References
1. Myers S, Baker A (2001) Drug discovery—an operating model for a new era. Nat
Biotechnol 19:727–730
2. Moses H III, Dorsey ER, Matheson DH et al (2005) Financial anatomy of biomedical
research. JAMA 294:1333–1342
3. Lahana R (1999) How many leads from HTS? Drug Discov Today 4:447–448
4. Veselovsky AV, Zharkova MS, Poroikov VV et al (2014) Computer-aided design and
discovery of protein-protein interaction inhibitors as agents for anti-HIV therapy.
SAR QSAR Environ Res 25:457–471
5. Song CM, Lim SJ, Tong JC (2009) Recent advances in computer-aided drug design. Brief
Bioinform 10:579–591
6. Taft CA, Da Silva VB, Da Silva CH (2008) Current topics in computer-aided drug design.
J Pharm Sci 97:1089–1098
7. Thiel KA (2004) Structure-aided drug design’s next generation. Nat Biotechnol 22:513–519
8. Reddy AS, Amarnath HSD, Bapi RS et al (2008) Protein ligand intreraction database
(PLID): datamining analysis of structure-function relationships. Comput Biol Chem 32:387–
390
9. Reddy ChS, Vijayasarathy K, Srinivas E et al (2006) Homology modeling of membrane
proteins: a critical assessment. Comput Biol Chem 30:120–126
10. Srivastava HK, Sastry GN (2012) A molecular dynamics investigation on a series of HIV
protease inhibitors: assessing the performance of MM-PBSA and MM-GBSA approaches.
J Chem Inf Model 52:3088–3098
11. Choudhury C, Priyakumar UD, Sastry GN (2014) Molecular dynamics investigation of the
active site dynamics of mycobacterial cyclopropane synthase during various stages of the
cyclopropanation process. J Struct Biol 187:38–48
12. Badrinarayan P, Sastry GN (2014) Specificity rendering ‘hot-spots’ for aurora kinase
inhibitor design: the role of non-covalent interactions and conformational transitions.
PLoS ONE 9:e113773
13. Srivastava HK, Choudhury C, Sastry GN (2012) The efficacy of conceptual DFT descriptors
and docking scores on the QSAR models of HIV protease inhibitors. Med Chem 8:811–825
14. Srivani P, Srinivas E, Raghu R et al (2007) Molecular modeling studies of pyridopurinone
derivatives—potential phosphodiesterase 5 inhibitors. J Mol Graph Model 26:378–390
15. Janardhan S, RamVivek M, Sastry GN (2016) Modeling the permeability of drug-like
molecules through the cell wall of mycobacterium tuberculosis: an analogue based approach.
Mol Bio Sys 12:3377–3384
16. Bohari MH, Sastry GN (2012) FDA approved drugs complexed to their targets: evaluating
pose prediction accuracy of docking protocols. J Mol Model 18:4263–4274
17. Choudhury C, Priyakumar UD, Sastry GN (2015) Dynamics based pharmacophore models
for screening potential inhibitors of mycobacterial cyclopropane synthase. J Chem Inf Model
55:848–860
18. Choudhury C, Priyakumar UD, Sastry GN (2016) Dynamic ligand-based pharmacophore
modeling and virtual screening to identify mycobacterial cyclopropane synthase inhibitors.
J Chem Sci 128:719–732
19. Reddy AS, Pati SP, Kumar PP et al (2007) Virtual screening in drug discovery—a
computational perspective. Curr Protein Pept Sci 8:329–351
20. Choudhury C, Priyakumar UD, Sastry GN (2016) Structural and functional diversities of the
hexadecahydro-1H-cyclopenta[a] phenanthrene framework, a ubiquitous scaffold in steroidal
hormones. Mol Inform 35:145–157
21. Agrafiotis DK, Bandyopadhyay D, Wegner JK et al (2007) Recent advances in
chemoinformatics. J Chem Inf Model 47:1279–1293
22. Vogt M, Bajorath J (2012) Chemoinformatics: a view of the field and current trends in
method development. Bioorg Med Chem 20:5317–5323
Pharmacophore Modelling and Screening: Concepts, Recent …
49
1. Myers S, Baker A (2001) Drug discovery—an operating model for a new era. Nat
Biotechnol 19:727–730
2. Moses H III, Dorsey ER, Matheson DH et al (2005) Financial anatomy of biomedical
research. JAMA 294:1333–1342
3. Lahana R (1999) How many leads from HTS? Drug Discov Today 4:447–448
4. Veselovsky AV, Zharkova MS, Poroikov VV et al (2014) Computer-aided design and
discovery of protein-protein interaction inhibitors as agents for anti-HIV therapy.
