Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser. One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing's capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of "re-dockings" with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing's docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening.
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http://dx.doi.org/10.1021/ci500322k | DOI Listing |
ACS Chem Biol
January 2025
Department of Chemistry, University of Florida, Gainesville Florida 32611, United States.
Small molecules are essential for investigating the pharmacology of membrane proteins and remain the most common approach for therapeutically targeting them. However, most experimental small molecule screening methods require ligands containing radiolabels or fluorescent labels and often involve isolating proteins from their cellular environment. Additionally, most conventional screening methods are suited for identifying compounds with moderate to higher affinities ( < 1 μM) and are less effective at detecting lower affinity compounds, such as weakly binding molecular fragments.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, via Marzolo 5, Padova 35131, Italy.
During the last 20 years, the fragment-based drug discovery approach gained popularity in both industrial and academic settings due to its efficient exploration of the chemical space. This bottom-up approach relies on identifying high-efficiency small ligands (fragments) that bind to a target binding site and then rationally evolve them into mature druglike compounds. To achieve such a task, researchers rely on accurate information about the ligand binding mode, usually obtained through experimental techniques, such as X-ray crystallography or computer simulations.
View Article and Find Full Text PDFComput Struct Biotechnol J
December 2024
Department of Medicinal Chemistry, Institute of Pharmacy, Martin-Luther-University of Halle-Wittenberg, Halle (Saale) 06120, Germany.
Reliable in silico prediction of fragment binding modes remains a challenge in current drug design research. Due to their small size and generally low binding affinity, fragments can potentially interact with their target proteins in different ways. In the current study, we propose a workflow aimed at predicting favorable fragment binding sites and binding poses through multiple short molecular dynamics simulations.
View Article and Find Full Text PDFCurr Drug Discov Technol
December 2024
Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Delhi Pharmaceutical Sciences and Research University, PushpViharSector-3, M-B Road, New Delhi, 110017, India.
Background: Computer-Aided Drug Design (CADD) approaches are essential in the drug discovery and development process. Both academic institutions and pharmaceutical and biotechnology corporations utilize them to enhance the efficacy of bioactive compounds.
Objective: This study aims to entice researchers by investigating the benefits of Computer-Aided Drug and Design (CADD) and its fundamental principles.
J Cheminform
January 2025
Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, UK.
Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that 'stitches' the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode.
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