Tyrosine nitration of human ERK1 introduces an intra-hydrogen bond by molecular dynamics simulations

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

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.

Development of a TSR-Based Method for Protein 3-D Structural Comparison With Its Applications to Protein Classification and Motif Discovery

Development of protein 3-D structural comparison methods is important in understanding protein functions. At the same time, developing such a method is very challenging. In the last 40 years, ever since the development of the first automated structural method, ~200 papers were published using different representations of structures. The existing methods can be divided into five categories: sequence-, distance-, secondary structure-, geometry-based, and network-based structural comparisons. Each has its uniqueness, but also limitations. We have developed a novel method where the 3-D structure of a protein is modeled using the concept of Triangular Spatial Relationship (TSR), where triangles are constructed with the C_α atoms of a protein as vertices. Every triangle is represented using an integer, which we denote as “key,” A key is computed using the length, angle, and vertex labels based on a rule-based formula, which ensures assignment of the same key to identical TSRs across proteins. A structure is thereby represented by a vector of integers. Our method is able to accurately quantify similarity of structure or substructure by matching numbers of identical keys between two proteins. The uniqueness of our method includes: (i) a unique way to represent structures to avoid performing structural superimposition; (ii) use of triangles to represent substructures as it is the simplest primitive to capture shape; (iii) complex structure comparison is achieved by matching integers corresponding to multiple TSRs. Every substructure of one protein is compared to every other substructure in a different protein. The method is used in the studies of proteases and kinases because they play essential roles in cell signaling, and a majority of these constitute drug targets. The new motifs or substructures we identified specifically for proteases and kinases provide a deeper insight into their structural relations. Furthermore, the method provides a unique way to study protein conformational changes. In addition, the results from CATH and SCOP data sets clearly demonstrate that our method can distinguish alpha helices from beta pleated sheets and vice versa. Our method has the potential to be developed into a powerful tool for efficient structure-BLAST search and comparison, just as BLAST is for sequence search and alignment.

Nitration-induced ubiquitination and degradation control quality of ERK1

The mitogen-activated protein kinase ERK1/2 (ERKs, extracellular-regulated protein kinases) plays important roles in a wide spectrum of cellular processes and have been implicated in many disease states. The spatiotemporal regulation of ERK activity has been extensively studied. However, scarce information has been available regarding the quality control of the kinases to scavenge malfunctioning ERKs. Using site-specific mutagenesis and mass spectrometry, we found that the disruption of the conserved H-bond between Y210 and E237 of ERK1 through point mutation at or naturally occurring nitration on Y210 initiates a quality control program dependent on chaperon systems and CHIP (C-terminal of Hsp70-interacting protein)-mediated ubiquitination and degradation. The H-bond is also important for the quality control of ERK2, but through a distinct mechanism. These findings clearly demonstrate how malfunctioning ERKs are eliminated when cells are in certain stress conditions or unhealthy states, and could represent a general mechanism for scavenging malfunctioning kinases in stress conditions.