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Background: Acute myeloid leukemia (AML) is a deadly cancer. B cell lymphoma 2 (BCL2) is frequently upregulated in AML and plays a vital role in the viability of both AML and AML stem cells. This study aimed to identify novel phytochemicals against BCL2 and evaluate their pharmacokinetics and toxicity prediction using in-silico tools. Methods: In-silico screening of phytochemicals against BCL2 active site using the PyRx0.8 AutoDock tool, followed by in silico pharmacokinetic and toxicity predictions was performed. Protein-protein interaction analysis was performed using the STRING database for assessing the interactions between BCL2 and neighboring interacting proteins. Results: In total, 1106 terpenoid compounds were screened to evaluate their binding affinity toward BCL2. Five natural compounds demonstrated strong binding to the BCL2 protein after extensive screening, detailed interaction analysis, and visual inspections. Notably, these compounds had higher binding energies than the positive control (venetoclax). In addition, these compounds were found to bind to key BCL2 residues and possess good drug-like properties. Conclusions: The identified phytochemicals represent an important initial step in drug discovery for AML management. Experimental validation is required to optimize the identified phytochemicals as potential BCL2 inhibitors. [ABSTRACT FROM AUTHOR]

Quantitative structure-activity relationship study was used to investigate the relationship between anti-pfdhfr activity and structure of twenty-eight 1,3,5-triazine derivatives. We performed benchmark studies on the molecular geometry, electron properties of 1,3,5-triazine using semi-empirical(PM3), density functional theory and post Hartree-Fock methods. Followed by a QSAR study using multiple linear regression (MLR) and artificial neural networks (ANN). The QSAR models developed allow identify/describe the relationship between the biological activity of the molecules and their molecular descriptors (topological, physicochemical, electronic...). A further external set of compounds was used for validation where a high correlation between experimental and predicted anti-pfdhfr activity values is noticed. This QSAR study provides useful information for developing novel pfdhfr inhibitors. The set's ADME properties and drug similarities, as well as newly produced compounds and reference ligand, were investigated. These findings would be extremely useful in guiding optimization for the development of new anti-pfdhfr drug candidates. [ABSTRACT FROM AUTHOR]

The emergence of multiresistant bacteria and the shortage of antibacterials in the drug pipeline creates the need to search for novel agents. Evolution drives the optimization of the structure of marine natural products to act as antibacterial agents. Polyketides are a vast and structurally diverse family of compounds that have been isolated from different marine microorganisms. Within the different polyketides, benzophenones, diphenyl ethers, anthraquinones, and xanthones have shown promising antibacterial activity. In this work, a dataset of 246 marine polyketides has been identified. In order to characterize the chemical space occupied by these marine polyketides, molecular descriptors and fingerprints were calculated. Molecular descriptors were analyzed according to the scaffold, and principal component analysis was performed to identify the relationships among the different descriptors. Generally, the identified marine polyketides are unsaturated, water-insoluble compounds. Among the different polyketides, diphenyl ethers tend to be more lipophilic and non-polar than the remaining classes. Molecular fingerprints were used to group the polyketides according to their molecular similarity into clusters. A total of 76 clusters were obtained, with a loose threshold for the Butina clustering algorithm, highlighting the large structural diversity of the marine polyketides. The large structural diversity was also evidenced by the visualization trees map assembled using the tree map (TMAP) unsupervised machine-learning method. The available antibacterial activity data were examined in terms of bacterial strains, and the activity data were used to rank the compounds according to their antibacterial potential. This potential ranking was used to identify the most promising compounds (four compounds) which can inspire the development of new structural analogs with better potency and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. [ABSTRACT FROM AUTHOR]

