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Molecular Docking of Phytochemicals Against RdRp (Mucormycosis)

Overview

This repository hosts the research paper:

“Molecular Docking Studies of Phytochemicals Against RNA-dependent RNA Polymerase of Mucormycosis”

The study performs in silico screening of antifungal phytochemicals targeting the RNA-dependent RNA polymerase (RdRp) of Rhizopus oryzae, with the aim of identifying potential antifungal drug candidates.


Problem Context

Mucormycosis is a high-mortality fungal infection, particularly in immunocompromised individuals. Current treatment options are limited. RdRp is a conserved and functionally critical enzyme, making it a strong therapeutic target.


Methodology

Pipeline

  • Protein modelling: RdRp sequence retrieved from NCBI; 3D structure generated via SWISS-MODEL
  • Ligand dataset: ~1000 antifungal phytochemicals from PubChem
  • Drug-likeness filtering: SwissADME (Lipinski’s Rule of Five)
  • Toxicity prediction: ProTox-II (LD50, hepatotoxicity, carcinogenicity, etc.)
  • Molecular docking: PyRx (AutoDock Vina) with UFF energy minimisation

Filtering Criteria

  • Molecular weight ≤ 500 Da
  • LogP ≤ 5
  • H-bond donors ≤ 5
  • H-bond acceptors ≤ 10

Results

  • 1000 → 209 compounds shortlisted after ADME screening

Top Candidates

Compound Binding Affinity (kcal/mol)
Dregamine -11.1
Alantolactone -9.5
Isoalantolactone -9.5
Solasodine -9.5
  • More negative binding energy indicates stronger ligand–protein interaction
  • Interaction types include hydrogen bonding, alkyl, π-alkyl, and electrostatic interactions

Key Findings

  • Dregamine is the most promising candidate based on binding affinity and pharmacokinetic profile
  • Several compounds were excluded due to toxicity despite good docking scores
  • In silico screening significantly reduces the search space for experimental validation

Tools & Technologies

  • PyRx / AutoDock Vina
  • SwissADME
  • ProTox-II
  • SWISS-MODEL
  • PubChem / NCBI

Limitations

  • No experimental (in vitro / in vivo) validation
  • Protein structure derived via homology modelling
  • Toxicity predictions are computational

Future Work

  • Molecular dynamics simulations
  • Experimental validation
  • Lead optimisation
  • Extension to additional targets

Citation

Jha et al., Molecular Docking Studies of Phytochemicals Against RNA-dependent RNA Polymerase of Mucormycosis, Journal of Diseases and Medicinal Plants, 2022

About

The antifungal activity of various phytochemicals against the RNA-dependent RNA polymerase protein was studied using in silico screening. Eventually, the most promising analogues can be further synthesized and evaluated to confirm their actual antifungal activity, allowing them to be used as bioactive compounds in the treatment of mucormycosis.

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