Introducing mirror-image discrimination capability to the TSR-based method for capturing stereo geometry and understanding hierarchical structure relationships of protein receptor family. (April 2023)

• Record Type: Journal Article
• Authors: Sarkar, Titli; Chen, Yuwu; Wang, Yu; Chen, Yixin; Chen, Feng; Reaux, Camille R.; Moore, Laura E.; Raghavan, Vijay; Xu, Wu
• Is Part Of: Computational biology and chemistry. Volume 103(2023)
• Publication Date: 2023-04
• Subjects: Protein receptor -- Structure comparison -- Mirror image -- TSR -- Hierarchical -- Structure motif -- Stereospecific -- Chirality; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2023.107824
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: 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 Cα 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 Cα atom, in conjunction with the integration of Cα 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. Graphical Abstract: ga1 Highlights: Mirror-image discrimination capability is introduced into the Triangular Spatial Relationship (TSR)-based key generation formula to capture stereo geometry. Applying mirror images decreases structural similarity which can be partially explained by the observation of a decrease in common keys. For a hierarchically organized structure dataset, applying mirror images enhances the opportunity to discover specific keys that exclusively belong to certain types of proteins. Different types of receptors share little sequence similarity and are functionally diverse. However, similar substructures are identified within each protein of a receptor family. Unique substructures are identified for the majority of the receptor types, which build a foundation for designing new inhibitors specifically for certain types of receptors. The TSR-based method has its advantage in studying protein sequence, structure and function relationships.