BACKGROUND: We present a C++ class library for Monte Carlo simulation of molecular systems, including proteins in solution. The design is generic and highly modular, enabling multiple developers to easily implement additional features. The statistical mechanical methods are documented by extensive use of code comments that - subsequently - are collected to automatically build a web-based manual. RESULTS: We show how an object oriented design can be used to create an intuitively appealing coding framework for molecular simulation. This is exemplified in a minimalistic C++ program that can calculate protein protonation states. We further discuss performance issues related to high level coding abstraction. CONCLUSION: C++ and the Standard Template Library (STL) provide a high-performance platform for generic molecular modeling. Automatic generation of code documentation from inline comments has proven particularly useful in that no separate manual needs to be maintained.

Institute of Organic Chemistry and Biochemistry The Academy of Sciences of the Czech Republic Flemingovo nam 2 CZ 16610 Prague 6 Czech Republic

Zobrazit více v PubMed

Metropolis NA, Rosenbluth AW, Rosenbluth MN, Teller A, Teller E. Equation of State Calculations by Fast Computing Machines. J Chem Phys. 1953;21:1087–1097. doi: 10.1063/1.1699114. DOI

Kamberaj H, Helms V. Monte Carlo simulation of biomolecular systems with BIOMCSIM. Computer Physics Communications. 2001;141:375–402. doi: 10.1016/S0010-4655(01)00434-9. DOI

Carlsson F, Malmsten M, Linse P. Monte Carlo Simulations of Lysozyme Self-Association in Aqueous Solution. J Phys Chem. 2001;105:12189–12195.

Hu J, Ma A, Dinner AR. Monte Carlo simulations of biomolecules: The MC module in CHARMM. J Comp Chem. 2006;27:203–216. doi: 10.1002/jcc.20327. PubMed DOI

Frenkel D, Smit B. Understanding Molecular Simulation. San Diego: Academic Press; 1996.

Stroustrup B. The C++ Programming Language. 3. Boston: Addison-Wesley; 1997.

MDAPI

Object-Oriented Model for Probing Assemblages of Atoms

Berendsen H, Spoel D, Drunen R. GROMACS: A message passing parallel molecular dynamics implementation. Comp Phys Comm. 1995;91:43–56. doi: 10.1016/0010-4655(95)00042-E. DOI

Veldhuizen T. Expression Templates. C++ Report. 1995;7:26–31.

Meloni S, Rosati M, Colombo L. Efficient particle labeling in atomistic simulations. J Chem Phys. 2007;126:121102. doi: 10.1063/1.2719690. PubMed DOI

Dagum L, Menon R. OpenMP: An Industry-Standard API for Shared-Memory Programming. IEEE Computational Science and Engineering. 1998;05:46–55. doi: 10.1109/99.660313. DOI

Doxygen

Hill TL. An Introduction to Statistical Thermodynamics. New York: Dover Publications Inc; 1986.

Lund M. PhD Thesis: Electrostatic Interactions in and between bio-molecules. Lund, Sweden: Lund University; 2006.

Lund M, Jönsson B. On the charge regulation of proteins. Biochemistry. 2005;44:5722–5727. doi: 10.1021/bi047630o. PubMed DOI

Humphrey W, Dalke A, Schulten K. VMD – Visual Molecular Dynamics. J Mol Graphics. 1996;14:27-8–33-8. PubMed

Tanford C, Roxby R. Interpretation of protein titration curves. Application to lysozyme. Biochemistry. 1972;11:2192–2198. doi: 10.1021/bi00761a029. PubMed DOI

Lund M, Jonsson B, Woodward CE. Implications of a high dielectric constant in proteins. J Chem Phys. 2007;126:225103. doi: 10.1063/1.2741543. PubMed DOI

POV-Ray – The Persistence of Vision Raytracer

Salt Effects on Caffeine across Concentration Regimes