Paul D. Adams

This paper designs novel Rubisco variants using protein language models, identifying active candidates with improved CO2/O2 specificity and structural validity.

The paper introduces NEF, a standard for NMR data exchange, and demonstrates its application in structure determination, metabolomics, and ligand screening.

The paper implements a method in CCTBX and Phenix to calculate variable-resolution maps from atomic models, improving accuracy by incorporating local resolution and atomic parameters.

The paper provides a library of 37,000 minimized small molecule geometries for use in macromolecular refinement and molecular dynamics simulations.

The paper characterizes the structural and functional diversity of rubisco by synthesizing and analyzing diverse sequences, revealing a dimeric origin and a novel large rubisco structure.

The paper uses a biosensor-driven strategy to enhance isoprenol production in Pseudomonas putida through combinatorial strain engineering and omics analysis.

AQuaRef uses machine learning to refine protein structures with quantum accuracy at lower computational cost, improving geometric quality and experimental data fit.

The paper develops MultiXray, a Bayesian method for multi-state and multi-condition protein structure modeling using X-ray crystallography data, improving Rfree values in both simulated and experimental cases.

The paper characterizes two GT61 enzymes in Sorghum bicolor, identifies their functions in xylan modification, and identifies a residue critical for sugar donor specificity through structural and biochemical analysis.

The paper examines microbial community diversity in a uranium-contaminated aquifer, finding reduced taxonomic and phylogenetic diversity but stable functional diversity.

This study introduces two methods, FluxRETAP and VAMMPIRE, to improve CRISPRi-mediated gene downregulation for bioproduction by enhancing target identification and multiplexed construct assembly.

This paper introduces a modular polyketide synthase platform for producing diols, amino alcohols, and hydroxyacids using engineered Streptomyces albus strains.

The paper introduces a likelihood-based local docking method for cryo-EM maps, improving speed and sensitivity when component locations are known, implemented in ChimeraX.

This paper engineers Pseudomonas putida for isoprenol production using computational modeling and strain optimization, achieving a titer of 3.5 g/L.

The paper describes a microfluidic system for high-throughput CRISPR-based gene editing and screening, demonstrating its ability to perform parallel genetic modifications in E. coli.

The paper introduces a mosaic bulk-solvent model that improves the fit between crystallographic models and data, enhancing density map quality and solving previously inaccessible problems.

The paper introduces a 3-track network for accurate protein structure and interaction prediction, achieving performance close to DeepMind's CASP14 results and enabling rapid modeling of protein complexes from sequence data.

This paper improves macromolecular structure refinement using Phenix and OPLS3e for better structure and ligand quality in X-ray and cryo-EM data.

The paper identifies an iron-dependent enzyme in plants that completes the lysine catabolism pathway, showing structural and functional conservation across species.

The paper integrates the Amber force field into Phenix for crystallographic refinement, improving model quality through better stereochemistry, fewer clashes, and better hydrogen bonds.

The paper introduces new computational tools for validating cryo-EM maps and atomic models, including methods for resolution estimation, map sharpening, and map analysis.

The paper describes real-space refinement in Phenix for improving cryo-EM models using additional restraints and shows significant model improvement.