Tailoring MIL-100(Fe)-derived catalyst for controlled carbon dioxide conversion and product selectivity.

Here in, we are reporting the effect of the catalyst particle size on the catalytic activity and product selectivity by understanding the strength of the interaction between the active catalyst and the reactants (CO and H). In this regard, two catalytic systems having different active catalyst particle sizes and support surface areas were synthesized using metal-organic frameworks (MOF) (MIL-100(Fe)) having two crystal size ranges as sacrificial templates. The active catalyst having smaller nanoparticles exhibited greater chemisorption of hydrogen (Fe-H bond), resulting in heightened selectivity for paraffin due to hydrogenation of re-adsorbed olefins.

Synthesis, Modelling, and Anticonvulsant Studies of New Quinazolines Showing Three Highly Active Compounds with Low Toxicity and High Affinity to the GABA-A Receptor.

Some novel fluorinated quinazolines (-) were designed and synthesized to be evaluated for their anticonvulsant activity and their neurotoxicity. Structures of all newly synthesized compounds were confirmed by their infrared (IR), mass spectrometry (MS) spectra, ¹H nuclear magnetic resonance (NMR), C-NMR, and elemental analysis (CHN). The anticonvulsant activity was evaluated by a subcutaneous pentylenetetrazole (scPTZ) test and maximal electroshock (MES)-induced seizure test, while neurotoxicity was evaluated by a rotorod test.

New ursane triterpenoids from Ficus pandurata and their binding affinity for human cannabinoid and opioid receptors.

Phytochemical investigation of Ficus pandurata Hance (Moraceae) fruits has led to the isolation of two new triterpenoids, ficupanduratin A [1β-hydroxy-3β-acetoxy-11α-methoxy-urs-12-ene] (11) and ficupanduratin B [21α-hydroxy-3β-acetoxy-11α-methoxy-urs-12-ene] (17), along with 20 known compounds: α-amyrin acetate (1), α-amyrin (2), 3β-acetoxy-20-taraxasten-22-one (3), 3β-acetoxy-11α-methoxy-olean-12-ene (4), 3β-acetoxy-11α-methoxy-12-ursene (5), 11-oxo-α-amyrin acetate (6), 11-oxo-β-amyrin acetate (7), palmitic acid (8), stigmast-4,22-diene-3,6-dione (9), stigmast-4-ene-3,6-dione (10), stigmasterol (12), β-sitosterol (13), stigmast-22-ene-3,6-dione (14), stigmastane-3,6-dione (15), 3β,21β-dihydroxy-11α-methoxy-olean-12-ene (16), 3β-hydroxy-11α-methoxyurs-12-ene (18), 6-hydroxystigmast-4,22-diene-3-one (19), 6-hydroxystigmast-4-ene-3-one (20), 11α,21α-dihydroxy-3β-acetoxy-urs-12-ene (21), and β-sitosterol-3-O-β-D-glucopyranoside (22). Compound 21 is reported for the first time from a natural source. The structures of the 20 compounds were elucidated on the basis of IR, 1D ((1)H and (13)C), 2D ((1)H-(1)H COSY, HSQC, HMBC and NOESY) NMR and MS spectroscopic data, in addition to comparison with literature data.

Synthesis, characterization, molecular modeling, and potential antimicrobial and anticancer activities of novel 2-aminoisoindoline-1,3-dione derivatives.

In an effort to establish new drug candidates with improved antimicrobial and anticancer activities, we report here synthesis, molecular modeling, and in vitro biological evaluation of novel substituted N-amino phthalamide derivatives (3a-b, 4a-b, 5a-j, and 6). Structures of the newly synthesized compounds were described by IR, (1)H &(13)CNMR and LC-MS spectral data. The novel compounds were evaluated for their antibacterial activity against four types of Gm+ve and two for Gm-ve types, and antifungal activity against three fungi microorganisms by well diffusion method.

Self Organizing Map-Based Classification of Cathepsin k and S Inhibitors with Different Selectivity Profiles Using Different Structural Molecular Fingerprints: Design and Application for Discovery of Novel Hits.

