The multiple roles of waters in protein solvation

Extensive molecular dynamics (MD) simulations have been used to characterize the multiple roles of water in solvating different types of proteins under different environmental conditions. We analyzed a small set of proteins, representative of the most prevalent meta-folds under native conditions, in the presence of crowding agents, and at high temperature with or without high concentration of urea. We considered also a protein in the unfolded state as characterized by NMR and atomistic MD simulations. Our results outline the main characteristics of the hydration environment of proteins and illustrate the dramatic plasticity of water, and its chameleonic ability to stabilize proteins under a variety of conditions

BioExcel Building Blocks Workflows (BioBB-Wfs), an integrated web-based plartform for biomolecular simulations.

We present BioExcel Building Blocks Workflows, a web-based graphical user interface (GUI) offering access to a collection of transversal pre-configured biomolecular simulation workflows assembled with the BioExcel Building Blocks library. Available workflows include Molecular Dynamics setup, protein-ligand docking, trajectory analyses and small molecule parameterization. Workflows can be launched in the platform or downloaded to be run in the users' own premises. Remote launching of long executions to user's available High-Performance computers is possible, only requiring configuration of the appropriate access credentials. The web-based graphical user interface offers a high level of interactivity, with integration with the NGL viewer to visualize and check 3D structures, MDsrv to visualize trajectories, and Plotly to explore 2D plots. The server requires no login but is recommended to store the users' projects and manage sensitive information such as remote credentials. Private projects can be made public and shared with colleagues with a simple URL. The tool will help biomolecular simulation users with the most common and repetitive processes by means of a very intuitive and interactive graphical user interface. The server is accessible at https://mmb.irbbarcelona.org/biobb-wfs

Bioactive conformational ensemble server and database. A public framework to speed up in silico drug discovery.

Modern high-throughput structure-based drug discovery algorithms consider ligand flexibility, but typically with low accuracy, which results in a loss of performance in the derived models. Here we present the Bioactive Conformational Ensemble (BCE) server and its associated database. The server creates conformational ensembles of drug-like ligands and stores them in the BCE database, where a variety of analyses are offered to the user. The workflow implemented in the BCE server combines enhanced sampling molecular dynamics with self-consistent reaction field quantum mechanics (SCRF/QM) calculations. The server automatizes all the steps to transform 1D or 2D representation of drugs into three dimensional molecules, which are then titrated, parametrized, hydrated and optimized before being subjected to Hamiltonian replica-exchange (HREX) molecular dynamics simulations. Ensembles are collected and subjected to a clustering procedure to derive representative conformers, which are then analyzed at the SCRF/QM level of theory. All structural data is organized in a noSQL database accessible through a graphical interface and in a programmatic manner through a REST API. The server allows the user to define a private workspace and offers a deposition protocol as well as input files for "in house" calculations in those cases where confidentiality is a must. The database and the associated server are available at https://mmb.irbbarcelona.org/BC

DNA structure directs positioning of the mitochondrial genome packaging protein Abf2p.

The mitochondrial genome (mtDNA) is assembled into nucleo-protein structures termed nucleoids and maintained differently compared to nuclear DNA, the involved molecular basis remaining poorly understood. In yeast (Saccharomyces cerevisiae), mtDNA is a ∼80 kbp linear molecule and Abf2p, a double HMG-box protein, packages and maintains it. The protein binds DNA in a non-sequence-specific manner, but displays a distinct 'phased-binding' at specific DNA sequences containing poly-adenine tracts (A-tracts). We present here two crystal structures of Abf2p in complex with mtDNA-derived fragments bearing A-tracts. Each HMG-box of Abf2p induces a 90° bend in the contacted DNA, causing an overall U-turn. Together with previous data, this suggests that U-turn formation is the universal mechanism underlying mtDNA compaction induced by HMG-box proteins. Combining this structural information with mutational, biophysical and computational analyses, we reveal a unique DNA binding mechanism for Abf2p where a characteristic N-terminal flag and helix are crucial for mtDNA maintenance. Additionally, we provide the molecular basis for A-tract mediated exclusion of Abf2p binding. Due to high prevalence of A-tracts in yeast mtDNA, this has critical relevance for nucleoid architecture. Therefore, an unprecedented A-tract mediated protein positioning mechanism regulates DNA packaging proteins in the mitochondria, and in combination with DNA-bending and U-turn formation, governs mtDNA compaction

The Role of Unconventional Hydrogen Bonds in Determining BII Propensities in B-DNA

An accurate understanding of DNA backbone transitions is likely to be the key for elucidating the puzzle of the intricate sequence-dependent mechanical properties that govern most of the biologically relevant functions of the double helix. One factor believed to be important in indirect recognition within protein–DNA complexes is the combined effect of two DNA backbone torsions (ε and ζ) which give rise to the well-known BI/BII conformational equilibrium. In this work we explain the sequence-dependent BII propensity observed in RpY steps (R = purine; Y = pyrimidine) at the tetranucleotide level with the help of a previously undetected C–H···O contact between atoms belonging to adjacent bases. Our results are supported by extensive multimicrosecond molecular dynamics simulations from the Ascona B-DNA Consortium, high-level quantum mechanical calculations, and data mining of the experimental structures deposited in the Protein Data Bank

