis for both top-1 and top-10 accuracies. The appearance frequency of the most abundantly generated SMILES was well correlated with the prediction outcome and can be used as a measure of the quality of reaction prediction.

Transformer-CNN: Swiss knife for QSAR modeling and interpretation.

We present SMILES-embeddings derived from the internal encoder state of a Transformer [1] model trained to canonize SMILES as a Seq2Seq problem. Using a CharNN [2] architecture upon the embeddings results in higher quality interpretable QSAR/QSPR models on diverse benchmark datasets including regression and classification tasks. The proposed Transformer-CNN method uses SMILES augmentation for training and inference, and thus the prognosis is based on an internal consensus. That both the augmentation and transfer learning are based on embeddings allows the method to provide good results for small datasets. We discuss the reasons for such effectiveness and draft future directions for the development of the method. The source code and the embeddings needed to train a QSAR model are available on https://github.com/bigchem/transformer-cnn. The repository also has a standalone program for QSAR prognosis which calculates individual atoms contributions, thus interpreting the model's result. OCHEM [3] environment (https://ochem.eu) hosts the on-line implementation of the method proposed.

Focused Library Generator: case of Mdmx inhibitors.

We present a Focused Library Generator that is able to create from scratch new molecules with desired properties. After training the Generator on the ChEMBL database, transfer learning was used to switch the generator to producing new Mdmx inhibitors that are a promising class of anticancer drugs. Lilly medicinal chemistry filters, molecular docking, and a QSAR IC50 model were used to refine the output of the Generator. Pharmacophore screening and molecular dynamics (MD) simulations were then used to further select putative ligands. Finally, we identified five promising hits with equivalent or even better predicted binding free energies and IC50 values than known Mdmx inhibitors. The source code of the project is available on https://github.com/bigchem/online-chem.

Prokineticin Receptor-1 Signaling Inhibits Dose- and Time-Dependent Anthracycline-Induced Cardiovascular Toxicity Via Myocardial and Vascular Protection.

OBJECTIVES: This study investigated how different concentrations of doxorubicin (DOX) can affect the function of cardiac cells. This study also examined whether activation of prokineticin receptor (PKR)-1 by a nonpeptide agonist, IS20, prevents DOX-induced cardiovascular toxicity in mouse models. BACKGROUND: High prevalence of heart failure during and following cancer treatments remains a subject of intense research and therapeutic interest. METHODS: This study used cultured cardiomyocytes, endothelial cells (ECs), and epicardium-derived progenitor cells (EDPCs) for in vitro assays, tumor-bearing models, and acute and chronic toxicity mouse models for in vivo assays. RESULTS: Brief exposure to cardiomyocytes with high-dose DOX increased the accumulation of reactive oxygen species (ROS) by inhibiting a detoxification mechanism via stabilization of cytoplasmic nuclear factor, erythroid 2. Prolonged exposure to medium-dose DOX induced apoptosis in cardiomyocytes, ECs, and EDPCs. However, low-dose DOX promoted functional defects without inducing apoptosis in EDPCs and ECs. IS20 alleviated detrimental effects of DOX in cardiac cells by activating the serin threonin protein kinase B (Akt) or mitogen-activated protein kinase pathways. Genetic or pharmacological inactivation of PKR1 subdues these effects of IS20. In a chronic mouse model of DOX cardiotoxicity, IS20 normalized an elevated serum marker of cardiotoxicity and vascular and EDPC deficits, attenuated apoptosis and fibrosis, and improved the survival rate and cardiac function. IS20 did not interfere with the cytotoxicity or antitumor effects of DOX in breast cancer lines or in a mouse model of breast cancer, but it did attenuate the decreases in left ventricular diastolic volume induced by acute DOX treatment. CONCLUSIONS: This study identified the molecular and cellular signature of dose-dependent, DOX-mediated cardiotoxicity and provided evidence that PKR-1 is a promising target to combat cardiotoxicity of cancer treatments.

Structural and functional features of lysine acetylation of plant and animal tubulins.

The study of the genome and the proteome of different species and representatives of distinct kingdoms, especially detection of proteome via wide-scaled analyses has various challenges and pitfalls. Attempts to combine all available information together and isolate some common features for determination of the pathway and their mechanism of action generally have a highly complicated nature. However, microtubule (MT) monomers are highly conserved protein structures, and microtubules are structurally conserved from Homo sapiens to Arabidopsis thaliana. The interaction of MT elements with microtubule-associated proteins and post-translational modifiers is fully dependent on protein interfaces, and almost all MT modifications are well described except acetylation. Crystallography and interactome data using different approaches were combined to identify conserved proteins important in acetylation of microtubules. Application of computational methods and comparative analysis of binding modes generated a robust predictive model of acetylation of the ϵ-amino group of Lys40 in α-tubulins. In turn, the model discarded some probable mechanisms of interaction between elements of interest. Reconstruction of unresolved protein structures was carried out with modeling by homology to the existing crystal structure (PDBID: 1Z2B) from B. taurus using Swiss-model server, followed by a molecular dynamics simulation. Docking of the human tubulin fragment with Lys40 into the active site of α-tubulin acetyltransferase, reproduces the binding mode of peptidomimetic from X-ray structure (PDBID: 4PK3).

