• Fri. May 27th, 2022


  1. Roy S, Gupta D (2022) DriverFuse: An R package for analysis of next-generation sequencing datasets to identify cancer driver fusion genes. PLOS ONE 17(2): e0262686.
  2. Yadav S, Ahamad S, Gupta D, Mathur P. Lead optimization, pharmacophore development and scaffold design of protein kinase CK2 inhibitors as potential COVID-19 therapeutics. Journal of Biomolecular Structure and Dynamics. 2022:1-17.
  3. Vandana, Pandey R, Srinivasan E, Kalia I, Singh AP, Saxena A, et al. Plasmodium falciparum metacaspase-2 capture its natural substrate in a non-canonical way. The Journal of Biochemistry. 2021.
  4.  Sourabh, S. et al. Plasmodium falciparum DDX17 is an RNA helicase crucial for parasite develpment. Biochemistry and Biophysics Reports 26, 101000 (2021).
  5. Singh, A.P., Kumar, R. & Gupta, D. Structural insights into the mechanism of human methyltransferase hPRMT4. J Biomol Struct Dyn, 1-14 (2021).
  6. Shehzad, S., Pandey, R., Malhotra, P. & Gupta, D. Computational Design of Novel Allosteric Inhibitors for Plasmodium falciparum DegP. Molecules 26(2021).
  7. Satish, D., Mukherjee, S.K. & Gupta, D. The landscape of microRNAs in plant viral infections. Plant Gene 26, 100293 (2021).
  8. Sardar, R., Sharma, A. & Gupta, D. Machine Learning Assisted Prediction of Prognostic Biomarkers Associated With COVID-19, Using Clinical and Proteomics Data. Frontiers in Genetics 12(2021).
  9. Roy, S., Singh, A.P. & Gupta, D. Unsupervised subtyping and methylation landscape of pancreatic ductal adenocarcinoma. Heliyon 7, e06000-e06000 (2021).
  10. Roy, Anirban, et al. “Virus-Free Improved Food in the Era of Bacterial Immunity.” Genome Engineering for Crop Improvement. Springer, Cham, 2021. 63-96.
  11. Prasad, K., Ahamad, S., Kanipakam, H., Gupta, D. & Kumar, V. Simultaneous Inhibition of SARS-CoV-2 Entry Pathways by Cyclosporine. ACS Chemical Neuroscience (2021).
  12. Prasad K, Ahamad S, Gupta D, Kumar V. Targeting cathepsins: A potential link between COVID-19 and associated neurological manifestations. Heliyon. 2021;7(10):e08089.
  13. Pandey, R., Gupta, P., Mohmmed, A., Malhotra, P. & Gupta, D. A Plasmodium falciparum protein tyrosine phosphatase inhibitor identified from the ChEMBL-NTD database blocks parasite growth. FEBS Open Bio n/a(2021).
  14. Onchieku NM, Kumari S, Pandey R, Sharma V, Kumar M, Deshmukh A, et al. Artemisinin Binds and Inhibits the Activity of Plasmodium falciparum Ddi1, a Retroviral Aspartyl Protease. Pathogens. 2021;10(11):1465.
  15. Hema, K., Ahamad, S., Joon, H.K., Pandey, R. & Gupta, D. Atomic Resolution Homology Models and Molecular Dynamics Simulations of Plasmodium falciparum Tubulins. ACS Omega (2021).
  16. Gupta D, Sardar R. Bioinformatics of Genome Annotation. Bioinformatics and Human Genomics Research: CRC Press; 2021. p. 7-30.
  17. Fatima, S. et al. Detection of truncated isoforms of human neuroserpin lacking the reactive center loop: Implications in noninhibitory role. IUBMB Life n/a(2021).
  18. Biji, A. et al. Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples. EBioMedicine 70(2021).
  19. Ahamad, S., Kanipakam, H., Kumar, V. & Gupta, D. A molecular journey to check the conformational dynamics of tau tubulin kinase 2 mutations associated with Alzheimer’s disease. RSC Advances 11, 1320-1331 (2021).
