This paper reports the hydrothermal synthesis, experimental and theoretical studies of a novel cocrystal compound in the 2:1 stoichiometric ratio of 6-methyluracil (6mu) and dipicolinic acid (pydcH(2)) formulated as [6mu](2)[pydcH(2)] (1), for the first time. DFT calculations were performed to access the most possible geometry of the title cocrystal compound. All calculations were carried out with the B3LYP hybrid density functional level and 6-311+G(d,p) basis sets. The vibrational frequencies together with the (1)H and (13)C NMR chemical shifts have been calculated on the fully optimized geometry of 1. The theoretical results are in good agreement with the experimental and solution data. The theoretical, solution, and experimental (elemental analysis, mass spectrometry, FTIR, (1)H and (13)C NMR spectroscopies) results confirmed our proposed structure for 1 in the 2:1 stoichiometric ratio of 6mu and pydcH(2), respectively. The protonation and equilibrium constants of 6mu and pydcH(2) and constituent systems were determined by potentiometric studies and the corresponding distribution diagrams depicted.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.saa.2011.01.016DOI Listing

Publication Analysis

Top Keywords

cocrystal compound
12
stoichiometric ratio
12
hydrothermal synthesis
8
synthesis experimental
8
experimental theoretical
8
novel cocrystal
8
compound stoichiometric
8
ratio 6-methyluracil
8
dipicolinic acid
8
13c nmr
8

Similar Publications

Design, Structure Optimization, and Preclinical Characterization of JAB-21822, a Covalent Inhibitor of KRAS.

J Med Chem

January 2025

Chief executive officer, Jacobio Pharmaceuticals Group Co., Ltd., Beijing100176, P. R. China.

KRAS is the most frequently mutated driver oncogene in human cancer, and KRAS mutation is commonly found in non-small-cell lung cancer (NSCLC), colorectal cancer (CRC), and pancreatic ductal adenocarcinoma (PDAC). Inhibitors that covalently modify the mutated codon 12 cysteine have completed proof-of-concept studies in the clinic. Here, we describe structure-based design and cocrystal-aided drug optimization of a series of compounds with the 1,8-naphthyridine-3-carbonitrile scaffold.

View Article and Find Full Text PDF

Objective: A new library of Thiazolidine-2,4-dione-biphenyl Derivatives derivatives (10a-j) was designed and synthesized. All compounds were characterized by spectral data. Further, these were evaluated for their in vitro anticancer activity.

View Article and Find Full Text PDF

A new Donor-Acceptor type pyrazinacene derivative (1) featuring strong ICT was synthesized by linking electron-donating triphenylamine (TPA) and electron-accepting CN groups via a pyrazinacene core. The compound exhibits a dramatic color change from greenish blue to red-violet upon selective recognition of naphthalene (3) to form a 1:1 co-crystal (1•3). This color change is induced by intermolecular CT between pyrazinacene and naphthalene's aromatic moieties, driven by π-hole···π interactions.

View Article and Find Full Text PDF

Structure-Based Rational Design and Evaluation of BET-Aurora Kinase Dual-Inhibitors for Treatment of Cancers.

J Med Chem

January 2025

Department of Medicinal Chemistry, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China.

Simultaneous inhibition of the bromodomain and extra-terminal domain and Aurora kinases is a promising anticancer therapeutic strategy. Based on our previous study on BET-kinase dual inhibitors, we employed the molecular docking approach to design novel dual BET-Aurora kinase A inhibitors. Through several rounds of optimization and with the guidance of the solved cocrystal structure of BRD4 bound to inhibitor , we finally obtained a series of highly potent dual BET-Aurora kinase A inhibitors.

View Article and Find Full Text PDF

Protein-ligand binding affinity prediction using multi-instance learning with docking structures.

Front Pharmacol

January 2025

Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA, United States.

Introduction: Recent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!