CAMPR4: a database of natural and synthetic antimicrobial peptides.

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. In this version of CAMP database, along with updating sequence information of AMPs, we have created separate prediction algorithms for natural and synthetic AMPs. CAMPR4 holds 24243 AMP sequences, 933 structures, 2143 patents and 263 AMP family signatures. In addition to the data on sequences, source organisms, target organisms, minimum inhibitory and hemolytic concentrations, CAMPR4 provides information on N and C terminal modifications and presence of unusual amino acids, as applicable. The database is integrated with tools for AMP prediction and rational design (natural and synthetic AMPs), sequence (BLAST and clustal omega), structure (VAST) and family analysis (PRATT, ScanProsite, CAMPSign). The data along with the algorithms of CAMPR4 will aid to enhance AMP research. CAMPR4 is accessible at http://camp.bicnirrh.res.in/.

FSHR antagonists can trigger a PCOS-like state.

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 (FSHß (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. These observations led us to hypothesize that use of FSHR antagonists can trigger a PCOS-like state. In the present study, to validate this hypothesis, we performed qRT-PCR validation using ovarian tissue samples from our previous study. Expression of three genes known to be differentially expressed in PCOS was evaluated and found to be similar to the PCOS state. To further test the hypothesis, theoretical simulations were carried out by using the human menstrual cycle model available in the literature. Model simulations for FSHR antagonism were indicative of increased testosterone levels, increased ratio of luteinizing hormone/follicle stimulating hormone, and stockpiling of secondary follicles, which are typical characteristics of PCOS. The findings of this study will be relevant while reviewing the utility of FSHR antagonists for fertility regulation and reproductive medicine.Abbreviations: FSH: Follicle-stimulating hormone; FSHR: Follicle-stimulating hormone receptor; cAMP: Cyclic adenosine 3'5' monophosphate; PKA: Protein kinase A; PI3K: Phosphoinositide 3-kinase; PKB: protein kinase B; ERK1/2: Extracellular signal-regulated protein kinase 1/2; MAPK: Mitogen-activated protein kinases; T: testosterone; E2: estradiol; PCOS: Polycystic ovarian syndrome; LH: luteinizing hormone; Lhcgr: luteinizing hormone/choriogonadotropin receptor; CYP17A1: cytochrome P450 family 17 subfamily A member 1; Inhba: inhibin subunit beta A; qRT-PCR: Real-Time quantitative reverse transcription polymerase chain reaction; FSHß: Follicle-stimulating hormone ß subunit; Ct: Cycle threshold; Rn18s: Rattus norvegicus 18S ribosomal RNA.

A QSAR modeling approach for predicting myeloid antimicrobial peptides with high sequence similarity.

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. On further experimental validation of the rationally designed peptides, CP was found to exhibit high antimicrobial activity with negligible hemolysis. Here, we provide CP, an AMP with potential therapeutic applications and a family-based QSAR model for AMP prediction.

A steady-state modeling approach for simulation of antimicrobial peptide-cell membrane interaction.

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. In the present study, a steady-state model that simulates AMP-membrane interaction was developed and was used to predict the mechanism of AMP binding. The predictions obtained from the model were validated with experimentally deciphered values available in literature. The model was further used to predict the mechanism for a set of designed AMPs with high sequence similarity to Myeloid Antimicrobial Peptide (MAP) family. Depending on the predicted mechanism, a unique half saturation constant and steepness of response (Hill coefficient) was obtained which was further validated with available data from literature. The model could reliably predict the mechanism, the half saturation constant and the Hill coefficient values. Further based on the analysis, it was observed that aggregation and oligomerization result in drastic killing action in a short range of peptide concentration owing to high Hill coefficient values. Mechanisms such as monomers binding at multiple sites with/without cooperativity result in antimicrobial activity at low half saturation constant though the killing action may not be steep. Thus, the methodology developed here can be used to develop hypothesis for studying AMP-membrane interaction mechanisms.

Collection of antimicrobial peptides database and its derivatives: Applications and beyond.

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, CAMPR3 has 10,247 sequences, 757 structures, and 114 family-specific signatures of AMPs along with associated tools for AMP sequence and structure analysis. CAMPSign uses family-specific sequence conservation, in the form of patterns and hidden Markov models for identification of AMPs. ClassAMP can be used to classify AMPs as antibacterial, antifungal, or antiviral based on sequence information. Here we describe CAMP and its derivatives and illustrate, with a few examples, the contribution of these online resources to the advancement of our current understanding of AMPs.

Leveraging family-specific signatures for AMP discovery and high-throughput annotation.

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. AMPs are known to have family-specific sequence composition, which can be mined for their discovery and rational design. Here, we present a detailed family-based study on AMP families. The study involved the use of sequence signatures represented by patterns and hidden Markov models (HMMs) present in experimentally studied AMPs to identify novel AMPs. Along with AMPs, peptides hitherto lacking antimicrobial annotation were also retrieved and wet-lab studies on randomly selected sequences proved their antimicrobial activity against Escherichia coli. CAMPSign, a webserver has been created for researchers to effortlessly exploit the use of AMP family signatures for identification of AMPs. The webserver is available online at www.campsign.bicnirrh.res.in. In this work, we demonstrate an optimised and experimentally validated protocol along with a freely available webserver that uses family-based sequence signatures for accelerated discovery of novel AMPs.

CAMPR3: a database on sequences, structures and signatures of antimicrobial peptides.

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.bicnirrh.res.in. It is a database of sequences, structures and family-specific signatures of prokaryotic and eukaryotic AMPs. Family-specific sequence signatures comprising of patterns and Hidden Markov Models were generated for 45 AMP families by analysing 1386 experimentally studied AMPs. These were further used to retrieve AMPs from online sequence databases. More than 4000 AMPs could be identified using these signatures. AMP family signatures provided in CAMPR3 can thus be used to accelerate and expand the discovery of AMPs. CAMPR3 presently holds 10247 sequences, 757 structures and 114 family-specific signatures of AMPs. Users can avail the sequence optimization algorithm for rational design of AMPs. The database integrated with tools for AMP sequence and structure analysis will be a valuable resource for family-based studies on AMPs.

CAMP: Collection of sequences and structures of antimicrobial peptides.

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.bicnirrh.res.in/. The 3D structures of peptides are known to influence antimicrobial activity. Although there exists databases of AMPs, information on structures of AMPs is limited in these databases. CAMP is manually curated and currently holds 6756 sequences and 682 3D structures of AMPs. Sequence and structure analysis tools have been incorporated to enhance the usefulness of the database.