CG-COA: a coarse-grained cubic orientation approach for systematic protein-protein docking validation

IF 3.1 4区生物学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of molecular graphics & modelling Pub Date : 2026-03-01 Epub Date: 2025-11-29 DOI:10.1016/j.jmgm.2025.109245

Zekeriya Duzgun , Zuhal Eroglu

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引用次数: 0

Abstract

Traditional protein-protein docking algorithms face significant limitations when handling flexible protein systems, particularly where conformational flexibility plays crucial roles in binding specificity. This study developed and validated a Coarse-Grained Cubic Orientation Approach (CG-COA) that systematically samples six cubic orientations combined with coarse-grained molecular dynamics simulations and MM/PBSA free energy calculations. As a local docking approach, CG-COA requires prior knowledge of putative bioactive surfaces and focuses computational resources on biologically relevant binding orientations.

The methodology was validated using six protein complexes: four core systems (PDB codes: 2HD5, 1MIM, 3QML, 2MWS) representing diverse binding mechanisms, plus two extreme scenarios (2MZD: intrinsically disordered proteins; 2QCS-1RGS: large conformational changes). Benchmark comparisons against established docking methods (ZDOCK and ClusPro) evaluated relative performance across different system types.

Results demonstrated robust performance with overall AUROC of 0.94, achieving F-scores up to 1.00 for well-defined systems. Benchmark analysis revealed system-dependent performance: significant advantages for flexible systems (3QML: 3.7–5.1-fold improvement over rigid-body methods) but inferior performance for rigid interfaces (2HD5: outperformed by conventional approaches). Extreme docking scenarios revealed clear method limitations with poor structural accuracy (RMSDs >13 Å), defining important applicability boundaries. The approach correctly diagnosed inherently flexible systems (2MWS) by not converging to single conformations.

CG-COA addresses specific limitations of conventional protein-protein docking methods for systems with moderate conformational flexibility while clearly defining applicability boundaries. The methodology is unsuitable for extensive structural rearrangements or intrinsically disordered regions. The dual capability to identify native binding modes and diagnose flexibility provides valuable guidance for protein interaction studies.

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CG-COA：用于系统蛋白质对接验证的粗粒度立方取向方法。

传统的蛋白质-蛋白质对接算法在处理柔性蛋白质系统时面临显著的局限性，特别是当构象灵活性在结合特异性中起着至关重要的作用时。本研究开发并验证了粗粒度立方取向方法（CG-COA），该方法结合粗粒度分子动力学模拟和MM/PBSA自由能计算，系统地采样了6个立方取向。作为局部对接方法，CG-COA需要预先了解假定的生物活性表面，并将计算资源集中在生物学相关的结合方向上。该方法使用6种蛋白质复合物进行验证：代表不同结合机制的4个核心系统（PDB代码：2HD5、1MIM、3QML、2MWS），以及2个极端场景（2MZD：内在无序蛋白质；2QCS-1RGS：大构象变化）。针对已建立的对接方法（ZDOCK和ClusPro）的基准比较评估了不同系统类型的相对性能。结果显示了稳健的性能，总体AUROC为0.94，在定义良好的系统中达到高达1.00的f分。基准分析揭示了系统相关性能：柔性系统的显著优势（3QML：比刚体方法提高3.7-5.1倍），但刚性界面的性能较差（2HD5：优于传统方法）。极端对接场景显示出明显的方法局限性和较差的结构精度（RMSDs >13 Å），定义了重要的适用性边界。该方法通过不收敛于单一构象来正确诊断固有柔性系统（2MWS）。CG-COA解决了传统蛋白质对接方法对具有中等构象灵活性的系统的特定限制，同时明确定义了适用性边界。该方法不适用于广泛的结构重排或内在无序的区域。鉴定天然结合模式和诊断灵活性的双重能力为蛋白质相互作用的研究提供了有价值的指导。

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来源期刊

Journal of molecular graphics & modelling 生物-计算机：跨学科应用

CiteScore

5.50

自引率

6.90%

发文量

216

审稿时长

35 days

期刊介绍： The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design. As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.