Rotamer Library Research Articles

Protein-Peptide Complex Prediction through Fragment Interaction Patterns

The number of protein-peptide interactions in a cell isso large that experimental determination of all these complex structures would be a daunting task. Although homology modeling and refinement protocols have vastly improved the number and quality of predicted structural models, ab initio methods are still challenged by both the large number of possible docking sites and the conformational space accessible to flexible peptides. We present a method that addresses these challenges by sampling the entire accessible surface of a protein with a reduced conformational space of interacting backbone fragment pairs from unrelated structures. We demonstrate its potential by predicting ab initio the bound structure for a variety of protein-peptide complexes. In addition, we show the potential of our method forthe discovery of domain interaction sites and domain-domain docking.

FTFlex: accounting for binding site flexibility to improve fragment-based identification of druggable hot spots

Computational solvent mapping finds binding hot spots, determines their druggability and provides information for drug design. While mapping of a ligand-bound structure yields more accurate results, usually the apo structure serves as the starting point in design. The FTFlex algorithm, implemented as a server, can modify an apo structure to yield mapping results that are similar to those of the respective bound structure. Thus, FTFlex is an extension of our FTMap server, which only considers rigid structures. FTFlex identifies flexible residues within the binding site and determines alternative conformations using a rotamer library. In cases where the mapping results of the apo structure were in poor agreement with those of the bound structure, FTFlex was able to yield a modified apo structure, which lead to improved FTMap results. In cases where the mapping results of the apo and bound structures were in good agreement, no new structure was predicted. FTFlex is freely available as a web-based server at http://ftflex.bu.edu/.

Rotamer Library of Spin Labeled Cysteines Attached to T4 Lysozyme Deduced from Molecular Dynamics Simulations Constrained by Double Electron-Electron Resonance (Deer) Experiments

DEER (Double Electron Electron Resonance) is a powerful pulsed EPR technique allowing the determination of spin-spin distance histograms between side-directed nitroxide label sites on a protein in their native environment. In this study, a novel molecular dynamics simulation method, the restrained ensemble (RE) method, has been used for the refinement of spin labels inserted in T4 Lysozyme (T4L) structures. In the RE method, the spin-spin distance distribution histograms calculated from a multiple-copy molecular dynamics simulations are forced, via a special ensemble-based energy restraint, to match those extracted from 51 EPR/DEER experimental spin-spin pairs. To examine the effect of the restraint on the rotameric state of the spin label at the 37 different sites in T4L, conventional long molecular dynamics (MD) and locally enhanced sampling (LES) simulations were also performed. As expected, the distance histograms obtained from the RE simulations are very similar to those obtained from experiment; however, the distance histograms from conventional long MD and LES simulations deviate from experiment. From the analysis of these simulations, a general trend is found in rotamer population distribution along five dihedral angles connecting the nitroxide ring to the protein backbone. Overall, the rotamer population obtained from the RE simulation agrees with those obtained from x-ray structure. From the analysis of the dynamics of nitroxide atoms in spin label side chains, a force field for a pseudo nitroxide dummy atom has been parameterized. This pseudo nitroxide was used in an RE simulation coupled with the EPR/DEER experimental distance distribution data to refine distorted structures of T4L. Thus, experimental restraints from DEER experiments in conjunction with RE simulations can be used to refine structural propertied of biological systems.

Incorporating Backbone Flexibility in MedusaDock Improves Ligand-Binding Pose Prediction in the CSAR2011 Docking Benchmark

Solution of the structures of ligand-receptor complexes via computational docking is an integral step in many structural modeling efforts as well as in rational drug discovery. A major challenge in ligand-receptor docking is the modeling of both receptor and ligand flexibilities in order to capture receptor conformational changes induced by ligand binding. In the molecular docking suite MedusaDock, both ligand and receptor side chain flexibilities are modeled simultaneously with sets of discrete rotamers, where the ligand rotamer library is generated "on the fly" in a stochastic manner. Here, we introduce backbone flexibility into MedusaDock by implementing ensemble docking in a sequential manner for a set of distinct receptor backbone conformations. We generate corresponding backbone ensembles to capture backbone changes upon binding to different ligands, as observed experimentally. We develop a simple clustering and ranking approach to select the top poses as blind predictions. We applied our method in the CSAR2011 benchmark exercise. In 28 out of 35 cases (80%) where the ligand-receptor complex structures were released, we were able to predict near-native poses (<2.5 Å RMSD), the highest success rate reported for CSAR2011. This result highlights the importance of modeling receptor backbone flexibility to the accurate docking of ligands to flexible targets. We expect a broad application of our fully flexible docking approach in biological studies as well as in rational drug design.

