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Salinisation of soil is associated with urban pollution, industrial development and rising sea level. Understanding how high salinity is managed at the plant cellular level is vital to increase sustainable farming output. Previous studies focus on plant stress responses under salinity tolerance. Yet, there is limited knowledge about the mechanisms involved from stress state until the recovery state; our research aims to close this gap. By using the most tolerance genotype (SS1-14) and the most susceptible genotype (SS2-18), comparative physiological, metabolome and post-harvest assessments were performed to identify the underlying mechanisms for salinity stress recovery in plant cells. The up-regulation of glutamine, asparagine and malonic acid were found in recovered-tolerant genotype, suggesting a role in the regulation of panicle branching and spikelet formation for survival. Rice could survive up to 150 mM NaCl (∼15 ds/m) with declined of production rate 5–20% ranged from tolerance to susceptible genotype. This show that rice farming may still be viable on the high saline affected area with the right selection of salt-tolerant species, including glycophytes. The salt recovery biomarkers identified in this study and the adaption underlined could be empowered to address salinity problem in rice field.
Nyuk Ling Ma; Su Datt Lam; Wan Afifudeen Che Lah; Aziz Ahmad; Jörg Rinklebe; Christian Sonne; Wanxi Peng. Integration of environmental metabolomics and physiological approach for evaluation of saline pollution to rice plant. Environmental Pollution 2021, 286, 117214 .
AMA StyleNyuk Ling Ma, Su Datt Lam, Wan Afifudeen Che Lah, Aziz Ahmad, Jörg Rinklebe, Christian Sonne, Wanxi Peng. Integration of environmental metabolomics and physiological approach for evaluation of saline pollution to rice plant. Environmental Pollution. 2021; 286 ():117214.
Chicago/Turabian StyleNyuk Ling Ma; Su Datt Lam; Wan Afifudeen Che Lah; Aziz Ahmad; Jörg Rinklebe; Christian Sonne; Wanxi Peng. 2021. "Integration of environmental metabolomics and physiological approach for evaluation of saline pollution to rice plant." Environmental Pollution 286, no. : 117214.
Coronavirus-like organisms have been previously identified in Arthropod ectoparasites (such as ticks and unfed cat flea). Yet, the question regarding the possible role of these arthropods as SARS-CoV-2 passive/biological transmission vectors is still poorly explored. In this study, we performed in silico structural and binding energy calculations to assess the risks associated with possible ectoparasite transmission. We found sufficient similarity between ectoparasite ACE and human ACE2 protein sequences to build good quality 3D-models of the SARS-CoV-2 Spike:ACE complex to assess the impacts of ectoparasite mutations on complex stability. For several species (e.g., water flea, deer tick, body louse), our analyses showed no significant destabilisation of the SARS-CoV-2 Spike:ACE complex, suggesting these species would bind the viral Spike protein. Our structural analyses also provide structural rationale for interactions between the viral Spike and the ectoparasite ACE proteins. Although we do not have experimental evidence of infection in these ectoparasites, the predicted stability of the complex suggests this is possible, raising concerns of a possible role in passive transmission of the virus to their human hosts.
Su Lam; Paul Ashford; Sandra Díaz-Sánchez; Margarita Villar; Christian Gortázar; José de la Fuente; Christine Orengo. Arthropod Ectoparasites Have Potential to Bind SARS-CoV-2 via ACE. Viruses 2021, 13, 708 .
AMA StyleSu Lam, Paul Ashford, Sandra Díaz-Sánchez, Margarita Villar, Christian Gortázar, José de la Fuente, Christine Orengo. Arthropod Ectoparasites Have Potential to Bind SARS-CoV-2 via ACE. Viruses. 2021; 13 (4):708.
Chicago/Turabian StyleSu Lam; Paul Ashford; Sandra Díaz-Sánchez; Margarita Villar; Christian Gortázar; José de la Fuente; Christine Orengo. 2021. "Arthropod Ectoparasites Have Potential to Bind SARS-CoV-2 via ACE." Viruses 13, no. 4: 708.
