In the present era, a major drawback of current anti-cancer drugs is the lack of satisfactory specificity towards tumor cells. Despite the presence of several therapies against cancer, tumor homing peptides are gaining importance as therapeutic agent...
Extracting a well-designed energy function is important for protein structure evaluation. Knowledge-based potential functions are one type of the energy functions which can be obtained from known protein structures. The pairwise potential between ato...
Canonical π-helices are short, relatively unstable secondary structure elements found in proteins. They comprise seven or more residues and are present in 15% of all known protein structures, often in functionally important regions such as ligand- an...
The zinc (Zn) cofactor has been proven to be involved in numerous biological mechanisms and the zinc-binding site is recognized as one of the most important post-translation modifications in proteins. Therefore, accurate knowledge of zinc ions in pro...
Protein-protein interactions (PPIs) play a crucial role in the life-sustaining activities of organisms. Although various methods for the prediction of PPIs have been developed in the past decades, their robustness and prediction accuracy need to be i...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 16, 2019
The order of amino acids in a protein sequence enables the protein to acquire a conformation suitable for performing functions, thereby motivating the need to analyze these sequences for predicting functions. Although machine learning based approache...
Proceedings of the National Academy of Sciences of the United States of America
Apr 12, 2019
To reduce experimental effort associated with directed protein evolution and to explore the sequence space encoded by mutating multiple positions simultaneously, we incorporate machine learning into the directed evolution workflow. Combinatorial sequ...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 1, 2019
The engineering of stable proteins is crucial for various industrial purposes. Several machine learning methods have been developed to predict changes in the stability of proteins corresponding to single point mutations. To improve the prediction acc...
Insect neuropeptides and their associated receptors have been one of the potential targets for the pest control. The present study describes in silico models developed using natural and modified insect neuropeptides for predicting and designing new n...
BACKGROUND: Traditional methods for drug discovery are time-consuming and expensive, so efforts are being made to repurpose existing drugs. To find new ways for drug repurposing, many computational approaches have been proposed to predict drug-target...