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Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in the development of optimized small-molecule compounds. Current approaches cannot identify the protein targets of a compound and also detect the interaction surfaces between ligands and protein targets without prior labeling or modification. To address this limitation, we here develop LiP-Quant, a drug target deconvolution pipeline based on limited proteolysis coupled with mass spectrometry that works across species, including in human cells. We use machine learning to discern features indicative of drug binding and integrate them into a single score to identify protein targets of small molecules and approximate their binding sites. We demonstrate drug target identification across compound classes, including drugs targeting kinases, phosphatases and membrane proteins. LiP-Quant estimates the half maximal effective concentration of compound binding sites in whole cell lysates, correctly discriminating drug binding to homologous proteins and identifying the so far unknown targets of a fungicide research compound. Proteomics is often used to map protein-drug interactions but identifying a drug’s protein targets along with the binding interfaces has not been achieved yet. Here, the authors integrate limited proteolysis and machine learning for the proteome-wide mapping of drug protein targets and binding sites.

Methionine is a sulfur amino acid standing at the crossroads of several biosynthetic pathways. In fungi, the last step of methionine biosynthesis is catalyzed by a cobalamine-independent methionine synthase (Met6, EC 2.1.1.14). In the present work, we studied the role of Met6 in the infection process of the rice blast fungus, Magnaporthe oryzae. To this end MET6 null mutants were obtained by targeted gene replacement. On minimum medium, MET6 null mutants were auxotrophic for methionine. Even when grown in presence of excess methionine, these mutants displayed developmental defects, such as reduced mycelium pigmentation, aerial hypha formation and sporulation. They also displayed characteristic metabolic signatures such as increased levels of cysteine, cystathionine, homocysteine, S-adenosylmethionine, S-adenosylhomocysteine while methionine and glutathione levels remained unchanged. These metabolic perturbations were associated with the over-expression of MgCBS1 involved in the reversed transsulfuration pathway that metabolizes homocysteine into cysteine and MgSAM1 and MgSAHH1 involved in the methyl cycle. This suggests a physiological adaptation of M. oryzae to metabolic defects induced by the loss of Met6, in particular an increase in homocysteine levels. Pathogenicity assays showed that MET6 null mutants were non-pathogenic on both barley and rice leaves. These mutants were defective in appressorium-mediated penetration and invasive infectious growth. These pathogenicity defects were rescued by addition of exogenous methionine and S-methylmethionine. These results show that M. oryzae cannot assimilate sufficient methionine from plant tissues and must synthesize this amino acid de novo to fulfill its sulfur amino acid requirement during infection.

The avirulence gene ACE1 from the rice blast fungus Magnaporthe grisea encodes a polyketide synthase (PKS) fused to a nonribosomal peptide synthetase (NRPS) probably involved in the biosynthesis of a secondary metabolite recognized by Pi33 resistant rice (Oryza sativa) cultivars. Analysis of the M. grisea genome revealed that ACE1 is located in a cluster of 15 genes, of which 14 are potentially involved in secondary metabolism as they encode enzymes such as a second PKS-NRPS (SYN2), two enoyl reductases (RAP1 and RAP2) and a putative Zn(II)₂Cys₆ transcription factor (BC2). These 15 genes are specifically expressed during penetration into the host plant, defining an infection-specific gene cluster. A pORF3-GFP transcriptional fusion showed that the highly expressed ORF3 gene from the ACE1 cluster is only expressed in appressoria, as is ACE1. Phenotypic analysis of deletion or disruption mutants of SYN2 and RAP2 showed that they are not required for avirulence in Pi33 rice cultivars, unlike ACE1. Inactivation of other genes was unsuccessful because targeted gene replacement and disruption were inefficient at this locus. Overall, the ACE1 gene cluster displays an infection-specific expression pattern restricted to the penetration stage which is probably controlled at the transcriptional level and reflects regulatory networks specific to early stages of infection.