Alternative splicing can expand the diversity of proteomes. Homologous mutually exclusive exons (MXEs) originate from the same ancestral exon and result in polypeptides with similar structural properties but altered sequence. Why would some genes switch homologous exons and what are their biological impact? Here, we analyse the extent of sequence, structural and functional variability in MXEs and report the first large scale, structure-based analysis of the biological impact of MXE events from different genomes. MXE-specific residues tend to map to single domains, are highly enriched in surface exposed residues and cluster at or near protein functional sites. Thus, MXE events are likely to maintain the protein fold, but alter specificity and selectivity of protein function. This comprehensive resource of MXE events and their annotations is available at: http://gene3d.biochem.ucl.ac.uk/mxemod/. These findings highlight how small, but significant changes at critical positions on a protein surface are exploited in evolution to alter function.
Su Datt Lam; M. Madan Babu; Jonathan Lees; Christine A. Orengo. Biological impact of mutually exclusive exon switching. PLOS Computational Biology 2021, 17, e1008708 .
AMA StyleSu Datt Lam, M. Madan Babu, Jonathan Lees, Christine A. Orengo. Biological impact of mutually exclusive exon switching. PLOS Computational Biology. 2021; 17 (3):e1008708.
Chicago/Turabian StyleSu Datt Lam; M. Madan Babu; Jonathan Lees; Christine A. Orengo. 2021. "Biological impact of mutually exclusive exon switching." PLOS Computational Biology 17, no. 3: e1008708.
CATH (https://www.cathdb.info) identifies domains in protein structures from wwPDB and classifies these into evolutionary superfamilies, thereby providing structural and functional annotations. There are two levels: CATH-B, a daily snapshot of the latest domain structures and superfamily assignments, and CATH+, with additional derived data, such as predicted sequence domains, and functionally coherent sequence subsets (Functional Families or FunFams). The latest CATH+ release, version 4.3, significantly increases coverage of structural and sequence data, with an addition of 65,351 fully-classified domains structures (+15%), providing 500 238 structural domains, and 151 million predicted sequence domains (+59%) assigned to 5481 superfamilies. The FunFam generation pipeline has been re-engineered to cope with the increased influx of data. Three times more sequences are captured in FunFams, with a concomitant increase in functional purity, information content and structural coverage. FunFam expansion increases the structural annotations provided for experimental GO terms (+59%). We also present CATH-FunVar web-pages displaying variations in protein sequences and their proximity to known or predicted functional sites. We present two case studies (1) putative cancer drivers and (2) SARS-CoV-2 proteins. Finally, we have improved links to and from CATH including SCOP, InterPro, Aquaria and 2DProt.
Ian Sillitoe; Nicola Bordin; Natalie Dawson; Vaishali P Waman; Paul Ashford; Harry M Scholes; Camilla S M Pang; Laurel Woodridge; Clemens Rauer; Neeladri Sen; Mahnaz Abbasian; Sean Le Cornu; Su Datt Lam; Karel Berka; Ivana Hutařová Varekova; Radka Svobodova; Jon Lees; Christine A Orengo. CATH: increased structural coverage of functional space. Nucleic Acids Research 2020, 49, D266 -D273.
AMA StyleIan Sillitoe, Nicola Bordin, Natalie Dawson, Vaishali P Waman, Paul Ashford, Harry M Scholes, Camilla S M Pang, Laurel Woodridge, Clemens Rauer, Neeladri Sen, Mahnaz Abbasian, Sean Le Cornu, Su Datt Lam, Karel Berka, Ivana Hutařová Varekova, Radka Svobodova, Jon Lees, Christine A Orengo. CATH: increased structural coverage of functional space. Nucleic Acids Research. 2020; 49 (D1):D266-D273.
Chicago/Turabian StyleIan Sillitoe; Nicola Bordin; Natalie Dawson; Vaishali P Waman; Paul Ashford; Harry M Scholes; Camilla S M Pang; Laurel Woodridge; Clemens Rauer; Neeladri Sen; Mahnaz Abbasian; Sean Le Cornu; Su Datt Lam; Karel Berka; Ivana Hutařová Varekova; Radka Svobodova; Jon Lees; Christine A Orengo. 2020. "CATH: increased structural coverage of functional space." Nucleic Acids Research 49, no. D1: D266-D273.
