基于片段的药物设计方法研究进展

基于片段的药物设计(FBDD)已经逐渐发展成为一种重要的药物设计新方法。FBDD利用表面等离子共振技术(SPR)、核磁共振技术(NMR)、质谱(MS)和X-射线单晶衍射等方法检测与靶蛋白相互作用的小分子片段,然后以片段为起点来设计先导化合物。与传统的药物设计方法相比,FBDD具有发现活性化合物效率高的特点,且发现的化合物具有活性强、类药性好等优点。该文结合实例综述了基于片段的药物设计方法的研究进展。     

新型小分子Bcl-2蛋白抑制剂的设计、合成及体外活性研究

目的 设计并合成新型小分子Bcl-2蛋白抑制剂.方法 基于已报道的活性小分子,运用Autodock4.2研究其与Bcl-2蛋白的作用模式,并以此设计、合成一系列新型小分子抑制剂,采用MTT法对人肝癌细胞HepG-2进行体外抗肿瘤活性实验.结果 设计合成了11个全新小分子化合物,其结构经1HNMR和13CNMR确定.结论 化合物Ⅱ、Ⅴ、Ⅹ、Ⅺ有明显的体外抗肿瘤活性,化合物Ⅵ显示出比较好的体外抗肿瘤活性,高于阳性对照.     

基于Bcl-2蛋白关键位点抑制剂的研究

目的 设计并合成高抑制活性的小分子Bcl-2蛋白抑制剂.方法 基于已报道的活性小分子,运用Autodock 4.2软件研究其与Bcl-2蛋白的作用模式,探索Bcl-2蛋白的关键位点并设计、合成一系列新型小分子抑制剂,并进行体外抗肿瘤活性的实验.结果 设计合成了8个全新的小分子化合物,其结构经1HNMR和13CNMR确证.结论 所合成的8个化合物均有明显的体外抗肿瘤活性,且大部分高于阳性对照紫杉醇.     

细胞分裂蛋白FtsZ抑制剂的研究进展

细菌耐药性问题日益严重,越来越多的致病菌对现有抗生素产生了耐药性.开发新靶点的抗生素迫在眉睫.FtsZ 是介导细菌细胞分裂的关键蛋白,由于与人类微管蛋白序列的差异,有可能设计选择性作用于细菌FtsZ而不干扰宿主细胞的抑制剂,FtsZ蛋白有希望成为抗菌药物研究的新靶点.本文从人类微管蛋白抑制剂、GTP类似物、天然产物和化合物库广筛等方面综述了以FtsZ为靶点的抗菌药物研究的最新进展.     

具有去甲斑蝥素结构的HDAC抑制剂的设计与合成

目的：设计与合成以去甲斑蝥素为骨架的苯甲酰胺类组蛋白去乙酰化酶抑制剂。方法利用拼合原理,将去甲斑蝥素的活性结构片段,引入具有不同取代基的苯甲酰胺类组蛋白去乙酰化酶抑制剂中,探索性设计并合成了2个未经报道的全新化合物。结果目标化合物为全新未报道化合物,结构经质谱、氢谱和碳谱确认。结论设计思想合理,合成方法温和,简便,适合该类化合物的合成。     

全新药物的设计方法

全新药物设计方法是近年来岗出现的一种合理药物设计新思想，它能用来人工设计新的先导化合物。根据所用的基本构建块不同，全新药物设计方法主要可分为三种类型：模板定位法、原子生长法和分子碎片法；其中基于分子碎片的方法又有碎片连接法和碎片生长法之分。本文对上述几种全新药物设计的基本方法及其在药物设计中的应用作了较全面的综述。     

2021年首创性小分子药物研究实例浅析

2021年,尽管新冠疫情仍然困扰全球,但新药创制的脚步却未因此减缓。美国FDA药物评价和研究中心(CDER)在过去一年里共计批准了50款新药,其中有27款为首创性(first-in-class)药物,为过去十年的峰值。小分子的首创性药物依旧占据主导地位,获批15款。其中包括多个具有里程碑式重要意义的首创性小分子药物,例如首个靶向“不可成药”靶标KRAS G12C突变蛋白的小分子共价抑制剂索托雷塞(sotorasib),首个靶向BCR-ABL1蛋白肉豆蔻酰口袋的小分子变构抑制剂阿思尼布(asciminib),首个抑制缺氧诱导因子HIF-2α的小分子抑制剂贝组替凡(belzutifan),首个治疗慢性心力衰竭恶化的sGC小分子激动剂维立西呱(vericiguat)等。首创性药物依赖于发现全新的作用靶标和生物机制,分子设计思路各不相同,具有重要的学习和借鉴意义。本文通过浅析其中3例首创性小分子药物的研发背景、研发过程和治疗应用,以期为更多的首创性药物提供研究思路与方法。     

降血脂药物研究进展

综述了近年来降血脂药物的研究进展,包括他汀类、贝特类、胆固醇吸收抑制刺、胆固醇酯转运蛋白抑制剂、微粒体甘油三酯转运蛋白抑制剂、酰基辅酶A-胆固醇酰基转移酶抑制剂等.     

