Pub Date : 2023-05-10DOI: 10.3389/fddsv.2023.1185679
Alan H Fairlamb, Susan Wyllie
Understanding the target and mode of action of compounds identified by phenotypic screening can greatly facilitate the process of drug discovery and development. Here, we outline the tools currently available for target identification against the neglected tropical diseases, human African trypanosomiasis, visceral leishmaniasis and Chagas' disease. We provide examples how these tools can be used to identify and triage undesirable mechanisms, to identify potential toxic liabilities in patients and to manage a balanced portfolio of target-based campaigns. We review the primary targets of drugs that are currently in clinical development that were initially identified via phenotypic screening, and whose modes of action affect protein turnover, RNA trans-splicing or signalling in these protozoan parasites.
{"title":"The critical role of mode of action studies in kinetoplastid drug discovery.","authors":"Alan H Fairlamb, Susan Wyllie","doi":"10.3389/fddsv.2023.1185679","DOIUrl":"10.3389/fddsv.2023.1185679","url":null,"abstract":"<p><p>Understanding the target and mode of action of compounds identified by phenotypic screening can greatly facilitate the process of drug discovery and development. Here, we outline the tools currently available for target identification against the neglected tropical diseases, human African trypanosomiasis, visceral leishmaniasis and Chagas' disease. We provide examples how these tools can be used to identify and triage undesirable mechanisms, to identify potential toxic liabilities in patients and to manage a balanced portfolio of target-based campaigns. We review the primary targets of drugs that are currently in clinical development that were initially identified via phenotypic screening, and whose modes of action affect protein turnover, RNA trans-splicing or signalling in these protozoan parasites.</p>","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614965/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10173670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-09DOI: 10.3389/fddsv.2023.1182146
Irene Tang, L. Schwimmer, Shenda Gu, Wei Wei Prior, Hieu Van Tran, Allan Chan, Anna McClain, C. Fraser, Chunyang Sun, M. Si, Guijiang Wang, Yunxia Zhao, Ning Zhang, Jiayu Fu, Mengxin Liu, Chuanzeng Cao, Shihao Chen
Cell surface molecules PD-L1 and CD47 are potent inhibitors of adaptive and innate anti-cancer immunity. We sought to generate a safe, therapeutic, bispecific antibody specifically targeting, and blocking both PD-L1 and CD47 inhibitory activity. Novel anti-PDL-1 and anti-CD47 antibodies with favorable inhibitory activity, were humanized and constructed into a unique bi-specific antibody intended for clinical use. Previous pre-clinical and clinical studies using anti-CD47 antibodies indicated anemia and thrombocytopenia as potential risks. QL401 is a PD-L1 x CD47 bispecific antibody engineered to reduce effect on red blood cells while retaining potent phagocytic activation of macrophages in vitro and delayed tumor growth in vivo. QL401 comprises three functional components: a PD-L1 binding Fab arm, a CD47 binding scFv arm, and a human IgG4 backbone. The PD-L1 binding arm provides both tumor targeting and blocking of PD-1 for reactivating T cells. The CD47 arm blocks the binding of SIRPα, while the IgG4 Fc retains Fc gamma receptor binding to provide a phagocytic signal. In preclinical efficacy studies, QL401 potently blocked SIRPα to promote phagocytosis of tumor cells with sub-nanomolar potency. In vivo efficacy studies in mouse xenograft tumor models showed QL401 to be comparable or superior to PD-L1 or CD47 monoclonal antibodies alone or in combination. In vitro safety evaluation of QL401 showed significantly reduced binding and phagocytosis of red blood cells, in contrast to CD47 monoclonal antibodies. In addition, QL401 did not induce hemagglutination. In non-human primates, QL401 was well tolerated up to 100 mg/kg without reduction of red blood cells or platelets below the normal range. QL401 is presently in a human phase I safety study.
