The official release of GROMACS 2018 is now available.
GROMACS is one of the major software packages for the simulation of biological macromolecules.
Highlights from this update include:-
- PME long-ranged interactions can now run on a single GPU, which means many fewer CPU cores are needed for good performance.
Optimized SIMD support for recent CPU architectures: AMD Zen, Intel Skylake-X and Skylake Xeon-SP.
The AWH (Accelerated Weight Histogram) method is now supported, which is an adaptive biasing method used for overcoming free energy barriers and calculating free energies (see http://dx.doi.org/10.1063/1.4890371).
- A new dual-list dynamic-pruning algorithm for the short-ranged interactions, that uses an inner and outer list to permit a longer-lived outer list, while doing less work overall and making runs less sensitive to the choice of the “nslist” parameter.
- A physical validation suite is added, which runs a series of short simulations, to verify the expected statistical properties, e.g. of energy distributions between the simulations, as a sensitive test that the code correctly samples the expected ensemble.
- Conserved quantities are computed and reported for more integration schemes - now including all Berendsen and Parrinello-Rahman schemes.
I see that SeeSAR now supports a parallelized 'real' fragment growing.
SeeSAR is a software tool for interactive, visual compound prioritisation as well as compound evolution. Structure-based design work ideally supports a multi-parameter optimization to maximise the likelihood of success, rather than affinity alone. Having the relevant parameters at hand in combination with real-time visual computer assistance in 3D is one of the strengths of SeeSAR. Stimulating exploration with SeeSAR, we have embarked on pursuing a new cheminformatics compute paradigm of "Propose & Validate".
You can download SeeSAR here and use it for free for 7 days.
I just stumbled across a fascinating series of lectures. These are recordings of the live discussions behind the ongoing software development led by Stephen Wolfram.
Of particular interest might be the discussion on incorporating chemistry into the Wolfram language.
A recent publication DOI describes an update to the popular molecule viewer UCSF Chimera
UCSF ChimeraX is next-generation software for the visualization and analysis of molecular structures, density maps, 3D microscopy, and associated data. It addresses challenges in the size, scope, and disparate types of data attendant with cutting-edge experimental methods, while providing advanced options for high-quality rendering (interactive ambient occlusion, reliable molecular surface calculations, etc.) and professional approaches to software design and distribution.
The application can be downloaded here http://www.rbvi.ucsf.edu/chimerax/download.html
It is important to note that ChimeraX is not backward compatible with Chimera and does not read Chimera session files. It has been tested on MacOS X 10.12. The ChimeraX user interface is implemented in Qt, offering a native-like look and feel on each platform. ChimeraX is largely implemented using Python, an interpreted programming language. To manipulate these very large datasets interactively, ChimeraX uses memory-efficient data structures combined with high-performance algorithms implemented in C++. MacroMolecular Crystallographic Interchange Format (mmCIF) is the preferred format for atomic data in ChimeraX, mmCIF replaces the aged and more limited PDB format and offers a number of advantages.