System and chemical biology

Advanced Bioinformatics & Chemistry

Advanced Bioinformatics and Chemistry is an international, open access, peer-reviewed journal that publishes: Original Research; Reviews; Hypothesis formation and commentaries in t More +

Editor-in-Chief: Hiroyuki Kurata

Advanced Bioinformatics & Chemistry

Volume 1 Number 1 2019

Table of Contents


Published online 26 August 2019
Manuscript-In-Press

In silico binding mechanism of Paynantheine, speciogynine and mitragynine with VEGF, TGFB, WNT, and NOTCH for anticancer potency

Aman Shah Abdul Majid B, Md Shamsuddin Sultan Khan A*

pp. 001-005

Mitragyna alkaloids adopt a binding pose at the VEGF, TGFB, WNT, and NOTCH receptor to produce anticancer potency through angiogenic pathway

Abstract | Full Text | Open Access Article

  

Published online 30 August 2019
Manuscript-In-Press

Molecular dynamics simulation and in silico binding study of CBS and IL17A outline modulation of tumor microenvironment

Md Shamsuddin Sultan Khan A*, Aman Shah Abdul Majid B, Amin Malik Shah Abdul Majid B

pp. 006-018

The tumorigenic reactions were more serious due to senescence of the tumor in the reaction of IL17A, CBS and MHCII molecules. 

Abstract | Full Text | Open Access Article

  

Published online 30 August 2019
Manuscript-In-Press

In Silico molecular mechanism determination with Falcipain-2 responsible for Antimalarial activity of (N-(5-Chloro-2-hydroxyphenyl)-2-(2-methyl-2-propanyl)-1,3-dioxo-5-isoindolinecarboxamide 

Farhana Mosaddqque A, B, Md Shamsuddin Sultan Khan C

pp. 019-024

The molecular interactions possessed the reason of being inhibitors of falcipain-2 as antimalarial agent.
 

Abstract | Full Text | Open Access Article

  

Published online 06 September 2019

Prediction of Protein–Metal Ion-Binding Sites Using Sequence Homology and Machine-Learning Methods

Zihan Tian 1, Cao Wei 1, Yutaka Moriwaki 1, Tohru Terada 1, Shugo Nakamura 1, Kazuya Sumikoshi 1, Fang Chun 1, and Kentaro Shimizu 1*

pp. 025-036

The sensitivity of the machine-learning method was 0.8239, and many metal ion-binding sites were predicted only by the machine-learning method.

Abstract | Full Text | PDF (2 MB) | Open Access Article

  

The peer-reviewed and edited version of record published online before inclusion in an issue

Published online 26 August 2019
Manuscript-In-Press

In silico binding mechanism of Paynantheine, speciogynine and mitragynine with VEGF, TGFB, WNT, and NOTCH for anticancer potency

Aman Shah Abdul Majid B, Md Shamsuddin Sultan Khan A*

Mitragyna alkaloids adopt a binding pose at the VEGF, TGFB, WNT, and NOTCH receptor to produce anticancer potency through angiogenic pathway

Abstract | Full Text

  

Published online 30 August 2019
Manuscript-In-Press

Molecular dynamics simulation and in silico binding study of CBS and IL17A outline modulation of tumor microenvironment

Md Shamsuddin Sultan Khan A*, Aman Shah Abdul Majid B, Amin Malik Shah Abdul Majid B

The tumorigenic reactions were more serious due to senescence of the tumor in the reaction of IL17A, CBS and MHCII molecules. 

Abstract | Full Text

  

Published online 30 August 2019
Manuscript-In-Press

In Silico molecular mechanism determination with Falcipain-2 responsible for Antimalarial activity of (N-(5-Chloro-2-hydroxyphenyl)-2-(2-methyl-2-propanyl)-1,3-dioxo-5-isoindolinecarboxamide 

Farhana Mosaddqque A, B, Md Shamsuddin Sultan Khan C

The molecular interactions possessed the reason of being inhibitors of falcipain-2 as antimalarial agent.
 

Abstract | Full Text

  

Published online 06 September 2019

Prediction of Protein–Metal Ion-Binding Sites Using Sequence Homology and Machine-Learning Methods

Zihan Tian 1, Cao Wei 1, Yutaka Moriwaki 1, Tohru Terada 1, Shugo Nakamura 1, Kazuya Sumikoshi 1, Fang Chun 1, and Kentaro Shimizu 1*

The sensitivity of the machine-learning method was 0.8239, and many metal ion-binding sites were predicted only by the machine-learning method.

Abstract | Full Text | PDF (2 MB) Open Access Article

  

These articles have been peer reviewed and accepted for publication. They are still in production and have not been edited, so may differ from the final published form.

Published online 26 August 2019 Manuscript-In-Press

In silico binding mechanism of Paynantheine, speciogynine and mitragynine with VEGF, TGFB, WNT, and NOTCH for anticancer potency

Aman Shah Abdul Majid B, Md Shamsuddin Sultan Khan A*

Mitragyna alkaloids adopt a binding pose at the VEGF, TGFB, WNT, and NOTCH receptor to produce anticancer potency through angiogenic pathway

Abstract


Published online 30 August 2019 Manuscript-In-Press

Molecular dynamics simulation and in silico binding study of CBS and IL17A outline modulation of tumor microenvironment

Md Shamsuddin Sultan Khan A*, Aman Shah Abdul Majid B, Amin Malik Shah Abdul Majid B

The tumorigenic reactions were more serious due to senescence of the tumor in the reaction of IL17A, CBS and MHCII molecules. 

Abstract


Published online 30 August 2019 Manuscript-In-Press

In Silico molecular mechanism determination with Falcipain-2 responsible for Antimalarial activity of (N-(5-Chloro-2-hydroxyphenyl)-2-(2-methyl-2-propanyl)-1,3-dioxo-5-isoindolinecarboxamide 

Farhana Mosaddqque A, B, Md Shamsuddin Sultan Khan C

The molecular interactions possessed the reason of being inhibitors of falcipain-2 as antimalarial agent.
 

Abstract


Published online 06 September 2019

Prediction of Protein–Metal Ion-Binding Sites Using Sequence Homology and Machine-Learning Methods

Zihan Tian 1, Cao Wei 1, Yutaka Moriwaki 1, Tohru Terada 1, Shugo Nakamura 1, Kazuya Sumikoshi 1, Fang Chun 1, and Kentaro Shimizu 1*

The sensitivity of the machine-learning method was 0.8239, and many metal ion-binding sites were predicted only by the machine-learning method.

Abstract


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Advanced Bioinformatics & Chemistry