CorrEA:一个考虑多种结合位点构象的配体-受体系统中计算能量和活性之间关系优化的Web服务器。

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Sergio Alfaro, Fabián González-Norambuena, José Luis Velázquez-Libera, Francisco Adasme-Carreño* and Julio Caballero*, 
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引用次数: 0

摘要

利用分子对接方法建立的受体-配体复合物的硅分子模型很有价值,因为它们有可能揭示导致特定亲和力的化学相互作用。当应用于一系列同类化合物时,它们有助于形成关于不同取代基对亲和差异影响的理论。分子对接提供了(i)化学相互作用得到优化的姿势和(ii)表明相互作用有利程度的能量值。分子对接在第一个目的上的能力是公认的,但在第二个目的上却相当失败。众所周知,通过分子对接获得的能量值是不可靠的,这使得它们在同类序列中的应用无法将这些计算出的能量值与实验室衍生的生物活性联系起来。理论上,在对接计算中考虑蛋白质柔韧性可以得到更好的相关性;也就是说,结合位点上蛋白质残基的灵活性可以提供更有代表性的对接解决方案。考虑到这一点,在这项工作中,我们提出了一种简单而创新的方式来考虑配体-蛋白质系统的灵活性的新型web服务器CorrEA。要应用该方法,用户必须生成一组在结合位点内表现出显著可变性的受体构象。随后,他们应该交叉对接他们打算研究的配体系列,以获得每个配体在不同受体构象上的各种姿势。CorrEA采用遗传算法(GA)选择,为每个配体提取具有代表性的配合物,从而更好地调整计算的对接能量值与实验对数生物活性之间的全局相关性。最后,CorrEA提供了产生最高相关性的配体-蛋白质对。新方法在几个不同的案例中进行了测试,以证明它的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

CorrEA: A Web Server for Optimizing Correlations between Calculated Energies and Activities in Ligand–Receptor Systems Considering Multiple Binding Site Conformations

CorrEA: A Web Server for Optimizing Correlations between Calculated Energies and Activities in Ligand–Receptor Systems Considering Multiple Binding Site Conformations

In silico molecular models of receptor–ligand complexes, built using molecular docking methods, are valuable as they potentially reveal the chemical interactions responsible for specific affinities. When applied to series of congeneric compounds, they help formulate theories about the effects of different substituents on affinity differences. Molecular docking provides (i) a pose where chemical interactions are optimized and (ii) an energy value indicating how favorable the interaction is. The capability of molecular docking for the first purpose is recognized, but it fails considerably in the second. It is widely known that energy values obtained by molecular docking are unreliable, which makes their application to congeneric series unable to correlate these computationally calculated energy values with laboratory-derived biological activities. Theoretically, an improved correlation could be obtained when protein flexibility is considered in the docking calculation; i.e., flexibility in the protein residues at the binding site can give access to more representative docking solutions. With this in mind, in this work, we present the novel web server CorrEA with a simple and innovative way of considering the flexibility of ligand–protein systems. To apply the method, users must generate a set of receptor conformations exhibiting significant variability within the binding site. Subsequently, they should cross-dock the ligand series they intend to study, to obtain various poses for each ligand across the different receptor conformations. CorrEA performs a genetic algorithm (GA) selection to extract a representative complex for each ligand that better adjusts the global correlation between calculated docking energy values and experimental logarithmic biological activities. In the end, CorrEA provides the ligand–protein pairs that produce the highest correlations. The new method was tested in several different cases to demonstrate its usefulness.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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