Bacterial resistance is one of the rising problems that needs to be addressed. To combat the antibiotic resistance of bacteria it is necessary to identify novel antibacterial agents by targeting novel pathways such as virulence and pathogenicity.
My main interest is to validate novel targets involved in bacterial virulence, metabolism, and growth using computational approaches. Additionally we are interested in fundamental biology of bacterial metabolism and virulence during infections. Our current focus is on Pseudomonas aeruginosa, an opportunistic pathogen.
We are happy to collaborate with other groups to utilise molecular modelling approaches such as docking, virtual screening, QSAR model development, Machine learning models, and Molecular Dynamics (MD) to understand the protein-small molecule interactions and binding mechanisms.
If you are interested for any Master’s projects or would like to pursue Doctoral studies in the field of antibacterial targets (proteins) or Molecular Modelling, please feel free to write to me.
Research groups
Article related to our research
Press Release of Research
Funding
Antibacterial agents
Publications
7/7 items-
Structural Characterization of LsrK as a Quorum Sensing Target and a Comparison between X-ray and Homology Models
Medarametla, Prasanthi; Kronenberger, Thales; Laitinen, Tuomo; Poso, Antti. 2021. Journal of chemical information and modeling. 61: 1346-1353 A1 Journal article (refereed), original research -
Identification and Design of New Antibacterial Agents Using Computational Approaches
Medarametla, Prasanthi. 2020. Publications of the University of Eastern Finland. Dissertations in Health Sciences G4 Doctoral dissertation (monograph) -
DPD-Inspired Discovery of Novel LsrK Kinase Inhibitors: An Opportunity To Fight Antimicrobial Resistance
Stotani, Silvia; Gatta, Viviana; Medarametla, Prasanthi; Padmanaban, Mohan; Karawajczyk, Anna; Giordanetto, Fabrizio; Tammela, Päivi; Laitinen, Tuomo; Poso, Antti; Tzalis, Dimitros; Collina, Simona. 2019. Journal of medicinal chemistry. 62: 2720-2737 A1 Journal article (refereed), original research -
Molecular Modelling Approaches to Antibacterial Drug Design and Discovery
Kaczor, Agnieszka A; Medarametla, Prasanthi; Bartuzi, Damian; Kondej, Magdalena; Matosiuk, Dariusz; Poso, Antti. Teoksessa: Rahman, Atta-ur; Choudhary, Iqbal M(toim.) , 2018. Frontiers in Anti-Infective Drug Discovery. s. 153-222. Bentham science publishers B2 Book section -
Structure-based virtual screening of LsrK kinase inhibitors to target quorum sensing
Medarametla, Prasanthi; Gatta, Viviana; Kajander, Tommi; Laitinen, Tuomo; Tammela, Päivi; Poso Antti. 2018. Chemmedchem. 13: 2400-2407 A1 Journal article (refereed), original research -
A QSAR and molecular modelling study towards new lead finding: polypharmacological approach to Mycobacterium tuberculosis
Janardhan S, John L, Prasanthi M, Poroikov V, Narahari Sastry G. 2017. Sar and qsar in environmental research. 28: 815-832 A1 Journal article (refereed), original research -
Structural and Functional Characterization of Malate Synthase G from Opportunistic Pathogen Pseudomonas aeruginosa
McVey Alyssa C, Medarametla Prasanthi, Chee Xavier, Bartlett Sean, Poso Antti, Spring David R, Rahman Taufiq, Welch Martin. 2017. Biochemistry. 56: 5539-5549 A1 Journal article (refereed), original research