BOC Sciences aims at developing the most accurate in silico methods to overcome bottlenecks in drug discovery and design innovative medicines to treat important disease.
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Virtual screening
1. Virtual Screening
Source page: https://www.bocsci.com/virtual-screening.html
Computational Simulations Lead to Accelerated Drug Design
In silico study in medicine takes advantage of computer simulations to predict the
protein-ligand binding site, reducing real laboratory experiments and accelerating
the drug discovery process in a more efficient and economical way. At BOC
Sciences, we focus on pharmaceutically interesting proteins that could become
targets for the next generation of pharmaceuticals. Working closely with our in-
house multi-disciplinary scientists in chemistry, biology and pharmaceutical
2. sciences, we have strong capabilities to accelerate the novel template design and
library compounds screening.
Development of new algorithms, for the detection of structurally similar protein
binding sites, enables us to search for local similarities in physicochemical
properties in different protein surface structures independently of sequence or
fold. Adapting specialized computational hardware and super high-performance
computer cluster with total 60 blades and 720 cores, our system is capable to
evaluate >1,000,000 compounds in less than 10 days.
Our scientific team has established virtual compound database for different client-
based projects with more than 2 million unique compounds, including ZINC,
MDDR, ACD, NCI, etc. Taking advantages of QSAR analysis, Similarity Search
and Scaffold Hopping for Structure Optimization, we provide virtual screening
services on molecular docking, molecular dynamics simulations, free energy
calculations and pharmacophore modeling. We have accomplished several
cutting edge industrial projects that involved a lot of programming. At BOC
Sciences, our expertise offers the best services in the combination of computing
and biochemistry.
Advantages of Our Services:
Integrated in silico and experimental team of multi-disciplinary experts in
chemistry, biology and computing sciences
Ligand-based and structure-based virtual screening
Super high-performance computer cluster with total 60 blades and 720 cores
Compound database containing over 10 million purchasable compounds
Compound database compliant with predefined filtering rules
Molecular docking, molecular dynamics simulations, free energy calculations
3D pharmacophore model building
Affinity prediction, fragment based approaches, handling of protein flexibility
Consideration of water and solvation effects
3. Virtual Screening
Structure-based virtual screening
The general scheme of a Structure-Based Virtual Screening (SBVS) strategy
starts with processing the 3D target structural information of pharmaceutical
protein interested. The target structure can be derived from experimental data (X-
ray, NMR or neutron scattering spectroscopy), homology modeling, or from
Molecular Dynamics (MD) simulations. The identification of ligand binding sites
on biological targets is incredibly important. Our expertise evaluates the
druggability of the receptor, the choice of binding site, the selection of the most
relevant protein structure, incorporating receptor flexibility, suitable assignment of
protonation states, and consideration of water molecules in a binding site. Our
highly experienced drug design professionals carefully choose the compound
library to be screened in the virtual screening (VS) exercise according to the
target in question, and preprocess libraries to assign the proper stereochemistry,
tautomeric, and protonation states.
4. Ligand-based virtual screening
In the absence of three-dimensional (3D) structures of potential drug targets,
ligand-based drug design is one of the most popular approaches for drug
discovery and lead optimization. Pharmacophore modelling, an ensemble of
steric and electronic features that is necessary to ensure the optimal
supramolecular interactions with a specific biological target and to trigger (or
block) its biological response, is a widely used tool in ligand-based drug design
and can provide predictive models suitable for lead compound optimization. At
BOC Sciences, we generate a pharmacophore model by superposing a set of
active molecules that are assumed to bind to the same target with the same
binding mode, and extracting common chemical features that are essential for
their bioactivity. Such a model can then be used to virtually screen libraries of
compounds with the aim of identifying potential new binders of the target of
interest. At BOC Sciences, we offer ligand-based virtual screening (LBVS)
services include similarity and substructure searching, quantitative structure-
activity relationships (QSAR), pharmacophore mapping, and machine learning.
5. Use of docking studies to aid prioritization novel templates
BOC Sciences aims at developing the most accurate in silico methods to
overcome bottlenecks in drug discovery and design innovative medicines to treat
important disease. Utilizing the tool of docking studies, we have strong
capabilities to prioritization novel templates, minimizing the real lab-based
experimental costs and driving the discovery process in a much more efficient
and economical way.