Introduction

The ineffectiveness of antimicrobial agents, i.e. antimicrobial resistance (AMR), has become a global public health threat. A large number of bacterial species have been reported to have resistant markers against different antibiotics. Klebsiella pneumoniae, E. coli, Staphlylococcus aureus, Mycobacterium, Streptococcus pneumoniae, etc., are some of the common species involved in infections [1–3]. It is a great menace to the patients having organ transplantation, major surgeries like hip transplant, breast biopsy, caesarean sections and cancer chemotherapies where the risk of spreading infection is high. Besides this, antimicrobial resistance (AMR) causes prolonged treatment of the disease and an enhanced cost of treatment [4]. As per WHO MDR-TB factsheet 2018 report about 558,000 new cases of multi-drug resistance tuberculosis (MDR-TB) have been estimated in 2017 and 161,000 cases of MDR or RR-TB have been detected and reported in 2017 [5]. The MRSA (Methicillin-resistant Staphylococcus aureus) infected people are 64% more likely to die than the people infected with non-resistant strains as per the WHO report [4].

CDC report of 2019 on antibiotic-resistance threats in the United States, showed that 2.8 million antibiotic-resistant infections reported every year, due to which is resulted in 35,000 deaths per year and a huge economic loss to the country [6]. European Centre For Disease Prevention and Control (ECDC) report on the bacterial challenge: "time to react", estimated about 25,000 people who have died due to antibiotic resistance problem in Europe, Iceland, and Norway, during 2007. Moreover, infection due to the antibiotic-resistant bacteria was responsible for staying patients in the hospital, extra 2.5 million days in Europe, Iceland and Norway, and these extra days may cost more than EUR 900 million [7].

There is a need to search novel effective lead molecules for future drug candidates against the antimicrobial-resistant microorganisms. In view of the above-described situation, we have developed a manually curated database of antimicrobial molecules (ACD), comprises of both synthetic chemical compounds and the antimicrobial peptides. These peptides were isolated mainly from biological sources along with some synthetic peptides. There are many databases available for antimicrobial peptides like CAMP (http://www.camp.bicnirrh.res.in/) [8], APD3 (http://aps.unmc.edu/AP/main.php) [9], PhytAMP (http://phytamp.pfba-lab-tun.org/main.php) [10] and similarly, a large number of databases are available for chemical compounds like PubChem (https://pubchem.ncbi.nlm.nih.gov/) [11], DrugBank (https://www.drugbank.ca/) [12], ZINC (http://zinc.docking.org/) [13], ChemDB (http://www.chemdb.com/) [14], etc., but none of the above databases provided a single platform where a user can get access to both synthetic chemical molecules and antimicrobial peptides. The purpose of this database was to provide a single user-friendly platform where a user can get information on both the synthetic compounds as well as the antimicrobial peptides. In ACD database, only the effective antimicrobial (compounds and peptides) agents were selected for the database. It makes easier to select the putative drug candidate. Further, this database is comprehensive in nature and provides multiple ways to find out the molecule of interest. In spite of this, the user can get good information about the properties of the molecule. The contemporary databases of ACD are generally based on data, which is very vast and nonspecific in nature, which may lead to time consuming and reduced work efficiency. The synthetic compound and antimicrobial peptide on a single platform will help researchers to go for virtual screening to identify effective lead molecules in minimum time.

Materials and methods

Data collection

The data collection of chemical compounds was made from the available databases ZINC [13], DrugBank [12], ChemDB [14], PubChem [11], PubChem Bioassays [15], and literature search. The antimicrobial peptides were collected from various sources like extensive literature searches from PubMed and some from Uniprot (Fig 1). The whole data of both synthetic compounds and antimicrobial compounds are collected based on their antibacterial and antifungal activity. Of the total data collected, about 2900 antibacterial, 1200 synthetic antifungal compounds, and about 1030 active antimicrobial peptides were selected (Fig 2).

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Fig 1. Antimicrobial chemotherapeutics database architecture.

https://doi.org/10.1371/journal.pone.0235193.g001

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Fig 2. Schematic representation of total compounds and peptides available in ACD.

https://doi.org/10.1371/journal.pone.0235193.g002

The data of each synthetic compound is arranged into two categories: the first category gives information about the name and identifier of the compound (compound name, target, CBD ID, Zinc ID, PubChem ID, Canonical SMILES, IUPAC Name, ISO Smiles and Bioassay) and the second category provides information about chemical and physical properties of the compound (Molecular weight, Molecular Formula, XLogP, hydrogen bond acceptor, hydrogen bond donor and Rotatable bond).

The peptide data is categorized based on antibacterial and antifungal activity. Further, the antibacterial peptides are divided into Gram-positive and Gram-negative. The user can also get information about the peptide length, charge, target, peptide sequence, the source of the peptide, i.e. the organism from which the peptide was collected, and also a brief description of the peptide with ACD ID.

Results

Conclusion

To get-rid-of global threat of antimicrobial resistance, a need of an hour is to translate the drug research into effective medicine. High throughput screening and validation of antimicrobial agents are required to combat this global problem. Therefore, the ACD database was designed to provide a user-friendly and convenient resource for the researcher to identify novel antimicrobial agents. The ACD database provides a single platform of both antimicrobial chemical compounds and peptides. It provides several user-friendly search tools and methods, which makes the finding of the specific drug candidate much easier than other databases. A wide range of properties and structure similarity search of synthetic compounds were given so that the user can find its desirable compounds quite easily. Similarly, the effective antimicrobial peptides were selected for this database with their several properties as described earlier. The database will save time and effort of students and researchers to search for potential antimicrobial agents as future drug candidates.

Update

The database will be updated regularly with new information and data entries from time to time. The authors and developers of this database will appreciate any comments, valuable suggestions, and queries from the users of this database.

Acknowledgments

We would like to thank Dr. Peter Ertl for providing us Java Script Molecular Editor (JSME) [16] for our Database.