SARS-CoV-2 has a zoonotic origin and was transmitted to humans via an undetermined intermediate host, leading to infections in humans and other mammals. To enter host cells, the viral spike protein (S-protein) binds to its receptor, ACE2, and is then processed by TMPRSS2. Whilst receptor binding contributes to the viral host range, S-protein:ACE2 complexes from other animals have not been investigated widely. To predict infection risks, we modelled S-protein:ACE2 complexes from 215 vertebrate species, calculated changes in the energy of the complex caused by mutations in each species, relative to human ACE2, and correlated these changes with COVID-19 infection data. We also analysed structural interactions to better understand the key residues contributing to affinity. We predict that mutations are more detrimental in ACE2 than TMPRSS2. Finally, we demonstrate phylogenetically that human SARS-CoV-2 strains have been isolated in animals. Our results suggest that SARS-CoV-2 can infect a broad range of mammals, but few fish, birds or reptiles. Susceptible animals could serve as reservoirs of the virus, necessitating careful ongoing animal management and surveillance.
Su Datt Lam; Nicola Bordin; Vaishali P Waman; Harry M Scholes; Paul Ashford; Neeladri Sen; Lucy van Dorp; Clemens Rauer; Natalie L Dawson; Camilla Sm Pang; Mahnaz Abbasian; Ian Sillitoe; Sarah Jl Edwards; Franca Fraternali; Jonathan G Lees; Joanne M Santini; Christine A Orengo. SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals. 2020, 1 .
AMA StyleSu Datt Lam, Nicola Bordin, Vaishali P Waman, Harry M Scholes, Paul Ashford, Neeladri Sen, Lucy van Dorp, Clemens Rauer, Natalie L Dawson, Camilla Sm Pang, Mahnaz Abbasian, Ian Sillitoe, Sarah Jl Edwards, Franca Fraternali, Jonathan G Lees, Joanne M Santini, Christine A Orengo. SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals. . 2020; ():1.
Chicago/Turabian StyleSu Datt Lam; Nicola Bordin; Vaishali P Waman; Harry M Scholes; Paul Ashford; Neeladri Sen; Lucy van Dorp; Clemens Rauer; Natalie L Dawson; Camilla Sm Pang; Mahnaz Abbasian; Ian Sillitoe; Sarah Jl Edwards; Franca Fraternali; Jonathan G Lees; Joanne M Santini; Christine A Orengo. 2020. "SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals." , no. : 1.
Diosgenin (DIO), a steroidal sapogenin with high therapeutic potential, has been shown to exhibit a myriad of pharmacologically significant properties and is commonly used as a template for synthesizing steroidal drugs. The efficacy of bioactive compounds as a potential drug depends mainly upon their interaction with proteins in the circulatory system. Therefore, the interaction of DIO with the major carrier proteins in humans, i.e. human serum albumin (HSA) and α1-acid glycoprotein (AAG), was characterized using multispectroscopic and molecular docking techniques. Analysis of fluorescence enhancement data showed intermediate binding affinity for both DIO–HSA and DIO–AAG interactions. Circular dichroism spectral results revealed minimal conformational alterations in HSA upon DIO binding, but the effect on AAG was more significant. Competitive ligand displacement results suggested that DIO does not bind strongly to the main drug binding sites of HSA. However, DIO was found to favor binding to subdomain IB of HSA based on molecular docking data. For AAG, the binding location of DIO was determined for the two variants of AAG (A and F1*S variants) using molecular docking. For variant A, the binding site was situated in lobes I and II of the central binding pocket of the protein, while in variant F1*S, DIO was docked to a cleft on the protein surface. Hydrophobic interactions and van der Waals forces were mainly responsible for complexation between DIO and both proteins. Additionally, there was involvement of hydrogen bonding between DIO and both variants of AAG, but not between DIO and HSA.
Khairul Azreena Bakar; Su Datt Lam; Hasidah Mohd Sidek; Shevin Rizal Feroz. Characterization of the interaction of diosgenin with human serum albumin and α1-acid glycoprotein using biophysical and bioinformatic tools. Journal of Molecular Liquids 2020, 306, 112865 .
AMA StyleKhairul Azreena Bakar, Su Datt Lam, Hasidah Mohd Sidek, Shevin Rizal Feroz. Characterization of the interaction of diosgenin with human serum albumin and α1-acid glycoprotein using biophysical and bioinformatic tools. Journal of Molecular Liquids. 2020; 306 ():112865.
