Predicting Accurate Lead Structures for Screening Molecular Libraries: A Quantum Crystallographic Approach

Abstract

Optimization of lead structures is crucial for drug discovery. However, the accuracy of such a prediction using the traditional molecular docking approach remains a major concern. Our study demonstrates that the employment of quantum crystallographic approach-counterpoise corrected kernel energy method (KEM-CP) can improve the accuracy by and large. We select human aldose reductase at 0.66 Å, cyclin dependent kinase 2 at 2.0 Å and estrogen receptor β at 2.7 Å resolutions with active site environment ranging from highly hydrophilic to moderate to highly hydrophobic and several of their known ligands. Overall, the use of KEM-CP alongside the GoldScore resulted superior prediction than the GoldScore alone. Unlike GoldScore, the KEM-CP approach is neither environment-specific nor structural resolution dependent, which highlights its versatility. Further, the ranking of the ligands based on the KEM-CP results correlated well with that of the experimental IC50 values. This computationally inexpensive yet simple approach is expected to ease the process of virtual screening of potent ligands, and it would advance the drug discovery research.

Compromise in Docking Power of Liganded Crystal Structures of Mpro SARS-CoV-2 Surpasses 90% Success Rate

“…Lastly, Pham et al 45 report a correlation coefficient between the same variables of 0.74 for a set 11 noncovalent M pro complexes. It should be noted that a direct comparison of IC 50 values with results of molecular docking gives rather a pessimistic outlook, 46,47 with docking being generally recognized as a screening tool useful for identification of potent compounds, when maintaining false-positive and false-negative rates at reasonable threshold. 48 Reliability of scoring functions is usually assessed by four aspects, namely, scoring power, ranking power, docking power, and screening power.…”