Using Density Functional Theory (DFT) Calculations to Reinterpret the Biological Activity of Square Planar Pt (II), Au (III), and Cu (II) Complexes From Molecular Level

ABSTRACT The geometric structures and electronic properties of three experimentally reported anticancer Pt (II), Au (III), and Cu (II) complexes (named complexes 1–3 ) as well as the interactions of these complexes with biological target molecules have been explored in detail by density functional theory (DFT) calculations. Significant differences in the polarity of M‐Cl (M = Pt, Au, and Cu) bonds and the nucleophilic reactivity of metal centers were revealed for these complexes. Further research shows that the differences in the hydrolysis and the ligand exchange reactions with biological targets of these complexes are the main reasons for their different antitumor activities. Based on these findings, four novel complexes 4–7 have been rationally designed by replacing the Cu (II) center of 3 with Ni (II), Zn (II), Pd (II), and Fe (II) ions for the first time. Therein, the obtained Zn (II)–centered complex 5 is predicted to exhibit the highest similarity to complex 3 . This study not only provides a profound theoretical insight into the activity difference of the reported metal complexes from molecular level but also proposes an effective strategy to design new anticancer drugs.

Authors

Institutions

Publication Details

Journal
Applied Organometallic Chemistry
Published
2026-01-06
DOI
https://doi.org/10.1002/aoc.70505
Primary Topic
Metal complexes synthesis and properties
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using Density Functional Theory (DFT) Calculations to Reinterpret the Biological Activity of Square Planar Pt (II), Au (III), and Cu (II) Complexes From Molecular Level

Xin Cheng, Wei‐Ming Sun, Xiaolin Huang, Hai‐Yan Zhong et al.
Applied Organometallic Chemistry
Metal complexes synthesis and properties
article

Using Density Functional Theory (DFT) Calculations to Reinterpret the Biological Activity of Square Planar Pt (II), Au (III), and Cu (II) Complexes From Molecular Level

Xin Cheng, Wei‐Ming Sun, Xiaolin Huang, Hai‐Yan Zhong, Yan‐Yan Cai, Jia‐Di Chen, Yao‐Fei Cui, Xu‐Jie Gao
article en

Abstract

ABSTRACT The geometric structures and electronic properties of three experimentally reported anticancer Pt (II), Au (III), and Cu (II) complexes (named complexes 1–3 ) as well as the interactions of these complexes with biological target molecules have been explored in detail by density functional theory (DFT) calculations. Significant differences in the polarity of M‐Cl (M = Pt, Au, and Cu) bonds and the nucleophilic reactivity of metal centers were revealed for these complexes. Further research shows that the differences in the hydrolysis and the ligand exchange reactions with biological targets of these complexes are the main reasons for their different antitumor activities. Based on these findings, four novel complexes 4–7 have been rationally designed by replacing the Cu (II) center of 3 with Ni (II), Zn (II), Pd (II), and Fe (II) ions for the first time. Therein, the obtained Zn (II)–centered complex 5 is predicted to exhibit the highest similarity to complex 3 . This study not only provides a profound theoretical insight into the activity difference of the reported metal complexes from molecular level but also proposes an effective strategy to design new anticancer drugs.

Applied Organometallic ChemistryVol. 40(2)
Fujian Medical University (CN), Union Hospital (CN)
Openalex Percentile: Top 96%
Metal complexes synthesis and properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.