MONSTER: Inferring non-covalent interactions in macromolecular structures from atomic coordinate data

35Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

A web application for inferring potentially stabilizing non-bonding interactions in macromolecular structures from input atomic coordinate data is described. The core software, called Monster, comprises a PERL wrapper that takes advantage of scripts developed in- house as well as established software in the public domain to validate atomic coordinate files, identify interacting residues and assign the nature of these interactions. The results are assembled and presented in an intuitive and interactive graphical format. Potential applications of Monster range from mining and validating experimentally determined structures to guiding functional analysis. Non-commercial users can perform Monster analysis free of charge at http://monster.northwestern.edu. © Oxford University Press 2004; all rights reserved.

References Powered by Scopus

WHAT IF: A molecular modeling and drug design program

3437Citations
N/AReaders
Get full text

Satisfying hydrogen bonding potential in proteins

1956Citations
N/AReaders
Get full text

Reduced surface: An efficient way to compute molecular surfaces

1859Citations
N/AReaders
Get full text

Cited by Powered by Scopus

COCOMAPS: A web application to analyze and visualize contacts at the interface of biomolecular complexes

221Citations
N/AReaders
Get full text

Structure of the Newcastle disease virus hemagglutinin-neuraminidase (HN) ectodomain reveals a four-helix bundle stalk

149Citations
N/AReaders
Get full text

Free resources to assist structure-based virtual ligand screening experiments

104Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Salerno, W. J., Seaver, S. M., Armstrong, B. R., & Radhakrishnan, I. (2004). MONSTER: Inferring non-covalent interactions in macromolecular structures from atomic coordinate data. Nucleic Acids Research, 32(WEB SERVER ISS.). https://doi.org/10.1093/nar/gkh434

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 7

47%

Professor / Associate Prof. 5

33%

Researcher 3

20%

Readers' Discipline

Tooltip

Agricultural and Biological Sciences 8

53%

Biochemistry, Genetics and Molecular Bi... 4

27%

Computer Science 2

13%

Pharmacology, Toxicology and Pharmaceut... 1

7%

Save time finding and organizing research with Mendeley

Sign up for free