  20. Ahamad, S., Kanipakam, H., Birla, S., Ali, M.S. & Gupta, D. Screening Malaria-box compounds to identify potential inhibitors against SARS-CoV-2 Mpro, using molecular docking and dynamics simulation studies. European Journal of Pharmacology 890, 173664-173
  21. Ahamad, S., Hema, K., Kumar, V. & Gupta, D. The structural, functional, and dynamic effect of Tau tubulin kinase1 upon a mutation: A neuro-degenerative hotspot. J Cell Biochem (2021).
  22. Ahamad, S., Hema, K. & Gupta, D. Structural stability predictions and molecular dynamics simulations of RBD and HR1 mutations associated with SARS-CoV-2 spike glycoprotein. Journal of Biomolecular Structure and Dynamics, 1-13 (2021).
  23. Sharma, A., Satish, D., Sharma, S. & Gupta, D. Indian Major Basmati Paddy Seed Varieties Images Dataset. Data in Brief, 106460-106460 (2020).
  24. Sharma, A., Satish, D., Sharma, S. & Gupta, D. iRSVPred: A Web Server for Artificial Intelligence Based Prediction of Major Basmati Paddy Seed Varieties. Frontiers in Plant Science 10, 1791-1791 (2020).
  25. Sharma, A., Rani, S. & Gupta, D. Artificial Intelligence-Based Classification of Chest X-Ray Images into COVID-19 and Other Infectious Diseases. International Journal of Biomedical Imaging 2020, 8889023-8889023 (2020).
  26. Sardar, R., Satish, D. & Gupta, D. Identification of Novel SARS-CoV-2 Drug Targets by Host MicroRNAs and Transcription Factors Co-regulatory Interaction Network Analysis. Frontiers in Genetics 11, 1105-1105 (2020).
  27. Sardar, R., Satish, D., Birla, S. & Gupta, D. Integrative analyses of SARS-CoV-2 genomes from different geographical locations reveal unique features potentially consequential to host-virus interaction, pathogenesis and clues for novel therapies. Heliyon
  28. Sardar, R., Satish, D., Birla, S. & Gupta, D. Dataset of mutational analysis, miRNAs targeting SARS-CoV-2 genes and host gene expression in SARS-CoV and SARS-CoV-2 infections. Data in Brief 32, 106207-106207 (2020).
  29. Sardar, R. et al. In-silico profiling and structural insights into the impact of nSNPs in the P. falciparum acetyl-CoA transporter gene to understand the mechanism of drug resistance in malaria. Journal of biomolecular structure & dynamics, 1-12 (2020).
  30. Roy, S., Kumar, R., Mittal, V. & Gupta, D. Classification models for Invasive Ductal Carcinoma Progression, based on gene expression data-trained supervised machine learning. Scientific reports 10, 4113-4113 (2020).
  31. Pandey, R. et al. Plasmodium Condensin Core Subunits SMC2/SMC4 Mediate Atypical Mitosis and Are Essential for Parasite Proliferation and Transmission. Cell reports 30, 1883-1897.e6 (2020).
  32. Meher, A. et al. Whole-Genome Sequence of Drug-Resistant Mycobacterium tuberculosis Strain S7, Isolated from a Patient with Pulmonary Tuberculosis. Microbiology resource announcements 9(2020).
  33. Jakeer, S. et al. Metagenomic analysis of the fecal microbiome of an adult elephant reveals the diversity of CAZymes related to lignocellulosic biomass degradation. Symbiosis (2020).
  34. Jade, D.D., Pandey, R., Kumar, R. & Gupta, D. Ligand-based pharmacophore modeling of TNF-α to design novel inhibitors using virtual screening and molecular dynamics. Journal of Biomolecular Structure and Dynamics, 1-17 (2020).
  35. Guttery, D.S. et al. Plasmodium DEH is ER-localized and crucial for oocyst mitotic division during malaria transmission. Life Science Alliance 3, e202000879-e202000879 (2020).
  36. Birla, S. et al. Classifying juvenile onset primary open angle glaucoma using cluster analysis. The British journal of ophthalmology 104, 827-835 (2020).
  37. Bano, S. et al. Identification and characterization of a novel isoform of heparin cofactor II in human liver. IUBMB life (2020).
