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DOI 10.3390/ijms26020587

Медицинская библиотека · International journal of molecular sciences · 2025

Dissecting the Binding Affinity of Anti-SARS-CoV-2 Compounds to Human Transmembrane Protease, Serine 2: A Computational Study.

Shi Yue-Hui, Shen Jian-Xin, Tao Yan, Xia Yuan-Ling, Zhang Zhi-Bi, Fu Yun-Xin, Zhang Ke-Qin, Liu Shu-Qun

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Аннотация

The human transmembrane protease, serine 2 (TMPRSS2), essential for SARS-CoV-2 entry, is a key antiviral target. Here, we computationally profiled the TMPRSS2-binding affinities of 15 antiviral compounds. Molecular dynamics (MD) simulations for the docked complexes revealed that three compounds exited the substrate-binding cavity (SBC), suggesting noncompetitive inhibition. Of the remaining compounds, five charged ones exhibited reduced binding stability due to competing electrostatic interactions and increased solvent exposure, while seven neutral compounds showed stronger binding affinity driven by van der Waals (vdW) interactions compensating for unfavorable electrostatic effects (including electrostatic interactions and desolvation penalties). Positive and negative hotspot residues were identified as uncharged and charged, respectively, both lining the SBC. Despite forming diverse interactions with compounds, the burial of positive hotspots led to strong vdW interactions that overcompensated for unfavorable electrostatic effects, whereas negative hotspots incurred high desolvation penalties, negating any favorable contributions. Charged residues at the SBC's outer rim can reduce binding affinity significantly when forming hydrogen bonds or salt bridges. These findings underscore the importance of enhancing vdW interactions with uncharged residues and minimizing the unfavorable electrostatic effects of charged residues, providing valuable insights for designing effective TMPRSS2 inhibitors.

Для цитирования: Shi Yue-Hui, Shen Jian-Xin, Tao Yan, Xia Yuan-Ling, Zhang Zhi-Bi, Fu Yun-Xin, Zhang Ke-Qin, Liu Shu-Qun. Dissecting the Binding Affinity of Anti-SARS-CoV-2 Compounds to Human Transmembrane Protease, Serine 2: A Computational Study.. International journal of molecular sciences. 2025. DOI: 10.3390/ijms26020587.

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