Why should medicinal chemists use software?
What exactly is a medicinal chemist’s role today? Firstly, let’s define a medicinal chemist’s role – to design and synthesise…
Surflex-QMOD integrates chemical structure and activity data to produce physically-realistic models for binding affinity prediction.
Here, we apply QMOD to a 3D-QSAR benchmark dataset and show broad applicability to a diverse set of targets. Testing new ligands within the QMOD model employs automated flexible molecular alignment, with the model itself defining the optimal pose for each ligand. QMOD performance was compared to that of four approaches that depended on manual alignments (CoMFA, two variations of CoMSIA, and CMF). QMOD showed comparable performance to the other methods on a challenging, but structurally limited, test set.
The QMOD models were also applied to test a large and structurally diverse dataset of ligands from ChEMBL, nearly all of which were synthesized years after those used for model construction. Extrapolation across diverse chemical structures was possible because the method addresses the ligand pose problem and provides structural and geometric means to quantitatively identify ligands within a model’s applicability domain. Predictions for such ligands for the four tested targets were highly statistically significant based on rank correlation.
What exactly is a medicinal chemist’s role today? Firstly, let’s define a medicinal chemist’s role – to design and synthesise…
The agrochemical industry is facing growing challenges around resistance, stringent regulations, and pressures to reduce the time and cost of…
Pairing AI with human expertise We present a novel AI compound optimisation system, designed to include human oversight as a…