In silico Drug Design: some concepts & tools

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Drug discovery, chemical biology & precision medicine

There are many in silico tools in the field, for instance, to predict ADMET properties, ligand binding pockets, protein-protein interaction interface,...for drug repositioning or repurposing... to predict the 3D structure of a macromolecule, graft a sugar onto a protein structure, dock peptides, perform virtual screening, investigate point mutations observed in patients, for protein docking...simulation...machine learning methods... Antibody/vaccine design...


In a first step, it is important to select the in silico tools needed. This is directly linked to the type of questions you want to address, the type of project, the stage of the project and the data that you have to start with. In some cases, in silico approaches can not really help initially, some experiments have to be performed first and then, in silico tools take over and then back to vitro/vivo.

Small chemicals or peptides can be used for chemical biology or for drug discovery.

About 90% of projects entering clinical trials fail

If your project is about target-based screening, you will need one or several 3D structure. You can check the PDB to find some experimental 3D structures (Xray or NMR, Cryo-EM). If not, you can try to predict the 3D structure, for instance via comparative model building (e,g., online tool such as SWISS-MODEL) or you can use AlphaFold or RoseTTAfold or related. You can find many valuable standalone and online servers in the Shortlist page and in the sections Modeling Molecules, Simulations, etc. There are also tools to predict the 3D structures of RNA, DNA.... These tools somewhat belong to the field of structural bioinformatics or AI-powered structural bioinformatics.

Next, assuming you have a target macromolecule in 3D (often a protein but it can be RNA, DNA...), you may need a peptide or a small non-peptidic chemical compound or an antibody that binds to your target. If you know the binding pocket, then you can use structure-based virtual screening approaches or peptide - protein docking. In general you'll need to prepare a compound collection or you can use many available online. Once you have a collection, then, by using in silico screening or related approaches you should be able to propose a small list of molecules that will then need to be tested experimentally (important to think about the assays, how molecular mechanisms are going to be investigated...). Maybe you do not know the binding pocket and then you can use tools that will predict binding cavities and the so-called druggable pockets or PPI regions. The pocket may not be visible (cryptic pocket) and in this case you may need simulation, fragment docking, searching for hotspots... You can also try tools that attempt to transfer ligands into your pocket by comparing your pocket with pockets present in the PDB.

If you know a small molecule that binds to your target, you can search in databases other molecules that are similar to your query, then you can test in vitro these new molecules and build some SAR (see for instance the ligand-based virtual screening tools) (Chemoinformatics).
If you search a hit compound that could be used as starting point for drug discovery, you may need to predict some ADME-Tox properties (this can be very valuable also for chemical biology projects). You could also check if the molecules have structural alerts, PAINS or promiscous cmpds. According to such analysis, you may have to perform additional experiments to double check your initial results. Tools that can be of interest at this stage can belong to the QSAR section or the virtual screening sections, and obviously to the ADME-Tox section...(Chemoinformatics).

In most cases, you will have to look at databases to see if your target has been screened already or if your favorite compounds are already known to hit many targets. Databases that are open are for instance PubChem and ChemBL, these will be in the chemoinfo section.

You may want to know if your compound could bind to other secondary targets, often called off-targets and if the effect on health is not favorable, these secondary targets are called anti-targets. To do this, you can use tools that belong to the off-targets, repurposing, repositioning section. There, different approaches are available, from ligand-similarity searches to reverse docking...etc. If you use phenotypic screening, then several of these methods can also help to try to identify putative target(s).

As mentioned, to develop a new drug it is likely to take many years and success is far from certain. It has been estimated that it takes 13.5 years to bring a new molecular entity to market and the success rate for taking oncology drugs from phase I to approval by the US Food and Drug Administration (FDA) was only around 7%. These numbers change a bit in different reports but it gives an overall idea. Repositioning could thus be valuable in some cases as it builds on previous research, allowing compounds to progress more quickly as well as saving a substantial amount of money when it works. In silico strategies can help here. One concept that helps to understand repositioning is for instance the notion of polypharmacology that is one small molecule drug is likely to have an average of six to seven targets.

If you are interested in protein-protein interactions (Bioinformatics) and the modulation of these interactions with a small compound, you may need to use protein docking methods. You may want to see all the known interactions with your target and thus will need some "network" tools. If you have a 3D structure of your protein-protein complex, you may want to analyze the interface and predict hot-spot residues. We have some recent reviews about "in silico approaches and compound design", for instance about protein-protein interaction inhibitors, see Villoutreix et al. Molecular Informatics June 2014).

If your protein has point mutations (experimental or naturally occurring, ...idea of precision medicine), you may want to predict the impact of the amino acid substitutions on folding, function etc... Then again, you need a different set of tools and you can go to the sections Simulations and Mutations...(Bioinformatics section).

You may need to search patent databases, find databases on diseases, find tools to help represent and visualize the data, you may want to find some commercial tools... These will be in the section related tools.

Bioinformatics: Ligand binding pockets
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© Bruno Villoutreix. A first version of this Website was launched in 2006. Thank to Natacha Oliveira