• Deep learning aims to improve and transform the drug discovery process at a rapid pace. • We propose DNMG, a generative adversarial network-based method combined with transfer learning. • DNMG offers significant advantages over other methods in terms of molecular pharmacophoric properties and binding affinity. • Analysis of the substructural fragments in the generated molecules, the pharmacochemical space can be efficiently scanned. Deep learning is improving and changing the process of de novo molecular design at a rapid pace. In recent years, great progress has been made in drug discovery and development by using deep generative models for de novo molecular design. However, most of the existing methods are string-based or graph-based and are limited by the lack of some very important properties, such as the three-dimensional information of molecules. We propose DNMG, a deep generative adversarial network (GAN) combined with transfer learning. Specifically, we use a Wasserstein-variant GAN based network architecture that considers the 3D grid spatial information of the ligand with atomic physicochemical properties to generate a representation of the molecule, which is then parsed into SMILES strings using an improved captioning network. Comprehensive in experiments demonstrate the ability of DNMG to generate valid and novel drug-like ligands. The DNMG model is used to design inhibitors for three targets, MK14, FNTA, and CDK2. The computational results show that the molecules generated by DNMG have better binding ability to the target proteins and better physicochemical properties. Overall, our deep generative model has excellent potential to generate molecules with high binding affinity for targets and explore the space of drug-like chemistry. [ABSTRACT FROM AUTHOR]

• We constructed drug-like datasets that cover the major drug-like spaces contained in QED and QEPPI. • We developed a conditional transformer method with MACCS fingerprints for generative design of drug-like molecules. • Deep molecular generation model explores the drug-like chemical space of drug-likeness and PPI-targeted drug-likeness. The generated drug-like molecules share the chemical space with known drugs. • The drug-like space captured by the combined quantitative estimation of drug-likeliness(QED) and quantitative estimate of protein–protein interaction targeting drug-likeness (QEPPI) can cover a larger drug-like space. The process of design/discovery of drugs involves the identification and design of novel molecules that have the desired properties and bind well to a given disease-relevant target. One of the main challenges to effectively identify potential drug candidates is to explore the vast drug-like chemical space to find novel chemical structures with desired physicochemical properties and biological characteristics. Moreover, the chemical space of currently available molecular libraries is only a small fraction of the total possible drug-like chemical space. Deep molecular generative models have received much attention and provide an alternative approach to the design and discovery of molecules. To efficiently explore the drug-like space, we first constructed the drug-like dataset and then performed the generative design of drug-like molecules using a Conditional Randomized Transformer approach with the molecular access system (MACCS) fingerprint as a condition and compared it with previously published molecular generative models. The results show that the deep molecular generative model explores the wider drug-like chemical space. The generated drug-like molecules share the chemical space with known drugs, and the drug-like space captured by the combination of quantitative estimation of drug-likeness (QED) and quantitative estimate of protein–protein interaction targeting drug-likeness (QEPPI) can cover a larger drug-like space. Finally, we show the potential application of the model in design of inhibitors of MDM2-p53 protein–protein interaction. Our results demonstrate the potential application of deep molecular generative models for guided exploration in drug-like chemical space and molecular design. [ABSTRACT FROM AUTHOR]

The purpose of the present study was to experimentally confirm the thermodynamic correlation between the intrinsic liquid–liquid phase separation (LLPS) concentration ( S 0 L L P S ) and crystalline solubility ( S 0 c ) of drug-like molecules. Based on the thermodynamic principles, the crystalline solubility LLPS concentration melting point ( T m ) equation (CLME) was derived ( l o g 10 S 0 C = l o g 10 S 0 L L P S − 0.0095 T m − 310 for 310 K). The S 0 L L P S values of 31 drugs were newly measured by simple bulk phase pH-shift or solvent-shift precipitation tests coupled with laser-assisted visual turbidity detection. To ensure the precipitant was not made crystalline at <10 s, the precipitation tests were also performed under the polarized light microscope. The calculated and observed log 10 S 0 C values showed a good correlation (root mean squared error: 0.40 log unit, absolute average error: 0.32 log unit). [ABSTRACT FROM AUTHOR]

In this paper, density, solubility parameter and transport properties viscosity, thermal conductivity and diffusion coefficient at infinite dilution in water (diffusivity) of drug-like fluids including two groups have been calculated. We have studied the modified perturbed hard trimmer chain equation of state combined with statistical model and modified rough hard-sphere (RHS) theory to model the solubility parameter and transport properties of drug-like fluids for temperature ranging from 129.95 to 1090.15 K and atmosphere pressure. From 838 experimental data points examined, the average absolute relative deviation (AARD) of calculated density was found to be 1.05%. In the case of solubility parameter, the new statistical-based model correlated 234 experimental data points with AARD equal to 0.70%. RHS-based model has also been extended to calculated 601, 771 and 261 experimental data points of viscosity, thermal conductivity and diffusivity with AARD equal to 3.11%, 2.12% and 7.69%, respectively. [ABSTRACT FROM AUTHOR]