  38. Ali, M.F., Kaushik, A., Gupta, D., Ansari, S. & Jairajpuri, M.A. Changes in strand 6B and helix B during neuroserpin inhibition: Implication in severity of clinical phenotype. Biochimica et biophysica acta. Proteins and proteomics 1868, 140363-140363 (202
  39. Ahamad, S., Kanipakam, H. & Gupta, D. Insights into the structural and dynamical changes of spike glycoprotein mutations associated with SARS-CoV-2 host receptor binding. Journal of biomolecular structure & dynamics, 1-13 (2020).
  40. Ahamad, S., Gupta, D. & Kumar, V. Targeting SARS-CoV-2 nucleocapsid oligomerization: Insights from molecular docking and molecular dynamics simulations. Journal of Biomolecular Structure and Dynamics, 1-14 (2020).
  41. Shinkafi, T.S. et al. Computational prediction and experimental validation of the activator function of C2-beta-D-glucopyranosyl-1,3,6,7-tetrahydroxyxanthone on pancreatic and hepatic hexokinase. Journal of biomolecular structure & dynamics, 1-12 (2019).
  42. Satish, D., Mukherjee, S.K. & Gupta, D. PAmiRDB: A web resource for plant miRNAs targeting viruses. Sci Rep 9, 4627 (2019).
  43. Sardar, R. et al. ApicoTFdb: the comprehensive web repository of apicomplexan transcription factors and transcription-associated co-factors. Database : the journal of biological databases and curation 2019(2019).
  44. Kumar, R., Jade, D. & Gupta, D. A novel identification approach for discovery of 5-HydroxyTriptamine 2A antagonists: combination of 2D/3D similarity screening, molecular docking and molecular dynamics. Journal of biomolecular structure & dynamics 37, 931-
  45. Kibria, K.M.K. et al. A genome-wide analysis of coatomer protein (COP) subunits of apicomplexan parasites and their evolutionary relationships. BMC genomics 20, 98-98 (2019).
  46. Haque, S. et al. S.Typhi derived OmpC peptide conjugated with Vi-polysaccharide evokes better immune response than free Vi-polysaccharide in mice. Biologicals : journal of the International Association of Biological Standardization 62, 50-56 (2019).
  47. Gupta, D. & Mukherjee, S.K. Antiviral RNAi mediated Plant defense versus its suppression by viruses. Journal of plant science and phytopathology 3, 8-8 (2019).
  48. Verma, D.K., Gupta, D. & Lal, S.K. Host Lipid Rafts Play a Major Role in Binding and Endocytosis of Influenza A Virus. Viruses 10(2018).
  49. Sharma, S. et al. Biochemical characterization of Plasmodium complement factors binding protein for its role in immune modulation. The Biochemical journal 475, 2877-2891 (2018).
  50. Sharma, C. et al. Investigation of Multiple Resistance Mechanisms in Voriconazole-Resistant Aspergillus flavus Clinical Isolates from a Chest Hospital Surveillance in Delhi, India. Antimicrobial agents and chemotherapy 62(2018).
  51. Shakeel, T. et al. A consensus-guided approach yields a heat-stable alkane-producing enzyme and identifies residues promoting thermostability. The Journal of biological chemistry 293, 9148-9161 (2018).
  52. Pandey, R. et al. High throughput in silico identification and characterization of Plasmodium falciparum PRL phosphatase inhibitors. Journal of biomolecular structure & dynamics 36, 3531-3540 (2018).
  53. Gupta, V. et al. Role of CYP1B1, p.E229K and p.R368H mutations among 120 families with sporadic juvenile onset open-angle glaucoma. Graefe’s archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle
  54. Zeeshan, M. et al. Proteomic Identification and Analysis of Arginine-Methylated Proteins of Plasmodium falciparum at Asexual Blood Stages. Journal of proteome research 16, 368-383 (2017).
  55. Sanan-Mishra, N., Chakraborty, S., Gupta, D. & Mukherjee, S.K. RNAi suppressors: biology and mechanisms. 199-230 (Springer, 2017).
  56. Pandey, R., Kumar, P. & Gupta, D. KiPho: malaria parasite kinome and phosphatome portal. Database : the journal of biological databases and curation 2017(2017).
  57. Ogunmolu, F.E. et al. Comparative insights into the saccharification potentials of a relatively unexplored but robust Penicillium funiculosum glycoside hydrolase 7 cellobiohydrolase. Biotechnology for biofuels 10, 71-71 (2017).
