A Combined Molecular Dynamics, Rigidity Analysis Approach for Studying Protein Complexes

Proteins form complexes when they bind to other molecules, which is often accompanied by a conformation change in one or both interacting partners. Details of how a compound associates with a target protein can be used to better design medicines that therapeutically regulate disease-causing proteins. Experimental and computational techniques for studying the binding process are available, however many of them are time and money intensive, or are computationally expensive, and hence cannot be done on a large data-set. In this work, we present a hybrid, computationally efficient approach for studying the stability of protein complex. We use short Molecular Dynamics (MD) simulations to generate a small ensemble of protein-complex conformations, whose flexibility we then analyze using an efficient graph-theoretic method implemented in the KINARI software. For our data-set of proteins, we show that our combined MD-rigidity analysis approach provides information about the stability of the protein-complex that would not be attained by either of the two methods alone

Allo-network drugs: Extension of the allosteric drug concept to protein-protein interaction and signaling networks

Allosteric drugs are usually more specific and have fewer side effects than orthosteric drugs targeting the same protein. Here, we overview the current knowledge on allosteric signal transmission from the network point of view, and show that most intra-protein conformational changes may be dynamically transmitted across protein-protein interaction and signaling networks of the cell. Allo-network drugs influence the pharmacological target protein indirectly using specific inter-protein network pathways. We show that allo-network drugs may have a higher efficiency to change the networks of human cells than those of other organisms, and can be designed to have specific effects on cells in a diseased state. Finally, we summarize possible methods to identify allo-network drug targets and sites, which may develop to a promising new area of systems-based drug design

Rigidity and flexibility of biological networks

The network approach became a widely used tool to understand the behaviour of complex systems in the last decade. We start from a short description of structural rigidity theory. A detailed account on the combinatorial rigidity analysis of protein structures, as well as local flexibility measures of proteins and their applications in explaining allostery and thermostability is given. We also briefly discuss the network aspects of cytoskeletal tensegrity. Finally, we show the importance of the balance between functional flexibility and rigidity in protein-protein interaction, metabolic, gene regulatory and neuronal networks. Our summary raises the possibility that the concepts of flexibility and rigidity can be generalized to all networks.Comment: 21 pages, 4 figures, 1 tabl

Protein flexibility is key to cisplatin crosslinking in calmodulin

Chemical crosslinking in combination with Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) has significant potential for studying protein structures and proteinprotein interactions. Previously, cisplatin has been shown to be a crosslinker and crosslinks multiple methionine (Met) residues in apo-calmodulin (apo-CaM). However, the inter-residue distances obtained from nuclear magnetic resonance structures are inconsistent with the measured distance constraints by crosslinking. Met residues lie too far apart to be crosslinked by cisplatin. Here, by combining FTICR MS with a novel computational flexibility analysis, the flexible nature of the CaM structure is found to be key to cisplatin crosslinking in CaM. It is found that the side chains of Met residues can be brought together by flexible motions in both apo-CaM and calcium-bound CaM (Ca4-CaM). The possibility of cisplatin crosslinking Ca4-CaM is then confirmed by MS data. Therefore, flexibility analysis as a fast and low-cost computational method can be a useful tool for predicting crosslinking pairs in protein crosslinking analysis and facilitating MS data analysis. Finally, flexibility analysis also indicates that the crosslinking of platinum to pairs of Met residues will effectively close the nonpolar groove and thus will likely interfere with the binding of CaM to its protein targets, as was proved by comparing assays for cisplatin-modified/unmodified CaM binding to melittin. Collectively, these results suggest that cisplatin crosslinking of apo-CaM or Ca4-CaM can inhibit the ability of CaM to recognize its target proteins, which may have important implications for understanding the mechanism of tumor resistance to platinum anticancer drugs

Structural characterization of intrinsically disordered proteins by NMR spectroscopy.

Recent advances in NMR methodology and techniques allow the structural investigation of biomolecules of increasing size with atomic resolution. NMR spectroscopy is especially well-suited for the study of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) which are in general highly flexible and do not have a well-defined secondary or tertiary structure under functional conditions. In the last decade, the important role of IDPs in many essential cellular processes has become more evident as the lack of a stable tertiary structure of many protagonists in signal transduction, transcription regulation and cell-cycle regulation has been discovered. The growing demand for structural data of IDPs required the development and adaption of methods such as 13C-direct detected experiments, paramagnetic relaxation enhancements (PREs) or residual dipolar couplings (RDCs) for the study of 'unstructured' molecules in vitro and in-cell. The information obtained by NMR can be processed with novel computational tools to generate conformational ensembles that visualize the conformations IDPs sample under functional conditions. Here, we address NMR experiments and strategies that enable the generation of detailed structural models of IDPs