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Exploring protein hotspots by optimized fragment pharmacophores.

ABSTRACT: Fragment-based drug design has introduced a bottom-up process for drug development, with improved sampling of chemical space and increased effectiveness in early drug discovery. Here, we combine the use of pharmacophores, the most general concept of representing drug-target interactions with the theory of protein hotspots, to develop a design protocol for fragment libraries. The SpotXplorer approach compiles small fragment libraries that maximize the coverage of experimentally confirmed binding pharmacophores at the most preferred hotspots. The efficiency of this approach is demonstrated with a pilot library of 96 fragment-sized compounds (SpotXplorer0) that is validated on popular target classes and emerging drug targets. Biochemical screening against a set of GPCRs and proteases retrieves compounds containing an average of 70% of known pharmacophores for these targets. More importantly, SpotXplorer0 screening identifies confirmed hits against recently established challenging targets such as the histone methyltransferase SETD2, the main protease (3CLPro) and the NSP3 macrodomain of SARS-CoV-2.

SUBMITTER: Bajusz D

PROVIDER: S-EPMC8159961 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundFragment-based ligand design is used for the development of novel ligands that target macromolecules, most notably proteins. Central to its success is the identification of fragment binding sites that are spatially adjacent such that fragments occupying those sites may be linked to create drug-like ligands. Current experimental and computational approaches that address this problem typically identify only a limited number of sites as well as use a limited number of fragment types.MethodsThe site-identification by ligand competitive saturation (SILCS) approach is extended to the identification of fragment bindings sites, with the method termed SILCS-Hotspots. The approach involves precomputation of the SILCS FragMaps following which the identification of Hotspots, performed by identifying of all possible fragment binding sites on the full 3D structure of the protein followed by spatial clustering.ResultsThe SILCS-Hotspots approach identifies a large number of sites on the target protein, including many sites not accessible in experimental structures due to low binding affinities and binding sites on the protein interior. The identified sites are shown to recapitulate the location of known drug-like molecules in both allosteric and orthosteric binding sites on seven proteins including the androgen receptor, the CDK2 and Erk5 kinases, PTP1B phosphatase and three GPCRs; the β2-adrenergic, GPR40 fatty-acid binding and M2-muscarinic receptors. Analysis indicates the importance of considering all possible fragment binding sites, and not just those accessible to experimental methods, when identifying novel binding sites and performing ligand design versus just considering the most favorable sites. The approach is shown to identify a larger number of known binding sites of drug-like molecules versus the commonly used FTMap and Fpocket methods.General significanceThe present results indicate the potential utility of the SILCS-Hotspots approach for fragment-based rational design of ligands, including allosteric modulators.

Project description:BackgroundSecretory signal peptides (SPs) are well-known sequence motifs targeting proteins for translocation across the endoplasmic reticulum membrane. After passing through the secretory pathway, most proteins are secreted to the environment. Here, we describe the modification of an expression vector containing the SP from secreted acid phosphatase 1 (SAP1) of Leishmania mexicana for optimized protein expression-secretion in the eukaryotic parasite Leishmania tarentolae with regard to recombinant antibody fragments. For experimental design the online tool SignalP was used, which predicts the presence and location of SPs and their cleavage sites in polypeptides. To evaluate the signal peptide cleavage site as well as changes of expression, SPs were N-terminally linked to single-chain Fragment variables (scFv's). The ability of L. tarentolae to express complex eukaryotic proteins with highly diverse post-translational modifications and its easy bacteria-like handling, makes the parasite a promising expression system for secretory proteins.ResultsWe generated four vectors with different SP-sequence modifications based on in-silico analyses with SignalP in respect to cleavage probability and location, named pLTEX-2 to pLTEX-5. To evaluate their functionality, we cloned four individual scFv-fragments into the vectors and transfected all 16 constructs into L. tarentolae. Independently from the expressed scFv, pLTEX-5 derived constructs showed the highest expression rate, followed by pLTEX-4 and pLTEX-2, whereas only low amounts of protein could be obtained from pLTEX-3 clones, indicating dysfunction of the SP. Next, we analysed the SP cleavage sites by Edman degradation. For pLTEX-2, -4, and -5 derived scFv's, the results corresponded to in-silico predictions, whereas pLTEX-3 derived scFv's contained one additional amino-acid (AA).ConclusionsThe obtained results demonstrate the importance of SP-sequence optimization for efficient expression-secretion of scFv's. We could successfully demonstrate that minor modifications in the AA-sequence in the c-region of the natural SP from SAP1, based on in-silico predictions following the (-3, -1) rule, resulted in different expression-secretion rates of the protein of interest. The yield of scFv production could be improved close to one order of magnitude. Therefore, SP-sequence optimization is a viable option to increase the overall yield of recombinant protein production.

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Exploring protein hotspots by optimized fragment pharmacophores.

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