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TANGO: A high through‐put conformation generation and semiempirical method‐based optimization tool for ligand molecules
Author(s) -
Gavane Vivek,
Koulgi Shruti,
Jani Vinod,
Uppuladinne Mallikarjunachari V. N.,
Sonavane Uddhavesh,
Joshi Rajendra
Publication year - 2019
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.25706
Subject(s) - dihedral angle , energy minimization , conformational isomerism , molecule , computer science , torsion (gastropod) , first generation , chemistry , computational chemistry , medicine , population , hydrogen bond , surgery , demography , organic chemistry , sociology
Lead optimization is one of the crucial steps in the drug discovery pipeline. After identifying the lead molecule and obtaining its 2D geometry, understanding the best conformation it would attain in 3D still remains one of the most challenging steps in drug discovery. There have been multiple methods and algorithms that are directed toward achieving best conformation for the lead molecules. TANGO focuses on conformation generation and its optimization using semiempirical energy calculations. The conformation generation is based on torsion angle rotation of the exocyclic bonds. The energy calculations are performed using MOPAC. The unique feature of this tool lies in the implementation of Message Passing Interface (MPI) for conformation generation and semiempirical‐based optimization. A well‐defined architecture handling the input and output generation has been used. The master and slave approach to handle operations involved in torsion angle rotation and energy calculations has helped in load balancing the process of conformation generation. The benchmarking results suggest that TANGO scales significantly well across eight nodes with each node utilizing 16 cores. This tool may prove to very useful in high throughput generation of semiempirically optimized small molecule conformations. The use of semiempirical methods for optimization generates a conformational ensemble thereby helping to obtain stable and alternate stable conformers for a given ligand molecule. © 2018 Wiley Periodicals, Inc.