## 2 Methods and Materials
### ADMET Prediction  
The co-crystallized ligand and the hits from the molecular docking and the receptor-based hopping were subjected to ADMET calculations using ADMET PredictorTM 10.3.0.7 machine-learning models [42]. The ADMET risk scores were predicted for the compounds. The ADMET risk score is a combination of three risks (_Absn_Risk_, _CYP_Risk_, and _Tox_Risk_) as well as two more that touch on potential pharmacokinetic problems: _hum_fup_% (fraction unbound) and V\({}_{\rm d}\) (steady-state volume of distribution). There are 20 rules that contribute to the three risk models [42]. Simulations Plus considered a World Drug Index (WDI) reference set that contained 2260 commercial drugs. Only 7% of those commercial drugsviolated more than 8 out of these 20 rules [42]. Therefore, a threshold value of concern of 8 for the overall ADMET risk score was considered. All the short-listed compounds from the Scaffold 1 hopping showed an ADMET risk score of \(\leq\)8, hence exhibiting a significantly low predicted ADMET risk. The study of protein-ligand complex dynamics can be an expensive and time-consuming process [43]. To maximize efficiency and conduct dynamics simulations on a reasonable number of compounds, the protein-ligand complexes formed between FmIH and the compounds that exhibited an ADMET risk of \(\leq\) 6 were then subjected to MD simulations. A detailed toxicity property prediction, such as of the compounds' cardiotoxicity, hepatotoxicity, acute toxicity in rats, carcinogenicity in mice, and mutagenicity, was also performed using the ADMET PredictorTM 10.3.0.7 Tox Module. The ADMET models that were used in this study are explained in-depth in the ADMET Predictor modules ([[https://www.simulations-plus.com/software/admetpredictor/toxicity/](https://www.simulations-plus.com/software/admetpredictor/toxicity/)]([https://www.simulations-plus.com/software/admetpredictor/toxicity/](https://www.simulations-plus.com/software/admetpredictor/toxicity/)) (accessed on 3 October 2024), [[https://www.simulations-plus.com/wp-content/uploads/ADMETPredictor9.5.5-16-19.pdf](https://www.simulations-plus.com/wp-content/uploads/ADMETPredictor9.5.5-16-19.pdf)]([https://www.simulations-plus.com/wp-content/uploads/ADMETPredictor9.5.5-16-19.pdf](https://www.simulations-plus.com/wp-content/uploads/ADMETPredictor9.5.5-16-19.pdf)) (accessed on 3 October 2024)). Briefly, the cardiotoxicity of our compounds was assessed by their predicted affinity for hERG-encoded K\({}^{+}\) channels. The Simulations Plus ADMET Predictor hERG prediction model is an artificial neural network ensemble model trained on a diverse set of 582 small molecules, and tested on 164 other molecules ([[https://www.simulations-plus.com/software/admetpredictor/toxicity/](https://www.simulations-plus.com/software/admetpredictor/toxicity/)]([https://www.simulations-plus.com/software/admetpredictor/toxicity/](https://www.simulations-plus.com/software/admetpredictor/toxicity/)) (accessed on 3 October 2024)). The model showed a root-mean-square error (RMSE) of \(\sim\)0.55 M ([[https://www.simulations-plus.com/software/admetpredictor/toxicity/](https://www.simulations-plus.com/software/admetpredictor/toxicity/)]([https://www.simulations-plus.com/software/admetpredictor/toxicity/](https://www.simulations-plus.com/software/admetpredictor/toxicity/)) (accessed on 3 October 2024)). The adverse effects of the compounds on the human liver were assessed by the prediction of the elevation of certain enzymes in the blood that are used in hepatotoxicity diagnostics (alkaline phosphatase, aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, and gamma-glutamyl transferase). The neural network ensemble hepatotoxicity models were trained on a subset of 490 compounds from a publicly available Spontaneous Reporting System database. The models showed an average sensitivity value of \(\sim\)90% and an average specificity value of \(\sim\)76%.