TY - JOUR
T1 - LiSIs
T2 - An online scientific workflow system for virtual screening
AU - Kannas, Christos C.
AU - Kalvari, Ioanna
AU - Lambrinidis, George
AU - Neophytou, Christiana M.
AU - Savva, Christiana G.
AU - Kirmitzoglou, Ioannis
AU - Antoniou, Zinonas
AU - Achilleos, Kleo G.
AU - Scherf, David
AU - Pitta, Chara A.
AU - Nicolaou, Christos A.
AU - Mikros, Emanuel
AU - Promponas, Vasilis J.
AU - Gerhauser, Clarissa
AU - Mehta, Rajendra G.
AU - Constantinou, Andreas I.
AU - Pattichis, Constantinos S.
PY - 2015
Y1 - 2015
N2 - Modern methods of drug discovery and development in recent years make a wide use of computational algorithms. These methods utilise Virtual Screening (VS), which is the computational counterpart of experimental screening. In this manner the in silico models and tools initial replace the wet lab methods saving time and resources. This paper presents the overall design and implementation of a web based scientific workflow system for virtual screening called, the Life Sciences Informatics (LiSIs) platform. The LiSIs platform consists of the following layers: the input layer covering the data file input; the pre-processing layer covering the descriptors calculation, and the docking preparation components; the processing layer covering the attribute filtering, compound similarity, substructure matching, docking prediction, predictive modelling and molecular clustering; post-processing layer covering the output reformatting and binary file merging components; output layer covering the storage component. The potential of LiSIs platform has been demonstrated through two case studies designed to illustrate the preparation of tools for the identification of promising chemical structures. The first case study involved the development of a Quantitative Structure Activity Relationship (QSAR) model on a literature dataset while the second case study implemented a docking-based virtual screening experiment. Our results show that VS workflows utilizing docking, predictive models and other in silico tools as implemented in the LiSIs platform can identify compounds in line with expert expectations. We anticipate that the deployment of LiSIs, as currently implemented and available for use, can enable drug discovery researchers to more easily use state of the art computational techniques in their search for promising chemical compounds. The LiSIs platform is freely accessible (i) under the GRANATUM platform at: http://www.granatum.org and (ii) directly at: http://lisis.cs.ucy.ac.cy.
AB - Modern methods of drug discovery and development in recent years make a wide use of computational algorithms. These methods utilise Virtual Screening (VS), which is the computational counterpart of experimental screening. In this manner the in silico models and tools initial replace the wet lab methods saving time and resources. This paper presents the overall design and implementation of a web based scientific workflow system for virtual screening called, the Life Sciences Informatics (LiSIs) platform. The LiSIs platform consists of the following layers: the input layer covering the data file input; the pre-processing layer covering the descriptors calculation, and the docking preparation components; the processing layer covering the attribute filtering, compound similarity, substructure matching, docking prediction, predictive modelling and molecular clustering; post-processing layer covering the output reformatting and binary file merging components; output layer covering the storage component. The potential of LiSIs platform has been demonstrated through two case studies designed to illustrate the preparation of tools for the identification of promising chemical structures. The first case study involved the development of a Quantitative Structure Activity Relationship (QSAR) model on a literature dataset while the second case study implemented a docking-based virtual screening experiment. Our results show that VS workflows utilizing docking, predictive models and other in silico tools as implemented in the LiSIs platform can identify compounds in line with expert expectations. We anticipate that the deployment of LiSIs, as currently implemented and available for use, can enable drug discovery researchers to more easily use state of the art computational techniques in their search for promising chemical compounds. The LiSIs platform is freely accessible (i) under the GRANATUM platform at: http://www.granatum.org and (ii) directly at: http://lisis.cs.ucy.ac.cy.
KW - Chemoinformatics
KW - Docking
KW - Drug discovery
KW - Predictive models
KW - QSAR
KW - Scientific workflow
KW - Virtual screening
UR - http://www.scopus.com/inward/record.url?scp=84931260350&partnerID=8YFLogxK
M3 - Article
C2 - 25747448
AN - SCOPUS:84931260350
SN - 1386-2073
VL - 18
SP - 281
EP - 295
JO - Combinatorial Chemistry and High Throughput Screening
JF - Combinatorial Chemistry and High Throughput Screening
IS - 3
ER -