Channel Estimation for Diffusive Molecular Communications

In molecular communication (MC) systems, the \textit{expected} number of molecules observed at the receiver over time after the instantaneous release of molecules by the transmitter is referred to as the channel impulse response (CIR). Knowledge of the CIR is needed for the design of detection and equalization schemes. In this paper, we present a training-based CIR estimation framework for MC systems which aims at estimating the CIR based on the \textit{observed} number of molecules at the receiver due to emission of a \textit{sequence} of known numbers of molecules by the transmitter. Thereby, we distinguish two scenarios depending on whether or not statistical channel knowledge is available. In particular, we derive maximum likelihood (ML) and least sum of square errors (LSSE) estimators which do not require any knowledge of the channel statistics. For the case, when statistical channel knowledge is available, the corresponding maximum a posteriori (MAP) and linear minimum mean square error (LMMSE) estimators are provided. As performance bound, we derive the classical Cramer Rao (CR) lower bound, valid for any unbiased estimator, which does not exploit statistical channel knowledge, and the Bayesian CR lower bound, valid for any unbiased estimator, which exploits statistical channel knowledge. Finally, we propose optimal and suboptimal training sequence designs for the considered MC system. Simulation results confirm the analysis and compare the performance of the proposed estimation techniques with the respective CR lower bounds.Comment: to be appeared in IEEE Transactions on Communications. arXiv admin note: text overlap with arXiv:1510.0861

Structural Analysis of the Protein Phosphatase 1 Docking Motif: Molecular Description of Binding Specificities Identifies Interacting Proteins

SummaryThe interplay between kinases and phosphatases represents a fundamental regulatory mechanism in biological systems. Being less numerous than kinases, phosphatases increase their diversity by the acquisition of a variety of binding partners, thereby forming a large number of holoenzymes. Proteins interacting with protein phosphatase 1 (PP1) often bind via a so-called docking motif to regulate its enzymatic activity, substrate specificity, and subcellular localization. Here, we systematically determined structural elements that mediate the binding specificity of PP1 interacting proteins, and propose a refined consensus sequence for high-affinity PP1 ligands. Applying this pattern to database searches, we predicted and experimentally confirmed several previously unknown PP1 interactors. Thus, the suggested PP1 docking motif enables a highly specific prediction of PP1 binding partners, thereby facilitating the genome-wide identification of PP1 interactors

Structural Basis for Species Selectivity in the HIV-1 gp120-CD4 Interaction: Restoring Affinity to gp120 in Murine CD4 Mimetic Peptides

The first step of HIV-1 infection involves interaction between the viral glycoprotein gp120 and the human cellular receptor CD4. Inhibition of the gp120-CD4 interaction represents an attractive strategy to block HIV-1 infection. In an attempt to explore the known lack of affinity of murine CD4 to gp120, we have investigated peptides presenting the putative gp120-binding site of murine CD4 (mCD4). Molecular modeling indicates that mCD4 protein cannot bind gp120 due to steric clashes, while the larger conformational flexibility of mCD4 peptides allows an interaction. This finding is confirmed by experimental binding assays, which also evidenced specificity of the peptide-gp120 interaction. Molecular dynamics simulations indicate that the mCD4-peptide stably interacts with gp120 via an intermolecular β-sheet, while an important salt-bridge formed by a C-terminal lysine is lost. Fixation of the C-terminus by introducing a disulfide bridge between the N- and C-termini of the peptide significantly enhanced the affinity to gp120

Synthetic protein scaffolds based on peptide motifs and cognate adaptor domains for improving metabolic productivity

he efficiency of many cellular processes relies on the defined interaction among different proteins within the same metabolic or signaling pathway. Consequently, a spatial colocalization of functionally interacting proteins has frequently emerged during evolution. This concept has been adapted within the synthetic biology community for the purpose of creating artificial scaffolds. A recent advancement of this concept is the use of peptide motifs and their cognate adaptor domains. SH2, SH3, GBD, and PDZ domains have been used most often in research studies to date. The approach has been successfully applied to the synthesis of a variety of target molecules including catechin, D-glucaric acid, H2, hydrochinone, resveratrol, butyrate, gamma-aminobutyric acid, and mevalonate. Increased production levels of up to 77-fold have been observed compared to non-scaffolded systems. A recent extension of this concept is the creation of a covalent linkage between peptide motifs and adaptor domains, which leads to a more stable association of the scaffolded systems and thus bears the potential to further enhance metabolic productivity

DNA binding by Corynebacterium glutamicum TetR-type transcription regulator AmtR

<p>Abstract</p> <p>Background</p> <p>The TetR family member AmtR is the central regulator of nitrogen starvation response in <it>Corynebacterium glutamicum</it>. While the AmtR regulon was physiologically characterized in great detail up to now, mechanistic questions of AmtR binding were not addressed. This study presents a characterization of functionally important amino acids in the DNA binding domain of AmtR and of crucial nucleotides in the AmtR recognition motif.</p> <p>Results</p> <p>Site-directed mutagenesis, the characterization of corresponding mutant proteins by gel retardation assays and surface plasmon resonance and molecular modelling revealed several amino acids, which are directly involved in DNA binding, while others have more structural function. Furthermore, we could show that the spacing of the binding motif half sites is crucial for repression of transcription by AmtR.</p> <p>Conclusion</p> <p>Although the DNA binding domain of TetR-type repressors is highly conserved and a core binding motif was identified for AmtR and TetR(D), the AmtR binding domain shows individual properties compared to other TetR proteins. Besides by distinct amino acids of AmtR, DNA binding is influenced by nucleotides not only of the conserved binding motif but also by spacing nucleotides in <it>C. glutamicum</it>.</p

