Understanding In-Silico Approaches to Design Synthetic Antifungal Peptides to Combat Fungal Infections like Mucormycosis

Antimicrobial peptides are the small sized molecule ranging in size from 2 to 9 kDa with expansive range of antimicrobial activity against bacteria, fungi, viruses etc. They are also used as first line of defense against various pathogens. With the emergence of various fungal infections in the present day and uprising antifungal resistance has made the choice of antifungal drugs very limited, the conventional drugs are slowly becoming ineffective to these fungal pathogens. Researchers have turned to these naturally occurring molecules which represent diverse range of functions and structural features but these naturally occurring peptides exhibit high toxicity, instability and low specificity towards the target which can be combatted by using various in silico and computational approaches to design and modify these AMPs in such a way that their efficiency is increased. In this article, we have specifically focused on Mucormycosis infection because of its high mortality rates and a very few synthetic AMPs have been produced against Mucorales considering the severity of this disease and the rapid surge in Mucormycosis cases emerged in the country. In this paper we will discuss about the present scenario of the disease, AMPs as antifungal therapy, role, classification of antifungal peptides, mechanism of action, advantages and limitations of natural AMPs, important physicochemical properties taken into account while designing synthetic AMPs (SAMPs) and the workflow pipeline to characterize and predict potential synthetic AMPs by using the existing web servers, databases and bioinformatics tools to develop new alternatives of conventional drugs available in the market against fungal infections.

DETECTION, OPTIMIZATION AND CHARACTERIZATION OF BACTERIOCIN PRODUCED BY LACTOBACILLUS FERMENTUM A STRAIN ISOLATED FROM HOME MADE CURD- INDIAN TRADITIONAL FOOD

Lactic acid bacteria display numerous antimicrobial activities mainly due to the production of bacteriocins and antifungal peptides. Bacteriocins are known for anti-microbial properties against various pathogens. The aim of this work is to investigate the effect of growth conditions on the maximum production of bacteriocin by Lactobacillus fermentum isolated from home made curd. Bacteriocin produced by Lactobacillus fermentum, inhibited the growth of Salmonella typhimurium, Escherichia coli, Staphylococcus aureus, Enterococcus faecalis and Proteus mirabilis. The exponential phase of the growth was started at 4h from the time of incubation. The stationary phase begins at the 12h from the time of incubation. Maximum bacteriocin production of 12650 AU/mL with more biomass was obtained in presence of glucose. Yeast extract as sole nitrogen source, in MRS broth, stimulated bacteriocin production upto 2400 AU/mL. The maximum bacteriocin production of 12200 AU/mL was obtained with 2 % of NaCl. The optimum pH for bacterial growth and bacteriocin production was identified as pH 5. The highest bacteriocin activity of 7250 AU/ml and maximum growth o of 1.90 was recorded at pH 5. Bacteriocin production was found to be highest at 40 C temperature (8100AU/ml). Optimization of bacteriocin production with the modification of environmental growth conditions will greatly benefit efficient commercial applications. The stability of the bacteriocin with respect to pH, temperature, enzyme sensitivity and organic solvents also studied.

Multivariate information fusion for identifying antifungal peptides with Hilbert-Schmidt Independence Criterion

Background: Antifungal peptides (AFP) have been found to be effective against many fungal infections. Objective: However, it is difficult to identify AFP. Therefore, it is great practical significance to identify AFP via machine learning methods (with sequence information). Method: In this study, a Multi-Kernel Support Vector Machine (MKSVM) with Hilbert-Schmidt Independence Criterion (HSIC) is proposed. Proteins are encoded with five types of features (188-bit, AAC, ASDC, CKSAAP, DPC), and then construct kernels using Gaussian kernel function. HSIC are used to combine kernels and multi-kernel SVM model is built. Results: Our model performed well on three AFPs datasets and the performance is better than or comparable to other state-of-art predictive models. Conclusion: Our method will be a useful tool for identifying antifungal peptides.

PhytoAFP: In Silico Approaches for Designing Plant-Derived Antifungal Peptides

Emerging infectious diseases (EID) are serious problems caused by fungi in humans and plant species. They are a severe threat to food security worldwide. In our current work, we have developed a support vector machine (SVM)-based model that attempts to design and predict therapeutic plant-derived antifungal peptides (PhytoAFP). The residue composition analysis shows the preference of C, G, K, R, and S amino acids. Position preference analysis shows that residues G, K, R, and A dominate the N-terminal. Similarly, residues N, S, C, and G prefer the C-terminal. Motif analysis reveals the presence of motifs like NYVF, NYVFP, YVFP, NYVFPA, and VFPA. We have developed two models using various input functions such as mono-, di-, and tripeptide composition, as well as binary, hybrid, and physiochemical properties, based on methods that are applied to the main data set. The TPC-based monopeptide composition model achieved more accuracy, 94.4%, with a Matthews correlation coefficient (MCC) of 0.89. Correspondingly, the second-best model based on dipeptides achieved an accuracy of 94.28% under the MCC 0.89 of the training dataset.

Antifungal peptides from a Burkholderia strain suppress basal stem rot disease of oil palm.

Basal stem rot (BSR) is the most common disease of oil palm (Elaeis guineensis Jacq.) in Southeast Asia. BSR is caused by a white-rot fungus Ganoderma boninense. The disease is difficult to manage. Therefore, development of novel and environmentally safe approaches to control the disease is important. Species of Burkholderia are known to have diverse lifestyles, some of which can be beneficial to plants either by suppressing diseases or enhancing plant growth. In the present study, antifungal peptides (AFPs) produced by a bacterial strain isolated from the rhizosphere of an oil palm tree, namely Burkholderia sp. strain CP01, exhibited strong growth inhibition on G. boninense. A loss-of-function mutant of CP01 was generated, and it has enabled the identification of a 1.2 kDa peptide and its variants as the active antifungal compounds. High-resolution mass spectrometry revealed six analogous compounds with monoisotopic masses similar to the previously reported cyclic lipopeptides occidiofungin and burkholdine. The antifungal compounds of CP01 were secreted into media and we sought to use CP01 culture extract without living cells to control BSR disease. Glasshouse experiments showed that CP01 culture extract suppressed BSR disease in oil palm seedlings. The ability of CP01 to produce an antifungal substance and suppress plant disease suggests its potential application as a biofungicide in agriculture.

Activity and Mechanism of Action of Antifungal Peptides from Microorganisms: A Review

Harmful fungi in nature not only cause diseases in plants, but also fungal infection and poisoning when people and animals eat food derived from crops contaminated with them. Unfortunately, such fungi are becoming increasingly more resistant to traditional synthetic antifungal drugs, which can make prevention and control work increasingly more difficult to achieve. This means they are potentially very harmful to human health and lifestyle. Antifungal peptides are natural substances produced by organisms to defend themselves against harmful fungi. As a result, they have become an important research object to help deal with harmful fungi and overcome their drug resistance. Moreover, they are expected to be developed into new therapeutic drugs against drug-resistant fungi in clinical application. This review focuses on antifungal peptides that have been isolated from bacteria, fungi, and other microorganisms to date. Their antifungal activity and factors affecting it are outlined in terms of their antibacterial spectra and effects. The toxic effects of the antifungal peptides and their common solutions are mentioned. The mechanisms of action of the antifungal peptides are described according to their action pathways. The work provides a useful reference for further clinical research and the development of safe antifungal drugs that have high efficiencies and broad application spectra.

Antifungal Peptides

Fungal infections represent an increasing public health crisis [...]