Photo of Prof Dan Rigden

Prof Dan Rigden BA, PhD

Professor of Protein Bioinformatics Biochemistry


    AMPLE: Molecular Replacement using unconventional protein models
    Ensembles search models of different sizes (magenta) solve protein crystal structures (cartoon)
    Ensembles search models of different sizes (magenta) solve protein crystal structures (cartoon)

    Our program AMPLE clusters and truncates sets of protein models to efficiently solve crystal structures by Molecular Replacement. Initially, it was designed to process cheaply obtained ab initio models from ROSETTA. More recently we have found it to work exceptionally well with NMR ensemble inputs, and for solving the structures of coiled-coil proteins. Having secured 5-year funding from BBSRC as part of the CCP4 grant renewal, we are currently exploring several new lines of research including application to membrane proteins.

    Protein structure modelling
    A model of a DUF2086 protein
    A model of a DUF2086 protein

    I have a broad interest in prediction of protein structures and complexes, whether by conventional homology modelling, ab initio methods or the recently arrived contract-driven algorithms. This feeds directly into AMPLE (above), often helps predict function (below) but has many other applications including interpreting the consequences of single nucleotide polymorphisms.

    Protein function prediction
    Convergently evolved calcium-binding motifs
    Convergently evolved calcium-binding motifs

    I am interested in using diverse bioinformatics methods to shed light on function of unannotated sequences - 'hypothetical proteins', Domains of Unknown Function' and the like. This often starts by detecting distant evolutionary relationships with sensitive database searches, but often requires input from, for example, gene context, domain architectures, and structural bioinformatics.

    Research Grants
    • Studentship Agreement between University of Liverpool and Diamond Light Source Ltd
    • Facilitating access to advanced Molecular Replacement pipelines via CCP4i2, CCP4 online and CCP4cloud
    • Identification of novel double-stranded RNA elements in developing antibiotic resistance in the agricultural environment
    • Identification and evaluation of algal sulphatransferases for enzymatic polysaccharide modifications
    • Wellcome Trust Vacationship Miss Kiani A Jeacock
    • A Simkin Studentship
    • Molecular function in post-genome biology (MOLFUN).
    • The genotypic and phenotypic impacts of Shiga toxin encoding bacteriophage interactions with their host cells: consequences for food borne zoonoses
    • Dealkylation of plant sterols during utilization in invertebrates
    • Tools for motif recognition in fungi
    • CCP4 Grant Renewal 2014-2019: Question-driven crystallographic data collection and advanced structure solution
    • Ab initio modelling for X-ray crystal structure solution
    • The structure-function relationship of anti-microbial peptides approached by ab initio protein modelling.
    • Development of lead compounds for trypanocidal drugs based on inhibitors targeted against parasite glycolysis (TRYGLYCHEMO).
    • Exploring covariance-based models for protein crystal structure solution with AMPLE.
    • The titin myofilament as emerging factor in cardiomyopathy
    Research Collaborations

    Prof. Michael Clague


    Dr Michael Ginger

    External: The University of Lancaster

    Dr Martyn Winn

    External: STFC

    Research collaboration

    Prof Paul Michels

    External: Université catholique de Louvain

    Dr Heather Allison


    Dr Michael Galperin

    External: National Center for Biotechnology Information

    Dr Mark Caddick


    Prof Dave Fernig


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