A solvated ligand rotamer approach and its application in computational protein design

The structure-based design of protein-ligand interfaces with respect to different small molecules is of great significance in the discovery of functional proteins. By statistical analysis of a set of protein-ligand complex structures, it was determined that water-mediated hydrogen bonding at the protein-ligand interface plays a crucial role in governing the binding between the protein and the ligand. Based on the novel statistic results, a solvated ligand rotamer approach was developed to explicitly describe the key water molecules at the protein-ligand interface and a water-mediated hydrogen bonding model was applied in the computational protein design context to complement the continuum solvent model. The solvated ligand rotamer approach produces only one additional solvated rotamer for each rotamer in the ligand rotamer library and does not change the number of side-chain rotamers at each protein design site. This has greatly reduced the total combinatorial number in sequence selection for protein design, and the accuracy of the model was confirmed by two tests. For the water placement test, 61% of the crystal water molecules were predicted correctly in five protein-ligand complex structures. For the sequence recapitulation test, 44.7% of the amino acid identities were recovered using the solvated ligand rotamer approach and the water-mediated hydrogen bonding model, while only 30.4% were recovered when the explicitly bound waters were removed. These results indicated that the developed solvated ligand rotamer approach is promising for functional protein design targeting novel protein-ligand interactions.

Tryptophan Rotamer Distribution Revealed for the α-Helix in Tear Lipocalin by Site-Directed Tryptophan Fluorescence

Rotamer libraries are a valuable tool for protein structure determination, modeling, and design. Site-directed tryptophan fluorescence (SDTF) was used in combination with the rotamer model for the fluorescence intensity decays to solve α-helical conformations of proteins in solution. Single Trp mutations located in an α-helical segment of human tear lipocalin were explored for structure assignment. Along with fluorescence λ(max) values, the rotamer model assignment of fluorescence lifetimes fits the backbone conformation. Typically, Trp fluorescence in proteins shows three lifetimes. However, for the α-helix, two lifetimes assigned to t and g(-) rotamers were satisfactory to describe Trp fluorescence intensity decays. The g(+) rotamer is not feasible in the α-helix due to steric restriction. Trp rotamer distributions obtained by fluorescence were compared with the rotamer library derived from X-ray crystallography data of proteins. The Trp rotamer distributions vary for solvent exposed and buried (tertiary interaction) sites. A new strategy using the rotamer distribution with SDTF (RD-SDTF) removes the limitation of regular SDTF and other labeling techniques, in which site-specific differences, e.g., accessibility, are presumed. The RD-SDTF technique does not rely on environmental differences of side chains and is able to detect α-helical structure where all side chains are exposed to solvent. Potentially, this technique is applicable to various proteins including membrane proteins, which are rich in α-helix motif.

GANM: A protein–ligand docking approach based on genetic algorithm and normal modes

We describe a new method and a software, called GANM (Genetic Algorithm with Normal Modes), that combines genetic algorithm and normal mode analysis in order to achieve protein–ligand docking simulations that take into account global and local conformational adjustments. The energetical and structural optimization during the ligand binding process is achieved with GA that uses a rotamer library for changing the side chain conformations within and around the binding site. The methodology uses normal modes to account for the global conformational changes of the protein. This software is implemented in distinct versions using different levels of approximations. In this article, we describe the methodology and discuss the results and the performance obtained with the first two versions of GANM. The protein–ligand complexes considered for the test calculations are: (1) Dihydrofolate Reductase (DHFR) and MTX as ligands, (2) HIV-1 Aspartyl Protease with ritonavir, nelfinavir and DMP323 as ligands, and (3) CDK-2 and DT-5 as ligands.