细胞表面分子PD-L1和CD47是适应性和先天抗癌免疫的有效抑制剂。我们寻求产生一种安全、治疗性、双特异性的抗体，特异性靶向并阻断PD-L1和CD47的抑制活性。将具有良好抑制活性的新型抗pdl -1和抗cd47抗体人源化并构建成一种独特的双特异性抗体，用于临床应用。先前使用抗cd47抗体的临床前和临床研究表明，贫血和血小板减少是潜在的风险。QL401是一种PD-L1 x CD47双特异性抗体，旨在减少对红细胞的影响，同时在体外保持巨噬细胞的有效吞噬激活，并在体内延缓肿瘤生长。QL401由三个功能组件组成:PD-L1结合Fab臂、CD47结合scFv臂和人IgG4骨干。PD-L1结合臂提供肿瘤靶向和阻断PD-1来重新激活T细胞。CD47臂阻断SIRPα的结合，而IgG4 Fc保留Fc γ受体结合以提供吞噬信号。在临床前疗效研究中，QL401有效阻断SIRPα，以亚纳摩尔的效力促进肿瘤细胞的吞噬。在小鼠异种移植肿瘤模型中的体内疗效研究表明，QL401与单独或联合使用的PD-L1或CD47单克隆抗体相当或优于单克隆抗体。体外安全性评价显示，与CD47单克隆抗体相比，QL401对红细胞的结合和吞噬作用显著降低。此外，QL401不诱导血凝。在非人类灵长类动物中，QL401耐受性良好，高达100 mg/kg，红细胞或血小板未减少到正常范围以下。QL401目前正在进行人体I期安全性研究。
{"title":"Generation of a potent anti-PD-L1-CD47 bispecific antibody with a strong therapeutic and safety profile for cancer immunotherapy","authors":"Irene Tang, L. Schwimmer, Shenda Gu, Wei Wei Prior, Hieu Van Tran, Allan Chan, Anna McClain, C. Fraser, Chunyang Sun, M. Si, Guijiang Wang, Yunxia Zhao, Ning Zhang, Jiayu Fu, Mengxin Liu, Chuanzeng Cao, Shihao Chen","doi":"10.3389/fddsv.2023.1182146","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1182146","url":null,"abstract":"Cell surface molecules PD-L1 and CD47 are potent inhibitors of adaptive and innate anti-cancer immunity. We sought to generate a safe, therapeutic, bispecific antibody specifically targeting, and blocking both PD-L1 and CD47 inhibitory activity. Novel anti-PDL-1 and anti-CD47 antibodies with favorable inhibitory activity, were humanized and constructed into a unique bi-specific antibody intended for clinical use. Previous pre-clinical and clinical studies using anti-CD47 antibodies indicated anemia and thrombocytopenia as potential risks. QL401 is a PD-L1 x CD47 bispecific antibody engineered to reduce effect on red blood cells while retaining potent phagocytic activation of macrophages in vitro and delayed tumor growth in vivo. QL401 comprises three functional components: a PD-L1 binding Fab arm, a CD47 binding scFv arm, and a human IgG4 backbone. The PD-L1 binding arm provides both tumor targeting and blocking of PD-1 for reactivating T cells. The CD47 arm blocks the binding of SIRPα, while the IgG4 Fc retains Fc gamma receptor binding to provide a phagocytic signal. In preclinical efficacy studies, QL401 potently blocked SIRPα to promote phagocytosis of tumor cells with sub-nanomolar potency. In vivo efficacy studies in mouse xenograft tumor models showed QL401 to be comparable or superior to PD-L1 or CD47 monoclonal antibodies alone or in combination. In vitro safety evaluation of QL401 showed significantly reduced binding and phagocytosis of red blood cells, in contrast to CD47 monoclonal antibodies. In addition, QL401 did not induce hemagglutination. In non-human primates, QL401 was well tolerated up to 100 mg/kg without reduction of red blood cells or platelets below the normal range. QL401 is presently in a human phase I safety study.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91355037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-27DOI: 10.3389/fddsv.2023.1157688
D. Gambino
COVID-19, the severe acute respiratory syndrome caused by Coronavirus (SARS-CoV-2) and identified for the first time in China in 2019, was recognized in 2020 as a global pandemic by the World Health Organization (Wu et al., 2020; WHO, 2023). Although elder people and all those with underlying medical conditions like cardiovascular disease, diabetes, chronic respiratory disease, or cancer are more likely to develop serious illness, people at any age can become seriously ill or die (WHO, 2023). The efforts of pharmaceutical companies and academia have successfully led to several vaccines against this virus in an unprecedented short period of time. Although vaccines provide protection to healthy people, they could be not effective for immune compromised individuals or those bearing some risky pathological comorbidities. Additionally, mutations could generate viral variants unaffected by currently available vaccines. Therefore, new chemotherapeutic agents are urgently needed for the treatment of SARS-CoV-2 in order to reduce virus dissemination and mortality. Although huge efforts are beingmade since 2020 towards the development of new drugs or the repurposing of already approved drugs to other targets, which would lead to a significant drop in the approval time of these drugs, drugs for the treatment of COVID-19 are not yet a reality (Ashburn and Thor, 2004; Nosengo, 2016; WHO, 2023). At present, there is a clinical need for direct-acting antivirals targeting SARS-CoV-2 to complement existing therapeutic strategies. Accordingly, the aim of this Research Topic of Frontiers in Drug Discovery, Antiinfective Agents, is to collect latest research on the topic focused on:
新冠肺炎是由冠状病毒（SARS-CoV-2）引起的严重急性呼吸综合征，于2019年在中国首次被发现，2020年被世界卫生组织确认为全球大流行（Wu et al.，2020；世界卫生组织，2023）。尽管老年人和所有患有心血管疾病、糖尿病、慢性呼吸道疾病或癌症等潜在疾病的人更有可能患上严重疾病，但任何年龄的人都可能患上重症或死亡（世界卫生组织，2023）。制药公司和学术界的努力在前所未有的短时间内成功研制出了几种针对这种病毒的疫苗。尽管疫苗为健康人提供了保护，但对免疫受损的个体或患有一些危险病理合并症的人可能无效。此外，突变可能产生不受当前可用疫苗影响的病毒变体。因此，迫切需要新的化疗药物来治疗严重急性呼吸系统综合征冠状病毒2型，以减少病毒传播和死亡率。尽管自2020年以来，正在为开发新药或将已批准的药物重新用于其他目标做出巨大努力，这将导致这些药物的批准时间大幅缩短，但治疗新冠肺炎的药物尚未成为现实（Ashburn和Thor，2004；诺森戈，2016；世界卫生组织，2023）。目前，临床上需要针对严重急性呼吸系统综合征冠状病毒2型的直接作用抗病毒药物来补充现有的治疗策略。因此，本研究主题“药物发现的前沿，抗感染剂”的目的是收集关于以下主题的最新研究：
