Molecular and Structural Aspects of Clinically Relevant Mutations of SARS-CoV-2 RNA-Dependent RNA Polymerase in Remdesivir-Treated Patients.

(1) Background: SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target to fight COVID-19, and many RdRp inhibitors nucleotide/nucleoside analogs, such as remdesivir, have been identified or are in clinical studies. However, the appearance of resistant mutations could reduce their efficacy. In the present work, we structurally evaluated the impact of RdRp mutations found at baseline in 39 patients treated with remdesivir and associated with a different degree of antiviral response in vivo. (2) Methods: A refined bioinformatics approach was applied to assign SARS-CoV-2 clade and lineage, and to define RdRp mutational profiles. In line with such a method, the same mutations were built and analyzed by combining docking and thermodynamics evaluations with both molecular dynamics and representative pharmacophore models. (3) Results: Clinical studies revealed that patients bearing the most prevalent triple mutant P323L+671S+M899I, which was present in 41% of patients, or the more complex mutational profile P323L+G671S+L838I+D738Y+K91E, which was found with a prevalence of 2.6%, showed a delayed reduced response to remdesivir, as confirmed by the increase in SARS-CoV-2 viral load and by a reduced theoretical binding affinity versus RdRp (ΔGbindWT = -122.70 kcal/mol; ΔGbindP323L+671S+M899I = -84.78 kcal/mol; ΔGbindP323L+G671S+L838I+D738Y+K91E = -96.74 kcal/mol). Combined computational approaches helped to rationalize such clinical observations, offering a mechanistic understanding of the allosteric effects of mutants on the global motions of the viral RNA synthesis machine and in the changes of the interactions patterns of remdesivir during its binding.

GABAA receptor-mediated seizure liabilities: a mixed-methods screening approach.

GABAA receptors, members of the pentameric ligand-gated ion channel superfamily, are widely expressed in the central nervous system and mediate a broad range of pharmaco-toxicological effects including bidirectional changes to seizure threshold. Thus, detection of GABAA receptor-mediated seizure liabilities is a big, partly unmet need in early preclinical drug development. This is in part due to the plethora of allosteric binding sites that are present on different subtypes of GABAA receptors and the critical lack of screening methods that detect interactions with any of these sites. To improve in silico screening methods, we assembled an inventory of allosteric binding sites based on structural data. Pharmacophore models representing several of the binding sites were constructed. These models from the NeuroDeRisk IL Profiler were used for in silico screening of a compiled collection of drugs with known GABAA receptor interactions to generate testable hypotheses. Amoxapine was one of the hits identified and subjected to an array of in vitro assays to examine molecular and cellular effects on neuronal excitability and in vivo locomotor pattern changes in zebrafish larvae. An additional level of analysis for our compound collection is provided by pharmacovigilance alerts using FAERS data. Inspired by the Adverse Outcome Pathway framework, we postulate several candidate pathways leading from specific binding sites to acute seizure induction. The whole workflow can be utilized for any compound collection and should inform about GABAA receptor-mediated seizure risks more comprehensively compared to standard displacement screens, as it rests chiefly on functional data.

A new set of KNIME nodes implementing the QPhAR algorithm.

Dissemination of novel research methods, especially in the form of chemoinformatics software, depends heavily on their ease of applicability for non-expert users with only a little or no programming skills and knowledge in computer science. Visual programming has become widely popular over the last few years, also enabling researchers without in-depth programming skills to develop tailored data processing pipelines using elements from a repository of predefined standard procedures. In this work, we present the development of a set of nodes for the KNIME platform implementing the QPhAR algorithm. We show how the developed KNIME nodes can be included in a typical workflow for biological activity prediction. Furthermore, we present best-practice guidelines that should be followed to obtain high-quality QPhAR models. Finally, we show a typical workflow to train and optimise a QPhAR model in KNIME for a set of given input compounds, applying the discussed best practices.

