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Hierarchical-Clustering, Scaffold-Mining Exercises and Dynamics Simulations for Effectual Inhibitors Against Lipid-A Biosynthesis of Helicobacter pylori

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Abstract

Introduction

Treatment failures of standard regimens and new strains egression are due to the augmented drug resistance conundrum. These confounding factors now became the drug designers spotlight to implement therapeutics against Helicobacter pylori strains and to safeguard infected victims with devoid of adverse drug reactions. Thereby, to navigate the chemical space for medicine, paramount vital drug target opting considerations should be imperative. The study is therefore aimed to develop potent therapeutic variants against an insightful extrapolative, common target LpxC as a follow-up to previous studies.

Methods

We explored the relationships between existing inhibitors and novel leads at the scaffold level in an appropriate conformational plasticity for lead-optimization campaign. Hierarchical-clustering and shape-based screening against an in-house library of > 21 million compounds resulted in panel of 11,000 compounds. Rigid-receptor docking through virtual screening cascade, quantum-polarized-ligand, induced-fit dockings, post-docking processes and system stability assessments were performed.

Results

After docking experiments, an enrichment performance unveiled seven ranked actives better binding efficiencies with Zinc-binding potency than substrate and in-actives (decoy-set) with ROC (1.0) and area under accumulation curve (0.90) metrics. Physics-based membrane permeability accompanied ADME/T predictions and long-range dynamic simulations of 250 ns chemical time have depicted good passive diffusion with no toxicity of leads and sustained consistency of lead1-LpxC in the physiological milieu respectively.

Conclusions

In the study, as these static outcomes obtained from this approach competed with the substrate and existing ligands in binding affinity estimations as well as positively correlated from different aspects of predictions, which could facilitate promiscuous new chemical entities against H. pylori.

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Abbreviations

DOPE:

Discrete optimized protein energy

OPLS_AA:

Optimized potential for liquid simulations for all atoms

VSW:

Virtual screening workflow

RRD:

Rigid receptor docking

QPLD:

Quantum polarized ligand docking

IFD:

Induced fit docking

ROC:

Receiver operating characteristic (ROC)

AUC:

Area under the curve

MM/GBSA:

Molecular mechanics/generalized born surface area

RMSD:

Root-mean-square deviation

RMSF:

Root mean square fluctuation

PE:

Potential energy

LBFGS:

Limited memory Broyden-Fletcher-Goldfarb-Shanno

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Acknowledgments

PC acknowledges to ICMR, New Delhi, for supporting him with the Senior Research Fellowship (3/1/3/JRF-2014/HRD-8). Authors are highly thankful to DBT, Ministry of Science and Technology, Govt. of India for providing Bioinformatics infrastructure facility to SVIMS Bioinformatics Centre (BT/BI/25/037/2012 (BIF-SVIMST)).

Conflict of interest

All authors declared that they have no conflicts of interest.

Ethical Approval

Neither human studies, nor animal studies were carried out by the authors for this article.

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Authors and Affiliations

  1. Bioinformatics Centre, Department of Bioinformatics, SVIMS University, Tirupati, 517507, AP, India

    Chiranjeevi Pasala, Sudheer Kumar Katari, Ravina Madhulitha Nalamolu & Umamaheswari Amineni

  2. Department of Biochemistry, SVIMS University, Tirupati, 517507, AP, India

    Aparna R. Bitla

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  1. Chiranjeevi Pasala
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Correspondence to Umamaheswari Amineni.

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Pasala, C., Katari, S.K., Nalamolu, R.M. et al. Hierarchical-Clustering, Scaffold-Mining Exercises and Dynamics Simulations for Effectual Inhibitors Against Lipid-A Biosynthesis of Helicobacter pylori. Cel. Mol. Bioeng. 12, 255–274 (2019). https://doi.org/10.1007/s12195-019-00572-5

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