Chicago/Turabian StyleKhairul Azreena Bakar; Su Datt Lam; Hasidah Mohd Sidek; Shevin Rizal Feroz. 2020. "Characterization of the interaction of diosgenin with human serum albumin and α1-acid glycoprotein using biophysical and bioinformatic tools." Journal of Molecular Liquids 306, no. : 112865.
Genome3D (https://www.genome3d.eu) is a freely available resource that provides consensus structural annotations for representative protein sequences taken from a selection of model organisms. Since the last NAR update in 2015, the method of data submission has been overhauled, with annotations now being ‘pushed’ to the database via an API. As a result, contributing groups are now able to manage their own structural annotations, making the resource more flexible and maintainable. The new submission protocol brings a number of additional benefits including: providing instant validation of data and avoiding the requirement to synchronise releases between resources. It also makes it possible to implement the submission of these structural annotations as an automated part of existing internal workflows. In turn, these improvements facilitate Genome3D being opened up to new prediction algorithms and groups. For the latest release of Genome3D (v2.1), the underlying dataset of sequences used as prediction targets has been updated using the latest reference proteomes available in UniProtKB. A number of new reference proteomes have also been added of particular interest to the wider scientific community: cow, pig, wheat and mycobacterium tuberculosis. These additions, along with improvements to the underlying predictions from contributing resources, has ensured that the number of annotations in Genome3D has nearly doubled since the last NAR update article. The new API has also been used to facilitate the dissemination of Genome3D data into InterPro, thereby widening the visibility of both the annotation data and annotation algorithms.
Ian Sillitoe; Antonina Andreeva; Tom L Blundell; Daniel W A Buchan; Robert D Finn; Julian Gough; David Jones; Lawrence A Kelley; Typhaine Paysan-Lafosse; Su Datt Lam; Alexey G Murzin; Arun Prasad Pandurangan; Gustavo A Salazar; Marcin J Skwark; Michael Sternberg; Sameer Velankar; Christine Orengo. Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation. Nucleic Acids Research 2019, 48, D314 -D319.
AMA StyleIan Sillitoe, Antonina Andreeva, Tom L Blundell, Daniel W A Buchan, Robert D Finn, Julian Gough, David Jones, Lawrence A Kelley, Typhaine Paysan-Lafosse, Su Datt Lam, Alexey G Murzin, Arun Prasad Pandurangan, Gustavo A Salazar, Marcin J Skwark, Michael Sternberg, Sameer Velankar, Christine Orengo. Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation. Nucleic Acids Research. 2019; 48 (D1):D314-D319.
Chicago/Turabian StyleIan Sillitoe; Antonina Andreeva; Tom L Blundell; Daniel W A Buchan; Robert D Finn; Julian Gough; David Jones; Lawrence A Kelley; Typhaine Paysan-Lafosse; Su Datt Lam; Alexey G Murzin; Arun Prasad Pandurangan; Gustavo A Salazar; Marcin J Skwark; Michael Sternberg; Sameer Velankar; Christine Orengo. 2019. "Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation." Nucleic Acids Research 48, no. D1: D314-D319.
Alternative splicing (AS) has been suggested as one of the major processes expanding the diversity of proteomes in multicellular organisms. Mutually exclusive exons (MXE) provide one form of AS that is less likely to disrupt protein structure and is over-represented in the proteome compared to other forms of AS. We used domain structure information from the CATH classification to perform a systematic structural analysis of the effects of MXE splicing in high quality animal genomes (e.g. human, fly, mouse and 2 fishes) and we were able to annotate approximately 50% of MXE events with structural information. For those MXE events which can be mapped to a structure, we found that although embedded in domains, they were strongly enriched in surface exposed residues. We also demonstrated that the variable residues between splicing events lie close to known and/or predicted functional sites. We present some examples of MXE events in proteins that have important roles in cells. This work presents the first large scale systematic study of the structural/functional effects of MXE splicing using predominantly domain based modelling and functional annotation tools. Our study supports and expands on previous work in this field and helps to build a picture of how MXE events facilitate evolution of new functions.