{"title":"Editorial: Development/repurposing of drugs to tackle the multiple variants of SARS-CoV-2","authors":"D. Gambino","doi":"10.3389/fddsv.2023.1157688","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1157688","url":null,"abstract":"COVID-19, the severe acute respiratory syndrome caused by Coronavirus (SARS-CoV-2) and identified for the first time in China in 2019, was recognized in 2020 as a global pandemic by the World Health Organization (Wu et al., 2020; WHO, 2023). Although elder people and all those with underlying medical conditions like cardiovascular disease, diabetes, chronic respiratory disease, or cancer are more likely to develop serious illness, people at any age can become seriously ill or die (WHO, 2023). The efforts of pharmaceutical companies and academia have successfully led to several vaccines against this virus in an unprecedented short period of time. Although vaccines provide protection to healthy people, they could be not effective for immune compromised individuals or those bearing some risky pathological comorbidities. Additionally, mutations could generate viral variants unaffected by currently available vaccines. Therefore, new chemotherapeutic agents are urgently needed for the treatment of SARS-CoV-2 in order to reduce virus dissemination and mortality. Although huge efforts are beingmade since 2020 towards the development of new drugs or the repurposing of already approved drugs to other targets, which would lead to a significant drop in the approval time of these drugs, drugs for the treatment of COVID-19 are not yet a reality (Ashburn and Thor, 2004; Nosengo, 2016; WHO, 2023). At present, there is a clinical need for direct-acting antivirals targeting SARS-CoV-2 to complement existing therapeutic strategies. Accordingly, the aim of this Research Topic of Frontiers in Drug Discovery, Antiinfective Agents, is to collect latest research on the topic focused on:","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45053551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-21DOI: 10.3389/fddsv.2023.1082058
Bach-Ngan Nguyen, Florian Tieves, Florian G. Neusius, H. Götzke, L. Schmitt, C. Schwarz
The application of long-chained peptides (+30 aa) and relatively short proteins (<300 aa) has experienced an increasing interest in recent years. However, a reliable production platform is still missing since manufacturing is challenged by inherent problems such as mis-folding, aggregation, and low production yields. And neither chemical synthesis nor available recombinant approaches are effective and efficient. This in particular holds true for disulfide-rich targets where the correct isomer needs to be formed. With the technology Numaswitch, we have now developed a biochemical tool that circumvents existing limitations and serves as first production platform for pepteins, hard-to-be-produced peptides and proteins between 30 and 300 amino acids in length, including disulfide-rich candidates. Numaswitch is based on bifunctional Switchtag proteins that force the high-titer expression of pure inclusion bodies and simultaneously assist in the efficient refolding of pepteins into functional pepteins. Here, we demonstrate the successful application of the Numaswitch platform for disulfide-containing pepteins, such as an antimicrobial fusion peptide, a single-chain variable fragment (scFv), a camelid heavy chain antibody fragment (VHH) and the human epidermal growth factor.
{"title":"Numaswitch, a biochemical platform for the efficient production of disulfide-rich pepteins","authors":"Bach-Ngan Nguyen, Florian Tieves, Florian G. Neusius, H. Götzke, L. Schmitt, C. Schwarz","doi":"10.3389/fddsv.2023.1082058","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1082058","url":null,"abstract":"The application of long-chained peptides (+30 aa) and relatively short proteins (<300 aa) has experienced an increasing interest in recent years. However, a reliable production platform is still missing since manufacturing is challenged by inherent problems such as mis-folding, aggregation, and low production yields. And neither chemical synthesis nor available recombinant approaches are effective and efficient. This in particular holds true for disulfide-rich targets where the correct isomer needs to be formed. With the technology Numaswitch, we have now developed a biochemical tool that circumvents existing limitations and serves as first production platform for pepteins, hard-to-be-produced peptides and proteins between 30 and 300 amino acids in length, including disulfide-rich candidates. Numaswitch is based on bifunctional Switchtag proteins that force the high-titer expression of pure inclusion bodies and simultaneously assist in the efficient refolding of pepteins into functional pepteins. Here, we demonstrate the successful application of the Numaswitch platform for disulfide-containing pepteins, such as an antimicrobial fusion peptide, a single-chain variable fragment (scFv), a camelid heavy chain antibody fragment (VHH) and the human epidermal growth factor.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47786351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-10DOI: 10.3389/fddsv.2023.1112992
Dennis A. Hauser, P. Mäser
Introduction: Suramin is one of the pharmacopeia’s most promiscuous drugs. Originally developed for African trypanosomiasis, suramin was also used for onchocerciasis and it has been proposed as an anticancer agent, antiviral drug, therapy for arthritis, autism, and antidote for snake bites. Target proteins of suramin have been described from different species. Here we identify the common motifs among these various targets, aiming to explain the promiscuous nature of suramin. Methods: We have searched for suramin target proteins in the literature and in chemical databases. Applying rigorous inclusion criteria, a list of 44 diverse proteins was assembled with experimental evidence for direct interaction with, and inhibition by, suramin. Hidden Markov model-based target profiling was performed by running the full set of Pfam protein family domains against these proteins. Results: Common denominators were identified by mapping the identified Pfam domains to molecular function gene ontology terms. This in silico pipeline identified nucleotide binding, nucleic acid binding, and binding to divalent cations as the most common denominators of the suramin targets. Discussion: Our results suggest that the extraordinary polypharmacology of suramin may be caused by its ability to inhibit the interaction of proteins with nucleotides or nucleic acids and with divalent cations (Mg2+, Ca2+, Zn2+). Suramin is well known to inhibit nucleotide receptors and nucleic acid-binding enzymes. The association with divalent cations is new and might be key towards the design of better, more selective inhibitors.
