Upgrading nirmatrelvir to inhibit SARS-CoV-2 Mpro via DeepFrag and free energy calculations.

The first oral drug for the treatment of COVID-19, Paxlovid, has been authorized; however, nirmatrelvir, a major component of the drug, is reported to be associated with some side effects. Moreover, the appearance of many novel variants raises concerns about drug resistance, and designing new potent inhibitors to prevent viral replication is thus urgent. In this context, using a hybrid approach combining machine learning (ML) and free energy simulations, 6 compounds obtained by modifying nirmatrelvir were proposed to bind strongly to SARS-CoV-2 Mpro.

Effective estimation of the inhibitor affinity of HIV-1 protease a modified LIE approach.

The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses. Computer-aided drug design (CADD) would enhance the discovery of new therapies, through which the estimation of ligand-binding affinity is critical to predict the most efficient inhibitor. A time-consuming binding free energy method would reduce the usefulness of CADD.

The influences of E22Q mutant on solvated 3Aβ peptide: A REMD study.

The residue E22 plays a critical role in the aggregation process of Amyloid beta (Aβ) peptides. The effect of E22Q mutant on the shapes of the solvated Aβ trimer is clarified using a replica exchange molecular dynamics (REMD) simulation employing ∼20.6 μs of MD simulations with 48 disparate replicas.