• Stars
    star
    142
  • Rank 258,495 (Top 6 %)
  • Language
    Jupyter Notebook
  • License
    Creative Commons ...
  • Created about 7 years ago
  • Updated 9 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Educational materials for, and related to, UC Irvine's Drug Discovery Computing Techniques course (PharmSci 175/275), currently taught by David Mobley.

Drug Discovery Computing Techniques: Educational Materials

This repository provides an introduction to computing techniques in drug discovery, and presents educational materials for David Mobley's course Drug Discovery Computing Techniques (PharmSci 175/275), taught at UC Irvine. Materials here focus on providing an introduction to computing techniques in drug discovery, including (but not limited to) topics covered in the course.

Repository goals

This repository has two main goals:

  1. To provide a general introduction to computing techniques used in drug discovery which will be broadly useful to the community, including providing access to course-specific materials which may be of broader utility.
  2. To give UCI PharmSci 175/275 students access to the materials they need for their course, as well as other relevant material which may be of interest.

In its initial stages, this will contain primarily material for item (2) as this provides the initial content for the repository. However, a goal is that this repository may also broaden to encompass material not directly related to the class (perhaps including related materials that others use in similar classes), and perhaps even could eventually provide tutorials which could be suitable for publication such as in the Living Journal of Computational Molecular Science.

Organization

In keeping with the two goals above, this repository is broadly organized to clearly delineate materials which students specifically need for UCI's PharmSci 175/275 from those which are here for other purposes, such as background material or tutorials on related or peripheral topics which are not specifically needed for the course. Usually each level of organization will have a README.md file, like this one, which explains what you can find there and how to navigate around.

Overall layout

Current organization is simple: At the base level is uci-pharmsci which provides materials relating to UCI's PharmSci 175/275 courses, and other-materials which contain other content.

Manifest

  • README.md: This document
  • LICENSE: A CC-BY 4.0 license giving others to reuse this content and do a variety of other things with it as long as credit is given.
  • other-materials: A directory which will contain materials not explicitly used in/required for UCI's PharmSci 175/275 course, but which may be referenced from there or from other courses.
  • uci-pharmsci: Content directly utilized in and (usually) required for UCI's PharmSci 175/275 course.

PharmSci 175/275

If you're here for UCI's PharmSci 175/275, please proceed directly to the uci-pharmsci directory and use the materials there.

Requirements

The content here has a variety of requirements which vary depending on the topic, especially if you want to use the tutorial/interactive material which involve the interactive Jupyter notebooks environment for Python. Many of the materials also require an OpenEye license, which is free for academics (though if you are in PharmSci 175/275, you can use our educational license for that course). PharmSci 175/275 students should begin with Getting Started for installation instructions.

Contributing

If you would like to contribute to this repository, please raise issues on the issue tracker or if you have changes you would like to propose to the material here, submit a pull request. Potentially, the repository could be broadened to include materials for other, related courses at different institutions; please contact us if you would like to propose this, but it's certainly a possibility we would like to pursue. We could potentially add folders at the base level for additional courses in addition to UCI's PharmSci 175/275.

Authors

In general, authorship will be noted in the individual documents presented. The current primary authors are:

  • David L. Mobley, UC Irvine

However, this material also draws heavily (with permission) on content adapted from M. Scott Shell's "Principles of modern molecular simulations" course at UC Santa Barbara; when material is adapted from Shell, this will typically be noted in the content itself and he should be acknowledged if it is reused in any form.

License

All written and graphical materials here are made available under a CC-BY 4.0 license, and all source code/software is made available under an MIT license. Both of these allow broad reuse with attribution.

Other related content

You may also wish to refer to the Volkamer lab's TeachOpenCADD and associated journal article which provides a fully open-source intro to CADD; many topics overlap.

Oliver Beckstein's Computational Methods in Physics course up online may also be helpful; notice it has a fairly extensive introduction to Python, debugging, NumPy, and various computational techniques.

Acknowledgments

We would like to particularly acknowledge:

  • M. Scott Shell for his excellent course material (see Authors)
  • OpenEye Scientific Software for extending a free academic license (which much of our content relies heavily on)
  • The previous students of PharmSci 275 for their contributions to this content and notes on what was unclear, etc.
  • James Haigh at OpenEye Scientific Software for answering many support questions over the years which helped me, both directly and indirectly, in developing the portions of this content utilizing OpenEye tools
  • John Chodera (MSKCC), from whom I (Mobley) learned a great deal when we were both at UCSF and afterwards. His contribution here is hard to quantify or even identify directly -- I've used so much of his code over the years, reading it, modifying it, repurposing it, and moving it around from one place to another that possibly some snippets from his code occur in some of the materials here without me realizing it. Certainly some of this material draws heavily on openmoltools which Chodera and I and others have both contributed substantially to, and which draws on even earlier material we began preparing when we were both at UCSF.
  • The many contributors to openmoltools

Additional acknowledgments will be given in specific content.