{"title":"HMM-based profiling identifies the binding to divalent cations and nucleotides as common denominators of suramin targets","authors":"Dennis A. Hauser, P. Mäser","doi":"10.3389/fddsv.2023.1112992","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1112992","url":null,"abstract":"Introduction: Suramin is one of the pharmacopeia’s most promiscuous drugs. Originally developed for African trypanosomiasis, suramin was also used for onchocerciasis and it has been proposed as an anticancer agent, antiviral drug, therapy for arthritis, autism, and antidote for snake bites. Target proteins of suramin have been described from different species. Here we identify the common motifs among these various targets, aiming to explain the promiscuous nature of suramin. Methods: We have searched for suramin target proteins in the literature and in chemical databases. Applying rigorous inclusion criteria, a list of 44 diverse proteins was assembled with experimental evidence for direct interaction with, and inhibition by, suramin. Hidden Markov model-based target profiling was performed by running the full set of Pfam protein family domains against these proteins. Results: Common denominators were identified by mapping the identified Pfam domains to molecular function gene ontology terms. This in silico pipeline identified nucleotide binding, nucleic acid binding, and binding to divalent cations as the most common denominators of the suramin targets. Discussion: Our results suggest that the extraordinary polypharmacology of suramin may be caused by its ability to inhibit the interaction of proteins with nucleotides or nucleic acids and with divalent cations (Mg2+, Ca2+, Zn2+). Suramin is well known to inhibit nucleotide receptors and nucleic acid-binding enzymes. The association with divalent cations is new and might be key towards the design of better, more selective inhibitors.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46032731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-20DOI: 10.3389/fddsv.2023.1087008
Elliasu Y. Salifu, James Abugri, Issahaku A Rashid, F. Osei, Joseph Atia Ayariga
Malaria caused by Plasmodium falciparum, remains one of the most fatal parasitic diseases that has affected nearly a third of the world’s population. The major impediment to the treatment of malaria is the emergence of resistance of the P. falciparum parasite to current anti-malaria therapeutics such as Artemisinin (ART)-based combination therapy (ACT). This has resulted in countless efforts to develop novel therapeutics that will counter this resistance with the aim to control and eradicate the disease. The application of in silico modelling techniques has gained a lot of recognition in antimalarial research in recent times through the identification of biological components of the parasite for rational drug design. In this study we employed various in silico techniques such as the Virtual screening, molecular docking and molecular dynamic simulations to identify potential new inhibitors of biotin acetyl-coenzyme A (CoA) carboxylase and enoyl-acyl carrier reductase, two enzyme targets that play a crucial role in fatty acid synthesis in the Plasmodium parasite. Initially, nine hit compounds were identified for each of the two enzymes from the ZINCPharmer database. Subsequently, all hit compounds bind favourably to the active sites of the two enzymes as well as show excellent pharmacokinetic properties. Three 3) of the hits for the biotin acetyl-coenzyme A (CoA) carboxylase and six 6) of the enoyl-acyl carrier reductase showed good toxicity properties. The compounds were further evaluated based on the Molecular Dynamics simulation that confirmed the binding stability of the compounds to the targeted proteins. Overall, the lead compounds ZINC38980461, ZINC05378039, and ZINC15772056, were identified for acetyl-coenzyme A (CoA) carboxylase whiles ZINC94085628, ZINC93656835, ZINC94080670, ZINC1774609, ZINC94821232 and ZINC94919772 were identified as lead compounds for enoyl-acyl carrier reductase. The identified compounds can be developed as a treatment option for the malaria disease although, experimental validation is suggested for further evaluation of the work.