Improved Lipophilicity and Aqueous Solubility Prediction with Composite Graph Neural Networks.

The accurate prediction of molecular properties, such as lipophilicity and aqueous solubility, are of great importance and pose challenges in several stages of the drug discovery pipeline. Machine learning methods, such as graph-based neural networks (GNNs), have shown exceptionally good performance in predicting these properties. In this work, we introduce a novel GNN architecture, called directed edge graph isomorphism network (D-GIN). It is composed of two distinct sub-architectures (D-MPNN, GIN) and achieves an improvement in accuracy over its sub-architectures employing various learning, and featurization strategies. We argue that combining models with different key aspects help make graph neural networks deeper and simultaneously increase their predictive power. Furthermore, we address current limitations in assessment of deep-learning models, namely, comparison of single training run performance metrics, and offer a more robust solution.

Selective DNA Gyrase Inhibitors: Multi-Target in Silico Profiling with 3D-Pharmacophores.

DNA gyrase is an important target for the development of novel antibiotics. Although ATP-competitive DNA gyrase (GyrB) inhibitors are a well-studied class of antibacterial agents, there is currently no representative used in therapy, largely due to unwanted off-target activities. Selectivity of GyrB inhibitors against closely related human ATP-binding enzymes should be evaluated early in development to avoid off-target binding to homologous binding domains. To address this challenge, we developed selective 3D-pharmacophore models for GyrB, human topoisomerase IIα (TopoII), and the Hsp90 N-terminal domain (NTD) to be used in in silico activity profiling paradigms to identify molecules selective for GyrB over TopoII and Hsp90, as starting points for hit expansion and lead optimization. The models were used to profile highly active GyrB, TopoII, and Hsp90 inhibitors. Selected compounds were tested in in vitro assays. GyrB inhibitors 1 and 2 were inactive against TopoII and Hsp90, while 3 and 4, potent Hsp90 inhibitors, displayed no inhibition of GyrB and TopoII, and TopoII inhibitors 5 and 6 were inactive at GyrB and Hsp90. The results provide a proof of concept for the use of target activity profiling methods to identify selective starting points for hit and lead identification.

Parameters for Irreversible Inactivation of Monoamine Oxidase.

The irreversible inhibitors of monoamine oxidases (MAO) slow neurotransmitter metabolism in depression and neurodegenerative diseases. After oxidation by MAO, hydrazines, cyclopropylamines and propargylamines form a covalent adduct with the flavin cofactor. To assist the design of new compounds to combat neurodegeneration, we have updated the kinetic parameters defining the interaction of these established drugs with human MAO-A and MAO-B and analyzed the required features. The Ki values for binding to MAO-A and molecular models show that selectivity is determined by the initial reversible binding. Common to all the irreversible inhibitor classes, the non-covalent 3D-chemical interactions depend on a H-bond donor and hydrophobic-aromatic features within 5.7 angstroms apart and an ionizable amine. Increasing hydrophobic interactions with the aromatic cage through aryl halogenation is important for stabilizing ligands in the binding site for transformation. Good and poor inactivators were investigated using visible spectroscopy and molecular dynamics. The initial binding, close and correctly oriented to the FAD, is important for the oxidation, specifically at the carbon adjacent to the propargyl group. The molecular dynamics study also provides evidence that retention of the allenyl imine product oriented towards FADH- influences the formation of the covalent adduct essential for effective inactivation of MAO.

Discovery of Novel Hsp90 C-Terminal Inhibitors Using 3D-Pharmacophores Derived from Molecular Dynamics Simulations.

