Hybrid Dynamic Pharmacophore Models as Effective Tools to Identify Novel Chemotypes for Anti-TB Inhibitor Design: A Case Study With Mtb-DapB

Abstract

Antimicrobial resistance (AMR) is one of the most serious global public health threats as it compromises the successful treatment of deadly infectious diseases like tuberculosis. New therapeutics are constantly needed but it takes a long time and is expensive to explore new biochemical space. One way to address this issue is to repurpose the validated targets and identify novel chemotypes that can simultaneously bind to multiple binding pockets of these targets as a new lead generation strategy. This study reports such a strategy, dynamic hybrid pharmacophore model (DHPM), which represents the combined interaction features of different binding pockets contrary to the conventional approaches, where pharmacophore models are generated from single binding sites. We have considered Mtb-DapB, a validated mycobacterial drug target, as our model system to explore the effectiveness of DHPMs to screen novel unexplored compounds. Mtb-DapB has a cofactor binding site (CBS) and an adjacent substrate binding site (SBS). Four different model systems of Mtb-DapB were designed where, either NADPH/NADH occupies CBS in presence/absence of an inhibitor 2, 6-PDC in the adjacent SBS. Two more model systems were designed, where 2, 6-PDC was linked to NADPH and NADH to form hybrid molecules. The six model systems were subjected to 200 ns molecular dynamics simulations and trajectories were analyzed to identify stable ligand-receptor interaction features. Based on these interactions, conventional pharmacophore models (CPM) were generated from the individual binding sites while DHPMs were created from hybrid-molecules occupying both binding sites. A huge library of 1,563,764 publicly available molecules were screened by CPMs and DHPMs. The screened hits obtained from both types of models were compared based on their Hashed binary molecular fingerprints and 4-point pharmacophore fingerprints using Tanimoto, Cosine, Dice and Tversky similarity matrices. Molecules screened by DHPM exhibited significant structural diversity, better binding strength and drug like properties as compared to the compounds screened by CPMs indicating the efficiency of DHPM to explore new chemical space for anti-TB drug discovery. The idea of DHPM can be applied for a wide range of mycobacterial or other pathogen targets to venture into unexplored chemical space.

Exploring cyclin-dependent kinase inhibitors: a comprehensive study in search of CDK-6 inhibitors using a pharmacophore modelling and dynamics approach

“…The docked complex for dynamics was then subjected to an OPLS forcefield. 69 The position of the complex was centred in an ortho rhombic cubic box, with TIP3P water molecules in addition to the buffers of nearly 10 Å between the protein atom and the box edge for dynamics simulation. The box volume has been computed with complex as well as counter ions like Na + and Cl − ions to neutralize the system.…”

In silico virtual screening for the identification of novel inhibitors against dihydrodipicolinate reductase (DapB) of Mycobacterium tuberculosis , a key enzyme of diaminopimelate pathway

“…However, these compounds were not evaluated for their ability to inhibit the growth of M. tb . Recently, a study compared conventional pharmacophore models with the dynamic hybrid pharmacophore model to screen a library of 15,63,764 molecules against DapB ( 21 ). It was noted that hybrid dynamic-based pharmacophore strategy yielded molecules with new chemotypes and better binding affinities and having drug-like properties.…”

“…It was noted that hybrid dynamic-based pharmacophore strategy yielded molecules with new chemotypes and better binding affinities and having drug-like properties. However, these molecules were not evaluated against the enzymatic activity of DapB ( 21 ).…”