More Repositories

1

alchemical-analysis

An open tool implementing some recommended practices for analyzing alchemical free energy calculations
Python
111
star
2

basic_simulation_training

A document for the Living Journal of Computational Molecular Science (LiveCoMS) which describes basic training for molecular simulations (oriented towards molecular dynamics (MD)), providing some training itself and linking out to other helpful information elsewhere. The intent is that this provide information on the prerequisites which will be required for understanding/following many of the other "best practices" documents being prepared.
TeX
105
star
3

FreeSolv

Experimental and calculated small molecule hydration free energies
Python
98
star
4

benchmarksets

Benchmark sets for binding free energy calculations: Perpetual review paper, discussion, datasets, and standards
TeX
41
star
5

Lomap

Alchemical mutation scoring map
Python
36
star
6

Training

Lab policies, training, style guides, etc.
35
star
7

blues

Applications of nonequilibrium candidate Monte Carlo (NCMC) to ligand binding mode sampling
Python
33
star
8

SolvationToolkit

In-house tools for setting up arbitrary solute-solvent mixtures for simulation in GROMACS, Amber, OpenMM or other codes
Python
31
star
9

GuthrieSolv

Experimental small molecule hydration free energy dataset
Python
30
star
10

SeparatedTopologies

Exploratory work on free energy calculations with GROMACS using "separated topologies" approach (Rocklin et al., 2013).
Python
22
star
11

chemper

Repository for Chemical Perception Sampling Tools
Python
19
star
12

HiMap

High Information Mapper (HiMap), successor of the Lead Optimization Mapper (LOMAP)
Python
16
star
13

alchemical-setup

Python
15
star
14

benchmarkff

Compare optimized geometries and energies from various force fields with respect to a QM reference.
Python
13
star
15

DEL_analysis

Code to analyze the data from DNA-encoded libraries (DELs)
Jupyter Notebook
9
star
16

off-ffcompare

Compare molecular structures after energy minimization in various force fields.
Jupyter Notebook
8
star
17

D3R-2018-AutoDock-MMGBSA

binding affinity ranking using MM-GBSA and AutoDock score in D3R 2018
Shell
4
star
18

mobleylab.org

Lab website
SCSS
4
star
19

quanformer

quanformer: quantum mechanical analysis of molecular conformers
Python
3
star
20

SMIRNOFF_paper_code

Code/tools relating to the initial SMIRNOFF format paper
Jupyter Notebook
3
star
21

qm-theory-benchmark

Jupyter Notebook
3
star
22

openff-spellbook

Handy functionality for working with OpenFF data
Python
3
star
23

thermoML_data

Jupyter Notebook
2
star
24

blues-water-hopping-paper

Contains files for blues-water-hopping paper
Python
2
star
25

off_nitrogens

Exploring the planar or pyramidal nature of conjugated nitrogens
Python
2
star
26

lysozyme_binding

Aggregator of binding data of small molecules to model binding sites in T4 lysozyme mutants, as popularized by Matthews, Shoichet and others.
Python
2
star
27

wbointerpolation

Analysis scripts for the development of wiberg bond order interpolated parameters in the Open Force Field.
Jupyter Notebook
2
star
28

orphans

Orphaned tools/scripts that might be useful but don't currently have a good home
Python
2
star
29

slow-rotations

Python
2
star
30

DEL_BB_design

Computational enumeration of DNA-encoded libraries with various building block filtering and selection strategies
Jupyter Notebook
2
star
31

fitting-exp

Python
1
star
32

gmx_fileprep

Scripts for local gromacs input file preparation
1
star
33

gromacs-binding-scripts

Scripts relating to setup of binding studies for the GROMACS simulation package
1
star
34

yank-restraints

Benchmarking project testing different restraints schemes for free energy calculations with Yank
1
star
35

PME-RF-benchmark

Supporting information for a paper benchmarking PME vs RF performance for relative free energies
1
star
36

waterNES

Workflows to calculate relative free energies using non-equilibrium switching for buried water molecules
Python
1
star
37

Hydroxynator

Adjusts topology files with GAFF to have GAFF-DC charges
Python
1
star
38

buried-water-electrostatics

We examined the electrostatic potential at the locations of buried waters within proteins to see if this exhibited any asymmetric behavior (previous work we had done suggested perhaps it might) and found none. Here's the code to reproduce.
Python
1
star