Kinetics of protein-DNA interaction: facilitated target location in sequence-dependent potential

Recognition and binding of specific sites on DNA by proteins is central for many cellular functions such as transcription, replication, and recombination. In the process of recognition, a protein rapidly searches for its specific site on a long DNA molecule and then strongly binds this site. Here we aim to find a mechanism that can provide both a fast search (1-10 sec) and high stability of the specific protein-DNA complex ($K_d=10^{-15}-10^{-8}$ M). Earlier studies have suggested that rapid search involves the sliding of a protein along the DNA. Here we consider sliding as a one-dimensional (1D) diffusion in a sequence-dependent rough energy landscape. We demonstrate that, in spite of the landscape's roughness, rapid search can be achieved if 1D sliding is accompanied by 3D diffusion. We estimate the range of the specific and non-specific DNA-binding energy required for rapid search and suggest experiments that can test our mechanism. We show that optimal search requires a protein to spend half of time sliding along the DNA and half diffusing in 3D. We also establish that, paradoxically, realistic energy functions cannot provide both rapid search and strong binding of a rigid protein. To reconcile these two fundamental requirements we propose a search-and-fold mechanism that involves the coupling of protein binding and partial protein folding. Proposed mechanism has several important biological implications for search in the presence of other proteins and nucleosomes, simultaneous search by several proteins etc. Proposed mechanism also provides a new framework for interpretation of experimental and structural data on protein-DNA interactions

Thermodynamic restrictions on evolutionary optimization of transcription factor proteins

Conformational fluctuations are believed to play an important role in the process by which transcription factor proteins locate and bind their target site on the genome of a bacterium. Using a simple model, we show that the binding time can be minimized, under selective pressure, by adjusting the spectrum of conformational states so that the fraction of time spent in more mobile conformations is matched with the target recognition rate. The associated optimal binding time is then within an order of magnitude of the limiting binding time imposed by thermodynamics, corresponding to an idealized protein with instant target recognition. Numerical estimates suggest that typical bacteria operate in this regime of optimized conformational fluctuations

Driftskontroll av kalkdoseringsanlegg i Mandalsvassdraget Avviksrapport 2011

Driftskontroll av kalkdoseringsanleggene i Mandalsvassdraget gjennomføres for å avdekke effektiviteten til de enkelte anleggene i vassdraget. Avviksrapporten er en sammenfatning av hendelser i rapporteringsperioden. Den foreslår også tiltak for optimalisering av rutiner, installasjoner og kalkingsstrategi. Den daglige driftskontrollen av Smeland doseringsanlegg måtte tidvis opphøre på grunn av mange svikt i telelinjen. Det var lav dosering fra anlegget. Håverstad doseringsanlegg hadde god driftssikkerhet gjennom hele året. Bjelland doseringsanlegg kalket tilfredsstillende, men det var en del mangler ved pH-målingene. Årsakene var ofte stopp i gjennomstrømmingen av pH-kyvetta, men også feil på måleutstyret. Logåna-anlegget hadde også for mange stopp i vanngjennom-strømmingen. Det foreslås tiltak for å bedre disse forholdene. Fisk kan ha tatt skade av for surt vann på grunn av manglende vannglass når behovet oppsto. pH-målet for lakseførende strekning av elva ble opprettholdt kontinuerlig i hele periodenSamarbeid om kalking av Mandalsvassdraget, MANKALK (Audnedal, Evje- og Hornnes, Mandal, Marnardal, Songdalen og Åseral kommune)

Predicting Transcription Factor Specificity with All-Atom Models

The binding of a transcription factor (TF) to a DNA operator site can initiate or repress the expression of a gene. Computational prediction of sites recognized by a TF has traditionally relied upon knowledge of several cognate sites, rather than an ab initio approach. Here, we examine the possibility of using structure-based energy calculations that require no knowledge of bound sites but rather start with the structure of a protein-DNA complex. We study the PurR E. coli TF, and explore to which extent atomistic models of protein-DNA complexes can be used to distinguish between cognate and non-cognate DNA sites. Particular emphasis is placed on systematic evaluation of this approach by comparing its performance with bioinformatic methods, by testing it against random decoys and sites of homologous TFs. We also examine a set of experimental mutations in both DNA and the protein. Using our explicit estimates of energy, we show that the specificity for PurR is dominated by direct protein-DNA interactions, and weakly influenced by bending of DNA.Comment: 26 pages, 3 figure

