Further Exploration of the Quantitative Distance-Energy and Contact Number-Energy Relationships for Predicting the Binding Affinity of the Protein-Ligand Complexes1.

IF 3.2 3区 生物学 Q2 BIOPHYSICS Biophysical journal Pub Date : 2025-02-27 DOI:10.1016/j.bpj.2025.02.021
Yong Xiao Yan, Bao Ting Zhu
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Abstract

Accurate estimation of the strength of the protein-ligand interaction is important in the field of drug discovery. The binding strength can be determined by using experimental binding affinity assays which are both time and labor consuming and costly. Predicting the binding affinity/energy in silico is an alternative approach, particularly for virtual screening of large datasets. In general, the distance-based terms such as electrostatic and van der Waals interactions are among the key determinants of binding energy. In this work, the distance-binding energy relationships, i.e., E ∝ -d-k, are further explored, extended and developed for protein-ligand binding affinity prediction. The contributions of different atom-type pairs were considered synthetically and jointly. Additionally, the contact number-energy relationships (E ∝ -nk) were also explored for protein-ligand binding affinity prediction. Significantly, the power exponents of the distances or contact numbers in the energy functions are not restricted by the existing theories concerning van der Waals and electrostatic energies (expressed as a a/r6 - b/r12 and c/r). The performances of the new distance-based or contact number-based models are better than the performances of those sophisticated non-machine learning-based scoring functions developed before. The exploration and extension of the distance-energy and contact number-energy relationships may offer insights into the development of more effective methods for predicting the protein-ligand binding affinity accurately and for analyzing the protein-ligand interactions rationally.

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准确估计蛋白质与配体相互作用的强度在药物发现领域非常重要。结合强度可以通过实验性结合亲和力测定来确定,这种方法既费时又费力,而且成本高昂。在硅学中预测结合亲和力/能量是一种替代方法,尤其适用于大型数据集的虚拟筛选。一般来说,静电和范德华相互作用等基于距离的因素是决定结合能的关键因素之一。在这项工作中,进一步探索、扩展和发展了距离-结合能关系,即 E ∝ -d-k,用于蛋白质-配体结合亲和力预测。综合并共同考虑了不同原子类型对的贡献。此外,还探讨了用于蛋白质配体结合亲和力预测的接触数-能量关系(E ∝ -nk)。值得注意的是,能量函数中距离或接触数的幂指数不受现有范德华和静电能量理论的限制(以 a/r6 - b/r12 和 c/r 表示)。基于距离或接触数的新模型的性能优于之前开发的基于非机器学习的复杂评分函数。对距离-能量和接触数-能量关系的探索和扩展可能会为开发更有效的方法提供启示,从而准确预测蛋白质与配体的结合亲和力并合理分析蛋白质与配体的相互作用。
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来源期刊
Biophysical journal
Biophysical journal 生物-生物物理
CiteScore
6.10
自引率
5.90%
发文量
3090
审稿时长
2 months
期刊介绍: BJ publishes original articles, letters, and perspectives on important problems in modern biophysics. The papers should be written so as to be of interest to a broad community of biophysicists. BJ welcomes experimental studies that employ quantitative physical approaches for the study of biological systems, including or spanning scales from molecule to whole organism. Experimental studies of a purely descriptive or phenomenological nature, with no theoretical or mechanistic underpinning, are not appropriate for publication in BJ. Theoretical studies should offer new insights into the understanding ofexperimental results or suggest new experimentally testable hypotheses. Articles reporting significant methodological or technological advances, which have potential to open new areas of biophysical investigation, are also suitable for publication in BJ. Papers describing improvements in accuracy or speed of existing methods or extra detail within methods described previously are not suitable for BJ.
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