Protein phosphatases potentially associated with regulation of microtubules, their spatial structure reconstruction and analysis.

According to the sequence and profile comparison with known catalytic domains, where identified protein phosphatases potentially involved in regulation of microtubule dynamics and structure from Arabidopsis thaliana, Nicotiana tabacum, Medicago sativa, Oryza sativa subsp. japonica, Zea mays, and Triticum aestivum. Selected proteins were related to classical non-receptor, serine/threonine-specific and dual protein phosphatases. By application of template structures of human protein phosphatases, it was performed homology modelling of the catalytic domains of 17 plant protein phosphatases. Based on the results of the structural alignment, molecular dynamics, and conservatism in positions of functionally importance, it was confirmed homology of selected plant proteins and known protein phosphatases regulating structure and dynamics of microtubules.

3D-modeling of carboxyl-terminal phosphorylation of plant αß-tubulin and its role in kinesin-8/microtubule interaction.

The results of computer modeling of plant kinesin-8/αß-tubulin complexes with such αß-tubulins' modified amino acid residues as phosphorylated Tyr262 and Tyr107 are reported in this paper. The molecular dynamics of these modified complexes in comparison with the dynamics of non-modified ones suggests that the phosphorylation of both α- and ß-tubulins reveals stabilizing effect on the protein structure around the modified residue. It was found also that the phosphorylation of Tyr107 in ß-tubulin molecule favors to more advantageous kinesin-8 binding with the phosphorylated microtubule surface in terms of energy.

A Survey of Multi-task Learning Methods in Chemoinformatics.

Despite the increasing volume of available data, the proportion of experimentally measured data remains small compared to the virtual chemical space of possible chemical structures. Therefore, there is a strong interest in simultaneously predicting different ADMET and biological properties of molecules, which are frequently strongly correlated with one another. Such joint data analyses can increase the accuracy of models by exploiting their common representation and identifying common features between individual properties. In this work we review the recent developments in multi-learning approaches as well as cover the freely available tools and packages that can be used to perform such studies.

MAST-like protein kinase IREH1 from Arabidopsis thaliana co-localizes with the centrosome when expressed in animal cells.

MAIN CONCLUSION: The similarity of IREH1 (Incomplete Root Hair Elongation 1) and animal MAST kinases was confirmed; IREH1cDNA was cloned while expressing in cultured animal cells co-localized with the centrosome. In mammals and fruit flies, microtubule-associated serine/threonine-protein kinases (MAST) are strongly involved in the regulation of the microtubule system. Higher plants also possess protein kinases homologous to MASTs, but their function and interaction with the cytoskeleton remain unclear. Here, we confirmed the sequence and structural similarity of MAST-related putative protein kinase IREH1 (At3g17850) and known animal MAST kinases. We report the first cloning of full-length cDNA of the IREH1 from Arabidopsis thaliana. Recombinant GFP-IREH1 protein was expressed in different cultured animal cells. It revealed co-localization with the centrosome without influencing cell morphology and microtubule arrangement. Structural N-terminal region of the IREH1 molecule co-localized with centrosome as well.

Three BUB1 and BUBR1/MAD3-related spindle assembly checkpoint proteins are required for accurate mitosis in Arabidopsis.

The spindle assembly checkpoint (SAC) is a refined surveillance mechanism which ensures that chromosomes undergoing mitosis do not segregate until they are properly attached to the spindle microtubules (MT). The SAC has been extensively studied in metazoans and yeast, but little is known about its role in plants. We identified proteins interacting with a MT-associated protein MAP65-3, which plays a critical role in organising mitotic MT arrays, and carried out a functional analysis of previously and newly identified SAC components. We show that Arabidopsis SAC proteins BUB3.1, MAD2, BUBR1/MAD3s and BRK1 interact with each other and with MAP65-3. We found that two BUBR1/MAD3s interacted specifically at centromeres. When stably expressed in Arabidopsis, BRK1 localised to the kinetochores during all stages of the mitotic cell cycle. Early in mitosis, BUB3.1 and BUBR1/MAD3.1 localise to the mitotic spindle, where MAP65-3 organises spindle MTs. A double-knockout mad3.1 mad3.2 mutant presented spindle MT abnormalities, chromosome misalignments on the metaphase plate and the production of lagging chromosomes and micronuclei during mitosis. We conclude that BRK1 and BUBR1/MAD3-related proteins play a key role in ensuring faithful chromosome segregation during mitosis and that their interaction with MAP65-3 may be important for the regulation of MT-chromosome attachment.

One-class classification as a novel method of ligand-based virtual screening: the case of glycogen synthase kinase 3ß inhibitors.

A virtual screening system based on one-class classification with molecular fingerprints as descriptors is developed and tested on a series of 1226 inhibitors and 209 noninhibitors of glycogen synthase kinase 3ß (GSK-3ß). The suggested system outperforms the ones based on pharmacophore hypothesis and molecular docking in a retrospective study. However, in a prospective study it should not be used as a sole classifier. The system is exceptionally useful for the identification of new scaffolds among the virtual screening results obtained with other methods.