Alkali metal cations modulate the geometry of different binding sites in HCN4 selectivity filter for permeation or block.

Hyperpolarization-activated cyclic-nucleotide gated (HCN) channels are important for timing biological processes like heartbeat and neuronal firing. Their weak cation selectivity is determined by a filter domain with only two binding sites for K+ and one for Na+. The latter acts as a weak blocker, which is released in combination with a dynamic widening of the filter by K+ ions, giving rise to a mixed K+/Na+ current. Here, we apply molecular dynamics simulations to systematically investigate the interactions of five alkali metal cations with the filter of the open HCN4 pore. Simulations recapitulate experimental data like a low Li+ permeability, considerable Rb+ conductance, a block by Cs+ as well as a punch through of Cs+ ions at high negative voltages. Differential binding of the cation species in specific filter sites is associated with structural adaptations of filter residues. This gives rise to ion coordination by a cation-characteristic number of oxygen atoms from the filter backbone and solvent. This ion/protein interplay prevents Li+, but not Na+, from entry into and further passage through the filter. The site equivalent to S3 in K+ channels emerges as a preferential binding and presumably blocking site for Cs+. Collectively, the data suggest that the weak cation selectivity of HCN channels and their block by Cs+ are determined by restrained cation-generated rearrangements of flexible filter residues.

Biotite: new tools for a versatile Python bioinformatics library.

BACKGROUND: Biotite is a program library for sequence and structural bioinformatics written for the Python programming language. It implements widely used computational methods into a consistent and accessible package. This allows for easy combination of various data analysis, modeling and simulation methods. RESULTS: This article presents major functionalities introduced into Biotite since its original publication. The fields of application are shown using concrete examples. We show that the computational performance of Biotite for bioinformatics tasks is comparable to individual, special purpose software systems specifically developed for the respective single task. CONCLUSIONS: The results show that Biotite can be used as program library to either answer specific bioinformatics questions and simultaneously allow the user to write entire, self-contained software applications with sufficient performance for general application.

EasySMPC: a simple but powerful no-code tool for practical secure multiparty computation.

BACKGROUND: Modern biomedical research is data-driven and relies heavily on the re-use and sharing of data. Biomedical data, however, is subject to strict data protection requirements. Due to the complexity of the data required and the scale of data use, obtaining informed consent is often infeasible. Other methods, such as anonymization or federation, in turn have their own limitations. Secure multi-party computation (SMPC) is a cryptographic technology for distributed calculations, which brings formally provable security and privacy guarantees and can be used to implement a wide-range of analytical approaches. As a relatively new technology, SMPC is still rarely used in real-world biomedical data sharing activities due to several barriers, including its technical complexity and lack of usability. RESULTS: To overcome these barriers, we have developed the tool EasySMPC, which is implemented in Java as a cross-platform, stand-alone desktop application provided as open-source software. The tool makes use of the SMPC method Arithmetic Secret Sharing, which allows to securely sum up pre-defined sets of variables among different parties in two rounds of communication (input sharing and output reconstruction) and integrates this method into a graphical user interface. No additional software services need to be set up or configured, as EasySMPC uses the most widespread digital communication channel available: e-mails. No cryptographic keys need to be exchanged between the parties and e-mails are exchanged automatically by the software. To demonstrate the practicability of our solution, we evaluated its performance in a wide range of data sharing scenarios. The results of our evaluation show that our approach is scalable (summing up 10,000 variables between 20 parties takes less than 300 s) and that the number of participants is the essential factor. CONCLUSIONS: We have developed an easy-to-use "no-code solution" for performing secure joint calculations on biomedical data using SMPC protocols, which is suitable for use by scientists without IT expertise and which has no special infrastructure requirements. We believe that innovative approaches to data sharing with SMPC are needed to foster the translation of complex protocols into practice.

Record linkage based patient intersection cardinality for rare disease studies using Mainzelliste and secure multi-party computation.

