Novel Paradigms For Drug Discovery: Computational Multitarget Screening

药物发现的新范式：计算多靶点筛选

• 批准号: 9015936
• 负责人: RAM SAMUDRALA
• 金额: $ 71.39万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9015936
• 关键词: Novel; Paradigms; Drug; Discovery; Computational

DESCRIPTION Abstract: We will create a comprehensive computational drug discovery platform by enhancing a novel technique for a dynamic, fragment based, screening of small molecule compounds against the three dimensional structures of multiple protein targets from infectious disease causing pathogens, followed by prospective in vitro and in vivo experimental verification. We will further modify the most promising lead candidates computationally and screen them against all known human proteins and variants simultaneously to assess for side effects against essential proteins, and to ensure that they possess safe and effective absorption, distribution, metabolism, and excretion profiles against major proteins in known drug delivery pathways. The top ranking leads will again be experimentally verified, and the computational protocol will be iteratively refined using machine learning techniques. We will initially focus on discovering preclinical drug candidates against infections caused by all eight human herpes viruses (HHVs). This virus family infects billions of humans worldwide every year and is the source of significant mortality in immunocompromised patients. Broad spectrum therapeutics against these key pathogens will benefit the entire global community. In contrast to other computational efforts, my group has successfuly applied and experimentally verified their predictions of inhibitors to treat herpes, malaria, and dengue. This was accomplished at a fraction of the time, effort, and cost typically required by pharmaceutical companies. Our significant successes thus far attest to the efficacy of our drug discovery technologies. The Pioneer Award funds will therefore allow us to bridge the gap of discovering computationally predicted lead compounds and demonstrating their preclinical effectiveness for further clinical and therapeutic use. The ultimate goal is to create a comprehensive computational drug discovery pipeline, applicable to any disease, thereby increasing the success rate and reducing the risk, cost, and time associated with traditional drug discovery methods.

描述 抽象的： 我们将通过增强新技术来创建一个综合的计算药物发现平台 用于基于三维动态、基于片段的小分子化合物筛选 来自引起传染病的病原体的多个蛋白质靶标的结构，随后进行前瞻性研究 体外和体内实验验证。我们将进一步修改最有希望的主要候选者 计算并同时针对所有已知的人类蛋白质和变体筛选它们以评估 针对必需蛋白质的副作用，并确保它们具有安全有效的吸收， 针对已知药物输送途径中主要蛋白质的分布、代谢和排泄概况。 排名靠前的线索将再次进行实验验证，计算协议将迭代 使用机器学习技术进行改进。 我们最初将专注于发现针对所有八种引起的感染的临床前候选药物 人类疱疹病毒（HHV）。该病毒家族每年感染全世界数十亿人，并且 免疫功能低下患者显着死亡的根源。广谱治疗 这些关键病原体将使整个国际社会受益。 与其他计算工作相比，我的团队已经成功应用并通过实验验证 他们预测治疗疱疹、疟疾和登革热的抑制剂。这是用一小部分完成的 制药公司通常需要的时间、精力和成本。我们的重大成功因此 远远证明了我们药物发现技术的功效。 因此，先锋奖资金将使我们能够弥合发现计算预测的差距 先导化合物并证明其临床前有效性以供进一步的临床和治疗用途。 最终目标是创建一个全面的计算药物发现管道，适用于任何 疾病，从而提高成功率并减少与传统方法相关的风险、成本和时间 药物发现方法。

项目成果

Homo-dimerization and ligand binding by the leucine-rich repeat domain at RHG1/RFS2 underlying resistance to two soybean pathogens.

• DOI: 10.1186/1471-2229-13-43
• 发表时间: 2013-03-15
• 期刊: BMC plant biology
• 影响因子: 5.3
• 作者: Afzal AJ;Srour A;Goil A;Vasudaven S;Liu T;Samudrala R;Dogra N;Kohli P;Malakar A;Lightfoot DA
• 通讯作者: Lightfoot DA

Probing the molecular mechanisms of quartz-binding peptides.

• DOI: 10.1021/la100049s
• 发表时间: 2010-07
• 期刊: Langmuir : the ACS journal of surfaces and colloids
• 作者: E. Oren;R. Notman;I. Kim;J. Evans;T. Walsh;R. Samudrala;C. Tamerler;M. Sarikaya

Correction: Distal Effect of Amino Acid Substitutions in CYP2C9 Polymorphic Variants Causes Differences in Interatomic Interactions against (S)-Warfarin

• DOI: 10.1371/annotation/416be1ef-f439-445a-96f8-b1d2f01c6957
• 发表时间: 2013-09-11
• 期刊: PLoS ONE
• 影响因子: 3.7
• 作者: Lertkiatmongkol P;Assawamakin A;White G;Chopra G;Rongnoparut P;Samudrala R;Tongsima S
• 通讯作者: Tongsima S

The evolution and functional repertoire of translation proteins following the origin of life.

• DOI: 10.1186/1745-6150-5-15
• 发表时间: 2010-04-08
• 期刊: Biology direct
• 影响因子: 5.5
• 作者: Goldman AD;Samudrala R;Baross JA
• 通讯作者: Baross JA

Mycobacterium Cytidylate Kinase Appears to Be an Undruggable Target.

分枝杆菌胞化酸酯激酶似乎是一个不难的靶标。

• DOI: 10.1177/1087057116646702
• 发表时间: 2016-08
• 期刊: Journal of biomolecular screening
• 作者: Craig JK;Risler JK;Loesch KA;Dong W;Baker D;Barrett LK;Subramanian S;Samudrala R;Van Voorhis WC
• 通讯作者: Van Voorhis WC