Small Details Matter: The 2'-Hydroxyl as a Conformational Switch in RNA

While DNA is mostly a primary carrier of genetic information and displays a regular duplex structure, RNA can form very complicated and conserved 3D structures displaying a large variety of functions, such as being an intermediary carrier of the genetic information, translating such information into the protein machinery of the cell, or even acting as a chemical catalyst. At the base of such functional diversity is the subtle balance between different backbone, nucleobase, and ribose conformations, finely regulated by the combination of hydrogen bonds and stacking interactions. Although an apparently simple chemical modification, the presence of the 2′OH in RNA has a profound effect in the ribonucleotide conformational balance, adding an extra layer of complexity to the interactions network in RNA. In the present work, we have combined database analysis with extensive molecular dynamics, quantum mechanics, and hybrid QM/MM simulations to provide direct evidence on the dramatic impact of the 2′OH conformation on sugar puckering. Calculations provide evidence that proteins can modulate the 2′OH conformation to drive sugar repuckering, leading then to the formation of bioactive conformations. In summary, the 2′OH group seems to be a primary molecular switch contributing to specific protein–RNA recognition

The BioExcel methodology for developing dynamic, scalable, reliable and portable computational biomolecular workflows

Developing complex biomolecular workflows is not always straightforward. It requires tedious developments to enable the interoperability between the different biomolecular simulation and analysis tools. Moreover, the need to execute the pipelines on distributed systems increases the complexity of these developments. To address these issues, we propose a methodology to simplify the implementation of these workflows on HPC infrastructures. It combines a library, the BioExcel Building Blocks (BioBBs), that allows scientists to implement biomolecular pipelines as Python scripts, and the PyCOMPSs programming framework which allows to easily convert Python scripts into task-based parallel workflows executed in distributed computing systems such as HPC clusters, clouds, containerized platforms, etc. Using this methodology, we have implemented a set of computational molecular workflows and we have performed several experiments to validate its portability, scalability, reliability and malleability.This work has been supported by Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033 under contract PID2019-107255GB-C21, by the Generalitat de Catalunya under contracts 2017-SGR-01414 and 2017-SGR1110, by the European Commission through the BioExcel Center of Excellence (Horizon 2020 Framework program) under contracts 823830, and 675728. This work is also partially supported by the CECH project which has been co-funded with 50% by the European Regional Development Fund under the framework of the ERFD Operative Programme for Catalunya 2014-2020, with a grant of 1.527.637,88€.Peer ReviewedPostprint (author's final draft

BIGNASim: A NoSQL database structure and analysis portal for nucleic acids simulation data

Molecular dynamics simulation (MD) is, just behind genomics, the bioinformatics tool that generates the largest amounts of data, and that is using the largest amount of CPU time in supercomputing centres. MD trajectories are obtained after months of calculations, analysed in situ, and in practice forgotten. Several projects to generate stable trajectory databases have been developed for proteins, but no equivalence exists in the nucleic acids world. We present here a novel database system to store MD trajectories and analyses of nucleic acids. The initial data set available consists mainly of the benchmark of the new molecular dynamics force-field, parmBSC1. It contains 156 simulations, with over 120s of total simulation time. A deposition protocol is available to accept the submission of new trajectory data. The database is based on the combination of two NoSQL engines, Cassandra for storing trajectories and MongoDB to store analysis results and simulation metadata. The analyses available include backbone geometries, helical analysis, NMR observables and a variety of mechanical analyses. Individual trajectories and combined metatrajectories can be downloaded from the portal. The system is accessible through http://mmb.irbbarcelona.org/BIGNASim/. Supplementary Material is also available on-line at http://mmb.irbbarcelona.org/BIGNASim/SuppMaterial/

High-Throughput Prediction of the Impact of Genetic Variability on Drug Sensitivity and Resistance Patterns for Clinically Relevant Epidermal Growth Factor Receptor Mutations from Atomistic Simulations

Mutations in the kinase domain of the epidermal growth factor receptor (EGFR) can be drivers of cancer and also trigger drug resistance in patients receiving chemotherapy treatment based on kinase inhibitors. A priori knowledge of the impact of EGFR variants on drug sensitivity would help to optimize chemotherapy and design new drugs that are effective against resistant variants before they emerge in clinical trials. To this end, we explored a variety of in silico methods, from sequence-based to "state-of-the-art" atomistic simulations. We did not find any sequence signal that can provide clues on when a drug-related mutation appears or the impact of such mutations on drug activity. Low-level simulation methods provide limited qualitative information on regions where mutations are likely to cause alterations in drug activity, and they can predict around 70% of the impact of mutations on drug efficiency. High-level simulations based on nonequilibrium alchemical free energy calculations show predictive power. The integration of these "state-of-the-art" methods into a workflow implementing an interface for parallel distribution of the calculations allows its automatic and high-throughput use, even for researchers with moderate experience in molecular simulations

BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows.

In the recent years, the improvement of software and hardware performance has made biomolecular simulations a mature tool for the study of biological processes. Simulation length and the size and complexity of the analyzed systems make simulations both complementary and compatible with other bioinformatics disciplines. However, the characteristics of the software packages used for simulation have prevented the adoption of the technologies accepted in other bioinformatics fields like automated deployment systems, workflow orchestration, or the use of software containers. We present here a comprehensive exercise to bring biomolecular simulations to the "bioinformatics way of working". The exercise has led to the development of the BioExcel Building Blocks (BioBB) library. BioBB's are built as Python wrappers to provide an interoperable architecture. BioBB's have been integrated in a chain of usual software management tools to generate data ontologies, documentation, installation packages, software containers and ways of integration with workflow managers, that make them usable in most computational environments