Taking into account formula's structure is extremely important for making SAT-solvers scalable. One of the problems here is that a SAT solver with conflict clause learning creates its own structure (induced by conflicts) that may have little to do with the real structure of the formula. In particular, a single resolution is "meaningless" in a SAT-solver based on the DPLL procedure unless it is used in deriving a conflict clause. We describe a SAT-algorithm called IBP (Interpolation with Boundary Point elimination) that is not conflict driven and so builds a proof from "individual" resolution operations. We show that IBP compares favorably with state- of-the-art SAT-solvers on narrow formulas. We also argue that IBP can be viewed as a generalization of the conflict clause generation procedure and so can be used to advance the state of the art in SAT-solvers based on the DPLL procedure.