Publications by authors named "Faiza H Waghu"

There has been an exponential increase in the design of synthetic antimicrobial peptides (AMPs) for its use as novel antibiotics. Synthetic AMPs are substantially enriched in residues with physicochemical properties known to be critical for antimicrobial activity; such as positive charge, hydrophobicity, and higher alpha helical propensity. The current prediction algorithms for AMPs have been developed using AMP sequences from natural sources and hence do not perform well for synthetic peptides.

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Over the recent years, FSHR has become an important target for development of fertility regulating agents, as impairment of FSH-FSHR interaction can lead to subfertility or infertility. In our previous study, we identified a 9-mer peptide (FSHβ (89-97)) that exhibited FSHR antagonist activity. The histopathological and biochemical observations indicated, in addition to FSHR antagonism, a striking resemblance to a PCOS-like state.

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Microbial resistance to conventional antibiotics has led to a surge in antimicrobial peptide (AMP) rational design initiatives that rely heavily on algorithms with good prediction accuracy and sensitivity. We present a quantitative structure-activity relationship (QSAR) approach for predicting activity of cathelicidins, an AMP family with broad-spectrum activity. The best multiple linear regression model built against Escherichia coli ATCC 25922 could accurately predict activity of three rationally designed peptides CP, DP, and Mapcon, having high sequence similarity.

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Antimicrobial Peptides (AMPs) are host defense molecules that initiate microbial death by binding to the membrane. On membrane binding, AMPs undergo changes in conformation and aggregation state to enable killing action. Depending on the AMP and cell membrane characteristics, the nature of binding can be aggregating or non-aggregating, with high/low cooperativity, at single or multiple sites with high/low affinity leading to a unique killing action that needs to be studied individually.

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Collection of antimicrobial peptides (CAMP), CAMPSign, and ClassAMP are open-access resources that have been developed to enhance research on antimicrobial peptides (AMPs). Comprehensive information on AMPs and machine learning-based predictive models are made available for users through these resources. As of date, CAMP has 10,247 sequences, 757 structures, and 114 family-specific signatures of AMPs along with associated tools for AMP sequence and structure analysis.

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Antimicrobial peptides (AMPs) are gaining attention as substitutes for antibiotics in order to combat the risk posed by multi-drug resistant pathogens. Several research groups are engaged in design of potent anti-infective agents using natural AMPs as templates. In this study, a library of peptides with high sequence similarity to Myeloid Antimicrobial Peptide (MAP) family were screened using popular online prediction algorithms.

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Antimicrobial peptides (AMPs) are diverse, biologically active, essential components of the innate immune system. As compared to conventional antibiotics, AMPs exhibit broad spectrum antimicrobial activity, reduced toxicity and reduced microbial resistance. They are widely researched for their therapeutic potential, especially against multi-drug resistant pathogens.

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Antimicrobial peptides (AMPs) are known to have family-specific sequence composition, which can be mined for discovery and design of AMPs. Here, we present CAMPR3; an update to the existing CAMP database available online at www.camp3.

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Antimicrobial peptides (AMPs) are gaining importance as anti-infective agents. Here we describe the updated Collection of Antimicrobial Peptide (CAMP) database, available online at http://www.camp.

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