  58. Kumar, P., Joy, J., Pandey, A. & Gupta, D. PRmePRed: A protein arginine methylation prediction tool. PloS one 12, e0183318-e0183318 (2017).
  59. Kaushik, A., Ali, S. & Gupta, D. Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways. Scientific reports 7, 40450-40450 (2017).
  60. Gupta, P. et al. Exploring Heme and Hemoglobin Binding Regions of Plasmodium Heme Detoxification Protein for New Antimalarial Discovery. Journal of medicinal chemistry 60, 8298-8308 (2017).
  61. Ghosh, S. et al. An RNAi-based high-throughput screening assay to identify small molecule inhibitors of hepatitis B virus replication. The Journal of biological chemistry 292, 12577-12588 (2017).
  62. Ali, M.F., Kaushik, A., Kapil, C., Gupta, D. & Jairajpuri, M.A. A hydrophobic patch surrounding Trp154 in human neuroserpin controls the helix F dynamics with implications in inhibition and aggregation. Scientific reports 7, 42987-42987 (2017).
  63. Kumar, R. & Gupta, D. Identification of CYP1B1-specific candidate inhibitors using combination of in silico screening, integrated knowledge-based filtering, and molecular dynamics simulations. Chemical Biology and Drug Design (2016).
  64. Kaur, I. et al. Widespread occurrence of lysine methylation in Plasmodium falciparum proteins at asexual blood stages. Scientific Reports 6(2016).
  65. Tajedin, L., Anwar, M., Gupta, D. & Tuteja, R. Comparative insight into nucleotide excision repair components of Plasmodium falciparum. DNA Repair 28(2015).
  66. Saraf, S. et al. 3′ and 5′ microRNA-end post-biogenesis modifications in plant transcriptomes: Evidences from small RNA next generation sequencing data analysis. Biochemical and Biophysical Research Communications 467(2015).
  67. Kaushik, A., Saraf, S., Mukherjee, S.K. & Gupta, D. miRMOD: A tool for identification and analysis of 5′ and 3′ miRNA modifications in Next Generation Sequencing small RNA data. PeerJ 2015(2015).
  68. Kaushik, A., Bhatia, Y., Ali, S. & Gupta, D. Gene network rewiring to study melanoma stage progression and elements essential for driving melanoma. PLoS ONE 10(2015).
  69. Jagga, Z. & Gupta, D. Machine learning for biomarker identification in cancer research developments toward its clinical application. Personalized Medicine 12(2015).
  70. Rastogi, A. & Gupta, D. GFF-Ex: A genome feature extraction package. BMC Research Notes 7(2014).
  71. Pandey, R. et al. Genome wide in silico analysis of Plasmodium falciparum phosphatome. BMC Genomics 15, 1024-1024 (2014).
  72. Mehrotra, S., Chugh, M., Singh, P.K., Gupta, D. & Malhotra, P. mRNA Splicing and Alternative Splicing BT – Encyclopedia of Malaria.  (eds. Kremsner, P.G. & Krishna, S.) 1-13 (Springer New York, New York, NY, 2014).
  73. Mastan, B.S., Kumari, A., Gupta, D., Mishra, S. & Kumar, K.A. Gene disruption reveals a dispensable role for Plasmepsin VII in the Plasmodium berghei life cycle. Molecular and Biochemical Parasitology 195(2014).
  74. Kaushik, A., Subramaniam, S. & Gupta, D. In silico characterization and molecular dynamics simulation of Pfcyc-1, a cyclin homolog of Plasmodium falciparum. Journal of Biomolecular Structure and Dynamics 32(2014).
  75. Kaur, R., Sharma, A., Gupta, D., Kalita, M. & Bhatnagar K, R. Bacillus thuringiensis Toxin, Cry1C interacts with 128HLHFHLP134 region of Aminopeptidase N of Agricultural Pest, Spodoptera litura. Process Biochemistry 49, 688-688 (2014).
  76. Jagga, Z. & Gupta, D. Supervised learning classification models for prediction of plant virus encoded RNA silencing suppressors. PLoS ONE 9(2014).
  77. Jagga, Z. & Gupta, D. Classification models for clear cell renal carcinoma stage progression, based on tumor RNAseq expression trained supervised machine learning algorithms. BMC Proc 8, S2-S2 (2014).