DISPLAR: an accurate method for predicting DNA-binding sites on protein surfaces

Structural and physical properties of DNA provide important constraints on the binding sites formed on surfaces of DNA-targeting proteins. Characteristics of such binding sites may form the basis for predicting DNA-binding sites from the structures of proteins alone. Such an approach has been successfully developed for predicting protein–protein interface. Here this approach is adapted for predicting DNA-binding sites. We used a representative set of 264 protein–DNA complexes from the Protein Data Bank to analyze characteristics and to train and test a neural network predictor of DNA-binding sites. The input to the predictor consisted of PSI-blast sequence profiles and solvent accessibilities of each surface residue and 14 of its closest neighboring residues. Predicted DNA-contacting residues cover 60% of actual DNA-contacting residues and have an accuracy of 76%. This method significantly outperforms previous attempts of DNA-binding site predictions. Its application to the prion protein yielded a DNA-binding site that is consistent with recent NMR chemical shift perturbation data, suggesting that it can complement experimental techniques in characterizing protein–DNA interfaces

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

Alumni Showcase

Below is a document containing the combined remarks delivered by six Illinois Wesleyan alumni about their experiences with collaborative engagement and the liberal arts. Martha Aguirre, Class of 2017, created this transcript, based on outlines provided by some of the speakers and the recording available at https://www.youtube.com/watch?v=FptKx2P9oVg The speakers\u27 photographs and this transcript are also available for download here.https://digitalcommons.iwu.edu/jensen_inauguration/1008/thumbnail.jp

Structural determinants of specific DNA-recognition by the THAP zinc finger

Human THAP1 is the prototype of a large family of cellular factors sharing an original THAP zinc-finger motif responsible for DNA binding. Human THAP1 regulates endothelial cell proliferation and G1/S cell-cycle progression, through modulation of pRb/E2F cell-cycle target genes including rrm1. Recently, mutations in THAP1 have been found to cause DYT6 primary torsion dystonia, a human neurological disease. We report here the first 3D structure of the complex formed by the DNA-binding domain of THAP1 and its specific DNA target (THABS) found within the rrm1 target gene. The THAP zinc finger uses its double-stranded β-sheet to fill the DNA major groove and provides a unique combination of contacts from the β-sheet, the N-terminal tail and surrounding loops toward the five invariant base pairs of the THABS sequence. Our studies reveal unprecedented insights into the specific DNA recognition mechanisms within this large family of proteins controlling cell proliferation, cell cycle and pluripotency

Structures of the Ets Protein DNA-binding Domains of Transcription Factors Etv1, Etv4, Etv5, and Fev: Determinants of DNA Binding and Redox Regulation by Disulfide Bond Formation.

Ets transcription factors, which share the conserved Ets DNA-binding domain, number nearly 30 members in humans and are particularly involved in developmental processes. Their deregulation following changes in expression, transcriptional activity, or by chromosomal translocation plays a critical role in carcinogenesis. Ets DNA binding, selectivity, and regulation have been extensively studied; however, questions still arise regarding binding specificity outside the core GGA recognition sequence and the mode of action of Ets post-translational modifications. Here, we report the crystal structures of Etv1, Etv4, Etv5, and Fev, alone and in complex with DNA. We identify previously unrecognized features of the protein-DNA interface. Interactions with the DNA backbone account for most of the binding affinity. We describe a highly coordinated network of water molecules acting in base selection upstream of the GGAA core and the structural features that may account for discrimination against methylated cytidine residues. Unexpectedly, all proteins crystallized as disulfide-linked dimers, exhibiting a novel interface (distant to the DNA recognition helix). Homodimers of Etv1, Etv4, and Etv5 could be reduced to monomers, leading to a 40-200-fold increase in DNA binding affinity. Hence, we present the first indication of a redox-dependent regulatory mechanism that may control the activity of this subset of oncogenic Ets transcription factors