Several hundred (396) compounds from New Zealand flora with medicinal properties were analyzed for their physicochemical properties. It was found that approximately 10 % fulfilled all the requirements to be considered to be lead‐like, over half of the compounds were deemed to be in the drug‐like space and ≈75 % were in the known drug space. These results indicate the presence of a significant proportion of compounds that are of particular interest to pursue as potential lead compounds or therapeutics. Additionally, compound classes were analyzed separately—most carbonyl‐containing compounds (aldehydes, ketones, esters and lactones), along with phenols were the most lead‐like compounds, which also displayed very good proportions in the drug‐like and known drug space. The information presented herein can be harnessed and utilized in future work, through focussing on the compounds and compound classes that exhibit high‐levels of lead‐likeness for further development. [ABSTRACT FROM AUTHOR]

The physicochemical properties of classical lignans, neolignans, flavonolignans and carbohydrate-lignan conjugates (CLCs) were analysed to assess their ADMET profiles and establish if these compounds are lead-like/drug-like and thus have potential to be or act as leads in the development of future therapeutics. It was found that while no studied compounds were lead-like, a very large proportion (>75%) fulfilled all the requirements to be deemed as present in drug-like space and almost all compounds studied were in the known drug space. Principal component analysis was an effective technique that enabled the investigation of the relationship between the studied molecular descriptors and was able to separate the lignans from their sugar derivatives and flavonolignans, primarily according to the parameters that are considered when defining chemical space (i.e., number of hydrogen bond donors, acceptors, rotatable bonds, polar surface area and molecular weight). These results indicate that while CLCs and flavonolignans are less drug-like, lignans show a particularly high level of drug-likeness, an observation that coupled with their potent biological activities, demands future pursuit into their potential for use as therapeutics. [ABSTRACT FROM AUTHOR]

Background In view of the need to continuously feed the pipeline with new anti-malarial agents adapted to differentiated and more stringent target product profiles (e g, new modes of action, transmission-blocking activity or long-duration chemo-protection), a chemical library consisting of more than 250,000 compounds has been evaluated in a blood-stage Plasmodium falciparum growth inhibition assay and further assessed for chemical diversity and novelty. Methods The selection cascade used for the triaging of hits from the chemical library started with a robust three-step in vitro assay followed by an in silico analysis of the resulting confirmed hits. Upon reaching the predefined requirements for selectivity and potency, the set of hits was subjected to computational analysis to assess chemical properties and diversity. Furthermore, known marketed anti-malarial drugs were co-clustered acting as 'signposts' in the chemical space defined by the hits. Then, in cerebro evaluation of the chemical structures was performed to identify scaffolds that currently are or have been the focus of anti-malarial medicinal chemistry programmes. Next, prioritization according to relaxed physicochemical parameters took place, along with the search for structural analogues. Ultimately, synthesis of novel chemotypes with desired properties was performed and the resulting compounds were subsequently retested in a P. falciparum growth inhibition assay. Results This screening campaign led to a 1.25% primary hit rate, which decreased to 0.77% upon confirmatory repeat screening. With the predefined potency (EC50 < 1 µM) and selectivity (SI > 10) criteria, 178 compounds progressed to the next steps where chemical diversity, physicochemical properties and novelty assessment were taken into account. This resulted in the selection of 15 distinct chemical series. Conclusion A selection cascade was applied to prioritize hits resulting from the screening of a mediumsized chemical library against blood-stage P. falciparum. Emphasis was placed on chemical novelty whereby computational clustering, data mining of known anti-malarial chemotypes and the application of relaxed physicochemical filters, were key to the process. This led to the selection of 15 chemical series from which ten confirmed their activity when newly synthesized sample were tested. [ABSTRACT FROM AUTHOR]