Methionine is a sulfur amino acid standing at the crossroads of several biosynthetic pathways. In fungi, the last step of methionine biosynthesis is catalyzed by a cobalamine-independent methionine synthase (Met6, EC 2.1.1.14). In the present work, we studied the role of Met6 in the infection process of the rice blast fungus, Magnaporthe oryzae. To this end MET6 null mutants were obtained by targeted gene replacement. On minimum medium, MET6 null mutants were auxotrophic for methionine. Even when grown in presence of excess methionine, these mutants displayed developmental defects, such as reduced mycelium pigmentation, aerial hypha formation and sporulation. They also displayed characteristic metabolic signatures such as increased levels of cysteine, cystathionine, homocysteine, S-adenosylmethionine, S-adenosylhomocysteine while methionine and glutathione levels remained unchanged. These metabolic perturbations were associated with the over-expression of MgCBS1 involved in the reversed transsulfuration pathway that metabolizes homocysteine into cysteine and MgSAM1 and MgSAHH1 involved in the methyl cycle. This suggests a physiological adaptation of M. oryzae to metabolic defects induced by the loss of Met6, in particular an increase in homocysteine levels. Pathogenicity assays showed that MET6 null mutants were non-pathogenic on both barley and rice leaves. These mutants were defective in appressorium-mediated penetration and invasive infectious growth. These pathogenicity defects were rescued by addition of exogenous methionine and S-methylmethionine. These results show that M. oryzae cannot assimilate sufficient methionine from plant tissues and must synthesize this amino acid de novo to fulfill its sulfur amino acid requirement during infection.

The avirulence gene ACE1 from the rice blast fungus Magnaporthe grisea encodes a polyketide synthase (PKS) fused to a nonribosomal peptide synthetase (NRPS) probably involved in the biosynthesis of a secondary metabolite recognized by Pi33 resistant rice (Oryza sativa) cultivars. * • Analysis of the M. grisea genome revealed that ACE1 is located in a cluster of 15 genes, of which 14 are potentially involved in secondary metabolism as they encode enzymes such as a second PKS-NRPS (SYN2), two enoyl reductases (RAP1 and RAP2) and a putative Zn(II)2Cys6 transcription factor (BC2). * • These 15 genes are specifically expressed during penetration into the host plant, defining an infection-specific gene cluster. A pORF3-GFP transcriptional fusion showed that the highly expressed ORF3 gene from the ACE1 cluster is only expressed in appressoria, as is ACE1. Phenotypic analysis of deletion or disruption mutants of SYN2 and RAP2 showed that they are not required for avirulence in Pi33 rice cultivars, unlike ACE1. Inactivation of other genes was unsuccessful because targeted gene replacement and disruption were inefficient at this locus. * • Overall, the ACE1 gene cluster displays an infection-specific expression pattern restricted to the penetration stage which is probably controlled at the transcriptional level and reflects regulatory networks specific to early stages of infection.

Chemoproteomics is a key technology to characterize the mode of action of drugs, as it directly identifies the protein targets of bioactive compounds and aids in developing optimized small-molecule compounds. Current unbiased approaches cannot directly pinpoint the interaction surfaces between ligands and protein targets. To address his limitation we have developed a new drug target deconvolution approach based on limited proteolysis coupled with mass spectrometry that works across species including human cells (LiP-Quant). LiP-Quant features an automated data analysis pipeline and peptide-level resolution for the identification of any small-molecule binding sites, Here we demonstrate drug target identification by LiP-Quant across compound classes, including compounds targeting kinases and phosphatases. We demonstrate that LiP-Quant estimates the half maximal effective concentration (EC50) of compound binding sites in whole cell lysates. LiP-Quant identifies targets of both selective and promiscuous drugs and correctly discriminates drug binding to homologous proteins. We finally show that the LiP-Quant technology identifies targets of a novel research compound of biotechnological interest.