Structural elucidation is an important step in chemical, pharmaceutical, biochemical, and natural product research because it helps researchers identify a compound and understand how its atoms are arranged. Traditional techniques such as nuclear magnetic resonance spectroscopy, mass spectrometry, infrared spectroscopy, ultraviolet spectroscopy, and X-ray crystallography remain the main methods used for structure determination. However, these methods may sometimes face difficulties, especially when compounds have closely related structures, are unstable, or are obtained in very small quantities. Molecular docking has become a useful computational tool that can support structural elucidation by providing information on how an identified or proposed compound may interact with a biological target. It does not replace experimental methods, but it can help explain the possible relationship between chemical structure and biological activity. In docking studies, a ligand is placed into the binding site of a protein to predict its binding pose, interaction pattern, and possible binding strength. This is useful in natural product research, drug discovery, and studies involving bioactive compounds, where researchers often need to understand how a compound may produce its observed activity. Molecular docking can also support the comparison of related compounds, interpretation of structure–activity relationships, and selection of promising molecules for further testing. Despite its usefulness, docking has limitations, including issues with protein flexibility, scoring accuracy, ligand preparation, and binding site selection. Therefore, docking results should be interpreted carefully and supported with experimental data, validation methods, molecular dynamics simulation, and biological assays where possible. This review discusses the principles, workflow, applications, limitations, and future relevance of molecular docking as a complementary tool in structural elucidation.
This work describes the growth of a proton-transfer single crystal, 2-aminopyridinium dihydrogen phosphate (2APDHP), using the slow solvent evaporation technique and confirmed that the crystal belongs to the monoclinic system.
G. Sivaraj, N. Jayamani, T. M. Viswanathan et al.· Asian Journal of Chemistry· 0 citations
In this study, a pyridinone-based compound was structurally characterized and computationally analyzed using integrated experimental and theoretical methods. The single-crystal X-ray diffraction (SC-XRD) results confirmed that the molecule adopts a non-planar conformation stabilized by strong N–H···O hydrogen bonds and weak π–π interactions. Density Functional Theory (DFT) calculations reveal a wide HOMO–LUMO energy gap (7.12 eV), indicative of high molecular stability and polar nature. Molecular docking simulations were carried out against Topoisomerase II (PDB ID: 3QX3) to investigate the binding affinity and interaction profile. The compound exhibited a moderate binding energy of –5.23 kcal/mol, dominated by van der Waals, hydrogen bonding, and π–π stacking interactions, suggesting a stable binding orientation within the enzyme’s active site. The combined results highlight the structural stability, electronic properties, and biointeraction potential of the synthesized ligand, supporting its relevance for future structure–activity relationship and anticancer studies.
G. Karakaya, Erdal Kurt, G. Yakalı et al.· Süleyman Demirel Üniversites...· 0 citations
FlexAutoDock is an automated cloud-based molecular docking platform that provides a unified environment for protein-ligand docking and large-scale virtual screening, providing researchers with an accessible computational resource for accelerating early-stage drug discovery.
Md. Feroj Ahmed, M. Faysal, Khalid Muntasir Sawad et al.· bioRxiv· 0 citations
Abstract One of the most frequently used methods in computational drug design is quantitative structure-activity relationship (QSAR). The main purpose of QSAR modeling is to estimate the relationship between chemical structures and biological activity in a group of molecules. In this method, molecules that have the greatest impact and the least side effects can be identified and extracted among huge numbers of molecular compounds. The molecular descriptors play a crucial role in QSAR design, and contain the physical, chemical, and geometric information. This information is called a feature that acts as an input to the QSAR model. Today, with the design of various applications to calculate molecular descriptors, the information obtained for each chemical structure is rising day by day which could lead to serious problems such as redundancy and over fitting. To solve this problem, researchers have used various techniques such as feature selection to improve the results of the model. The important point is that if the features are not properly selected, the QSAR model will fail. Up to now, different algorithms have been proposed to select the descriptors, which there are two main categories, supervised and unsupervised. The main purpose of this paper is to review feature selection methods in QSAR studies.
Fahimeh Motamedi, S. Zareian, S. Sardari et al.· Journal of Nonlinear, Comple...· 0 citations
The present work describes the synthesis, molecular docking, and preliminary anticancer evaluation of a hybrid compound, product-
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composed of a fluorinated sulfur heterocyclic core and an adamantane moiety. The synthesis method was designed to tune the electronic, lipophilic and structural properties of the compound through the introduction of CF₃, F and Cl functional groups, which are well known for the improving metabolic stability, physicochemical properties and drug-likeness. The structure of the synthesized compound was confirmed by
1
H and
13
C nuclear magnetic resonance (NMR) spectra. Molecular docking against phosphoinositide 3-kinase (PI3K), a protein target implicated in multiple cancers, showed that product-
C
exhibited a binding affinity of -10.6 kcal/mol, suggesting favorable interaction with the target. In parallel, the SRB (Sulforhodamine B) assay was used to evaluate the cytotoxicity of product-
C
toward PANC-1 cells. Preliminary results showed cell viabilities of 98.86% and 95.55% after exposure to 10 μM and 100 μM of product-
C
, respectively. These findings indicate that product-
C
displays low cytotoxicity toward PANC-1 cells under the tested conditions; however, they do not by themselves demonstrate marked antiproliferative activity.
M. Alamri, Yassine Riadi, A. Altharawi et al.· Arabian Journal of Chemistry· 0 citations
It was concluded that compound 9b is a promising antiproliferative agent, with an IC50 of 90 μM against all three cancer cell lines and little to no cytotoxicity towards the WS1 cell line, indicating an acceptable safety profile and selective cytotoxicity against cancer cells.
Aayushi Joshi, Abhishek Sharma, Giftson J. Senapathy et al.· Biochemical and Biophysical...· 0 citations
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