Context: Galbanic acid (GA) is a biologically active sesquiterpene coumarin from Ferula species (Apiaceae). This compound showed various biological properties including anticancer, cancer chemopreventive, anticoagulant, antiviral, and antileishmanial activities. Objectives: This article is a review on the synthesis, biosynthesis, and biological activities of GA. In addition, we discussed gaps in our knowledge about GA that deserve future research. In this article, we also evaluated the drug-likeness of GA in silico. Methods: All relevant databases were searched for the terms 'galbanic acid', 'methyl galbanate', ' Ferula' and 'sesquiterpene coumarin' without limitation, up to May 2013. Information on GA was collected via electronic search using Pubmed, Scopus, Web of Science, and Sciencedirect. All physicochemical parameters used for the prediction of drug-likeness were calculated using MarvinSketch (version 5.11, academic package, ChemAxon). Results: This compound showed various biological properties including anticancer, cancer chemopreventive, anticoagulant, antiviral and antileishmanial activities. GA can inhibit the growth of prostate cancer cells via decreasing androgen receptor abundance. In silico physicochemical studies on GA showed that this compound has drug-like properties, the parameters that are important to predict potential of a compound for being a future drug. Conclusion: GA is a valuable natural product with various biological activities. New discoveries with GA are to be expected. [ABSTRACT FROM AUTHOR]

Abstract: Kinase enzymes play a key role in the development and progression of cancer. Inhibitors of deregulated kinases are effective small molecule anticancer drugs. The 2(1H)-pyrazinone heterocycle is a previously unexploited motif that can fulfil the structural requirements for ATP-competitive inhibition of kinases. Rapid solution-phase syntheses of novel 3,5- and 3,6-disubstituted-2(1H)-pyrazinones were developed through selective, sequential substitution of 2,5-dihalo-3-benzyloxypyrazine and 3,5-dihalo-2(1H)-pyrazinone intermediates. Palladium-catalysed cross-couplings and SNAr reactions were used to introduce substituents chosen on the basis of the calculated physicochemical properties of the target pyrazinones. Representative compounds demonstrated good solubility, kinase inhibitory activity and antiproliferative activity in human tumour cells, confirming the suitability of this chemical class as a kinase-focused library. [Copyright &y& Elsevier]

Abstract: Solubility data in different solvents are an important issue for separation processes involving complex molecules such as natural products and pharmaceutical drugs. Nonetheless, solubility data are in general scarce and difficult to obtain, and so models are important tools to generate the necessary estimates. Different correlative, statistical and thermodynamic models have been proposed to evaluate solubilities. From these, the more theoretically sound thermodynamic models allow to generate estimates at broader temperature, pressure and composition conditions while using a smaller amount of experimental information. Among these, the cubic-plus-association equation of state that combines the simplicity and robustness of a cubic equation of state with the Wertheim''s association contribution has been under attention. In this work, this EoS is for the first time proposed to model organic phase solubilities of drug-like molecules in a wide range of temperatures. Solubilities of acetanilide, acetylsalicylic acid, adipic acid, ascorbic acid, hydroquinone, ibuprofen, paracetamol and stearic acid were estimated in alcohols, ketones, alkanes, esters, acids, aromatics, chlorinated solvents, as well as in other common solvents. The hydrogen bonding behaviour was explicitly accounted for with each associating group being treated individually, as well as multiple group substitutions. Accurate correlations were obtained using a single binary interaction parameter (global AAD of 24.2%), while considering the complexity of the studied systems predictions were generally also satisfactory. [Copyright &y& Elsevier]

Abstract: Although of extreme importance for evaluating the effective therapeutic action, aqueous solubility data involving drug-like molecules are scarce. Thermodynamic models can be used to estimate these solubilities, and different models, namely activity coefficient models, have been applied for that purpose. Still, these frequently cannot describe with accuracy broad temperature and pressure ranges, various solvent compositions or multifunctional molecules. Despite the success of the cubic-plus-association (CPA) equation of state (EoS) in modeling complex systems, it has never been used for modeling the phase equilibria of drug-like molecules, explicitly accounting for the number and nature of associating sites. In this work, aqueous solubilities of different complex solutes, like acetamide, acetanilide, acetylsalicylic acid, adipic acid, ascorbic acid, bisphenol A, camphor, dibenzofuran, hexachlorobenzene, hydroquinone, ibuprofen, nicotinic acid, paracetamol, piperazine, stearic acid, sorbitol, terephthalic acid and vanillin are estimated in a wide temperature range with the CPA EoS. Generally, the modeling results are within the experimental uncertainties using a single temperature independent binary interaction parameter, or a solvation parameter for some non-associating solutes. Globally, an average absolute deviation of 39% was obtained. [Copyright &y& Elsevier]