  78. Jackson, A.P. et al. The evolutionary dynamics of variant antigen genes in Babesia reveal a history of genomic innovation underlying host-parasite interaction. Nucleic Acids Research 42(2014).
  79. Kaushik, A. & Gupta, D. Protein folding grand challenge: Hydrophobic vs. hydrophilic forces. Journal of Biomolecular Structure and Dynamics 31(2013).
  80. Subramaniam, S., Mehrotra, M. & Gupta, D. Development of target focused library against drug target of P. falciparumusing SVM and Molecular docking. Journal of Cheminformatics 4, P48-P48 (2012).
  81. Nanni, L., Lumini, A., Gupta, D. & Garg, A. Identifying bacterial virulent proteins by fusing a set of classifiers based on variants of Chou’s Pseudo amino acid composition and on evolutionary information. IEEE/ACM Transactions on Computational Biology an
  82. Joshi, P.K. et al. Identification of mirtrons in rice using MirtronPred: A tool for predicting plant mirtrons. Genomics 99(2012).
  83. Gupta, S. et al. Molecular cloning and characterization of chikungunya virus genes from indian isolate of 2006 Outbreak. Journal of Pharmacy Research 5(2012).
  84. Subramaniam, S., Monica, M. & Gupta, D. Support Vector Machine Based Classification Model for Screening Plasmodium falciparum Proliferation Inhibitors and Non-Inhibitors. Biomedical Engineering and Computational Biology 3(2011).
  85. Subramaniam, S., Mehrotra, M. & Gupta, D. Support vector machine based prediction of P. falciparum proteasome inhibitors and development of focused library by molecular docking. Combinatorial Chemistry and High Throughput Screening 14(2011).
  86. Rathore, S. et al. Disruption of a mitochondrial protease machinery in Plasmodium falciparum is an intrinsic signal for parasite cell death. Cell Death and Disease 2(2011).
  87. Gupta, D. & Tuteja, N. Chaperones and foldases in endoplasmic reticulum stress signaling in plants. Plant Signaling and Behavior 6(2011).
  88. Rathore, S. et al. A cyanobacterial serine protease of Plasmodium falciparum is targeted to the apicoplast and plays an important role in its growth and development. Molecular Microbiology 77(2010).
  89. Rao, J.L. et al. Thermo and pH stable ATP-independent chaperone activity of heat-inducible Hsp70 from Pennisetum glaucum. Plant Signal Behav 5, 110-121 (2010).
  90. Ramana, J. & Gupta, D. Machine learning methods for prediction of CDK-inhibitors. PLoS ONE 5(2010).
  91. Ramana, J. & Gupta, D. FaaPred: A SVM-based prediction method for fungal adhesins and adhesin-like proteins. PLoS ONE 5(2010).
  92. Subramaniam, S., Mohmmed, A. & Gupta, D. Molecular modeling studies of the interaction between Plasmodium falciparum HslU and HslV subunits. Journal of Biomolecular Structure and Dynamics 26(2009).
  93. Ramana, J. & Gupta, D. ProtVirDB: A database of protozoan virulent proteins. Bioinformatics 25(2009).
  94. Ramana, J. & Gupta, D. LipocalinPred: A SVM-based method for prediction of lipocalins. BMC Bioinformatics 10(2009).
  95. Gangwar, D., Kalita, M.K., Gupta, D., Chauhan, V.S. & Mohmmed, A. A systematic classification of Plasmodium falciparum P-loop NTPases: Structural and functional correlation. Malaria Journal 8(2009).
  96. Subramaniam, S., Mehrotra, M. & Gupta, D. Virtual high throughput screening (vHTS)–a perspective. Bioinformation 3, 14-17 (2008).
  97. Kalita, M.K. et al. CyclinPred: A SVM-based method for predicting cyclin protein sequences. PLoS ONE 3(2008).
  98. Garg, A. & Gupta, D. VirulentPred: A SVM based prediction method for virulent proteins in bacterial pathogens. BMC Bioinformatics 9(2008).
  99. Ramasamy, G., Gupta, D., Mohmmed, A. & Chauhan, V.S. Characterization and localization of Plasmodium falciparum homolog of prokaryotic ClpQ/HslV protease. Molecular and Biochemical Parasitology 152(2007).