The main step in a successful drug discovery pipeline is the identification of small potent compounds that selectively bind to the target of interest with high affinity. However, there is still a shortage of efficient and accurate computational methods with powerful capability to study and hence predict compound selectivity properties. In this work, we propose an affordable machine learning method to perform compound selectivity classification and prediction.

Discovery of novel phthalimide analogs: Synthesis, antimicrobial and antitubercular screening with molecular docking studies.

In continuation of our endeavor towards the design and development of potent and effective antimicrobial agents, three series of phthalimide derivatives ( and ) were synthesized, fully characterized and evaluated for their potential antibacterial, antifungal and antimycobacterial activities. These efforts led to the discovery of nine compounds , and (MIC range from 0.49 to 31.

Berberine Reduces Neurotoxicity Related to Nonalcoholic Steatohepatitis in Rats.

Berberine is a plant alkaloid that has several pharmacological effects such as antioxidant, antilipidemic, and anti-inflammatory effects. Nonalcoholic steatohepatitis (NASH) triggers different aspects of disorders such as impaired endogenous lipid metabolism, hypercholesterolemia, oxidative stress, and neurotoxicity. In this study, we examined the mechanism by which NASH induces neurotoxicity and the protective effect of berberine against both NASH and its associated neurotoxicity.

Design and evaluation of bonded atom pair descriptors.

Atom pairs have been among the first systematically derived fragment-type topological descriptors and have been one of the origins of two-dimensional fingerprint searching. These descriptors continue to be popular and widely used to this date. Herein we introduce a new type of atom pair descriptors, bonded atom pairs, that exclusively capture short-range atom environment information and, thus, depart in their design from other topological descriptors that enumerate bond paths of varying length.

Methods for computer-aided chemical biology. Part 5: rationalizing the selectivity of cathepsin inhibitors on the basis of molecular fragments and topological feature distributions.

We report a fragment-based approach to analyze the target selectivity of active compounds. Sets of inhibitors were studied having different activity and selectivity for cathepsins, a family of therapeutically relevant thiol proteases. A systematic analysis was carried out of molecular fragments and atom environment features and their frequency of occurrence for compounds with different selectivity.

Methods for computer-aided chemical biology. Part 4: selectivity searching for ion channel ligands and mapping of molecular fragments as selectivity markers.

For the computational exploration of structure-selectivity relationships, a compound selectivity system consisting of 243 antagonists of ionotropic glutamate ligand-gated ion channels was designed. Selected antagonists were organized in nine different selectivity sets. In systematic selectivity search calculations utilizing these data sets, structural fingerprints produced a significant enrichment of selective compounds over non-selective molecules and database decoys.

Exploring structure-selectivity relationships of biogenic amine GPCR antagonists using similarity searching and dynamic compound mapping.

We design and analyze compound selectivity sets of antagonists with differential selectivity against seven biogenic amine G-protein coupled receptors. The selectivity sets consist of a total of 267 antagonists and contain a spectrum of in part closely related molecular scaffolds. Each set represents a different selectivity profile.

Methods for computer-aided chemical biology. Part 2: Evaluation of compound selectivity using 2D molecular fingerprints.

We analyze 558 compounds with selectivity against members of different protein families using two-dimensional molecular fingerprint methods. The calculations target compounds selective for 13 targets belonging to three families. These compound sets were especially designed for selectivity studies.

Methods for computer-aided chemical biology. Part 1: Design of a benchmark system for the evaluation of compound selectivity.

Computational drug design and discovery methods have traditionally put much emphasis on the identification of novel active compounds and the optimization of their potency. For chemical genetics and genomics applications, an important task is the identification of small molecules that are selective against target families, subfamilies, or individual targets and can be used as molecular probes for specific functions. In order to develop or tune computational methods for such applications, there is a need for molecular benchmark systems that focus on compound selectivity, rather than biological activity (in qualitative terms) or potency.