Abstract: We have optimized a novel series of potent p38 MAP kinase inhibitors based on an α-ketoamide scaffold through structure based design that due to their extended molecular architecture bind, in addition to the ATP site, to an allosteric pocket. In vitro ADME, in vivo PK and efficacy studies show these compounds to have drug-like characteristics and have resulted in the nomination of a development candidate which is currently in phase II clinical trials for the oral treatment of inflammatory conditions. [ABSTRACT FROM AUTHOR]

The 3′-ends of human chromosomal DNA terminate in short single-stranded guanine-rich tandem-repeat sequences. In cancer cells, these are associated with the telomere-maintenance enzyme telomerase together with the end-binding protein hPOT1. Small molecules that can compete with these proteins and induce the single-stranded DNA to form quadruplex–ligand complexes are, in effect, able to expose these 3′-ends, which results in the activation of a DNA damage response and selective inhibition of cell growth. Several of these G-quadruplex binding molecules have shown promising anticancer activity in tumour xenograft models, which indicate that the approach may be applicable to the treatment of a wide range of human cancers. This minireview summarizes the available data on these compounds and the challenges posed for drug discovery. [ABSTRACT FROM AUTHOR]

Abstract: Despite the extensive literature describing the role of the ATP-gated P2X3 receptors in a variety of physiological processes the potential of antagonists as therapeutic agents has been limited by the lack of drug-like selective molecules. In this paper we report the discovery and optimization of RO-85, a novel drug-like, potent and selective P2X3 antagonist. High-throughput screening of the Roche compound collection identified a small hit series of heterocyclic amides from a large parallel synthesis library. Rapid optimization, facilitated by high-throughput synthesis, focusing on increasing potency and improving drug-likeness resulted in the discovery of RO-85. [Copyright &y& Elsevier]

Acid-base ionization constant (pKa) values have considerable influence on the physicochemical and pharmacokinetic properties of therapeutic substances. A set of 907 drugs was examined to determine the proportion of drugs that contain an ionizable group and the distribution of their pKa values. Using this contemporary set of compounds it was found that 64% of these compounds contained an ionizable group. Within this group of ionizable compounds, 34% contained a single basic group while only 20% contained a single acidic functional group. The single acid and single base containing substances were investigated further to examine the distributions of their pKa values. These data are discussed and analyzed with a focus on the entire set as well as central nervous system, non-central nervous system and oral drugs. The findings from this research will prompt pharmaceutical companies to assess the constitution of their screening libraries, such that focus is placed on the proportion of ionizable substances, the ratio of acids to bases and the distribution of pKa values. [ABSTRACT FROM AUTHOR]

