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Computer Aided Drug Design (CADD) From Ligand-Based Methods to Structure-Based Approaches - Rudrapal M., Egbuna C. 2022 PDF Eslevier BOOKS SCIENCE AND STUDY
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Computer Aided Drug Design (CADD) From Ligand-Based Methods to Structure-Based Approaches
Author: Rudrapal M., Egbuna C.
Year: 2022
Pages: 324
Format: PDF
File size: 12,6 MB
Language: ENG



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Book Description: ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: I. Introduction * Overview of the importance of computer-aided drug design (CADD) in modern drug discovery * Historical background and evolution of CADD techniques * Objectives and scope of the book II. Fundamental Concepts and Theories * Basic principles of ligand-based design * Structure-based drug design * Molecular dynamics simulations * Machine learning and artificial intelligence in drug design III. Advanced Methods and Techniques * Quantitative structure-activity relationship (QSAR) models * Molecular docking and molecular dynamics simulations * Free energy calculations * Machine learning algorithms for predicting drug efficacy and safety IV. Applications of CADD * Target identification and validation * Lead optimization and selection * Property prediction and optimization * Virtual screening and hit discovery V. Recent Developments and Future Directions * Advances in AI and machine learning for drug design * Integration of CADD with other omics technologies (genomics, proteomics, metabolomics) * Challenges and opportunities in CADD VI.
ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: I. Введение * Обзор важности автоматизированного проектирования лекарственных средств (CADD) in modern drug discovery * Историческая справка и эволюция методов CADD * Цели и объем книги II. фундаментальные концепции и теории * Основные принципы конструирования на основе лигандов * Конструирование лекарств на основе структуры * Моделирование молекулярной динамики * Машинное обучение и искусственный интеллект в конструировании лекарств III. Передовые методы и методы * Количественные отношения структура-активность (QSAR) модели * Молекулярная стыковка и моделирование молекулярной динамики * Расчеты свободной энергии * Алгоритмы машинного обучения для прогнозирования эффективности и безопасности лекарств IV. Применение CADD * Идентификация и валидация целей * Оптимизация и выбор лидов * Прогнозирование свойств и оптимизация * Виртуальный скрининг и обнаружение хитов V. Последние разработки и будущие направления * Достижения в области ИИ и машинного обучения для проектирования лекарств * Интеграция CADD с другими технологиями омики (геномика, протеомика, метаболомика) * Проблемы и возможности в CADD VI.
ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: I. Introduction * Examen de l'importance de la conception assistée par ordinateur des médicaments (CADD) in modern drug discovery * Référence historique et évolution des méthodes CADD * Objectifs et portée du livre II. Concepts et théories fondamentaux * Principes de base de la conception à base de ligands * Conception de médicaments à base de structures * Modélisation de la dynamique moléculaire * Apprentissage automatique et intelligence artificielle dans la conception de médicaments III. Méthodes avancées et méthodes * Relations structure-activité quantitatives. (QSAR) modèles * Ancrage moléculaire et modélisation de la dynamique moléculaire * Calculs de l'énergie libre * Algorithmes d'apprentissage automatique pour prédire l'efficacité et la sécurité des médicaments IV. Application CADD * Identification et validation des objectifs * Optimisation et sélection des leaders * Prédiction des propriétés et optimisation * Dépistage virtuel et détection des succès V. Développements récents et orientations futures * Réalisations dans le domaine IA et apprentissage automatique pour la conception de médicaments * Intégration de la CADD avec d'autres technologies omiques (génomique, protéomique, métabolomique) * Défis et possibilités dans la CADD VI.
ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: I. Introducción * Descripción general de la importancia del diseño automatizado de medicamentos (CADD) in modern drug discovery * Referencia histórica y evolución de los métodos CADD * Objetivos y alcance del libro II. conceptos y teorías fundamentales * Principios básicos de la construcción basada en ligandos * Diseño de fármacos basado en estructura * Modelado de dinámicas moleculares * Aprendizaje automático y artificial Inteligencia en el diseño de fármacos III. Técnicas y métodos avanzados * Relaciones cuantitativas estructura-actividad. Modelos (QSAR) * Acoplamiento molecular y modelado de dinámica molecular * Cálculos de energía libre * Algoritmos de aprendizaje automático para predecir la eficacia y seguridad de los medicamentos IV. Aplicación CADD * Identificación y validación de objetivos * Optimización y selección de leads * Predicción de propiedades y optimización * Cribado y detección virtuales éxitos V. Desarrollos recientes y direcciones futuras * Avances en IA y aprendizaje automático para el diseño de fármacos * Integración de CADD con otras tecnologías ómicas (genómica, proteómica, metabolómica) * Desafíos y oportunidades en CADD VI.
ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: I. Introdução * Revisão da importância da engenharia automatizada de medicamentos (CADD) in modern drug discovery * Referência histórica e evolução das técnicas CADD * Objetivos e volume do livro II. Conceitos e Teorias Fundamentais * Princípios Básicos de Construção Baseados em Ligandas * Construção de Medicamentos Baseado em Estrutura * mulação de Dinâmica Molecular * Aprendizagem de Máquinas e Inteligência Artificial na Construção de Medicamentos I. Técnicas e métodos avançados * Estrutura quantitativa-atividade (QSAR) modelos * Acoplamento molecular e simulação de dinâmica molecular * Cálculos de energia livre * Algoritmos de aprendizagem de máquinas para prever a eficácia e a segurança dos medicamentos IV. Aplicação de CADD * Identificação e validação de objetivos * Otimização e escolha de lidas * Previsão de propriedades e otimização * Screening virtual e detecção de hits v. v. Avanços em IA e aprendizagem de máquinas para projetar medicamentos * Integração CADD com outras tecnologias de ômica (genômica, proteômica, metabolômica) * Problemas e oportunidades no CADD VI.
ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: I. Introduzione * Panoramica dell'importanza della progettazione automatizzata dei medicinali (CADD) in modern drug discovery * Riferimento storico e evoluzione dei metodi CADD * Obiettivi e volume del libro II. Concetti e teorie fondamentali * Principi di base per la progettazione basata su legandi * Progettazione di farmaci basata sulla struttura * Modellazione delle dinamiche molecolari * Apprendimento automatico e intelligenza artificiale nella progettazione di farmaci IIIII.I.L.a. Best practice e procedure * Quantitative Interazioni struttura-attività. (QSAR) modelli * Accostamento molecolare e modellazione dinamica molecolare * Calcoli di energia libera * Algoritmi di apprendimento automatico per la previsione di efficacia e sicurezza dei farmaci IV. Applicazione di CADD * Identificazione e validazione degli obiettivi * Ottimizzazione e selezione dei lidi * Previsione delle proprietà e ottimizzazione * Screening virtuale e rilevamento dei successi V. Progressi nell'intelligenza artificiale e nell'apprendimento automatico per la progettazione di farmaci * Integrazione di CADD con altre tecnologie omiche (genomica, proteomica, metabolica) * Problemi e opportunità in CADD VI.
ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: I. Einleitung * Überblick über die Bedeutung des computergestützten Designs von Arzneimitteln (CADD) in der modernen Arzneimittelentdeckung * Historischer Hintergrund und Entwicklung der CADD-Methoden * Ziele und Umfang des Buches II. Grundlegende Konzepte und Theorien * Grundprinzipien des ligandenbasierten Designs * Strukturbasiertes Design von Arzneimitteln * Modellierung der molekularen Dynamik * Maschinelles rnen und künstliche Intelligenz im Arzneimitteldesign III. Fortgeschrittene Techniken und Methoden * Quantitative Struktur-Aktivitäts-Beziehungen (QSAR) Modelle * Molekulare Kopplung und molekulare Dynamiksimulation * Freie-Energie-Berechnungen * Maschinelle rnalgorithmen zur Vorhersage der Wirksamkeit und cherheit von Medikamenten IV. Anwendung von CADD * Identifizierung und Validierung von Zielen * Optimierung und Auswahl von ads * Vorhersage von Eigenschaften und Optimierung * Virtuelles Screening und Erkennung von Treffern V. Neueste Entwicklungen und zukünftige Richtungen * Fortschritte bei KI und maschinellem rnen für das Medikamentendesign * Integration von CADD mit anderen Omics-Technologien (Genomik, Proteomik, Metabolomik) * Herausforderungen und Chancen in CADD VI.
