Benchmarking calculations of excitonic couplings between bacteriochlorophylls

TL;DR

This paper benchmarks various computational methods for calculating excitonic couplings between bacteriochlorophyll molecules, highlighting the limitations imposed by experimental uncertainties and recommending the electrostatic TrEsp method for its accuracy and efficiency.

Contribution

It provides a comprehensive comparison of approximation techniques for excitonic couplings and offers practical guidelines for their application in biological energy transport studies.

Findings

Crystallographic coordinate uncertainty causes about 20% error in couplings.

Quantum-chemical corrections are often smaller than 20%, questioning their cost-effectiveness.

The electrostatic TrEsp method is recommended for its accuracy and low computational cost.

Abstract

Excitonic couplings between (bacterio)chlorophyll molecules are necessary for simulating energy transport in photosynthetic complexes. Many techniques for calculating the couplings are in use, from the simple (but inaccurate) point-dipole approximation to fully quantum-chemical methods. We compared several approximations to determine their range of applicability, noting that the propagation of experimental uncertainties poses a fundamental limit on the achievable accuracy. In particular, the uncertainty in crystallographic coordinates yields an uncertainty of about 20% in the calculated couplings. Because quantum-chemical corrections are smaller than 20% in most biologically relevant cases, their considerable computational cost is rarely justified. We therefore recommend the electrostatic TrEsp method across the entire range of molecular separations and orientations because its cost is minimal and it generally agrees with quantum-chemical calculations to better than the geometric uncertainty. We also caution against computationally optimizing a crystal structure before calculating couplings, as it can lead to large, uncontrollable errors. Understanding the unavoidable uncertainties can guard against striving for unrealistic precision; at the same time, detailed benchmarks can allow important qualitative questions--which do not depend on the precise values of the simulation parameters--to be addressed with greater confidence about the conclusions.