Biology subjects

Waller, M. P.

Publications and source records attributed to Waller, M. P..

5 recordsLinked to original sources

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↗

bioRxiv2024

Studies of vegetation and land-use history on Bodmin Moor: pollen investigations from Leskernick

Details of pollen investigations that accompanied archaeological excavations (of a Late Neolithic/Early Bronze ritual complex and a Middle to Late Bronze Age settlement) at Leskernick Hill Bodmin Moor, undertaken between 1995 and 1999, are presented. Samples were collected both from a nearby off-site location and from a variety of on-site contexts. The off-site peat profile contains a major hiatus. The earliest assemblage corresponds to the Late Neolithic/Early Bronze Age and indicates a largely open landscape in which both pasture and arable agriculture were practiced. Sedimentation recommenced during the early Medieval period and the pollen record shows the varying degrees to which grazing and arable agriculture were practiced up until the recent past. These phases do not accord well with historic evidence from the wider area, though other pollen diagrams from the region also record a wetter phase found at Leskernick (and dated here to c. 1400-1600 AD). Evidence obtained during the archaeological excavations suggests the ritual complex was abandoned early and the pollen records indicate this was accompanied by a period of low grazing pressure. Samples from the interiors of huts/houses dated to the Middle Bronze Age are dominated by Poaceae pollen suggesting relatively intense human activity. The assemblages from beneath the boundary walls around the settlement probably cover a considerable time period, in part as a result of rebuilding and the reuse of stone. With high Calluna vulgaris values they appear largely to reflect the stony nature of the environment in which the settlement was established. PreambleThis pre-print details the results of pollen investigations that accompanied archaeological excavations at Leskernick Hill, Bodmin Moor, undertaken between 1995 and 1999. A draft manuscript was prepared for publication in 2005, but the monograph in which it was to be included outlining the excavations, has not been forthcoming. Details of the archaeological/historic features present at Leskernick can be found in Johnson and Rose (1994) and Herring et al. (2008), while Bender et al. (2007) provides information on the work that these investigations formed part of. The 2005 manuscript is reproduced here with a new introduction and revisions incorporating information from the later publications.

ecology↗

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↗

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↗