Defining the importance of landscape metrics for large branchiopod biodiversity and conservation: the case of the Iberian Peninsula and Balearic Islands

The deficiency in the distributional data of invertebrate taxa is one of the major impediments acting on the bias towards the low awareness of its conservation status. The present study sets a basic framework to understand the large branchiopods distribution in the Iberian Peninsula and Balearic Islands. Since the extensive surveys performed in the late 1980s, no more studies existed updating the information for the whole studied area. The present study fills the gap, gathering together all available information on large branchiopods distribution since 1995, and analysing the effect of human population density and several landscape characteristics on their distribution, taking into consideration different spatial scales (100 m, 1 km and 10 km). In overall, 28 large branchiopod taxa (17 anostracans, 7 notostracans and 4 spinicaudatans) are known to occur in the area. Approximately 30% of the sites hosted multiple species, with a maximum of 6 species. Significant positive co-occurring species pairs were found clustered together, forming 4 different associations of large branchiopod species. In general, species clustered in the same group showed similar responses to analysed landscape characteristics, usually showing a better fit at higher spatial scales.Brazilian Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-CNPq [401045/2014-5]Spanish Ministry of Education, Culture and Sport [FPU014/06783]info:eu-repo/semantics/publishedVersio

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC00100

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Protein assembly modeling by pyDock: integration of ab initio docking and energy-based scoring of AlphaFold interfaces

Resumen del trabajo presentado en 15th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP15), celebrado en Turquía, del 10 al 13 de diciembre de 2022We explored here new strategies for modeling of protein assemblies by integrating deep learning approaches like AlphaFold with the docking and energy-based scoring function of pyDock1, which previously showed successful results on template-based and ab initio docking models2. For that, we participated in the CASP15 Assembly category, as part of the 5th common CASP-CAPRI Assembly Prediction challenge (CAPRI Round 54), consisting in 39 targets: nine homo-dimers (A2), 13 hetero-dimers (A1B1 or E1I1), five homo-trimers (A3), three hetero-trimers (A2B1), and nine higher-degree homo- and heter-oligomers (ranging from a hetero-pentamer to a homo-16mer). As human predictors, we participated in all of the proposed targets except in H1137/T204. As scorers, we participated in all 38 proposed targets (target H1106/T191 was not included in the scoring experiment)

Application of pyDock, CCharPPI and ConSurf to identify physiological dimers

Trabajo presentado en 3D-BioInfo ELIXIR Community Annual Meeting, celebrado online (vía zoom), del 2 al 4 de noviembre de 2021We describe here our participation in the Activity II of the ELIXIR 3D-BioInfo Community "Open resources for sharing, integrating and benchmarking software tools for modelling the proteome in 3D". A major goal of this 3D-BioInfo activity is the application of computational tools to improve the discrimination between physiological and non-physiological dimer interfaces. With this purpose, we have applied a variety of scoring parameters to the proposed benchmark version 3, composed of 836 physiological and 841 non-physiological dimer interfaces. The scoring functions we have evaluated are: i) pyDock [1] docking score, which is composed of electrostatics, desolvation, and van der Waals energy terms (the latter weighted by 10%). This combination was optimized for the scoring of poses from ab initio docking, and seems also suitable for models generated by template-based docking. Here we will apply this function as well as each individual pyDock energy term to the proposed benchmark of dimer interfaces. ii) 88 descriptors in CCharPPI [2] (https://life.bsc.es/pid/ccharppi/). From the original 108 descriptors, we have discarded those descriptors that failed in a significant number cases. iii) Conservation score in ConSurf [3] (https://consurf.tau.ac.il/). We have applied the score to evaluate the conservation of protein-protein interface residues and provide a composite value that help to identify the physiological interfaces. We will also discuss the performance of all these descriptors on the discrimination of physiological and non-physiological dimer interfaces, and propose ways of combining these descriptors for optimal predictions. [1] Cheng TM, Blundell TL, Fernandez-Recio J (2007) Proteins 68, 503¿515. [2] Moal IH, Jiménez-García B, Fernandez-Recio J (2015) Bioinformatics 31, 123-125. [3] Glaser F, Pupko T, Paz I, Bell RE, Bechor D, Martz E, Ben-Tal N (2003) Bioinformatics 19, 163-164