Simulation vs. Reality: A Comparison of In Silico Distance Predictions with DEER and FRET Measurements

Site specific incorporation of molecular probes such as fluorescent- and nitroxide spin-labels into biomolecules, and subsequent analysis by Förster resonance energy transfer (FRET) and double electron-electron resonance (DEER) can elucidate the distance and distance-changes between the probes. However, the probes have an intrinsic conformational flexibility due to the linker by which they are conjugated to the biomolecule. This property minimizes the influence of the label side chain on the structure of the target molecule, but complicates the direct correlation of the experimental inter-label distances with the macromolecular structure or changes thereof. Simulation methods that account for the conformational flexibility and orientation of the probe(s) can be helpful in overcoming this problem. We performed distance measurements using FRET and DEER and explored different simulation techniques to predict inter-label distances using the Rpo4/7 stalk module of the M. jannaschii RNA polymerase. This is a suitable model system because it is rigid and a high-resolution X-ray structure is available. The conformations of the fluorescent labels and nitroxide spin labels on Rpo4/7 were modeled using in vacuo molecular dynamics simulations (MD) and a stochastic Monte Carlo sampling approach. For the nitroxide probes we also performed MD simulations with explicit water and carried out a rotamer library analysis. Our results show that the Monte Carlo simulations are in better agreement with experiments than the MD simulations and the rotamer library approach results in plausible distance predictions. Because the latter is the least computationally demanding of the methods we have explored, and is readily available to many researchers, it prevails as the method of choice for the interpretation of DEER distance distributions.

An energy‐based conformer library for side chain optimization: Improved prediction and adjustable sampling

Side chain optimization is a fundamental component of protein modeling applications such as docking, structural prediction, and design. In these applications side chain flexibility is often provided by rotamer or conformer libraries, which are collections of representative side chain conformations. Here we demonstrate that the sampling provided by the library can be substantially improved by adding an energetic criterion to its creation. The result of the new procedure is the Energy-Based library, a conformer library selected according to the propensity of its elements to fit energetically into natural protein environments. The new library performs outstandingly well in side chain optimization, producing structures with significantly lower energies and resulting in improved side chain conformation prediction. In addition, because the library was created as an ordered list, its size can be adjusted to any desired level. This feature provides unprecedented versatility in tuning sampling. It allows to precisely balance the number of conformers required by each amino acid type, equalizing their chances to fit into structural environments. It also allows to scale the amount of sampling to the specific requirement of any given side optimization problem. A rotameric version of the library was also produced with the same method to support applications that require a dihedral-only description of side chain conformation. The libraries are available at http://seneslab.org/EBL.

Rotamer libraries and probabilities of transition between rotamers for the side chains in protein–protein binding

Conformational changes in the side chains are essential for protein-protein binding. Rotameric states and unbound- to-bound conformational changes in the surface residues were systematically studied on a representative set of protein complexes. The side-chain conformations were mapped onto dihedral angles space. The variable threshold algorithm was developed to cluster the dihedral angle distributions and to derive rotamers, defined as the most probable conformation in a cluster. Six rotamer libraries were generated: full surface, surface noninterface, and surface interface-each for bound and unbound states. The libraries were used to calculate the probabilities of the rotamer transitions upon binding. The stability of amino acids was quantified based on the transition maps. The noninterface residues' stability was higher than that of the interface. Long side chains with three or four dihedral angles were less stable than the shorter ones. The transitions between the rotamers at the interface occurred more frequently than on the noninterface surface. Most side chains changed conformation within the same rotamer or moved to an adjacent rotamer. The highest percentage of the transitions was observed primarily between the two most occupied rotamers. The probability of the transition between rotamers increased with the decrease of the rotamer stability. The analysis revealed characteristics of the surface side-chain conformational transitions that can be utilized in flexible docking protocols.

Protein structure optimization by side-chain positioning via beta-complex

A molecular structure determines a molecular function(s) and a correct understanding of molecular structure is important for biotechnology. The computational prediction of molecular structure is a frequent requirement for important biomolecular applications such as a homology modeling, a docking simulation, a protein design, etc. where the optimization of molecular structure is fundamental. One of the core problems in the optimization of protein structure is the optimization of side-chains called the side-chain positioning problem. The side-chain positioning problem, assuming the rigidity of backbone and a rotamer library, attempts to optimally assign a rotamer to each residue so that the potential energy of protein is minimized in its entirety. The optimal solution approach using (mixed) integer linear programming, with the dead-end elimination technique, suffers even for moderate-sized proteins because the side-chain positioning problem is NP-hard. On the other hand, popular heuristic approaches focusing on speed produce solutions of low quality. This paper presents an efficient algorithm, called the BetaSCP, for the side-chain positioning problem based on the beta-complex which is a derivative geometric construct of the Voronoi diagram. Placing a higher priority on solution quality, the BetaSCP algorithm produces a solution very close to the optima within a reasonable computation time. The effectiveness and efficiency of the BetaSCP are experimentally shown via a benchmark test against well-known algorithms using twenty test models selected from Protein Data Bank.

