MOLECULAR TAILORING APPROACH: TOWARDS PC-BASED AB INITIO TREATMENT OF LARGE MOLECULES

The development of a fragmentation-based scheme, viz. molecular tailoring approach (MTA) for ab initio computation of one-electron properties and geometry optimization is described. One-electron properties such as the molecular electrostatic potential (MESP), molecular electron density (MED), and dipole moments are computed by synthesizing the density matrix (DM) of the parent molecule from DMs of its small overlapping fragments. The electron density obtained via MTA was found to be typically within 0.5% of its actual counterpart, while maximum errors of about 2% were noticed in the case of the dipole moment and MESP distribution. An attempt is made to develop MTA-based geometry optimization that involves picking relevant energy gradients from fragment self-consistent field (SCF) calculations, bypassing the CPU and memory extensive SCF step of the complete molecule. This is based on the observation that the MTA gradients mimic the actual ones fairly well. As the calculations on individual fragments are mutually independent, this algorithm is amenable to large-scale parallelization and has been extended to a distributed setup of PCs. The code developed is put to test on γ-cyclodextrin, taxol, and a small albumin-binding protein (1prb) for one-electron properties. Further, molecules such as γ-cyclodextrin, taxol, a silicalite, and 1prb are subjected to MTA-based geometry optimization, on a PC cluster. The results indicate a favorable speedup of two to three times over the actual computations in the initial phase of optimization. Furthermore, it enables computations otherwise not possible on a PC. Preliminary results indicate similar savings with sustained accuracy even for large molecules at the level of Moller–Plesset second order perturbation (MP2) theory.