Hsp90 C-terminal domain (CTD) inhibitors are promising novel agents for cancer treatment, as they do not induce the heat shock response associated with Hsp90 N-terminal inhibitors. One challenge associated with CTD inhibitors is the lack of a co-crystallized complex, requiring the use of predicted allosteric apo pocket, limiting structure-based (SB) design approaches. To address this, a unique approach that enables the derivation and analysis of interactions between ligands and proteins from molecular dynamics (MD) trajectories was used to derive pharmacophore models for virtual screening (VS) and identify suitable binding sites for SB design. Furthermore, ligand-based (LB) pharmacophores were developed using a set of CTD inhibitors to compare VS performance with the MD derived models. Virtual hits identified by VS with both SB and LB models were tested for antiproliferative activity. Compounds 9 and 11 displayed antiproliferative activities in MCF-7 and Hep G2 cancer cell lines. Compound 11 inhibited Hsp90-dependent refolding of denatured luciferase and induced the degradation of Hsp90 clients without the concomitant induction of Hsp70 levels. Furthermore, compound 11 offers a unique scaffold that is promising for the further synthetic optimization and development of molecules needed for the evaluation of the Hsp90 CTD as a target for the development of anticancer drugs.

Cytotoxicity Of Chalcone Of Eugenia aquea Burm F. Leaves Against T47D Breast Cancer Cell Lines And Its Prediction As An Estrogen Receptor Antagonist Based On Pharmacophore-Molecular Dynamics Simulation.

BACKGROUND: The 2',4'-dihydroxy-6-methoxy-3,5-3-dimethylchalcone (ChalcEA) isolated from Eugenia aquea Burm f. leaves has potential anticancer activity against human breast-adenocarcinoma cell lines (MCF-7) with an IC50 value of 250 µM. However, its apoptotic activity on the T47D breast cancer cell lines which is involving caspase-3 has not been investigated. MATERIALS AND METHODS: Therefore, this study aims to evaluate the cytotoxicity of ChalcEA on the T47D cell lines using the 2-(4-iodophenyl)-3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium (WST) method and to predict its possible antagonistic activity on the human estrogen receptor alpha (hERα) using pharmacophore and molecular dynamics (MD) methods. The in vitro test of 10 synthesized ChalcEA derivatives was also performed as an insight into the further development of its structure as an anticancer agent. RESULTS: It is shown that ChalcEA has an IC50 of 142.58 ± 4.6 µM against the hERα-overexpressed T47D breast cancer cell lines, indicating its possible mechanism of anticancer activity as an antagonist of hERα. Pharmacophore study showed that ChalcEA shares similar features with the known hERα antagonist, 4-hydroxytamoxifen (4-OHT), which has hydrogen bond donor (HBD), hydrogen bond acceptor (HBA), ring aromaticity (RA), and hydrophobicity (Hy) features. Molecular docking showed that ChalcEA formed hydrogen bonds with Glu353 and Arg394, and hydrophobic interactions in a similar manner with 4-OHT. Moreover, MD simulations showed that ChalcEA destabilized the conformation of His524, a remarkable behavior of a known hERa antagonist, including 4-OHT. Furthermore, the 10 best chalcone derivatives resulted from pharmacophore- and docking-based screening, were tested against the T47D cell lines. None of the derivatives have better activity than ChalcEA. It is suggested that the functional groups at the B-ring of ChalcEA are interesting to be further optimized in the next studies. CONCLUSION: ChalcEA might act as an antagonist toward hERα, thus warranting further investigation as a potential anticancer agent.

Postintensive Care Syndrome.

Patients admitted to the intensive care unit (ICU) are at an extremely high risk for developing intensive care syndrome. Increased illness severity often result in prolonged immobility, altered cognition, and the development of psychotic manifestations. Any constellation of these problems can result in prolonged patient impairment long after transfer from the ICU. Quick recognition of these symptoms leads to the development of a targeted rehabilitation to minimize long-term sequelae and optimize functional recovery.

The Mu.Ta.Lig. Chemotheca: A Community-Populated Molecular Database for Multi-Target Ligands Identification and Compound-Repurposing.

