Daniel John Rigden

A validation approach for RNA structures based on deep-learning 3D-structure predictions

This paper extends a protein structure validation method to RNA, showing it can detect errors in low-resolution structures where map-based methods fail.

reactifpTM: an accessible reimplementation of actifpTM

reactifpTM reimplements actifpTM to calculate interface quality scores using standard outputs from model prediction software, showing strong correlation with actifpTM on a PDB dataset.

Phosphorylation at S345 Converts HIF-2α from a Transcription Factor to an RNA binding protein

This study shows that phosphorylation at S345 converts HIF-2α from a transcription factor to an RNA-binding protein, altering its function in hypoxia response.

The promise of AlphaFold for gene structure annotation

This study uses AlphaFold 3 scores to assess gene model quality in three species, finding they strongly favor curated models and suggest combining scores from multiple tools improves accuracy.

OpenAc4C: A gateway to decode the landscape, regulation and pathogenesis of N4-acetylcytidine (ac4C) epitranscriptome

OpenAc4C compiles and analyzes ac4C epitranscriptome data from 33 species, identifying 536,745 ac4C sites and 4,766 pathogenic variants, and provides a web-based platform for exploration.

ANUBI: A Platform for Affinity Optimization of Proteins and Peptides in Drug Design

ANUBI optimizes protein and peptide drug candidates by simulating sequence space and binding affinity calculations, improving target binding efficiency and reducing costs.

Capturing α-synuclein polymorphism with AlphaFold 3 and rivals

This paper evaluates AlphaFold 3 and other methods in predicting α-synuclein polymorphs using a reference set of known structures and finds they can generate fibril-like models, though performance varies with template use.

From paleness to albinism: Contribution of OCA2 exon 10 skipping to hypopigmentation

The paper investigates how variants in OCA2 exon 10 affect splicing and pigmentation, showing that some variants increase exon skipping and contribute to hypopigmentation.

Predicting Protein Crystal Solvent Content from Patterson Maps Using Machine Learning

This study uses machine learning to predict protein crystal solvent content from Patterson maps, achieving over 50% error reduction compared to existing methods.

The role of Akkermansia muciniphila sulfatases in colonic mucinutilisation

This study investigates the role of Akkermansia muciniphila sulfatases in colonic mucin utilization, revealing unique adaptations compared to Bacteroides species.

AlphaFold-driven discovery of ORP-PIP phosphatase interactions using new generation confidence scores

The paper uses AlphaFold models to identify conserved ORP-PIP phosphatase interactions and predict functionally relevant protein-lipid interfaces.

AlphaFold 3-enabled in silico exploration of PGAM1 interactions in cancer

This study uses AlphaFold 3 to model how phosphorylation of PGAM1 at Y119 enables PEP binding, enhancing its enzymatic activity in cancer metabolism.

AlphaFold 2, but not AlphaFold 3, predicts confident but unrealistic beta-solenoid structures for repeat proteins

The paper evaluates AlphaFold 2's performance on repeat proteins, finding it predicts confident but unrealistic beta-solenoid structures, unlike other methods.

ABCFold: easier running and comparison of AlphaFold 3, Boltz-1 and Chai-1

ABCFold simplifies running and comparing AlphaFold 3, Boltz-1, and Chai-1 for protein structure prediction with standardized input and unified result handling.

m6AConquer: a Data Resource for Unified Quantification and Integration of m6A Detection Techniques

m6AConquer provides a unified framework for quantifying and integrating m6A detection techniques, improving data consistency and biological relevance across methods.

Investigating Medin Cleavage Accessibility in MfgE8: Conformational Insights Derived from Molecular Dynamics Simulations and AlphaFold2 Models

This study uses molecular dynamics simulations and AlphaFold2 models to investigate MfgE8 conformations and how they affect medin cleavage site accessibility.

In the AlphaFold era, when is experimental phasing of protein crystals still required?

The paper assesses how many protein structures still require experimental phasing when using AlphaFold 2 models, finding that most can be solved with Molecular Replacement.

Using deep learning predictions reveals a large number of register errors in PDB deposits

The paper identifies thousands of register errors in PDB structures using deep learning predictions and shows corrections improve refinement statistics.

Deep-learning protein structure predictions suggest likely molecular functions for three uncharacterised polytopic membrane proteins from the P. falciparum apicoplast

The paper uses AlphaFold2 to predict structures of three uncharacterized apicoplast proteins and suggests their potential molecular functions as transporters.

Deep Learning-based structural and functional annotation of Pandoravirus hypothetical proteins

The paper uses deep learning to predict structures and functions of hypothetical proteins in Pandoraviruses, identifying some functional roles but finding many remain unclear.

CASP15 cryoEM protein and RNA targets: refinement and analysis using experimental maps

The paper evaluates CASP15 cryoEM predictions using density maps, showing high accuracy but challenges in side-chain positioning and loop modeling.

Structural Insights into Pink-eyed Dilution Protein (Oca2)

This study uses computational structural biology to reveal the topology and function of Oca2, showing it is a Na+/dicarboxylate symporter with a unique structure and potential role in melanosomal trafficking.

Using deep learning predictions of inter-residue distances for model validation

The paper introduces validation methods using deep learning-predicted inter-residue distances to detect and correct sequence register errors in protein models.

m6A-TSHub: unveiling the context-specific m6A methylation and m6A-affecting mutations in 23 human tissues

The paper introduces m6A-TSHub, a platform that provides m6A methylation sites and mutations across 23 human tissues and 25 tumor conditions, enabling tissue-specific analysis of m6A regulation.

Slice'N'Dice: Maximising the value of predicted models for structural biologists

SliceNDice improves Molecular Replacement by splitting and repositioning predicted structural models to enhance accuracy in domain orientations.

MrParse: Finding homologues in the PDB and the EBI AlphaFold database for Molecular Replacement and more

MrParse streamlines Molecular Replacement by consolidating homologue searches and rankings from PDB and EBI AlphaFold, using eLLG and structural predictions.

Identification of unknown proteins in X-ray crystallography and cryo-EM

The paper presents an automated pipeline to identify protein sequences from cryo-EM and crystallographic data, demonstrating its application on an unknown snake venom protein.

Assessing the utility of CASP14 models for molecular replacement

This paper evaluates CASP14 models for molecular replacement using a new metric, reLLG, which is independent of diffraction data and shows AlphaFold2 models outperform others.

In silico prediction of structure and function for a large family of transmembrane proteins that includes human Tmem41b

The paper uses structural bioinformatics to predict the structure and function of Tmem41b and its homologues, identifying them as potential transporters with H+ antiporter activity.

Helical ensembles out-perform ideal helices in Molecular Replacement

This paper introduces helical ensembles as improved search models for molecular replacement, achieving a 30% increase in solutions and faster convergence compared to ideal helices.