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Updated: Jan 18, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Computationally Efficient Yet Quantitatively Accurate Scaled MP2 Protocols for the Prediction of Weak Interaction
Luis Soriano-Agueda1, Anaid Flores2, Paulino Zeron1,2
1Departamento de Física y Química Teórica, Facultad de Química, Universidad Nacional Autónoma de México, Cd. Universitaria, 04510 Ciudad de Mexico, Mexico.
None:
In this study, we introduce a set of novel computational strategies based on second-order Mo̷ller-Plesset perturbation theory (MP2), enhanced through acceleration techniques, such as the resolution of the identity (RI). These approaches are further refined via spin-component scaling (SCS), following Grimme's methodology, and are specifically calibrated for the quantitatively accurate prediction of weak interaction energiesinteractions that play a critical role in biological systems. Among the developed methods, three variants exhibit outstanding performance, surpassing the accuracy of several state-of-the-art, nondynamical electronic structure techniques. Benchmarking against a comprehensive data set of 274 dimerization energies, computed at the CCSD-(T)/CBS level of theory, reveals that these models deliver quantitatively accurate interaction energies. In particular, the RIJCOSX-SCS-MP2BWI‑DZ method, employing uniquely optimized scaling parameters, demonstrates exceptional accuracy (errors below 1 kcal/mol) while maintaining computational efficiency superior to widely used hybrid and meta-GGA density functional approximations (DFAs). This method reliably captures a range of biologically relevant interactions, including π-π stacking between nucleotide base pairs, halogen bonding, and dissociation energy profiles, showcasing its robustness and predictive power. Given its accuracy, efficiency, and versatility, RI-SCS-MP2BWI‑DZ, RIJK-SCS-MP2BWI‑DZ, and RIJCOSX-SCS-MP2BWI‑DZ emerge as promising and reliable alternatives for modeling weak interactions in complex biological environments.
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