Biology subjects

Moriarty, N. W.

Publications and source records attributed to Moriarty, N. W..

9 recordsLinked to original sources

bioRxiv2025

Validated ligand geometries for macromolecular refinement restraints and molecular mechanics force fields

In macromolecular structure refinement the low observation-to-parameter ratio and the lack of high-resolution data is countered by using a priori information in the form of restraints. Having accurate geometries of the chemical entities in the sample is paramount for generating accurate chemical restraints and, therefore, accurate macromolecular structures. In particular, it is desirable to have accurate restraints for known and novel ligand entities. Quantum Mechanics (QM) can minimise the energy of a ligand by adjusting its geometry, and these geometries can be used to generate restraints macromolecular refinement. We describe here a library of 37,000 small molecules extracted from the Chemical Components Dictionary in the Protein Data Bank and minimized by density functional QM. The library includes restraint files for use in crystallography or cryo-EM refinement, along with files suitable for molecular dynamics simulation. Because the geometries are validated, the restraints library provides users with both functional restraints and minimised geometries. This work also provides procedures for generating new and accurate restraints.

molecular biology↗

bioRxiv2025

Structure of active methyl-CoM reductase, Earth's main methane producer

Our work reveals the structure of the active state of Methyl-Coenzyme M Reductase (MCR), the key and rate-limiting enzyme in biological methane formation. We find large differences between the active Ni(I) and inactive Ni(II) proteins and provide insight into how nature makes and breaks the C-H bond of methane. The Ni(II)-F430 center in inactive MCR contains four planar nitrogen ligands, a lower axial glutamine oxo, and an upper axial thiolate. The Ni(I)-enzyme replaces the axial ligands with a single water. The one-electron redox change results in movement of the Ni ion and upward swing of the {beta}-lactam ring in the tetrapyrrole coupled to a domino-like protein quake through second sphere residues, inter-subunit interactions, a substrate tunnel, affecting even the dimensions of the unit cell. These structural changes lead Ni(I)-MCR to release a charge clamp that, in the Ni(II) state, locks down substrate Coenzyme B. Determining the Ni(I)-MCR structure required development of rigorous anaerobic crystallographic techniques. Validation of the MCR redox state was accomplished by in-line and parallel spectroscopic and unit cell analyses. This structure has large implications for developing technologies to limit methane emissions and efficiently produce biofuels. Methodology described here will enhance structural biology for other oxygen-sensitive enzymes.

biochemistry↗

bioRxiv2024

AQuaRef: Machine learning accelerated quantum refinement of protein structures

Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical restraints, which, in addition to being limited to known chemical entities, do not include meaningful noncovalent interactions relying solely on nonbonded repulsions. Quantum mechanical (QM) calculations could alleviate these issues but are too expensive for large molecules. We present a novel AI-enabled Quantum Refinement (AQuaRef) based on AIMNet2 neural network potential mimicking QM at substantially lower computational costs. By refining 41 cryo-EM and 30 X-ray structures, we show that this approach yields atomic models with superior geometric quality compared to standard techniques, while maintaining an equal or better fit to experimental data. Notably, AQuaRef aids in determining proton positions, as illustrated in the challenging case of short hydrogen bonds in the parkinsonism-associated human protein DJ-1 and its bacterial homolog YajL.

biochemistry↗

bioRxiv2022

Optimal clustering for quantum refinement of biomolecular structures: Q|R#4

Quantum refinement (Q|R) of crystallographic or cryo-EM derived structures of biomolecules within the Q|R project aims at using ab initio computations instead of library-based chemical restraints. An atomic model refinement requires the calculation of the gradient of the objective function. While it is not a computational bottleneck in classic refinement it is a roadblock if the objective function requires ab initio calculations. A solution to this problem adopted in Q|R is to divide the molecular system into manageable parts and do computations for these parts rather than using the whole macromolecule. This work focuses on the validation and optimization of the automatic divide-and-conquer procedure developed within the Q|R project. Also, we propose an atomic gradient error score that can be easily examined with common molecular visualization programs. While the tool is designed to work within the Q|R setting the error score can be adapted to similar fragmentation methods. The gradient testing tool presented here allows a priori determination of the computationally efficient strategy given available resources for the potentially time-expensive refinement process. The procedure is illustrated using a peptide and small protein models considering different quantum mechanical (QM) methodologies from Hartree-Fock, including basis set and dispersion corrections, to the modern semi-empirical method from the GFN-xTB family. The results obtained provide some general recommendations for the reliable and effective quantum refinement of larger peptides and proteins.

biochemistry↗

bioRxiv2020

Real-space quantum-based refinement for cryo-EM: Q|R#3

Electron cryo-microscopy (cryo-EM) is fast becoming a major competitor to X-ray crystallography especially for large structures that are difficult or impossible to crystallize. While recent spectacular technology improvements are leading to significantly higher resolution of three-dimensional reconstructions, the average quality of cryo-EM maps is still on the low-resolution end of the range compared to crystallography. A long-standing challenge for atomic model refinement has been the production of stereochemically meaningful models for this resolution regime. Here we demonstrate how including accurate model geometry restraints derived from ab initio quantum-chemical calculations (HF-D3/6-31G) can improve the refinements of an example structure (chain A of 3j63). The robustness of the procedure is tested for additional structures with up to 7k atoms (3a5x, and chain C of 5fn5) by means of the less expensive semi-empirical (GFN1-xTB) model. Necessary algorithms enabling real-space quantum refinement are implemented in the latest version of qr.refine and are described herein. SynopsisThe implementation of quantum-based real-space refinement in qr.refine is described.

