Lynx: A Programmatic SAT Solver for the RNA-folding Problem

15th International Conference, Trento, Italy, June 17-20, 2012. ProceedingsThis paper introduces Lynx, an incremental programmatic SAT solver that allows non-expert users to introduce domain-specific code into modern conflict-driven clause-learning (CDCL) SAT solvers, thus enabling users to guide the behavior of the solver. The key idea of Lynx is a callback interface that enables non-expert users to specialize the SAT solver to a class of Boolean instances. The user writes specialized code for a class of Boolean formulas, which is periodically called by Lynx’s search routine in its inner loop through the callback interface. The user-provided code is allowed to examine partial solutions generated by the solver during its search, and to respond by adding CNF clauses back to the solver dynamically and incrementally. Thus, the user-provided code can specialize and influence the solver’s search in a highly targeted fashion. While the power of incremental SAT solvers has been amply demonstrated in the SAT literature and in the context of DPLL(T), it has not been previously made available as a programmatic API that is easy to use for non-expert users. Lynx’s callback interface is a simple yet very effective strategy that addresses this need. We demonstrate the benefits of Lynx through a case-study from computational biology, namely, the RNA secondary structure prediction problem. The constraints that make up this problem fall into two categories: structural constraints, which describe properties of the biological structure of the solution, and energetic constraints, which encode quantitative requirements that the solution must satisfy. We show that by introducing structural constraints on-demand through user provided code we can achieve, in comparison with standard SAT approaches, upto 30x reduction in memory usage and upto 100x reduction in time

Prediction of molecular alignment of nucleic acids in aligned media

Contains fulltext : 35529.pdf (publisher's version ) (Closed access)We demonstrate - using the data base of all deposited DNA and RNA structures aligned in Pf1-medium and RDC refined - that for nucleic acids in a Pf1-medium the electrostatic alignment tensor can be predicted reliably and accurately via a simple and fast calculation based on the gyration tensor spanned out by the phosphodiester atoms. The rhombicity is well predicted over its full range from 0 to 0.66, while the alignment tensor orientation is predicted correctly for rhombicities up to ca. 0.4, for larger rhombicities it appears to deviate somewhat more than expected based on structural noise and measurement error. This simple analytical approach is based on the Debye-Huckel approximation for the electrostatic interaction potential, valid at distances sufficiently far away from a poly-ionic charged surface, a condition naturally enforced when the charge of alignment medium and solute are of equal sign, as for nucleic acids in a Pf1-phage medium. For the usual salt strengths and nucleic acid sizes, the Debye-Huckel screening length is smaller than the nucleic acid size, but large enough for the collective of Debye-Huckel spheres to encompass the whole molecule. The molecular alignment is then purely electrostatic, but it's functional form is under these conditions similar to that for steric alignment. The proposed analytical expression allows for very fast calculation of the alignment tensor and hence RDCs from the conformation of the nucleic acid molecule. This information provides opportunities for improved structure determination of nucleic acids, including better assessment of dynamics in (multi-domain) nucleic acids and the possibility to incorporate alignment tensor prediction from shape directly into the structure calculation process. The procedures are incorporated into MATLAB scripts, which are available on request