For every lead compound developed in medicinal chemistry research, numerous other inactive or less active candidates are synthetized/isolated and tested. The majority of these compounds will not be selected for further development due to a sub-optimal pharmacological profile. However, some poorly active or even inactive compounds could live a second life if tested against other targets. Thus, new therapeutic opportunities could emerge and synergistic activities could be identified and exploited for existing compounds by sharing information between researchers who are working on different targets. The Mu.Ta.Lig (Multi-Target Ligand) Chemotheca database aims to offer such opportunities by facilitating information exchange among researchers worldwide. After a preliminary registration, users can (a) virtually upload structures and activity data for their compounds with corresponding, and eventually known activity data, and (b) search for other available compounds uploaded by the users community. Each piece of information about given compounds is owned by the user who initially uploaded it and multiple ownership is possible (this occurs if different users uploaded the same compounds or information pertaining to the same compounds). A web-based graphical user interface has been developed to assist compound uploading, compounds searching and data retrieval. Physico-chemical and ADME properties as well as substructure-based PAINS evaluations are computed on the fly for each uploaded compound. Samples of compounds that match a set of search criteria and additional data on these compounds could be requested directly from their owners with no mediation by the Mu.Ta.Lig Chemotheca team. Guest access provides a simplified search interface to retrieve only basic information such as compound IDs and related 2D or 3D chemical structures. Moreover, some compounds can be hidden to Guest users according to an owner's decision. In contrast, registered users have full access to all of the Chemotheca data including the permission to upload new compounds and/or update experimental/theoretical data (e.g., activities against new targets tested) related to already stored compounds. In order to facilitate scientific collaborations, all available data are connected to the corresponding owner's email address (available for registered users only). The Chemotheca web site is accessible at http://chemotheca.unicz.it.

Filling the gaps: Preparing nurse practitioners for hospitalist practice.

Over the last 20 years, the emergence of the hospitalist has changed the face of medicine. Hospitalists may serve as either general or specialty-focused providers caring for acutely ill patients in the hospital setting. As the demands and constraints of hospital-specific patient management have continued to grow, an increased need for inclusion of nurse practitioners (NP) into current hospitalist staffing models has occurred. A hospitalist-focused educational model has been developed to better prepare NP students for a variety of hospitalist roles after graduation. A hospitalist focused masters-level curriculum is discussed, as well as opportunities for advanced hospitalist education with post-graduate opportunities.

Molecular Docking and 3D-Pharmacophore Modeling to Study the Interactions of Chalcone Derivatives with Estrogen Receptor Alpha.

Tamoxifen is the most frequently used anti-estrogen adjuvant treatment for estrogen receptor-positive breast cancer. However, it is associated with an increased risk of several serious side-effects, such as uterine cancer, stroke, and pulmonary embolism. The 2',4'-dihydroxy-6-methoxy-3,5-dimethylchalcone (ChalcEA) from plant leaves of Eugenia aquea, has been found to inhibit the proliferation of MCF-7 human breast cancer cells in a dose-dependent manner, with an IC50 of 74.5 µg/mL (250 µM). The aim of this work was to study the molecular interactions of new ChalcEA derivatives formed with the Estrogen Receptor α (ERα) using computer aided drug design approaches. Molecular docking using Autodock 4.2 was employed to explore the modes of binding of ChalcEA derivatives with ERα. The 3D structure-based pharmacophore model was derived using LigandScout 4.1 Advanced to investigate the important chemical interactions of the ERα-tamoxifen complex structure. The binding energy and the tamoxifen-pharmacophore fit score of the best ChalcEA derivative (HNS10) were -12.33 kcal/mol and 67.07 kcal/mol, respectively. The HNS10 interacted with Leu346, Thr347, Leu349, Ala350, Glu353, Leu387, Met388, Leu391, Arg394, Met421, and Leu525. These results suggest that the new ChalcEA derivatives could serve as the lead compound for potent ERα inhibitor in the fight against breast cancer.

Rational drug design paradigms: the odyssey for designing better drugs.