BACKGROUND: The low number of patients suffering from any given rare diseases poses a difficult problem for medical research: With the exception of some specialized biobanks and disease registries, potential study participants' information are disjoint and distributed over many medical institutions. Whenever some of those facilities are in close proximity, a significant overlap of patients can reasonably be expected, further complicating statistical study feasibility assessments and data gathering. Due to the sensitive nature of medical records and identifying data, data transfer and joint computations are often forbidden by law or associated with prohibitive amounts of effort. To alleviate this problem and to support rare disease research, we developed the Mainzelliste Secure EpiLinker (MainSEL) record linkage framework, a secure Multi-Party Computation based application using trusted-third-party-less cryptographic protocols to perform privacy-preserving record linkage with high security guarantees. In this work, we extend MainSEL to allow the record linkage based calculation of the number of common patients between institutions. This allows privacy-preserving statistical feasibility estimations for further analyses and data consolidation. Additionally, we created easy to deploy software packages using microservice containerization and continuous deployment/continuous integration. We performed tests with medical researchers using MainSEL in real-world medical IT environments, using synthetic patient data. RESULTS: We show that MainSEL achieves practical runtimes, performing 10 000 comparisons in approximately 5 minutes. Our approach proved to be feasible in a wide range of network settings and use cases. The "lessons learned" from the real-world testing show the need to explicitly support and document the usage and deployment for both analysis pipeline integration and researcher driven ad-hoc analysis use cases, thus clarifying the wide applicability of our software. MainSEL is freely available under: https://github.com/medicalinformatics/MainSEL CONCLUSIONS: MainSEL performs well in real-world settings and is a useful tool not only for rare disease research, but medical research in general. It achieves practical runtimes, improved security guarantees compared to existing solutions, and is simple to deploy in strict clinical IT environments. Based on the "lessons learned" from the real-word testing, we hope to enable a wide range of medical researchers to meet their needs and requirements using modern privacy-preserving technologies.

Secure Multi-Party Computation Based Distributed Feasibility Queries - A HiGHmed Use Case.

The integration of routine medical care data into research endeavors promises great value. However, access to this extra-domain data is constrained by numerous technical and legal requirements. The German Medical Informatics Initiative (MII) - initiated by the Federal Ministry of Research and Education (BMBF) - is making progress in setting up Medical Data Integration Centers to consolidate data stored in clinical primary information systems. Unfortunately, for many research questions cross-organizational data sources are required, as one organization's data is insufficient, especially in rare disease research. A first step, for research projects exploring possible multi-centric study designs, is to perform a feasibility query, i.e., a cohort size calculation transcending organizational boundaries. Existing solutions for this problem, like the previously introduced feasibility process for the MII's HiGHmed consortium, perform well for most use cases. However, there exist use cases where neither centralized data repositories, nor Trusted Third Parties are acceptable for data aggregation. Based on open standards, such as BPMN 2.0 and HL7 FHIR R4, as well as the cryptographic techniques of secure Multi-Party Computation, we introduce a fully automated, decentral feasibility query process without any central component or Trusted Third Party. The open source implementation of the proposed solution is intended as a plugin process to the HiGHmed Data Sharing Framework. The process's concept and underlying algorithms can also be used independently.

SPIKE: secure and private investigation of the kidney exchange problem.

BACKGROUND: The kidney exchange problem (KEP) addresses the matching of patients in need for a replacement organ with compatible living donors. Ideally many medical institutions should participate in a matching program to increase the chance for successful matches. However, to fulfill legal requirements current systems use complicated policy-based data protection mechanisms that effectively exclude smaller medical facilities to participate. Employing secure multi-party computation (MPC) techniques provides a technical way to satisfy data protection requirements for highly sensitive personal health information while simultaneously reducing the regulatory burdens. RESULTS: We have designed, implemented, and benchmarked SPIKE, a secure MPC-based privacy-preserving KEP protocol which computes a locally optimal solution by finding matching donor-recipient pairs in a graph structure. SPIKE matches 40 pairs in cycles of length 2 in less than 4 min and outperforms the previous state-of-the-art protocol by a factor of [Formula: see text] in runtime while providing medically more robust solutions. CONCLUSIONS: We show how to solve the KEP in a robust and privacy-preserving manner achieving significantly more practical performance than the current state-of-the-art (Breuer et al., WPES'20 and CODASPY'22). The usage of MPC techniques fulfills many data protection requirements on a technical level, allowing smaller health care providers to directly participate in a kidney exchange with reduced legal processes. As sensitive data are not leaving the institutions' network boundaries, the patient data underlie a higher level of protection than in the currently employed (centralized) systems. Furthermore, due to reduced legal barriers, the proposed decentralized system might be simpler to implement in a transnational, intereuropean setting with mixed (national) data protecion laws.