Assembly prediction in CASP14 with pyDock ab initio docking and scoring

Trabajo presentado en 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction CASP14, celebrado online entre los meses de mayo y septiembre de 2020In the past 3rd common CASP-CAPRI Assembly Prediction challenge, our modeling approach, integrating ab initio docking, template-based modeling, distance-based restraints, low-resolution structural data and symmetry constraints, yielded excellent performance, ranking 2nd among CAPRI predictors, and 1st among CAPRI scorers1. Here we describe our participation in the CASP14 Assembly category, as part of the 4th common CASP-CAPRI Assembly Prediction challenge (CAPRI Round 50). We have participated as human predictors, human scorers, and server scorers, in all the 18 proposed targets, consisting in four hetero-dimers (A1B1), six homodimers (A2), two homo-trimers (A3), two homo-tetramers (A4), one hetero-nonamer (A3B3C3), one homo-20mer (A20), one hetero-27mer (A6B3C12D6), and one homo-240mer (A240)

Machine learning applied to estimate the impact of mutations at protein-protein interfaces based on physico-chemical, statistical and evolutionary conservation descriptors

Trabajo presentado en el Annual General Meeting ELIXIR 3D BioInfo Community F2F (hybrid meeting), celebrado en Hinxton (Reino Unido), del 2 al 4 de noviembre de 2022Inspired by our participation in the Activity II of the ELIXIR 3D-BioInfo Community "Open resources for sharing, integrating and benchmarking software tools for modelling the proteome in 3D"., in which we applied a variety of scoring parameters from pyDock [1], CCharPPI [2] and ConSurf [3] to improve the discrimination between physiological and non-physiological dimer interfaces, we have further explored the use of these functions to estimate the impact of mutations on protein-protein binding affinity. Sets of mutants were obtained from SKEMPI v2.0 database [4], as well as their binding affinity and kinetic values and the wild type (WT) complex structures. The structure of mutants can be modelled by SCWRL [5] and by molecular dynamics (MD). Then, different descriptors were applied to the mutated and WT structures (as well as on different MD-based conformations), first individually, and then in combination obtained from random forest classifiers. Energy-based descriptors such as electrostatics, desolvation and van der Waals provided predictive results comparable to other multiparametric methods. The application of random forest classifiers to the entire set of descriptors shows promising predictive results for the detection of beneficial and deleterious mutations regarding their impact on protein-protein binding affinity. The results of this predictor are comparable with the gold-standard MM-PBSA [6] at much lower computational cost. Finally, the approach was extended to mutations affecting protein-protein interactions for which no complex structure is available, by using docking models

New insights Into the evolution of the electron transfer from cytochrome f to photosystem I in the green and red branches of photosynthetic eukaryotes

In cyanobacteria and most green algae of the eukaryotic green lineage, the copper-protein plastocyanin (Pc) alternatively replaces the heme-protein cytochrome c6 (Cc6) as the soluble electron carrier from cytochrome f (Cf) to photosystem I (PSI). The functional and structural equivalence of 'green' Pc and Cc6 has been well established, representing an example of convergent evolution of two unrelated proteins. However, plants only produce Pc, despite having evolved from green algae. On the other hand, Cc6 is the only soluble donor available in most species of the red lineage of photosynthetic organisms, which includes, among others, red algae and diatoms. Interestingly, Pc genes have been identified in oceanic diatoms, probably acquired by horizontal gene transfer from green algae. However, the mechanisms that regulate the expression of a functional Pc in diatoms are still unclear. In the green eukaryotic lineage, the transfer of electrons from Cf to PSI has been characterized in depth. The conclusion is that in the green lineage, this process involves strong electrostatic interactions between partners, which ensure a high affinity and an efficient electron transfer (ET) at the cost of limiting the turnover of the process. In the red lineage, recent kinetic and structural modeling data suggest a different strategy, based on weaker electrostatic interactions between partners, with lower affinity and less efficient ET, but favoring instead the protein exchange and the turnover of the process. Finally, in diatoms the interaction of the acquired green-Type Pc with both Cf and PSI may not yet be optimized.Ministerio de Economía, Industria y Competitividad BIO2015-64169-P, BIO2016-79930-RJunta de Andalucía PAIDI BIO-02