Incorporation of Noncanonical Amino Acids into Rosetta and Use in Computational Protein-Peptide Interface Design

Noncanonical amino acids (NCAAs) can be used in a variety of protein design contexts. For example, they can be used in place of the canonical amino acids (CAAs) to improve the biophysical properties of peptides that target protein interfaces. We describe the incorporation of 114 NCAAs into the protein-modeling suite Rosetta. We describe our methods for building backbone dependent rotamer libraries and the parameterization and construction of a scoring function that can be used to score NCAA containing peptides and proteins. We validate these additions to Rosetta and our NCAA-rotamer libraries by showing that we can improve the binding of a calpastatin derived peptides to calpain-1 by substituting NCAAs for native amino acids using Rosetta. Rosetta (executables and source), auxiliary scripts and code, and documentation can be found at (http://www.rosettacommons.org/).

Examination of Mechanism of N-Acetyl-1-d-myo-inosityl-2-amino-2-deoxy-α-d-glucopyranoside Deacetylase (MshB) Reveals Unexpected Role for Dynamic Tyrosine

Actinomycetes are a group of gram-positive bacteria that includes pathogenic mycobacterial species, such as Mycobacterium tuberculosis. These organisms do not have glutathione and instead utilize the small molecule mycothiol (MSH) as their primary reducing agent and for the detoxification of xenobiotics. Due to these important functions, enzymes involved in MSH biosynthesis and MSH-dependent detoxification are targets for drug development. The metal-dependent deacetylase N-acetyl-1-D-myo-inosityl-2-amino-2-deoxy-α-D-glucopyranoside deacetylase (MshB) catalyzes the hydrolysis of N-acetyl-1-D-myo-inosityl-2-amino-2-deoxy-α-D-glucopyranoside to form 1-D-myo-inosityl-2-amino-2-deoxy-α-D-glucopyranoside and acetate in MSH biosynthesis. Herein we examine the chemical mechanism of MshB. We demonstrate that the side chains of Asp-15, Tyr-142, His-144, and Asp-146 are important for catalytic activity. We show that NaF is an uncompetitive inhibitor of MshB, consistent with a metal-water/hydroxide functioning as the reactive nucleophile in the catalytic mechanism. We have previously shown that MshB activity has a bell-shaped dependence on pH with pK(a) values of ∼7.3 and 10.5 (Huang, X., Kocabas, E. and Hernick, M. (2011) J. Biol. Chem. 286, 20275-20282). Mutagenesis experiments indicate that the observed pK(a) values reflect ionization of Asp-15 and Tyr-142, respectively. Together, findings from our studies suggest that MshB functions through a general acid-base pair mechanism with the side chain of Asp-15 functioning as the general base catalyst and His-144 serving as the general acid catalyst, whereas the side chain of Tyr-142 probably assists in polarizing substrate/stabilizing the oxyanion intermediate. Additionally, our results indicate that Tyr-142 is a dynamic side chain that plays key roles in catalysis, modulating substrate binding, chemistry, and product release.

Sequence-Specific Mapping of the Interaction between Urea and Unfolded Ubiquitin from Ensemble Analysis of NMR and Small Angle Scattering Data

The molecular details of how urea interacts with, and eventually denatures proteins, remain largely unknown. In this study we have used extensive experimental NMR data, in combination with statistical coil ensemble modeling and small-angle scattering, to analyze the conformational behavior of the protein ubiquitin in the presence of urea. In order to develop an atomic resolution understanding of the denatured state, conformational ensembles of full-atom descriptions of unfolded proteins, including side chain conformations derived from rotamer libraries, are combined with random sampling of explicit urea molecules in interaction with the protein. Using this description of the conformational equilibrium, we demonstrate that the direct-binding model of urea to the protein backbone is compatible with available experimental data. We find that, in the presence of 8 M urea, between 30 and 40% of the backbone peptide groups bind a urea molecule, independently reproducing results from a model-free analysis of small-angle neutron and X-ray scattering data. Crucially, this analysis also provides sequence specific details of the interaction between urea and the protein backbone. The pattern of urea-binding along the amino-acid sequence reveals a higher level of binding in the central part of the protein, a trend which resembles independent results derived from chemical shift mapping of the urea-protein interaction. Together these results substantiate the direct-binding model and provide a framework for studying the physical basis of interactions between proteins and solvent molecules.