bioinformatics↗

bioRxiv2020

A global Ramachandran score identifies protein structures with unlikely stereochemistry

Ramachandran plots report the distribution of the ({varphi}, {Psi}) torsion angles of the protein backbone and are one of the best quality metrics of experimental structure models. Typically, validation software reports the number of residues belonging to "outlier", "allowed" and "favored" regions. While "zero unexplained outliers" can be considered the current "gold standard", this can be misleading if deviations from expected distributions, even within the favored region, are not considered. We therefore revisited the Ramachandran Z-score (Rama-Z), a quality metric introduced more than two decades ago, but underutilized. We describe a re-implementation of the Rama-Z score in the Computational Crystallography Toolbox along with a new algorithm to estimate its uncertainty for individual models; final implementations are available both in Phenix and in PDB-REDO. We discuss the interpretation of the Rama-Z score and advocate including it in the validation reports provided by the Protein Data Bank. We also advocate reporting it alongside the outlier/allowed/favored counts in structural publications.

biophysics↗

bioRxiv2019

Including Crystallographic Symmetry in Quantum-based Refinement: Q|R#2

Three-dimensional structure models refined using low-resolution data from crystallographic or electron cryo-microscopy experiments can benefit from high quality restraints derived from quantum chemical methods. However, non-periodic atom-centered quantum chemistry codes do not inherently account for nearest neighbor interactions of crystallographic symmetry related copies in a satisfactory way. Herein, we have included these nearest neighbor effects in our model by expanding to a super-cell, and then truncating the super-cell to only include residues from neighboring cells that are interacting with the asymmetric unit. In this way our fragmentation approach can adequately and efficiently include the nearest neighbor effects. We have shown previously that a moderately sized X-ray structure can be treated with quantum methods if a fragmentation approach was applied. In this study, we partition a target protein (4gif) into a number of large fragments. The use of large fragments (typically hundreds of atoms) is tractable when a GPU based package such as TeraChem is employed or cheaper (semi-empirical) methods are used. We run the QM calculations at the HF-D3/6-31G level. We compare and contrast the models refined using a recently developed semi-empirical method (GFN2-xTB). To validate the refinement procedure for a non-P1 structure, we use a standard set of crystallographic metrics. We show the robustness of our implementation by refining 13 additional protein models across multiple space-groups and present the summary of the refinement metrics.\n\nSynopsisC-terminal coiled-coil domain of transient receptor potential channel TRPP3 in the P321 space group (PDB code: 4gif) is re-refined with restraints from quantum chemistry using Hartree-Fock theory.

bioinformatics↗

bioRxiv2019

Improved chemistry restraints for crystallographic refinement by integrating the Amber force field into Phenix

The refinement of biomolecular crystallographic models relies on geometric restraints to help address the paucity of experimental data typical in these experiments. Limitations in these restraints can degrade the quality of the resulting atomic models. Here we present an integration of the full all-atom Amber molecular dynamics force field into Phenix crystallographic refinement, which enables a more complete modeling of biomolecular chemistry. The advantages of the force field include a carefully derived set of torsion angle potentials, an extensive and flexible set of atom types, Lennard-Jones treatment of non-bonded interactions and a full treatment of crystalline electrostatics. The new combined method was tested against conventional geometry restraints for over twenty-two thousand protein structures. Structures refined with the new method show substantially improved model quality. On average, Ramachandran and rotamer scores are somewhat better; clash scores and MolProbity scores are significantly improved; and the modelling of electrostatics leads to structures that exhibit more, and more correct, hydrogen bonds than those refined with traditional geometry restraints. We find in general that model improvements are greatest at lower resolutions, prompting plans to add the Amber target function to real-space refinement for use in electron cryo-microscopy. This work opens the door to the future development of more advanced applications such as Amber-based ensemble refinement, quantum mechanical representation of active sites and improved geometric restraints for simulated annealing.\n\nIMPORTANTthis document contains embedded data - to preserve data integrity, please ensure where possible that the IUCr Word tools (available from http://journals.iucr.org/services/docxtemplate/) are installed when editing this document.\n\nSynopsisThe full Amber force field has been integrated into Phenix as an alternative refinement target. With a slight loss in speed, it achieves improved stereochemistry, fewer steric clashes and better hydrogen bonds.

molecular biology↗

bioRxiv2018

New tools for the analysis and validation of Cryo-EM maps and atomic models

Recent advances in the field of electron cryo-microscopy (cryo-EM) have resulted in a rapidly increasing number of atomic models of bio-macromolecules solved using this technique and deposited in the Protein Data Bank and the Electron Microscopy Data Bank. Similar to macromolecular crystallography, validation tools for these models and maps are required. While some of these validation tools may be borrowed from crystallography, new methods specifically for cryo-EM validation are required. We discuss new computational methods and tools implemented in Phenix, including d99 to estimate resolution, phenix.auto_sharpen to improve maps, and phenix.mtriage to analyze cryo-EM maps. We suggest that cryo-EM half-maps and masks are deposited to facilitate evaluation and validation of cryo-EM derived atomic models and maps. We also present the application of these tools to deposited cryo-EM atomic models and maps.

bioinformatics↗