Biology subjects

Urzhumtsev, A.

Publications and source records attributed to Urzhumtsev, A..

6 recordsLinked to original sources

bioRxiv2025

DIRECT CALCULATION OF VARIABLE-RESOLUTION MAPS BY FULLY ANALYTIC APPROXIMATIONS TO ATOMIC IMAGES

Crystallographic maps are typically computed as Fourier series using complex-valued structure factors, with a single set of coefficients applied across the entire region, and associating a single resolution value with the whole map. In cryo-electron microscopy, however, experimental maps often have variable local resolution. As a consequence, applying the same procedure to compute model maps for comparison with the respective experimental ones becomes complicate. An alternative strategy involves representing model maps as sums of atomic images. They are oscillatory functions of the distance from the atomic center and depend on atomic displacement parameters and local resolution. To calculate such maps, we propose a stand-alone program which uses the shell-function approximation of atomic images making them analytic functions of all its parameters including the local resolution associated to each atom. SynopsisCrystallographic and cryo electron microscopy maps with variable resolution can be calculated as a sum of analytic shell-function approximations to atomic images using the developed stand-alone python script.

biophysics↗

bioRxiv2022

Direct calculation of cryo EM and crystallographic model maps for real-space refinement

Real-space refinement of atomic models improves them by their fit to experimental scattering electrostatic potential maps in cryo electron microscopy and to electron density maps in crystallography. This procedure has a number of advantages in comparison with reciprocal-space refinement, is complementary to it in crystallographic studies and is the principal technique in cryo EM. An accurate real-space refinement of atomic models can be done by comparison of the model maps, calculated according to the respective theory, with the experimental ones, when the former mimic imperfections of the latter, mainly a limited resolution and an atomic disorder. Calculation of model maps as a sum of contributions of individual atoms means that these contributions - atomic images in the given map - should also be affected by the resolution and positional disorder. This blurs atomic images and surrounds their central peak by Fourier ripples. These ripples can be described by a specially designed function which allows combining both principal effects of map imperfection in an analytic way. The atomic images, at any resolution and with any value of the atomic displacement parameter, can be decomposed into a linear combination of such functions with the precalculated parameter values. As a consequence, each map value becomes an analytic function of atomic parameters including displacement parameter and a local resolution if required. Using the chain rule for the score function which compares the maps, such model results in analytic expressions for its partial derivatives with respect to all atomic parameters allowing an efficient real-space refinement. At the same time, for practical calculations atomic images are cut at some truncation distance, i.e., include a limited number of ripples. This introduced in the model maps errors which are not present in the experimental maps. Due to oscillating behavior of the atomic images, the choice of the value of this truncation distance is not straightforward and discussed in this work. SynopsisA new method is suggested to calculate maps of a limited and eventually inhomogeneous resolution as an analytic function of all atomic parameters, including local resolution.

biophysics↗

bioRxiv2021

A mosaic bulk-solvent model improves density maps and the fit between model and data

Bulk solvent is a major component of bio-macromolecular crystals and therefore contributes significantly to diffraction intensities. Accurate modeling of the bulk-solvent region has been recognized as important for many crystallographic calculations, from computing of R-factors and density maps to model building and refinement. Owing to its simplicity and computational and modeling power, the flat (mask-based) bulk-solvent model introduced by Jiang & Brunger (1994) is used by most modern crystallographic software packages to account for disordered solvent. In this manuscript we describe further developments of the mask-based model that improves the fit between the model and the data and aids in map interpretation. The new algorithm, here referred to as mosaic bulk-solvent model, considers solvent variation across the unit cell. The mosaic model is implemented in the computational crystallography toolbox and can be used in Phenix in most contexts where accounting for bulk-solvent is required. It has been optimized and validated using a sufficiently large subset of the Protein Data Bank entries that have crystallographic data available. SynopsisA mosaic bulk-solvent method models disordered solvent more accurately than current flat bulk solvent model. This improves the fit between the model and the data, improves map quality and allows for the solution of problems previously inaccessible.

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↗

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↗

bioRxiv2018

Real-space refinement in Phenix for cryo-EM and crystallography

This article describes the implementation of real-space refinement in the phenix.real_space_refine program from the Phenix suite. Use of a simplified refinement target function enables fast calculation, which in turn makes it possible to identify optimal data-restraints weight as part of routine refinements with little runtime cost. Refinement of atomic models against low-resolution data benefits from the inclusion of as much additional information as is available. In addition to standard restraints on covalent geometry, phenix.real_space_refine makes use of extra information such as secondary-structure and rotamer-specific restraints, as well as restraints or constraints on internal molecular symmetry. Re-refinement of 385 cryo-EM derived models available in the PDB at resolutions of 6 [A] or better shows significant improvement of models and the fit of these models to the target maps.\n\nSynopsisA description of the implementation of real-space refinement in the phenix.real_space_refine program from the Phenix suite and its application to re-refinement of cryo-EM derived models.

bioinformatics↗