Książka Opis: CADD Projektowanie ków Z Metod LigandBased do Oparte na podejściach Zarys: I. Wprowadzenie * Przegląd znaczenia projektowania leków wspomaganych komputerowo (CADD) in modern drug discovery * Historical background and evolution of CADD methods * Goals and scope of book II. fundamental concepts and theories * Basic principles of ligand-based design * Structure based drug design * Molecular dynamics modeling * Machine learning and artificial intelligence in drug design III. Najlepsze praktyki i metody * Relacje struktura ilościowa-aktywność. Modele (QSAR) * Modelowanie dokowania molekularnego i dynamiki molekularnej * Obliczenia wolnej energii * Algorytmy uczenia maszynowego w celu przewidywania skuteczności i bezpieczeństwa narkotyków IV. Zastosowanie CADD * Identyfikacja i walidacja celu * Optymalizacja i wybór ołowiu * Przewidywanie i optymalizacja właściwości * Wirtualna kontrola przesiewowa i hit detection V. Najnowsze osiągnięcia i przyszłe kierunki * Postępy w sztucznej inteligencji i nauce maszynowej w projektowaniu leków * Integracja CADD z innymi technologiami omickimi (genomika, proteomika, metabolomika) * Wyzwania i możliwości w CADD VI.
תיאור ספרים: CADD לעיצוב סמים באמצעות סייען משיטות מבוססות ליגנדנדים לקווי מתאר של גישות מבוססות: מבוא * סקירה של החשיבות של עיצוב סמים בסיוע מחשב (CADD) בגילוי תרופות מודרניות * רקע היסטורי ואבולוציה של שיטות CADD * מטרות והיקף הספר II. מושגי יסוד ותאוריות * עקרונות בסיסיים של עיצוב מבוסס ליגנד * עיצוב תרופות מבוססות מבנה * מודל דינמיקה מולקולרית * למידת מכונה ובינה מלאכותית בעיצוב סמים III. מודלים * עגינה מולקולרית ודינמיקה מולקולרית מודלים * חישובי אנרגיה חופשית * אלגוריתמי למידת מכונה לחיזוי יעילות תרופה ובטיחות IVD יישום של CADD * זיהוי יעד ואימות * אופטימיזציה ובחירה * חיזוי נכסים ואופטימיזציה * סינון וירטואלי וזיהוי פגעי V אינטגרציה של CADD עם טכנולוגיות אומיות אחרות (גנומיקה, פרוטאומיקה, מטבולומיקה) * אתגרים והזדמנויות ב-CADD VI.''
Kitap Açıklaması: Ligand Tabanlı Yöntemlerden Yapı Tabanlı Yaklaşımlara Bilgisayar Destekli İlaç Tasarımı CADD Anahat: I. Giriş * Bilgisayar destekli ilaç tasarımının önemine genel bakış Modern ilaç keşfinde (CADD) * CADD yöntemlerinin tarihsel geçmişi ve evrimi * II. Kitabın amaçları ve kapsamı * Temel kavram ve teoriler * Ligand tabanlı tasarımın temel ilkeleri * Yapı tabanlı ilaç tasarımı * Moleküler dinamik modelleme * İlaç tasarımında makine öğrenmesi ve yapay zeka III. en iyi uygulamalar ve yöntemler * Kantitatif yapı-aktivite ilişkileri (QSAR) modelleri * Moleküler yerleştirme ve moleküler dinamik modelleme * Serbest enerji hesaplamaları * İlaç etkinliğini ve güvenliğini tahmin etmek için makine öğrenme algoritmaları IV. CADD'nin uygulanması * Hedef tanımlama ve doğrulama * Kurşun optimizasyonu ve seçimi * Özellik tahmini ve optimizasyonu * Sanal tarama ve isabet tespiti V. Son gelişmeler ve gelecekteki yönler * İlaç tasarımı için AI ve makine öğrenimindeki gelişmeler * CADD'nin entegrasyonu Diğer omik teknolojileri (genomik, proteomik, metabolomik) * CADD VI'daki zorluklar ve fırsatlar.
