Projects / Programmes
Role and relevance of empirical geometric parameters in crystal structure determination of macromolecules for prediction of ligand binding
| Code |
Science |
Field |
Subfield |
| 1.05.00 |
Natural sciences and mathematics |
Biochemistry and molecular biology |
|
| Code |
Science |
Field |
| B120 |
Biomedical sciences |
Molecular biophysics |
| Code |
Science |
Field |
| 1.04 |
Natural Sciences |
Chemical sciences |
structure biology, drug discovery, 3D structures of macromolecules, bioinformatics, database, heterocompound
Researchers (12)
Organisations (3)
Abstract
3-dimensional structures of biological macromolecules are the key to understanding of the chemical basis of physiological processes in the living organisms, yet they are a result of gathering the experimental data and their interpretation. The perfection of crystals of biological macromolecules seldom enables collection of data sets at resolutions which enable determination of individual atomic positions independently from their surroundings. Therefore prior knowledge is used to assure that the resulting structures are chemically and physically reasonable. The notions a) that the structures in the current Protein Data Bank entries are not optimal for use in the ligand binding prediction studies, b) that the extracted statistical parameters from the small molecule database may overcome this problem, and c) that modeling studies may provide better targets for ligand binding than the experimentaly determined structures indicate that there may be systematic inconsistency in the prior knowledge. The bonding parameters in use, which restrain the geometry of biopolymers, have been extracted from the small molecule crystal structures by statiostical approach, however, those for the heterocompounds as well as nonbonding parameters have other sources.
Therefore we plan to investigate the dependance of the crystal structure accuracy from these terms. In particular the nonbonding terms will be address since they effect almost every single macromolecular crystal structure. Re-refining the structrues by using the alreday developed statistical nonbonding parameters from the groups of Klebe (Uni Marburg) and Sali (UCSF), we plan to examine the orgin of the discrepencies between the small and macro molecular worlds and to improve the accuracy of 3D crystal structures deposited in PDB. This will be done by revisting the already published works of collaborating groups and applied and co-developed in a drug discovery project. The results are expected to have an impact on the whole structural biology community. The ultimate outcome of this project, extending beyond its time frame, is an automated procedure for re-refinment of all PDB entries which will be continously updated with the progress of knowledge and technology through the years to come.
The findings will be published in high quality scientific journals. The tools and procedures will be made availabe to the
academic and industrial community via the www interface and as tools for the lab use.
Significance for science
Drug discovery as well as herbicide research strongly depend on the delivery of reliable sources of information such as 3-dimensional structures of drug and herbicide targets and their complexes with drug candidates in development. With this project we aimed to improve the general reliability and accuracy of this information and thereby increase the information content in 3-D structures of macromolecules. The new target function of refinement called Free Kick Maximum Likelihood function (Pražnikar and Turk, 2014) we believe to have made a world wide impact on the science and technology which depends on the results of macromolecular crystallography. The impact of the upgrade of the “prior knowledge” on which the 3-dimensional structure determination of biological macromolecules and their complexes depend upon, is expected upon completion of the work started here. The collaboration with the groups of two world class leading scientists in this area (prof. Andrej Sˇali - University of California San Francisco, California; Prof. Paul Adams - Lawrence Berkeley Lab, Berkeley, California) reflects international importance of this project. Prof. Sˇali is one of the world leading bioinformatic scientist in the area of prediction and modeling of 3-dimensional structures of macromolecules and their complexes and equally renown Prof. Paul Adams PI of the PHENIX project recently involved in development of the parameters of the Chemical Prior knowledge. The collaboration with these groups will raise visibility of our achievements. This project was of interest for the pharmaceutical industry. SME AciesBio has joined the project with the hope that the application of the approaches under development will provide them the edge crucial for the success of their product.
Significance for the country
D. Turk is the third most cited scientist in the field ob biological sciences in Slovenia (approximately 7000 citations, Hirsch index 40). This project is a continuation of his long devotion to software development tools for structural biology which has laid the foundation for his international recognition and reflected in that of Slovenia. The results of this project are of interest for the pharmaceutical industry. SME AciesBio has joined the project with the hope that the application of the approaches under development will provide them the edge crucial for the success of their product.
Most important scientific results
Annual report
2012,
2013,
final report,
complete report on dLib.si
Most important socioeconomically and culturally relevant results
Annual report
2012,
final report,
complete report on dLib.si
