TY - CHAP
T1 - A multimodal data analysis approach for targeted drug discovery involving topological data analysis (TDA)
AU - Alagappan, Muthuraman
AU - Jiang, Dadi
AU - Denko, Nicholas
AU - Koong, Albert C.
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - In silico drug discovery refers to a combination of computational techniques that augment our ability to discover drug compounds from compound libraries. Many such techniques exist, including virtual high-throughput screening (vHTS), high-throughput screening (HTS), and mechanisms for data storage and querying. However, presently these tools are often used independent of one another. In this chapter, we describe a new multimodal in silico technique for the hit identification and lead generation phases of traditional drug discovery. Our technique leverages the benefits of three independent methods—virtual high-throughput screening, high-throughput screening, and structural fingerprint analysis—by using a fourth technique called topological data analysis (TDA). We describe how a compound library can be independently tested with vHTS, HTS, and fingerprint analysis, and how the results can be transformed into a topological data analysis network to identify compounds from a diverse group of structural families. This process of using TDA or similar clustering methods to identify drug leads is advantageous because it provides a mechanism for choosing structurally diverse compounds while maintaining the unique advantages of already established techniques such as vHTS and HTS.
AB - In silico drug discovery refers to a combination of computational techniques that augment our ability to discover drug compounds from compound libraries. Many such techniques exist, including virtual high-throughput screening (vHTS), high-throughput screening (HTS), and mechanisms for data storage and querying. However, presently these tools are often used independent of one another. In this chapter, we describe a new multimodal in silico technique for the hit identification and lead generation phases of traditional drug discovery. Our technique leverages the benefits of three independent methods—virtual high-throughput screening, high-throughput screening, and structural fingerprint analysis—by using a fourth technique called topological data analysis (TDA). We describe how a compound library can be independently tested with vHTS, HTS, and fingerprint analysis, and how the results can be transformed into a topological data analysis network to identify compounds from a diverse group of structural families. This process of using TDA or similar clustering methods to identify drug leads is advantageous because it provides a mechanism for choosing structurally diverse compounds while maintaining the unique advantages of already established techniques such as vHTS and HTS.
KW - Computer aided drug discovery
KW - Fingerprint
KW - High- throughput screening
KW - In silico
KW - Topological data analysis
KW - Virtual screening
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U2 - 10.1007/978-3-319-26666-4_15
DO - 10.1007/978-3-319-26666-4_15
M3 - Chapter
C2 - 27325272
AN - SCOPUS:84978194066
T3 - Advances in Experimental Medicine and Biology
SP - 253
EP - 268
BT - Advances in Experimental Medicine and Biology
PB - Springer New York LLC
ER -