Data-Driven Systems Level Approaches for Drug Repurposing: Combating Drug Resistance in Priority Pathogens

2020

Front. Chem.

Self Cite

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.

Section: Introductionmentioning

confidence: 99%

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

2020

Front. Chem.

Self Cite

“…The standard therapies of treating TB with a combination of several antibiotics over a period of six to nine months (Dutt and Stead, 1997),(Zumla et al, 2015) and have severe limitations due to compliance which leads to emergence of drug resistant Mycobacterium tuberculosis (Mtb) (Prasad and Srivastava, 2013). Antimicrobial resistance (AMR) is one of the most serious global public health threats (Passi et al, 2019). The “End Tuberculosis Strategy” (Global Tuberculosis Report 2019) of WHO calls for intensified research and innovation in TB drug discovery using multidisciplinary approaches to identify novel drug targets as well as fast and accurate techniques to design new chemical entities with higher potency to address the scourge of Mtb.…”

Section: Introductionmentioning

confidence: 99%

Hybrid dynamic pharmacophore models as effective tools to identify novel chemotypes for anti-TB inhibitor design: A case study with Mtb-DapB

2020

Preprint

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The current study examines the efficacy of dynamics-based hybrid pharmacophore models (DHPM) based on newly explored interaction features, as tools to screen potential inhibitors of Mycobacterium tuberculosis (Mtb)-DapB, a validated target essential for L-Lysin biosynthesis. Molecular dynamics (MD) simulations were performed on Mtb-DapB models, generated from a reported crystal structure by linking the cofactor (NADH) and substrate mimetic inhibitor (2,6-PDC), thereby creating a hybrid molecule (HM). Comparative investigation of the dynamics of interactions made by NADH, 2,6-PDC and HM from the MD trajectories revealed a number of stable interactions between HM and the hinge region residues leading to significant alterations of the Mtb-DapB structure. These newly identified interactions, translated into DHPM may be utilized as Mtb-DapB specific screening filters and provide new insights for structure activity relationships. To validate the applicability of the DHPM, about 10 million compounds compiled from the publicly available chemical space were screened using the DHPM as well as conventional pharmacophore models (based on the NADH/2,6-PDC). Systematic analyses of structures, physicochemical/ADMET properties and molecular docking of the 387 and 982 compounds screened by the DHPM and conventional models respectively demonstrate the capabilities of DHPM to screen structurally diverse chemical entities with better druglike properties and higher target binding potentials. The study demonstrates application of DHPM to predict 8 highly active anti-Mtb (MIC<=2µM)compounds whose mechanisms of action were previously unknown.3

“…The standard therapies of treating TB with a combination of several lines of antibiotics over a period of six to nine months [3], [4] have severe limitations due to compliance and leads to emergence of drug resistant Mycobacterium tuberculosis (Mtb) strains [5]. Antimicrobial resistance (AMR) is one of the most serious global public health threats as, it compromises the successful prevention and treatment of deadly infectious diseases like tuberculosis [6]. The "End Tuberculosis Strategy" [1] of WHO calls for intensi ed research and innovation in TB drug discovery using multidisciplinary approaches to identify novel drug targets as well as fast and accurate techniques to design new chemical entities with higher potency to address the scourge of Mtb.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Dynamic Pharmacophore Models as Effective Tools to Identify Novel Chemotypes for Anti-tb Inhibitor Design: a Case Study With Mtb-dapb

2020

Preprint

Self Cite

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 200ns molecular dynamics simulations and trajectories were analysed 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 15, 63,764 publically 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 and the reported anti-mycobacterial molecules 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.