# Molecular Recognition of Proteins and Ligand Design

> **NIH NIH R01** · YALE UNIVERSITY · 2021 · $400,109

## Abstract

Project Summary/Abstract
 The purpose of the research program is to develop improved computational methods for the simulation of
biomolecular systems and to apply them to discover new drugs for treatment of human diseases, especially
HIV/AIDS, inflammatory diseases, and cancer. The approach combines technology for computer-aided
molecular design, synthetic organic chemistry, biological assaying, and structural biology, i.e., crystallographic
determination of structures of the designed molecules bound to their protein targets by X-ray diffraction. The
PI’s group develops and applies widely used force fields, which are at the heart of biomolecular modeling, and
methods for computing free energy changes in solution. Discovery of initial active compounds (“hits”) is
facilitated by virtual screening and by de novo design with the ligand-growing program BOMB. Optimization of
the hits to yield potent, drug-like inhibitors is then guided by free-energy perturbation (FEP) calculations using
Monte Carlo (MC) statistical mechanics and molecular dynamics (MD) simulations for the inhibitors and
protein-inhibitor complexes in water. The viability of the approach has been well established through the
discovery of numerous potent inhibitors for multiple proteins. It serves as a model for efficient drug discovery
that is applicable to the pursuit of remedies for numerous diseases.
 The principal biomolecular targets are now macrophage migration inhibitory factor (MIF) and JAK2 kinase.
Disruption of the cytokine signaling of MIF has known potential for treatment of inflammatory diseases and
cancer, while reversal of the activating effect of the V617F mutation for JAK2 kinase is expected to provide
remedies for the majority of myeloproliferative disorders. Organic molecules are being designed, synthesized,
and tested to achieve these therapeutic goals. For MIF, substantial progress has been made with the discovery
of compounds in two chemical series that bind extraordinarily tightly to the protein and inhibit the growth of
prostate cancer cells. Lead optimization is also well along for JAK2 for which desired, selective binding to the
pseudokinase JH2 domain instead of the JH1 kinase domain has been achieved. Additional exploration of
these and new chemical series is planned to provide multiple, structurally diverse compounds that are suitable
for preclinical development. For both targets, the progress and interpretation of activity data are greatly
enhanced by the acquisition of high-resolution crystal structures of many protein-inhibitor complexes. In
addition, there continue to be numerous technical advances for the force fields and for computing free energies
of binding for the complexes, which are used to guide the selection of molecules to synthesize and test. The
research program is particularly notable for the close interplay of state-of-the-art computation and experiment
in one laboratory. The immediate feedback on the success of the computational predictio...

## Key facts

- **NIH application ID:** 10150016
- **Project number:** 5R01GM032136-38
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** William L. Jorgensen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $400,109
- **Award type:** 5
- **Project period:** 1990-07-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10150016

## Citation

> US National Institutes of Health, RePORTER application 10150016, Molecular Recognition of Proteins and Ligand Design (5R01GM032136-38). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10150016. Licensed CC0.

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