  Under correlation-type conditions, we derive an upper bound of order $(\log
n)/n$ for the average Kolmogorov distance between the distributions of weighted
sums of dependent summands and the normal law. The result is based on improved
concentration inequalities on high-dimensional Euclidean spheres. Applications
are illustrated on the example of log-concave probability measures.
