AlphaFold, allosteric, and orthosteric drug discovery: Ways forward

Nussinov, Ruth; Zhang, Mingzhen; Liu, Yonglan; Jang, Hyunbum

doi:10.1016/j.drudis.2023.103551

Cited by 33 publications

(28 citation statements)

References 136 publications

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“…These inhibitory effects can be directly inferred from the structural models. However, the effects of the interactions outside functional elements could be more challenging to interpret solely based on AlphaFold models (Nussinov et al, 2022(Nussinov et al, , 2023. Experimental studies have shown that many of these interactions allow for allosteric regulations of kinase activity.…”

Section: Discussionmentioning

confidence: 99%

Computational analysis of regulatory regions in human protein kinases

Pei,

Cong

2023

Protein Science

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Eukaryotic proteins often feature modular domain structures comprising of globular domains that are connected by linker regions and intrinsically disordered regions that may contain important functional motifs. The intramolecular interactions of globular domains and nonglobular regions can play critical roles in different aspects of protein function. However, studying these interactions and their regulatory roles can be challenging due to the flexibility of nonglobular regions, the long insertions separating interacting modules, and the transient nature of some interactions. Obtaining the experimental structures of multiple domains and functional regions is more difficult than determining structures of individual globular domains. High‐quality structural models generated by AlphaFold offer a unique opportunity to study intramolecular interactions in eukaryotic proteins. In this study, we systematically explored intramolecular interactions between human protein kinase domains and potential regulatory regions, including globular domains, N‐ and C‐terminal tails, long insertions, and distal nonglobular regions. Our analysis identified intramolecular interactions between human kinase domains and 35 different types of globular domains, exhibiting a variety of interaction modes that could contribute to orthosteric or allosteric regulation of kinase activity. We also identified prevalent interactions between human kinase domains and their flanking regions (N‐ and C‐terminal tails). These interactions exhibit group‐specific characteristics and can vary within each specific kinase group. Although long‐range interactions between kinase domains and nonglobular regions are relatively rare, structural details of these interactions offer new insights into the regulation mechanisms of several kinases, such as HASPIN, MAPK7, MAPK15 and SIK1B.This article is protected by copyright. All rights reserved.

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Section: Discussionmentioning

confidence: 99%

Computational analysis of regulatory regions in human protein kinases

Pei,

Cong

2023

Protein Science

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“…As shown in Table S10, no hot spot of the model overlaps with the small ligand quinazolin-4(1H)-one (JPZ). In the X-ray structure 4PPN the strongest hot spot overlapping with the ligand is 02 (12), which is not very strong, but hot spot 06( 8) is also at an overlapping location, and the site has a well-defined pocket (Figure S5). The RMSDs for the AF2 model downloaded from the AF database and truncated to the domain of interest are around 7 Å for both global and local alignments (Table 4).…”

Section: ■ Introductionmentioning

confidence: 99%

“…One of the most important potential applications is the use of AF2-generated models for drug discovery. , The most relevant method in question is the docking of small organic molecules to the models, allowing for high-throughput virtual screening. A number of recent studies have addressed the feasibility and potential accuracy of these applications.…”

Section: Introductionmentioning

confidence: 99%

Conservation of Hot Spots and Ligand Binding Sites in Protein Models by AlphaFold2

Bekar-Cesaretli,

Khan,

Nguyen

et al. 2024

J. Chem. Inf. Model.

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The neural network-based program AlphaFold2 (AF2) provides high accuracy structure prediction for a large fraction of globular proteins. An important question is whether these models are accurate enough for reliably docking small ligands. Several recent papers and the results of CASP15 reveal that local conformational errors reduce the success rates of direct ligand docking. Here, we focus on the ability of the models to conserve the location of binding hot spots, regions on the protein surface that significantly contribute to the binding free energy of the protein–ligand interaction. Clusters of hot spots predict the location and even the druggability of binding sites, and hence are important for computational drug discovery. The hot spots are determined by protein mapping that is based on the distribution of small fragment-sized probes on the protein surface and is less sensitive to local conformation than docking. Mapping models taken from the AlphaFold Protein Structure Database show that identifying binding sites is more reliable than docking, but the success rates are still 5% to 10% lower than based on mapping X-ray structures. The drop in accuracy is particularly large for models of multidomain proteins. However, both the model binding sites and the mapping results can be substantially improved by generating AF2 models for the ligand binding domains of interest rather than the entire proteins and even more if using forced sampling with multiple initial seeds. The mapping of such models tends to reach the accuracy of results obtained by mapping the X-ray structures.

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“…Among allosteric drugs, positive allosteric modulators (PAMs) and negative allosteric modulators (NAMs) affect the response of the protein to natural ligands or orthosteric agonists, while allosteric agonists and antagonists could directly activate and inhibit protein function, respectively. 1,15 A popular mechanism of these allosteric drugs is the ''population-shift'' model. It suggests that different conformations (such as active, half-active, and inactive) of a protein naturally exist, and the binding of allosteric ligands would stabilize certain conformations and ''shuffle'' the population of all conformations (Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Most drugs nowadays are orthosteric drugs. 1,2 Orthosteric agonists promote protein functions while orthosteric antagonists inhibit protein function, both by replacing the natural ligand in the orthosteric (active) site. Such direct binding mode is usually very effective.…”

Section: Introductionmentioning

confidence: 99%