Sharing data from molecular simulations

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 (https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD 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

SWISS-MODEL es un generador de modelos estructurales de proteínas cuyas estructuras aún no están depositadas en el PDB

En los últimos 15 años, los científicos han mejorado la habilidad para generar modelos estructurales de las proteínas, cuya estructura tridimensional (3D) se desconoce, gracias al crecimiento del número de estructuras depositadas en la base de datos Protein Data Bank (PDB). En la actualidad, uno de los métodos más usados y más rápidos para la generación de modelos estructurales es el servidor bioinformático SWISS-MODEL, creado para el modelado por homología de estructuras 3D, que comparten hasta 30% de identidad en su secuencia de aminoácidos con otras proteínas de estructura conocida. La calidad de los modelos resultantes se evalúa con varios parámetros bioquímicos (por ejemplo: QMEAN, RAMACHANDRAN plot). El modelo puede mejorarse al incluir el SWISS-MODEL en una línea de trabajo, seguido del servidor CHARMM-GUI y el programa GROMACS. Mientras el servidor CHARMM-GUI aplica al modelo producido, parámetros de un campo de fuerza para crear un sistema proteína-agua, bajo condiciones relevantes biológicamente, apto para simulación, el programa GROMACS minimiza la energía del modelo hasta alcanzar una estructura energéticamente estable, más cercana a como se encuentra en solución o en el sistema biológico. Los modelos generados por esta línea de trabajo pueden ser analizados a detalle por los biólogos estructurales en programas para visualización, como PyMOL, para obtener un mayor entendimiento del fenómeno biológico bajo estudio

Recent advances in computational studies of GPCR-G protein interactions

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Protein-protein interactions are key in cellular signaling. G protein-coupled receptors (GPCRs), the largest superfamily of human membrane proteins, are able to transduce extracellular signals (e.g., hormones and neurotransmitters) to intracellular proteins, in particular the G proteins. Since GPCRs serve as primary targets of ~ 1/3 of currently marketed drugs, it is important to understand mechanisms of GPCR signaling in order to design selective and potent drug molecules. This chapter focuses on recent advances in computational studies of the GPCR-G protein interactions using bioinformatics, protein-protein docking and molecular dynamics simulation approaches

Elucidating The Molecular Mechanisms by Which Mixed Phospholipid Bilayers Prevent The Formation of Amyloid-β Fibrils and Mediate Their Degradation in Alzheimer’s Disease

The buildup in the brain of plaques composed of aggregated amyloid-&beta; fibrils, is one of the major hallmarks in Alzheimer&rsquo;s disease(AD). Though many different strategies have been explored to slow Amyloid-&beta; fibril formation, very few strategies have been aimed at degrading already-formed fibrils. One recent in vitro study by Sosa et al. showed Amyloid- &beta; fibrils were prevented from being formed and that mature fibrils were also degraded in the presence of mixed phospholipid vesicles. The optimal lipid composition was observed to be 50% 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) and 50% 1,2-dio-leoyl-sn-glycero-3-phosphoglycerol (DOPG) and showed that fibril formation was inhibited by up to 76% and mature fibril content was reduced by up to 74%. Yet, the underlying mechanisms of this promising result remains unclear, hindering rational design efforts to further improve the properties of these vesicles against AD. The goal of this project is to fully elucidate the molecular mechanisms by which mixed phospholipid bilayers destabilize Amyloid-&beta; fibrils and stabilize Amyloid-&beta; monomers, towards the design of improved biomaterials-based platforms for combatting Alzheimer&rsquo;s disease. A&beta; plaque formation is believed to occur through a series of steps where the misfolding of Amyloid-&beta; monomers leads to their aggregation into neurotoxic oligomers, with increased &beta;-sheet content after encountering membrane-like media. These oligomers then aggregate into soluble protofibrils, that stabilize into mature fibrils, that in turn aggregate to form plaques in the brain. Using several experimental techniques, Sosa et al. deduced the lipid vesicles were acting like molecular chaperones to both catalyze the breakdown of the mature fibrils and the refolding of misfolded Amyloid-&beta; monomers, thus preventing fibril formation. It was hypothesized that the Amyloid-&beta;/bilayer binding energy was in essence &lsquo;just right&rsquo; at the optimal lipid composition: not too strong such that refolding/unfolding of A&beta; monomers/fibrils, respectively, could not occur due to stabilized misfolded/ aggregated states, and not too weak such that refolding/unfolding could not occur due to energetics. This project tests this hypothesis using atomistic, molecular dynamics (MD) simulations to rigorously characterize the molecular-level interactions of Amyloid-&beta; species and mixed phospholipid bilayers.</p

