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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Stalis: A Computational Method for Template-Based Ab Initio Ligand Design.

Hui Sun Lee¹, Wonpil Im¹

¹Departments of Biological Sciences and Bioengineering, Lehigh University, 111 Research Drive, Bethlehem, Pennsylvania 18015.

Journal of Computational Chemistry

|March 5, 2019

Summary

This summary is machine-generated.

Structure template-based ab initio ligand design solution (Stalis) generates virtual ligands for protein binding sites. Stalis enables fast screening and structural insights, aiding drug discovery and biological studies.

Keywords:

computer-aided drug discovery fragment-based drug design protein-ligand interaction template-based approach virtual screening

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Area of Science:

Biochemistry
Computational Biology
Drug Discovery

Background:

Protein-small molecule interactions are vital for biological functions.
Understanding these interactions is critical for basic science and developing new drugs.

Purpose of the Study:

To introduce Stalis, a novel knowledge-based approach for ab initio ligand design.
To evaluate Stalis's performance in virtual screening and its utility in drug discovery.

Main Methods:

Stalis utilizes structure templates from the Protein Data Bank for ligand and fragment libraries.
It generates virtual ligands that mimic the target binding site's shape and chemical properties.
Performance was benchmarked against receptor structure-based virtual screening using AutoDock Vina.

Main Results:

Ligand structure-based virtual screening with Stalis virtual ligands outperformed AutoDock Vina.
Stalis demonstrated reliable performance for computational high-throughput screening.
Virtual ligands from Stalis showed limitations in recognizing active compounds compared to crystal ligands due to lower structural resolution.

Conclusions:

Stalis facilitates drug discovery by enabling rapid ligand structure-based virtual screening.
The tool provides 3D ligand structures, offering structural insights into potential drug candidates.
Stalis serves as an efficient computational platform for high-throughput ligand design in biological and proteomic studies.