TERPRED: A Dynamic Structural Data Analysis Tool.

Computational protein structure prediction mainly involves the main-chain prediction and the side-chain confirmation determination. In this research, we developed a new structural bioinformatics tool, TERPRED for generating dynamic protein side-chain rotamer libraries. Compared with current various rotamer sampling methods, our work is unique in that it provides a method to generate a rotamer library dynamically based on small sequence fragments of a target protein. The Rotamer Generator provides a means for existing side-chain sampling methods using static pre-existing rotamer libraries, to sample from dynamic target-dependent libraries. Also, existing side-chain packing algorithms that require large rotamer libraries for optimal performance, could possibly utilize smaller, target-relevant libraries for improved speed.

Rigid Core and Flexible Terminus: STRUCTURE OF SOLUBILIZED LIGHT-HARVESTING CHLOROPHYLL a/b COMPLEX (LHCII) MEASURED BY EPR

The structure of the major light-harvesting chlorophyll a/b complex (LHCII) was analyzed by pulsed EPR measurements and compared with the crystal structure. Site-specific spin labeling of the recombinant protein allowed the measurement of distance distributions over several intra- and intermolecular distances in monomeric and trimeric LHCII, yielding information on the protein structure and its local flexibility. A spin label rotamer library based on a molecular dynamics simulation was used to take the local mobility of spin labels into account. The core of LHCII in solution adopts a structure very similar or identical to the one seen in crystallized LHCII trimers with little motional freedom as indicated by narrow distance distributions along and between α helices. However, distances comprising the lumenal loop domain show broader distance distributions, indicating some mobility of this loop structure. Positions in the hydrophilic N-terminal domain, upstream of the first trans-membrane α helix, exhibit more and more mobility the closer they are to the N terminus. The nine amino acids at the very N terminus that have not been resolved in any of the crystal structure analyses give rise to very broad and possibly bimodal distance distributions, which may represent two families of preferred conformations.

A protein-dependent side-chain rotamer library

BackgroundProtein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rotamer libraries summarize the existing knowledge of the experimentally determined structures quantitatively. Depending on how much contextual information is encoded, there are backbone-independent rotamer libraries and backbone-dependent rotamer libraries. Backbone-independent libraries only encode sequential information, whereas backbone-dependent libraries encode both sequential and locally structural information. However, side-chain conformations are determined by spatially local information, rather than sequentially local information. Since in the side-chain prediction problem, the backbone structure is given, spatially local information should ideally be encoded into the rotamer libraries.MethodsIn this paper, we propose a new type of backbone-dependent rotamer library, which encodes structural information of all the spatially neighboring residues. We call it protein-dependent rotamer libraries. Given any rotamer library and a protein backbone structure, we first model the protein structure as a Markov random field. Then the marginal distributions are estimated by the inference algorithms, without doing global optimization or search. The rotamers from the given library are then re-ranked and associated with the updated probabilities.ResultsExperimental results demonstrate that the proposed protein-dependent libraries significantly outperform the widely used backbone-dependent libraries in terms of the side-chain prediction accuracy and the rotamer ranking ability. Furthermore, without global optimization/search, the side-chain prediction power of the protein-dependent library is still comparable to the global-search-based side-chain prediction methods.

