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Visualizing water molecules in transmembrane proteins using radiolytic labeling methods.

ABSTRACT: Essential to cells and their organelles, water is both shuttled to where it is needed and trapped within cellular compartments and structures. Moreover, ordered waters within protein structures often colocalize with strategically placed polar or charged groups critical for protein function, yet it is unclear if these ordered water molecules provide structural stabilization, mediate conformational changes in signaling, neutralize charged residues, or carry out a combination of all these functions. Structures of many integral membrane proteins, including G protein-coupled receptors (GPCRs), reveal the presence of ordered water molecules that may act like prosthetic groups in a manner quite unlike bulk water. Identification of "ordered" waters within a crystalline protein structure requires sufficient occupancy of water to enable its detection in the protein's X-ray diffraction pattern, and thus, the observed waters likely represent a subset of tightly bound functional waters. In this review, we highlight recent studies that suggest the structures of ordered waters within GPCRs are as conserved (and thus as important) as conserved side chains. In addition, methods of radiolysis, coupled to structural mass spectrometry (protein footprinting), reveal dynamic changes in water structure that mediate transmembrane signaling. The idea of water as a prosthetic group mediating chemical reaction dynamics is not new in fields such as catalysis. However, the concept of water as a mediator of conformational dynamics in signaling is just emerging, because of advances in both crystallographic structure determination and new methods of protein footprinting. Although oil and water do not mix, understanding the roles of water is essential to understanding the function of membrane proteins.

SUBMITTER: Orban T

PROVIDER: S-EPMC2819031 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Visualizing water molecules in transmembrane proteins using radiolytic labeling methods.

Orban Tivadar T Gupta Sayan S Palczewski Krzysztof K Chance Mark R MR

Biochemistry 20100201 5

Essential to cells and their organelles, water is both shuttled to where it is needed and trapped within cellular compartments and structures. Moreover, ordered waters within protein structures often colocalize with strategically placed polar or charged groups critical for protein function, yet it is unclear if these ordered water molecules provide structural stabilization, mediate conformational changes in signaling, neutralize charged residues, or carry out a combination of all these functions ...[more]

PMID: 20047303

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Project description:Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it is difficult to identify the conserved water molecules (CWMs) from free water molecules (FWMs) directly as CWMs are normally deeply embedded in proteins and form strong hydrogen bonds with surrounding polar groups. To circumvent this difficulty, in this work, the abundance of spatial structure information and physicochemical properties of water molecules in proteins inspires us to adopt machine learning methods for identifying the CWMs. Therefore, in this study, a machine learning framework to identify the CWMs in the binding sites of the proteins was presented. First, by analyzing water molecules' physicochemical properties and spatial structure information, six features (i.e., atom density, hydrophilicity, hydrophobicity, solvent-accessible surface area, temperature B-factors, and mobility) were extracted. Those features were further analyzed and combined to reach a higher CWM identification rate. As a result, an optimal feature combination was determined. Based on this optimal combination, seven different machine learning models (including support vector machine (SVM), K-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), discriminant analysis (DA), naïve Bayes (NB), and ensemble learning (EL)) were evaluated for their abilities in identifying two categories of water molecules, i.e., CWMs and FWMs. It showed that the EL model was the desired prediction model due to its comprehensive advantages. Furthermore, the presented methodology was validated through a case study of crystal 3skh and extensively compared with Dowser++. The prediction performance showed that the optimal feature combination and the desired EL model in our method could achieve satisfactory prediction accuracy in identifying CWMs from FWMs in the proteins' binding sites.

Project description:Membrane proteins, particularly those that are α-helical, such as transporters and G-protein-coupled receptors (GPCRs), have significant biological relevance. However, their expression and purification pose difficulties because of their poor water solubilities, which impedes progress in this field. The QTY method, a code-based protein-engineering approach, was recently developed to produce soluble transmembrane proteins. Here, we describe a comprehensive Web server built for QTY design and its relevance for in silico analyses. Typically, the simple design model is expected to require only 2 to 4 min of computer time, and the library design model requires 2 to 5 h, depending on the target protein size and the number of transmembrane helices. Detailed protocols for using the server with both the simple design and library design modules are provided. Methods for experiments following the QTY design are also included to facilitate the implementation of this approach. The design pipeline was further evaluated using microbial transmembrane proteins and structural alignment between the designed proteins and their origins by employing AlphaFold2. The results reveal that mutants generated by the developed pipeline were highly identical to their origins in terms of three-dimensional (3D) structures. In summary, the utilization of our Web server and associated protocols will enable QTY-based protein engineering to be implemented in a convenient, fast, accurate, and rational manner. The Protein Solubilizing Server (PSS) is publicly available at http://pss.sjtu.edu.cn. IMPORTANCE Water-soluble expression and purification are of considerable importance for protein identification and characterization. However, there has been a lack of an effective method for water-soluble expression of membrane proteins, which has severely hampered their studies. Here, an enabling comprehensive Web server, PSS, was developed for designing water-soluble mutants of α-helical membrane proteins, based on QTY design, a code-based protein-engineering approach. With microbial transmembrane proteins and GPCRs as examples, we systematically evaluated the server and demonstrated its successful performance. PSS is readily available for worldwide users as a Web-based tool, rendering QTY-based protein engineering convenient, efficient, accurate, and rational.

Dataset Information

Visualizing water molecules in transmembrane proteins using radiolytic labeling methods.

Publications

Visualizing water molecules in transmembrane proteins using radiolytic labeling methods.

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