药物设计中的模拟肽学*

本文综述了药物设计中的模拟肽学方法.     

基因组学对基于结构的药物设计的影响*

基于靶标结构的药物设计方法是先导药物设计的重要手段.近年来,随着基因组计划的顺利进行,基因组学对药物设计有着巨大的冲击和影响.本文试图从近几年的一些研究领域如结构基因组学、化学基因组学、微生物基因组学等来综述基因组学对基于药物作用靶标的分子设计方法的影响.     

配体-受体相互作用的计算机模拟及其在药物设计中的应用

配体-受体相互作用在许多生物过程中起重要作用, 计算机分子模拟技术和理论化学计算方法在配体-受体相互作用研究中得到了广泛的应用。本文综述了有关配体-受体相互作用分子模拟和理论计算的常用方法及其在药物设计中的应用。     

遗传算法与药物分子设计

本文对遗传算法及其近年来在药物设计中的应用进行了较为系统的介绍。遗传算法非常适合解决组合优化问题, 它在柔性分子构象搜寻、药效基团推测、蛋白质结构预测、分子对接、全新药物设计以及组合合成中都具有很大的应用潜力。     

药物设计中的三维结构搜索方法

利用分子的三维特征, 在三维结构数据库中进行三维结构搜索的方法是一种发现先导化合物的快捷而有效的方法, 已经得到了广泛的重视。本文综述了三维结构搜索方法的原理、发展及其近年来在药物分子设计中的应用。     

氟原子在药物分子设计中的应用

含氟药物在临床治疗药物中占有相当比重.将氟原子或含氟基团引入到小分子药物中,是药物化学结构改造的重要研究策略之一.综述了氟原子在药物分子设计中的应用,氟原子或含氟基团的引入可以调节药物小分子的物理化学特性,改变小分子的药代动力学性质,提高药物的生物利用度;通过影响化合物的构象,增强配体与靶标蛋白的相互结合能力以及对其它靶标蛋白的选择性;通过阻断易代谢位点进而提高药物代谢稳定性等.     

Design, synthesis and in vitro evaluation of L-amino acid esters prodrugs of acyclic nucleoside phosphonates as anti-HBV agent

A series of novel L-amino acid esters prodrugs of acyclic nucleoside phosphonates was synthesized and their anti-HBVactivity was evaluated in HepG2 2.2.15 cells. Compound 1d exhibited more potent anti-HBV activity and lower cytotoxicity than those of adefovir dipivoxil with EC50 and CC50 values of 0.207 mmol/L and 2530 mmol/L, respectively.     

模拟肽的构象限制在药物设计中的应用

构象限制的模拟肽具有更好的生物活性和代谢稳定性,可以作为酶和受体活性位点的多肽替代物,是重要的药物设计工具。将特定的结构引入到生物活性肽中进行构象限制就得到了模拟肽,设计合成特定结构的模拟肽,需要一些方法作为指导,这些方法可以使模拟肽按设想产生特定的生物活性而减少设计的盲目性。本文综述了模拟肽构象限制的两类方法,即模拟肽的局部构象限制和模拟肽的整体环化。通过这两种主要方式的结构改进得到的构象限制的模拟肽,对改进模拟肽的药效学和药代动力学性质起了重要作用,包括提高其生物活性、选择性、代谢的稳定性和吸收性质。     

Boron‐Based Drug Design

The use of the element boron, which is not generally observed in a living body, possesses a high potential for the discovery of new biological activity in pharmaceutical drug design. In this account, we describe our recent developments in boron‐based drug design, including boronic acid containing protein tyrosine kinase inhibitors, proteasome inhibitors, and tubulin polymerization inhibitors, and ortho‐carborane‐containing proteasome activators, hypoxia‐inducible factor 1 inhibitors, and topoisomerase inhibitors. Furthermore, we applied a closo‐dodecaborate as a water‐soluble moiety as well as a boron‐10 source for the design of boron carriers in boron neutron capture therapy, such as boronated porphyrins and boron lipids for a liposomal boron delivery system.     

Targeted Covalent Inhibitors for Drug Design

In contrast to the traditional mechanism of drug action that relies on the reversible, noncovalent interaction of a ligand with its biological target, a targeted covalent inhibitor (TCI) is designed such that the initial, reversible association is followed by the formation of a covalent bond between an electrophile on the ligand and a nucleophilic center in the protein. Although this approach offers a variety of potential benefits (high potency and extended duration of action), concerns over the possible toxicological consequences of protein haptenization have hindered the development of the TCI concept. Recently, approaches to mitigate the risk of serious adverse reactions to this new class of agent have emerged, thus stimulating interest in the field and leading to authorization of the first cadre of TCIs to be marketed. The covalent inhibitor approach is rapidly gaining acceptance as a valuable tool in drug discovery, and is poised to make a major impact on the design of enzyme inhibitors and receptor modulators.     

动态组合化学研究进展及其在药物设计中的应用

动态组合化学利用可逆过程连接库内的各种组分,实现动态库的多样性.在库中加入靶标分子,通过分子识别、分子组装,诱导产生和靶标分子产生最强键合的化合物,推动化合物库的移动.介绍了动态组合化学的基本原理,并综述了近年来发现的动态可逆过程和动态组合化学在生物学、新药设计中的应用.     