{"title":"In silico identification of potential inhibitors of acyl carrier protein reductase and acetyl CoA carboxylase of Plasmodium falciparum in antimalarial therapy","authors":"Elliasu Y. Salifu, James Abugri, Issahaku A Rashid, F. Osei, Joseph Atia Ayariga","doi":"10.3389/fddsv.2023.1087008","DOIUrl":"https://doi.org/10.3389/fddsv.2023.1087008","url":null,"abstract":"Malaria caused by Plasmodium falciparum, remains one of the most fatal parasitic diseases that has affected nearly a third of the world’s population. The major impediment to the treatment of malaria is the emergence of resistance of the P. falciparum parasite to current anti-malaria therapeutics such as Artemisinin (ART)-based combination therapy (ACT). This has resulted in countless efforts to develop novel therapeutics that will counter this resistance with the aim to control and eradicate the disease. The application of in silico modelling techniques has gained a lot of recognition in antimalarial research in recent times through the identification of biological components of the parasite for rational drug design. In this study we employed various in silico techniques such as the Virtual screening, molecular docking and molecular dynamic simulations to identify potential new inhibitors of biotin acetyl-coenzyme A (CoA) carboxylase and enoyl-acyl carrier reductase, two enzyme targets that play a crucial role in fatty acid synthesis in the Plasmodium parasite. Initially, nine hit compounds were identified for each of the two enzymes from the ZINCPharmer database. Subsequently, all hit compounds bind favourably to the active sites of the two enzymes as well as show excellent pharmacokinetic properties. Three 3) of the hits for the biotin acetyl-coenzyme A (CoA) carboxylase and six 6) of the enoyl-acyl carrier reductase showed good toxicity properties. The compounds were further evaluated based on the Molecular Dynamics simulation that confirmed the binding stability of the compounds to the targeted proteins. Overall, the lead compounds ZINC38980461, ZINC05378039, and ZINC15772056, were identified for acetyl-coenzyme A (CoA) carboxylase whiles ZINC94085628, ZINC93656835, ZINC94080670, ZINC1774609, ZINC94821232 and ZINC94919772 were identified as lead compounds for enoyl-acyl carrier reductase. The identified compounds can be developed as a treatment option for the malaria disease although, experimental validation is suggested for further evaluation of the work.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43816255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-12DOI: 10.3389/fddsv.2022.1093153
M. Argiriadi, Kangwen Deng, D. Egan, Lei Gao, F. Gizatullin, J. Harlan, Denise Karaoglu Hanzatian, W. Qiu, Ruth Villanueva, Andrew Goodearl
LRP8 is a member of the LDLR-like protein family. It is a transport receptor, which can be used in the design of antibodies specific for investigating increasing exposure to therapeutics with respect to the blood brain barrier (BBB). In this study, a LRP8 peptide immunization strategy was implemented to generate antibodies to a specific epitope of the CR1 domain of LRP8 that could enable transport function and cross-react in mice, cynomolgus monkeys and humans. Additionally, a cyclized peptide immunogen was designed to conserve the structural β-hairpin element observed in a previously solved crystal structure of a related CR domain. As a result of this structure-based antigenic design, an LRP8 specific antibody, 11H1, was selected and characterized in ligand binding assays and crystallographic structure determination. The high-resolution structure of the 11H1 Fab complexed to the cyclized CR1 peptide revealed key interactions driving epitope recognition that were confirmed using a site-directed mutagenesis approach. A critical observation was that the identified structural CR1 epitope of 11H1 did not compete with reelin’s recognition of CR1 allowing for simultaneous binding. This was predicted by an in silico ternary model and confirmed by reelin binding data. These simultaneous binding events (11H1/CR1/reelin) could therefore enable the CR1 domain of LRP8, 11H1 and reelin to be used as a “BBB transporter” ternary complex in the design of therapeutic proteins. More importantly, 11H1 showed enhanced brain penetration after systemic intravenous dosing in a mouse study, which confirmed its potential function as BBB transporter for therapeutic proteins.