• Pyridazines have a prominent place in various science, especially in medicinal chemistry and agrochemical. • Exhibiting a wide range of pyridazine-containing drugs and agrochemical products. • Collection and classification of arylglyoxal monohydrates-based one-pot multi-component synthetic strategies for the preparation of various potentially biologically active pyridazines. Pyridazine derivatives are a consequential class of heterocyclic compounds, which expose a wide range of distinguished biological activities. For example, pyridazine scaffolds are known as inhibitors of acetylcholinesterase (AChE), butyrylcholinesterase (BChE), tyrosine kinase (TYK), janus kinase (JAK), tankyrase (TNKS), autotaxin (ATX), glyoxalase 1 (GLO-1), carbonic anhydrase (CA), aldose reductase (ALR), aldehdyde oxidase (AOX), excitatory amino acid transporter 2 (EAAT-2) activator, vascular endothelial growth factor receptor 2 (VEGFR-2), glutaminase 1 (GLS-1), α-glucosidase, α-amylase, cyclooxygenases 1 and 2 (COX-1 and COX-2), cyclin-dependant kinase (CDK), glycogen synthase kinase 3 (GSK-3), apoptosis signal-regulating kinase 1 (ASK-1), hedgehog (Hh) signaling pathway, sodium-glucose transport protein 2 (SGLT-2), hypoxia-inducible factor (HIF) prolyl hydroxylase (PHD), factor XIa, stearoyl-CoA desaturase 1 (SCD-1), HIV-1 reverse transcriptase 1, monoamine oxidases A and B (MAO-A and MAO-B), tubulin polymerization topoisomerase Iiα (Topo Iiα), poly(ADP-ribose) polymerase (PARP), angiotensin-converting enzyme (ACE), phosphodiesterase (PDE), and many others. Furthermore, the mentioned heterocyclic frameworks exist in the structure of commercial drugs and agrochemical products. In addition, they have a decisive role in organic synthesis, especially as starting material in the pharmaceutically interesting compounds preparations. In this regard, the design and introduce simple, cost-effective, highly efficient, and selective synthetic strategies for the mentioned six-membered nitrogen-containing heterocyclic frameworks preparation are precious. This review has been covered almost all research papers that were described a series of arylglyoxal monohydrates-based one-pot multi-component protocols for the synthesis of various attention-grabbing potentially biologically active pyridazines. It is hoped that this review paper can be a little help to synthetic scientists, methodologists, and drug (or drug-like compounds) designers. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: P2X purinoceptors are ligand-gated ion channels whose endogenous ligand is ATP. Both the P2X3 and P2X2/3 receptor subtypes have been shown to play an important role in the regulation of sensory function and dual P2X3/P2X2/3 antagonists offer significant potential for the treatment of pain. A high-throughput screen of the Roche compound collection resulted in the identification of a novel series of diaminopyrimidines; subsequent optimization resulted in the discovery of RO-4, a potent, selective and drug-like dual P2X3/P2X2/3 antagonist. [Copyright &y& Elsevier]

Abstract: We have identified a second series of potent p38 inhibitors. As with our first generation series, these compounds are based on an α-ketoamide scaffold. The reversal of the ketoamide order, however, introduces more chemical flexibility and in addition results in improve potencies against p38. [Copyright &y& Elsevier]

Abstract: We have identified a novel series of potent p38 MAP kinase inhibitors through structure-based design which due to their extended molecular architecture bind, in addition to the ATP site, to an allosteric pocket. In vitro ADME and in vivo PK studies show these compounds to have drug-like characteristics which could result in the development of an oral treatment for inflammatory conditions. [Copyright &y& Elsevier]

The low success rate of converting lead compounds into drugs owing to unfavorable pharmacokinetic parameters has evoked a renewed interest in understanding more clearly what makes a compound drug-like. This article reviews a number of computational techniques for identifying drug-like molecules, ranging from simple counting schemes to sophisticated machine learning techniques such as neural networks, along with their application and challenges. [ABSTRACT FROM AUTHOR]