Su Datt Lam; Christine Orengo; Jonathan Lees. Protein structure and function analyses to understand the implication of mutually exclusive splicing. 2018, 292813 .
AMA StyleSu Datt Lam, Christine Orengo, Jonathan Lees. Protein structure and function analyses to understand the implication of mutually exclusive splicing. . 2018; ():292813.
Chicago/Turabian StyleSu Datt Lam; Christine Orengo; Jonathan Lees. 2018. "Protein structure and function analyses to understand the implication of mutually exclusive splicing." , no. : 292813.
Salinity threat is estimated to reduce global rice production by 50%. Comprehensive analysis of the physiological and metabolite changes in rice plants from salinity stress (i.e. tolerant versus susceptible plants) is important to combat higher salinity conditions. In this study, we screened a total of 92 genotypes and selected the most salinity tolerant line (SS1-14) and most susceptible line (SS2-18) to conduct comparative physiological and metabolome inspections. We demonstrated that the tolerant line managed to maintain their water and chlorophyll content with lower incidence of sodium ion accumulation. We also examined the antioxidant activities of these lines: production of ascorbate peroxidase (APX) and catalase (CAT) were significantly higher in the sensitive line while superoxide dismutase (SOD) was higher in the tolerant line. Partial least squares discriminant analysis (PLS-DA) score plots show significantly different response for both lines after the exposure to salinity stress. In the tolerant line, there was an upregulation of non-polar metabolites and production of sucrose, GABA and acetic acid, suggesting an important role in salinity adaptation. In contrast, glutamine and putrescine were noticeably high in the susceptible rice. Coordination of different strategies in tolerant and susceptible lines show that they responded differently after exposure to salt stress. These findings can assist crop development in terms of developing tolerance mechanisms for rice crops.
Nyuk Ling Ma; Wan Afifudeen Che Lah; Nisrin Abd. Kadir; Mohamad Mustaqim; Zaidah Rahmat; Aziz Ahmad; Su Datt Lam; Mohd Razi Ismail. Susceptibility and tolerance of rice crop to salt threat: Physiological and metabolic inspections. PLoS ONE 2018, 13, e0192732 .
AMA StyleNyuk Ling Ma, Wan Afifudeen Che Lah, Nisrin Abd. Kadir, Mohamad Mustaqim, Zaidah Rahmat, Aziz Ahmad, Su Datt Lam, Mohd Razi Ismail. Susceptibility and tolerance of rice crop to salt threat: Physiological and metabolic inspections. PLoS ONE. 2018; 13 (2):e0192732.
Chicago/Turabian StyleNyuk Ling Ma; Wan Afifudeen Che Lah; Nisrin Abd. Kadir; Mohamad Mustaqim; Zaidah Rahmat; Aziz Ahmad; Su Datt Lam; Mohd Razi Ismail. 2018. "Susceptibility and tolerance of rice crop to salt threat: Physiological and metabolic inspections." PLoS ONE 13, no. 2: e0192732.
Gene3D (http://gene3d.biochem.ucl.ac.uk) is a database of globular domain annotations for millions of available protein sequences. Gene3D has previously featured in the Database issue of NAR and here we report a significant update to the Gene3D database. The current release, Gene3D v16, has significantly expanded its domain coverage over the previous version and now contains over 95 million domain assignments. We also report a new method for dealing with complex domain architectures that exist in Gene3D, arising from discontinuous domains. Amongst other updates, we have added visualization tools for exploring domain annotations in the context of other sequence features and in gene families. We also provide web-pages to visualize other domain families that co-occur with a given query domain family.
Tony E Lewis; Ian Sillitoe; Natalie Dawson; Su Datt Lam; Tristan Clarke; David Lee; Christine Orengo; Jonathan Lees. Gene3D: Extensive prediction of globular domains in proteins. Nucleic Acids Research 2017, 46, D435 -D439.
AMA StyleTony E Lewis, Ian Sillitoe, Natalie Dawson, Su Datt Lam, Tristan Clarke, David Lee, Christine Orengo, Jonathan Lees. Gene3D: Extensive prediction of globular domains in proteins. Nucleic Acids Research. 2017; 46 (D1):D435-D439.
