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

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

Ciudad Autónoma de Buenos Aires

Congreso; Drug Discovery for Neglected Diseases International Congress 2018; 2018

Instituto de la Química Y Metabolismo del Fármaco (IQUIMEFA), Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires

Malaria is a life-threatening condition, typically transmitted through the bite of Anopheles mosquitoes infected withparasites 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 keyenzyme in the life cycle of P. falciparum since it degrades hemoglobin at the early trophozoite stage and cleavescytoskeletal elements vital to the stability of red cell membrane, at the schizont stage [1]. Development ofcomputational 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] incombination with a random subspace approximation [3] 1000 ligand-based classificatory models capable ofidentifying Falcipain-2 inhibitors were inferred. These models were validated through external validation and also in aretrospective virtual screening experiment, dispersing a small number of known inhibitors (31) among a large numberof decoys (1500) generated through DUD-e [4]. Ensemble learning was applied to increase the predictive power of theindividual classifiers, evaluating the performance through ROC curve-related metrics [5]. The best model-ensemble wasapplied in the prospective VS of DrugBank and Sweetlead databases. Four of the hits were acquired and tested againstrecombinant 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 VScampaign. 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 Odanacatibdisplaying 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 analysisat 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 tocomputer-guided drug repurposing; finding two novel inhibitors of the enzyme.