Due to the time and effort requirements for the development of a new drug, and the high attrition rates associated with this developmental process, there is an intense effort by academic and industrial researchers to find novel ways for more effective drug development schemes. The first step in the discovery process of a new drug is the identification of the lead compound. The modern research tendency is to avoid the synthesis of new molecules based on chemical intuition, which is time and cost consuming, and instead to apply in silico rational drug design. This approach reduces the consumables and human personnel involved in the initial steps of the drug design. In this review real examples from our research activity aiming to discover new leads will be given for various dire warnings diseases. There is no recipe to follow for discovering new leads. The strategy to be followed depends on the knowledge of the studied system and the experience of the researchers. The described examples constitute successful and unsuccessful efforts and reflect the reality which medicinal chemists have to face in drug design and development. The drug stability is also discussed in both organic molecules and metallotherapeutics. This is an important issue in drug discovery as drug metabolism in the body can lead to various toxic and undesired molecules.

Hit finding: towards 'smarter' approaches.

Drug discovery is complex and risky, and the chances of success are low. One starting point to discover a new drug is the selective screening of a collection of high value and good quality compounds. Selection of compounds for screening is one of the challenging initial steps in the drug discovery process and is crucial for the success of the project. Optimal selection will enhance the chances of successful hit finding with regard to both number and quality of hits. Several scenarios for compound selection can be envisaged, and are primarily driven by knowledge of the target. Deciding the most appropriate scenario is important and appropriate software packages and chemoinformatics tools are available for these purposes. After screening, researchers may face challenges in selecting the best hits for further optimization. Numerous chemoinformatics tools have emerged recently to address challenges in hit analysis, prioritization and optimization.

Synthesis of opioidmimetics, 3-[H-Dmt-NH(CH(2))(m)]-6-[H-Dmt-NH(CH(2))(n)]-2(1H)-pyrazinones, and studies on structure-activity relationships.

Opioidmimetics containing 3-[H-Dmt-NH-(CH(2))(m)]-6-[H-Dmt-NH-(CH(2))(n)]-2(1H)-pyrazinone symmetric (m = n, 1-4) (1 - 4) and asymmetric (m, n = 1 - 4) aliphatic chains (5 - 16) were synthesized using dipeptidyl chloromethylketone intermediates. They had high mu-affinity (K(i)mu = 0.021 - 2.94 nM), delta-affinity (K(i)delta = 1.06 - 152.6 nM), and mu selectivity (K(i)delta/K(i)mu = 14 - 3,126). The opioidmimetics (1 - 16) exhibited mu agonism in proportion to their mu-receptor affinity. delta-Agonism was essentially lacking in the compounds except (4) and (16), and (1) and (2) indicated weak delta antagonism (pA(2) = 6.47 and 6.56, respectively). The data verify that a specific length of aliphatic linker is required between the Dmt pharmacophore and the pyrazinone ring to produce unique mu-opioid receptor ligands.

A new opioid designed multiple ligand derived from the micro opioid agonist endomorphin-2 and the delta opioid antagonist pharmacophore Dmt-Tic.

Opioid compounds with mixed micro agonist/delta antagonist properties could be used as analgesics with low propensity to induce tolerance and dependence. Here we report the synthesis of a new designed multiple ligand deriving from the micro selective agonist endomorphin-2 and the delta selective antagonist pharmacophore Dmt-Tic. As predicted, the resulting bivalent ligand showed a micro agonist/delta antagonist profile deriving from the corresponding activities of each pharmacophore.

Design and synthesis of opioidmimetics containing 2',6'-dimethyl-L-tyrosine and a pyrazinone-ring platform.

