SMMDB: A web-accessible database for small molecule modulators and their targets involved in neurological diseases

Abstract

High-throughput screening and better understanding of small molecule's structure-activity relationship (SAR) using computational biology techniques have greatly expanded the face of drug discovery process in better discovery of therapeutics for various disease. Small Molecule Modulators Database (SMMDB) includes >1100 small molecules that have been either approved by US Food and Drug Administration, are under investigation or were rejected in clinical trial for any kind of neurological diseases. The comprehensive information about small molecules includes the details about their molecular targets (such as protein or enzyme, DNA, RNA, antisense RNA etc.), pharmacokinetic and pharmacodynamic properties such as binding affinity to their targets (K d , K i , IC 50 and EC 50 if available), mode of action, log P-value, number of hydrogen bond donor and acceptors, their clinical trial status, their 2D and three-dimensional structures etc. To enrich the basic annotation of every small molecule entry present in SMMDB, it is hyperlinked to their description present in PubChem, DrugBank, PubMed and KEGG database. The annotation about their molecular targets was enriched by linking it with UniProt and GenBank and STRING database that can be utilized to study the interaction and relation between various targets involved in single neurological disease. All molecules present in the SMMDB are made available to download in single file and can be further used in establishing the SAR, structure-based drug designing as well as shape-based virtual screening for developing the novel therapeutics against neurological diseases. The scope of this database majorly covers the interest of scientific community and researchers who are engaged in putting their endeavor toward therapeutic development and investigating the pathogenic mechanism of various neurological diseases. The graphical user interface of the SMMDB is accessible on http://bsbe.iiti.ac.in/bsbe/smmdb. © The Author(s) 2018. Published by Oxford University Press.