Weak Cation Selectivity in HCN Channels Results From K+-Mediated Release of Na+ From Selectivity Filter Binding Sites.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels generate the pacemaker current which plays an important role in the timing of various biological processes like the heart beat. We used umbrella sampling to explore the potential of mean force for the conduction of potassium and sodium through the open HCN4 pore. Our data explain distinct functional features like low unitary conductance and weak selectivity as a result of high energetic barriers inside the selectivity filter of this channel. They exceed the 3-5 kJ/mol threshold which is presumed as maximal barrier for diffusion-limited conductance. Furthermore, simulations provide a thermodynamic explanation for the weak cation selectivity of HCN channels that contain only two ion binding sites in the selectivity filter (SF). We find that sodium ions bind more strongly to the SF than potassium and are easier released by binding of potassium than of another sodium. Hence ion transport and selectivity in HCN channels is not determined by the same mechanism as in potassium-selective channels; it rather relies on sodium as a weak blocker that can only be released by potassium.

Consistent Quantification of Complex Dynamics via a Novel Statistical Complexity Measure.

Natural systems often show complex dynamics. The quantification of such complex dynamics is an important step in, e.g., characterization and classification of different systems or to investigate the effect of an external perturbation on the dynamics. Promising routes were followed in the past using concepts based on (Shannon's) entropy. Here, we propose a new, conceptually sound measure that can be pragmatically computed, in contrast to pure theoretical concepts based on, e.g., Kolmogorov complexity. We illustrate the applicability using a toy example with a control parameter and go on to the molecular evolution of the HIV1 protease for which drug treatment can be regarded as an external perturbation that changes the complexity of its molecular evolutionary dynamics. In fact, our method identifies exactly those residues which are known to bind the drug molecules by their noticeable signal. We furthermore apply our method in a completely different domain, namely foreign exchange rates, and find convincing results as well.

Adding hydrogen atoms to molecular models via fragment superimposition.

BACKGROUND: Most experimentally determined structures of biomolecules lack annotated hydrogen positions due to their low electron density. However, thorough structure analysis and simulations require knowledge about the positions of hydrogen atoms. Existing methods for their prediction are either limited to a certain range of molecules or only work effectively on small compounds. RESULTS: We present a novel algorithm that compiles fragments of molecules with known hydrogen atom positions into a library. Using this library the method is able to predict hydrogen positions for molecules with similar moieties. We show that the method is able to accurately assign hydrogen atoms to most organic compounds including biomacromolecules, if a sufficiently large library is used. CONCLUSIONS: We bundled the algorithm into the open-source Python package and command line program Hydride. Since usually no additional parametrization is necessary for the problem at hand, the software works out-of-box for a wide range of molecular systems usually within a few seconds of computation time. Hence, we believe that Hydride could be a valuable tool for structural biologists and biophysicists alike.

Mainzelliste SecureEpiLinker (MainSEL): privacy-preserving record linkage using secure multi-party computation.

MOTIVATION: Record Linkage has versatile applications in real-world data analysis contexts, where several datasets need to be linked on the record level in the absence of any exact identifier connecting related records. An example are medical databases of patients, spread across institutions, that have to be linked on personally identifiable entries like name, date of birth or ZIP code. At the same time, privacy laws may prohibit the exchange of this personally identifiable information (PII) across institutional boundaries, ruling out the outsourcing of the record linkage task to a trusted third party. We propose to employ privacy-preserving record linkage (PPRL) techniques that prevent, to various degrees, the leakage of PII while still allowing for the linkage of related records. RESULTS: We develop a framework for fault-tolerant PPRL using secure multi-party computation with the medical record keeping software Mainzelliste as the data source. Our solution does not rely on any trusted third party and all PII is guaranteed to not leak under common cryptographic security assumptions. Benchmarks show the feasibility of our approach in realistic networking settings: linkage of a patient record against a database of 10 000 records can be done in 48 s over a heavily delayed (100 ms) network connection, or 3.9 s with a low-latency connection. AVAILABILITY AND IMPLEMENTATION: The source code of the sMPC node is freely available on Github at https://github.com/medicalinformatics/SecureEpilinker subject to the AGPLv3 license. The source code of the modified Mainzelliste is available at https://github.com/medicalinformatics/MainzellisteSEL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Erratum: Three-body interactions improve contact prediction within direct-coupling analysis [Phys. Rev. E 96, 052405 (2017)].

