A degenerate symbol over an alphabet Σ is a non-empty subset of Σ, and a sequence of such symbols is a degenerate string. We investigate the exact computation of maximal degenerate palindromes with gaps and mismatches. We present an algorithm which, given a degenerate string of length n and natural number parameters g and m, efficiently detects exact maximal palindromes with a gap size ≤g, and ≤m permitted mismatches. We show that it can be done in O(k|Σ|(k+log⁡|Σ|)+(k+g+m)n) time and O((g+m)n) space, where k represents an upper bound on the number of degenerate symbols contained in the string. Furthermore, we also show that the problem of factorisation a string into maximal degenerate palindromes with gaps and mismatches can also be done in O(k|Σ|(k+log⁡|Σ|)+(k+g+m)n) time and O((g+m)n) space. An inverted repeat is a specific type of palindrome which refers to a nucleotide sequence followed by its reverse complement. Our results can also be used to find maximal inverted repeated sequences with gaps and mismatches, where changing the structure of palindromes to inverted repeats does not affect the overall running time. Finally we demonstrate our algorithm on several strains of SARS-CoV-2, and quantify the number of inverted repeats found with ≤0,1,2 mismatches and ≤0,10,100 gap size.

The quest for small drug-like compounds that selectively inhibit the function of biological targets has always been a major focus in the pharmaceutical industry and in academia as well. High-throughput screening of compound libraries requires time, cost and resources. Therefore, the use of alternative methods is necessary for facilitating lead discovery. Computational techniques that dock small molecules into macromolecular targets and predict the affinity and activity of the small molecule are widely used in drug design and discovery, and have become an integral part of the industrial and academic research. In this review, we present an overview of some state-of-the-art technologies in modern drug design that have been developed for expediting the search for novel drug candidates.

SUMMARY: Drugster is a fully interactive pipeline designed to break the command line barrier and introduce a new user-friendly environment to perform drug design, lead and structure optimization experiments through an efficient combination of the PDB2PQR, Ligbuilder, Gromacs and Dock suites. Our platform features a novel workflow that guides the user through each logical step of the iterative 3D structural optimization setup and drug design process, by providing a seamless interface to all incorporated packages. AVAILABILITY: Drugster can be freely downloaded via our dedicated server system at http://www.bioacademy.gr/bioinformatics/drugster/.