MOTIVATION: Software plays a crucial and growing role in research. Unfortunately, the computational component in Life Sciences research is often challenging to reproduce and verify. It could be undocumented, opaque, contain unknown errors that affect the outcome, or be directly unavailable and impossible to use for others. These issues are detrimental to the overall quality of scientific research. One step to address this problem is the formulation of principles that research software in the domain should meet to ensure its quality and sustainability, resembling the FAIR (findable, accessible, interoperable, and reusable) data principles. RESULTS: We present here a comprehensive series of quantitative indicators based on a pragmatic interpretation of the FAIR Principles and their implementation on OpenEBench, ELIXIR's open platform providing both support for scientific benchmarking and an active observatory of quality-related features for Life Sciences research software. The results serve to understand the current practices around research software quality-related features and provide objective indications for improving them. AVAILABILITY AND IMPLEMENTATION: Software metadata, from 11 different sources, collected, integrated, and analysed in the context of this manuscript are available at https://doi.org/10.5281/zenodo.7311067. Code used for software metadata retrieval and processing is available in the following repository: https://gitlab.bsc.es/inb/elixir/software-observatory/FAIRsoft_ETL.

Interactive Jupyter Notebooks in combination with Conda environments can be used to generate FAIR (Findable, Accessible, Interoperable and Reusable/Reproducible) biomolecular simulation workflows. The interactive programming code accompanied by documentation and the possibility to inspect intermediate results with versatile graphical charts and data visualization is very helpful, especially in iterative processes, where parameters might be adjusted to a particular system of interest. This work presents a collection of FAIR notebooks covering various areas of the biomolecular simulation field, such as molecular dynamics (MD), protein-ligand docking, molecular checking/modeling, molecular interactions, and free energy perturbations. Workflows can be launched with myBinder or easily installed in a local system. The collection of notebooks aims to provide a compilation of demonstration workflows, and it is continuously updated and expanded with examples using new methodologies and tools.

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.

MOTIVATION: The BioExcel Building Blocks (BioBB) library offers a broad collection of wrappers on top of common biomolecular simulation and bioinformatics tools. The possibility to access the library remotely and programmatically increases its usability, allowing individual and sporadic executions and enabling remote workflows. RESULTS: BioBB REST API extends and complements the BioBB library offering programmatic access to the collection of biomolecular simulation tools included in the BioExcel Building Blocks library. Molecular Dynamics setup, docking, structure modeling, free energy simulations and flexibility analyses are examples of functionalities included in the endpoints collection. All functionalities are accessible through standard REST API calls, voiding the need for tool installation. AVAILABILITY AND IMPLEMENTATION: All the information related to the BioBB REST API endpoints is accessible from https://mmb.irbbarcelona.org/biobb-api/. Links to extended documentation, including OpenAPI endpoints specification and examples, Read-The-Docs documentation and a complete workflow tutorial can be found in the Supplementary Table S1. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

After decades of using urea as denaturant, the kinetic role of this molecule in the unfolding process is still undefined: does urea actively induce protein unfolding or passively stabilize the unfolded state? By analyzing a set of 30 proteins (representative of all native folds) through extensive molecular dynamics simulations in denaturant (using a range of force-fields), we derived robust rules for urea unfolding that are valid at the proteome level. Irrespective of the protein fold, presence or absence of disulphide bridges, and secondary structure composition, urea concentrates in the first solvation shell of quasi-native proteins, but with a density lower than that of the fully unfolded state. The presence of urea does not alter the spontaneous vibration pattern of proteins. In fact, it reduces the magnitude of such vibrations, leading to a counterintuitive slow down of the atomic-motions that opposes unfolding. Urea stickiness and slow diffusion is, however, crucial for unfolding. Long residence urea molecules placed around the hydrophobic core are crucial to stabilize partially open structures generated by thermal fluctuations. Our simulations indicate that although urea does not favor the formation of partially open microstates, it is not a mere spectator of unfolding that simply displaces to the right of the folded ←→ unfolded equilibrium. On the contrary, urea actively favors unfolding: it selects and stabilizes partially unfolded microstates, slowly driving the protein conformational ensemble far from the native one and also from the conformations sampled during thermal unfolding.

SUMMARY: MDWeb and MDMoby constitute a web-based platform to help access to molecular dynamics (MD) in the standard and high-throughput regime. The platform provides tools to prepare systems from PDB structures mimicking the procedures followed by human experts. It provides inputs and can send simulations for three of the most popular MD packages (Amber, NAMD and Gromacs). Tools for analysis of trajectories, either provided by the user or retrieved from our MoDEL database (http://mmb.pcb.ub.es/MoDEL) are also incorporated. The platform has two ways of access, a set of web-services based on the BioMoby framework (MDMoby), programmatically accessible and a web portal (MDWeb). AVAILABILITY: http://mmb.irbbarcelona.org/MDWeb; additional information and methodology details can be found at the web site ( http://mmb.irbbarcelona.org/MDWeb/help.php)

Abstract Summary: FlexServ is a web-based tool for the analysis of protein flexibility. The server incorporates powerful protocols for the coarse-grained determination of protein dynamics using different versions of Normal Mode Analysis (NMA), Brownian dynamics (BD) and Discrete Dynamics (DMD). It can also analyze user provided trajectories. The server allows a complete analysis of flexibility using a large variety of metrics, including basic geometrical analysis, B-factors, essential dynamics, stiffness analysis, collectivity measures, Lindemann's indexes, residue correlation, chain-correlations, dynamic domain determination, hinge point detections, etc. Data is presented through a web interface as plain text, 2D and 3D graphics. Availability: http://mmb.pcb.ub.es/FlexServ; http://www.inab.org Contact: [email protected] or [email protected] Supplementary information: Additional information and methodology details can be found at http://mmb.pcb.ub.es/FlexServ/help.

Summary: PMUT allows the fast and accurate prediction (~80% success rate in humans) of the pathological character of single point amino acidic mutations based on the use of neural networks. The program also allows the fast scanning of mutational hot spots, which are obtained by three procedures: (1) alanine scanning, (2) massive mutation and (3) genetically accessible mutations. A graphical interface for Protein Data Bank (PDB) structures, when available, and a database containing hot spot profiles for all non-redundant PDB structures are also accessible from the PMUT server. Availability: PMUT is freely accessible at http://mmb2.pcb.ub.es:8080/PMut/ Contact: [email protected] Supplementary information: http://mmb2.pcb.ub.es:8080/PMutWeb/methodology.html

Abstract Classical molecular interaction potentials, in conjunction with other theoretical techniques, are used to analyze the dependence of the binding sites of representative proteins on the bound ligand. It is found that the ligand bound introduces in general small structural perturbations at the binding site of the protein. However, such small structural changes can lead to important alterations in the recognition pattern of the protein. The impact of these findings in docking procedures is discussed. Contact: [email protected]; [email protected] * To whom correspondence should be addressed.