Biology subjects

Liebschner, D.

Publications and source records attributed to Liebschner, D..

3 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↗

bioRxiv2024

Likelihood-based interactive local docking into cryo-EM maps in ChimeraX

The interpretation of cryo-EM maps often includes the docking of known or predicted structures of the components, which is particularly useful when the map resolution is worse than 4 [A]. Although it can be effective to search the entire map to find the best placement of a component, the process can be slow when the maps are large. However, frequently there is a well-founded hypothesis about where particular components are located. In such cases, a local search using a map subvolume will be much faster because the search volume is smaller, and more sensitive because optimizing the search volume for the rotation search step enhances signal-to-noise. A Fourier-space likelihood-based local search approach, based on the previously-published em_placement software, has been implemented in the new emplace_local program. Tests confirm that the local search approach enhances speed and sensitivity of the computations. An interactive graphical interface in the ChimeraX molecular graphics program provides a convenient way to set up and evaluate docking calculations, particularly in defining the part of the map into which the components should be placed. SynopsisLikelihood-based cryo-EM docking using our emplace_local software is faster and more sensitive than our related software, em_placement, when the approximate location of a component is known, and is available conveniently through a plugin to the ChimeraX visualization software.

biophysics↗

bioRxiv2022

Accelerating crystal structure determination with iterative AlphaFold prediction

Experimental structure determination can be accelerated with AI-based structure prediction methods such as AlphaFold. Here we present an automatic procedure requiring only sequence information and crystallographic data that uses AlphaFold predictions to produce an electron density map and a structural model. Iterating through cycles of structure prediction is a key element of our procedure: a predicted model rebuilt in one cycle is used as a template for prediction in the next cycle. We applied this procedure to X-ray data for 215 structures released by the Protein Data Bank in a recent 6-month period. In 87% of cases our procedure yielded a model with at least 50% of C atoms matching those in the deposited models within 2[A]. Predictions from our iterative template-guided prediction procedure were more accurate than those obtained without templates. We suggest a general strategy for macromolecular structure determination that includes AI-based prediction both as a starting point and as a method of model optimization.

biochemistry↗