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Welcome to LigPred

Lignin is the second most abundant organic polymer on earth. Found as a major component of plant cell walls and some algae this complex homopolymer contains a higher energy density than cellulose. Thus it is no surprise many industrial applications involving lignin have developed such as the ability to derive useful chemicals from lignin or uses based on its structural properties. These structural properties mainly it's recalcitrance continue to be an issue for the use of many kinds of plant material for biofuels and livestock food efficiency. Research has looked to plants to reduce the recalcitrance and quantity of lignin produced by plants and to lignin degraders for more efficient enzymes as solutions to reducing the negative impact of lignin in biofuel production. Next-generation sequencing offers a powerful tool for the study of the genetics of lignin synthesis and degradation though the study of plant genomes and metagenomes of lignin degrading environments. However, many proteins function cannot be accurately predicted with general identification techniques such as sequence similarity, clustering, motifs, or evolutionary relationships.

LigPred is an attempt to discover novel lignin related proteins not discoverable through more general means. To accomplish this we created high quality training sets from known lignin related enzymes and created models using a support vector machine (SVM). This allows for greater ability to recognize certain types of proteins at the expense of the inability to generally classify proteins.

We offer a web tool which accepts fasta data and will attempt to classify the sequences as belonging to lignin related enzyme class or not. In the event there is no relation the out will simply return unknown.

based method for recognition of enzymes related to degradation and synthesis of lignin. It can predict the 37 different classes of lignin related enzymes. See the table below for classes. The primary motivation for its development is to search genomic and metagenomic data for lignin related enzymes with low sequence similarity to currently known lignin related enzymes.

LigPred is made possible by generous funding from Oklahoma State University Provost through the iCREST research group and OCAST.