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<p>Black pepper (Piper nigrum, 2<i>n</i> = 52) has been traditionally valued for its therapeutic properties and used in treating various diseases for centuries. AMPs, often referred to as “nature’s antibiotics,” have gained significant attention due to the increasing multidrug resistance of microorganisms, emerging microbial infections and the scarcity of novel antibiotics. While the mechanism of defense and multiple types of action mechanisms of AMPs in animals have been widely researched, in plants, especially in medicinal crops like black pepper, their role is not much explored. This paper introduces BPepAMPred (<a href="http://46.202.167.198:5001/">http://46.202.167.198:5001/</a>), a species-specific AMP prediction server for black pepper. We obtained plant AMPs and evolutionary related non-AMPs and blast it with black pepper peptides to obtain 90 and 76 unique black pepper species-specific AMPs and non-AMPs, respectively. Using the sliding window technique, we produced 1353 subsequences for training and 151 for model testing. The model based on a deep neural network of a bidirectional-gated recurrent unit was tested on data subjected to tenfold cross-validation, yielding 99.34% accuracy, 98.68% sensitivity and 98.67% specificity. BPepAMPred is associated with a comprehensive database named BPepAMPdb (<a href="https://bpepampdb.daasbioinfromaticsteam.in/">https://bpepampdb.daasbioinfromaticsteam.in/</a>), which encompasses 43,759 predicted AMPs in the black pepper proteome, along with 10,935 functionally associated unique genes, chromosome numbers, genomic locations and respective gene IDs along with functional annotations. These molecular insights might help molecular biologists to validate and further develop AMPs in their wet laboratories, which could lead to novel therapeutic molecules and improvement in microbial resistance in black pepper and other crops.</p>

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Genome-wide identification of plant-based natural antimicrobial peptides using deep learning approach in black pepper

  • 期刊论文

  • 发表日期：

    2025年3月28日

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  • Ankita Negi,
  • Kalpana Singh,
  • Bulbul Ahmed,
  • Sarika Jaiswal,
  • Mir Asif Iquebal,
  • U. B. Angadi,
  • Anil Rai,
  • Dinesh Kumar

摘要

Black pepper (Piper nigrum, 2n = 52) has been traditionally valued for its therapeutic properties and used in treating various diseases for centuries. AMPs, often referred to as “nature’s antibiotics,” have gained significant attention due to the increasing multidrug resistance of microorganisms, emerging microbial infections and the scarcity of novel antibiotics. While the mechanism of defense and multiple types of action mechanisms of AMPs in animals have been widely researched, in plants, especially in medicinal crops like black pepper, their role is not much explored. This paper introduces BPepAMPred (http://46.202.167.198:5001/), a species-specific AMP prediction server for black pepper. We obtained plant AMPs and evolutionary related non-AMPs and blast it with black pepper peptides to obtain 90 and 76 unique black pepper species-specific AMPs and non-AMPs, respectively. Using the sliding window technique, we produced 1353 subsequences for training and 151 for model testing. The model based on a deep neural network of a bidirectional-gated recurrent unit was tested on data subjected to tenfold cross-validation, yielding 99.34% accuracy, 98.68% sensitivity and 98.67% specificity. BPepAMPred is associated with a comprehensive database named BPepAMPdb (https://bpepampdb.daasbioinfromaticsteam.in/), which encompasses 43,759 predicted AMPs in the black pepper proteome, along with 10,935 functionally associated unique genes, chromosome numbers, genomic locations and respective gene IDs along with functional annotations. These molecular insights might help molecular biologists to validate and further develop AMPs in their wet laboratories, which could lead to novel therapeutic molecules and improvement in microbial resistance in black pepper and other crops.