This corrects the article DOI: 10.1103/PhysRevE.96.052405.

Gating movements and ion permeation in HCN4 pacemaker channels.

The HCN1-4 channel family is responsible for the hyperpolarization-activated cation current If/Ih that controls automaticity in cardiac and neuronal pacemaker cells. We present cryoelectron microscopy (cryo-EM) structures of HCN4 in the presence or absence of bound cAMP, displaying the pore domain in closed and open conformations. Analysis of cAMP-bound and -unbound structures sheds light on how ligand-induced transitions in the channel cytosolic portion mediate the effect of cAMP on channel gating and highlights the regulatory role of a Mg2+ coordination site formed between the C-linker and the S4-S5 linker. Comparison of open/closed pore states shows that the cytosolic gate opens through concerted movements of the S5 and S6 transmembrane helices. Furthermore, in combination with molecular dynamics analyses, the open pore structures provide insights into the mechanisms of K+/Na+ permeation. Our results contribute mechanistic understanding on HCN channel gating, cyclic nucleotide-dependent modulation, and ion permeation.

Identification of biophysical interaction patterns in direct coupling analysis.

Direct-coupling analysis is a statistical learning method for protein contact prediction based on sequence information alone. The maximum entropy principle leads to an effective inverse Potts model. Predictions on contacts are based on fitted local fields and couplings from an empirical multiple sequence alignment. Typically, the l_{2} norm of the resulting two-body couplings is used for contact prediction. However, this procedure discards important information. In this paper we show that the usage of the full fields and coupling information improves prediction accuracy.

Inferring functional units in ion channel pores via relative entropy.

Coarse-grained protein models approximate the first-principle physical potentials. Among those modeling approaches, the relative entropy framework yields promising and physically sound results, in which a mapping from the target protein structure and dynamics to a model is defined and subsequently adjusted by an entropy minimization of the model parameters. Minimization of the relative entropy is equivalent to maximization of the likelihood of reproduction of (configurational ensemble) observations by the model. In this study, we extend the relative entropy minimization procedure beyond parameter fitting by a second optimization level, which identifies the optimal mapping to a (dimension-reduced) topology. We consider anisotropic network models of a diverse set of ion channels and assess our findings by comparison to experimental results.

A Spatial and Functional Interaction of a Heterotetramer Survivin-DNA-PKcs Complex in DNA Damage Response.

Substantial evidence has shown that overexpression of the inhibitor of apoptosis protein (IAP) survivin in human tumors correlates significantly with treatment resistance and poor patient prognosis. Survivin serves as a radiation resistance factor that impacts the DNA damage response by interacting with DNA-dependent protein kinase (DNA-PKcs). However, the complexity, molecular determinants, and functional consequences of this interrelationship remain largely unknown. By applying coimmunoprecipitation and flow cytometry-based Förster resonance energy transfer assays, we demonstrated a direct involvement of the survivin baculovirus IAP repeat domain in the regulation of radiation survival and DNA repair. This survivin-mediated activity required an interaction of residues S20 and W67 with the phosphoinositide 3-kinase (PI3K) domain of DNA-PKcs. In silico molecular docking and dynamics simulation analyses, in vitro kinase assays, and large-scale mass spectrometry suggested a heterotetrameric survivin-DNA-PKcs complex that results in a conformational change within the DNA-PKcs PI3K domain. Overexpression of survivin resulted in enhanced PI3K enzymatic activity and detection of differentially abundant phosphopeptides and proteins implicated in the DNA damage response. The survivin-DNA-PKcs interaction altered the S/T-hydrophobic motif substrate specificity of DNA-PKcs with a predominant usage of S/T-P phosphorylation sites and an increase of DNA-PKcs substrates including Foxo3. These data demonstrate that survivin differentially regulates DNA-PKcs-dependent radiation survival and DNA double-strand break repair via formation of a survivin-DNA-PKcs heterotetrameric complex. SIGNIFICANCE: These findings provide insight into survivin-mediated regulation of DNA-PKcs kinase and broaden our knowledge of the impact of survivin in modulating the cellular radiation response.See related commentary by Iliakis, p. 2270 GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/9/2304/F1.large.jpg.

