Fragment-Based Drug Discovery: Lab Report

Categories: Chemistry

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Abstract

Fragment-Based Drug Discovery (FBDD) is a powerful approach for identifying potential drug candidates by screening libraries of fragment compounds. This report discusses the key aspects of FBDD, including screening methods, thermodynamics, and the use of multivalent systems.

Introduction

FBDD, developed in the 1990s, focuses on achieving tight binding to a drug target while minimizing time and maximizing efficiency. Unlike traditional drug discovery emphasizing potency, FBDD prioritizes efficient and complementary binding.

In FBDD, we start with a library of small compounds that resemble fragments of typical drug molecules.

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These fragments adhere to the 'rule of three,' ensuring their suitability. Due to their size, these fragments typically exhibit weak binding affinity. To compensate, we use higher ligand concentrations in our assays.

Detection Methods

FBDD relies on detection techniques to identify lead fragments. Initially, Nuclear Magnetic Resonance (NMR) with active isotopes is used, followed by X-ray crystallography. NMR provides preliminary binding location information, complemented by NOESY experiments. X-ray crystallography offers detailed insights into binding site orientation.

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While NMR is efficient for initial lead identification, crystallography offers higher precision.

Solvent mapping techniques in FBDD assist in locating binding hotspots on protein targets. Hotspots are residues capable of forming binding interactions with diverse functional groups present in fragments. Identifying hotspots efficiently guides target selection.

Molecular Surface-Casting and Solvent Mapping Combined with X-ray Crystallography (MSCS) allows us to map solvent distribution around the target. By superimposing data from multiple assays, we can identify dense ligand patches, indicating hotspots (See Table 1).

Table 1: Solvent Molecule Distribution on the Surface of Elastase
Hotspots	Several "hotspots" clearly indicated by organic solvents

Structure-Activity Relationship by NMR (SAR by NMR) employs active NMR isotopes to detect binding-induced chemical shift changes in protein residues (See Figure 2).

Figure 2: 2D 15N-HSQC NMR of Fragment Binding
Residues S70, D71, D72, L73 indicate binding (Color variations represent ligand concentrations)

FBDD is transitioning towards computational solvent mapping.

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Methods like Site Identification from Ligand Competitive Saturation (SILCS) use Molecular Dynamics to simulate a protein's behavior in aqueous conditions, accurately modeling structural flexibility (Citation 13).

Thermodynamics

FBDD simplifies thermodynamics in binding complexes. Enthalpy and entropy considerations become simpler when dealing with isolated fragments (Citation 10). Titration Calorimetry (Table 2) allows precise analysis of energy contributions from each fragment to binding affinity (Citation 17).

Table 2: Kd Values of Fragments Binding to hPNMT Enzyme
Temperature	Buffer	Enthalpy	Kd
25°C	20mM Tris/HCl	Calculated from ΔG = -RTln(Ka)	Calculated from ΔG = -RTln(Ka)

Proteins exhibit diverse interactions with water. Polar interactions, for instance, involve desolvation before binding, affecting their favorability (Citation 10).

Routes from Fragments to Drug

Multivalent System

Multivalency is a crucial concept where two molecules form multiple binding interactions at distinct sites. Linking fragments binding to separate but proximal locations significantly enhances affinity. Avidity, representing overall binding strength from multiple affinities, is calculated additively using Equation 1 (See Equation 1).

^{Equation 1:}

KdAvidity = (1/Kd,N+1/Kd,N-1+…+1/Kd,1)-1

Incorporating multivalency necessitates covering a primary binding hotspot to enable weak affinity fragments to bind elsewhere. NMR is the preferred technique for detecting these interactions due to the millimolar assay concentrations.

Alternatively, merging two fragments with overlapping binding regions of the target protein is a strategy. This involves combining structural elements from both fragments into a single structure.

Conclusion

FBDD offers several advantages over traditional drug discovery methods. It focuses on optimizing binding interactions one at a time, resulting in fully optimized orientations and enthalpy of binding. This approach minimizes the compromise often seen in simultaneous binding interactions, leading to suboptimal results. FBDD is more likely to produce hydrophilic binding interactions, which can provide valuable insights into drug design. By increasing the efficiency of High Throughput Screening (HTS), FBDD offers a broader diversity of hits, including weaker interactions that can be further analyzed and developed.

In summary, FBDD is a powerful strategy in drug discovery, providing efficient and complementary binding solutions, offering precise thermodynamic insights, and enabling the exploration of multivalent systems.