Simultaneous modeling of multiple loops in proteins

Rosenbach, Dror; Rosenfeld, Rakefet

doi:10.1002/pro.5560040316

Cited by 23 publications

(10 citation statements)

References 30 publications

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“…The number of degrees of freedom sampled is much larger, which makes the problem challenging, but by doing so we predict near‐native loops within many of these antibody models. This approach complements other studies in which the backbone atoms surrounding loops have been optimized,52–54 and studies in which the effects of the environment on loop prediction have been investigated 20, 47. In addition, since H3 is often directly involved in antigen binding, we discuss the effects of antibody binding partners (i.e., induced fit) on H3 loop prediction accuracy.…”

Section: Introductionmentioning

confidence: 80%

A study of D‐lactate and extracellular methylglyoxal production in lactate Re‐Utilizing CHO cultures

Paoli

Faulkner

O’Kennedy

et al. 2010

Biotech & Bioengineering

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In large-scale mammalian cell culture, the key toxic by-products assessed and monitored are lactate and ammonia. Often no distinction between the two isoforms of lactate is made. Here, we present profiles of both D- and L-lactate. D-Lactate is the end molecule of the methylglyoxal pathway. D-Lactate unlike L-lactate is not re-utilized, and although during normal culture time frames it represents one-tenth of total lactate, during lactate re-use it represents nearly 35%. This indicates significant carbon flow through pathways not associated with primary metabolites. We have observed that the behavior of D-lactate is radically different from that of L-lactate with the level of one isoform changing, whilst the concentration of the other remains constant. This is an example of an alternate carbon flow pathway containing metabolic intermediates that may potentially have a detrimental effect on cells. The activity of the methylglyoxal pathway when measured as a proportion of glucose consumption in this study far exceeds any previously reported. This highlights the potential importance of "non-primary" metabolisms to long lifespan mammalian fermentation practices.

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Section: Introductionmentioning

confidence: 80%

A study of D‐lactate and extracellular methylglyoxal production in lactate Re‐Utilizing CHO cultures

Paoli

Faulkner

O’Kennedy

et al. 2010

Biotech & Bioengineering

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“…This is particularly true of the extracellular and intracellular loops of GPCRs [11]. Thus, over the last several years an intense effort has been mounted for predicting loop structures using approaches that do not depend on homology modeling [12][13][14][15][16][17][18]. Instead, ab initio approaches are used in the context of a classical or molecular mechanics (MM) approximation, requiring only the primary amino acid sequence of the segment for which the structure is to be determined.…”

Section: Introductionmentioning

confidence: 99%

Ab initio computational modeling of long loops in G-protein coupled receptors

Kortagere

Roy

Mehler

2006

J Comput Aided Mol Des

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A newly developed approach for predicting the structure of segments that connect known elements of secondary structure in proteins has been applied to some of the longer loops in the G-protein coupled receptors (GPCRs) rhodopsin and the dopamine receptor D2R. The algorithm uses Monte Carlo (MC) simulation in a temperature annealing protocol combined with a scaled collective variables (SCV) technique to search conformation space for loop structures that could belong to the native ensemble. Except for rhodopsin, structural information is only available for the transmembrane helices (TMHs), and therefore the usual approach of finding a single conformation of lowest energy has to be abandoned. Instead the MC search aims to find the ensemble located at the absolute minimum free energy, i.e., the native ensemble. It is assumed that structures in the native ensemble can be found by an MC search starting from any conformation in the native funnel. The hypothesis is that native structures are trapped in this part of conformational space because of the high-energy barriers that surround the native funnel. In this work it is shown that the crystal structure of the second extracellular loop (e2) of rhodopsin is a member of this loop's native ensemble. In contrast, the crystal structure of the third intracellular loop is quite different in the different crystal structures that have been reported. Our calculations indicate, that of three crystal structures examined, two show features characteristic of native ensembles while the other one does not. Finally the protocol is used to calculate the structure of the e2 loop in D2R. Here, the crystal structure is not known, but it is shown that several side chains that are involved in interaction with a class of substituted benzamides assume conformations that point into the active site. Thus, they are poised to interact with the incoming ligand.

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“…The conformational search is often guided by efficient scoring functions and biased by a discrete set of (Φ,Ψ)‐backbone torsional angles derived from a population analysis of existing PDB structures 27, 28. Optimization of the initial loop conformations involves methods such as molecular dynamics simulations,29 Monte Carlo simulations,30–32 bond scaling with relaxation,33–35 genetic algorithms,36, 37 random tweak,38 and direct tweak 39. Side chains are often added in a subsequent step, followed by structural refinement by energy minimization, and final scoring and ranking.…”

Section: Introductionmentioning

confidence: 99%

New computational method for prediction of interacting protein loop regions

Danielson¹,

Lill²

2010

Proteins

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Flexible loop regions of proteins play a crucial role in many biological functions such as protein-ligand recognition, enzymatic catalysis, and protein-protein association. To date, most computational methods that predict the conformational states of loops only focus on individual loop regions. However, loop regions are often spatially in close proximity to one another and their mutual interactions stabilize their conformations. We have developed a new method, titled CorLps, capable of simultaneously predicting such interacting loop regions. First, an ensemble of individual loop conformations is generated for each loop region. The members of the individual ensembles are combined and are accepted or rejected based on a steric clash filter. After a subsequent side-chain optimization step, the resulting conformations of the interacting loops are ranked by the statistical scoring function DFIRE that originated from protein structure prediction. Our results show that predicting interacting loops with CorLps is superior to sequential prediction of the two interacting loop regions, and our method is comparable in accuracy to single loop predictions. Furthermore, improved predictive accuracy of the top-ranked solution is achieved for 12-residue length loop regions by diversifying the initial pool of individual loop conformations using a quality threshold clustering algorithm.

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Simultaneous modeling of multiple loops in proteins

Cited by 23 publications

References 30 publications

A study of D‐lactate and extracellular methylglyoxal production in lactate Re‐Utilizing CHO cultures

A study of D‐lactate and extracellular methylglyoxal production in lactate Re‐Utilizing CHO cultures

Ab initio computational modeling of long loops in G-protein coupled receptors

New computational method for prediction of interacting protein loop regions

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