Substitution matrix based color schemes for sequence alignment visualization.

BACKGROUND: Visualization of multiple sequence alignments often includes colored symbols, usually characters encoding amino acids, according to some (physical) properties, such as hydrophobicity or charge. Typically, color schemes are created manually, so that equal or similar colors are assigned to amino acids that share similar properties. However, this assessment is subjective and may not represent the similarity of symbols very well. RESULTS: In this article we propose a different approach for color scheme creation: We leverage the similarity information of a substitution matrix to derive an appropriate color scheme. Similar colors are assigned to high scoring pairs of symbols, distant colors are assigned to low scoring pairs. In order to find these optimal points in color space a simulated annealing algorithm is employed. CONCLUSIONS: Using the substitution matrix as basis for a color scheme is consistent with the alignment, which itself is based on the very substitution matrix. This approach allows fully automatic generation of new color schemes, even for special purposes which have not been covered, yet, including schemes for structural alphabets or schemes that are adapted for people with color vision deficiency.

SICOR: Subgraph Isomorphism Comparison of RNA Secondary Structures.

RNA aptamer selection during SELEX experiments builds on secondary structural diversity. Advanced structural comparison methods can focus this diversity. We develop SICOR, which uses probabilistic subgraph isomorphisms for graph distances between RNA secondary structure graphs. SICOR outperforms other comparison methods and is applicable to many structural comparisons in experimental design.

The HCN domain couples voltage gating and cAMP response in hyperpolarization-activated cyclic nucleotide-gated channels.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels control spontaneous electrical activity in heart and brain. Binding of cAMP to the cyclic nucleotide-binding domain (CNBD) facilitates channel opening by relieving a tonic inhibition exerted by the CNBD. Despite high resolution structures of the HCN1 channel in the cAMP bound and unbound states, the structural mechanism coupling ligand binding to channel gating is unknown. Here we show that the recently identified helical HCN-domain (HCND) mechanically couples the CNBD and channel voltage sensing domain (VSD), possibly acting as a sliding crank that converts the planar rotational movement of the CNBD into a rotational upward displacement of the VSD. This mode of operation and its impact on channel gating are confirmed by computational and experimental data showing that disruption of critical contacts between the three domains affects cAMP- and voltage-dependent gating in three HCN isoforms.

Next-level riboswitch development-implementation of Capture-SELEX facilitates identification of a new synthetic riboswitch.

The development of synthetic riboswitches has always been a challenge. Although a number of interesting proof-of-concept studies have been published, almost all of these were performed with the theophylline aptamer. There is no shortage of small molecule-binding aptamers; however, only a small fraction of them are suitable for RNA engineering since a classical SELEX protocol selects only for high-affinity binding but not for conformational switching. We now implemented RNA Capture-SELEX in our riboswitch developmental pipeline to integrate the required selection for high-affinity binding with the equally necessary RNA conformational switching. Thus, we successfully developed a new paromomycin-binding synthetic riboswitch. It binds paromomycin with a KD of 20 nM and can discriminate between closely related molecules both in vitro and in vivo. A detailed structure-function analysis confirmed the predicted secondary structure and identified nucleotides involved in ligand binding. The riboswitch was further engineered in combination with the neomycin riboswitch for the assembly of an orthogonal Boolean NOR logic gate. In sum, our work not only broadens the spectrum of existing RNA regulators, but also signifies a breakthrough in riboswitch development, as the effort required for the design of sensor domains for RNA-based devices will in many cases be much reduced.

Tuning the Performance of Synthetic Riboswitches using Machine Learning.

Riboswitch development for clinical, technological, and synthetic biology applications constantly seeks to optimize regulatory behavior. Here, we present a machine learning approach to improve the regulation of a tetracycline (tc)-dependent riboswitch device composed of two individual tc aptamers. We developed a bioinformatics model that combines random forest analysis with a convolutional neural network to predict the switching behavior of such tandem riboswitches. We found that both biophysical parameters and the hydrogen bond pattern influence regulation. Our new design pipeline led to significant improvement of the tc riboswitch device with a dynamic range extension from 8.5 to 40-fold. We are confident that our novel method not only results in an excellent tc-dependent riboswitch device but further holds great promise and potential for the optimization of other riboswitches.