  100. Kalita, M.K., Ramasamy, G., Duraisamy, S., Chauhan, V.S. & Gupta, D. ProtRepeatsDB: A database of amino acid repeats in genomes. BMC Bioinformatics 7(2006).
  101. Gowthaman, R., Sekhar, D., Kalita, M.K. & Gupta, D. A database for Plasmodium falciparum protein models. Bioinformation 1, 50-51 (2005).
  102. Singh N, A., Gupta, D. & Jameel, S. Bioinformatic analysis of the SARS virus X1 protein shows it to be a calcium-binding protein. Current Science 86, 842-842 (2004).
  103. Ravi Chandra, B., Gowthaman, R., Raj Akhouri, R., Gupta, D. & Sharma, A. Distribution of proline-rich (PxxP) motifs in distinct proteomes: functional and therapeutic implications for malaria and tuberculosis. Protein Eng Des Sel 17, 175-182 (2004).
  104. Bahl, A. et al. PlasmoDB: The Plasmodium genome resource. A database integrating experimental and computational data. Nucleic Acids Research 31(2003).
  105. Kissinger, J.C. et al. The Plasmodium genome database. Nature 419(2002).
  106. Bahl, A. et al. PlasmoDB: The Plasmodium genome resource. An integrated database providing tools for accessing, analyzing and mapping expression and sequence data (both finished and unfinished). Nucleic Acids Research 30(2002).
  107. Pant, V. et al. Molecular characterization of the Rep protein of the blackgram isolate of Indian mungbean yellow mosaic virus. J Gen Virol 82, 2559-2567 (2001).
  108. Korkaya, H. et al. The ORF3 protein of hepatitis E virus binds to Src homology 3 domains and activates MAPK. J Biol Chem 276, 42389-42400 (2001).
  109. Agrawal, S., Gupta, D. & Panda, S.K. The 3′ end of hepatitis E virus (HEV) genome binds specifically to the viral RNA-dependent RNA polymerase (RdRp). Virology 282, 87-101 (2001).
  110. Ansari, I.H. et al. Cloning, sequencing, and expression of the hepatitis E virus (HEV) nonstructural open reading frame 1 (ORF1). Journal of medical virology 60, 275-283 (2000).
  111. Kothekar, V., Ashish, Gupta, D. & Kishore, R. Theoretical study of conformational flexibility of tuftsin in vacuum and in aqueous environment. Indian journal of biochemistry & biophysics 36, 14-28 (1999).
  112. Kothekar, V. & Gupta, D. Conformational flexibility of voltage gated dihydropyridine sensitive calcium channel in hydrated DMPC bilayer. Indian J Biochem Biophys 35, 273-283 (1998).
  113. Gupta, D. & Kothekar, V. Molecular dynamics simulation of the interaction of nifedipine and its meta and para NO2 analogs with a hydrated dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) bilayer. Journal of Molecular Structure: THEOCHEM 431, 17-31 (1998)
  114. Gupta, D. & Kothekar, V. 500 picosecond molecular dynamics simulation of amphiphilic polypeptide Ac(LKKL)4 NHEt with 1,2 di-mysristoyl-sn-glycero-3-phosphorylcholine (DMPC) molecules. Indian J Biochem Biophys 34, 501-511 (1997).
  115. Gupta, D. & Kothekar, V. Conformation of nifedipine in hydrated 1,2-di-myristoyl-sn-glycero-3-phosphorylcholine bilayer molecular dynamics simulation. Journal of Biosciences 22, 177-177 (1997).
  116. Kothekar, V., Mahajan, K., Raha, K. & Gupta, D. Molecular dynamics simulation of conformational flexibility of alamethicin fragments in aqueous and membranous environment. J Biomol Struct Dyn 14, 303-316 (1996).
  117. Kothekar, V. & Gupta, D. 200 picosecond molecular dynamics simulation of interaction of nifedipine with 1-2 dimyristoyl phosphatidylcholine membrane. Indian Journal of Biochemistry and Biophysics 31, 24-30 (1994).
  118. Kothekar, V. & Gupta, D. Molecular Mechanics Simulation of Ligand Induced Structural Changes in Biological Membrane. Int. J. Toxicol. Occup. Environ. Hlth. 1, 1-1 (1992).