Photoacoustic tomography (PAT) is an emerging ultrasound-mediated biophotonic imaging modality that has great potential for many biomedical imaging applications. In many practical implementations of PAT, the photoacoustic signals are recorded over an aperture that does not enclose the object, which results in a limitedview tomographic reconstruction problem. When conventional reconstruction algorithms are applied to limitedview measurement data, the resulting images can contain severe image artifacts and distortions. To circumvent such artifacts, we exploit a priori information about the locations of boundaries within the object (optical absorption function) to improve the fidelity of the reconstructed images. Such boundary information can be inferred, for example, from a co-registered B-mode ultrasound image or other adjunct imaging study. We develop and implement an iterative reconstruction algorithm that exploits a priori object information in the form of support constraints. We demonstrate that the developed iterative reconstruction algorithm produces images with reduced artifact levels as compared to those produced by a conventional PAT reconstruction algorithm.