وصف الكتاب |: تصميم الأدوية بمساعدة الكمبيوتر CADD من الأساليب القائمة على Ligand إلى مخطط الأساليب القائمة على الهيكل: لمحة عامة عن أهمية تصميم العقاقير بمساعدة الحاسوب (CADD) في اكتشاف الأدوية الحديثة * الخلفية التاريخية وتطور طرق CADD * أهداف ونطاق الكتاب الثاني. المفاهيم والنظريات الأساسية * المبادئ الأساسية للتصميم القائم على الرباط * تصميم الأدوية القائم على الهيكل * نمذجة الديناميكيات الجزيئية * التعلم الآلي والذكاء الاصطناعي في تصميم الأدوية ثالثًا. أفضل الممارسات والعلاقات الكمية بين الهيكل والنشاط. نماذج (QSAR) * نمذجة الالتحام الجزيئي والديناميكيات الجزيئية * حسابات الطاقة المجانية * خوارزميات التعلم الآلي للتنبؤ بفعالية الدواء وسلامته IV. تطبيق CADD * تحديد الهدف والتحقق من صحته * تحسين الرصاص والاختيار * التنبؤ بالممتلكات وتحسينها * الفحص الافتراضي واكتشاف الضرب الخامس التطورات الأخيرة والاتجاهات المستقبلية * التقدم في الذكاء الاصطناعي والتعلم الآلي لتصميم الأدوية * دمج CADD مع تقنيات omics الأخرى (الجينوميات، البروتيوميات، الأيض) * التحديات والفرص في CADD VI.
책 설명: 리간드 기반 방법에서 구조적 기반 접근 방식에 이르기까지 전산화 된 약물 설계 CADD: I. 소개 * 컴퓨터 보조 의약품 설계의 중요성에 대한 개요 현대 약물 발견에서 (CADD) * CADD 방법의 역사적 배경과 진화 * 책 II의 목표 및 범위 * 리간드 기반 디자인의 기본 원리 * 구조 기반 약물 디자인 * 분자 역학 모델링 * 기계 학습 및 인공 지능 약물 설계 IIII 최고의 관행 및 방법 * 양적 구조 활동 관계 (QSAR) 모델 * 분자 도킹 및 분자 역학 모델링 * 무료 에너지 계산 * 약물 효능 및 안전성을 예측하기위한 기계 학습 알고리즘 CADD * 목표 식별 및 검증 * 납 최적화 및 선택 * 가상 선별 및 적중 탐지 V. 최근 개발 및 미래 방향 * 약물 통합 * CADD VI의 기술 (유전체학, 단백질 학, 대사 체학) * 도전과 기회.
Book Description: ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approach Outline: I。はじめに*コンピュータ支援薬の設計の重要性の概要 (CADD)現代創薬における*CADD法の歴史的背景と進化*本の目的と範囲II。基本的な概念と理論*リガンドベースの設計の基本原則*構造ベースの薬物設計*分子動力学モデリング*薬物設計における機械学習と人工知能III。ベストプラクティスと方法*定量的な構造活動関係。 (QSAR)モデル*分子ドッキングと分子動力学モデリング*自由エネルギー計算*薬剤有効性と安全性を予測するための機械学習アルゴリズムIV。 CADDの応用*標的同定と検証*鉛の最適化と選択*特性予測と最適化*仮想スクリーニングとヒット検出V今後の方向性*AIの進歩と医薬品設計のための機械学習*他のオミクス技術(ゲノミクス、プロテオミクス、メタボロミクス)とのCADDの統合*CADD VIにおける課題と機会。
ComputerAided Drug Design CADD From LigandBased Methods to StructureBased Approaches Outline: 一、導言*審查計算機輔助藥物設計的重要性 (CADD)在現代藥物發現*CADD*方法的歷史背景和演變*書的目標和範圍II.基本概念和理論*基於配體的基本設計原理*基於結構的藥物構造*分子動力學建模*藥物構造中的機器學習和人工智能定量結構-活動關系. (QSAR)模型*分子對接和分子動力學建模*自由能計算*用於預測藥物功效和安全性的機器學習算法IV。CADD*應用識別和驗證目標*優化和選擇線索*性能預測和優化*虛擬篩查和命中檢測V.最新發展和未來發展方向*未來進展以及用於藥物設計的機器學習*CADD與其他組學技術(基因組學,蛋白質組學,代謝組學)的集成*CADD VI中的挑戰和機遇。

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