药物输送体系构筑中的超分子组装策略

超分子组装提供了药物输送体系设计的新原理。以高效的分子间非共价键作用为驱动力,超分子药物输送体系能够利用结构简单的分子单体获得精确的成分控制,并使得载体结构易于预测,形貌与体积易于调控,有利于实现药物的控制释放。本文首先总结超分子药物输送体系的研究背景,之后重点介绍基于环糊精、杯芳烃、柱芳烃和葫芦脲的主-客体体系的超分子药物输送体系的构建与药物输送功能,然后介绍水溶性的超分子有机框架在药物输送方面的应用,最后提出了超分子药物载体实用化需要克服的若干挑战性问题。     

遗传算法在计算机辅助药物分子设计中的应用

作为一种重要的启发式优化算法,遗传算法在计算机辅助药物分子设计中得到了广泛的应用.本文介绍了遗传算法的基本概念以及工作原理,同时结合作者科研组的工作,就遗传算法在定量构效关系、构象分析、药效团模拟、分子对接以及虚拟组合化学等方面的应用做了系统的阐述。     

Library Design Strategies To Accelerate Fragment-Based Drug Discovery

Fragment-based drug discovery (FBDD) has become an established approach for the generation of early lead candidates. However, despite its success and inherent advantages, hit-to-candidate progression for FBDD is not necessarily faster than that of traditional high-throughput screening. Thus, new technology-driven library design strategies have emerged as a means to facilitate more efficient fragment screening and/or subsequent fragment-to-hit chemistry. This minireview discusses such strategies, which cover the use of labeled fragments for NMR spectroscopy, X-ray crystallographic screening of specialized fragments, covalent linkage for mass spectrometry, dynamic combinatorial chemistry, and fragments optimized for easy elaboration.     

In Silico Structure-Based Approach for Group Efficiency Estimation in Fragment-Based Drug Design Using Evaluation of Fragment Contributions

The notion of a contribution of a specific group in an organic molecule’s property and/or activity is both common in our thinking and is still not strictly correct due to the inherent non-additivity of free energy with respect to molecular fragments composing a molecule. The fragment- based drug discovery (FBDD) approach has proven to be fruitful in addressing the above notions. The main difficulty of the FBDD, however, is in its reliance on the low throughput and expensive experimental means of determining the fragment-sized molecules binding. In this article we propose a way to enhance the throughput and availability of the FBDD methods by judiciously using an in silico means of assessing the contribution to ligand-receptor binding energy of fragments of a molecule under question using a previously developed in silico Reverse Fragment Based Drug Discovery (R-FBDD) approach. It has been shown that the proposed structure-based drug discovery (SBDD) type of approach fills in the vacant niche among the existing in silico approaches, which mainly stem from the ligand-based drug discovery (LBDD) counterparts. In order to illustrate the applicability of the approach, our work retrospectively repeats the findings of the use case of an FBDD hit-to-lead project devoted to the experimentally based determination of additive group efficiency (GE)—an analog of ligand efficiency (LE) for a group in the molecule—using the Free-Wilson (FW) decomposition. It is shown that in using our in silico approach to evaluate fragment contributions of a ligand and to estimate GE one can arrive at similar decisions as those made using the experimentally determined activity-based FW decomposition. It is also shown that the approach is rather robust to the choice of the scoring function, provided the latter demonstrates a decent scoring power. We argue that the proposed approach of in silico assessment of GE has a wider applicability domain and expect that it will be widely applicable to enhance the net throughput of drug discovery based on the FBDD paradigm.     

Computer-Aided Drug Design Boosts RAS Inhibitor Discovery

The Rat Sarcoma (RAS) family (NRAS, HRAS, and KRAS) is endowed with GTPase activity to regulate various signaling pathways in ubiquitous animal cells. As proto-oncogenes, RAS mutations can maintain activation, leading to the growth and proliferation of abnormal cells and the development of a variety of human cancers. For the fight against tumors, the discovery of RAS-targeted drugs is of high significance. On the one hand, the structural properties of the RAS protein make it difficult to find inhibitors specifically targeted to it. On the other hand, targeting other molecules in the RAS signaling pathway often leads to severe tissue toxicities due to the lack of disease specificity. However, computer-aided drug design (CADD) can help solve the above problems. As an interdisciplinary approach that combines computational biology with medicinal chemistry, CADD has brought a variety of advances and numerous benefits to drug design, such as the rapid identification of new targets and discovery of new drugs. Based on an overview of RAS features and the history of inhibitor discovery, this review provides insight into the application of mainstream CADD methods to RAS drug design.     

On the Topological Sub-Structural Molecular Design (TOSS-MODE) in QSPR/QSAR and Drug Design Research

Abstract

A recently introduced graph-theoretical approach to the study of structure-property-activity relationships is presented. The theoretical approach and the computational strategy for the use of the TOSS-MODE approach are given with details. Several QSPR and QSAR applications are reviewed including the study of physical properties of organic compounds, diamagnetic susceptibilities, and biological properties. The applications of the TOSS-MODE approach to discrimination of active/inactive compounds, the virtual screening of compounds with a desired property from databases of chemical structures, identification of active/inactive fragments and its relationships with 2D/3D pharmacophores, and to the design of novel compounds with desired biological activities are also reviewed.     

Thoughts on What Chemists Can Contribute to Fighting SARS‐CoV‐2 – A Short Note on Hand Sanitizers,Drug Candidates and Outreach

The SARS‐CoV‐2 outbreak causing the respiratory disease COVID‐19 has left many chemists in academia without an obvious option to contribute to fighting the pandemic. Some of our recent experiences indicate that there are ways to overcome this dilemma. A three‐pronged approach is proposed.