Daniel J. Sindhikara

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This page has been superseded as of June 22nd, 2012.
This page will remain for a while but will not be updated.
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Advisor:
Professor Fumio Hirata
Department: Institute of Science and Engineering 総合理工学研究機構
Institution: Ritsumeikan University 立命館大学

Lab: Hirata Lab c/o Kikuchi Lab
Phone: (+81)
077-561-2617 ext 6841
Room: クリエーションコア・2F・計算生命化学研究室
Creation Core, 2nd Floor, Computational Biochemistry lab
Email: sindhikara(AT)gmail.com
Address:
立命館大学
びわこ
・くさつキャンパス
〒525-8577 滋賀県草津市野路東-1-1

Ritsumeikan University
Biwako-Kusatsu Campus
c/o Takeshi Kikuchi
1-1-1 Noji Higashi, Kusatsu, Shiga, 525-8577 Japan


“…it all works because Avogadro’s number is closer to infinity than to 10.”
R. Baierlein, Am. J. Phys., Vol 46, No. 10, October 1978.










I study and create analytical tools for computational study of biological molecules. Primarily I work in the classical/atomistic  regime making use of statistical mechanical techniques such as liquid state theory (e.g. 3D-RISM) and generalized ensemble theory (e.g. REMD) to ascertain biologically relevant information with both accuracy and efficiency.





I have been focusing on the application of the statistical theory of liquids known as 3D-RISM towards the study of molecular recognition.  I have been using 3D-RISM to study the 3D-distribution of solvent, ions, and small molecules in the presence of biomolecules. I am interested in both development of this theory as well new applications. Please contact me if you have an exciting project for which 3D-RISM can be applied.


Other work of mine focuses on the development enhanced sampling methods such as REMD, studies of protein allostery and statistical reweighting methods. Please see my publication list or software page for more details.



Research keywords:

3D-RISM, enhanced sampling, molecular dynamics, Monte Carlo, replica exchange molecular dynamics, QMMM, NikR, Langevin dynamics, AMBER, synchronization, convergence, ergodicity, metalloproteins, metal modeling, WHAM, Frypan sampling, RISM theory, molecular recognition, fragment-based design, drug design, neuraminidase