{"title":"The use of cyclic peptide antigens to generate LRP8 specific antibodies","authors":"M. Argiriadi, Kangwen Deng, D. Egan, Lei Gao, F. Gizatullin, J. Harlan, Denise Karaoglu Hanzatian, W. Qiu, Ruth Villanueva, Andrew Goodearl","doi":"10.3389/fddsv.2022.1093153","DOIUrl":"https://doi.org/10.3389/fddsv.2022.1093153","url":null,"abstract":"LRP8 is a member of the LDLR-like protein family. It is a transport receptor, which can be used in the design of antibodies specific for investigating increasing exposure to therapeutics with respect to the blood brain barrier (BBB). In this study, a LRP8 peptide immunization strategy was implemented to generate antibodies to a specific epitope of the CR1 domain of LRP8 that could enable transport function and cross-react in mice, cynomolgus monkeys and humans. Additionally, a cyclized peptide immunogen was designed to conserve the structural β-hairpin element observed in a previously solved crystal structure of a related CR domain. As a result of this structure-based antigenic design, an LRP8 specific antibody, 11H1, was selected and characterized in ligand binding assays and crystallographic structure determination. The high-resolution structure of the 11H1 Fab complexed to the cyclized CR1 peptide revealed key interactions driving epitope recognition that were confirmed using a site-directed mutagenesis approach. A critical observation was that the identified structural CR1 epitope of 11H1 did not compete with reelin’s recognition of CR1 allowing for simultaneous binding. This was predicted by an in silico ternary model and confirmed by reelin binding data. These simultaneous binding events (11H1/CR1/reelin) could therefore enable the CR1 domain of LRP8, 11H1 and reelin to be used as a “BBB transporter” ternary complex in the design of therapeutic proteins. More importantly, 11H1 showed enhanced brain penetration after systemic intravenous dosing in a mouse study, which confirmed its potential function as BBB transporter for therapeutic proteins.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41635901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-09DOI: 10.3389/fddsv.2022.1083198
Carlos D. Flores-León, Luis Fernando Colorado-Pablo, Miguel Á. Santos-Contreras, R. Aguayo‐Ortiz
Human epigenetic enzyme disruptor of telomeric silencing 1-like (DOT1L) is a key drug target for treating acute myeloid leukemia. Several nucleoside and non-nucleoside DOT1L inhibitors have been developed to inhibit its histone methyltransferase activity. Non-mechanism-based nucleoside DOT1L inhibitors have shown good inhibitory activity and high on-target residence times. Previous computational studies have explored the dynamic behavior of this group of molecules on DOT1L to design compounds with enhanced binding affinities. Nevertheless, it is well known that drug-target kinetics also plays a crucial role in the discovery of new drugs. Therefore, we performed τ-Random Acceleration Molecular Dynamics (τRAMD) simulations to estimate the residence times of nucleoside DOT1L inhibitors. The high correlation between the calculated and experimental residence times suggested that the method can reliably estimate the residence time of nucleoside DOT1L inhibitors when modifications are made to those substituents that occupy the buried hydrophobic pocket of the active site, exhibit hydrophobic interactions with F245 or that form H-bonds with D161 and G163. Overall, this study will be a step toward understanding the binding kinetics of nucleoside DOT1L inhibitors for the treatment of acute myeloid leukemia.
{"title":"Determination of nucleoside DOT1L inhibitors’ residence times by τRAMD simulations","authors":"Carlos D. Flores-León, Luis Fernando Colorado-Pablo, Miguel Á. Santos-Contreras, R. Aguayo‐Ortiz","doi":"10.3389/fddsv.2022.1083198","DOIUrl":"https://doi.org/10.3389/fddsv.2022.1083198","url":null,"abstract":"Human epigenetic enzyme disruptor of telomeric silencing 1-like (DOT1L) is a key drug target for treating acute myeloid leukemia. Several nucleoside and non-nucleoside DOT1L inhibitors have been developed to inhibit its histone methyltransferase activity. Non-mechanism-based nucleoside DOT1L inhibitors have shown good inhibitory activity and high on-target residence times. Previous computational studies have explored the dynamic behavior of this group of molecules on DOT1L to design compounds with enhanced binding affinities. Nevertheless, it is well known that drug-target kinetics also plays a crucial role in the discovery of new drugs. Therefore, we performed τ-Random Acceleration Molecular Dynamics (τRAMD) simulations to estimate the residence times of nucleoside DOT1L inhibitors. The high correlation between the calculated and experimental residence times suggested that the method can reliably estimate the residence time of nucleoside DOT1L inhibitors when modifications are made to those substituents that occupy the buried hydrophobic pocket of the active site, exhibit hydrophobic interactions with F245 or that form H-bonds with D161 and G163. Overall, this study will be a step toward understanding the binding kinetics of nucleoside DOT1L inhibitors for the treatment of acute myeloid leukemia.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48062743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-05DOI: 10.3389/fddsv.2022.1082065
Denis N Prada Gori, S. Ruatta, Martín Fló, L. Alberca, C. Bellera, Soonju Park, Jinyeong Heo, Honggun Lee, K. P. Park, O. Pritsch, D. Shum, M. Comini, A. Talevi
The COVID-19 pandemic prompted several drug repositioning initiatives with the aim to rapidly deliver pharmacological candidates able to reduce SARS-CoV-2 dissemination and mortality. A major issue shared by many of the in silico studies addressing the discovery of compounds or drugs targeting SARS-CoV-2 molecules is that they lacked experimental validation of the results. Here we present a computer-aided drug-repositioning campaign against the indispensable SARS-CoV-2 main protease (MPro or 3CLPro) that involved the development of ligand-based ensemble models and the experimental testing of a small subset of the identified hits. The search method explored random subspaces of molecular descriptors to obtain linear classifiers. The best models were then combined by selective ensemble learning to improve their predictive power. Both the individual models and the ensembles were validated by retrospective screening, and later used to screen the DrugBank, Drug Repurposing Hub and Sweetlead libraries for potential inhibitors of MPro. From the 4 in silico hits assayed, atpenin and tinostamustine inhibited MPro (IC50 1 µM and 4 μM, respectively) but not the papain-like protease of SARS-CoV-2 (drugs tested at 25 μM). Preliminary kinetic characterization suggests that tinostamustine and atpenin inhibit MPro by an irreversible and acompetitive mechanisms, respectively. Both drugs failed to inhibit the proliferation of SARS-CoV-2 in VERO cells. The virtual screening method reported here may be a powerful tool to further extent the identification of novel MPro inhibitors. Furthermore, the confirmed MPro hits may be subjected to optimization or retrospective search strategies to improve their molecular target and anti-viral potency.