Twelve 2',6'-dimethyl-L-tyrosine (Dmt) analogues linked to a pyrazinone platform were synthesized as 3- or 6-[H-Dmt-NH(CH(2))(n)],3- or 6-R-2(1H)-pyrazinone (n=1-4). 3-[H-Dmt-NH-(CH(2))(4)]-6-beta-phenethyl-5-methyl-2(1H)-pyrazinone 11 bound to mu-opioid receptors with high affinity (K(i)mu=0.13 nM; K(i)delta/K(i)mu=447) with mu-agonism (GPI IC(50)=15.9 nM) and weak delta-antagonism (MVD pA(2)=6.35). Key factors affecting opioid affinity and functional bioactivity are the length of the aminoalkyl chain linked to Dmt and the nature of the R residue. These data present a simplified method for the formation of pyrazinone opioidmimetics and new lead compounds.

[N-allyl-Dmt1]-endomorphins are micro-opioid receptor antagonists lacking inverse agonist properties.

[N-allyl-Dmt1]-endomorphin-1 and -2 ([N-allyl-Dmt1]-EM-1 and -2) are new selective micro-opioid receptor antagonists obtained by N-alkylation with an allyl group on the amino terminus of 2',6'-dimethyl-L-tyrosine (Dmt) derivatives. To further characterize properties of these compounds, their intrinsic activities were assessed by functional guanosine 5'-O-(3-[35S]thiotriphosphate) binding assays and forskolin-stimulated cyclic AMP accumulation in cell membranes obtained from vehicle, morphine, and ethanol-treated SK-N-SH cells and brain membranes isolated from naive and morphine-dependent mice; their mode of action was compared with naloxone or naltrexone, which both are standard nonspecific opioid-receptor antagonists. [N-allyl-Dmt1]-EM-1 and -2 were neutral antagonists under all of the experimental conditions examined, in contrast to naloxone and naltrexone, which behave as neutral antagonists only in membranes from vehicle-treated cells and mice but act as inverse agonists in membranes from morphine- and ethanol-treated cells as well as morphine-treated mice. Both endomorphin analogs inhibited the naloxone- and naltrexone-elicited withdrawal syndromes from acute morphine dependence in mice. This suggests their potential therapeutic application in the treatment of drug addiction and alcohol abuse without the adverse effects observed with inverse agonist alkaloid-derived compounds that produce severe withdrawal symptoms.

Bifunctional [2',6'-dimethyl-L-tyrosine1]endomorphin-2 analogues substituted at position 3 with alkylated phenylalanine derivatives yield potent mixed mu-agonist/delta-antagonist and dual mu-agonist/delta-agonist opioid ligands.

Endomorphin-2 (H-Tyr-Pro-Phe-Phe-NH2) and [Dmt1]EM-2 (Dmt = 2',6'-dimethyl-l-tyrosine) analogues, containing alkylated Phe3 derivatives, 2'-monomethyl (2, 2'), 3',5'- and 2',6'-dimethyl (3, 3', and 4', respectively), 2',4',6'-trimethyl (6, 6'), 2'-ethyl-6'-methyl (7, 7'), and 2'-isopropyl-6'-methyl (8, 8') groups or Dmt (5, 5'), had the following characteristics: (i) [Xaa3]EM-2 analogues exhibited improved mu- and delta-opioid receptor affinities. The latter, however, were inconsequential (Kidelta = 491-3451 nM). (ii) [Dmt1,Xaa3]EM-2 analogues enhanced mu- and delta-opioid receptor affinities (Kimu = 0.069-0.32 nM; Kidelta = 1.83-99.8 nM) without kappa-opioid receptor interaction. (iii) There were elevated mu-bioactivity (IC50 = 0.12-14.4 nM) and abolished delta-agonism (IC50 > 10 muM in 2', 3', 4', 5', 6'), although 4' and 6' demonstrated a potent mixed mu-agonism/delta-antagonism (for 4', IC50mu = 0.12 and pA2 = 8.15; for 6', IC50mu = 0.21 nM and pA2 = 9.05) and 7' was a dual mu-agonist/delta-agonist (IC50mu = 0.17 nM; IC50delta = 0.51 nM).