The design and optimisation of novel human dihydrofolate reductase inhibitors for the management of proliferative disease

Abstract

Tetrahydrofolate (THF) mediates DNA and RNA synthesis through production of purine and thymidylate precursors. During this process THF is reduced to the inactive dihydrofolate (DHF) and recycled back to the active DHF via a redox reaction, catalysed by dihydrofolate reductase (DHFR). DHFR inhibition prevents cellular growth, hence drug design at this locus is considered valuable with DHFR antagonists having clinical relevance in proliferative disease management. This study utilised methotrexate (MTX) as lead molecule in the design and optimisation of novel DHFR antagonists. PDB crystallographic deposition 1U72 (Cody et al., 2005) 3 describing the holo MTX: human DHFR complex was modelled in SYBYL-X® v1.2 (Tripos) and affinity of MTX for the cognate receptor measured in X-SCORE v1.2 (Wang et al.,1998)to establish baseline affinity. Structure activity data and 2D-topology maps generated in PoseView v1.1 (Stierand and Gastreich, 2011)6 guided the creation of 7 seeds in which moieties considered non-critical for binding and clinical effect were computationally modified using the GROW module of LigBuilder v1.2 (Wang et al., 2000)7 .Each of the 7 seeds yielded 200 novel structures which were classified according to pharmacophore structure, physiochemical parameter and binding affinity. This molecular cohort was assessed for Lipinski Rule compliance which reduced the total number of viable molecules to 177. These were rendered in UCSF Chimera v1.8 (Pettersen et al., 2004)5 and Accelerys Draw® v4.1(Accelrys Software Inc., 2013)1 for visualisation and pharmacophoric growth deduction. The optimal structures combining affinity and Lipinski Rule compliance from each pharmacophoric group were identified, which could be further optimised for in vitro validation on the premise that they hold promise as clinically use antiproliferative drugs.