Ab initio protein modelling for automated X-ray crystal structure solution

蛋白质构成了所有生物的功能机器。它们的特殊作用取决于它们的三维结构，这种结构允许特定的蛋白质与环境中的其他分子特异性地相互作用。一些蛋白质——酶——更进一步，可以将某些化合物转化为其他化合物。为了更好地理解蛋白质是如何工作的，并能够在工业和医学上使用它们，科学家们对弄清楚它们的三维结构非常感兴趣。有很多方法可以做到这一点，但主要的技术是x射线晶体学。在这种方法中，一束强烈的x射线射向蛋白质晶体。x射线在穿过晶体时被衍射，产生一种射线模式，这是所研究蛋白质的特征。为了阐明蛋白质的结构，必须将从同一蛋白质在不同条件下获得的多个衍射图中获得的信息汇总在一起。获得这种额外的衍射图案可能是耗时的，昂贵的，并且通常涉及危险的化学品。然而，有一种技术是存在的，在这种技术中，计算机通过从与所研究的蛋白质相似的可用结构中估计等效信息来代替额外的实验。用这种方法，蛋白质结构可以从一个单一的衍射图中求解。这种技术被称为分子替代（MR），它快速、经济、清洁而且通常不复杂。然而，由于MR依赖于预先存在的结构，因此它不适用于许多感兴趣的蛋白质，因为它们根本没有类似的结构。多年来，科学家们一直试图开发计算机方法来预测蛋白质的结构，完全基于它们的序列。这些方法通常被称为从头建模方法。在过去十年中，这些努力已开始取得成果。这些预测模型不太可能很快取代晶体结构，因为它们通常包含误差，但最近的工作表明，它们有时足够接近真实结构，可以用于MR过程。这是本建议背后的主要思想-使当前的从头算建模程序适应mr的具体需求。使用从头算建模，通常情况下，计算机计算越详细（即越长），您可以做出的模型就越好。不幸的是，实现最好的模型是如此的苛刻，它往往需要大量的计算时间或访问超级计算机或其他大量的计算机资源。很少有晶体学家能接触到这些设备，使得建模方法不切实际。因此，我们提出了一种不同的方法，有效地利用可以在典型计算机上轻松获得的更简单的模型。在我们的初步工作中，我们已经证明了这种方法可以成功地用于mr。我们现在要做的是找到生成最优模型的最佳方法，并自动完成。这实际上意味着调整方法以满足现代x射线晶体学的要求，使其快速，以便它可以作为常规方法使用，并且其他晶体学家无需从头开始建模的专业知识即可访问。然后，我们希望将该方法包含在MrBUMP程序中，该程序是一个完善的软件包，允许轻松，自动化MR. MrBUMP可以添加到一个名为CCP4i的软件包中，该软件包被晶体学家广泛使用。通过将我们的处理方法整合到一个熟悉的程序中，我们希望它能在世界范围内得到广泛应用。我们期望，通过扩展核磁共振计算方法，我们将使蛋白质结构的确定更快，更便宜。通过这种方式，依赖于蛋白质结构信息的各种领域的研究，比如药物设计，将会进行得更快。

Proteins make up the functional machinery of all living beings. Their particular roles depend on their 3-dimensional structures which allow given proteins to interact specifically with other molecules in their environment. Some proteins - enzymes - go further and can transform certain compounds into others. To understand better how proteins work and be able to use them in industry and medicine, scientists are greatly interested in figuring out their 3-dimensional structures. There are various ways to do this, but the dominant technique is X-ray crystallography. In this, an intense beam of X-rays is fired at a protein crystal. The X-rays are diffracted when passing through the crystal, producing a pattern of rays that is characteristic of the protein under study. In order to elucidate the structure of the protein, information derived from multiple diffraction patterns obtained from the same protein but under different conditions must be drawn together. The acquisition of such extra diffraction patterns can be time consuming, expensive, and commonly involves hazardous chemicals. A technique exists, however, where computers substitute the additional experiments by estimating equivalent information from available structures of proteins similar to that under study. In this way, protein structures can be solved from one single diffraction pattern. This technique - called Molecular Replacement (MR) - is fast, economical, clean and often uncomplicated. However, since MR relies on pre-existing structures, it is not applicable to many proteins of interest, for which similar structures are simply not available. For many years, scientists have tried to develop computer methods to predict the structure of proteins, purely based on their sequences. These methods are generally called ab initio modelling methods. Over the past decade, these efforts have started to bear fruit. These predicted models are unlikely to substitute for crystal structures any time soon since they typically contain errors, but recent work has shown that they are sometimes close enough to the real structure for them to be used in the MR process. This is the main idea behind this proposal - to adapt current ab initio modelling procedures to the specific needs of MR. With ab initio modelling, it is generally the case that the more detailed (i.e. the longer) the computer calculation, the better the model you can make. Unfortunately, achieving the best models is so demanding that it often requires extensive calculation times or access to supercomputers or other vast computer resources. Few crystallographers have access to these facilities, making the modelling method impractical. We therefore propose a different approach, making efficient use of simpler models that can be easily obtained on typical computers. In our preliminary work, we have already proven that this approach can work successfully for MR. What we want to do now is find the best way to produce optimal models and to do this automatically. This effectively means adapting the method to meet the demands of modern X-ray crystallography, making it fast so that it can be used as a routine approach and accessible to other crystallographers without specialist knowledge of ab initio modelling. We then want to include the method in the MrBUMP program, which is a well-established package allowing for easy, automated MR. MrBUMP can be added to a software package called CCP4i that is widely used by crystallographers. By incorporating our processing method in a familiar program, we expect it to become widely used across the world. We expect that by extending the MR computational approach we will enable protein structures to be determined more quickly and cheaply. In this way, research in all sorts of areas that depend on protein structure information, like drug design, will proceed faster.