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WIREs Comput Mol Sci
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Rational design of allosteric modulators: Challenges and successes

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Abstract Recent advances in structural biology and computational techniques have revealed allosteric mechanisms for an abundance of targets leading to the establishment of rational design of allosteric modulators as a new avenue for drug discovery. Considering that allostery is an intrinsic property of the protein conformational ensemble, allosteric drug design has the potential to develop into an innovative approach to modulate the dysregulation of therapeutic targets that are considered to be undruggable at their orthosteric site, explore strategic design opportunities to tackle new chemical space, or develop mutant‐specific therapies to target mutations occurring far from the enzyme active site. Traditionally, allosteric drug discovery has been performed through high‐throughput screening or through serendipitous discoveries; however, recent developments in structure‐based and ligand‐based methods have led to exciting advancements of designing bioactive allosteric ligands rationally. In this review article, we highlight the advantages and disadvantages of allosteric modulators and present structure‐based and ligand‐based drug design methodologies for the identification of allosteric binding sites and allosteric modulators. We also illustrate representative studies for the design allosteric modulators for proteins belonging to a wide range of protein families, also considering irreversible binding with covalent allosteric modulators. Additionally, we analyze challenges and successes in the rational design of allosteric inhibitors and activators. Finally, we present the future of rational allosteric ligand design with newly built computational tools that we expect to be applied in future studies, concluding to theoretical and practical guidelines for allosteric ligand design strategies and identify knowledge gaps that need to be addressed to improve efficiency in allosteric drug design. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Structure and Mechanism > Molecular Structures
Schematic representation of positive allosteric modulator (PAM), negative allosteric modulator (NAM), or silent allosteric modulator (SAM) binding on allosteric sites on a receptor and the effect on the protein orthosteric site. All binding sites can adopt two states, the relaxed (R), where the substrate/co‐factor can bind with high affinity, and the tense (T), where the substrate/co‐factor cannot bind or binds with low affinity. All possible combinations are expressed in a two letter code, for example, RT, where each letter denotes the state of the allosteric and the orthosteric sites, respectively. In the unbound conformational ensemble there are four possible combinations of protein states with different probabilities based on the free energy landscape. Binding of an allosteric modulator shifts the conformational ensemble towards the relaxed form (in case of a PAM) or the tense form (in case of a NAM) for the orthosteric site through preexisting allosteric pathways. Binding of a SAM in the allosteric site does not affect the orthosteric site, which can exist in either of the relaxed or the tense states. However, a SAM binds with high affinity acting as an antagonist to other allosteric modulators, blocking the allosteric regulation
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Proposed workflow for computational allosteric ligand design
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Possible mechanisms describing the binding of a ligand or a probe in a cryptic site. (a) In the conformational selection mechanism the protein must adopt a conformation in which the cryptic pocket is open in order for the ligand to bind. (b) In the induced‐fit mechanism the cryptic binding pocket is closed and conformational changes are only observed when the ligand encounters the pocket. (c) A mixed approach combines both mechanisms; first the cryptic pocket adopts a semi‐open form with the conformational selection mechanism, and then, the ligand selects these conformations and binds with the induced‐fit mechanism, fully opening the cryptic binding site66,513
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The crystal structure of Myosin‐2 (PDB: 2XO8) and the calculated allosteric pathway shown in CPK representation. With green we show the fragments produced by FTMap. In the inset, a close‐up of the predicted binding site next to Met486 (the sulfur atom of Met486 that could facilitate allosteric binding is shown in yellow)
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On the left panel the crystal structure of K‐Ras G12C mutant cocrystallized with allosteric covalent inhibitor ARS‐1620 and GDP (PDB ID: 5V9U) is depicted. On the right panel, the crystal structure of K‐Ras G12C mutant cocrystallized with allosteric covalent inhibitor AMG 510 (sotorasib) and GDP (PDB ID: 6OIM) is seen. Binding of AMG 510 opens up the cryptic pocket enclosed by H95/Y96/Q99, which are depicted in red
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Superimposed crystal structures of Tropomyosin receptor kinase A bound to three different allosteric inhibitors (PDBs: 6D1Y, 6D1Z, and 6D20). N‐terminal residues 481–483 were truncated for clarity
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The crystal structure of PDK1 with the orthosteric (blue) and allosteric PDK1‐interacting fragment‐pocket (red) binding sites in surface representation is visualized on the left (PDB: 4XX9). On the right, the 2D representation of the allosteric compound RF4 is depicted in red
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The crystal structure of M2 muscarinic acetylcholine receptor bound to the orthosteric agonist iperoxo and the positive allosteric modulator LY2119620 in an adjacent allosteric site above the orthosteric site (PDB: 4MQT) is visualized on the left. On the right, the 2D representation of LY2119620 (top) and iperoxo (bottom) are shown
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Structure and Mechanism > Molecular Structures
Structure and Mechanism > Computational Biochemistry and Biophysics

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