SAR QSAR Environ Res 25:457–471
5. Song CM, Lim SJ, Tong JC (2009) Recent advances in computer-aided drug design. Brief
Bioinform 10:579–591
6. Taft CA, Da Silva VB, Da Silva CH (2008) Current topics in computer-aided drug design.
J Pharm Sci 97:1089–1098
7. Thiel KA (2004) Structure-aided drug design’s next generation. Nat Biotechnol 22:513–519
8. Reddy AS, Amarnath HSD, Bapi RS et al (2008) Protein ligand intreraction database
(PLID): datamining analysis of structure-function relationships. Comput Biol Chem 32:387–
390
9. Reddy ChS, Vijayasarathy K, Srinivas E et al (2006) Homology modeling of membrane
proteins: a critical assessment. Comput Biol Chem 30:120–126
10. Srivastava HK, Sastry GN (2012) A molecular dynamics investigation on a series of HIV
protease inhibitors: assessing the performance of MM-PBSA and MM-GBSA approaches.
J Chem Inf Model 52:3088–3098
11. Choudhury C, Priyakumar UD, Sastry GN (2014) Molecular dynamics investigation of the
active site dynamics of mycobacterial cyclopropane synthase during various stages of the
cyclopropanation process. J Struct Biol 187:38–48
12. Badrinarayan P, Sastry GN (2014) Specificity rendering ‘hot-spots’ for aurora kinase
inhibitor design: the role of non-covalent interactions and conformational transitions.
PLoS ONE 9:e113773
13. Srivastava HK, Choudhury C, Sastry GN (2012) The efficacy of conceptual DFT descriptors
and docking scores on the QSAR models of HIV protease inhibitors. Med Chem 8:811–825
14. Srivani P, Srinivas E, Raghu R et al (2007) Molecular modeling studies of pyridopurinone
derivatives—potential phosphodiesterase 5 inhibitors. J Mol Graph Model 26:378–390
15. Janardhan S, RamVivek M, Sastry GN (2016) Modeling the permeability of drug-like
molecules through the cell wall of mycobacterium tuberculosis: an analogue based approach.
Mol Bio Sys 12:3377–3384
16. Bohari MH, Sastry GN (2012) FDA approved drugs complexed to their targets: evaluating
pose prediction accuracy of docking protocols. J Mol Model 18:4263–4274
17. Choudhury C, Priyakumar UD, Sastry GN (2015) Dynamics based pharmacophore models
for screening potential inhibitors of mycobacterial cyclopropane synthase. J Chem Inf Model
55:848–860
18. Choudhury C, Priyakumar UD, Sastry GN (2016) Dynamic ligand-based pharmacophore
modeling and virtual screening to identify mycobacterial cyclopropane synthase inhibitors.
J Chem Sci 128:719–732
19. Reddy AS, Pati SP, Kumar PP et al (2007) Virtual screening in drug discovery—a
computational perspective. Curr Protein Pept Sci 8:329–351
20. Choudhury C, Priyakumar UD, Sastry GN (2016) Structural and functional diversities of the
hexadecahydro-1H-cyclopenta[a] phenanthrene framework, a ubiquitous scaffold in steroidal
hormones. Mol Inform 35:145–157
21. Agrafiotis DK, Bandyopadhyay D, Wegner JK et al (2007) Recent advances in
chemoinformatics. J Chem Inf Model 47:1279–1293
22. Vogt M, Bajorath J (2012) Chemoinformatics: a view of the field and current trends in
method development. Bioorg Med Chem 20:5317–5323
Pharmacophore Modelling and Screening: Concepts, Recent …
49