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Updated: Jul 14, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Spectroscopic characterization, molecular docking and machine learning studies of sulphur containing hydrazide
Soni Shukla1, Poonam Rawat1, Pulkit Sharma1
1Department of Chemistry, University of Lucknow, Lucknow-226007, Uttar Pradesh, India. abhabishnoi5@gmail.com.
Abstract:
Machine learning applied in chemistry is a growing field of research. For assessing structure-property variations, this paper describes in silico studies of the hydrazide derivatives of thiosemicarbazide (TSCZ) and thiocarbohydrazide (TCHZ). The structures of TSCZ and TCHZ have been elucidated using modern spectroscopic techniques. The UV-vis spectra showed strong charge transfer transitions (π-π*) for TSCZ and TCHZ with high extinction coefficients. The NBO analysis showed orbital overlap between lp1 (N2) and σ* (C3-S4) in TSCZ and TCHZ due to intramolecular charge transfer. The first hyperpolarizabilities (β0) for TSCZ and TCHZ were found to be 0.7155 and 2.1615 × 10-30 esu, respectively, indicating their greater suitability for NLO applications as compared to standard reference urea. The strong electrophilic behaviour of TSCZ and TCHZ has been indicated by their global elecrophilicity index. The electrophilic reactivity descriptor analysis indicated that the investigated molecules could serve as precursors for the targeted synthesis of new heterocyclic derivatives. The docking studies showed appreciable binding energies with target proteins having PDB IDs 2WJE and 6CLU of Gram-positive bacteria, namely, Streptococcus pneumoniae phosphatase (PTP-CPS4B) and Staphylococcus aureus dihydropteroate synthase (saDHPS), respectively, for TSCZ and TCHZ, predicting good antimicrobial activity.
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