Victor S. Lamzin

Bio: Victor S. Lamzin is an academic researcher from European Bioinformatics Institute. The author has contributed to research in topics: Active site & Formate dehydrogenase. The author has an hindex of 46, co-authored 144 publications receiving 12203 citations. Previous affiliations of Victor S. Lamzin include Russian Academy of Sciences.

Automated protein model building combined with iterative structure refinement.

Abstract: In protein crystallography, much time and effort are often required to trace an initial model from an interpretable electron density map and to refine it until it best agrees with the crystallographic data. Here, we present a method to build and refine a protein model automatically and without user intervention, starting from diffraction data extending to resolution higher than 2.3 A and reasonable estimates of crystallographic phases. The method is based on an iterative procedure that describes the electron density map as a set of unconnected atoms and then searches for protein-like patterns. Automatic pattern recognition (model building) combined with refinement, allows a structural model to be obtained reliably within a few CPU hours. We demonstrate the power of the method with examples of a few recently solved structures.

Automated macromolecular model building for X-ray crystallography using ARP/wARP version 7.

Abstract: ARP/wARP is a software suite to build macromolecular models in X-ray crystallography electron density maps. Structural genomics initiatives and the study of complex macromolecular assemblies and membrane proteins all rely on advanced methods for 3D structure determination. ARP/wARP meets these needs by providing the tools to obtain a macromolecular model automatically, with a reproducible computational procedure. ARP/wARP 7.0 tackles several tasks: iterative protein model building including a high-level decision-making control module; fast construction of the secondary structure of a protein; building flexible loops in alternate conformations; fully automated placement of ligands, including a choice of the best-fitting ligand from a 'cocktail'; and finding ordered water molecules. All protocols are easy to handle by a nonexpert user through a graphical user interface or a command line. The time required is typically a few minutes although iterative model building may take a few hours.

Automated refinement of protein models.

Abstract: An automated refinement procedure (ARP) for protein models is proposed, and its convergence properties discussed. It is comparable to the iterative least-squares minimization/difference Fourier synthesis approach for small molecules. ARP has been successfully applied to three proteins, and for two of them resulted in models very similar to those obtained by conventional least-squares refinement and rebuilding with FRODO. In real time ARP is about ten times faster than conventional refinement. In its present form ARP requires high (2.0 A or better) resolution data, which should be of high quality and a starting protein model having about 75% of the atoms in roughly the correct position. For the third protein at 2.4 A resolution, ARP was significantly less powerful but nevertheless gave definite improvement, in the density map at least.

ARP/wARP and automatic interpretation of protein electron density maps.

Abstract: Publisher Summary This chapter presents phase improvement, coupled with automated map interpretation and model building, as one unified process within the framework of the automated refinement procedure (ARP/wARP) software suite. ARP/wARP is an experimental hypothesis-generating and testing procedure for placing atoms in the most likely places (according to density) and using graph-searching combined with geometric comparisons against expected stereochemical parameters to determine the most likely mainchain fragments. ARP/wARP is a software suite (copyrighted by the European Molecular Biology Laboratory) based on the paradigm of viewing model building and refinement as one unified procedure for optimizing phase estimates. The current version ARP/wARP 6.0, released in July 2002, works with density recognition-driven procedures for placing and removing atoms and therefore is limited to diffraction data extending to about 2.5 A. The iterative cycles of density modeling by the placement of atoms, unrestrained refinement of their parameters, automated model building, and restrained refinement of the hybrid model provide a powerful means of phase refinement.

