Skip to main content

Compiling inchi-1 to JavaScript

There are more and more software libraries being ported to JavaScript. The best example is JavaScript/HTML5 Citadel demo of the Unreal Engine. So why not to try with some chemical stuff? One of the most important chemical software libraries is IUPAC InChi. It's also extremely hard to reimplement as it's written in low-level, functional-style C. On the other hand it's just a few headers and source files, without any dependencies so it's a perfect use case for Emscripten.

Emscripten 'is an LLVM-to-JavaScript compiler'. It can be used as a drop-in replacement for standard tools such as gcc or make. Recently it got support for asm.js - optimizable, low-level subset of JavaScript.

I wasn't the first to come up with this idea - one of our local heroesNoel O'Boyle wrote a set of articles about translating the InChI code into JavaScript on his blog. I didn't know about his work during my experiments, which is good, because I took slightly different approach and came up with different results:
  1. I decided to compile inchi-1 binary (by exposing its main function) not the library, because, according to readme file in InChI distribution package, the binary 'does extensively check the input data and does provide diagnostic concerning input structure' so it's the only tool that can be used as an InChi generator with 100% guarantee of having correct results for all input files.
  2. I used '-O2 -s ASM_JS=1' flags to optimize speed.
  3. The resulting JavaScript code (emscripten generated html with embedded JS) weighted 2.8 MB and 732 kB after zip compression (all modern servers and browsers support compressed files). The original inchi-1 binary is about 1.1 MB large so this sounds reasonable.
Of course there are some drawbacks of my approach - the most obvious one is IO. inchi-1 is command line tool expecting a file or plain text as input and printing some text to stdoutand stderr. JavaScript doesn't have any standard input or output. This means that this behavior must be somehow mapped to browser environment. Emscripten maps output to specific textarea element which is reasonable. On the other hand any request for user input is mapped to javascript prompt window. This prompt can accept one line of text at time. Molfiles contain many lines so putting a molfile line by line is tedious.

The solution to this problem would be adding a file input to the webpage and accessing it via Javascript Blob interface. Having the files selected allocating some memory in Emscripten using hints from this SO question and pass it to process_single_input function from inchimain.c file (this should be exported instead of main).

So far I haven't solved the last issue. You can check proof-of-concept here. To use it, open link in your browser, open javascript console (Control-Shift-K on Firefox, Control-Shift-J on Chrome), then type (as two separate commands, pressing Enter after each one):

bla = Module.cwrap('process_single_input', 'string', 'string')
bla('bla -STDIO')

After that, the standard javascript prompt will pop up. You have to copy there your mol file - line by line. If the line should be empty (usually 1st and 3rd lines are) just press enter in the input box. After last line (M END) hit cancel instead of OK. Then select a checkbox suppressing all further popups and press OK. If you entered all mol file lines correctly you will see the result!



Noel O'Boyle said…
Nice. Here's the missing link:

Popular posts from this blog

A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEMBL d

ChEMBL 29 Released

  We are pleased to announce the release of ChEMBL 29. This version of the database, prepared on 01/07/2021 contains: 2,703,543 compound records 2,105,464 compounds (of which 2,084,724 have mol files) 18,635,916 activities 1,383,553 assays 14,554 targets 81,544 documents Data can be downloaded from the ChEMBL FTP site: .  Please see ChEMBL_29 release notes for full details of all changes in this release: New Deposited Datasets EUbOPEN Chemogenomic Library (src_id = 55, ChEMBL Document IDs CHEMBL4649982-CHEMBL4649998): The EUbOPEN consortium is an Innovative Medicines Initiative (IMI) funded project to enable and unlock biology in the open. The aims of the project are to assemble an open access chemogenomic library comprising about 5,000 well annotated compounds covering roughly 1,000 different proteins, to synthesiz

Identifying relevant compounds in patents

  As you may know, patents can be inherently noisy documents which can make it challenging to extract drug discovery information from them, such as the key targets or compounds being claimed. There are many reasons for this, ranging from deliberate obfuscation through to the long and detailed nature of the documents. For example, a typical small molecule patent may contain extensive background information relating to the target biology and disease area, chemical synthesis information, biological assay protocols and pharmacological measurements (which may refer to endogenous substances, existing therapies, reaction intermediates, reagents and reference compounds), in addition to description of the claimed compounds themselves.  The SureChEMBL system extracts this chemical information from patent documents through recognition of chemical names, conversion of images and extraction of attached files, and allows patents to be searched for chemical structures of interest. However, the curren

Julia meets RDKit

Julia is a young programming language that is getting some traction in the scientific community. It is a dynamically typed, memory safe and high performance JIT compiled language that was designed to replace languages such as Matlab, R and Python. We've been keeping an an eye on it for a while but we were missing something... yes, RDKit! Fortunately, Greg very recently added the MinimalLib CFFI interface to the RDKit repertoire. This is nothing else than a C API that makes it very easy to call RDKit from almost any programming language. More information about the MinimalLib is available directly from the source . The existence of this MinimalLib CFFI interface meant that we no longer had an excuse to not give it a go! First, we added a BinaryBuilder recipe for building RDKit's MinimalLib into Julia's Yggdrasil repository (thanks Mosè for reviewing!). The recipe builds and automatically uploads the library to Julia's general package registry. The build currently targe

New Drug Warnings Browser

As mentioned in the announcement post of  ChEMBL 29 , a new Drug Warnings Browser has been created. This is an updated version of the entity browsers in ChEMBL ( Compounds , Targets , Activities , etc). It contains new features that will be tried out with the Drug Warnings and will be applied to the other entities gradually. The new features of the Drug Warnings Browser are described below. More visible buttons to link to other entities This functionality is already available in the old entity browsers, but the button to use it is not easily recognised. In the new version, the buttons are more visible. By using those buttons, users can see the related activities, compounds, drugs, mechanisms of action and drug indications to the drug warnings selected. The page will take users to the corresponding entity browser with the items related to the ones selected, or to all the items in the dataset if the user didn’t select any. Additionally, the process of creating the join query is no