Manchester Institute of Biotechnology, School of Chemistry , The University of Manchester , 131 Princess Street , Manchester M1 7DN , U.K.
Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR) , Matrix 07-01, 30 Biopolis Street , Singapore 138671 , Singapore.
J Chem Inf Model. 2019 Jan 28;59(1):245-261. doi: 10.1021/acs.jcim.8b00765. Epub 2019 Jan 9.
Networks of biological molecules are key to cellular function, governing processes ranging from signal cascade propagation to metabolic pathway regulation. Genetic duplication processes give rise to sets of regulatory proteins that have evolved from a common ancestor, leading to interactomes whose dysregulation is often associated with disease. A better understanding of the determinants of specificity at interfaces shared by functionally related proteins is crucial to the rational design of novel pharmacotherapeutic agents. To this end, a comprehensive data set of drug and drug-like binders was assembled for the Bcl-xL and Bcl-2 antiapoptotic proteins-archetypal examples of regulatory systems governed by evolutionarily conserved protein-protein interactions. These were first used to derive a two-dimensional quantitative structure-activity relationship (2D QSAR) model, predicting ligand specificity for these homologous proteins. The strengths and weaknesses of high-throughput 2D QSAR were then compared and contrasted to those of theoretically rigorous thermodynamic integration calculations performed on 14 complexes of Bcl-xL-specific, Bcl-2-specific, and potent dual binders bound to the Bcl-xL and Bcl-2 proteins. We demonstrate that free energy calculations provide an added layer of essential information, which traditional QSAR cannot capture. Moreover, we show that protein energetic responses to different ligands, expressed as per-residue energy values, can be used to fingerprint the protein-ligand interaction, extending the framework of four-dimensional molecular dynamics/quantitative structure-activity relationships (4D-MD/QSAR) toward the facilitation of future drug design strategies.
生物分子网络是细胞功能的关键,控制着从信号级联传播到代谢途径调节等各种过程。遗传复制过程产生了一组从共同祖先进化而来的调节蛋白,导致相互作用组的失调,这通常与疾病有关。更好地理解功能相关蛋白界面的特异性决定因素,对于合理设计新型药物治疗剂至关重要。为此,我们为 Bcl-xL 和 Bcl-2 抗凋亡蛋白(受进化保守蛋白-蛋白相互作用调控的典型调控系统)组装了一个全面的药物和类药物结合物数据集。首先,我们利用这些数据集来推导二维定量构效关系(2D-QSAR)模型,预测这些同源蛋白的配体特异性。然后,我们比较和对比了高通量 2D-QSAR 的优缺点,并与对 Bcl-xL 特异性、Bcl-2 特异性和强效双结合物与 Bcl-xL 和 Bcl-2 蛋白结合的 14 个复合物进行的理论严格热力学积分计算的优缺点进行了比较。我们证明,自由能计算提供了一个额外的重要信息层,这是传统 QSAR 无法捕捉到的。此外,我们还表明,不同配体对蛋白质的能量响应,以每个残基的能量值表示,可以用于对蛋白质-配体相互作用进行指纹识别,从而将四维分子动力学/定量构效关系(4D-MD/QSAR)框架扩展到未来药物设计策略的促进中。