Discovery of new falcipain inhibitors by application of computer-assisted drug repurposing

ALBERCA, L.N.; CHUGURANSKY, S. ; TALEVI, A.; SALAS-SURDUY, E.

Buenos Aires

Congreso; DRUG DISCOVERY FOR NEGLECTED DISEASES INTERNATIONAL CONGRESS 2018; 2018

/ Instituto de la Química y Metabolismo del Fármaco FFyB UBA

Malaria is a life-threatening condition, typically transmitted through the bite of Anopheles mosquitoes infected with parasites from the Plasmodium genre. Though there exist efficacious medications to treat malaria, the emergenceand spread of drug resistant parasites determines the need for ongoing drug discovery programs. Falcipain-2 is a key enzyme in the life cycle of P. falciparum since it degrades hemoglobin at the early trophozoite stage and cleaves cytoskeletal elements vital to the stability of red cell membrane, at the schizont stage [1]. Development of computational models capable of identifying new inhibitors of Falcipain-2, and subsequent application to virtualscreening (VS) campaigns focused on drug repurposing opportunities.We have compiled a database of molecules tested against falcipain-2. Using a semicorrelation approach [2] in combination with a random subspace approximation [3] 1000 ligand-based classificatory models capable of identifying Falcipain-2 inhibitors were inferred. These models were validated through external validation and also in a retrospective virtual screening experiment, dispersing a small number of known inhibitors (31) among a large number of decoys (1500) generated through DUD-e [4]. Ensemble learning was applied to increase the predictive power of the individual classifiers, evaluating the performance through ROC curve-related metrics [5]. The best model-ensemble was applied in the prospective VS of DrugBank and Sweetlead databases. Four of the hits were acquired and tested against recombinant Falcipain-2 using a fluorogenic continuous enzymatic assay under balanced assay conditions ([S]0/KM=1)[6]. The reversibility of the interaction, mode of inhibition and Ki were further investigated for validated hits [7].The best individual classifier achieved an AUROC of 0.853 in the retrospective screen; the best model-ensemble (MIN operator, 11 models) significantly improved such metric to 0.921 and was employed in the prospective VS campaign. 157 hits were selected, among them 64 approved drugs. Three of them (Benzthiazide, Bendroflumethiazide, Methacycline) plus the shelved drug Odanacatib were acquired and tested, with Methacycline and Odanacatib displaying FP2 inhibition ≥ 35% at 31.25 μM. Although both inhibitors showed reversible interactions with FP2,Odanacatib exhibited time-dependent inhibition (with slow association and dissociation steps). Dose-response analysis at growing substrate concentrations indicated that Odanacatib is a Competitive inhibitor (Ki=1.03±0.08 x10-7 M) of FP2, whereas Methacycline displayed Non-competitive behavior (Ki= 8.44±0.65 x10-5 M; α=1.42±0.15).We have generated a ligand-based model ensemble capable of recognizing falcipain-2 inhibitors, which was applied to computer-guided drug repurposing; finding two novel inhibitors of the enzyme.