The Influence of Allostery Governing the Changes in Protein Dynamics Upon Substitution

The focus of this research is to investigate the effects of allostery on the function/activity of an enzyme, human immunodeficiency virus type 1 (HIV-1) protease, using well-defined statistical analyses of the dynamic changes of the protein and variants with unique single point substitutions 1. The experimental data1 evaluated here only characterized HIV-1 protease with one of its potential target substrates. Probing the dynamic interactions of the residues of an enzyme and its variants can offer insight of the developmental importance for allosteric signaling and their connection to a protein’s function. The realignment of the secondary structure elements can modulate the mobility along with the frequency of residue contacts as well as which residues are making contact together2-5. We postulate that if there are more contacts occurring within a structure the mobility is being constrained and therefore gaining novel contacts can negatively influence the function of a protein. The evolutionary importance of protein dynamics is probed by analyzing the residue positions possessing significant correlations and the relationship between experimental information1 (variant activities). We propose that the correlated dynamics of residues observed to have considerable correlations, if disrupted, can be used to infer the function of HIV-1 protease and its variants. Given the robustness of HIV-1 protease the identification of any significant constraint imposed on the dynamics from a potential allosteric site found to disrupt the catalytic activity of the variant is not plainly evident. We also develop machine learning (ML) algorithms to predict the protein function/activity change caused by a single point substitution by using the DCC of each residue pair. Recognition of any substantial association between the dynamics of specific residues and allosteric communication or mechanism requires detailed examination of the dynamics of HIV-1 protease and its variants. We also explore the non-linear dependency between each pair of residues using Mutual Information (MI) and how it can influence the dynamics of HIV-1 protease and its variants. We suggest that if the residues of a protein receive more or less information than that of the WT it will adversely impact the function of the protein and can be used to support the classification of a variant structure. Furthermore, using the MI of residues obtained from the MD simulations for the HIV-1 protease structure, we build a ML model to predict a protein’s change in function caused by a single point substitution. Effectively the mobility, dynamics, and non-linear features tested in these studies are found to be useful towards the prediction of potentially drug resistant substitutions related to the catalytic efficiency of HIV-1 protease and the variants

Selectivity Mechanisms Employed by Flavin-Dependent Monooxygenases

Nature is an incredible source of inspiration for the discovery and subsequent development of new bioactive compounds. Unfortunately, the synthesis of these molecules is often prohibitively complex, requiring the installation of multiple functional groups with intricate three-dimensional architectures critical to their biological activity. Biocatalytic reactions embody many features of ideal chemical transformations, including the potential for impeccable selectivity, high catalytic efficiency, mild reaction conditions, and the use of environmentally benign reagents. These advantages have created a demand for new biocatalysts that expand the portfolio of complexity-generating reactions available to synthetic chemists. Oxidative dearomatization is a powerful transformation in the synthesis of complex molecules, as it generates a stereocenter and simultaneously producing a compound primed for further reactions. Nature has developed a class of biocatalysts, flavin-dependent monooxygenases, which perform this reaction with an excellent site- and stereoselectivity under mild conditions. Our studies on the TropB-catalyzed hydroxylation of phenolic compounds has defined the substrate scope of these biocatalysts; however, the mechanistic underpinnings were a mystery. Through analysis of class A FAD monooxygenases and biochemical characterization of TropB we determined that the phenolate form of the substrate interacts with Tyr239 and Arg206 to control the site- and stereo-selectivity of the hydroxylation. We then we explore how this control for site- and stereo-selective is translated to a selection of FAD-dependent monooxygenases. Through a sequence-profiling approach, we identified the FDMO AfoD with complementary selectivity compared to TropB. We determined by probing similarly positioned residues through mutagenesis and biochemical characterization that selectivity can be eroded when Tyr118 hydrogen bonding is affected. These findings pave the way in identifying new biocatalysts for reaction development toward natural product synthesis.PHDChemical BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/167982/1/attabey_1.pd

Novel antimicrobial peptides for enhanced antimicrobial activity against methicillin resistant Staphylococcus aureus: design, synthesis and formulation.

Doctoral Degree. University of KwaZulu-Natal, Durban.Abstract available in pdf