Charuvaka Muvva

发表

In silico identification of miRNAs and their targets from the expressed sequence tags of Raphanus sativus

Kasoju Aruna, P. Ranjit, Charuvaka Muvva, 2012, Bioinformation.

Influenza A(H1N1)pdm09 virus: therapeutics and challenges

S. Saxena, S. Tiwari, Charuvaka Muvva, 2012 .

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A. S. Gaur, Deepak R. Bharti, Kumardeep Chaudhary, 2017, Journal of Chemical Sciences.

Role of Preferential Ions of Ammonium Ionic Liquid in Destabilization of Collagen.

N. Fathima, J. Raghava Rao, Charuvaka Muvva, 2016, The journal of physical chemistry. B.

Phosphonium based ionic liquids-stabilizing or destabilizing agents for collagen?

N. Fathima, J. Rao, Charuvaka Muvva, 2016 .

PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications

Agastya P. Bhati, U. D. Priyakumar, P. Pal, 2022, Scientific Data.

Governing the Inhibition of Reconstituted Collagen Type I Assemblies Mediated Through Noncovalent Forces of (±)-α Lipoic Acid.

N. Fathima, Charuvaka Muvva, K. Rasheeda, 2019, Langmuir : the ACS journal of surfaces and colloids.

Assessment of Amyloid Forming Tendency of Peptide Sequences from Amyloid Beta and Tau Proteins Using Force-Field, Semi-Empirical, and Density Functional Theory Calculations

N. A. Murugan, V. Subramanian, Charuvaka Muvva, 2021, International journal of molecular sciences.

PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications

Agastya P. Bhati, U. D. Priyakumar, P. Pal, 2022, Scientific Data.

Unraveling the Unbinding Pathways of Products Formed in Catalytic Reactions Involved in SIRT1-3: A Random Acceleration Molecular Dynamics Simulation Study

Charuvaka Muvva, N Arul Murugan, Venkata Surya Kumar Choutipalli, 2019, J. Chem. Inf. Model..

Structure-based virtual screening of novel, high-affinity BRD4 inhibitors.

V. Subramanian, Charuvaka Muvva, S. S. Raman, 2014, Molecular bioSystems.

Molecular docking and virtual screening for novel protein tyrosine phosphatase 1B (PTP1B) inhibitors

K. Geethanjali, Charuvaka Muvva, P. Rao, 2012, Bioinformation.

Performance of Force-Field- and Machine Learning-Based Scoring Functions in Ranking MAO-B Protein–Inhibitor Complexes in Relevance to Developing Parkinson’s Therapeutics

N. A. Murugan, J. Jeyakanthan, V. Subramanian, 2020, International journal of molecular sciences.

Assessing therapeutic potential of molecules: molecular property diagnostic suite for tuberculosis $$(\mathbf{MPDS}^{\mathbf{TB}})$$(MPDSTB)

Arun Sharma, Prasun Dutta, Devesh Kumar, 2017 .