HIV-1蛋白酶抑制剂分子设计策略研究进展

由于HIV的强变异性，根据HIV蛋白酶的理化性质、晶体结构及底物的特征，设计、合成、筛选新型高效的蛋白酶抑制剂，一直以来是抗艾滋病药物的热点之一。笔者将近年来研究的HIV蛋白酶抑制剂，接其化学结构分为拟肽和非肽两类，详细介绍了各类HIV蛋白酶抑制剂的分子设计策略、作用机制和活性等方面的研究进展。     

全新药物设计方法的新进展

简要概述全新药物设计方法的一般原理、步骤及应用实例，重点评述全新药物设计方法中分子生成策略的进展。全新药物设计方法是一种基于受体结构三维信息，采用计算机辅助药物设计技术，设计出能与受体特异性结合的先导化合物。     

Strategy of computer-aided drug design

Modern strategies of computer-aided drug design (CADD) are reviewed. The task of CADD in the pipeline of drug discovery is accelerating of finding the new lead compounds and their structure optimization for the following pharmacological tests. The main directions in CADD are based on the availability of the experimentally determined three-dimensional structure of the target macromolecule. If spatial structure is known the methods of structure-based drug design are used. In the opposite case the indirect methods of CADD based on the structures of known ligands (ligand-based drug design) are used. The interrelationship between the main directions of CADD is reviewed. The main CADD approaches of molecule de novo design and database mining are described. They include methods of molecular docking, de novo design, design of pharmacophore and quantity structure-activity relationship models. New ways and perspectives of CADD are discussed.     

De novo design: balancing novelty and confined chemical space

Importance of the field: De novo drug design serves as a tool for the discovery of new ligands for macromolecular targets as well as optimization of known ligands. Recently developed tools aim to address the multi-objective nature of drug design in an unprecedented manner. Areas covered in this review: This article discusses recent advances in de novo drug design programs and accessory programs used to evaluate compounds post-generation. What the reader will gain: The reader is introduced to the challenges inherent in de novo drug design and will become familiar with current trends in de novo design. Furthermore, the reader will be better prepared to assess the value of a tool, and be equipped to design more elegant tools in the future. Take home message: De novo drug design can assist in the efficient discovery of new compounds with a high affinity for a given target. The inclusion of existing chemoinformatic methods with current structure-based de novo design tools provides a means of enhancing the therapeutic value of these generated compounds.     

Computational drug design targeting protein-protein interactions

Novel discoveries in molecular disease pathways within the cell, combined with increasing information regarding protein binding partners has lead to a new approach in drug discovery. There is interest in designing drugs to modulate protein-protein interactions as opposed to solely targeting the catalytic active site within a single enzyme or protein. There are many challenges in this new approach to drug discovery, particularly since the protein-protein interface has a larger surface area, can comprise a discontinuous epitope, and is more amorphous and less well defined than the typical drug design target, a small contained enzyme-binding pocket. Computational methods to predict modes of protein-protein interaction, as well as protein interface hot spots, have garnered significant interest, in order to facilitate the development of drugs to successfully disrupt and inhibit protein-protein interactions. This review summarizes some current methods available for computational protein-protein docking, as well as tabulating some examples of the successful design of antagonists and small molecule inhibitors for protein-protein interactions. Several of these drugs are now beginning to appear in the clinic.     

De novo drug design: integration of structure-based and ligand-based methods

Structure-based and ligand-based methods are used to derive predictive models in de novo drug design. Structure-based methods rely exclusively on prior knowledge of a protein structure to derive novel ligands, while ligand-based methods are traditionally used when no protein structure is available. Where there is sufficient information, these methods can be used in conjunction to increase the accuracy of simulation and enhance the drug design process. This review presents developments in the integration of these methods for de novo drug design, and recent results from both systems are highlighted.     

In silico fragment-based drug design

Importance of the field: In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates.

Areas covered in this review: Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed.

What the reader will gain: The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs.

Take home message: In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein–protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.     

The effect of workstation technology on methods in drug design and discovery

Summary The last two decades have seen the birth, emergence and acceptance of the field of computational drug design and discovery. In the early days of this period, computer-aided drug design was performed on mainframe or supercomputers by specialists. Modern-day workstations provide access to a large palette of powerful software tools to a wide audience of computational, medicinal and bioorganic chemists. In this paper we review the trends in computer hardware that have led to powerful computer systems, including the evolution of workstations from the microprocessors used in personal computers and the gradual development of workstation networks. We predict how advances in workstation technology will affect computational drug design and discovery in the future. We also outline some challenges that need to be faced to make workstation-based computational chemistry even more useful.     

The quest for novel chemical matter and the contribution of computer-aided de novo design

Identifying novel chemical matter is the focus of many drug discovery efforts. Through these efforts, computer-based de novo design of drug-like molecules, which aim to build an entire molecule 'from scratch', has emerged as a valuable approach to identify novel chemical matter. In this paper, the author discusses the recent research efforts that aim to build, in silico, more chemically accessible molecules, sample more efficiently the chemical space and rank the proposed molecules. The author reviews de novo design algorithms developed between 2008 and 2010 and the issue of validation, and highlights some recent successful applications of de novo design to drug discovery projects. Although research has addressed the lack of synthetic accessibility of the molecules proposed by the first generation of de novo design tools, the lack of accurate scoring function remains a major limitation of structure-based de novo design. However, de novo design is a valuable approach to generate either chemical starting points or ideas.     

Structure-based drug design of catechol-O-methyltransferase inhibitors for CNS disorders

Catechol-O-methyltransferase (COMT) is of great importance in pharmacology because it catalyzes the metabolism (methylation) of endogenous and xenobiotic catechols. Moreover, inhibition of COMT is the drug target in the management of central nervous system (CNS) disorders such as Parkinson''s disease due to its role in regulation of the dopamine level in the brain. The X-ray crystal structures for COMT have been available since 1994. The active sites for cofactor and substrate/inhibitor binding are well resolved to an atomic level, providing valuable insights into the catalytic mechanisms as well as the role of magnesium ions in catalysis. Determination of how the substrates/inhibitors bind to the protein leads to a structure-based approach that has resulted in potent and selective inhibitors. This review focuses on the design of two types of inhibitors (nitrocatechol-type and bisubstrate inhibitors) for COMT using the protein structures.