Synthetic Peptides as Protein Mimics

The design and generation of molecules capable of mimicking the binding and/or functional sites of proteins represents a promising strategy for the exploration and modulation of protein function through controlled interference with the underlying molecular interactions. Synthetic peptides have proven an excellent type of molecule for the mimicry of protein sites because such peptides can be generated as exact copies of protein fragments, as well as in diverse chemical modifications, which includes the incorporation of a large range of non-proteinogenic amino acids as well as the modification of the peptide backbone. Apart from extending the chemical and structural diversity presented by peptides, such modifications also increase the proteolytic stability of the molecules, enhancing their utility for biological applications. This article reviews recent advances by this and other laboratories in the use of synthetic protein mimics to modulate protein function, as well as to provide building blocks for synthetic biology

Agonist Binding and G Protein Coupling in Histamine H2 Receptor: A Molecular Dynamics Study

The histamine H2 receptor (H2R) plays an important role in the regulation of gastric acid secretion. Therefore, it is a main drug target for the treatment of gastroesophageal reflux or peptic ulcer disease. However, there is as of yet no 3D-structural information available hampering a mechanistic understanding of H2R. Therefore, we created a model of the histamine-H2R-Gs complex based on the structure of the ternary complex of the β2-adrenoceptor and investigated the conformational stability of this active GPCR conformation. Since the physiologically relevant motions with respect to ligand binding and conformational changes of GPCRs can only partly be assessed on the timescale of conventional MD (cMD) simulations, we also applied metadynamics and Gaussian accelerated molecular dynamics (GaMD) simulations. A multiple walker metadynamics simulation in combination with cMD was applied for the determination of the histamine binding mode. The preferential binding pose detected is in good agreement with previous data from site directed mutagenesis and provides a basis for rational ligand design. Inspection of the H2R-Gs interface reveals a network of polar interactions that may contribute to H2R coupling selectivity. The cMD and GaMD simulations demonstrate that the active conformation is retained on a μs-timescale in the ternary histamine-H2R-Gs complex and in a truncated complex that contains only Gs helix α5 instead of the entire G protein. In contrast, histamine alone is unable to stabilize the active conformation, which is in line with previous studies of other GPCRs

A Metadynamics-Based Protocol for the Determination of GPCR-Ligand Binding Modes

G protein-coupled receptors (GPCRs) are a main drug target and therefore a hot topic in pharmaceutical research. One important prerequisite to understand how a certain ligand affects a GPCR is precise knowledge about its binding mode and the specific underlying interactions. If no crystal structure of the respective complex is available, computational methods can be used to deduce the binding site. One of them are metadynamics simulations which have the advantage of an enhanced sampling compared to conventional molecular dynamics simulations. However, the enhanced sampling of higher-energy states hampers identification of the preferred binding mode. Here, we present a novel protocol based on clustering of multiple walker metadynamics simulations which allows identifying the preferential binding mode from such conformational ensembles. We tested this strategy for three different model systems namely the histamine H1 receptor in combination with its physiological ligand histamine, as well as the β2 adrenoceptor with its agonist adrenaline and its antagonist alprenolol. For all three systems, the proposed protocol was able to reproduce the correct binding mode known from the literature suggesting that the approach can more generally be applied to the prediction of GPCR ligand binding in future

Challenges for the implementation of next generation sequencing-based expanded carrier screening: Lessons learned from the ciliopathies

Next generation sequencing (NGS) can detect carrier status for rare recessive disorders, informing couples about their reproductive risk. The recent ACMG recommendations support offering NGS-based carrier screening (NGS-CS) in an ethnic and population-neutral manner for all genes that have a carrier frequency >1/200 (based on GnomAD). To evaluate current challenges for NGS-CS, we focused on the ciliopathies, a well-studied group of rare recessive disorders. We analyzed 118 ciliopathy genes by whole exome sequencing in ~400 healthy local individuals and ~1000 individuals from the UK1958-birth cohort. We found 20% of healthy individuals (1% of couples) to be carriers of reportable variants in a ciliopathy gene, while 50% (4% of couples) carry variants of uncertain significance (VUS). This large proportion of VUS is partly explained by the limited utility of the ACMG/AMP variant-interpretation criteria in healthy individuals, where phenotypic match or segregation criteria cannot be used. Most missense variants are thus classified as VUS and not reported, which reduces the negative predictive value of the screening test. We show how gene-specific variation patterns and structural protein information can help prioritize variants most likely to be disease-causing, for (future) functional assays. Even when considering only strictly pathogenic variants, the observed carrier frequency is substantially higher than expected based on estimated disease prevalence, challenging the 1/200 carrier frequency cut-off proposed for choice of genes to screen. Given the challenges linked to variant interpretation in healthy individuals and the uncertainties about true carrier frequencies, genetic counseling must clearly disclose these limitations of NGS-CS