Structural biology aims at characterizing the structural and dynamic properties of biological macromolecules at atomic details. Gaining insight into three dimensional structures of biomolecules and their interactions is critical for understanding the vast majority of cellular processes, with direct applications in health and food sciences. Since 2010, the WeNMR project (www.wenmr.eu) has implemented numerous web-based services to facilitate the use of advanced computational tools by researchers in the field, using the high throughput computing infrastructure provided by EGI. These services have been further developed in subsequent initiatives under H2020 projects and are now operating as Thematic Services in the European Open Science Cloud portal (www.eosc-portal.eu), sending >12 millions of jobs and using around 4,000 CPU-years per year. Here we review 10 years of successful e-infrastructure solutions serving a large worldwide community of over 23,000 users to date, providing them with user-friendly, web-based solutions that run complex workflows in structural biology. The current set of active WeNMR portals are described, together with the complex backend machinery that allows distributed computing resources to be harvested efficiently.

We present the results for CAPRI Round 46, the third joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 heterocomplexes. Eight of the homo‐oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher‐order assemblies. These were more difficult to model, as their prediction mainly involved “ab‐initio” docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance “gap” was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template‐based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.

Background: GAC supplies for increased metabolic needs of tumors because of exclusive localization and kinetic properties. Results: Higher than tetramer oligomers are the active form in in vitro and in cellular assays. Bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide disrupts oligomers. Conclusion: A novel molecular mechanism for GAC activation is proposed. Significance: The data affect the development of therapies targeting GAC in tumors, with emphasis on allosteric inhibitors.

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

BackgroundThe characterization of protein binding sites is a major challenge in computational biology. Proteins interact with a wide variety of molecules and understanding of such complex interactions is essential to gain deeper knowledge of protein function. Shape complementarity is known to be important in determining protein-ligand interactions. Furthermore, these protein structural features have been shown to be useful in assisting medicinal chemists during lead discovery and optimization.ResultsWe developed KVFinder, a highly versatile and easy-to-use tool for cavity prospection and spatial characterization. KVFinder is a geometry-based method that has an innovative customization of the search space. This feature provides the possibility of cavity segmentation, which alongside with the large set of customizable parameters, allows detailed cavity analyses. Although the main focus of KVFinder is the steered prospection of cavities, we tested it against a benchmark dataset of 198 known drug targets in order to validate our software and compare it with some of the largely accepted methods. Using the one click mode, we performed better than most of the other methods, staying behind only of hybrid prospection methods. When using just one of KVFinder’s customizable features, we were able to outperform all other compared methods. KVFinder is also user friendly, as it is available as a PyMOL plugin, or command-line version.ConclusionKVFinder presents novel usability features, granting full customizable and highly detailed cavity prospection on proteins, alongside with a friendly graphical interface. KVFinder is freely available on http://lnbio.cnpem.br/bioinformatics/main/software/.

Psychrophilic enzymes evolved from a plethora of structural scaffolds via multiple molecular pathways. Elucidating their adaptive strategies is instrumental to understand how life can thrive in cold ecosystems and to tailor enzymes for biotechnological applications at low temperatures. In this work, we used X-ray crystallography, in solution studies and molecular dynamics simulations to reveal the structural basis for cold adaptation of the GH1 β-glucosidase from Exiguobacterium antarcticum B7. We discovered that the selective pressure of low temperatures favored mutations that redesigned the protein surface, reduced the number of salt bridges, exposed more hydrophobic regions to the solvent and gave rise to a tetrameric arrangement not found in mesophilic and thermophilic homologues. As a result, some solvent-exposed regions became more flexible in the cold-adapted tetramer, likely contributing to enhance enzymatic activity at cold environments. The tetramer stabilizes the native conformation of the enzyme, leading to a 10-fold higher activity compared to the disassembled monomers. According to phylogenetic analysis, diverse adaptive strategies to cold environments emerged in the GH1 family, being tetramerization an alternative, not a rule. These findings reveal a novel strategy for enzyme cold adaptation and provide a framework for the semi-rational engineering of β-glucosidases aiming at cold industrial processes.

Background:The identification of potential interaction partners for TACE could be instrumental in understanding the regulation of TACE activity. Results: Trx-1 interacts with the cytoplasmic domain of ADAM17. Conclusion: Trx-1 regulates ADAM17 activity. Significance: The data suggest a negative ADAM17 regulation in the HB-EGF shedding model.

Background: MyoVs are molecular motors widely distributed in eukaryotic cells responsible for membrane trafficking and intracellular transport. Results: The cargo-binding domain from human MyoV paralogs was structurally and biophysically characterized. Conclusion: We identified singular structural changes and molecular events conferring functional differentiation and modulating cargo binding. Significance: This work provides structural insights into cargo recognition and regulatory mechanisms in MyoVs.