{"title":"Drug repurposing screening validated by experimental assays identifies two clinical drugs targeting SARS-CoV-2 main protease","authors":"Denis N Prada Gori, S. Ruatta, Martín Fló, L. Alberca, C. Bellera, Soonju Park, Jinyeong Heo, Honggun Lee, K. P. Park, O. Pritsch, D. Shum, M. Comini, A. Talevi","doi":"10.3389/fddsv.2022.1082065","DOIUrl":"https://doi.org/10.3389/fddsv.2022.1082065","url":null,"abstract":"The COVID-19 pandemic prompted several drug repositioning initiatives with the aim to rapidly deliver pharmacological candidates able to reduce SARS-CoV-2 dissemination and mortality. A major issue shared by many of the in silico studies addressing the discovery of compounds or drugs targeting SARS-CoV-2 molecules is that they lacked experimental validation of the results. Here we present a computer-aided drug-repositioning campaign against the indispensable SARS-CoV-2 main protease (MPro or 3CLPro) that involved the development of ligand-based ensemble models and the experimental testing of a small subset of the identified hits. The search method explored random subspaces of molecular descriptors to obtain linear classifiers. The best models were then combined by selective ensemble learning to improve their predictive power. Both the individual models and the ensembles were validated by retrospective screening, and later used to screen the DrugBank, Drug Repurposing Hub and Sweetlead libraries for potential inhibitors of MPro. From the 4 in silico hits assayed, atpenin and tinostamustine inhibited MPro (IC50 1 µM and 4 μM, respectively) but not the papain-like protease of SARS-CoV-2 (drugs tested at 25 μM). Preliminary kinetic characterization suggests that tinostamustine and atpenin inhibit MPro by an irreversible and acompetitive mechanisms, respectively. Both drugs failed to inhibit the proliferation of SARS-CoV-2 in VERO cells. The virtual screening method reported here may be a powerful tool to further extent the identification of novel MPro inhibitors. Furthermore, the confirmed MPro hits may be subjected to optimization or retrospective search strategies to improve their molecular target and anti-viral potency.","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41404972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-05DOI: 10.3389/fddsv.2022.1126955
J. Medina‐Franco
Entering the third decade of the 21st Century, artificial intelligence (AI) continues to offer significant advances in drug discovery (Jiménez-Luna et al., 2021; Jayatunga et al., 2022). When used rationally beyond the hype, AI offers clear promise to advance further basic and applied research (Medina-Franco et al., 2021). At the same time, AI faces challenges to address at different levels. The present Research Topic brings together experts worldwide from industry, academic, not-for-profit, and governmental settings to openly discuss novel insights, recent advances, latest discoveries, and current challenges in the field of In silico Methods and Artificial Intelligence for Drug Discovery. From an industry point of view, DiNuzzo presents a perspective on how AI enables the modeling and simulation of biological networks to accelerate drug discovery. He emphasizes that the proper combination of the predictive capability of AI with the mechanistic knowledge of modeling and simulation is expected to provide a major contribution to the pharmaceutical industry. DiNuzzo also concludes that AI will be a key player in analyzing biological networks that will deliver substantial progress towards the improvement of drug target identification and validation, qualify potentially associated side-effects, identify the efficacy and toxicity of biomarkers, aid with hypothesis generation, optimal experimental design, and testing for disease understanding and identification of disease biomarkers. McDermott et al. discuss a platform based on AI that aids in the discovery of DNA damaging agents for ultra-rare cancer atypical teratoid rhabdoid tumors (ATRT). Specifically, the authors showed the power of using the public USA’s National Cancer Institute (NCI)’s CellMiner Cross Database and Lantern Pharma’s proprietary AI and machine learning (ML) RADR® platform to uncover biological insights and potentially new target indications for the acylfulvene derivative drugs LP-100 (Irofulven) and LP-184. Lantern’s AI and ML RADR® platform was used to develop a model to test, computationally, if LP-184 would be effective in ATRT patients. RADR® suggested that ATRT would be sensitive to LP-184, which was then validated in vitro and in vivo. Namba-Nzanguim et al. review how AI is helping to advance antiviral drug discovery in low-resourced settings. Authors shared their perspectives on the benefits, limitations, and pitfalls of AI/ML tools in the discovery of novel antivirals. Namba-Nzanguim et al. also present current and novel data sharing models, including intellectual property-preserving AI/ML. Authors concluded that AI/ML provides a cost-effective solution for developing antivirals, but AI/ML tools depend on improved access to viral assays data and better data integration protocols. Schmitz et al. OPEN ACCESS