SIDEpro: A novel machine learning approach for the fast and accurate prediction of side‐chain conformations

Accurate protein side-chain conformation prediction is crucial for protein modeling and existing methods for the task are widely used; however, faster and more accurate methods are still required. Here we present a new machine learning approach to the problem where an energy function for each rotamer in a structure is computed additively over pairs of contacting atoms. A family of 156 neural networks indexed by amino acid and contacting atom types is used to compute these rotamer energies as a function of atomic contact distances. Although direct energy targets are not available for training, the neural networks can still be optimized by converting the energies to probabilities and optimizing these probabilities using Markov Chain Monte Carlo methods. The resulting predictor SIDEpro makes predictions by initially setting the rotamer probabilities for each residue from a backbone-dependent rotamer library, then iteratively updating these probabilities using the trained neural networks. After convergences of the probabilities, the side-chains are set to the highest probability rotamer. Finally, a post processing clash reduction step is applied to the models. SIDEpro represents a significant improvement in speed and a modest, but statistically significant, improvement in accuracy when compared with the state-of-the-art for rapid side-chain prediction method SCWRL4 on the following datasets: (1) 379 protein test set of SCWRL4; (2) 94 proteins from CASP9; (3) a set of seven large protein-only complexes; and (4) a ribosome with and without the RNA. Using the SCWRL4 test set, SIDEpro's accuracy (χ(1) 86.14%, χ(1+2) 74.15%) is slightly better than SCWRL4-FRM (χ(1) 85.43%, χ(1+2) 73.47%) and it is 7.0 times faster. On the same test set SIDEpro is clearly more accurate than SCWRL4-rigid rotamer model (RRM) (χ(1) 84.15%, χ(1+2) 71.24%) and 2.4 times faster. Evaluation on the additional test sets yield similar accuracy results with SIDEpro being slightly more accurate than SCWRL4-flexible rotamer model (FRM) and clearly more accurate than SCWRL4-RRM; however, the gap in CPU time is much more significant when the methods are applied to large protein complexes. SIDEpro is part of the SCRATCH suite of predictors and available from: http://scratch.proteomics.ics.uci.edu/.

Transmembrane Gate Movements in the Type II ATP-binding Cassette (ABC) Importer BtuCD-F during Nucleotide Cycle

ATP-binding cassette (ABC) transporters are ubiquitous integral membrane proteins that translocate substrates across cell membranes. The alternating access of their transmembrane domains to opposite sides of the membrane powered by the closure and reopening of the nucleotide binding domains is proposed to drive the translocation events. Despite clear structural similarities, evidence for considerable mechanistic diversity starts to accumulate within the importers subfamily. We present here a detailed study of the gating mechanism of a type II ABC importer, the BtuCD-F vitamin B(12) importer from Escherichia coli, elucidated by EPR spectroscopy. Distance changes at key positions in the translocation gates in the nucleotide-free, ATP- and ADP-bound conformations of the transporter were measured in detergent micelles and liposomes. The translocation gates of the BtuCD-F complex undergo conformational changes in line with a "two-state" alternating access model. We provide the first direct evidence that binding of ATP drives the gates to an inward-facing conformation, in contrast to type I importers specific for maltose, molybdate, or methionine. Following ATP hydrolysis, the translocation gates restore to an apo-like conformation. In the presence of ATP, an excess of vitamin B(12) promotes the reopening of the gates toward the periplasm and the dislodgment of BtuF from the transporter. The EPR data allow a productive translocation cycle of the vitamin B(12) transporter to be modeled.

Conformational changes of the betaine transporter BetP from Corynebacterium glutamicum studied by pulse EPR spectroscopy

The betaine transporter BetP from Corynebacterium glutamicum is activated by hyperosmotic stress critically depending on the presence and integrity of its sensory C-terminal domain. The conformational properties of the trimeric BetP reconstituted in liposomes in the inactive state and during osmotic activation were investigated by site-directed spin labeling and electron paramagnetic resonance (EPR) spectroscopy. Comparison of intra- and intermolecular inter spin distance distributions obtained by double electron–electron resonance (DEER) EPR with the crystal structure of BetP by means of a rotamer library analysis suggest a rotation of BetP protomers within the trimer by about 15° as compared to the X-ray structure. Furthermore, we observed conformational changes upon activation of BetP, which are reflected in changes of the distances between positions 545 and 589 of different protomers in the trimer. Introduction of proline at positions 550 and 572, both leading to BetP variants with a permanent (low level) transport activity, caused changes of the DEER data similar to those observed for the activated and inactivated state, respectively. This indicates that not only displacements of the C-terminal domain in general but also concomitant interactions of its primary structure with surrounding protein domains and/or lipids are crucial for the activity regulation of BetP.