Department of Chemistry, University of Louisiana at Lafayette, P.O. Box 44370, Lafayette, LA 70504, USA; The Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA 70504, USA.
San Diego Supercomputer Center, University of California San Diego, Gilman Drive, La Jolla, CA 92093, USA.
Comput Biol Chem. 2023 Apr;103:107824. doi: 10.1016/j.compbiolchem.2023.107824. Epub 2023 Feb 3.
We have developed a Triangular Spatial Relationship (TSR)-based computational method for protein structure comparison and motif discovery that is both sequence and structure alignment-free. A protein 3D structure is modeled by all possible triangles that are constructed with every three C atoms of amino acids as vertices. Every triangle is represented using an integer (a key). The keys are calculated by a rule-based formula which is a function of a representative length, a representative angle, and the vertex labels associated with amino acids. A 3D structure is thereby represented by a vector of integers (TSR keys). Global or local structure comparisons are achieved by computing all keys or a set of keys, respectively. Many enzymatic reactions and notable marketed drugs are highly stereospecific. Thus, in this paper, we propose a modified key calculation formula by including a mechanism for discriminating mirror-image keys to capture stereo geometry. We assign a positive or a negative sign to the integers representing mirror-image keys. Applying the new key calculation function provides the ability to further discriminate mirror-image keys that were previously considered identical. As the result, applying the mirror-image discrimination capability (i) significantly increases the number of distinct keys; (ii) decreases the number of common keys; (iii) decreases structural similarity; (iv) increases the opportunity to identify specific keys for each type of the receptors. The specific keys identified in this study for the cases of without (not applying) and with (applying) mirror-image discrimination can be considered as the structure signatures that exclusively belong to a certain type of receptors. Applying mirror-image discrimination introduces stereospecificity to keys for allowing more precise modeling of ligand - target interactions. The development of mirror-image TSR keys of C atom, in conjunction with the integration of C TSR keys with all-atom TSR keys for amino acids and drugs, will lead to a new and promising computational method for aiding drug design and discovery.
我们开发了一种基于三角空间关系（TSR）的计算方法，用于蛋白质结构比较和基序发现，该方法既不进行序列比对，也不进行结构比对。蛋白质 3D 结构由所有可能的三角形建模而成，这些三角形由氨基酸的每三个 C 原子作为顶点构建。每个三角形都用一个整数（键）表示。键通过基于规则的公式计算得出，该公式是代表长度、代表角和与氨基酸相关联的顶点标签的函数。因此，3D 结构由整数向量（TSR 键）表示。全局或局部结构比较通过分别计算所有键或一组键来实现。许多酶促反应和著名的市售药物具有高度的立体特异性。因此，在本文中，我们提出了一种修改后的键计算公式，其中包括一种区分镜像键的机制，以捕获立体几何形状。我们为代表镜像键的整数分配正号或负号。应用新的键计算函数提供了进一步区分以前被认为相同的镜像键的能力。结果，应用镜像区分能力：（i）显著增加了不同键的数量；（ii）减少了公共键的数量；（iii）降低了结构相似度；（iv）增加了为每种类型的受体识别特定键的机会。在没有（不应用）和有（应用）镜像区分的情况下，本研究为案例识别的特定键可以被认为是仅属于特定类型受体的结构特征。应用镜像区分引入了键的立体特异性，以允许更精确地模拟配体 - 靶相互作用。C 原子镜像 TSR 键的开发，结合 C TSR 键与氨基酸和药物的全原子 TSR 键的整合，将为辅助药物设计和发现带来一种新的、有前途的计算方法。