进入21世纪的第三个十年，人工智能（AI）继续在药物发现方面取得重大进展（Jiménez-Luna等人，2021；Jayatunga等人，2022）。当在炒作之外合理使用时，人工智能为进一步推进基础和应用研究提供了明确的承诺（Medina Franco et al.，2021）。与此同时，人工智能面临着不同层面的挑战。本研究主题汇集了来自世界各地行业、学术界、非营利组织和政府机构的专家，公开讨论药物发现的计算机方法和人工智能领域的新见解、最新进展、最新发现和当前挑战。从行业的角度来看，DiNuzzo介绍了人工智能如何使生物网络的建模和模拟加速药物发现。他强调，人工智能的预测能力与建模和模拟的机械知识的适当结合有望为制药行业做出重大贡献。DiNuzzo还得出结论，人工智能将在分析生物网络方面发挥关键作用，该网络将在改进药物靶点识别和验证、鉴定潜在的相关副作用、识别生物标志物的疗效和毒性、帮助产生假设、优化实验设计、，以及测试疾病理解和疾病生物标志物的鉴定。McDermott等人讨论了一个基于人工智能的平台，该平台有助于发现超恶性癌症非典型畸胎瘤样横纹肌样肿瘤（ATRT）的DNA损伤剂。具体而言，作者展示了使用美国国家癌症研究所（NCI）的CellMiner交叉数据库和Lantern Pharma专有的人工智能和机器学习（ML）RADR®平台来揭示酰基富烯衍生物药物LP-100（Irofulven）和LP-184的生物学见解和潜在新靶点适应症的力量。Lantern的AI和ML RADR®平台用于开发一个模型，通过计算测试LP-184是否对ATRT患者有效。RADR®表明ATRT对LP-184敏感，随后在体外和体内进行了验证。Namba Nzanguim等人综述了人工智能如何在资源匮乏的环境中帮助推进抗病毒药物的发现。作者分享了他们对AI/ML工具在发现新型抗病毒药物方面的好处、局限性和陷阱的看法。Namba Nzanguim等人还介绍了当前和新的数据共享模型，包括保护知识产权的AI/ML。作者得出结论，AI/ML为开发抗病毒药物提供了一种具有成本效益的解决方案，但AI/ML工具依赖于改进对病毒检测数据的访问和更好的数据集成协议。Schmitz等人开放访问
{"title":"Editorial: Insights in silico methods and artificial intelligence for drug discovery: 2022","authors":"J. Medina‐Franco","doi":"10.3389/fddsv.2022.1126955","DOIUrl":"https://doi.org/10.3389/fddsv.2022.1126955","url":null,"abstract":"Entering the third decade of the 21st Century, artificial intelligence (AI) continues to offer significant advances in drug discovery (Jiménez-Luna et al., 2021; Jayatunga et al., 2022). When used rationally beyond the hype, AI offers clear promise to advance further basic and applied research (Medina-Franco et al., 2021). At the same time, AI faces challenges to address at different levels. The present Research Topic brings together experts worldwide from industry, academic, not-for-profit, and governmental settings to openly discuss novel insights, recent advances, latest discoveries, and current challenges in the field of In silico Methods and Artificial Intelligence for Drug Discovery. From an industry point of view, DiNuzzo presents a perspective on how AI enables the modeling and simulation of biological networks to accelerate drug discovery. He emphasizes that the proper combination of the predictive capability of AI with the mechanistic knowledge of modeling and simulation is expected to provide a major contribution to the pharmaceutical industry. DiNuzzo also concludes that AI will be a key player in analyzing biological networks that will deliver substantial progress towards the improvement of drug target identification and validation, qualify potentially associated side-effects, identify the efficacy and toxicity of biomarkers, aid with hypothesis generation, optimal experimental design, and testing for disease understanding and identification of disease biomarkers. McDermott et al. discuss a platform based on AI that aids in the discovery of DNA damaging agents for ultra-rare cancer atypical teratoid rhabdoid tumors (ATRT). Specifically, the authors showed the power of using the public USA’s National Cancer Institute (NCI)’s CellMiner Cross Database and Lantern Pharma’s proprietary AI and machine learning (ML) RADR® platform to uncover biological insights and potentially new target indications for the acylfulvene derivative drugs LP-100 (Irofulven) and LP-184. Lantern’s AI and ML RADR® platform was used to develop a model to test, computationally, if LP-184 would be effective in ATRT patients. RADR® suggested that ATRT would be sensitive to LP-184, which was then validated in vitro and in vivo. Namba-Nzanguim et al. review how AI is helping to advance antiviral drug discovery in low-resourced settings. Authors shared their perspectives on the benefits, limitations, and pitfalls of AI/ML tools in the discovery of novel antivirals. Namba-Nzanguim et al. also present current and novel data sharing models, including intellectual property-preserving AI/ML. Authors concluded that AI/ML provides a cost-effective solution for developing antivirals, but AI/ML tools depend on improved access to viral assays data and better data integration protocols. Schmitz et al. OPEN ACCESS","PeriodicalId":73080,"journal":{"name":"Frontiers in drug discovery","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43510989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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