# AutoDock Suite: Next Generation Environment for Drug Design

> **NIH NIH R01** · SCRIPPS RESEARCH INSTITUTE, THE · 2020 · $538,555

## Abstract

Project Summary
Computational docking is an essential tool for analysis of biomolecular structure and function and for the
discovery and development of new bioactive compounds. In particular, virtual screening is now widely used to
discover new compounds to bind and inhibit targets of medicinal interest. The AutoDock Suite of programs is
currently the most widely used, freely-available method for automated computational docking. This success is
the result of several aspects of the work performed under the previous granting period: the continued
development of the method to address problems of interest in the community, such as covalent docking and
active site prediction, and the development of user-friendly interfaces and user support that ensure that the
method is accessible to the widest community possible. As a result of this work, we have seen adoption and
extension of the AutoDock suite by expert users, using the suite as a platform for research in computational
chemistry and algorithm development, in parallel with widespread application by experimental chemists and
molecular biologists who are not experts in computational chemistry. In the proposed work, we will develop
AutoDock into a next generation tool for drug design and discovery. This will include extensions of the methods
of AutoDock to address the expanding and varied needs of a large user community. We will develop new
methods for ligand design that allow to generate novel compounds, employing specific constraints that will
ensure that such compounds are synthetically accessible, and predicted to have desirable pharmacological
properties. We will also continue and expand our strong commitment to user support, creating interfaces that
streamline use of the AutoDock suite by the user community, and providing effective support and training.

## Key facts

- **NIH application ID:** 10023186
- **Project number:** 5R01GM069832-17
- **Recipient organization:** SCRIPPS RESEARCH INSTITUTE, THE
- **Principal Investigator:** Stefano Forli
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $538,555
- **Award type:** 5
- **Project period:** 2004-01-01 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10023186

## Citation

> US National Institutes of Health, RePORTER application 10023186, AutoDock Suite: Next Generation Environment for Drug Design (5R01GM069832-17). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10023186. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*