Protein–ligand binding affinity prediction of cyclin‐dependent kinase‐2 inhibitors by dynamically averaged fragment molecular orbital‐based interaction energy

Abstract

Fragment molecular orbital (FMO) method is a powerful computational tool for structure-based drug design, in which protein-ligand interactions can be described by the inter-fragment interaction energy (IFIE) and its pair interaction energy decomposition analysis (PIEDA). Here, we introduced a dynamically averaged (DA) FMO-based approach in which molecular dynamics simulations were used to generate multiple protein-ligand complex structures for FMO calculations. To assess this approach, we examined the correlation between the experimental binding free energies and DA-IFIEs of six CDK2 inhibitors whose net charges are zero. The correlation between the experimental binding free energies and snapshot IFIEs for X-ray crystal structures was R 2 = 0.75. Using the DA-IFIEs, the correlation significantly improved to 0.99. When an additional CDK2 inhibitor with net charge of À1 was added, the DA FMO-based scheme with the dispersion energies still achieved R 2 = 0.99, whereas R 2 decreased to 0.32 employing all the energy terms of PIEDA.

Quantum Chemical Interaction Analysis between SARS-CoV-2 Main Protease and Ensitrelvir Compared with Its Initial Screening Hit

“…In addition, ensitrelvir attractively interacts with Thr24 (Thr25 fragment), Thr25, Thr26 (itself and Leu27 fragments), Met49, Phe140 (Leu141 fragment), Asn142, Ser144, Cys145, Met165, Glu166, Gln189, and five bridging waters. From the short MD simulation, we have confirmed that the inhibitor binding pose is stable to some extent compared with the X-ray crystal structures, while it might be even better to evaluate it with dynamically averaged FMO-based IFIE analysis using the MD snapshot structures . We have registered the FMO calculation data of M pro and inhibitor complexes published in PDB to the FMODB, , and the data are made available to SBDD for researchers worldwide.…”

“…From the short MD simulation, we have confirmed that the inhibitor binding pose is stable to some extent compared with the X-ray crystal structures, while it might be even better to evaluate it with dynamically averaged FMO-based IFIE analysis using the MD snapshot structures. 41 We have registered the FMO calculation data of M pro and inhibitor complexes published in PDB to the FMODB, 27,29 and the data are made available to SBDD for researchers worldwide. These findings are expected to provide creative insights for further improvement of inhibitory potency against M pro and help develop novel inhibitors with SBDD.…”

Probing RNA–Small Molecule Interactions Using Biophysical and Computational Approaches

“…One limitation of performing FMO calculations in the gas phase, as performed in this study, is that the binding affinities of ligands with different net charges cannot be predicted. To overcome this limitation, we are currently testing more theoretically sophisticated approaches, such as the FMO-based Poisson–Boltzmann surface area , and the dynamically averaged FMO approach . Here, we conclude that rational design of RNA binders is possible using FMO, especially after establishing structure–activity relationships.…”

How E-, L-, and P-Selectins Bind to sLex and PSGL-1: A Quantification of Critical Residue Interactions

“…The partition analysis (PA), as implemented in GAMESS, allows us to circumvent this “inconvenience” by allowing arbitrary monomer definitions (called segments in PA to differentiate them from fragments). − The FMO method, in its many flavors, was successfully used to gain insight into complex biomolecular systems. − The choice of DFTB in our work is motivated by the availability of PA only in combination with this self-consistent field (SCF) method. Nevertheless, as recent works show, it may be an appropriate tool for our needs. , Unless indicated differently, all data discussed in this work is from PA based on FMO2-DFTB3/PCM/D3­(BJ)/3ob calculations.…”