Literature DB >> 1489919

Teaching macromolecular modeling.

S C Harvey1, R K Tan.   

Abstract

Training newcomers to the field of macromolecular modeling is as difficult as is training beginners in x-ray crystallography, nuclear magnetic resonance, or other methods in structural biology. In one or two lectures, the most that can be conveyed is a general sense of the relationship between modeling and other structural methods. If a full semester is available, then students can be taught how molecular structures are built, manipulated, refined, and analyzed on a computer. Here we describe a one-semester modeling course that combines lectures, discussions, and a laboratory using a commercial modeling package. In the laboratory, students carry out prescribed exercises that are coordinated to the lectures, and they complete a term project on a modeling problem of their choice. The goal is to give students an understanding of what kinds of problems can be attacked by molecular modeling methods and which problems are beyond the current capabilities of those methods.

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Year:  1992        PMID: 1489919      PMCID: PMC1262289          DOI: 10.1016/S0006-3495(92)81758-7

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  6 in total

Review 1.  Treatment of electrostatic effects in macromolecular modeling.

Authors:  S C Harvey
Journal:  Proteins       Date:  1989

2.  Prediction of the three-dimensional structure of Escherichia coli 30S ribosomal subunit: a molecular mechanics approach.

Authors:  A Malhotra; R K Tan; S C Harvey
Journal:  Proc Natl Acad Sci U S A       Date:  1990-03       Impact factor: 11.205

3.  Criteria that discriminate between native proteins and incorrectly folded models.

Authors:  J Novotný; A A Rashin; R E Bruccoleri
Journal:  Proteins       Date:  1988

4.  Molecular mechanics model of supercoiled DNA.

Authors:  R K Tan; S C Harvey
Journal:  J Mol Biol       Date:  1989-02-05       Impact factor: 5.469

5.  An analysis of incorrectly folded protein models. Implications for structure predictions.

Authors:  J Novotný; R Bruccoleri; M Karplus
Journal:  J Mol Biol       Date:  1984-08-25       Impact factor: 5.469

6.  Picosecond dynamics of tyrosine side chains in proteins.

Authors:  J A McCammon; P G Wolynes; M Karplus
Journal:  Biochemistry       Date:  1979-03-20       Impact factor: 3.162

  6 in total

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