Chicago/Turabian StyleTony E Lewis; Ian Sillitoe; Natalie Dawson; Su Datt Lam; Tristan Clarke; David Lee; Christine Orengo; Jonathan Lees. 2017. "Gene3D: Extensive prediction of globular domains in proteins." Nucleic Acids Research 46, no. D1: D435-D439.
Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, reviews recent developments and describes resources dedicated to large-scale comparative modelling of genome sequences. The value of subclustering protein domain superfamilies to guide the template-selection process is investigated. Some recent cases in which structural modelling has aided experimental work to determine very large macromolecular complexes are also cited.
Su Datt Lam; Sayoni Das; Ian Sillitoe; Christine Orengo. An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences. Acta Crystallographica Section D Structural Biology 2017, 73, 628 -640.
AMA StyleSu Datt Lam, Sayoni Das, Ian Sillitoe, Christine Orengo. An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences. Acta Crystallographica Section D Structural Biology. 2017; 73 (8):628-640.
Chicago/Turabian StyleSu Datt Lam; Sayoni Das; Ian Sillitoe; Christine Orengo. 2017. "An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences." Acta Crystallographica Section D Structural Biology 73, no. 8: 628-640.
This chapter describes the generation of the data in the CATH-Gene3D online resource and how it can be used to study protein domains and their evolutionary relationships. Methods will be presented for: comparing protein structures, recognizing homologs, predicting domain structures within protein sequences, and subclassifying superfamilies into functionally pure families, together with a guide on using the webpages.
Natalie L. Dawson; Ian Sillitoe; Jonathan G. Lees; Su Datt Lam; Christine A. Orengo. CATH-Gene3D: Generation of the Resource and Its Use in Obtaining Structural and Functional Annotations for Protein Sequences. Chromosomal Mutagenesis 2017, 1558, 79 -110.
AMA StyleNatalie L. Dawson, Ian Sillitoe, Jonathan G. Lees, Su Datt Lam, Christine A. Orengo. CATH-Gene3D: Generation of the Resource and Its Use in Obtaining Structural and Functional Annotations for Protein Sequences. Chromosomal Mutagenesis. 2017; 1558 ():79-110.
Chicago/Turabian StyleNatalie L. Dawson; Ian Sillitoe; Jonathan G. Lees; Su Datt Lam; Christine A. Orengo. 2017. "CATH-Gene3D: Generation of the Resource and Its Use in Obtaining Structural and Functional Annotations for Protein Sequences." Chromosomal Mutagenesis 1558, no. : 79-110.
Gene3D http://gene3d.biochem.ucl.ac.uk is a database of domain annotations of Ensembl and UniProtKB protein sequences. Domains are predicted using a library of profile HMMs representing 2737 CATH superfamilies. Gene3D has previously featured in the Database issue of NAR and here we report updates to the website and database. The current Gene3D (v14) release has expanded its domain assignments to ∼20 000 cellular genomes and over 43 million unique protein sequences, more than doubling the number of protein sequences since our last publication. Amongst other updates, we have improved our Functional Family annotation method. We have also improved the quality and coverage of our 3D homology modelling pipeline of predicted CATH domains. Additionally, the structural models have been expanded to include an extra model organism (Drosophila melanogaster). We also document a number of additional visualization tools in the Gene3D website.
Su Datt Lam; Natalie L. Dawson; Sayoni Das; Ian Sillitoe; Paul Ashford; David Lee; Sonja Lehtinen; Christine A. Orengo; Jonathan G. Lees. Gene3D: expanding the utility of domain assignments. Nucleic Acids Research 2015, 44, D404 -D409.
AMA StyleSu Datt Lam, Natalie L. Dawson, Sayoni Das, Ian Sillitoe, Paul Ashford, David Lee, Sonja Lehtinen, Christine A. Orengo, Jonathan G. Lees. Gene3D: expanding the utility of domain assignments. Nucleic Acids Research. 2015; 44 (D1):D404-D409.
Chicago/Turabian StyleSu Datt Lam; Natalie L. Dawson; Sayoni Das; Ian Sillitoe; Paul Ashford; David Lee; Sonja Lehtinen; Christine A. Orengo; Jonathan G. Lees. 2015. "Gene3D: expanding the utility of domain assignments." Nucleic Acids Research 44, no. D1: D404-D409.