ARP/wARP and molecular replacement

Abstract: The aim of ARP/wARP is improved automation of model building and refinement in macromolecular crystallography. Once a molecular-replacement solution has been obtained, it is often tedious to refine and rebuild the initial (search) model. ARP/wARP offers three options to automate that task to varying extents: (i) autobuilding of a completely new model based on phases calculated from the molecular-replacement solution, (ii) updating of the initial model by atom addition and deletion to obtain an improved map and (iii) docking of a structure onto a new (or mutated) sequence, followed by rebuilding and refining the side chains in real space. A few examples are presented where ARP/wARP made a considerable difference in the speed of structure solution and/or made possible refinement of otherwise difficult or uninterpretable maps. The resolution range allowing complete autobuilding of protein structures is currently 2.0 A, but for map improvement considerable advances over more conventional refinement techniques are evident even at 3.2 A spacing.

A short history of SHELX

Abstract: An account is given of the development of the SHELX system of computer programs from SHELX-76 to the present day. In addition to identifying useful innovations that have come into general use through their implementation in SHELX, a critical analysis is presented of the less-successful features, missed opportunities and desirable improvements for future releases of the software. An attempt is made to understand how a program originally designed for photographic intensity data, punched cards and computers over 10000 times slower than an average modern personal computer has managed to survive for so long. SHELXL is the most widely used program for small-molecule refinement and SHELXS and SHELXD are often employed for structure solution despite the availability of objectively superior programs. SHELXL also finds a niche for the refinement of macromolecules against high-resolution or twinned data; SHELXPRO acts as an interface for macromolecular applications. SHELXC, SHELXD and SHELXE are proving useful for the experimental phasing of macromolecules, especially because they are fast and robust and so are often employed in pipelines for high-throughput phasing. This paper could serve as a general literature citation when one or more of the open-source SHELX programs (and the Bruker AXS version SHELXTL) are employed in the course of a crystal-structure determination.

Features and development of Coot.

Abstract: Coot is a molecular-graphics application for model building and validation of biological macromolecules. The program displays electron-density maps and atomic models and allows model manipulations such as idealization, real-space refinement, manual rotation/translation, rigid-body fitting, ligand search, solvation, mutations, rotamers and Ramachandran idealization. Furthermore, tools are provided for model validation as well as interfaces to external programs for refinement, validation and graphics. The software is designed to be easy to learn for novice users, which is achieved by ensuring that tools for common tasks are `discoverable' through familiar user-interface elements (menus and toolbars) or by intuitive behaviour (mouse controls). Recent developments have focused on providing tools for expert users, with customisable key bindings, extensions and an extensive scripting interface. The software is under rapid development, but has already achieved very widespread use within the crystallographic community. The current state of the software is presented, with a description of the facilities available and of some of the underlying methods employed.

PHENIX: a comprehensive Python-based system for macromolecular structure solution

Abstract: Macromolecular X-ray crystallography is routinely applied to understand biological processes at a molecular level. How­ever, significant time and effort are still required to solve and complete many of these structures because of the need for manual interpretation of complex numerical data using many software packages and the repeated use of interactive three-dimensional graphics. PHENIX has been developed to provide a comprehensive system for macromolecular crystallo­graphic structure solution with an emphasis on the automation of all procedures. This has relied on the development of algorithms that minimize or eliminate subjective input, the development of algorithms that automate procedures that are traditionally performed by hand and, finally, the development of a framework that allows a tight integration between the algorithms.

Phaser crystallographic software

Abstract: Phaser is a program for phasing macromolecular crystal structures by both molecular replacement and experimental phasing methods. The novel phasing algorithms implemented in Phaser have been developed using maximum likelihood and multivariate statistics. For molecular replacement, the new algorithms have proved to be significantly better than traditional methods in discriminating correct solutions from noise, and for single-wavelength anomalous dispersion experimental phasing, the new algorithms, which account for correlations between F+ and F−, give better phases (lower mean phase error with respect to the phases given by the refined structure) than those that use mean F and anomalous differences ΔF. One of the design concepts of Phaser was that it be capable of a high degree of automation. To this end, Phaser (written in C++) can be called directly from Python, although it can also be called using traditional CCP4 keyword-style input. Phaser is a platform for future development of improved phasing methods and their release, including source code, to the crystallographic community.

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