This paper addresses the problem of optimally designing molecular products. A systematic analysis framework is presented for transforming a class of optimal computer-aided molecular design problems with nonlinear structure-property functionalities into equivalent mixed-integer linear (MILP) problems. While, in general, it is not possible to solve the original problem formulation for the best molecular design with mathematical certainty, the equivalent (MILP) reformulation can be solved efficiently with existing solvers and identify not only the best, but also the second, third, etc., best molecular designs. Two alternative design objectives are considered : (i) minimization of the scaled deviation of design properties from some target values, property matching, and (ii) minimization/maximization of a single property subject to lower and upper bounds on the rest of the properties, property optimization. The framework is applied to the design of polymers where thermophysical and mechanical properties are estimated using group contribution methods; Three case studies, including comparisons with existing, methods, illustrate the computational efficiency and feasibility of the proposed methodology.