Three dipicolylamine based ligands and their rhenium(I) complexes were synthesized and characterized toward utilizing the compounds as potential imaging and anti-inflammatory agents. Herein we report two new fac -Re(I) tricarbonyl complexes, fac -[Re(CO) 3 (N (SO 2)(1-nap)dpa)]PF 6 (C1) and fac -[Re(CO) 3 (N (SO 2)(2-nap)dpa)]PF 6 (C2), of two naphthalene derivatized tridentate ligands (N (SO 2)(1-nap)dpa (L1) and N (SO 2)(2-nap)dpa (L2)) and one reported Re(I) complex, fac -[Re(CO) 3 (N (SO 2 Me 2 Nnap)dpa)]PF 6 (C3), of a dansyl appended di-2-picolylamine ligand (N (SO 2 Me 2 Nnap)dpa (L3)). The properties of the compounds were elucidated using spectrophotometric measurements (UV–Vis, FTIR and 1H NMR). A single crystal X-ray study was carried out for the three ligands. The 1H NMR spectra of the three complexes obtained in DMSO‑ d 6 displayed two doublets (exo -CH and endo -CH) for the magnetically inequivalent methylene protons, compared to their uncoordinated ligands where the methylene protons show a singlet peak. The formation of the metal complexes was further supported by FTIR spectra in which the S N stretching band for the metal complexes appears at lower wavenumbers compared to that of the corresponding free ligands. In comparison with the uncoordinated ligands, the Re(I) complexes, C1 and C3 , displayed a bathochromic shift while C2 showed a hypsochromic shift in the absorption spectra in methanol. The fluorescent maxima and the fluorescence quantum yield (ΦF) of L1 and L2 were 338 nm (ΦF = 0.056) and 343 nm (ΦF = 0.039), respectively. Interestingly, all the compounds except C2 showed excellent fluorescent emissions. Biologically, the compounds were investigated for their cytotoxicity in vitro on human lymphocytes following the Trypan blue dye exclusion method. It was observed that both Re(I) complexes as well as the ligands show low toxicity towards human lymphocytes at working concentrations below 10 mg/ml (L1 , L2 : 0.026 M, L3 : 0.023 M, C1 , C2 , C3 : 0.012 M). In silico studies revealed that the ligands are potential candidates for anti-inflammatory agents and this was further supported by molecular docking studies, in which they showed a higher affinity for Prostaglandin synthase 2. These drug-like molecules, having an affinity to bovine serum albumin, are thus potential drug leads for anti-inflammatory agents. [ABSTRACT FROM AUTHOR]

After benchmarks on pyrazolo[1,5-a][1,3,5]triazin-2-thioxo-4-ones, we carried out B3LYP density functional theory computations on the structure and vibrational spectroscopy of a series of twenty-one of its derivatives exhibiting various extent of inhibitory activity against thymidine phosphorylase (TP). Then, we performed drug-like calculations, quantitative structure-activity relationship (QSAR) modeling and an evaluation of the physicochemical properties of this series. In order to design the relationships between molecular descriptors and TP inhibition by pyrazolo[1,5-a][1,3,5]triazin-2-thioxo-4-ones derivatives, we used a multiple linear regression (MLR) procedure. A QSAR model is predicted. A further external set of molecules was used for validation where a high correlation between experimental and predicted activity values is noticed. Image 1 • Equilibrium structure and vibrational spectroscopy of Pyrazolo[1,5-a][1,3,5]triazin-2-thioxo-4-ones. • Theoretical equilibrium structures of Pyrazolo[1,5-a][1,3,5]triazin-2-thioxo-4-ones derivatives. • Validation of B3LYP/6-31G++(d,p) method for computing Pyrazolo[1,5-a][1,3,5]triazin-2-thioxo-4-ones derivatives properties. • QSAR modeling of Pyrazolo[1,5-a][1,3,5]triazin-2-thioxo-4-ones derivatives as thymidine phosphorylase inhibitors. [ABSTRACT FROM AUTHOR]

Deep-sea natural products have been created by unique marine organisms that thrive in a challenging environment of extreme conditions for its inhabitants. In this study, 179 deep-sea natural products isolated from 2009 to 2013 were investigated by analysing their physicochemical properties that are important indicators of the ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) profile of a compound. The study and analysis of these molecular descriptors and characteristics enabled the defining of these compounds in various chemical spaces, particularly as an indication of their drug-likeness and position in chemical space and is the first to be conducted to analyse deep-sea derived natural products. It was found that ~40% of all deep-sea natural products were drug-like and 2/3 were within Known Drug Space (KDS), highlighting the high drug-likeness of a significant proportion of deep-sea natural products, most of which have already been shown to have notable biological activities, that should be further investigated as potential therapeutics. Furthermore, this study was able to reveal the general structural differences between compounds from Animalia, Bacteria and Fungi organisms where it was observed that natural products from members of the Animalia kingdom are structurally more varied than compounds from bacteria and fungi. It was also noted that, in general, fungi-derived compounds occupy a more favourable position in drug-like chemical space and are a rich and promising source of biologically-active natural products for the purposes of drug development and therapeutic application. [ABSTRACT FROM AUTHOR]