The Relationship between the Flexibility of Proteins and their Conformational States on Forming Protein–Protein Complexes with an Application to Protein–Protein Docking

Smith, Graham R.; Sternberg, Michael J.E.; Bates, Paul A.

doi:10.1016/j.jmb.2005.01.058

Cited by 160 publications

(142 citation statements)

References 75 publications

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“…3 compares the observed motion over the binding with the motion predicted by NMA for three sample proteins. Splitting the binding site into core and periphery residues, we find that for five of the proteins, the observed motion of the peripheral residues is more than twice that of the core, in agreement with other studies (45,46). These results agree with another study (32) that observed a maximum O j of Ͼ0.6 in the lowest three modes in 7 of 20 proteins.…”

Section: Resultssupporting

confidence: 92%

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Dobbins

Lesk²,

Sternberg³

2008

Proc. Natl. Acad. Sci. U.S.A.

209

216

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Understanding protein interactions has broad implications for the mechanism of recognition, protein design, and assigning putative functions to uncharacterized proteins. Studying protein flexibility is a key component in the challenge of describing protein interactions. In this work, we characterize the observed conformational change for a set of 20 proteins that undergo large conformational change upon association (>2 Å C␣ RMSD) and ask what features of the motion are successfully reproduced by the normal modes of the system. We demonstrate that normal modes can be used to identify mobile regions and, in some proteins, to reproduce the direction of conformational change. In 35% of the proteins studied, a single low-frequency normal mode was found that describes well the direction of the observed conformational change. Finally, we find that for a set of 134 proteins from a docking benchmark that the characteristic frequencies of normal modes can be used to predict reliably the extent of observed conformational change. We discuss the implications of the results for the mechanics of protein recognition.conformational selection ͉ elastic network model ͉ induced fit ͉ protein interactions ͉ protein recognition P roteins are not static, and many undergo substantial rearrangements upon binding to other molecules (1). Such changes are central to protein function (2). The limitations of our understanding of conformational change impact markedly on our ability to model such changes. A successful approach to modeling protein flexibility, one of the key current challenges in developing protein-protein docking algorithms, would have far-reaching consequences for the fields of drug design and function prediction.The initial lock-and-key description of protein interaction, first introduced by Fischer in 1894 (3), did not account for conformational change and has since been modified, beginning with Koshland's induced fit hypothesis in 1958 (4). However, a range of studies including molecular dynamics (picosecondnanosecond time scales), NMR, and single-molecule FRET experiments (microsecond-millisecond time scales) (5-7), have questioned the extent to which conformational change can be considered induced by the binding partner.An alternative mechanism is conformational selection, where the native state of the protein exists in an ensemble of conformations, with the partner binding selectively to a specific conformation, thus shifting the equilibrium toward the binding conformation (8). An elaboration, proposed by Grunberg et al. (9), describes a three-stage process consisting of (i) independent diffusion of the receptor and ligand each subject to conformational fluctuations, (ii) an encounter between the receptor and ligand leading to a series of microcollisions that may result in the formation of a recognition complex, and (iii) either dissociation of the encounter complex or formation of the bound complex with possible further conformational changes resulting from induced fit. An important question to address is, therefore, ...

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Section: Resultssupporting

confidence: 92%

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Dobbins

Lesk²,

Sternberg³

2008

Proc. Natl. Acad. Sci. U.S.A.

209

216

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“…A large body of evidence links these movements to the structural changes that often accompany protein functions. For example, the displacements involved in allosteric changes in many proteins occur along the collective coordinates corresponding to the low-energy modes of the two stable structures (Delarue and Sanejouand 2002;Falke 2002;Rod et al 2003;Alexandrov et al 2005;Ming and Wall 2005;Smith et al 2005;Zheng et al 2007).The collective and large-scale character of these fluctuations has justified their characterization by simplified approaches, typically elastic network models (ENM) (Bahar et al 1997;Hinsen 1998;Atilgan et al 2001;Delarue and Sanejouand 2002;Micheletti et al 2004;Sulkowska et al 2007). These models rely on a simplified Reprint requests to: Cristian Micheletti, International School for Advanced Studies and CNR-INFM Democritos, Via Beirut 2-4, 34014 Trieste, Italy; e-mail: michelet@sissa.it; fax: 39-040-3787528.…”

mentioning

confidence: 99%

Correspondences between low‐energy modes in enzymes: Dynamics‐based alignment of enzymatic functional families

