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Virtual screening (VS) is an important approach in drug discovery and relies on the availability of a virtual library of synthetically tractable molecules. Ugi reaction (UR) represents an important multi-component reaction (MCR) that reliably produces a peptidomimetic scaffold. Recent literature shows that a tactically assembled Ugi adduct can be subjected to further chemical modifications to yield a variety of rings and scaffolds, thus, renewing the interest in this old reaction. Given the reliability and efficiency of UR, we collated an UR derived library (URDL) of small molecules (total = 5773) for VS. The synthesis of the majority of URDL molecules may be carried out in 1-2 pots in a time and cost-effective manner. The detailed analysis of the average property and chemical space of URDL was also carried out using the open-source Datawarrior program. The comparison with FDA-approved oral drugs and inhibitors of protein-protein interactions (iPPIs) suggests URDL molecules are 'clean', drug-like, and conform to a structurally distinct space from the other two categories. The average physicochemical properties of compounds in the URDL library lie closer to iPPI molecules than oral drugs thus suggesting that the URDL resource can be applied to discover novel iPPI molecules. The URDL molecules consist of diverse ring systems, many of which have not been exploited yet for drug design. Thus, URDL represents a small virtual library of drug-like molecules with unexplored chemical space designed for VS. The structures of all molecules of URDL, oral drugs, and iPPI compounds are being made freely accessible as supplementary information for broader application.

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In an effort to discover a novel potential bioactive compound, a mono-nuclear Pd(II) complex with an amino acid derivative as ligand was synthesized and characterized through experimental and computational methodologies. A square-planar configuration was suggested for palladium(II) complex utilizing density functional theory. MEP map and Mulliken atomic charge were detected electrophilic and nucleophilic regions of the compound for reactions. The lipophilicity and cytotoxic activity of the complex was more effective than cisplatin. Also, OSIRIS DataWarrior revealed proper oral bioavailability and good drug-likeness for the compound. In-vitro binding behavior of the Pd(II) complex with DNA and serum albumin (BSA) were fully determined via variety of procedures including fluorescence, UV-Vis, CD, viscosity, gel electrophoresis experiments and molecular simulation. The negative signs of ΔH° and ΔS° for Pd(II) complex-CT-DNA/-BSA systems indicated the existence of hydrogen bonding/van der Waals interactions for both binding systems. Additionally, docking simulation illustrated the interaction of Pd(II) complex with the minor groove of DNA and the hydrophobic cavity of the BSA (drug binding site I).

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Aim: Phytocompounds are important due to their uniqueness, however, only few reach the development phase due to their poor pharmacokinetics. Therefore, preassessing the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties is essential in drug discovery. Methodology: Biologically diverse databases (Phytochemica, SerpentinaDB, SANCDB and NuBBEDB) covering the region of India, Brazil and South Africa were considered to predict the ADMET using chemoinformatic tools (Qikprop, pkCSM and DataWarrior). Results: Screening through each of pharmacokinetic criteria resulted in identification of 24 compounds that adhere to all the ADMET properties. Furthermore, assessment revealed that five have potent anticancer biological activity against cancer cell lines. Conclusion: We have established an open-access database (ADMET-BIS) to enable identification of promising molecules that follow ADMET properties and can be considered for drug development.

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Botulinum neurotoxins (BoNTs) are the most toxic category A biological warfare agents. There is no therapeutics available for BoNT intoxication yet, necessitating the development of a medical countermeasure against these neurotoxins. The discovery of small molecule-based drugs has revolutionized in the last two decades resulting in the identification of several small molecule inhibitors of BoNTs. However, none progressed to clinical trials. 8-Hydroxyquinolines scaffold-based molecules are important 'privileged structures' that can be exploited as inhibitors of a diverse range of targets. In this review, our study of recent reports suggests the development of 8-hydroxyquinoline derived molecules as a potential drug may be on the horizon.

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BACKGROUND: The logarithmic acid dissociation constant pKa reflects the ionization of a chemical, which affects lipophilicity, solubility, protein binding, and ability to pass through the plasma membrane. Thus, pKa affects chemical absorption, distribution, metabolism, excretion, and toxicity properties. Multiple proprietary software packages exist for the prediction of pKa, but to the best of our knowledge no free and open-source programs exist for this purpose. Using a freely available data set and three machine learning approaches, we developed open-source models for pKa prediction. METHODS: The experimental strongest acidic and strongest basic pKa values in water for 7912 chemicals were obtained from DataWarrior, a freely available software package. Chemical structures were curated and standardized for quantitative structure-activity relationship (QSAR) modeling using KNIME, and a subset comprising 79% of the initial set was used for modeling. To evaluate different approaches to modeling, several datasets were constructed based on different processing of chemical structures with acidic and/or basic pKas. Continuous molecular descriptors, binary fingerprints, and fragment counts were generated using PaDEL, and pKa prediction models were created using three machine learning methods, (1) support vector machines (SVM) combined with k-nearest neighbors (kNN), (2) extreme gradient boosting (XGB) and (3) deep neural networks (DNN). RESULTS: The three methods delivered comparable performances on the training and test sets with a root-mean-squared error (RMSE) around 1.5 and a coefficient of determination (R2) around 0.80. Two commercial pKa predictors from ACD/Labs and ChemAxon were used to benchmark the three best models developed in this work, and performance of our models compared favorably to the commercial products. CONCLUSIONS: This work provides multiple QSAR models to predict the strongest acidic and strongest basic pKas of chemicals, built using publicly available data, and provided as free and open-source software on GitHub.

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INTRODUCTION: ß-Tubulin is an important target for the binding of anti-cancer drugs, in particular, paclitaxel (taxol), vinblastine and epothilone. However, mutations in ß-tubulin structure give resistance to chemotherapeutic agents. Notably, mutations at R306C, F270 V, L217R, L228F, A185T and A248V positions in ß-tubulin give high resistance for paclitaxel binding. OBJECTIVE: To discover novel inhibitors of ß-tubulin from natural sources, particularly alkaloids, using a virtual screening approach. METHODOLOGY: A virtual screening approach was employed to find potent lead molecules from the Naturally-occurring Plant-based Anti-cancer Compound-activity Target (NPACT) database. Alkaloids have great potential to be anti-cancer agents. Therefore, we have screened all alkaloids from a total of 1574 molecules from the NPACT database for our study. Initially, Molinspiration and DataWarrior programs were utilised to calculate pharmacokinetics and toxicity risks of the alkaloids, respectively. Subsequently, AutoDock algorithm was employed to understand the binding efficiency of alkaloids against ß-tubulin. The binding affinity of the docked complex was confirmed by means of an intermolecular interaction study. Moreover, oral toxicity was predicted by using ProTox program. Further, metabolising capacity of drugs was studied by using SmartCYP software. Additionally, scaffold analysis was done with the help of scaffold trees and dendrograms, providing knowledge about the building blocks for parent-compound synthesis. RESULTS: Overall, the results of our computational analysis indicate that isostrychnine, obtained from Strychnosnux-vomica, satisfies pharmacokinetic and bioavailability properties, binds efficiently with ß-tubulin. Thus, it could be a promising lead for the treatment of paclitaxel resistant cancer types. CONCLUSION: This is the first observation of inhibitory activity of isostrychnine against ß-tubulin and warrants further experimental investigation. Copyright © 2016 John Wiley & Sons, Ltd.

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