Designing efficacious, safe and differentiated molecules
“Think before you act” in pharmaceutical terms spells
“use in silico methods before going to the lab”.
Let Selvita’s experienced CADD team be your secret weapon when planning the drug discovery strategy.
Selvita’s computer-aided drug design (CADD) centre was created to foster collaborative research between medicinal chemists, biologists, biophysicists, structural biologists and computational scientists. In a drug discovery campaign, CADD is usually used for three major purposes:
- Physico-chemical and structural characterization of compounds from various libraries followed by filtering large compound libraries into smaller sets of predicted active compounds that can be tested experimentally;
- SAR analysis to guide the optimization of lead compounds, whether to increase its affinity or optimize drug metabolism and pharmacokinetic (DMPK) properties including absorption, distribution, metabolism, excretion, and the potential for toxicity (ADMET);
- Design novel compounds with a help of a miscellaneous set of computational tools.
CADD depends on the extent of structure and other information available regarding the target (enzyme/receptor/protein) and the ligands. The latest advancements like AI, QSAR, combinatorial chemistry, different databases and available new software tools provide a basis for designing of ligands and inhibitors that require specificity and novelty.
At hit identification, hit-to-lead or lead optimization stage our CADD can apply the following methods:
- Ligand-Based Drug Design, LBDD (flexible shape-based and/or field-based alignments with active molecules when 3D structure of target is unknown, pharmacophore modelling)
- Structure-Based Drug Design, SBDD (ligand-receptor interaction studies with known 3D structure of receptor, docking, molecular dynamics)
- Homology modelling of proteins
- Chemoinformatics
- In silico physico-chemical profiling
- In silico ADMET profiling
- Focused libraries design for screening or synthesis (in silico or in collaboration with our medicinal chemists)
- HTS data analysis (hit confirmation and hit expansion to provide missed starting points for the project)
- SAR analysis and proposal of new compounds within currently investigated and/or new chemical series (bioisostere replacements, scaffold hopping)
- Quantitative Structure-Activity Relationship (QSAR) analysis
- Quantitative Structure-Property Relationship (QSPR) analysis
- Support to NMR screening for Fragment Based Drug Discovery (FBDD)
- Support to synthetic chemistry with ab initio profiling of small molecules and chemical reactions
Most notably, our computational and medicinal chemists are working seamlessly together in interactive molecular design sessions, in order to rapidly generate hypotheses for molecular drug designs that are immediately assessed in suitable in silico models before molecules are prioritized and selected for syntheses in our laboratories or purchasing. Using a diverse set of available computational chemistry tools that are applicable for a given project, we assist the medical chemists in order to minimize the time, synthetic efforts and detours along the transformation process of a hit compound into a candidate.
In addition to the expertise in small molecule drug discovery, our CADD team is experienced in:
- Molecular modelling of macrocycles (larger natural non-Rule-of-5 compounds)
- Creating and optimizing focused macrocyclic libraries supported by in-house physico-chemical and ADMET profiling
- Performing macrolide-receptor interaction studies