et al. 2008

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Proteins that show similarity in their equilibrium dynamics can be aligned by identifying regions that undergo similar concerted movements. These movements are computed from protein native structures using coarse-grained elastic network models. We show the existence of common large-scale movements in enzymes selected from the main functional and structural classes. Alignment via dynamics does not require prior detection of sequence or structural correspondence. Indeed, a third of the statistically significant dynamics-based alignments involve enzymes that lack substantial global or local structural similarities. The analysis of specific residue-residue correspondences of these structurally dissimilar enzymes in some cases suggests a functional relationship of the detected common dynamic features. Including dynamics-based criteria in protein alignment thus provides a promising avenue for relating and grouping enzymes in terms of dynamic aspects that often, though not always, assist or accompany biological function.Keywords: structure and function of enzymes; large-scale movements; protein alignment; dynamics-based alignment Supplemental material: see www.proteinscience.org Available alignment tools detect similarities among proteins in the first step of the logical cascade: sequence ! structure ! function. We introduce and apply a general and systematic algorithm to address functional relationships of enzymes by including dynamics in the alignment procedure. We focus on a common although not universal feature of enzymatic function, internal large-scale concerted movements. A large body of evidence links these movements to the structural changes that often accompany protein functions. For example, the displacements involved in allosteric changes in many proteins occur along the collective coordinates corresponding to the low-energy modes of the two stable structures (Delarue and Sanejouand 2002;Falke 2002;Rod et al. 2003;Alexandrov et al. 2005;Ming and Wall 2005;Smith et al. 2005;Zheng et al. 2007).The collective and large-scale character of these fluctuations has justified their characterization by simplified approaches, typically elastic network models (ENM) (Bahar et al. 1997;Hinsen 1998;Atilgan et al. 2001;Delarue and Sanejouand 2002;Micheletti et al. 2004;Sulkowska et al. 2007). These models rely on a simplified Reprint requests to: Cristian Micheletti, International School for Advanced Studies and CNR-INFM Democritos, Via Beirut 2-4, 34014 Trieste, Italy; e-mail: michelet@sissa.it; fax: 39-040-3787528.Abbreviations: ENM, elastic network model; MD, molecular dynamics; RMSD, root mean square distance; RMSIP, root mean square inner product.Article published online ahead of print. Article and publication date are at

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“…Studies of bound and unbound pairs of protein complexes for which three-dimensional structural information is available have suggested that in around half of the complexes, the unbound state at the interacting surface is perturbed to an observed bound state during MD simulation. 26 Whilst MD can be useful in exploring local conformational variation in proteins, normal-mode analysis (NMA) is a more appropriate approach for prediction of bulk protein movement. 27 NMA represents each amino acid as a bead, with proximal beads in the structure being computationally represented as springs.…”

Section: Site Identificationmentioning

confidence: 99%

Fragment-based drug discovery and protein–protein interactions

Turnbull¹,

Boyd²,

Walse³

2014

RRBC

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Protein-protein interactions (PPIs) are involved in many biological processes, with an estimated 400,000 PPIs within the human proteome. There is significant interest in exploiting the relatively unexplored potential of these interactions in drug discovery, driven by the need to find new therapeutic targets. Compared with classical drug discovery against targets with well-defined binding sites, developing small-molecule inhibitors against PPIs where the contact surfaces are frequently more extensive and comparatively flat, with most of the binding energy localized in "hot spots", has proven far more challenging. However, despite the difficulties associated with targeting PPIs, important progress has been made in recent years with fragmentbased drug discovery playing a pivotal role in improving their tractability. Computational and empirical approaches can be used to identify hot-spot regions and assess the druggability and ligandability of new targets, whilst fragment screening campaigns can detect low-affinity fragments that either directly or indirectly perturb the PPI. Once fragment hits have been identified and confirmed using biochemical and biophysical approaches, three-dimensional structural data derived from nuclear magnetic resonance or X-ray crystallography can be used to drive medicinal chemistry efforts towards the development of more potent inhibitors. A small-scale comparison presented in this review of "standard" fragments with those targeting PPIs has revealed that the latter tend to be larger, be more lipophilic, and contain more polar (acid/base) functionality, whereas three-dimensional descriptor data indicate that there is little difference in their three-dimensional character. These physiochemical properties can potentially be exploited in the rational design of PPI-specific fragment libraries and correlate well with optimized PPI inhibitors, which tend to have properties outside currently accepted guidelines for drug-likeness. Several examples of small-molecule PPI inhibitors derived from fragment-based drug discovery now exist and are described in this review, including navitoclax, a novel Bcl-2 family inhibitor which has entered Phase II clinical trials in patients with small-cell lung cancer and chronic lymphocytic leukemia.

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The Relationship between the Flexibility of Proteins and their Conformational States on Forming Protein–Protein Complexes with an Application to Protein–Protein Docking

Cited by 160 publications

References 75 publications

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Correspondences between low‐energy modes in enzymes: Dynamics‐based alignment of enzymatic functional families

Fragment-based drug discovery and protein–protein interactions

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The Relationship between the Flexibility of Proteins and their Conformational States on Forming Protein–Protein Complexes with an Application to Protein–Protein Docking

Cited by 160 publications

References 75 publications

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Insights into protein flexibility: The relationship between normal modes and conformational change upon protein–protein docking

Correspondences between low‐energy modes in enzymes: Dynamics‐based alignment of enzymatic functional families

Fragment-based drug discovery and protein&ndash;protein interactions

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Fragment-based drug discovery and protein–protein interactions