Draft:The DTC Lab, Jadavpur University
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The DTC Lab (Drug Theoretics and Cheminformatics Laboratory) is situated at Jadavpur University, a state-funded University in the state of West Bengal, India. It started functioning in 2002 in the Department of Pharmaceutical Technology of Jadavpur University. Since its inception, the DTC Lab has been instrumental in developing various molecular descriptors, validation methods, and modeling algorithms connected with Quantitative structure-activity relationship studies, with the application in drug design, materials science, and predictive toxicology. Inspired by the early works of Prof. A. U De of the Department, a theoretical modeling laboratory was established. It was initially named the Drug Theoretics Laboratory (named by Prof. De himself) and later renamed the DTC Laboratory. During the early days, Prof. C. Sengupta and D. K Pal contributed a lot to the development of the DTC Lab. In the initial days, the DTC Laboratory developed extended topochemical atom (ETA) descriptors, a class of topological index, and rm2 metrics used for validation of regression analysis based Quantitative Structure-Activity Relationship (QSAR) models. The ETA descriptors developed by the DTC Laboratory have been included in several descriptor computing software tools like PaDEL-Descriptor (http://yapcwsoft.com/dd/padeldescriptor/), alvaDesc (https://www.alvascience.com/alvadesc/), and modred (https://github.com/mordred-descriptor/mordred). This was followed by the development of various Cheminformatics/QSAR tools like data set division, multiple linear regression or partial least squares regression model development, external validation, the determination of the applicability domain, etc. which are hosted mainly at the site https://teqip.jdvu.ac.in/QSAR_Tools/ . Most of these tools were developed by Pravin Ambure, an alumnus of the laboratory [1]. Recently, the laboratory has developed a number of tools in connection with quantitative read-across and quantitative read-across structure-activity relationship (q-RASAR) and hosted at the site https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home . The supervised dimensionality reduction tool (the Arithmetic Residuals in K-Groups Analysis or the ARKA descriptors in QSAR has been introduced to identify the activity cliffs while the Multi-class ARKA framework has been reported for the improvement of q-RASAR models. These tools have been developed by Arkraprava Banerjee of the laboratory [2]. The methods/tools developed by the DTC Laboratory have received wide usage and citations [3]. Some of the studies have received special attention and coverages [4, 5]. There are several book contributions from the DTC Laboratory such as Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment, Academic Press, 2015 (http://books.google.co.uk/books/reader?id=bkFOBQAAQBAJ&printsec=frontcover&output=reader&source=gbs_atb&pg=GBS.PA23), A Primer on QSAR/QSPR Modeling: Fundamental Concepts (SpringerBriefs in Molecular Science), Springer, 2015 (http://www.springer.com/gp/book/9783319172804), and A Path to Predictive Cheminformatics (SpringerBriefs in Molecular Science), Springer, 2024, (https://doi.org/10.1007/978-3-031-52057-0).
References
1. Roy K, Quantitative structure-activity relationships (QSARs): A few validation methods and software tools developed at the DTC laboratory. Journal of the Indian Chemical Society, 95, 2018, 1497 - 1502
2. Banerjee A, Roy K, Read-Across and RASAR Tools from the DTC Laboratory. In Current Trends in Computational Modeling for Drug Discovery (Kar S & Leszczynski J, Eds.) Springer, 2023, https://doi.org/10.1007/978-3-031-33871-7_9
3. https://scholar.google.it/citations?user=dSjLSgIAAAAJ&hl=en
4. https://www.alvascience.com/model-mutagenicity-ta98/