The pyDock interface scoring functions

Trabajo presentado en el 3D-Bioinformatics 2020 Annual Workshop, celebrado online del 24 al 26 de noviembre de 2020We describe here the application of pyDock [1] methodology for the scoring of protein-protein interfaces, which can be relevant for the Activity II of the ELIXIR 3D-BioInfo Community "Open resources for sharing, integrating and benchmarking software tools for modelling the proteome in 3D". A major goal of this 3D-BioInfo activity is the application of computational tools for the identification of physiological dimer interfaces and the correct description of functional oligomerization states of proteins and protein assemblies. Indeed, this is an important problem that needs to be targeted before attempting more ambitious structural interactomics projects, such as the structure- and docking-based impact of interface mutations in genes related to diseases detected by newborn screening programs [2]. The capabilities of pyDock for the scoring of modelled assemblies, as recently shown in the recent CASP13-CAPRI and 7th CAPRI rounds, prompted us to explore its application to the characterization of biologically relevant assembly modes. The scoring function of pyDock is composed of electrostatics, desolvation, and van der Waals energy terms (the latter weighted by 10%). This combination was optimized for the scoring of poses from ab initio docking, and seems also suitable for models generated by template-based docking. Here we will apply this function to the proposed benchmark of dimer interfaces, and we will also discuss the performance of each individual pyDock energy term and their different combinations on the discrimination of physiological and non-physiological dimer interfaces. In addition, pyDock binding energy can be easily partitioned per residue, as implemented in the pyDockEneRes web server (https://life.bsc.es/pid/pydockeneres/) [3], which can provide additional information to further characterize the benchmark of dimer interfaces. [1] Cheng TM, Blundell TL, Fernandez-Recio J (2007) Proteins 68, 503¿515. [2] Navío D, Rosell M, Aguirre J, de la Cruz X, Fernánde-Recio J (2019) Int J Mol Sci 20, 1583. [3] Romero-Durana M, Jiménez-García B, Fernández-Recio J (2020) Bioinformatics 36, 2284-2285

New insights into the evolution of the electron transfer from cytochrome f to photosystem i in the green and red branches of photosynthetic eukaryotes

In cyanobacteria and most green algae of the eukaryotic green lineage, the copper-protein plastocyanin (Pc) alternatively replaces the heme-protein cytochrome c6 (Cc6) as the soluble electron carrier from cytochrome f (Cf) to photosystem I (PSI). The functional and structural equivalence of ‘green’ Pc and Cc6 has been well established, representing an example of convergent evolution of two unrelated proteins. However, plants only produce Pc, despite having evolved from green algae. On the other hand, Cc6 is the only soluble donor available in most species of the red lineage of photosynthetic organisms, which includes, among others, red algae and diatoms. Interestingly, Pc genes have been identified in oceanic diatoms, probably acquired by horizontal gene transfer from green algae. However, the mechanisms that regulate the expression of a functional Pc in diatoms are still unclear. In the green eukaryotic lineage, the transfer of electrons from Cf to PSI has been characterized in depth. The conclusion is that in the green lineage, this process involves strong electrostatic interactions between partners, which ensure a high affinity and an efficient electron transfer (ET) at the cost of limiting the turnover of the process. In the red lineage, recent kinetic and structural modeling data suggest a different strategy, based on weaker electrostatic interactions between partners, with lower affinity and less efficient ET, but favoring instead the protein exchange and the turnover of the process. Finally, in diatoms the interaction of the acquired green-type Pc with both Cf and PSI may not yet be optimized.Peer reviewe