Exploration and Validation of Force Field Design Protocols through QM-to-MM Mapping

The scale of the parameter optimisation problem in traditional molecular mechanics force field construction means that design of a new force field is a long process, and sub-optimal choices made in the early stages can persist for many generations of the force field. We hypothesise that careful use of quantum mechanics to inform molecular mechanics parameter derivation (QM-to-MM mapping) should be used to significantly reduce the number of parameters that require fitting to experiment and increase the pace of force field development. Here, we design a collection of 15 new protocols for small, organic molecule force field design, and test their accuracy against experimental liquid properties. Our best performing model has only seven fitting parameters, yet achieves mean unsigned errors of just 0.031 g/cm3 and 0.69 kcal/mol in liquid densities and heats of vaporisation, compared to experiment. The software required to derive the designed force fields is freely available at https://github.com/qubekit/QUBEKit.

Molecular Docking and Dynamics Investigations for Identifying Potential Inhibitors of the 3-Chymotrypsin-like Protease of SARS-CoV-2: Repurposing of Approved Pyrimidonic Pharmaceuticals for COVID-19 Treatment

This study demonstrates the inhibitory effect of 42 pyrimidonic pharmaceuticals (PPs) on the 3-chymotrypsin-like protease of SARS-CoV-2 (3CLpro) through molecular docking, molecular dynamics simulations, and free binding energies by means of molecular mechanics–Poisson Boltzmann surface area (MM-PBSA) and molecular mechanics–generalized Born surface area (MM-GBSA). Of these tested PPs, 11 drugs approved by the US Food and Drug Administration showed an excellent binding affinity to the catalytic residues of 3CLpro of His41 and Cys145: uracil mustard, cytarabine, floxuridine, trifluridine, stavudine, lamivudine, zalcitabine, telbivudine, tipiracil, citicoline, and uridine triacetate. Their percentage of residues involved in binding at the active sites ranged from 56 to 100, and their binding affinities were in the range from −4.6 ± 0.14 to −7.0 ± 0.19 kcal/mol. The molecular dynamics as determined by a 200 ns simulation run of solvated docked complexes confirmed the stability of PP conformations that bound to the catalytic dyad and the active sites of 3CLpro. The free energy of binding also demonstrates the stability of the PP–3CLpro complexes. Citicoline and uridine triacetate showed free binding energies of −25.53 and −7.07 kcal/mol, respectively. Therefore, I recommend that they be repurposed for the fight against COVID-19, following proper experimental and clinical validation.

Proofreading experimentally assigned stereochemistry through Q2MM predictions in Pd-catalyzed allylic aminations

The palladium-catalyzed enantioselective allylic substitution by carbon or nitrogen nucleophiles is a key transformation that is particularly useful for the synthesis of bioactive compounds. Unfortunately, the selection of a suitable ligand/substrate combination often requires significant screening effort. Here, we show that a transition state force field (TSFF) derived by the quantum-guided molecular mechanics (Q2MM) method can be used to rapidly screen ligand/substrate combinations. Testing of this method on 77 literature reactions revealed several cases where the computationally predicted major enantiomer differed from the one reported. Interestingly, experimental follow-up led to a reassignment of the experimentally observed configuration. This result demonstrates the power of mechanistically based methods to predict and, where necessary, correct the stereochemical outcome.

Evaluation on the performance of MM/PBSA in nucleic acid-protein systems

The molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method has been widely used in predicting the binding affinity among the ligands, the proteins and the nucleic acids. However, the accuracy of the predicted binding energy by the standard MM/PBSA is not always good, especially in highly charged systems. In this work, we take the protein-nucleic acid complexes as an example, and showed that the use of screening electrostatic energy (instead of coulomb electrostatic energy) in molecular mechanics can greatly improve the performance of MM/PBSA. In particular, the Pearson correlation coefficient of dataset II in the modified MM/PBSA (i.e., screening MM/PBSA) is about 0.52, much better than that (<0.33) in the standard MM/PBSA. Further, we also evaluate the effect of the solute dielectric constant and the salt concentration on the performance of the screening MM/PBSA. The present study highlights the potential power of the screening MM/PBSA for predicting the binding energy in highly charged bio-systems.